Snow and ice in polar and sub-polar seas:
numerical modeling and in situ observations
Bin Cheng, Timo Vihma, Jouko Launiainen, Laura Rontu,
Juha Karvonen, Marko Mäkynen, Markku Simila, Jari Haapala,
Anna Kontu, Jouni Pulliainen
Finnish Meteorological Institute (FMI)
27 -28 October, Sino-Finnish Arctic Seminar
0 C
T
Initial ice formation
Freezing season
z
Thermal equilibrium stage
Melting Season
27 -28 October, Sino-Finnish Arctic Seminar
27 -28 October, Sino-Finnish Arctic Seminar
• Objectives




to develop snow and ice thermodynamic model HIGHTSI
to investigate snow and ice mass balance and temperature regimes.
to understand snow and ice physical properties.
to improve the snow and ice schemes used as boundary condition for
numerical prediction models.
 to provide physical background information for ice thickness analysis
using remote sensing data.
 to carry out sustainable long term snow and ice observations in Arctic
and seasonal ice covered seas.
• Tasks
 Snow and ice modeling
 In situ observations
27 -28 October, Sino-Finnish Arctic Seminar
• Snow and ice modeling








Model validations (Bohai Sea, Baltic Sea, Arctic Ocean)
Numerical scheme: spatial resolution on model results
External forcing: in situ measurements; NWP model results
Effect of snow on ice mass balance: snow ice and superimposed ice
formation.
Evaluation of albedo schemes applied in ice model.
Thermal and optical properties of snow and ice.
HIGHTSI model for lake applications.
Basin scale ice thermodynamic growth.
• Field observation
 Bohai Sea; Baltic Sea
 CHINARE2003; CHINARE2008
 Arctic lakes
27 -28 October, Sino-Finnish Arctic Seminar
Snow
Ice
Air
Snow
D s
Tsfc
h
snow F
T
cs
x
Tin
F
hs
Snow/ice
ci
Water
Ice
Tice
HIGHTSI: One dimensional snow/ice
thermodynamic model considered in
a horizontal unit area
External forcing: NWP models
(HIRLAM/ECMWF)
Result: Snow and ice thickness; surface
temperature
27 -28 October, Sino-Finnish Arctic Seminar
pond
hi
water
Snow/Ice
Open water/ice concentration
inforamtion (SAR, AMSR_E, MODIS)
External weather forcing data:
- Wind speed (m/s)
- Air temperature (°C)
- Moisture, in format of relative humidity %
- Cloudiness (0-1)
- Precipitation, in format of snow liquid water content (mm/T)
- Downward shortwave radiative flux (W/m2)
- Downward longwave radiative flux (W/m2)
- Sensible heat flux from water below (W/m2)
- Surface albedo (0-1)
- Open water/ice concentration inforamtion (SAR, AMSR_E, MODIS)
27 -28 October, Sino-Finnish Arctic Seminar
27 -28 October, Sino-Finnish Arctic Seminar
Karvonen et al, (2008)
27 -28 October, Sino-Finnish Arctic Seminar
Vertical air and in-ice temperature profiles a) during a cold day of 30 to 31
January 1990, from 23h to 18h , and b) during a milder day of , 5 February
1990, from 03h to 17h . A few observations are given (+, o, x) for
comparison. (Note the different vertical scaling in ice and air.) (Launiainen
and Cheng, 1998, Cold Reg. Sci. Technol)
Observed and modeled ice growth in the Baltic Sea (Cheng, et al, 2000, Ann. Glaciol)
27 -28 October, Sino-Finnish Arctic Seminar
The