Surface Ocean – Lower Atmosphere Studies
Ireland
Edited by
Colin D. O’Dowd
Centre for Climate & Air Pollution Studies
Environmental Change Institute & Department of Physics
National University of Ireland, Galway
Proceedings of the SOLAS Ireland Workshop 2006
Table of Contents
1.
Executive Summary
1
2.
The Goals of SOLAS
1
3.
List of Attendees of SOLAS Ireland workshop 2006
4
4.
List of workshop presentations
5
5.
Met Éireann Research Overview
Ray Mc Grath
6
Oceanic Whitecaps and Production of Sea Spray Aerosol
Gerrit de Leeuw, Leo Cohen & Adrian Callaghan
8
Marine Aerosol Production: Primary & Secondary Marine Aerosol
Production from Natural Sources (MAP)
Colin D. O’Dowd
Global warming impacts on storminess
Tido Semmler, Saji Varghese, Ray McGrath, Paul Nolan, Shiyu Wang,
Peter Lynch & Colin D. O’Dowd
13
20
Regional Model Estimates of Aerosol Exchanges to and from the NE
Atlantic
Bärbel Langmann, Saji Varghese, Colin D. O’Dowd & Claire Scannell
28
Predictive North-East Atlantic and Irish Sea models – hydrodynamic,
surge and wave modelling
Indiana Olbert & Michael Hartnett
34
Algal responses to environmental change: seaweed-environment interactions
and their applications
Dagmar Stengel
40
Groundwater Inputs to the Coastal Zone of south County Galway and
north and west County Clare
Rachel R. Cave & Tiernan Henry
46
Coastal CO2 eddy-covariance measurements
Colin D. O’Dowd & Philip McVeigh
52
Coastal Biogenic Aerosol Flux – BIOFLUX
Colin D. O’Dowd, Karine Selligri & Young Jun Yoon
57
Seaweed, Iodine and Health
Peter Smyth
62
The Irish Weather Buoy Network: Platforms for sustained oceanatmosphere measurements
Glenn Nolan
Observations of the effect of fetch on whitecap coverage in the Irish Sea
Adrian Callaghan & Martin White
68
70
SOLAS – Ireland
Proceedings
2006
1. Executive Summary
The 2nd Irish SOLAS meeting was held in the National University of Ireland, Galway on December 1st
2006. The objective of the meeting, as in the case of the 1st Irish SOLAS meeting, was to bring together
the Irish scientific research communities relevant to SOLAS objectives; to consolidate our oceanatmosphere research into an Irish SOLAS framework; and to serve as a platform to generate awareness
of related research across different disciplines. An increased awareness is evidenced by an increase in
the workshop attendance from 14 in 2005 to 31 in 2006.
The meeting demonstrated an increase in activities over the year between 2005 and 2006 particularly in
terms of more developed ocean-atmosphere research. In particular, regional scale models, both for
atmospheric predictions and oceanic predictions have been shown to be in an impressive state after
development over the last 3-4 years. In addition, process based research is also at an advanced level,
both in terms of individual group activities and also in terms of international collaborations and the
execution of large scale international research projects. The observational capability for continuous
monitoring of ocean and atmospheric projects has also been significantly increased over the period.
Overall, the inter-linkages between physical, chemical and biological processes and systems is
becoming more evident, as is the need to conduct inter-disciplinary research across these thematic areas
in the context of ocean-atmosphere interactions, climate change, and impacts on ecosystems.
2. The Goal of SOLAS
SOLAS (Surface Ocean - Lower Atmosphere Study) is a new international research initiative that has
as its goal:
To achieve quantitative understanding of the key biogeo-chemical-physical interactions and feedbacks
between the ocean and atmosphere, and of how this coupled system affects and is affected by climate
and environmental change. The scope of the study is illustrated in Figures 1- 4 and described in detail
in this Science Plan and Implementation Strategy. The Science Plan parts of this document are largely
based on the results of the International SOLAS Open Science Meeting held in Damp, near Kiel,
Germany in February 2000 which involved more than 250 scientists from 22 different countries. The
International Geosphere-Biosphere Programme (IGBP), Scientific Committee on Oceanic Research
(SCOR), Commission on Atmospheric Chemistry and Global Pollution (CACGP) and the World
Climate Research Programme (WCRP) have approved SOLAS and are sponsors of it.
1
SOLAS – Ireland
Proceedings
2006
Figure 1: The Scope of SOLAS
Figure 2: Key Processes in the ocean-atmospheric system
2
SOLAS – Ireland
Proceedings
2006
Figure 3: SOLAS Structure
Figure 4: Research foci in SOLAS
3
SOLAS – Ireland
Proceedings
2006
3. List of Attendees of SOLAS Ireland workshop 2006
SOLAS (Surface Ocean Lower Atmosphere Studies) Workshop
Martin Ryan Institute, National University of Ireland, Galway
Attended:
Colin O’Dowd
National University of Ireland, Galway
Ireland
(SOLAS National Coordinator)
Gerard Jennings
National University of Ireland, Galway
Ireland
(Director, Environmental Change Institute)
Frank McGovern
Environmental Protection Agency
Ireland
(Climate Change Unit)
Aodhagan O’Roddy National University of Ireland, Galway
Ireland
(Chair, Irish Committee on Climate Change)
Gerrit de Leeuw
Finnish Meteorological Institute
Finland
(International SOLAS Committee Member)
Ray McGrath
Met Éireann
Ireland
(C4I Project Leader)
Dagmar Stengel
National University of Ireland, Galway
Ireland
Mike Hartnett
National University of Ireland, Galway
Ireland
Indiana Olbert
National University of Ireland, Galway
Ireland
Glenn Nolan
Marine Institute
Ireland
Darius Ceburnis
National University of Ireland, Galway
Ireland
Robert Devoy
University College Cork
Ireland
Ned Dwyer
University College Cork
Ireland
Rowan Fealy
National University of Ireland, Maynooth
Ireland
Michael Guiry
National University of Ireland, Galway
Ireland
(Martin Ryan Institute)
Jeff Hare
University of East Anglia
UK
(Executive Officer, SOLAS International Project Office)
Peter Heffernan
Marine Institute
Ireland
Tiernan Henry
National University of Ireland, Galway
Ireland
Baerbel Langmann National University of Ireland, Galway
Ireland
Philip McVeigh
National University of Ireland, Galway
Ireland
Tom Neary
National University of Ireland, Galway
Ireland
Martina Prendergast National University of Ireland, Galway
Ireland
Tido Semmler
Met Éireann
Ireland
Peter Smyth
University College Dublin
Ireland
John Sweeney
National University of Ireland, Maynooth
Ireland
Jenny Ullgren
National University of Ireland, Galway
Ireland
Xiaochen Liu
National University of Ireland, Maynooth
Ireland
Phillip O’Brien
Environmental Protection Agency
Ireland
Rodney Teck
National University of Ireland, Maynooth
Ireland
Claire Scannell
National University of Ireland, Galway
Ireland
Martin White
National University of Ireland, Galway
Ireland
4
SOLAS – Ireland
Proceedings
5. List of workshop presentations
2006
1st December 2006
Agenda
11:00 – 11:20
Welcome & Coffee
11:20-11:30
11:30-11:40
11:40-11:50
11:50-12:00
12:00-12:10
12:10-12:20
SOLAS-Ireland & Welcome from MRI & ECI
International Activities & Updates from SOLAS
EPA Perspective on Air-Sea Exchange
Marine Institute Research Strategy & FP7
Met Éireann Research Overview
Oceanic Whitecaps and Production of Sea-Spray Aerosol
12:20-13:20
Lunch
13:20-13:30
13:30-13:40
13:40-13:50
13:50-14:00
14:00-14:10
14:10-14:20
14:20-14:30
14:30-14:40
14:40-14:50
14:50-15:00
Marine Aerosol Production
Global Warming Impacts on Storminess
Regional Model Estimates of Aerosol Exchange to and
from the NE Atlantic
Modelling N. Atlantic Ocean Dynamics
Algae Response to Environmental Change
Ground Water Inputs to Coastal Zones
Wave Dynamics and Coastal Processes
CO2 Fluxes in the Coastal Zone
Iodine Fluxes from inter-tidal algae
Seaweed, Iodine & Health
15:00-15:20
Coffee
15:20-15:30
15:40-16:45
The Irish weather buoy network, platforms for sustained
Glenn Nolan
ocean-atmosphere measurements
An Investigation into the Effect of Sea State on Whitecap
Martin White
Coverage in the Irish Sea
Discussion: developing an integrated research approach for SOLAS-Ireland.
Acronymns
ACCENT
C4I
SOLAS
GEMS
GEO
GEOSS
MAP
ECI
MRI
SFI
RFP
EOS
Atmospheric Composition & Change – A European Network of Excellence
Community Climate Change Consortium for Ireland
Surface Ocean Lower Atmosphere Studies
Global Monitoring for Environment and Security
Global Earth Observing
Global Observing System of Systems
Marine Aerosol Production (from natural sources)
Environmental Change Institute
Martin Ryan (Marine Science) Institute
Science Foundation of Ireland
Research Frontiers Programme
Earth & Ocean Sciences
15:30-15:40
O’Dowd, Michael Guiry, Gerard Jennings
Jeff Hare
SOLAS
Frank McGovern
EPA
Peter Heffernan
Marine Institute
Ray McGrath
Met Éireann
Gerrit de Leeuw
FMI
Colin O’Dowd
Tido Semmler
Bärbel Langmann
ECI/NUIG
Met Éireann
ECI/MRI
Indiana A. Olbert
Dagmar Stengel
Tiernan Henry
Robert Devoy
Philip McVeigh
Colin O’Dowd
Peter Smyth
MRI/NUIG
MRI/NUIG
EOS/NUIG
CMRC/UCC
ECI/NUIG
ECI/NUIG
UCD
Marine Institute
EOS/NUIG
5
SOLAS – Ireland
Proceedings
2006
Met Éireann Research Overview
Ray Mc Grath
Met Éireann, Ireland
1 Monitoring Activities
In cooperation with NUIG the monitoring of pollutants such PM10 and PM2.5 will be enhanced.
Measurements of total column ozone will also be increased with an additional sonde launch each week
from Valentia during the winter months; with EPA funding this period may be extended to cover all of
2007.
Interest in air quality issues is increasing. Dispersion modelling capability will be upgraded by using
community models such as AERMOD and CALPUFF in-house. In cooperation with the Radiological
Protection Institute of Ireland (RPII) an emergency system will be installed in Met Éireann’s
Headquarters as part of the National Emergency Plan for Nuclear Accidents to model the spread and
deposition of radioactive materials arising from nuclear incidents using the Danish DERMA model.
2 Operational Developments
2.1 Numerical Weather Prediction
Met Éireann’s operational Numerical Weather Prediction suite, based on the HIRLAM system, will be
enhanced in 2007. Currently, the system is run on a dedicated computer but it is likely that production
runs will be outsourced early in the year. The resolution of the HIRLAM analysis and forecast models
will be increased: the main model will continue to have a horizontal resolution of about 15km but the
number of vertical levels will increase from 31 to 60; the “nested” version will be run on a 5km grid
(with 60 vertical levels).
Currently, the data assimilation system is based on a three-dimensional variational method (3DVAR); a
more advanced four-dimensional system (4DVAR) is currently being tested within the HIRLAM
community and will be tested operationally by Met Éireann in late 2007. 4DVAR will enable us to
make more effective use of observational data.
The HIRLAM forecast model has a hydrostatic dynamical core. Work is presently underway within the
HIRLAM and ALADIN consortia to develop jointly a meso-scale non-hydrostatic model targeted for
operational running at scales ~2km. Met Éireann is contributing to this development work.
2.2 Marine Activities
Currently, we provide operational wave forecasts in coastal areas using the WAM wave model
(horizontal resolution ~30km). In 2007, a nested PRO-WAM wave model will be used: the outer mesh
with a resolution of 15km, the inner mesh with a resolution of 5km.
6
SOLAS – Ireland
Proceedings
2006
Figure 1 Example of tidal
surge forecast using ROMS
model driven with HIRLAM
data
Recently, Met Éireann has been running the ROMS ocean model (~9km horizontal grid) to produce
semi-operational forecasts of tidal surges in Irish coastal areas (see Figure 1). This will continue in
2007, possibly developing into a full operational system.
3 Climate Research
The Community Climate Change Consortium for Ireland (C4I) project is the main vehicle for climate
research in Met Éireann. The project is focused on dynamically downscaling GCM outputs to
determine the future Irish climate at a regional level. So far, a small ensemble of simulations have been
run (see Figure 2). The output data are used to drive application models (e.g. catchment flooding due to
runoff). Currently, the project is performing a long simulation with the ROMS ocean model to
investigate the impact of climate change on tidal surges and coastal flooding.
C4I is also a partner in the EU-funded ENSEMBLES project and has run a 100-year simulation of the
European climate.
Project funding for C4I will terminate at the end of 2007 but it is likely that the climate research
activities will continue within Met Éireann.
Figure 2: Mean Precipitation (mm) Change (2021-2060) - (1961-2000)
Based on dynamical downscaling of different GCMs and GHG emission
scenarios
J
F
M
A
M
J
J
A
S
O
N
D
(2061-2100) - (1961-2000)
7
SOLAS – Ireland
Proceedings
2006
Oceanic Whitecaps and Production of Sea Spray Aerosol
Gerrit de Leeuw1, Leo Cohen2 and Adrian Callaghan3
1
Finnish Meteorological Institute, R&D, ClimateChange Unit, Helsinki, Finland & University of Helsinki, Dept. of Physical
Sciences, Helsinki, Finland & TNO Build Environment, Apeldoorn, The Netherlands
TNO Defence, Security and Safety, The Hague, The Netherlands
3
NUIG, Dept. of Earth and Ocean Sciences, Galway, Ireland
2
1 Introduction
Primary marine aerosol production is produced by the interaction between wind and waves. The wind
drag at the sea surface creates waves. When the wind speeds exceeds a certain threshold, between 4 and
7 ms-1, the drag becomes so high that the waves break and air is entrained into the water. The air breaks
up into bubbles which rise to the surface where they burst and produce sea spray aerosol. The bubble
plume undergoes various stages from formation, injection, rise and senescence with associated changes
in the bubble size distribution [Leifer, and De Leeuw, 2006]. The larger bubbles rise fastest and thus
most of the air is released back into the atmosphere very fast after wave breaking. The largest bubbles
produce film drops due to breaking of the bubble surface film after protruding the surface [Spiel, 1998].
Bubbles smaller than 1.7 mm also produce jet drops when the cavity left after rupture of the bubble
film shoots up [Spiel, 1997]. When wind speeds exceeds about 9 ms-1 the drag becomes strong enough
to directly tear off sea spray droplets from the wave tops which are called spume drops. Laboratory
experiments indicate that 1-6 jet drops and up to 1000 film drops are produced from each bubble,
depending on the bubble size. Laboratory experiments on simulated breaking waves provide
quantitative information on the number of sea spray droplets produced from a breaking wave and the
experimental set up determines whether only bubble-mediated (film and jet) droplets are measured, or
whether spume drops are studied as well.
The sea spray source function (S3F) describes the sea spray flux per unit area and per unit of time,
parameterized as function of environmental parameters such as wind speed and/or water temperature.
Several formulations are available, based on different physical and experimental approaches. One of
the approaches is to parameterize the S3F in terms of whitecap cover, i.e. the fraction of the ocean
surface covered with whitecaps [Monahan et al., 1986]:
S 3F = W (u10 ,...) f (r , t w ,...)
(1)
where W is the whitecap cover formulated in terms of wind speed u10 and possibly other parameters, f
is the production of number of sea spray aerosol droplets per unit whitecap area and per unit of time as
a function of radius r, water temperature tw and possibly other parameters. Detailed measurements of
f(r, tw) are available from Mårtensson et al. [2003].
One of the goals EU FP6 project MAP (Marine Aerosol Production) coordinated by Professor Colin
O’Dowd (NUIG) is “to quantify the number and size flux of primary inorganic and organic marine seaspray aerosol (PMA)”. Data to achieve this objective were collected during the MAP cruise with the
Celtic Explorer (Figure 1), 11 June – 5 July, 2006. Various types of experiments were conducted to
provide data to derive the S3F. Here we report on whitecap measurements and the first preliminary
results from the analysis.
8
SOLAS – Ireland
Proceedings
2006
(a)
(b)
Figure 1. (a) Celtic Explorer in the port of Killybegs. The mast on the foredeck was constructed and
mounted to measure sea spray fluxes using eddy covariance. Containers on the foredeck contained
sophisticated instrumentation for characterization of atmospheric components relevant for the
assessment of primary and secondary aerosol production: atmospheric trace gases and aerosol chemical
and physical properties; (b) Whitecap camera mounted to the railing of the Monkey deck.
2 Experimental set-up
The whitecap measurements were made with a video camera mounted on the monkey deck of the
Celtic Explorer, (Figure 1b). The video signal was grabbed and recorded on the hard disk of a pc in the
Celtic Explorer dry lab. Data were processed when the video frame neither included the horizon, nor
looked very close to the ship. The recording was automatically started after day break and stopped
before dusk. Frames were continuously recorded, with a frequency of 50 Hz, during 55 minutes each
hour.
3 Results
The Celtic Explorer cruise took place on the North Atlantic Ocean, NW of Ireland. A variety of
conditions was encountered. Of particular interest was a gale on 20 and 21 June, 2007, with sustained
wind speeds of about 27 ms-1, see Figure 2. Data recorded with the video camera throughout this gale,
from the beginning until the wind subsided, was used for the initial analysis of the whitecap cover
because a wide range of wind speeds was encountered, including periods with increasing and
decreasing wind speed. Results are presented in Figure 3 where we show both the wind speed and the
percentage whitecap cover as time series on 20 and 21 June, 2007.
9
SOLAS – Ireland
Proceedings
2006
rel. wspd kts
True wspd kts
60
60
50
50
40
40
30
30
20
20
10
10
0
38879
38881
38883
38885
38887
38889
CE speed kts
CE speeds kts
wspd kts
Celtic Explorer speeds
0
38891
Julian Day
Figure 2. Wind speed during the first MAP cruise with the Celtic Explorer, for Julian Days 3887938891 (11-21 June, 2007). The true wind speed was calculated from the relative wind speed and the
Celtic Explorer speed.
25
20
15
10
5
21
:0
0
17
:0
0
13
:0
0
09
:0
0
05
:0
0
21
:0
0
17
:0
0
11
:0
0
09
:0
0
0
05
:0
0
WindSpeed(m/s)
Hourly Averaged Wind Speed (m/s)
Time - From 20/06 to 21/06
21:00
19:00
17:00
15:00
13:00
11:00
09:00
07:00
05:00
22:00
21:00
19:00
17:00
13:00
11:00
10:00
09:00
07:00
8
7
6
5
4
3
2
1
0
05:00
WhitecapCoverage (%)
Percentage Whitecap Coverage (W)
Time - From 20/06 to 21/06
Figure 3. Time series of wind speed and percentage whitecap cover during the gale on 20 and 21 June,
2007.
Figure 3 clearly shows the increase in whitecap cover as wind speed increases. However, when the
storm was over its top and the wind speed decreased, the decrease in the whitecap cover appears to be
slower. This is clearly illustrated in Figure 4 which shows the whitecap cover as a function of wind
speed for increasing wind speed (Figure 4a) and decreasing wind speed (Figure 4b). The regression
10
SOLAS – Ireland
Proceedings
2006
coefficients and least square fit parameters between whitecap cover and wind speed are given in the
Figures. There are fewer data points for the decreasing wind speed curve in Figure 4b, with a gap
between 10 and 16 ms-1, which gives the 10 ms-1 data point a relatively high weight. Therefore the data
will be further processed to obtain more data points over the whole range. The current data clearly
show the difference in the wind speed dependence of the whitecap cover for increasing wind speed
(slope 3.4, a value that is also commonly used in the literature, cf. Monahan and O’Muirchaertaigh,
1986) and for decreasing wind speed (slope 2.7).
W vs Decreasing Wind Speed
8
y = 0.0001x 3.4333
R2 = 0.7565
6
4
2
0
0
5
10
15
Wind Speed m/s
20
25
W hite c a p C ov e ra ge
(% )
W h itecap C o verag e
(% )
W vs Increasing Wind Speed
8
2.7408
y = 0.0015x
R2 = 0.8018
6
4
2
0
0
5
10
15
20
25
Wind Speed m/s
(a)
(b)
Figure 4. Whitecap cover during the gale on 20 and 21 June, 2007: (a) increasing wind speed; (b)
decreasing wind speed
4 Conclusions
Preliminary results have been presented from whitecap measurements during the gale which was
experienced during the MAP cruise on 20 and 21 June, 2006. The results clearly show the difference
between the effects of increasing and decreasing wind speed. Only a limited selection of all available
data has thus far been processed and analyzed. The processing and analysis is on-going and results will
be related to direct measurements of sea spray and sea salt aerosol fluxes using the eddy co-variance
method to derive a parameterization for the sea spray aerosol flux based on detailed analysis of
processes described by a variety of environmental parameters.
Acknowledgements
The MAP project is financially supported by the European Commission (FP6, project number 018332)
and the participating institutes; the Celtic Explorer cruise was supported by the Marine Institute. The
captain and the crew of the Celtic Explorer made the cruise to a success thanks to their able seamen
ship, which made it possible to continue collecting valuable data during the storm.
References
Leifer, I and de Leeuw, G (2006). Bubbles generated from wind-steepened breaking waves: 1. Bubble
plume bubbles, J. Geophys. Res., 111, C06020, doi:10.1029/2004JC002673.
Mårtensson, M., Nilsson, E.D., de Leeuw, G., Cohen, L.H., and Hansson, H-C (2003). Laboratory
simulations of the primary marine aerosol generated by bubble bursting, JGR-Atmospheres 108
(D9), 10.1029/2002JD002263.
Monahan, E.C. and O'Muircheartaigh, I.G. (1986). Whitecaps and the passive remote sensing of the
ocean surface. Int. J. Remote Sensing 7, 627-642.
11
SOLAS – Ireland
Proceedings
2006
Spiel, D.E. (1997). More on the births of jet drops from bubbles bursting on seawater surfaces, J.
Geophys. Res., 102, 5815–5821.
Spiel, D.E. (1998). On the birth of film drops from bubbles bursting on seawater surfaces, J. Geophys.
Res., 103, 24,907–24,918.
12
SOLAS – Ireland
Proceedings
2006
Marine Aerosol Production: Primary & Secondary Marine Aerosol Production
from Natural Sources (MAP)
Colin D. O’Dowd
School of Physics & Centre for Climate & Air Pollution Studies, Environmental Change Institute,
National University of Ireland, Galway, Ireland
Abstract. Marine aerosol contributes significantly to the global radiative budget and consequently,
changes in marine aerosol abundance and/or chemical composition will impact on climate change.
Various climate feedback mechanisms have been proposed involving the sulphur, sea-salt, iodine and
organic sea-spray cycles; however, all cycles and their impacts on aerosol haze and cloud layers
remains poorly quantified. MAP will consolidate the current state-of-the-art in the fields of aerosol
nucleation and growth and primary marine aerosol (PMA) production to quantify the key processes
associated with primary and secondary marine aerosol (SMA) production from natural sources. MAP
focuses on the newly identified aerosol formation mechanisms involving iodine oxides, for secondary
aerosol production, and the primary production of marine organic matter aerosols produced by
plankton and transferred to the atmosphere via the bubble bursting process at the ocean surface. Key
processes are being identified, parameterized and implemented in a Global/Regional-scale chemical
transport model and in a regional climate model. Combining the knowledge gathered on key
processes with satellite-derived information on oceanic and meteorological parameters, an algorithm is
being developed to produce a Sea-Spray Source Function (S3F) which will subsequently be used in
large scale models to quantify the impacts of marine aerosols. The algorithm and its application will be
a product contributing to GMES/GEOSS. Similarly, an organo-iodine source function will also be
developed. The impact of marine aerosol on atmospheric chemistry, radiative forcing and climate will
be evaluated using the large-scale models.
1 Introduction
Marine aerosols contribute to a global heat shield through the formation of aerosol haze layers and
cloud layers. The haze layers directly scatter incoming solar energy back out to space and this
contributes to the Earths albedo. Since these haze layers overly dark and absorbing oceans, their
influence to the radiative budget is significant. Similarly, and perhaps more importantly, they provide
the nuclei for cloud formation. Clouds provide event greater reflective layers that haze layers and
could be considered to have an even greater global cooling effect. The cloud reflectance is determined
by the availability of cloud nuclei, a water-soluble subset of aerosol. Although it is generally
considered (Twomey, 1974) that an increase in cloud nuclei availability leads to the formation of
brighter clouds (since the liquid water has to be shared out amongst more nuclei, it results in a
reduction in mean cloud droplet size which results in an increase in scattering efficiency), work has
shown that this effect is not necessarily the case and depends on a complex, non-linear relationship
13
SOLAS – Ireland
Proceedings
2006
between meteorological dynamics and chemical composition of the aerosol, in particular, sea-salt
produced by wind wave interaction and sulphate aerosol produced by gaseous plankton emissions
(O’Dowd et al., 1999).
For a number of decades now, it has been postulated dimethylsulphide, a major plankton emission is
the main source of marine aerosols – it is oxidised to SO2 and then further oxidised to aerosol sulphate
(so called secondary aerosol production) – could control climate through a negative feedback effect
(Charlson et al., 1987). This assumption is based on a minimal role for mechanically-generated seaspray production (so called primary aerosol production). However, recent work has demonstrated that
sea-spray production can significantly influence marine aerosol (O’Dowd et al., 1997) and cloud fields
(O’Dowd et al., 1999), and, more recently, that its chemical composition can be significantly
influenced by marine biogenic organic matter (O’Dowd et al., 2004). Moreover, the role of sulphur
species in dominating secondary aerosol formation has been questioned by the identification of iodine
species in the production of new, secondary marine aerosol particles (O’Dowd et al., 2002). The recent
findings have set the scene for a large-scale EU project MAP to attempt to further elucidate the
formation of marine aerosols, the relative roles of dynamical and biological processes, and the impact
of marine aerosol on regional-scale climate.
The Specific MAP Objectives are:
(1) To elucidate the dominant condensable vapours driving secondary marine aerosol (SMA)
formation.
(2) To quantify the number and size flux of primary inorganic and organic marine sea-spray aerosol
(PMA)
(3) To produce a PMA and iodo-carbon source function using integrated Global Earth Observing
satellite data and in-situ data.
(4) To quantify the impact of SMA and PMA on radiative forcing and atmospheric chemistry.
Consortium Partners
Coordinator
National University of Ireland, Galway
Participant 2
Participant 3
Participant 4
Participant 5
Participant 6
Participant 7
Participant 8
Participant 9
Participant 10
Participant 11
Participant 12
Netherlands Organization for Applied Research
Ireland
Netherlands
Italy
Finland
Finland
Finland
UK
UK
UK
Sweden
Germany
Germany
Colin O'Dowd
University of Mainz
Joint Research Centre
NUIG
TNO
CNR-ISAC
UHel
UKU
FMI
UMAN
UoY
UEA
SU
UHEI.IP
MPGMPIK
JGUM
JRC
Participant 13
Participant 14
Germany
CEC
Participant 15
University of Crete
UoC
Greece
Participant 16
Polytechnic University of Marche
UNIVPM
Italy
Thorsten Hoffmann
Frank Dentener
(Jean-Philip Putaud)
Euripides Stephanou
(Maria Kanakidou)
Roberto Danovaro
Institute of Atmosphere Science & Climate
University of Helsinki
University of Kuopio
Finnish Meteorological Institute
University of Manchester
University of York
University of East Anglia
Stockholm University
University of Heidelberg
Max Planck Institute for Nuclear Physics
Gerrit de Leeuw
Maria Cristina Facchini
Markku Kulmala
Ari Laaksonen
Veli-Matti Kerminen
Gordon McFiggans
Lucy Carpenter
Peter Liss
Douglas Nilsson
Ulrich Platt
Frank Arnold
14
SOLAS – Ireland
Proceedings
MAP Structure and Work Package Outline.
2006
MAP comprises 5 research Work Packages
(WP).
WP1 focuses on quantifying the
seasonality in marine aerosol properties on the
North Atlantic coastline and in the
Mediterranean. Advanced aerosol physics and
chemistry measurements were conducted from
January 2006 and continue through to December
2006.
WP2 focuses on an intensive winter and summer
campaign where the most advanced instruments
available for aerosol and gas characterisations
and air-sea exchange fluxes were deployed both
at Mace Head and offshore on the Celtic
Explorer Research Vessel.
WP4 aims to develop two GEOSS (Global Earth
Observations System of Systems) products – one to
produce a global sea-spray source function (S3F) for
combined organic-inorganic sea-spray, the other to
produce a global organo-halogen source function.
The WP integrates field and laboratory flux and airsea exchange experiments, along with satellite
products, into large scale models.
WP3 focuses on developing detailed process
models to elucidate key process leading to the
formation of marine aerosol and its subsequent
evolution. In addition, it focused on developing
appropriate parameterisations for inclusion in
global and regional chemical transport and
climate models.
WP5 focuses on initially upgrading the largescale models to the currently most advanced
aerosol and gas schemes, and following the
development of new parameterisations under
WP3 and source functions under WP4, will
implement these schemes to produce a
quantification of the impact of marine aerosols
on regional climate and the global radiative
budget.
2 Progress to date
During the first year (September 2005 – September 2006), the MAP consortium conducted the majority
of its field studies. These included three intensive campaigns over the North Atlantic during winter and
summer in order to capture the main aerosol properties during periods of low and high biological
activities. In addition, advanced measurements, albeit to a lesser extend, were conduced at the
Mediterranean station Finokalia in Crete. The North Atlantic campaigns were conduced at the Mace
Head Atmospheric Research Station (Figure 1) and off-shore on the Celtic Explorer (Figure 2). In
addition, a year-long programme of advanced measurements was initiated at Mace Head, starting
January 2006. The most challenging component of the intensive field studies was the massive
deployment of instruments on the Celtic Explorer and to mobilise this deployment into the peak of the
plankton bloom on the continental shelf (Figure 3 and 4). Almost the whole consortium participated on
the cruise, deploying the most advanced aerosol and gas mass spectrometers, detailed aerosol physics
and off-line chemical samplers, air-sea exchange experiments and flux measurements of micro15
SOLAS – Ireland
Proceedings
2006
meteorology, aerosols, and gases. Along with atmospheric and water column sampling, extensive
bubble-mediated exchange experiments were conducted in the shops wet labs.
Significant advances were also made on the model development. In particular, the process models have
been upgraded to handle specific processes relating to marine aerosol production and marine
atmospheric chemistry, while the large scale models have been upgraded to handle new aerosol modal
dynamics modules and improved atmospheric chemistry schemes. Initial developments of schemes to
produce a sea-spray-source-function has been developed as a first attempt to produce a combined
organic-inorganic source function and distribution over the North Atlantic.
A wide range of conditions were encountered, as expected for the seasonality measurements, but also
for the Celtic Explorer campaign. During the ship campaign, two extensive periods of very high winds
were encountered with one event gusting up to 30 m s-1. Such conditions proved excellent for the
eddy-covariance flux measurements deployed. In addition, good periods of clear sky irradiance under
clean air conditions were also encountered - these are ideal for quantifying open ocean atmospheric
chemistry processes. As mentioned above, the ship encountered an extensive plankton bloom and,
combined with in-situ and satellite measurement guidance, performed many transects into and out of
regions of high biological activity. A detailed web-site was set up and used for project management
and field study forecasting studies. In addition, it serves as the database for data products. The
location is http://macehead.nuigalway.ie/map. A full work programme can be found here.
Figure 1. The Mace Head Atmospheric Research Station
operated by the National University of Ireland, Galway. This
station was the host of a winter and summer intensive field
campaign and a year long programme of advanced
measurements to determine seasonality in aerosol properties.
Figure 2. The Celtic Explorer Research Vessel operated by
Ireland’s Marine Institute. This platform was the host of
extensive and advanced measurements into air-sea exchange
fluxes of marine aerosols and gases (CO2 and organo-halogens).
The vessel sampled within and outside the North Atlantic summer
plankton bloom.
16
SOLAS – Ireland
Proceedings
Figure 3. Visible satellite (MIRIS) image of the extensive
plankton bloom which was the focus of the MAP ship
campaign.
Figure 5. Celtic Explorer transects through plankton bloom
during leg 1 of the cruise
2006
Figure 4: Chlorophyll concentration from MODIS during MAP
intensive summer campaign. Blank areas are either cloud
contaminated or land areas.
Figure 6. Celtic Explorer transects through plankton bloom
during leg 2 of the cruise
3 Main Results to Date
MAP has produced an extensive and unique database on marine aerosol and gas properties as well as
air-sea exchange products. At this short time after the end of the main campaign, and with the yearlong seasonality measurement programme still running, only a glimpse of the results are available.
One of the main underlying objectives of all work packages was to quantify the organic fraction of seaspray aerosol. Previous measurements have indicated a significant organic fraction as a function of
season, or biological activity, over the North Atlantic. Continuous measurements confirm increased
organic carbon during periods of increasing biological activity. This is summarised in Figure 7 which
shows the increase in the baseline of organic carbon (OC) up until September 2006. The peaks
represent polluted air incursions. While the baseline of OC increases during spring to summer there is
no similar increase in elemental carbon (EC) suggesting a biogenic source for the OC. Detailed size
17
SOLAS – Ireland
Proceedings
2006
Carbon concentration, μgC/m
3
segregated aerosol chemical samples illustrate (Figure 8), during the summer intensive campaign, an
increasing fraction of water soluble organic carbon (WSOC) for the submicron size fraction. Water
insoluble organic carbon, which is expected to be greater than WSOC, has yet to be analysed. Larger
than 1 micron, the majority of the mass is due inorganic sea-salt, although the absolute OC mass
concentrations are similar for sub-and super-micron modes. The main question relating to the organic
fraction of marine aerosol is the fraction of OC produced by primary processes (i.e. bubble-bursting
from whitecaps) and what is produced by secondary gas-to-particle production processes. This
question was tackled by conducted controlled bubble-mediated aerosol production experiments in the
plankton bloom onboard the Celtic Explorer. Initial indications suggest significant organic mass
fractions of primary aerosol produced inside the bloom.
5.0
4.5
4.0
3.5
3.0
MH 19-28/06/06
OC
EC
100%
90%
80%
70%
2.5
60%
50%
2.0
40%
30%
1.5
20%
10%
1.0
0%
0.060.125
0.5
0.1250.25
0.25-0.5
0.5-1.0
1.0-2.0
2.0-4.0
4.0-8.0
8.0-16.0
im pactor s tage
0.0
0
50
100
200
250
Sea Salt [ug/m3]
NO3 [ug/m3]
NH4 [ug/m3]
nssCa [ug/m3]
Other ions [ug/m3]
WSOM [ug/m3]
nssSO4 [ug/m3]
julian day
Figure 7. Continuous measurements of organic carbon
(OC) and elemental carbon (EC) in aerosols arriving at
Mace Head.
Figure 8 Size segregated relative chemical composition of
the water soluble fraction of the clean sector sample collected
from 19th to 28th June 2006; stage 1 (0.06-0.125µm) not
detectable.
Initial flux data indicate an excellent database for aerosol and gas exchange processes, however, at this
stage; the dataset is under-going a correction for the ship motion before accurate fluxes can be
calculated. Another critical question relating to marine aerosol formation is whether or not new
particle production can occur over the option ocean. During clear sky conditions, evidence of at least
two particle production events was observed.
The full range of initial results is just emerging from the experimental and modelling studies but these
are reported in detail in the Activity Progress Report.
4 Conclusions
MAP conducted a very successful first 12 months of extensive field and laboratory studies and multiscale model developments. The first year was very challenging in terms of the scale of the project and
objectives over the reporting period, and, although challenging, the work programme was managed and
executed very successfully. The next year will produce an analysis of the main datasets as well as key
parameterisations from the process models to be implemented in the large scale models.
18
SOLAS – Ireland
Proceedings
2006
References
Charlson, R.J., Lovelock, J.E., Andreae, M.O. and Warren, S.G (1987). Oceanic phytoplankton,
atmospheric sulfur, cloud albedo and climate. Nature 326, 655-661.
O’Dowd, C.D., Smith, M.H., Consterdine, I.E. and Lowe, J.A. (1997). Marine aerosol, sea salt, and the
marine sulphur cycle: a short review, Atmospheric Environment 31, 73-80.
O'Dowd, C.D., Lowe, J., Smith, M.H. and Kaye, A.D. (1999). The relative importance of sea-salt and
nss-sulphate aerosol to the marine CCN population: An improved multi-component aerosol-droplet
parameterisation. Q. J. Roy. Met. Soc., 125, 1295-1313.
O’Dowd, C.D., Jimenez, J.L., Bahreini, R., Flagan, R.C., Seinfeld, J.H., Hämeri, K., Pirjola, L.,
Kulmala, M., Jennings, S.G. and Hoffman, T. (2002a). Marine aerosol formation from biogenic
iodine emissions. Nature 417, 632-636.
O'Dowd, C.D., Facchini, M.C., Cavalli, F., Ceburnis, D., Mircea, M., Decesari, S., Fuzzi, S., Yoon,
Y.J. and Putaud, J.P. (2004). Biogenically-driven organic contribution to marine aerosol, Nature,
doi:10.1038/nature02959.
Twomey, S.A., (1974). Pollution and the Planetary albedo. Atmos. Environ., 8, 1251-1256.
19
SOLAS – Ireland
Proceedings
2006
Global warming impacts on storminess
Tido Semmler 1, Saji Varghese 2, Ray McGrath 1, Paul Nolan 1, Shiyu Wang 1, Peter Lynch 3 &
Colin O'Dowd 2
1
Met Eireann, Glasnevin Hill, Dublin 9
School of Physics & Centre for Climate & Air Pollution Studies, Environmental Change Institute,
National University of Ireland, Galway, Ireland
3
University College Dublin, School of Mathematical Sciences
2
Abstract
The influence of an increased sea surface temperature (SST) on the frequency and intensity of cyclones
over the North Atlantic is investigated using four data sets from simulations with the Rossby Centre
regional climate model RCA3. The model domain comprises large parts of the North Atlantic and the
adjacent continents. The first pair of simulations with RCA3 is driven by reanalysis data for May to
December 1985-2000 at the lateral and lower boundaries, once using original SST and lateral boundary
temperature and once increasing these temperatures by 1 K. The second pair of RCA3 simulations is
driven by general circulation model (GCM) data for May to December 1985-2000 and May to
December 2085-2100 assuming the SRES-A2 emission scenario. The setup of an idealized sensitivity
experiment versus a GCM driven experiment ensures that we can separate different factors influencing
the development of cyclones. In both pairs of experiments an increase in the frequency of hurricanes is
simulated. In the first pair there is not much change in the location of hurricanes, whereas in the second
pair there is a pronounced shift in November and December: more hurricanes can be found over the
Gulf of Mexico, the Caribbean Sea and the western Sargasso Sea and less over the southern North
Atlantic. Contrasting and generally weaker changes are seen in the extratropical region and for the less
extreme events. Increases of 9% in the number of extratropical cyclones and 39% in the number of
tropical cyclones with wind speeds of at least 18 m/s can be found in the first pair of experiments,
whereas decreases by 18% and 13% are simulated in the second pair due to a strongly increased
atmospheric stability.
1 Introduction
According to climate simulations the SST is predicted to increase in most regions. If an increased SST
would lead to more intense cyclones the probability of severe weather events such as heavy
precipitation and strong wind storms could increase over Ireland. If an increased SST would lead to an
environment favourable for tropical cyclones in more northern latitudes Western Europe could be
affected by a larger number of transitioned tropical cyclones. Thus it is very relevant to study changes
purely induced by an increased SST as well as changes induced by other influence factors.
The influence of SST on the development of extratropical and tropical cyclones has been widely
studied already. Gyakum and Danielson (2000) found that the combination of warm SST anomalies
with cold air masses over the Western North Pacific leads to enhanced sensible and latent heat fluxes
from the ocean into the atmosphere, favoring explosive cyclogenesis. According to Sanders and
Gyakum (1980) explosive extratropical cyclogenesis is found preferably over regions with strong SST
gradients. Emanuel (1987) showed using a Carnot cycle approach that the maximum possible pressure
drop towards the eye of a hurricane can be expressed as a function of the SST, the ambient relative
humidity and the thermodynamic efficiency, which is proportional to the difference between the SST
20
SOLAS – Ireland
Proceedings
2006
and a weighted mean temperature in the upper atmosphere. All of these studies as well as many other
studies suggest that the SST is one of the key factors influencing the development of cyclones.
Even though numerous studies have been conducted on the influence of the SST on the frequency and
intensity of cyclones, the results of previous work using GCMs to study future changes in the
frequency and intensity of extratropical cyclones due to increased greenhouse gas concentrations differ
dependent on the methodology and the GCM used (König et al., 1993, Hall et al., 1994, Zhang and
Wang, 1997, Sinclair and Watterson, 1999). It is very important to reduce the sources of these
uncertainties to achieve a better understanding of cyclone characteristics in a future climate.
2 Model setup
In this study the regional climate model RCA3 (Rossby Centre regional Atmospheric Climate model
version 3) (Kjellström et al., 2005; Jones et al., 2004) is used on a model domain including large parts
of the North Atlantic to allow the increased SST to have an impact on the development of cyclones.
Western Europe and North West Africa are included in the east of the model domain with Ireland, the
UK and the Iberian Peninsula being far enough away from the lateral boundaries (Figure 1). The south
of North America, Central America, the north of South America, the Gulf of Mexico and the Caribbean
Sea are included in the west of the model domain to allow the simulation of tropical cyclones making
landfall or traveling across the North Atlantic towards Western Europe while transforming into
extratropical cyclones.
Figure 1: Orography [m] in the simulation domain
Two pairs of simulations have been performed. The first pair has been driven by the 40-year reanalysis
data (ERA-40: Uppala et al., 2005) from the European Centre for Medium-Range Weather Forecasts
(ECMWF) at the lateral and lower boundaries. The time period simulated with RCA3 is May to
December 1985 to 2000. The model has been initialized each year on the 1st of May and continuously
run until end of December to ensure that we simulate the strongest tropical storms and their journey
across the North Atlantic including their transition into extratropical storms. The model has been run in
a horizontal resolution of 0.25° or around 28 km with 31 non-equally spaced vertical levels on a rotated
latitude/longitude grid. One simulation of the first pair uses the original SST from ERA40 as lower
boundary values (standard experiment), whereas the other one uses an SST increased by 1 K
(sensitivity experiment). In the sensitivity experiment the atmospheric temperature has been increased
by 1K in the lateral boundary data at all model levels to maintain the vertical structure of the
atmosphere. The specific humidity has also been increased such that the relative humidity remains the
same as in the standard experiment at all model levels. According to model projections (Knutson and
21
SOLAS – Ireland
Proceedings
2006
Tuleya, 2004) it is realistic to assume the relative humidity in a warmer climate to be similar to the one
observed today, whereas the vertical temperature structure is likely to change towards a more stable
stratification in the troposphere.
The second pair of simulations has been run on the same model domain and has been driven by data
from the GCM ECHAM5-OM1 (Roeckner et al., 2003) from May to December 1985-2000 (control
experiment) and from May to December 2085-2100 assuming the SRES-A2 emission scenario
(scenario experiment). This second pair of simulations has been carried out to investigate differences to
the idealized first pair, which could arise from changes in the general circulation, the vertical structure
of the atmosphere or the spatial pattern of SST. The pure influence of a homogeneous warming all over
the model domain can be separated from other influences.
3 Results
3.1 Standard/sensitivity experiments
Figure 2 shows the number of extratropical and tropical cyclones grouped into intensity classes for the
standard and the sensitivity experiment. All cyclones are counted every 3-hour interval. The frequency
of the less intense extratropical cyclones does not change very much with increasing SST while the
occurrence of more intense extratropical cyclones is increased. An increase in the number of tropical
cyclones can be seen in nearly all intensity classes except for the weak classes. A 9% and 39% increase
in the number of major extratropical cyclones and tropical cyclones respectively with maximum wind
speeds of more than 18 m/s can be found in the sensitivity experiment compared to the standard
experiment. The differences are most evident in the very strong intensity classes. The number of
extratropical cyclones attaining maximum wind speeds of more than 34 m/s in the sensitivity and the
standard experiment are 84 and 21 respectively. The number of hurricanes with wind speeds of more
than 42 m/s (category 2 on the Saffir-Simpson Hurricane Scale) increases from 196 to 570 which is a
factor of nearly 3 in the sensitivity experiment compared to the standard experiment. The most obvious
increase occurs for tropical cyclones over the Gulf of Mexico, the Caribbean Sea and the western
Sargasso Sea, where their frequency is more than doubled.
a)
b)
Figure 2: Total number of (a) extratropical and (b) tropical cyclones as in the standard and in the
sensitivity experiment for May to December 1985-2000. All cyclones are counted in each 3-hourly
time interval and categorized in intensity classes with a width of 4 m/s maximum wind speed (2-6 m/s,
6-10 m/s, ... , 50-54 m/s).
22
SOLAS – Ireland
Proceedings
2006
In addition more simulated tropical cyclones undergo ET (48% in the sensitivity experiment compared
to 44% in the standard experiment) and substantially more cyclones re-intensify after their ET (24%
compared to 12%). Therefore more major cyclones with tropical origin reach the vicinity of Western
European coastal areas and more major tropical cyclones and extratropical cyclones with tropical origin
reach the Eastern US according to the sensitivity experiment compared to the standard experiment
(Figure 3).
a)
b)
Figure 3: Cyclone tracks for all storms in May to December 1985-2000 undergoing extratropical
transition during their lifetime with a maximum wind speed of 18 m/s or more from (a) the standard
experiment and (b) the sensitivity experiment (red arrows: cyclone classified as tropical; blue arrows:
cyclone classified as extratropical). Only cyclones which sustain a minimum wind speed of 18 m/s over
at least two time steps are tracked.
3.2 Control/scenario experiments
In the ECHAM5-OM1-A2 driven scenario experiment for 2085 to 2100 where factors other than the
SST are considered, the number of extratropical cyclones decreases for many intensity compared to the
ECHAM5-OM1 driven control experiment for 1985 to 2000 (Figure 4). For the stronger intensity
classes beyond 34 m/s increases in the extratropical cyclone numbers are simulated. However these
increases are smaller than in the first pair of experiments. Whereas a 4-fold increase in the number of
extratropical cyclones is simulated in the first pair, the increase here is slightly more than 2-fold.
Because of a weakening of the thermohaline circulation in the ECHAM5-OM1 simulation the SST
does not increase very much over the Northeastern North Atlantic – in a small region southwest of
Ireland and northwest of Spain it even mildly decreases. But even in the region of tropical cyclones,
where the SST clearly increases by more than 2 K in large regions, the increase in the cyclone
frequency is smaller than in the first pair for most intensity classes – especially for the strong intensity
classes. 207 hurricanes with maximum wind speeds of more than 42 m/s are simulated in the control
experiment; 227 such hurricanes in the scenario experiment. For intermediate intensity classes and even
for hurricanes with wind speeds up to 42 m/s there is a slight decrease in the frequency. The number of
all major extratropical cyclones with maximum wind speeds of at least 18 m/s decreases by 18% and
by 13% in the case of tropical cyclones. Here factors other than the SST play a role.
23
SOLAS – Ireland
Proceedings
a)
2006
b)
Figure 4: Total number of (a) extratropical and (b) tropical cyclones as in the control experiment for
May to December 1985-2000 and in the scenario experiment for May to December 2085-2100. All
cyclones are counted in each 3-hourly time interval and categorized in intensity classes with a width of
4 m/s maximum wind speed (2-6 m/s, 6-10 m/s, ... , 50-54 m/s).
The vertical temperature profile change in the future according to ECHAM5-OM1 is reflected in the
second pair of RCA3 experiments as well. Both in the tropical and in the extratropical regions the
atmosphere is getting more stable according to ECHAM5-OM1. The stabilization is even stronger in
the extratropical regions compared to the tropical regions mainly because of the lesser warming of the
near surface layers. The stabilization of the atmosphere and in addition generally drier conditions seem
to be responsible for the smaller increase in the number of very intense tropical cyclones and for the
decrease in the numbers of tropical cyclones of intermediate intensity compared to the first pair of
experiments. This is also true for the extratropical cyclones, where the stabilization is even stronger due
to a weaker SST increase. Since the conditions are less favorable for the development of both tropical
and extratropical cyclones in the scenario experiment compared to the control experiment, the total
number of tropical cyclones undergoing extratropical transition is reduced (Figure 5).
a)
b)
Figure 5: Cyclone tracks for all storms undergoing extratropical transition during their lifetime with a
maximum wind speed of 18 m/s or more from (a) the control experiment (May to December 19852000) and (b) the scenario experiment (May to December 2085-2100; red arrows: cyclone classified as
tropical; blue arrows: cyclone classified as extratropical). Only cyclones which sustain a minimum
wind speed of 18 m/s over at least two time steps are tracked.
24
SOLAS – Ireland
Proceedings
2006
In terms of the proportion of cyclones undergoing ET to all tropical cyclones, a 2% increase is found
similar to the first pair of experiments. 49% of all tropical cyclones undergo ET in the scenario
experiment compared to 47% in the control. Furthermore, in the scenario experiment 24% of the
cyclones reintensify after their ET compared to 15% in the control which is again consistent with the
first pair of experiments. A considerable shift in the location of major cyclones undergoing ET can be
seen. Whereas less of these cyclones reach the vicinity of Western Europe, more can be found over the
Gulf of Mexico and the Caribbean Sea. Most of this frequency increase is taking place in November
and December. Therefore also a strong increase of more than 200% in the 99.9 percentile of daily
precipitation is simulated in large portions of this region for November and December (Figure 6).
Figure 6: Ratio of the 99.9 percentile of daily precipitation in November-December (scenario
experiment divided by control experiment).
4 Summary and Conclusions
In this study two pairs of RCM experiments have been conducted to separate different influencing
factors on tropical and extratropical cyclones. The first pair has been driven by ERA-40 data with the
original SST (standard experiment) and with an SST increased by 1 K with adapted lateral boundary
values (sensitivity experiment) whereas the second pair has been driven by ECHAM5-OM1 data for
present day climate (control experiment) and by ECHAM5-OM1-A2 scenario data for future climate
(scenario experiment).
The results of the first pair of experiments suggest that higher SSTs alone lead to more frequent
cyclones over most parts of the North Atlantic at least during the extended hurricane season. In
particular, the number of very intense tropical and extratropical cyclones is strongly increasing as well
as the number of tropical cyclones undergoing extratropical transition (ET), re-intensifying thereafter
and affecting continental areas. Connected extreme precipitation is mainly increasing in regions of
tropical cyclones.
However, according to most GCM simulations, not only is the SST predicted to increase but also the
vertical atmospheric temperature structure is predicted to change towards more stable conditions in the
future (Knutson and Tuleya, 2004). Also according to the ECHAM5-OM1-A2 scenario the atmospheric
temperature structure will clearly stabilize in the future which counteracts the SST influence. In
addition, troposphere above the boundary layer will get slightly drier limiting the available latent heat.
It seems that a stabilization of the atmosphere leads to a decrease in the numbers of cyclones for all
25
SOLAS – Ireland
Proceedings
2006
intensity classes similarly, whereas the SST seems to influence the intense cyclones more than the less
intense ones. As in the first pair of experiments, re-intensification after ET occurs more often. In the
second pair, this is due to a change in location of tropical cyclones and possibly more favorable
conditions for post ET re-intensification over the east coast of North America compared to the Central
North Atlantic. The SST seems to influence the intense cyclones more than the less intense cyclones.
In the two pairs of experiments, the important differences are the drastic change in precipitation and its
spatial and temporal distribution which is linked to the cyclone genesis and its path. It is interesting to
note that according to both pairs of experiments increases in extreme precipitation are particularly
strong over the hurricane prone region Gulf of Mexico, Caribbean Sea, Sargasso Sea and adjoining
land areas. There is also a change in the location of occurrence of maximum wind speeds which is
again largely associated to the shift in location and intensity of tropical cyclones. Most of the changes
in wind speed, precipitation increase and its distribution can be attributed to the tropical cyclones. The
increase in storm intensity and near storm precipitation increase is consistent with that of Knutson and
Tuleya (2004) and other studies. A similar agreement can be seen in the increase in number of high
intensity cyclones although the total number of cyclones is reduced compared to control experiment.
The changes as simulated in the scenario experiment compared to the control experiment can not be
regarded as a prediction for future climate because of the uncertainty in the GCM prediction of the
different influence factors on extratropical and tropical cyclones. The scope of this study is to separate
different influence factors on the development of tropical and extratropical cyclones. To conduct a
prediction for the future, regional ensemble simulations using different GCM projections as driving
data could be performed.
Acknowledgements
This work was carried out under the Community Climate Change Consortium for Ireland (C4I) Project,
funded by the following Irish agencies: Environmental Protection Agency (under the National
Development Plan), Met Éireann, Sustainable Energy Ireland, and the Higher Education Authority. The
work was also supported by the CosmoGrid project, funded under the Programme for Research in
Third Level Institutions (PRTLI) administered by the Irish Higher Education Authority under the
National Development Plan and with partial support from the European Regional Development Fund.
References
Emanuel, K. A. (1987). The dependence of hurricane intensity on climate, Nature, 326, 483-485.
Gyakum, J. R., and Danielson, R.E. (2000). Analysis of Meteorological Precursors to Ordinary and
Explosive Cyclogenesis in the Western North Pacific, Monthly Weather Review, 128, 851-863.
Hall, N.M.J., Hoskins, B.J., Valdes, P.J. and Senior, C.A. (1994). Storm tracks in a high-resolution
GCM with doubled carbon dioxide, Quarterly Journal of the Royal Meteorological Society, 120,
1209-1230.
Jones, C.G., Willén U., Ullerstig, A. and Hansson, U. (2004). The Rossby Centre regional atmospheric
climate model part I: model climatology and performance for the present climate over Europe,
Ambio, 33, 199-210.
Kjellström, E., Bärring, L., Gollvik, S., Hansson, U., Jones, C., Samuelsson, P., Rummukainen, M.,
Ullerstig, A., Willén, U., and Wyser, K. (2005). A 140-year simulation of European climate with the
26
SOLAS – Ireland
Proceedings
2006
new version of the Rossby Centre regional atmospheric climate model (RCA3), SMHI Reports
Meteorology and Climatology, 108, SMHI, SE-60176 Norrköping, Sweden, 54 pp.
Knutson, T.R., and Tuleya, R.E. (2004). Impact of CO2-induced warming on simulated hurricane
intensity and precipitation: sensitivity to the choice of climate model and convective
parameterization, Journal of Climate, 17, 3477-3495.
König, W., Sausen, R., and Sielmann, F. (1993). Objective Identification of Cyclones in GCM
Simulations, Journal of Climate, 6, 2217-2231.
Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S.,
Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U. and Tompkins,
A. (2003). The atmospheric general circulation model ECHAM5. Part I: model description, MaxPlanck-Institute for Meteorology Report, 349, Hamburg, Germany, ISSN 0937-1060.
Sanders, F. and Gyakum, J.R. (1980). Synoptic-dynamic climatology of the “Bomb”, Monthly Weather
Review, 108, 1589-1606.
Sinclair, M.R., and Watterson, I.G. (1999). Objective assessment of extratropical weather systems in
simulated climates, Journal of Climate, 12, 3467-3485.
Uppala, S. M., Kållberg, P.W., Simmons, A.J., Andrae, U., da Costa Bechtold, V., Fiorino, M., Gibson
J.K., J. Haseler, A. Hernandez, G. A. Kelly, X. Li, K. Onogi, S. Saarinen, N. Sokka, R. P. Allan, E.
Andersson, K. Arpe, M. A. Balmaseda, A. C. M. Beljaars, L. van de Berg, J. Bidlot, N. Bormann, S.
Caires, F. Chevallier, A. Dethof, M. Dragosavac, M. Fisher, M. Fuentes, S. Hagemann, E. Hólm, B.
J. Hoskins, L. Isaksen, P. A. E. M. Janssen, R. Jenne, A. P. McNally, J.-F. Mahfouf, J.-J. Morcrette,
N. A. Rayner, R. W. Saunders, P. Simon, A. Sterl, K. E. Trenberth, A. Untch, D. Vasiljevic, P.
Viterbo, and J. Woollen (2005). The ERA-40 reanalysis, Quarterly Journal of the Royal
Meteorological Society, 131, 2961-3012.
Zhang, Y., and Wang, W.-C. (1997). Model-simulated northern winter cyclone and anticyclone activity
under a greenhouse warming scenario, Journal of Climate, 10, 1616-1634.
27
SOLAS – Ireland
Proceedings
2006
Regional Model Estimates of Aerosol Exchanges to and from the NE Atlantic
Bärbel Langmann, Saji Varghese, Colin O’Dowd and Claire Scannell
School of Physics & Centre for Climate & Air Pollution Studies, Environmental Change Institute,
National University of Ireland, Galway, Ireland
Abstract
This paper describes numerical model simulation results of the exchange of short living gases and
aerosols between the ocean surface and the marine atmosphere carried out with a regional atmospheric
climate-chemistry/aerosol model. The major goal is to contribute to an improved understanding of the
formation, chemical composition and climate impact of the marine aerosol.
1 Introduction
Recent publications (Meskhidze and Nennes, 2006; O’Dowd et al., 2004) emphasise the importance of
the contribution of organic matter to submicron marine aerosols which are observed in connection with
enhanced biological activity of the ocean. These aerosols act as efficient cloud condensation nuclei
(CCN) and can significantly influence cloud properties and thereby modify the climate of the earth
atmosphere. Generally, it is expected that modified global climate conditions will impact on the today’s
interdependencies of the phytoplankton content at the ocean surface, the marine aerosol concentration
and marine clouds. However, even today these interactions are far away from being fully understood.
Concerning to the organic contribution of the marine aerosol it is not clear until now, if these are
primary aerosols which are directly released from the ocean or secondary aerosols which form in the
atmosphere through chemical reactions of gases (e.g. isoprene) released at the ocean surface
(Meskhidze and Nennes, 2006; O’Dowd et al., 2004). Available source functions of sea spray aerosols
(e.g. Geever et al., 2005; Martenssen et al., 2003; Smith et al., 1993; Monahan et al., 1986) reveal
considerable differences of the aerosol size distribution and dependency on wind speed resulting in
huge variations of the estimated global sea salt emissions to the atmosphere (Schulz et al., 2004).
On the other hand the atmosphere is a source of nutrient (e.g. Fe, NH4NO3) for the ocean via dry and
wet deposition of gases and aerosols. These nutrients increase phytoplankton production in costal
regions. Too much nutrients, however, can lead to strong oxygen reduction in the surface water.
Through the combination of field experiments, laboratory studies and numerical modelling an
improved understanding of the above mentioned chemical, physical and biological processes at the
ocean surface and the marine atmosphere can be achieved. The application of three-dimensional
atmospheric climate-chemistry/aerosol models allows to study such simultaneous processes over large
regions and long periods of time. The today’s knowledge can be integrated into such models, even
though usually in a simplified way and assumption of potentially important processes can be tested.
Here we describe first and preliminary results from model simulations which consider the ocean as a
source of primary and secondary organic aerosols. Until now, regional and global atmospheric climate
models do not take these emissions into account. Additional model results of wet deposition fluxes are
presented to demonstrate the potential of atmospheric climate models to deliver information of fluxes
of nutrients to the ocean.
28
SOLAS – Ireland
Proceedings
2006
2 Model set-up
We use the regional three-dimensional on-line climate-chemistry/aerosol model REMOTE (Regional
Model with Tracer Extension, http://www.mpimet.mpg.de/en/wissenschaft/modelle/remote.html)
(Langmann, 2000) which is one of the few regional climate models which determines the physical,
photochemical and aerosol microphysical state of the model atmosphere at every model time step. The
physical parameterisations of the global ECHAM-4 model (Roeckner et al., 1996) are used for the
current study. Photochemical and aerosol trace species undergo transport processes (horizontal and
vertical advection, transport in convective clouds, vertical turbulent diffusion) and are removed from
the atmosphere by sedimentation, dry and wet deposition (Langmann, 2000). For the determination of
aerosol dynamics and thermodynamics we use the M7 module (Vignati et al., 2004; Stier et al., 2005).
Five aerosol components sulphate (SO4), black carbon (BC), organic carbon (OC), sea salt (SS) and
mineral dust (DU) are considered in M7 either as compounds with no or low solubility or as internal
mixture of insoluble and soluble compounds. The aerosol size spectrum is subdivided into a nucleation,
aitken, accumulation and coarse mode. Each mode can be described by three moments: aerosol number
N, number median radius r, and standard deviation σ. Standard deviations are prescribed in M7, so that
the median radius of each mode can be calculated from the corresponding aerosol number and aerosol
mass, which are transported as 25 tracers. Thus, the total number of prognostic trace species in
REMOTE is 63, where 38 ones are included to describe photochemical transformations (Langmann,
2000).
Temporally variable anthropogenic emissions of SOx, NOx, NH3, CO, VOC’s, BC and POC are
taken from the EMEP emission inventory. For primary anthropogenic aerosol emissions, number mean
radius and number concentration of the respective size mode is related the mass concentration based on
Stier et al. (2005). In addition to terrestrial biogenic terpene and isoprene emissions from forests
(Langmann, 2000) we consider isoprene emissions from the ocean based on Meskhidze and Nennes
(2006). The net accumulation sea spray flux from Geever et al. (2005) is modified into a power law fit
in order to represent more realistically the flux at wind speeds below 5 m/s and above 20 m/s and is
used as an organic-inorganic source function for the mixture of POC and sea salt aerosols. Based on
clean sector measurements of the marine aerosol chemical composition at the Mace Head station (Yoon
et al., 2006), we set up a linear relationship between chlorophyll-a concentration and the percentage
contribution of POC to sea spray. Chlorophyll-a concentration in the surface ocean water measured
from MODIS (http://oceancolor.gsfc.nasa.gov/) serves as proxy for the ocean biological activity (Fig.
1c). Further details will be given in Langmann et al. (2007).
REMOTE is applied with 20 vertical layers of increasing thickness between the Earth’s surface and
the 10 hPa pressure level using terrain following hybrid pressure-sigma coordinates. The model domain
covers Europe and the Northeast Atlantic (see Fig. 1). At the first time step, REMOTE is initialised
using meteorological analysis data of the European Centre for Medium Range Weather Forecast
(ECMWF), which are updated at the lateral boundaries every 6h. Here we describe model results for
the months of June and December 2002.
3 Model Results
Preliminary REMOTE model estimates of the contribution of accumulation mode POC aerosols from
the ocean are illustrated in Fig.1 for June 2002. Without marine POC emissions (Fig. 1a) near surface
accumulation mode POC aerosols show elevated mass concentrations mainly over land in the vicinity
of urban and industrial centres, and at oil platforms off shore the Norwegian coast. By taking into
account marine POC emissions as described in section 2, near surface accumulation mode POC aerosol
mass concentration is considerably increased over the ocean (Fig.1b), in particular over the Baltic Sea,
29
SOLAS – Ireland
Proceedings
2006
the Black Sea and the North Atlantic west of Norway, but remains nearly unchanged over land. The
very high POC concentrations over the Baltic Sea and Black Sea result from high monthly mean
chlorophyll-a concentration during June (Fig.1c) whereas over the North Atlantic the wind speed
influence in the source function modulates the direct connection between near surface accumulation
mode POC aerosol mass concentration and chlorophyll-a concentration at the ocean surface. Isoprene
shows the highest near surface concentration over the Baltic Sea as well (Fig. 1d). The isoprene
distribution over the North Atlantic is different form the POC distribution in Fig. 1b, because isoprene
undergoes fast photochemical oxidation in the presence of OH, O3 and NO3 and is believed to be a
major precursor of secondary organic aerosols. During December 2002 negligible marine POC fluxes
occur due to the low ocean biological activity.
REMOTE: June 2002 near surface accumulation mode POC [ug/m3]
(a) without marine POC
(b) with marine POC
(c) Chlorophyll-a [mg/m3]
(d) Isoprene [ug/m3]
Fig. 1: Preliminary REMOTE model results of monthly mean near surface POC in the accumulation mode for June 2002
without marine POC emissions (a) and including marine POC emissions (b). For comparison the monthly mean chlorophylla content interpolated from MODIS satellite data to the REMOTE area is shown (c) and near surface monthly mean
isoprene concentration from marine and terrestrial sources (d).
REMOTE model results at the Mace Head measurement facility at the west coast of Ireland are
shown in Fig. 2 for June and December 2002. For the comparison the nearest model grid cell to Mace
Head was chosen. The land-sea-mask of this grid cell is covered half by land, half by the ocean. Taking
into account the horizontal model resolution of 0.5° and the more efficient deposition over land, it
might be more representative to choose the next grid point west for a comparison of model results with
Mace Head measurements, where slightly higher concentrations are expected.
During June 2002, westerly wind directions dominate at Mace Head with wind speeds between
about 4 to 10 m/s. BC mass concentrations in the accumulation mode reach only two times 50 ng/m3,
reflecting the very small influence of continental air masses at Mace Head during June 2002. Sea salt
and POC mass concentration are variable with maximum concentrations reaching 0.15 ug/m3. The
marine contribution to near surface POC mass concentration clearly dominates over the anthropogenic
contribution.
During December 2002 the weather situation at Mace Head is characterised by a long period with
easterly winds due of the influence of a high pressure system over Europe, and westerly winds at the
beginning and end of the month. Except the first few days, wind speed is only between about 2 to 8
m/s. Elevated concentrations of BC (and POC) up to 250 ng/m3 point to the transport of European
continental air masses to Mace Head. Due to the unusually low wind speeds for this season of the year
sea salt aerosol mass concentration remains pretty low.
30
SOLAS – Ireland
Wind speed
in 10m
Proceedings
Wind direction
in 10m
BC
accum. mode
Sea salt
accum. mode
2006
POC
accum. mode
Fig. 2: REMOTE model results at the Mace Head measurement facility at the west coast of Ireland for June
2002 (upper row) and December 2002 (lower row). Near surface aerosol mass concentrations are shown for the
accumulation (accum.) mode size interval only.
Fig. 3 shows exemplarily wet deposition fluxes of HNO3 and H2SO4 during December 2002. The
spatial distribution and magnitude of the two species wet deposition fluxes differ considerably. This
results from the different distribution of the emission sources of the precursor gases, different time
scales of chemical reactions and transport processes. A considerable amount of HNO3 is removed from
the atmosphere by wet deposition over the Atlantic Ocean, whereas H2SO4 is mainly deposited over the
eastern Mediterranean Sea.
REMOTE: December 2002: wet deposition [mg/m2/month]
HNO3
H2SO4
Fig. 3: REMOTE model results for wet deposition of HNO3 and H2SO4 in December 2002.
31
SOLAS – Ireland
Proceedings
2006
4 Conclusions and Outlook
The model simulation results of the exchange of short living gases and aerosols between the ocean
surface and the marine atmosphere presented in this paper are the first steps towards the inclusion of
other marine emissions than sea salt in atmospheric climate models. Over the ocean, a considerable
impact on climate can be expected from these preliminary simulation results. Evaluation of these model
simulation results by comparison with measurement data is a next important step. Further analysis in
higher atmospheric layers will be necessary to investigate the transport of marine aerosols from the
ocean to land areas. Formation of secondary OC aerosols from marine isoprene emissions will be
studied to distinguish between the contribution of primary and secondary organic aerosols, and water
soluble and insoluble organic aerosols. It should be noted that the REMOTE model is not restricted to
applications over Europe; it is applicable in any focus region worldwide up to a horizontal resolution of
10 km.
For further investigations, e.g., under climate change conditions it will be necessary to develop a
coupled biogeochemical ocean-atmosphere model system. The ocean model should be able to provide
sea surface temperature, chlorophyll-a concentration at the ocean surface and white cap coverage to
better determine trace species fluxes from the ocean to the atmosphere. On the other hand, the
atmospheric model should be able to provide heat, water and nutrient fluxes for the ocean model.
Coupled model simulations would contribute to improve our understanding on the release and
formation of primary and secondary marine aerosols and their impact on marine photochemistry. In
addition, investigations of cloud processes, precipitation formation and the solar radiation budget in the
marine atmosphere with feedbacks to the ocean would be possible.
References
Geever, M., O’Dowd, C., van Ekeren, S., Flanagan, R., Nilsson, E.D., de Leeuw, G. and Rannik, Ü.,
Submicron sea spray fluxes (2005). Geophys. Res. Lett., 32, doi: 10.1029/2005GL023081.
Langmann, B. (2000). Numerical modelling of regional scale transport and photochemistry directly
together with meteorological processes. Atmos. Environ. 34, 3585-3598,
Langmann, B., O’Dowd, C., Varghese, S., Scannell, C. and Ceburnis, D. (2007). Regional model
estimates of organic matter in sea spray aerosols, in preparation for Geophys. Res. Lett.,
Lohmann, U. and Feichter, J. (2005). Global indirect aerosol effects: a review, Atmos. Chem. Phys. 5,
725-737.
Martensson, E. M., Nilsson, E. D., de Leeuw, G., Cohen, L.H. and Hansson, H.-C. (2003). Laboratory
simulation and parameterization of the primary marine aerosol production, J. Geophys. Res. 108,
doi: 10.1029/2002JD002263.
Meskhidze, N. and Nenes, A. (2006). Phytoplankton and Cloudiness in the Southern Ocean, Science
314, 1419-1423.
Monahan, E.C., Spiel, D.E. and Davidson, K.L. (1986). A model of marine aerosol generation via
whitecaps and wave disruption, in Oceanic Whitecaps and their Role in Air-Sea Exchange, ed. E. C.
Monahan and G. Mac Niocaill, D. Reidel, 167-174.
O’Dowd, C., Facchini, M.C., Cavalli, F., Ceburnis, D., Mircea, M., Decesari, S., Fuzzi, S., Yoon, Y.J.
and Putaud, J.-P. (2004). Biologically driven organic contribution to marine aerosol, Nature 431,
676-680.
32
SOLAS – Ireland
Proceedings
2006
Roeckner, E., Arpe, K., Bengtsson, L., Christoph, M., Claussen, M., Dümenil, L., Esch, M., Giorgetta,
M., Schlese, U. and Schulzweida, U. (1996). The atmospheric general circulation model ECHAM4: Model description and simulation of present-day climate, Report No. 218, Max Planck Institute
for Meteorology, Hamburg, Germany,
Schulz, M., de Leeuw, G. and Balkanski, Y. (2004). Sea-salt aerosol source functions and emissions,
in: Emission of the Atmospheric Trace Compounds, Kluwer, 333-359.
Smith, M.H., Park, P.M. and Consterdine, I.E. (1993). Marine aerosol concentrations and estimated
fluxes over the sea, Q. J. R. Meteorol. Soc. 119, 809-824.
Stier, P. et al. (2005.) The aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys. 5, 1125-1156.
Vignati, E., Wilson, J. and Stier, P. (2004.). M7: An efficient size-resolved aerosol microphysics
module for large-scale aerosol transport models, J. Geophys. Res. 109, doi:10.1029/2003JD004485.
Yoon, Y.J., Ceburnis, D., Cavalli, F., Jourdan, O., Putaud, J.P., Facchini, M.C., Decesari, S., Fuzzi, S.,
Jennings, S.G. and O’Dowd, C. (2006). Seasonal characteristics of the physico-chemical properties
of North Atlantic marine atmospheric aerosols, J. Geophys. Res. submitted.
33
SOLAS – Ireland
Proceedings
2006
Predictive North-East Atlantic and Irish Sea models – hydrodynamic, surge and
wave modelling
Indiana Olbert and Michael Hartnett
Marine Modelling Group, MRI, NUI Galway, Ireland.
Climate change and its potential impact on the coastline of Ireland is a problem of high urgency.
Among the most significant challenges to be faced are rising sea level coupled with a trend towards
increased storminess. These phenomena are now considered to have a major effect on the stability of
beaches and offshore sandbanks. The greatest concern is focused on the erosion of dune systems with
the devastating effect on a shoreline habitat. The long-term observations show the increased erosion
due to the action of wave energy generated by winter storms. This is often accompanied a lowering of
the beach level as sand is carried offshore – and uncertainty surrounds the importance of offshore
sandbanks and the role that they play in both protecting the shoreline from wave action and in
replenishing the beach with sand following a storm event. The remobilisation of sediment, storminess
and rising sea level are also responsible for local flooding. In 2001 the Intergovernmental panel on
Climate Change (IPCC, 2001) reported based on records since 1861 that the average surface
temperatures are projected to rise 1.4ºC to 5.8ºC between 1990 and 2100. In the same period mean sea
levels are projected to rise by 0.09 to 0.88 m primarily due to thermal expansion and the loss of ice
from glaciers and ice cups.
To provide insight into the mechanism acting on coastal locations due to extreme weather events, highresolution numerical models have been developed within PRISM project and used to study
hydrodynamic processes, wave action, water quality and movement of sand in the near-shore region. In
particular, these covered the influence of changing sea levels, impact of increased wind and storm
direction, precipitation rate, freshwater discharge and heat exchange at air-sea interface. Although, the
PRISM project is focused on the Irish Sea region, the hydrodynamic and wave models developed cover
the North-East Atlantic region in order to provide the large-scale Atlantic forcing to the Irish Sea zone
within which the local-scale tidal model with water quality and sediment transport mode have been
imbedded.
The PRISM project has resulted in the development of 5 numerical models giving hydrodynamic and
wave dynamics outputs for 4 regions namely: North-East Atlantic, Continental Shelf, Irish Sea and
Dublin Bay. The scheme of dependencies between models has one-way cascade structure using nesting
technique. For hydrodynamics, the Dublin Bay model is nested within the Irish Sea model, while Irish
Sea model is nested with the North-East Atlantic model. Similarly for wave simulation, the North-East
Atlantic wave model provides boundary conditions for Continental Shelf wave model.
The domain of North-East Atlantic is defined by the geographic region: -30ºE ÷ 0ºE longitude and
40ºN ÷ 60ºN latitude as presented in Figure 1. The numerical model chosen for the system is the
Princeton Ocean Model (POM) developed originally by Blumberg and Mellor (Mellor, 1988). The
computation includes hydrodynamic and surge residual fields and is carried out on high-resolution 5’x
2.5’ horizontal grid. The three-dimensional hydrodynamics is forced by baroclinic conditions on top of
variable water elevations due to tides that consist of 5 constituents. Meteorological conditions covering
the whole region are derived from Met Eireann HIRLAM model at two horizontal resolutions and one
hour time average. The results form both the fine and coarse grid models are integrated together and
interpolated on POM mesh to provide the optimum surface meteorological boundary conditions to the
POM surge model. The surge residual outputs were extensively compared against 40 storm events data.
34
SOLAS – Ireland
Proceedings
2006
The overall model validation was found to be successful. Exemplary results from the comparison are
presented in Figure 2.
The NE Atlantic grid outputs of water elevations are interpolated down to 1/24º of latitude and 1/12º of
longitude (~5 km) scale to be fed at the open boundary of Irish Sea model. This one-way nesting allows
a transfer of boundary tidal and surge energy from coarse grid into fine grid of the Irish Sea.
Coordinates -7ºE ÷ -2.625ºE and 51ºN ÷ 56ºN bound the model area shown in Figure 3. The
POLCOMS 3D numerical model of the Irish Sea is used to provide three-dimensional hydrodynamic,
temperature and conservative tracer fields for web display. The temperature validation graphs are
presented in Figure 4 and Figure 5.
The Dublin Bay model (Figure 6) is nested within the Irish Sea model from which it extracts elevation
conditions and feeds them at the open boundaries. Depth-averaged DIVAST numerical model
developed by Professor Falconer (Falconer and Liu,1988) is employed to run the hydrodynamics and
solute transport within the shallow Dublin Bay as the code unlike any other is adapted to periodical
wetting and drying of coastline. The high resolution model resolves hydrodynamic fields on 50m x
50m square grid.
In modelling of wave dynamics the WAM wave model is adopted for the North East Atlantic region
within which the Continental Shelf zone is resolved using the SWAN wave numerical model. Both
WAM (Wave Model) developed by the WAMDI Group (Hasselmann et al., 1987) and the SWAN
(Simulation of WAves Nearshore) model (Booij et al., 1999) solve the non-linear interaction processes
by incorporating time varying meteorological conditions, currents, tides and bottom conditions. The
wave energy conditions extracted from large NE Atlantic are implemented to high-resolution
Continental Shelf SWAN model so that the shallow water physics can be resolved without loosing the
importance of small-scale processes. The significant height, direction and period of waves in the Irish
Sea are uploaded to the website. Figure 7 shows the comparison between SWAN model and data buoy.
All numerical models developed under PRISM project run operationally to provide 48 hour forecasts of
meteorological and oceanographic conditions. Data are available in form of 6 hour interval snapshots
covering the Irish Sea domain or as timeseries for 13 specified locations. The forecasts are displayed on
a dedicated website www.prism.ie where they can be accessed by the public. The website provides map
information on wind strength and direction, tides, surface currents and temperatures as well as wave
heights and periods. Additionally, timeseries data also contain surge residual forecasts. This range of
information gives conditions that are essential to promote activities such as sailing and surfing.
For end users, the data set is enlarged by surge snapshots as well as 3-dimensional fields of
conservative tracer, temperature and currents. These data are protected by password and allow make a
‘what if’ calculations on flooding and/or water quality issues. On that basis the public can be aware in
case of marine danger. The extensively tested and validated PRISM models have become a data source
for Department of Communications, Marine and Natural Resources to issue their warning letters for
storm surge forecast in Irish Waters.
Recent researches show that the Atlantic Ocean is very sensitive to climate change. The PRISM models
can be now the basis for climate change studies and can serve as a tool in prediction of reliable changes
in the coming decades. Particularly, when coupled with atmospheric model it may provide valuable
information on moving spatio-temporal changes in stratification and distribution of vertical fluxes. This
would further allow exploring and analysing the effect of changes in solar radiation, clouds cover and
ocean stratification on sea-air exchange.
35
SOLAS – Ireland
Proceedings
2006
Figure 1. Bathymetry model of NE Atlantic constructed from the 2004 GEBCO data set and the Irish
National Seabed Survey data (INNS). Depth in meters.
Fishguard
1
NUMERICAL MODEL
BODC
Surge residual, m
0.8
0.6
0.4
0.2
0
-0.2
-0.4
00:00 01-04
00:00 01-05
00:00 01-06
00:00 01-07
00:00 01-08
00:00 01-09
00:00 01-10
00:00 01-11
00:00 01-12
00:00 01-07
00:00 01-08
00:00 01-09
00:00 01-10
00:00 01-11
00:00 01-12
Mumbles
1.2
Surge residual, m
1
0.8
NUMERICAL MODEL
BODC
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
00:00 01-04
00:00 01-05
00:00 01-06
36
SOLAS – Ireland
Proceedings
2006
Barmouth
1.4
1.2
Surge residual, m
1
NUMERICAL MODEL
BODC
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
00:00 01-04
00:00 01-05
00:00 01-06
00:00 01-07
00:00 01-08
00:00 01-09
00:00 01-10
00:00 01-11
00:00 01-12
Figure 2. Validation figures of storm surge simulation1993/01/04 – 1993/01/12.
Figure 3. The numerical domain of POLCOMS Irish Sea model.
37
SOLAS – Ireland
Proceedings
2006
19
Temperature [deg C ]
17
15
data surface T
13
data nearbed T
POLCOMS surface T
POLCOMS nearbed T
11
9
7
5
0
50
100
150
200
250
300
350
Year day 1995
Figure 4. Annual temperature timetrace at chosen point in the Irish Sea.
Figure 5. Vertical profile of temperature in the Western Irish Sea (WIS) responsible for developing
western gyre.
38
SOLAS – Ireland
Proceedings
(a)
2006
(b)
Figure 6. Mid flood (a) and high water (b) currents in Dublin Bay
SW AN
M2 BUOY
5.0
4.5
Significant Height (m)
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
5
6
7
8
9
10
11
12
13
14
15
Time (days)
Figure 7. Comparison between SWAN numerical prediction of significant wave height and M2 Buoy
data.
References
Booij, N., Ris R.C. and Holthuijsen, L.H. (1999). A Third Generation Wave Model for Coastal Regions
Part 1. Model Description and Validation. Journal of Geophysical Research, Vol. 104, pp. 76497666.
Falconer, R.A. and Liu, S. (1988) Modelling of Solute Transport Using QUICK Scheme. Journal of
Environmental Engineering, Vol. 14, No. 1, pp. 3-20;
Hasselmann, S. (1987) The WAM model – A Third Generation Ocean Wave Prediction Models.
Journal of Physical Oceanography, Vol. 18, pp. 1775-1810;
IPCC (2001) Climate Change 2001, The Scientific Basis. Ed: Houghton, J.T., Cambridge University
Press, pp. 994.
Mellor, G.L. (1988) The Three-Dimensional, Primitive Equation, Numerical Ocean Model. Program in
Atmospheric and Ocean Sciences, Princeton University.
39
SOLAS – Ireland
Proceedings
2006
Algal responses to environmental change: seaweed-environment interactions and
their applications
Dagmar Stengel
Department of Botany, National University of Ireland, Galway
As primary producers upon which marine food webs depend, marine macro- and microalgae are at the
centre of a number of current strategic research foci. As photoautotrophic organisms algae are impacted
by their immediate ambient environment, and particularly intertidal macroalgae influenced by naturally
fluctuating osmotic, temperature and nutrient regimes imposed by tides and seasons. Responses to
environmental factors, and also biotic stresses such as grazer attack, endo- and epibiontic microbial and
viral infection, are species-specific and have resulted in a range of natural stress- and defence
mechanisms. Eco-typic specificity and phenotypic plasticity allow small-scale adjustments of
metabolites to optimise productivity or survival, depending on life-strategy of the particular species.
Research in Dr Stengel’s group at NUIG is currently integrating a number of aspects regarding
the application of seaweeds in environmental monitoring, and is investigating some key issues related
to climate change. Most research has focused on quantifying the effects of environmental parameters
on physiological responses and biochemical compounds with a view to develop bioassays, biomarkers
and protocols for assessing environmental change using seaweeds. Additionally, experimental
investigations into the environmental control of bioactive compounds are underway. An improved
understanding, through careful R&D, of the control of the production of bioactive properties can be
manipulated and optimised simply by modifying growth conditions in controlled environments. For
example, the production of naturally produced substances with certain biochemical properties can be
induced or enhance by exposing algae to certain environmental conditions. Such substance may be
natural defence-compounds against UV-radiation (polyphenols) or osmotic stress (e.g. mannitol). As
some of these compounds have significant bioactive properties, the investigation of the metabolic
function and environmental control has implications in the future use as biomarkers for environmental
impacts, but also in applied industrial research (Fig. 1).
Algae, and marine macroalgae in particular, at the forefront of marine research in Ireland as
their biological compounds have applications in biomedical and pharmaceutical research through the
screening of natural marine resources for new bioactive products, some of them natural stress-induced
defence products, with pharmaceutical applications (‘biodiscovery’). An improved understanding of the
mechanisms of compound production and function will potentially allow their optimisation and the
maximisation of their yield. Ecophysiological research at NUIG in Dr Stengel’s group bridges the gap
in knowledge between applying environmental stressors and observing the presence of the compounds
by trying to understand the biological mechanisms involved in their production.
40
SOLAS – Ireland
Proceedings
2006
Seaweed-environment interactions and their applications
Climate change
bio
se
ns
ing
Baseline conditions
ing
ns
se
bio
Physiological response
nit
ori
ng
&
Seaweeds
B io
mo
&
g
rin
i to
on
om
Bi
Environmental conditions/
Environmental quality
F eeb
ack
Eutrophication
Pollution/contamination
Biochemical composition, biomarkers
(Non)bioactive compounds, known or new
Biodiscovery
Fig. 1. Seaweed environment-interactions and their applications in environmental monitoring and biodiscovery research.
In addition, fast, sensitive measurable physiological responses of algae can be used in biomonitoring,
as biomarkers and ecological indicators: as algal functional physiology is directly controlled by the
ambient environment, seaweed responses can be used to sensitively assess and monitor environmental
condition. The relationship between environmental triggers and responses can then be used
quantitatively, and ecologically relevant, to measure environmental quality. Such applications of algae
in environmental monitoring have included their use in monitoring of eutrophication and pollution in
coastal ecosystems. In particular, as bioavailable fractions of metals are ad- or absorbed by seaweeds
and subsequently will bioaccumulate in the marine food chain; their application in biomonitoring has
many advantages over traditional methods. Current and recent research at NUI Galway has included
the development of biomarkers in the assessment of metal contamination, the development and
application of bioassays, with particular emphasis on chlorophyll fluorescence and compared these
methods with traditional biomonitoring approaches (e.g., Stengel et al. 2004, 2005)
General key issues regarding the effects of global change on algae include effects of solar
radiation, temperatures and CO2-availability which is linked to potential future ocean acidification.
Table 1 summarises some key questions of algal-environment interactions with relevance to global
change. Algal biological processes of particular relevance to SOLAS include their carbon metabolism
(as part of the photosynthetic process) including short-term acclimation and long-term adaptations of
populations to elevated CO2 concentrations, the release of organic matter into the sea, as was as the
production and release of DMS (DMSP) and halocarbons which have received particular attention.
41
SOLAS – Ireland
Proceedings
•
Solar radiation:
– Decrease: decreased productivity?
– Increase: increased productivity in deeper water? Decreased at surface and
in intertidal?
– Change in diffuse: species-specific?
– UV: no effect in subtidal? Severe effect in intertidal/surface?
•
Temperature:
– Enhanced productivity; reduced productivity? Incomplete life-cycles; change
in species composition? Change in distribution and ranges, adaptations.
•
Nutrients (N, Fe):
– Increased productivity?
– Changes in metabolism likely: adaptations?
– Change in species composition?
•
CO2:
– Enhanced productivity? C bioavailable? Carbon concentration
mechanisms? C:N ratios; adaptations?
– Distinguish between intertidal and subtidal/phytoplankton; community
changes?
2006
Table 1: Key issues of algal research: potential algal responses
to global change.
Recent research has focused on algal physiological and chemical responses to O3, UV-radiation and
elevated temperatures. Algae-environment interactions are complex, marine environments are
characterised by natural fluctuations and many algal responses are group- or even species-specific so
that generalisations of algal responses should be treated with caution. Particular ‘unknowns’ and areas
of research that need attention are short- and long-term adaptations of populations and species, and
their responses to potential interactive effects of environmental parameters.
Important issues concerning algae and climate change include currently unpredictable effects of
changes in solar radiation, including UV and PAR and changes in diffuse radiation, on productivity of
species occupying different marine, coastal and off-shore, habitats. For example, productivity of
intertidal and subtidal species may be affected differently; in particular UV radiation is likely to have
significant effects in intertidal and shallow subtidal waters, but less pronounced impacts at greater
depths. Some preliminary observations from Galway Bay suggest that significant pigment bleaching
events take place in red algae during spring tides in early winter. These appear to be recent phenomena
and potentially represent direct evidence of recent climate change impacts on local marine species.
Further research in this field is needed to consolidate these results. Also, temperatures responses are
difficult to predict in that they affect both photosynthesis and respiration, and both short- and long-term
adjustments can be expected, at least in some species, and productivity of certain species may be
reduced, while that of others increased. Similarly, different life stages of algae may respond differently
to temperature changes, and the completion of life cycles that are often controlled, or their initiation
triggered, by combinations of photoperiod and temperature, could be under threat. As regards
phytoplankton, changes in ocean currents but also overall changes in surface water temperatures are
likely to alter species distribution patterns. Little is known about long-term adaptations of species to
changes in temperature and abundances and distributions of algae, e.g. those with particular ecological
functions, or, in the context of SOLAS, those emitting marine aerosols. Similarly little is known about
any temperature effects on iodine emissions or those of other halogens and halocarbons.
Although the major form of inorganic carbon utilised by algae is CO2, several species of both
macro- and microalgae have developed carbon-concentrating mechanisms which allows them to fix
(and later convert) other forms of inorganic carbon. The driving, or limiting, factors of carbon
assimilation by algae in situ directly influence the abundance of algal biomass; this ultimately absorbs
more (or less) carbon and also results in the production of compounds of ecological importance,
42
SOLAS – Ireland
Proceedings
2006
including aerosols. However these essential processes are poorly understood and will require
significant attention in the near future.
Specific algae-environment interactions relevant to SOLAS include their contribution to
biogeochemical cycling in coastal and off-shore waters, with basic metabolic functions of algae, both
micro- and macroalgae, controlled by light, nutrients and temperatures. A range of organic compounds,
including non-methane hydrocarbons (alkenes) that could be detected in marine systems have been
related to the presence of algae, both macro and microalgae. Some of these are considered of algal
origin and substantial temporal fluctuations have been observed (Gist and Lewis, 2006). Also, isoprene
and alkyl halides were recently measured near Mace Head, Co. Galway, and appeared to be linked to
the presence of large amounts of macroalgal biomass (Greenberg, 2005). Both planktonic single-celled
algae and seaweeds contribute significantly to ethane production, with a particularly high production in
coastal areas suggesting a macroalgal origin (Broadgate et al. 2004). Recent evidence suggests that
algal metabolic compounds, often those produced under stress, are released into the water in potentially
large quantities, significantly contributing to the pool of dissolved organic matter. Such compounds
include polyphenols from brown algae, but also mycosporine-like amino acids from red algae. Our
understanding of the origin, production as well as the mechanisms by which these compounds are
produced is limited. For example, polyphenols appear to have a range of ecological functions, and their
production has been linked to a number of factors including UV-radiation, nutrient and temperature
conditions and grazing activity. Some aspects of the environmental control of this are currently under
investigation in Dr Stengel’s group. Stability of DOM, including that of brown algal origin in seawater
is photo- and UV- sensitive (e.g. Ratte et al. 1998; Riemer et al. 2000). On the other hand, light
(including UV radiation) also directly influences algal organic matter production, as well as the rate
and degree of its release, as well as algal growth and photosynthetic performance (e.g. Bishof et al.
1998; Davison et al. 2007). This emphasises the importance of improving our understanding of the
mechanisms by which such compounds are produced and released into the sea, in addition to
attempting to quantify their actual amounts. In the past several publications have high-lighted
emissions into the atmosphere either by algae directly or by coastal and off-shore systems where algae
were growing; of particular interest, and significance, were iodocarbons and different forms of iodine,
including I2. For example, these were emitted from brown macroalgae (mainly Laminaria and Fucus
species, possibly due to their greatest abundance) and these have particular significance in aerosol
formation (McFiggans 2004; Greenberg et al. 2005; Palmer et al. 2005).
Other research at NUI Galway, as part of EPA (ERTDI)-funded project (WP4 in Cluster-project
BioChange; www.BioChange.ie), focuses on the characterisation of natural productivity of a model
keystone species (Ascophyllum nodosum) under today’s climatic conditions and the assessment and
modelling of the effects of predicted global change on Ascophyllum nodosum as a habitat-forming
keystone primary producer in intertidal Irish environments. It aims to predict potential changes in
standing crop and productivity that could affect its role as a habitat facilitator for high coastal
biodiversity. Further, potential effects of harvesting in the future under increased environmental
pressure and habitat loss due to climate change, eutrophication and sea level rise are under
investigation. Also, the potential for Ascophyllum nodosum as a biological indicator for global change
is being evaluated and its possible role as a carbon sink is considered. This work encompasses field and
laboratory studies in selected sites in Galway Bay (Counties Galway and Clare). Currently
measurements of productivity (measured as in vivo Pulse Amplitude Modulated chlorophyll
fluorescence), O2-evolution and CO2-uptake are underway under a range of environmental conditions,
including in air and water. Correlations of results obtained using different methods to measure
productivity are established. Fig. 2 illustrates some preliminary results of changes in CO2-uptake rates
of a plant undergoing desiccation using an Infra-red Gas Analyser.
43
SOLAS – Ireland
Proceedings
2006
-2
-1
Photosynthetic rate (µmol C m s )
10
8
6
4
2
IRGA analysis of Ascophyllum nodosum tip in air
o
-2
-1
(20 C, 1000 µmol m s )
0
0
20
40
60
80
100
120
Time (min) after emersion
Fig 2. CO2-uptake rate over 2h of A. nodosum (Fucales, Phaeophyceae) from Galway Bay undergoing dehydration
(measured in air, 20ºC, December 2006). Data: McGrath and Stengel, (unpublished data)
Another application of current knowledge in algal ecophysiology is in the field of natural sunscreens
produced by brown algae such as fucoids (Fucales) and kelps (Laminariales). Photoprotective
compounds in brown algae include carotenoid pigments that absorb excess energy, as well as
phlorotannins. Current research focuses on the distribution of polyphenols in selected algal species,
their seasonal and spatial variation, and their potential application as sunscreens in cosmetic industries.
This project is funded by the Marine Institute under the Marine RTDI Measure (Strategic Programme
2005).
Polyphenols, and particularly the environmental control of their production and exudation, are
also the focus of another, EPA-funded, project in the group. Given that they can bind significant
amounts of metals under natural conditions, besides algal polysaccharides they have an important role
to play in the development of biomonitoring protocols for marine systems in Ireland. As this project
concentrates on the influences of light, temperature and nutrients on the production and release of
phenols which represents a significant contribution of DOM in coastal waters, it is also of direct
relevance, and importance, to SOLAS. In this project a dual approach is used by combining field
monitoring of phlorotannins in algae from selected sites, and relating these to site-specific
environmental features, with laboratory-based research under controlled conditions.
References
Bishof, K., Hanelt, D., Tüg, H., Karsten, U., Patty E., Brouwer, P.E.M. and Wiencke, C. (1998).
Acclimation of brown algal photosynthesis to ultraviolet radiation in Arctic coastal waters
(Spitsbergen, Norway). Polar Biology, 20, 388-395.
Broadgate, W.J., Malin, G., Küpper, F.C., Thompson, A. and Liss, P.S. (2004). Isoprene and other nonmethane hydrocarbons from seaweeds: a course of reactive hydrocarbons to the atmosphere. Marine
Chemistry 88, 61-73.
44
SOLAS – Ireland
Proceedings
2006
Davison, I.R., Jordan, T.L., Fegley, J.C. and Grobe, C.W. (2007). Response of Laminaria saccharina
(Phaeophyta) growth and photosynthesis to simultanous ultraviolet radiation and nitrogen limitation.
Journal of Phycology, in press.
Gist, N. and Lewis, A.C. (2006). Seasonal variations in dissolved alkenes in coastal waters. Marine
Chemistry 100, 1-10.
Greenberg, J., Guenther, A.B., and Turnipseed, A. (2005). Marine organic halide and isoprene
emissions near Mace Head, Ireland. Environmental Chemistry 2, 291-294.
McFiggans, Coe, H., Burgess, R., Allan, J., Cubison, M., Alfarra, M.R., Saunders, R., Siaz-Lopez, A.,
Plane, J.M.C., Wevill, D.J., Carpenter, L.J., Rickard, A.R. and Monks, P.S. (2004). Direct evidence
for coastal particles from Laminaria macroalgae – linkage to emissions of molecular iodine.
Atmospheric Chemistry Research 4, 701-713.
Palmer, C.J., Anders, T.L., Carpenter, L.J., Kuepper, F.C. and McFiggans, G.B. (2005). Iodine and
halocarbon response of Laminaria digitata to oxidative stress and links to atmospheric new particle
production. Environmental Chemistry 2, 282-290.
Ratte, M., Bujok, O., Spitzy, A. and Rudolph, R. (1998). Photochemical alkene formation in seawater
from dissolved organic carbon: results from laboratory experiments. Journal of Geophysical
Research 103, 5707-5717.
Riemer, D.D., Milne P.J., Zika, R.G. and Pos, W.H. (2000). Photoproduction of nonmethane
hydrocarbons (NMHCs) in seawater. Marine Chemistry 71, 177-198.
Stengel, D.B., Macken, A., Morrison, L. and Morley, N. (2004). Zn concentrations in marine
macroalgae and a lichen from western Ireland in relation to phylogenetic grouping, habitat and
morphology. Marine Pollution Bulletin 48: 902-909.
Stengel, D.B., McGrath, H., and Morrison, L.J. (2005). Tissue Cu, Fe and Mn concentrations in
different-aged and different functional thallus regions of three brown algae from western Ireland.
Estuarine, Coastal and Shelf Science 65(4): 687-696.
45
SOLAS – Ireland
Proceedings
2006
Groundwater Inputs to the Coastal Zone of south County Galway and north and
west County Clare
Rachel R. Cave & Tiernan Henry
Department of Earth & Ocean Sciences, NUI, Galway
1 Introduction
There are two distinct freshwater discharge regimes to Galway Bay: predominantly surface water on
the north side of the Bay; and predominantly groundwater on the south side of the Bay. This study
focuses on the groundwater discharges from the catchment that covers an area of approximately
1000km2 from Kilchreest/Loughrea in the east to Slievecarran in the west and below Lough Cutra in
the south.
The hydrogeology of the catchment is well understood (Drew & Daly, 1993) and has been well
documented but there has been no direct quantification of discharges to the coastal zone (Jennings
O’Donovan & Southern Global Water, 1997). Indeed, little work has been done in Ireland in
quantifying groundwater discharges in coastal zones. Therefore there is scant data on the nutrient and
contaminant loads delivered by groundwater to our coastal waters. Such studies are common in other
regions and locations (Bayari & Kurttas, 2002; Beddows, 2004).
The objectives of this ongoing study are:
•
To measure/quantify groundwater discharges;
•
To sample levels of nutrients in the discharge;
•
To determine loads entering coastal waters from groundwater; and,
•
To compare results with river inputs.
2 Background
An explanation of the catchment is important in understanding water movement.
2.1 Geology
The upland area in the south east of the catchment (Slieve Aughty) is composed of a mixture of silt,
sand and mudstones (Pracht et al, 2004). The lower ground along the western flank of the hills is made
up of Carboniferous Lower-Limestone Shales and muddy fossiliferous limestones.
The remainder of the catchment is made up of Carboniferous Limestone.
2.2 Hydrology
The surface drainage network in the catchment is entirely reflective of the underlying geology. There is
a well-developed surface water stream and river network in the Slieve Aughty area. Runoff from the
46
SOLAS – Ireland
Proceedings
2006
upland area discharges to the lowlands and eventually to Galway Bay. The surface drainage features in
the lowland area are intermittent and/or seasonal.
Rainfall runoff from the upland area is rapid. There is little storage of water in the soils or in the rock.
Rainfall amounts are elevated in the upland areas. The lowland area has a very low gradient (from
Limepark to Kinvarra the gradient is less than 10-3 – one metre/kilometre) so this tends to drain less
quickly than the upland areas. If input is greater than output then storage in the system must increase,
leading to flooding.
This flooding was most pronounced in the winter of 1994/1995 when almost 70 percent of the annual
average rainfall fell between December and February (Jennings O’Donovan & Southern Global Water,
1997). The volume of water generated could not drain as quickly as it fell leading to flooding. This was
exacerbated by a series of very high tides in Galway Bay driven by westerly winds (Smyth, 1998).
2.3 Hydrogeology
The geology of the catchment determines the nature of the groundwater flow regime. This catchment
has two distinct lithological settings (the sandstones and impure limestones in the south east, and the
pure limestones in the remainder of the catchment) that have very distinct flow regimes.
Groundwater will flow through all material, but the rates of flow can vary over 12 orders of magnitude,
expressed by the hydraulic conductivity (K). Sandstones and impure limestones tend to have low
conductivity values, indicating that groundwater will move relatively slowly through these formations.
Unweathered pure limestone tends to have low conductivity values too, but where the rock is
weathered the conductivity values increase dramatically.
Flow occurs most readily through openings or conduits in rock. Rock subjected to weathering or
faulting can develop high values of secondary porosity in localised areas in the rock. While the pure
limestone has a low porosity and conductivity, if conduits are open in the rock the porosity and
conductivity increases.
Almost all drinking water in the limestone area is derived from groundwater sources (principally bored
wells). Although the limestone has a low conductivity, where dissolution has occurred there is potential
for rapid movement of large volumes of water. These areas are the targets for the placement of large
yield wells.
Wells bored into karst conduits can readily supply large volumes of water. Kinvarra’s drinking water is
supplied from wells located at Loughcurra South (approximately 1.5km southeast of the village). These
wells (a duty and standby) yield 60-70m3/hour, 24-hours a day (Cave et al, 2005). In the years of
operation the wells have never dried out.
Karst areas can therefore be excellent water supply aquifers. The pure limestone in this area is classed
as Regionally Important Kart Aquifer (Rk) (DoELG, 1999). The upland area in the southeast of the
catchment is classed as a Poor Aquifer, generally unproductive except for local zones (Pl). The lower
limestone shales form Locally Important aquifers, moderately productive in local zones only (Ll).
The vulnerability of the groundwater to contamination varies as a function of geology and soil cover.
Through most of the catchment the soil cover is thin or non-existent and the entire area underlain by the
pure limestone is classed as Extremely Vulnerable.
47
SOLAS – Ireland
Proceedings
2006
Contaminants entering the conduits can be transported long distances very rapidly, so the high yield
wells are very vulnerable to contamination.
The catchment is largely agricultural and stocking densities are low. The principal contaminants of
concern in the area are nitrate, phosphate and micro-organisms. Non-aqueous phase liquids (NAPLs)
are of local concern in limited areas (at petrol stations and where fuels are stored). Intrusion by
seawater is also a major water quality issue in this catchment.
Far more water flows through the aquifer than is abstracted from, or stored in, the system. Most of the
water flows into the sea. A large part of the flow from the Gort-Kinvarra catchment flows into the sea
between the town of Kinvarra and Dunguaire Castle on the Galway Road (Drew, 2001). Some of it
flows into the sea further south along the coast, into Aughinish Bay, Muckinish Bay (Bell Harbour) and
Ballyvaughan Bay. Many of the flows are very strong, and at low tide it appears as though a river is
running into the sea, but one that springs straight out of the rock. It is likely than when sea level was
lower, some of these 'springs' that are in the intertidal zone today were the source springs for rivers
flowing out to sea across large areas of the exposed continental shelf.
This flow into the coastal waters is very important, because many of the bays around Galway support
aquaculture of fish and shellfish, and harvesting of seaweeds. If the groundwater is contaminated in any
way, these contaminants are carried out into the coastal waters (Valiela et al, 1990; UNESCO, 2004). If
the groundwater is rich in nutrients, for example, it may lead to 'blooms' of algae, which can strip
oxygen from the water when they die, killing fish and other aquatic life (Slomp & Cappellen, 2004;
Giblin & Gaines, 1990). Some of these blooms may be toxic, and as phytoplankton are the food for
filter feeders such as mussels and oysters which are cultivated in these bays, they then become
dangerous to eat (Johannes, 1980). In either of these cases, the aquaculture sites may have to be closed,
representing a significant economic loss to the owners and to the local economy.
The presence of large conduits in the intertidal zone also means that seawater can find its way into the
groundwater system (Capone, & Bautista, 1985; Saltrans, 2003; Marin & Perry, 1994). This can
happen at times of spring tides, when the tide comes high up the shore, especially if the spring tide
coincides with a dry spell, where rainfall and therefore water flow through the system is low. Often this
happens in the summer holiday season, when lots of tourists are about, and the demand for fresh water
is high, which exacerbates the problem. Contamination of an aquifer by seawater can be serious, as the
water from wells close to the coast will be unfit to drink, and it may take days or even weeks to flush
all the salt out of the system (Moore, 1996).
3 Determination of Discharges
Discharges from the Shannon and the Corrib are recorded with accuracy and show how the disposition
of rainfall is expressed in river discharges. Simple water balance calculations show that in both these
large catchments surface water discharge dominates (see Table No. 1). Using annual data it can be
shown that measured and calculated discharges are of the same order of magnitude for both rivers.
48
SOLAS – Ireland
Proceedings
2006
Table No. 1: Water balance calculations for the River Shannon and River Corrib
Catchment
Name
Area
(km2)
AAR
(mm)
PET
(mm)
ER
(mm)
Calculated
Discharge
(m3/s)
Measured
Discharge
(m3/s)
Shannon
11,903
1024
450
574
215
213
Corrib
3,111
1331
450
881
87
99
The Kinvarra catchment is part of Hydrometric Area No. 29 and the West Clare coast is part of
Hydrometric Area No. 28. If the above exercise is repeated for these systems the importance of
groundwater discharges becomes immediately apparent (see Table No. 2).
Table No. 2: Water balance calculations for the Kinvarra Catchment & Hydrometric Area No. 29
Catchment
Name
Area
(km2)
AAR
(mm)
PET
(mm)
ER
(mm)
Calculated
Discharge
(m3/s)
Measured
Discharge
(m3/s)
Kinvarra
1,000
1320
450
870
28
0
Hydrometric
Area 29
900
1320
450
870
25
6
Surface water discharges in the Kinvarra catchment are negligible, so on average 28m3/s discharges to
Galway Bay from this catchment through groundwater. In Hydrometric Area No. 29, approximately
three quarters of the discharge to the sea is in the form of groundwater.
3.1 Study Data
Staff and students of the Department of Earth & Ocean Sciences (EOS) have been measuring
discharges and nutrient inputs in the Kinvarra area since 2004 (Cave et al, 2005). In the immediate
vicinity of Kinvarra groundwater discharges to the sea are of the order of 8m3/s. A number of other
discharges have been identified along the north coast but it is estimated that 50 percent of the potential
discharge is as yet unaccounted for. It is likely that this discharge is entering the sea further out in the
bay in the form of Submarine Groundwater Discharge (SGD).
3.2 Water Quality & Nutrient Loads
One of the most striking things about the Kinvarra catchment is the nutrient loading as a function of
discharge.
49
SOLAS – Ireland
Proceedings
2006
Table No. 3: Nutrient loading in River Corrib and in Kinvarra groundwater
River Corrib
July 05
Dunguaire
Castle
July 05
River Corrib
Nov 01
Kinvarra Bay
Nov 06
Discharge
(m3/s)
90
3
115
6
NO2 + NO3
(tonnes/d)
4.0
0.3
4.4
2.3
Measured discharges at Dunguaire Castle and in Kinvarra Bay show nutrient loading of 0.3 and 2.3
tonnes/day; while discharges from the Corrib are one or two orders of magnitude greater the nutrient
loading is comparable. The nutrient loading from the Corrib may be affected by Lough Corrib (acting
as a sink) but it is apparent that nutrient loading through groundwater is significant along the south side
of the bay.
4 Conclusions
Groundwater discharges make up a significant portion of freshwater discharges to the coastal zone
along the south side of Galway Bay and along the west coast of Clare. These discharges are not
monitored (either quantitatively or qualitatively) and only indirect determination of discharge volumes
has been completed to date.
In the context of the Water Framework Directive the nutrient loading presents significant management
problems. Under the terms of the WFD all Irish waters (surface, ground and coastal) are to be of good
qualitative and quantitative status by 2015, and must be maintained as such into the future. The
groundwater discharges along the south side of Galway Bay are adding significant nutrient loads to
coastal waters and mitigating their entry to the groundwater system (and therefore the coastal zone)
will be hugely problematic, given the geological and hydrogeological regime in the region.
Much work has been completed in the United States, the western Mediterranean, Australia and Japan
on the impact and importance of Submarine Groundwater Discharges; no such studies have been
completed in Ireland to date.
Given the data collected to date as part of this ongoing study it would appear that groundwater may be
a significant source of nutrients to certain Irish coastal waters.
5 Recommendations
The work of the Department of Earth & Ocean Sciences in this area continues and will cover:
•
•
•
•
•
•
•
Field mapping of inter-tidal groundwater discharge sites throughout Galway Bay
Flow measurements at selected sites
Sampling for nutrients
GIS database of results
Future proposals
Irish coastline survey for groundwater discharge
SGD investigations in Galway bay
50
SOLAS – Ireland
Proceedings
2006
References
Bayari, C.S. & Kurttas, T., (2002). Coastal and submarine karstic discharges in the Gokova Bay, SW
Turkey. Quarterly Journal of Engineering Geology and Hydrogeology 35, 381-390.
Beddows, P. (2004), Hydrology, microbiology and geochemistry of a density stratified conduit flow
carbonate aquifer: Caribbean Coast, Yucatan Peninsula, Mexico. PhD Thesis, Bristol University
School of Geographical Sciences
Burnett, W.C., Bokuniewicz, H., Huettel, M., Moore, W.S., Taniguchi, M.,(2003). Groundwater and
pore water inputs to the coastal zone. Biogeochemistry 66, 3-33.
Capone, D.G., Bautista, M.F., (1985). A Groundwater Source of Nitrate in Nearshore MarineSediments. Nature 313, 214-216.
Cave, R.R., Henry, T. and O’Connor. T. (2005). The impact of groundwater on Irish coastal waters – a
preliminary study. Environ ’05 Conference, 28th-30th Jan 2005, IT Sligo
Department of the Environment & Local Government. (1999). Groundwater Protection Schemes.
Department of the Environment & Local Government, Dublin.
Drew, D. (2001). Classic Landforms of the Burren Karst. The British Geomorphological Research
Group.
Drew, D.P. & Daly, D.,(1993). Groundwater and karstification in mid-Galway, south Mayo and north
Clare. Geological Survey of Ireland. GSI report series RS93\3. Dublin.
Giblin, A.E., Gaines, A.G., (1990). Nitrogen Inputs to a Marine Embayment - the Importance of
Groundwater. Biogeochemistry 10, 309-328.
Gobler, C.J., Sanudo-Wilhelmy, S.A., (2001). Temporal variability of groundwater seepage and brown
tide blooms in a Long Island embayment. Marine Ecology-Progress Series 217, 299-309
O’Donovan, J., & Southern Global Water, (1997). An Investigation of the Flooding Problems in the
Gort-Ardrahan Area of South Galway, Final Report, Volumes 1-3. For the OPW, Dublin.
Johannes, R.E., (1980). The Ecological Significance of the Submarine Discharge of Groundwater.
Marine Ecology-Progress Series 3, 365-373.
Marin, L.E. & Perry, E.C. (1994), The hydrogeology and contamination potential of northwestern
Yucatan, Mexico. Geofisica Internacional, 33(4), 619-23
Moore, W.S., (1996). The subterranean estuary: A reaction zone of groundwater and sea water. Marine
Chemistry 65(1-2), pp.111-125.
Pracht, M., Lees, A., Leake, B., Feely, M., Long, B., Morris, J. & McConnell, B.(2004). Geology of
Galway Bay: A Geological Description to accompany the Bedrock Geology 1:100000 Scale Map
Series, Sheet 14, Galway Bay. Geological Survey of Ireland, Dublin.
Saltrans, (2003). Methods For Assessing Salt Intrusion and Transport In Heterogeneous And Fractured
Aquifers, Fifth Framework Programme. http://www.weizmann.ac.il/ESER/Saltrans/
Slomp, C.P & Cappellen.,(2004). Nutrient inputs to the coastal ocean through submarine groundwater
discharge: controls and potential impact. Journal of Hydrology 295 pp. 64-86.
Smyth, T.,(1998). A case study in the Gort- Ardrahan area of south Galway: A summary and
introduction in Floodaware Final Report. EU Commission, Directorate General XII. Office of
Public Works, Dublin.
Valiela, I., Costa, J., Foreman, K., Teal, J.M., Howes, B., Aubrey, D.,(1990). Transport of
Groundwater-Borne Nutrients from Watersheds and Their Effects on Coastal Waters.
Biogeochemistry 10, 177-197.
UNESCO,(2004). Submarine groundwater discharge: management implications, measurements and
effects. UNESCO. Report no. IHP-6 Series on Groundwater no 5/IOC Manuals and Guides no. 44.
Paris, 35 pp.
51
SOLAS – Ireland
Proceedings
2006
Coastal CO2 eddy-covariance measurements
Colin D. O’Dowd and Philip McVeigh
Centre for Climate & Air Pollution Studies, Environmental Change Institute, and School of Physics, National University of
Ireland, Galway, Ireland.
Abstract. Oceanic micrometeorological and CO2 fluxes from a coastal station (Mace Head) have been
derived using an eddy-covariance technique. While the data are in a stage of first-look analysis, it can
be concluded that CO2 fluxes are found to increase with wind speed and reach a maximum of -0.0050.035 micromoles m-2 s-1. The magnitude of the coastal flux is significantly lager that that reported for
open ocean conditions
1 Introduction
It is estimated that about half of the anthropogenic CO2 emitted to the atmosphere since the industrial
revolution has been absorbed by the oceans (Sabine et al., 2004). This has the beneficial effect of
regulating atmospheric levels of the greenhouse gas. However, this can impact biogeochemical cycling
and there are many feedback mechanisms which may reduce ocean CO2 uptake, for example due to the
reduced buffering capacity due to decreasing alkalinity. It is essential to fully elucidate the processes
governing oceanic CO2 flux. In recent years there has been increasing concern that the change in
seawater CO2 concentration in the world’s oceans could well have major and long lasting
consequences, particularly due to the predictable reduction in the alkalinity of seawater (ocean
acidification), (The Royal Society, 2005, OSPAR, 2006). Only in recent years did direct ship-borne
eddy-covariance flux techniques to measure CO2 flux is deployed (McGillis et al., 2007) with
promising results. In this study we present first results from coastal water CO2 fluxes using a similar
technique.
2 Experimental
The flux package was deployed on the Mace Head 22 m tower and comprised the following
components: Gill, Omnidirectional R3 Ultrasonic Anemometer, TSI, 3762 Condensation Particle
Counter (CPC), Li-COR, LI 7500 open path H2O/C2O gas analyser, Young anemometer, Data Logging
system (Figure 1).
52
SOLAS – Ireland
Proceedings
2006
Figure 1a. Flux package components.
Figure 1b. Close-up of sonic and Licor on extended boom from tower.
53
SOLAS – Ireland
Proceedings
2006
3 Eddy Covariance Theory
The characteristic spectral gap in boundary layer motions separates slowly changing large-scale
motions from the rapid fluctuations caused by micro scale turbulence. Turbulent fluctuations of a
meteorological variable can be decomposed into a mean and fluctuating part, known as the Reynolds
decomposition, and can be used to quantify turbulence. For example, the macroscopic wind speed, U,
can be separated into its mean and fluctuating part, as well as its three orthogonal components, u, v and
w, e.g.:
The over bar denotes an average, and the prime denotes a fluctuation. The variance of U is then got by
multiplying averaging the product of its prime over a chosen time interval.
The covariance of two variables is obtained in a similar way:
This means that we can find fluxes from covariances. Specifically, we find vertical turbulent fluxes
from the covariances of w’ with the variable of interest. The eddy covariance technique assumes that
there are no horizontal concentration gradients, and that a scalar species comprises a mean and
fluctuating component. It also assumes that there are no low frequency trends in the data, nevertheless,
this is rarely the case, so the data must be detrended, and departures from a short term mean can then be
used. A running mean will accomplish this task. For this work, a running mean of 30mins was selected.
The running mean simply involves taking an ensemble of all the points either side of every point and
finding their average.
Variances and covariances are calculated from the running means. These variances and covariances are then averaged using
a fixed mean, and then co-ordinate rotation transforms are applied to them.
The equation above is used to rotate the covariances of a w and a scalar, c.
Where:
and
Separate equations are used to rotate the means and variances, as well as the covariances between two
of the wind components. Many other parameters can be derived from this combination of basic raw
data and subsequent calculations. A useful parameter is the Friction velocity, u*, which can be used for
open-water fetch quality control:
54
SOLAS – Ireland
Proceedings
2006
4 Results
Data were first screened for wind sector to ensure an open water fetch and secondly were screened for
friction velocity deviations as a function of wind speed. Invariably, from a coastal station, influenced
by tides, significant filtering of data is required and results in a reduced dataset. Figure 2 (a) illustrates
the relationship between u* and wind speed and, for the filtered data selection, demonstrates a
relationship typical for an open water fetch, thus suggesting the selected data were valid for oceanic
flux product derivation. For example, McGillis et al., (2001) found u* values of between 0.7 and 0.8
for wind speeds of 15 m s-1 over the open ocean, as did Geever et al., (2005) for Mace Head during
high tide conditions. For the selected high-tide and marine sector filtered data CO2 fluxed range from 0.0001 micromoles m-2 s-1 at wind speeds of 2-4 m s-1 to -0.005-0.035 micromoles m-2 s-1 at wind
speed of up to 16 m s-1. The flux values reported here demonstrate a net oceanic sink for CO2, as
observed over the open ocean, however, the magnitude of the coastal CO2 sink is significantly higher.
Figure 2. (Top) u* as a function of wind speed for filter open ocean data. (Bottom) CO2
flux as a function of wind speed for open ocean data.
55
SOLAS – Ireland
Proceedings
2006
5 Conclusions
This study has demonstrated, from a micrometeorological flux perspective that open water fluxes of
scaler parameters such as CO2 can be derived from a coastal site such as Mace Head. The derived CO2
fluxes are observed to increase with wind speeds and demonstrate a net oceanic sink for CO2. The
magnitude of the sink is significantly greater than that reported for open ocean sinks.
References
Geever, M., O'Dowd, C.D., van Ekeren, S., Flanagan, R., Nilsson, D. E., de Leeuw, G., Rannik, Ü.
(2005), Sub-Micron Sea-Spray Fluxes, Geophys. Res. Letts., doi:10.1029/2005GL023081,.
McGillis, W. R., Edson, J. B., Hare, J. E. and Fairall, C. W. (2001a), Direct covariance air-sea CO2
fluxes, J. Geophys. Res., 106, 16,729– 16,745.
OSPAR (2006). Effects on the Marine Environment of Ocean Acidification resulting from elevated
levels of CO2 in the atmosphere. Biodiversity Series. ISBN 1-905859-23-6. OSPAR Commission
London.
Sabine C. L. et al. (2004). The oceanic sink for anthropogenic CO2. Science 305, 367 – 371.
56
SOLAS – Ireland
Proceedings
2006
Coastal Biogenic Aerosol Flux - BIOFLUX
Colin O’Dowd, Karine Selligri, Young Jun Yoon
School of Physics & Centre for Climate & Air Pollution Studies, Environmental Change Institute, National University of
Ireland, Galway, Ireland
Abstract. Experiments on coastal new particle formation have been conducted at Mace Head and
nearby hotspots in order to elucidate the role of molecular iodine in the formation of new particles and
the associated fluxes of these aerosol particles. Molecular iodine concentrations were taken in air
samples during nucleation events and during algae chamber experiments under pseudo-natural
conditions. Concentrations of the order of 35-125 ppt were found during atmospheric particle
production events and up to 800 ppt in controlled chamber events. In the chamber experiments, I2
concentrations were strongly correlated to algae biomass, although saturating at the highest
concentrations. In addition, a linear correlation was found between I2 concentrations and particle
production rate. For a algae coverage range of 1-5 kg m2 biomass, it was calculated that the production
of new particles, in the 3-3.5 nm range, was between 1 x 1010 and 5 x 1010 particles m-2 s-1. A coastal
emission inventory for the Mace Head / MRI Carna region was derived and input into the RAMS
chemical transport model to evaluation horizontal and vertical dispersion of the coastal aerosol plume.
Significant particle concentrations were predicted for 10 km inland and being vertically-mixed up to a
height of 600 m.
1 Introduction
New particle formation events have been studied previously at Mace Head and during these events,
where the background aerosol concentration can increase from 500 cm-3 to more than 1,000,000 cm-3,
iodine oxides have been implicated as the main source of the condensable material (O’Dowd et al.,
2002a,b). The precursor of IO has been an open question as initial studies suggested the source was
CH2I2 (O’Dowd et al., 2002b Hoffmann et al., 2001) although this organo-halogen may not be able to
provide sufficient material at a high enough rate to account for the production rate. As a result,
molecular iodine (I2) has been suggested as an alternative source of IO in the coastal environment. A
series of experiments were designed to measure the concentration of both new particles and I2 at Mace
Head, nearby hotspots (near MRI-Carna) and in chamber experiments in order to explore its role in
particle production.
2 Experimental I2 concentrations were
determined over 30 minute periods using
a starch denuder technique. Aerosol
concentrations were determined using a
Scanning Mobility Particle Sizer
covering sized from 3.5 nm – 50 nm.
Ambient samples were taken at Mace
Head and in a mobile lab at hotspots
nearby (i.e. close to the MRI-Carna
labs).
Chamber experiments were
undertaken in a 2 m3 perspex flowthrough chamber which allowed 50%
Figure 1. Flow-through chamber for chamber experiments at
Mace Head
57
SOLAS – Ireland
Proceedings
2006
ozone was not removed thus allowing a natural source of ozone for oxidation. The experiments were
conduced on local algae such as Laminarie and Fucus. The algae chamber is illustrated in Figure 1.
3 Results
The first set of experiments were conducted with no flow through the chamber and under these
conditions, nucleation pulses, flowed by rapid aerosol growth were seen (Figure 2.). Large increases in
particle concentration are initially seen at 3 nm sizes and the peak in concentration grows rapidly to 2030 nm via condensation growth. The initial burst increases aerosol surface area (vapour condensation
sink), reducing the gas-phase concentration, and thus inhibiting nucleation of further new particles.
After rapid growth, the condensation sink eventually reduces due to particle deposition processes and a
subsequent nucleation pulse results.
Figure 2. 2-D contour plot of aerosol concentration and growth under conditions of no throughput flow
in chamber.
The second phase of the chamber experiments centred around pseudo-steady-state conditions where the
aerosol size distribution did not evolve with time. These experiments were repeated for four different
levels of biomass (5 kg, 9 kg, 16 kg and 25 kg algae mass per square meter) with a resultant aerosol
concentration of up to 107 cm-3 for these scenarios. The I2 concentrations were found to range from
130 to 380 ppt depending on the biomass concentration. At higher concentrations of biomass, the I2
concentration seemed to top out (Figure 3a). However, a clear linear relationship was found between
particle concentration and molecular iodine concentration as shown in Figure 3b.
58
SOLAS – Ireland
Proceedings
2006
For a range of 1-5 kg m2 biomass, it was calculated that the production of new particles, in the 3-3.5
nm range, was between 1 x 1010 and 5 x 1010 particles m-2 s-1. The corresponding estimated iodine flux
in the chamber was of the order of 0.5-1.5 x 109 cm-3 s-1. In terms of particle production per unit of
molecular iodine, the production rate corresponded to 2800 particles cm-3 ppt-1.
Figure 3 (a) I2 concentrations as a function (b) Particle concentration as a function of I2
of sea weed biomass.
concentration.
Figure 4. Range of I2 concentrations observed at MRI Carna, bridge nearby MRI Carna
and in the chamber.
Figure 4 highlights the range of I2 concentrations encountered at MRI Carna, the more exposed bridge
about 1 km from MRI Carna, and in the chamber. Concentrations at MRI Carna were of the order of
35 ppt while at the nearby bridge hotsport, they were 121-125 ppt. By comparison, the chamber
concentration ranged from 519-846 ppt.
The meso-scale atmospheric chemical transport model RAMS was used to simulate particle
concentrations resulting from new particle emissions in the tidal regions upwind. Boundary conditions
were taken from the ECMWF reanalysis database. RAMS can operate at a resolution from 1 km to
59
SOLAS – Ireland
Proceedings
2006
1000 km and includes nested grids. For this study, simulations are preformed for three nested grids
simultaneously to take account of the synoptic and local meteorological circulations. Grid 1 covers the
region with a horizontal resolution of 15 km2, Grid 2 covers an intermediate domain of 5 km2, while
Grid 3 consists of a 1 km2 domain. A time step of 10 s and 35 vertical levels, 15 in the lower 1500 m
was used. An emission inventory for particle emissions was developed based on the chamber derived
fluxes as a function of seaweed biomass and applied to the calculated percentage seaweed biomass
derived from tidal maps and visual observations of mass loadings.
Figure 5 illustrates the spatial distribution of particle concentration fields in the Mace Head
(coordinates 0,2) and MRI Carna (coordinates 4, -2) region. Peak concentrations are seen at MRI
Carna with concentrations approaching 350,000 cm-3. These concentrations are in excellent agreement
with the observed concentrations. The results, as evident from the concentration distribution maps,
indicate significant horizontal dispersion of the coastal aerosol plumes. The Section A and Section B
lines in Figure 5 mark regions where vertical distributions are extracted from the model simulations
and shown in Figure 6. In both sections, significant vertical distribution of coastal new particles is seen
up to 600 m which corresponds to the typical boundary/surface layer observed in the region (Kunz et
al., 2002). The coastal aerosol plume reaches 300 m after 4 km and 600 m after 10 km.
Figure 5. Surface level distribution of particle concentration around Mace Head and
MRI Carna. Section A and B mark regions for extraction of vertical distributions in
Figure 6.
60
SOLAS – Ireland
Proceedings
2006
Figure 6. Vertical distributions of particle concentration around Mace Head and MRI
Carna as marked along Section B and A, respectively, in Figure 5.
4 Conclusions
Chamber studies were used to elucidate the emissions of I2 and new particles from coastal macro-algae.
In addition, the inter-relationship between I2 and biomass, and new particles and I2 was investigated. I2
concentrations were positively correlated with algae biomass, although at high concentrations, I2
concentrations seemed to saturate. Strikingly, a linear relationship between particle concentration and
I2 was observed. For a range of 1-5 kg m2 biomass, it was calculated that the production of new
particles, in the 3-3.5 nm range, was between 1 x 1010 and 5 x 1010 particles m-2 s-1. Peak I2
concentrations under atmospheric conditions were of the order of 125 ppt while chamber conditions led
to peak concentrations of > 800 ppt I2. Emission inventories of new particles as a function of coastal
biomass were derived and input to a chemical transport model to examine the spatial distribution of the
coastal aerosol plumes. The coastal aerosol plume becomes vertically mixed to 600 m after 10 km
horizontal advection.
References
Kunz, G., de Leeuw, G., Becker, E. and O’Dowd, C.D. (2002), Lidar observations of atmospheric
boundary layer structure and sea spray aerosol plumes generation and transport at Mace Head,
Ireland (PARFORCE experiment). J. Geophys. Res., 107, 10.1029/2001JD001240.
O’Dowd, C.D., K. Hämeri, J.M. Mäkelä, L. Pirjola, M. Kulmala, S.G. Jennings, H. Berresheim, H.-C.
Hansson, G. de Leeuw, A. G. Allen, C. N. Hewitt, A. Jackson, Y. Viisanen, T. Hoffmann (2002).
A dedicated study of new particle formation and fate in the coastal environment (PARFORCE):
Overview of objectives and initial achievements. J. Geophys. Res., 107, 10.1029/2001000555.
O’Dowd, C.D., Jimenez, J.L., Bahreini R., Flagan, R.C. Seinfeld, J.H., Pirjola, L., Kulmala, M.,
Jennings, S.G. and Hoffmann, T. (2002). Marine particle formation from biogenic iodine
emissions, Nature, 417, 632-636.
61
SOLAS – Ireland
Proceedings
2006
Seaweed, Iodine and Health
Peter Smyth
UCD Conway Institute of Biomolecular and Biomedical Research
University College Dublin
1 Introduction
Iodine forms one of the most important mineral constituents of seaweeds. The iodine content and its
chemical form varies with different species but is generally greater in brown seaweeds (kelps) than the
green or red varieties (Morrissey et al 2001).
Seaweeds form an important part of daily diet in many Asian countries such as Japan, Korea and
coastal parts of China. Various seaweed species are widely used in sushi, soups, salads and in
powdered form as condiments. Japan is the world’s largest seaweed market and is highly regulated
with seaweeds divided into 21 categories (www.seaweed.ie). Apart from being treasured as a food
supplement, many health benefits have been attributed to seaweed consumption and Japan even has a
“National Seaweed Day” (Feb 6) (Watts 2004). The increasing spread of ethnic restaurants and
interest in natural foods has also lead to an upsurge in seaweed/sea vegetable consumption in the West.
Many curative properties have been attributed to iodine particularly its possible involvement in redox
reactions; as an antioxidant or antiseptic agent and in circulatory illness (Winkler and Kliber 1998,
Smyth 2004). Despite many centuries of seaweed use as both foodstuffs and medicines (in modern
parlance “nutriceuticals”), little is known of the mechanism through which seaweed consumption might
exert its effect on mammalian cell function or growth. An exception is the case of seaweeds as a
source of iodine nutrition in iodine deficiency and associated disorders of the thyroid gland (WHO
2004). In recent times there has been much speculation on a role for seaweed consumption in
protecting against the onset of breast cancer (Smyth 1997, Cann et al 2001, Funahashi et al 2001,
Smyth 2003, Aceves et al 2005, Garcia Solis et al 2005 ). This has arisen from epidemiological data
showing that the incidence of breast cancer is much lower in countries where seaweed consumption is
highest. Incidence rates in Korea were 8.6/100000 females, in Japan 10.9; 21.2 USA; 26.0 UK but 27.5
Ireland (Parkin et al 2002). Whether this relationship reflects the iodine content of seaweeds or some
other factor is not clear but both iodine and seaweed extracts have been shown to inhibit carcinogen
induced breast tumour growth in experimental animals (Funahashi et al 2001).
The ability of stable (nonradioactive) iodine to block uptake of radioactive iodine by the thyroid gland
and thus offer protection following a nuclear accident is well established and forms the theoretical
background for the distribution of the much discussed nationwide distribution of iodine tablets.
Although ingestion of radioactive iodine can have harmful effects it is also used as a therapeutic
ablative agent in the treatment of thyroid cancer and hyperthyroidism (overactive thyroid gland). The
effectiveness of this form of therapy depends on the ability of the tumour tissue to both accumulate and
retain therapeutically administered radioactive iodine. This catatonic effect of iodine may not be
confined to its radioactive form as larger doses of nonradioactive iodine can prevent proliferation of
both thyroid and other cells and suggest a wider role for iodine as a therapeutic agent (Smyth et al
2003, 2004, Garcia Solis et al 2005). This communication outlines some experience in measuring
seaweed iodine content and the ability of seaweeds to take up and retain radioactive iodine 125I in vitro.
In addition, the possible contribution to human iodine intake of gaseous iodine released by seaweeds is
discussed.
62
SOLAS – Ireland
Proceedings
2006
2 Materials and Methods
Seaweeds Samples of 10 seaweed species (Chandra’s crisps, Palm aria palmate, Porphyry, Ulna
lactic, Heteromorphy intestinal is, Laminar digitise, Laminar sac carina, Laminar hyperborean,
Malaria esculent and Himanthalia elongata) were collected off the Spiddal coast, Co Galway every
three months to cover all seasons. When ultra fresh samples were required collections were also made
from Dublin Bay (Forty Foot, Sandycove, Co Dublin). Fresh seaweed was dried at 50ºC for 48 hours,
after which it was stored in airtight containers at room temperature.
Iodine Analysis Total iodine in seaweeds was measured by dry alkaline ashing. This involves
preliminary drying of samples and standards at 150˚C followed by incineration for 3 hours at 600˚C in
the presence of 1ml strong alkali (KOH). The ash was reconstituted in 5 ml distilled water. Potassium
iodate (KIO3) was used to generate a standard curve in the range 0 – 120 ng I. The iodide content was
measured colorimetrically at 420nm using the Sandell-Kolthoff reaction.
Isolation of protoplasts The seaweed plant is surrounded by an external cuticle and internal cell
walls. In order to clarify whether uptake of iodide is a cell wall-mediated process, whether the iodine
present is only in the cell wall or if it is transported across the cell membrane into the cytoplasm and
possibly the vacuole, an enzyme- mediated protoplast generating protocol was established for L.
digitata using a cellulase-alginate lyase mixture. Purification of these protoplasts allowed viability to
be assessed and permitted investigation of radioiodide efflux in the absence of a cell wall. This
facilitated verification of the intracellular localisation of 125I accumulated iodide and iodo-compounds
125
I Uptake and Efflux Studies 125I uptake – tissue/protoplasts incubated at room temperature in
seawater spiked with 10,000cpm 125I. CPM of supernatant measured.
125
I efflux – radioactive seaweed tissue/protoplasts transferred to fresh seawater and CPM of
supernatant measured after fixed time points
Seaweed
I-
Seawater I -
Iodine
Thyroid
IBlood I -
•Thyroid gland takes up iodide
•Seaweed takes up iodide/iodine
Accumulates it against a concentration
•Accumulates it against a concentration gradient •gradient
6
•Can accumulate iodines up to 10 • Concentrated to 20-40 times that
times that in seawater
•Role of iodines in seaweed uncertain
of the bloodstream
•Organifies iodide to iodine
•Leads to formation of thyroid hormones
Fig 1 The ability to transport iodine defines the relationship between seaweeds and the mammalian thyroid
63
SOLAS – Ireland
Proceedings
2006
3 Results
The common ability of both the mammalian thyroid and seaweed plants to accumulate and retain
iodine forms the basis for the work presented in this communication. Figure 1 shows a comparison
between the abilities of seaweeds and the human thyroid to accumulate iodide from
seawater/bloodstream. The main difference is that seaweed has much greater ability to accumulate
iodide from its surrounding fluid than does the thyroid (up to 106 in some species. While the main
function of iodide in the thyroid is to provide a source of iodine for the formation of thyroid hormones,
its role in seaweed is much less certain as is its chemical composition within the plant ( Hou et al 1997
; Kupper et al 1998 ; Shah et al 2005). Similarly the bioavailability of iodine stored in seaweeds is not
fully understood (Hou et al 1997; Aquaron et al 2002).
Species
Chondrus crispus
Palmaria palmata
Porphyra umbilicalis
Enteromorpha intestinalis
Ulva lactuca
Alaria esculenta
Himanthalia elongata
Laminaria digitata
Laminaria hyperborea
Laminaria saccharina
Autumn/ Winter Spring/ Summer
251
282
88
69
N/A
44
325
144
N/A
150
308
150
7470
6343
5714
N/A
188
5120
5106
5260
Table 1 shows the median iodine content (ppm) of the three different classes of seaweed and when
available their seasonal variation. It can be seen that the iodine content of the brown seaweeds was in
general greater than that of green or red with higher values observed in the summer months.
Fig 2 Uptake (A) and Efflux (B) of 125I by different seaweed species.
64
SOLAS – Ireland
Proceedings
2006
Figure 2 shows the effect of incubating samples of different seaweeds with radioactive 125I for varying
times and measuring both uptake and efflux of radioactivity. In Fig 2A It can be seen that uptake of
125
I increased with time. Highest uptakes were observed with Chondrus Crispus (plateau at 60 mins)
while others continued to rise with time. Because of its ready availability and relatively high uptake the
seaweed Laminaria Digitata was selected for future experiments.
Efflux of accumulated 125I at varying times from different seaweed species is shown in Fig 2 B. It can
be seen that efflux from the various seaweeds is much slower than that from the thyroid cell line. In
fact less than 10% of accumulated 125I was lost at 60 minutes and in most cases at 120 minutes. Thus
approximately 90% of accumulated 125I was retained by the plant at these times.
Localisation of 125I in seaweed plants.
As shown Fig 3 A and B both uptake and retention of 125I was shown in the protoplasts demonstrating
that iodide enters the cell and is not just bound to the cell wall.
Fig 3. Uptake (A) and Efflux (B) of 125I in whole seaweed (L. digitata) and isolated protoplasts
Iodide Uptake through Respiration
Since iodovolatilisation can account for a higher iodine content in the air over seaweed rich areas
(Pirjola et al 2005; Sellegri et al 2005), a rough calculation was made bases on the figures of this group
to determine if volatile iodine released from seaweeds could exert a significant influence on iodine
intake in humans or animals. Table 2 shows approximations of various respiratory indices
demonstrating that respiration in an adult could vary from a resting level of 6L per minute to an
exercise level of 50L /minute. Correspondingly air samples taken at coastal areas where seaweed mass
was low, at “hot spots” where it was high or in an enclosed seaweed containing chamber. Assuming
that I2 was absorbed quantitatively as suggested by Morgan et al 1968, respiration could account for
an increment in daily iodine intake from as low as 1.5 μg/day in a resting subject (6L/min) at low
atmospheric iodine content to 13.0 μg/hr at exercise (50L/min) at the highest atmospheric iodine
content. Higher intakes would arise following vigorous exercise with correspondingly increased
respiration. These are arbitrary figures, subject to many variables, and require experimental
confirmation.
65
SOLAS – Ireland
Proceedings
Lung Capacity
Resting
6L/min
Exercise
50L/min
2006
Examples of different iodine emissions from seaweeds
μg/24 hrs
Low iodine
Hot Spots
Seaweed Chamber
Iodine ingestion
Resting 24 hrs
1.5
5.3
37.0
Exercise (1.0 hr)
0.54
1.80
13.0
Table 2 Estimate of iodine intakes arising from gaseous I2 emitted from seaweeds from different
seashores and from an experimental seaweed chamber (Sellegri et al 2005; Pirjola et al 2005).
4 Discussion
The daily intake of iodine for adults recommended by the World Health organisation (WHO) is 150 μg
(WHO 2004). This intake can be readily achieved by consuming marine products but unfortunately
due to cost, lack of availability or dietary preference this source is not always availed of. In many
countries adequate dietary iodine intake is provided by iodisation of table salt and indeed the WHO
recommends a policy of universal salt iodisation to achieve this goal. In the case of Ireland, only
approximately 4% of table salt is iodised with the result that dietary iodine intake is almost entirely
opportunistic exposing a large part of the population to the dangers of iodine deficiency, in particular
infants born to iodine deficient mothers (Smyth et al 2006).It is generally believed that iodine
deficiency is less prevalent in populations living near the sea and this was thought to be a major reason
why South Tipperary had a high goitre rate (O’Donovan 1950). However this is not a universal
finding as iodine deficiency has been frequently reported in coastal communities. On the basis of
published values for marine aerosol iodine as extrapolated in this communication into daily iodine
intakes, the contribution of respired air to dietary intake is probably not significant. However earlier
reports on the high biological availability of inspired iodine vapour (Morgan et al 1968) this pathway
requires further investigation.
The study of iodine in seaweeds, its uptake into, formulation within and efflux from the plants has
provided an exciting model for the study of mammalian tissue interactions with iodine and of
improving its usefulness as a therapeutic agent. Recent demonstrations of atmospheric particle
formation induced by iodine emanating from seaweeds offer the possibility of extending this work to
studying the effects of gaseous iodine ingestion through respiration.
Acknowledgements
George Cloughley, Emma Burbridge, UCD Conway Institute, M D Guiry, Stefan Kraan, Martin Ryan
Institute, NUI (G), Germain Levielle, UCD School of Biological and Environmental Science.
Supported by Marine Institute Postdoctoral Fellowship Ref No: PDOC/01/005 Title: Iodine in
Commercially used Irish seaweeds.
References
Morrissey, J., Kraan, S. and Guiry, M.D. (2001). A guide to commercially important seaweeds on the
Irish Coast. Bord Iascaigh Mhara, Dublin.
Watts,
J.
(2001).
Seaweed
dries
up
in
Japan
The
Guardian
Feb
8th
www.guardian.co.uk/print/0,3858,4133519,00.html
66
SOLAS – Ireland
Proceedings
2006
Winkler, R and Klieber, M. (1998). Important results of about 45 years balneo-medical research in Bad
Hall. Wien MedWorchenschrSupp 148 3-11.
Smyth, P.P.(2003). Role of iodine in antioxidant defence in thyroid and breast disease. Biofactors
19(3-4):121-30
Cann, S.A, van Netten, J.P., and van Netten, C. (2000). Hypothesis: iodine, selenium and the
development of breast cancer. Cancer Causes Control. 11:121-7.
Funahashi H, Imai T, Mase T, Sekiya M, Yokoi K, Hayashi H, Shibata A, Hayashi T, Nishikawa M,
Suda N, Hibi Y, Mizuno Y, Tsukamura K, Hayakawa A, and Tanuma, S. (2001). Seaweed prevents
breast cancer? Jpn J Cancer Res. 5:483-7.
Smyth, P.P.( 2003). The thyroid, iodine and breast cancer. Breast Cancer Res.;5(5):235-8
Aceves, C., Anguiano, B. and Delgado, G. (2005). Is iodine a gatekeeper of the integrity of the
mammary gland? J Mammary Gland Biol Neoplasia. Apr;10(2):189-96
Garcia-Solis P, Alfaro Y, Anguiano B, Delgado G, Guzman R.C, Nandi S, Diaz-Munoz M, VazquezMartinez O and Aceves C (2005). Inhibition of N-methyl-N-nitrosourea-induced mammary
carcinogenesis by molecular iodine (I2) but not by iodide (I-) treatment Evidence that I2 prevents
cancer promotion.Mol Cell Endocrinol. 236:49-57.
Parkin D.M, Bray F, Ferlay J and Pisani P. Global Cancer Statistics 2002 CA Cancer J Clin. 2005
55:74-108.
Hou, X, Yan, X, and Chai, C. (2000). Chemical Species of iodine in some stefan.kraan@nuigalway.ie
seaweeds II. Iodine-bound biological macromolecules. J. Radioanal. Nucl.Chem., 245(3), 461-467
Kupper FC, Schweigert N,et al.Iodine Uptake In Laminarials Involves Extracellular,HaloperoxidaseMediated Oxidation of Iodide. Planta(1998) 207:163-171
Shah M, Wuilloud R.G, Kannamkumarath S.S, Caruso J.A. (2005). Iodine speciation studies in
commercially available seaweed by coupling different chromatographic techniques with UV and
ICP-MS detectioin. J Anal At Spectrom 20: 176-182.
Aquaron R, Delange F, Marchal P, Lognone V, and Ninane L. (2002) . Bioavailability Of Seaweed
Iodine In Human Beings.Cell Mol Biol (Noisy-Le-Grand). 48:563-9.
Sellegri, K., Yoon Y. J., Jennings S.G., O’Dowd C.D., Pirjola L., Cautenet S., Chen H.and Hoffmann
T., (2005). Quantification of Coastal New Ultra-Fine Particles Formation from In situ and Chamber
Measurements during the BIOFLUX Campaign. Environ. Chem. 2, 260. doi:10.1071/EN05074
Pirjola, L., O’Dowd C., Yoon Y.J.and Sellegri K. (2005). Modelling Iodine Particle Formation and
Growth from Seaweed in a Chamber. Environ. Chem. 2, 271. doi:10.1071/EN05075
Morgan A, Morgan DJ, Black A (1968). A study of the deposition , translocation and excretion of
radioiodine inhaled as iodine vapour. Health Physics 15: 313-322.
WH0, 004. Iodine status worldwide.
WHO Global Database on iodine deficiency.
(http://whqlibdoc.who.int/publications/2004/9241592001.pdf) Geneva.
O’ Donovan D.K. (1950). The problem of endemic goitre in Ireland. Irish J Med Science 161-171.
Nawoor Z., Burns R, Smith D.F., Sheehan S., O’Herlihy C. and Smyth P.P.A. (2006). Iodine intake in
pregnancy in Ireland –A cause for concern? Irish J Med Science 175: 21-24.
67
SOLAS – Ireland
Proceedings
2006
The Irish Weather Buoy Network: Platforms for sustained ocean-atmosphere
measurements
Glenn Nolan
Marine Institute
1 Introduction
A network of 6 offshore weather buoys is maintained by the Oceanographic Services team at the Irish
Marine Institute at the locations shown in figure 1. The buoys were deployed in response to
recommendations from the Fishing Vessel Safety review (1996) outlining the need for offshore
platforms to enhance sea area weather forecasts. Some of the other drivers for marine observations
from these platforms include:
ƒ Weather forecasting/safety at sea
ƒ Water Framework Directive
ƒ Research (oceans and atmosphere)
ƒ Aquaculture: early warning
ƒ Baseline climatic conditions
Figure 1 Locations of the buoys within the Irish National Weather Buoy Network (FS1 is a gas
platform where observations are available periodically)
2 Recent developments
The most significant recent development in the buoy network was the deployment of a new deep water
buoy at the M6 location (west of Porcupine Bank). This presented a significant challenge to the
Oceanographic Services team in that the location is remote and the water depth is ca. 3000m. Expertise
68
SOLAS – Ireland
Proceedings
2006
had to be drawn from the Woods Hole Oceanographic Institution in the U.S. to design and build an
inverse catenary mooring for the M6 buoy that is similar in design to buoys deployed in the Gulf
Stream and in the Tropical Pacific Ocean.
The data acquisition systems currently on the weather buoys are somewhat outdated technology in that
only one-way communication is possible and the sensors the system can interrogate is limited. During
2006 and 2007 the acquisition systems will be upgraded to a modern system that has two-way
communications between the buoy and the shore and the ability to interrogate advanced sensors such as
directional wave sensors and solid state wind sensors. The new system will also be compatible with a
wide range of oceanographic instruments including CTDs and Doppler Current Profilers.
Figure 2 Cleaning and maintenance of the M1 weather buoy aboard the RV Celtic Explorer.
3 Future opportunities
As highlighted above there is scope to include additional sensors on the weather buoy platforms in the
coming years. This could include the gathering of offshore PCO2 data sets as an example.
Oceanographic Services are open to assisting with proposed deployments of other sensors from
researchers on the weather buoy network.
69
SOLAS – Ireland
Proceedings
2006
Observations of the effect of fetch on whitecap coverage in the Irish Sea
Adrian Callaghan and Martin White
Department of Earth and Ocean Sciences, National University of Ireland, Galway
1 Introduction
One of the most obvious features of any sea or ocean on a windy day is the large presence of whitecaps
on the sea surface. Breaking waves and the resulting whitecap coverage have a significant impact on a
number of oceanographic processes. The trapping of air and enhancement of interfacial area between
air and water as a result of the wave breaking greatly enhances air-sea fluxes of heat and gas.
Whitecapping is also responsible for the injection of seawater droplets into the air which is the primary
mechanism controlling the rate of sea-salt aerosol generation over the ocean (Stramska and Petelski,
2003). The high albedo of all stages of whitecap evolution introduces the need to include whitecap
reflectance in atmospheric corrections for the remote sensing of ocean colour from satellites.
Knowledge of the surface coverage of whitecaps gives a means to quantify these resulting effects of
breaking waves.
Whitecap coverage measurements have largely been made in the open ocean and the simplest
empirical parameterisations of whitecap coverage and wave breaking are in terms of wind speed alone
(Woolf, 2005). While it is generally considered that there exists an approximate cubic relationship
between wind speed and whitecap coverage (e.g. Monahan and O’Muircheartaigh, 1980) different
relationships have been reported. Zhao and Toba (2001) reported a relationship to the fourth power
between whitecap coverage and wind speed. Wind speed is the most readily studied factor controlling
the fraction of the sea surface covered by whitecaps but other factors such as fetch are also important.
The lack of inclusion of the effect of fetch, in whitecap coverage models may explain the differences in
reported relationships.
In this study, we investigate the effect of fetch on whitecap coverage. Fetch is the distance over
which the wind acts on the sea surface from the coastline in the direction of the wind. For a given wind
speed, variations in fetch can lead to the development of different wave fields. According to the
models of Zhao and Toba (2003) and Woolf (2005), at a given wind speed whitecap coverage increases
with increasing fetch. The geographical nature of the Irish Sea lends itself to a study of the effect of
fetch on whitecap coverage due to its rectangular shaped basin. Conditions of largest fetch occur when
the wind blows from the south-west or the north-east. Winds from the west or the east result in
conditions of much shorter fetch. Here we present measurements of whitecap coverage from ship
borne images that show whitecap coverage does increase with increasing fetch for a given wind speed,
supporting the hypotheses of Zhao and Toba (2003) and Woolf (2005).
2 Methods and Study Area
Sea surface images were collected using the Irish Ferries car ferry, “The Ulysses” in the
summer of 2004. The ferry made 2 daylight crossings each day between Dublin port situated on the
north side of Dublin Bay ( 53.35º N, 353.87º E ) and Holyhead port situated on the island of Holy to
the west of Anglesey ( 53.32º N, 355.27º E ), indicated by the black line in figure 1. The morning
crossing was from Dublin to Holyhead, with the return crossing in the afternoon. The Irish Sea is
70
SOLAS – Ireland
Proceedings
2006
approximately 102 kilometres wide at this point. The deepest point along this line is approximately
150 metres which occurs roughly halfway between Dublin port on the west and Holyhead port on the
east.
Two digital CCD cameras were mounted on the top deck of the ferry (approximately 32 metres
above the sea surface), one facing port and the other facing starboard. The cameras were connected to
a computer which controlled the data acquisition. The cameras collected video footage of the sea
surface at a rate of one frame per second which was later decomposed into individual frames. Video
acquisition was confined to three 15 minute periods and images were taken on both crossings. Each
continuous 15 minute period corresponded to a different geographical location in the Irish Sea. The
first and last periods were near the beginning and end of each crossing and will be referred to as the
Dublin and Holyhead stations respectively, and the middle period took place mid crossing and will be
referred to as the Middle station.
Whitecaps were detected and quantified in images using an automated threshold method
developed during this project. Video footage of the sea surface was separated into its constituent
frames, and each frame constituted one image. Each resultant image was changed from its original
RGB format to a greyscale format. In the greyscale format, each pixel in the image had a single value
ranging from 0 to 1 with 0 representing black and 1 representing white. All levels of grey are
represented by numbers between these two extremes. The image processing method identified a
suitable threshold for each image. All pixels above this threshold were considered whitecap pixels and
all other pixels were considered background water pixels. The whitecap pixels were counted and a
percentage value for each image was calculated. The automation of the process meant that large
numbers of images could be analysed in a short time and without the subjectivity of a human analyst.
Figure 1. Relief Map of the Irish Sea.
Black line showing ferry track.
71
SOLAS – Ireland
Proceedings
2006
3 Results
Percentage Whitecap Coverage
Results presented below are from the analysis of images which were taken in the Irish Sea in summer
2004. Wind speed during this period was low; values were less than 8 m/s for more than 75% of the
measurement period. Figure 2 shows percentage whitecap coverage (W) values for three sampling
stations on the morning Dublin to Holyhead crossings when the wind direction was only from the
southern quadrants.
Figure 2. Timeseries of W at 3 different stations along the morning Dublin to Holyhead crossing,
Summer 2004.
Values of W are generally largest at the station closest to Holyhead and smallest at the station
closest to Dublin. Wind for this period was largely from the south-west quadrant. With a south
westerly wind, fetch conditions are larger at the Holyhead station than at the Dublin station. However,
on the 10th June and the 20th July, values for W are greater on the western side relative to the eastern
side of the Irish Sea. On these days the wind direction had changed from south west to south east thus
changing conditions of greatest fetch from the Holyhead station to the Dublin station. In all cases wind
speed was steady and an increase in W during any one particular voyage cannot be attributed to an
increase in wind speed. Figure 3 shows a log-log relationship between W and wind speed which
resulted in the following empirical relationship:
W = 4.93 * 10 -6 (U10 3.90)
(1)
W = Percentage whitecap coverage.
U10 = Wind speed at 10 metres above the sea surface.
72
Proceedings
2006
Percentage Whitecap Coverage
SOLAS – Ireland
Wind Speed (m/s)
Figure 3. Relationship of W with wind speed, Irish Sea, summer 2004.
The exponent (3.90) of Eq.1 above agrees well with a relationship between W and wind speed
reported by Zhao and Toba (2001) :
W = 2.98 * 10-5 (U104.04)
(2)
However, the coefficient, 4.93 * 10 -6, of equation 1 is an order of magnitude less than that of
equation 2. While Lafon et al (2006) also report smaller values of W in coastal fetch limited regions
the values given by equation 1 are lower than expected. Possible causes for the low values reported
here are offered in the discussion section.
Figures 4 (a), (b) and (c) display observations of W, wind speed and wind direction at the
Dublin station, the middle station and the Holyhead station respectively. Wind speed is measured
radially from the origin. Wind speed in the north south direction is on the y axis and east west wind
speed is given on the x axis. Largest values of W are seen for south-westerly and north-easterly winds.
Both these directions also correspond to conditions of largest fetch for the Irish Sea. When the wind is
from the north east, W is larger at the Dublin station than at the Holyhead station, corresponding to
larger fetch conditions at the Dublin station. W values are larger at the Holyhead station than at the
Dublin station for winds from the south west, corresponding to larger fetch conditions at the Holyhead
station. Figures 4 (d), (e) and (f) display the modelled W for each of these stations for the measured
wind speed as given by equation 2. As expected the wind speed only model does not reflect the effect
differences in fetch have on W.
73
Proceedings
2006
Wind Speed (m/s)
SOLAS – Ireland
(d)
(b)
(e)
(c)
(f)
Wind Speed (m/s)
Wind Speed (m/s)
(a)
Figure 4. (a) - (c) show whitecap coverage as a function of wind speed and wind direction at
the three sampling points between Dublin and Holyhead. (d) to (f) show the percentage
whitecap coverage from the Zhao and Toba(2001) model for each of the three locations.
4 Discussion and Conclusions
An increasing positive relationship between wind speed and W was found. It has been shown that W
exhibits a large spatial variability for a given wind speed which appears to depend on fetch. For a
south westerly wind, values of W increased from lower values at the Dublin station to higher values at
the Holyhead station, corresponding to increases in fetch conditions. South easterly winds resulted in
higher values of W at the Dublin station than the Holyhead station, corresponding to higher fetch
conditions at the Dublin station. When the wind is from the north east quadrant, W was larger at the
Dublin station where fetch conditions are greatest for this wind direction than at the Holyhead station
which has smaller fetch. These findings that W increases with increasing fetch are in agreement with
other studies (e.g. Zhao and Toba (2003) and Woolf (2005)).
The exponent of the resulting W to wind speed power law relationship for this study agrees well
with that of Zhao and Toba (2001) although the coefficient is an order of magnitude less. This results
in lower than expected values for W which may be due to a number of reasons. Values of W
characteristically vary greatly for any given wind speed especially at low wind speeds therefore a large
74
SOLAS – Ireland
Proceedings
2006
range of values of W can be expected. In addition, the wave field is often unsteady in the coastal zone
and W can be small even for relatively high wind speeds (Lafon et. al. 2004). At lower wind speeds
and for a given fetch, it takes longer for the wave field to become in equilibrium with the wind than at
larger wind speeds. It is also plausible that the spatial coverage for each individual estimate of W was
not large enough. The footprint for each image was approximately 130 m2 which may not have been
enough to adequately capture wave breaking events, which at low wind speeds can be spatially
inhomogeneous and sparse. Subsequent images were taken with a much larger field of view and a
forthcoming analysis may reveal an effect of image footprint area on measured values for W. We are
confident, however, that the image processing method developed is robust as recent unpublished data
shows a relationship between wind speed and W that closely resembles published values.
The variability of W with varying fetch has implications for a number of processes. A whitecap
correction term, based on wind speed alone, is applied to the retrieval of ocean colour from satellite
remote sensing which is used to obtain estimates of chlorophyll. Fetch by its definition varies most
significantly in the coastal zone where phytoplankton blooms are common. Wind speed-derived values
for W are also used in models for sea salt aerosol generation. Relationships between gas transfer
velocities and wind speed also exhibit a large scatter but W may provide a more appropriate
parameterisation. The results presented here represent the first analysis of data taken from a much
larger dataset which spans 2 years of images from the Irish Sea. Follow up work is underway to try to
quantify the effect of fetch on values of W which would help improve estimates of processes affected
by whitecapping.
Acknowledgements
This project was funded through the INTERREG III A programme. I would like to thank Irish Ferries
for the use of their vessel M.V. “The Ulysses”. I am pleased to acknowledge the expertise of the
technicians from the workshops in both the Department of Earth and Ocean Sciences at NUI,Galway
and the School of Ocean Sciences at UWB, Menai Bridge, Wales for the construction and maintenance
of the waterproof camera housings. I would like to thank H. Graven for manuscript comments.
References
Lafon, C., Piazzola, J., Forget, P., Le Calve, O. and Despiau, S. (2004). Analysis of the variation of the
whitecap fraction as measured in a coastal zone. Boundary-Layer Meteorology. 111, 339-360.
Monahan, E.C. and O’Muircheartaigh, I.G.(1980). Optimal power-law description of oceanic whitecap
coverage dependence on wind speed. J. Physical Oceanography. 10. 2094-2099.
Stramska, M. and Petelski, T. (2003). Observations of oceanic whitecaps in the north polar waters of
the Atlantic. J. Geophysical Research. 108, 3086.
Woolf, D.K. (2005). Parameterisation of gas transfer velocities and sea-state-dependent wave breaking.
Tellus. 57B. 87-94.
Zhao, D. and Toba, Y. (2001). Dependence of whitecap coverage on wind and wind-wave properties. J.
Oceanography. 57, 603-616.
Zhao, D., Toba, Y., Suzuki, Y. and Komori, S. (2003). Effect of wind waves on air-sea gas exchange:
proposal of an overall CO2 transfer velocity formula as a function of breaking wave parameter.
Tellus 55 B, 478-487.
75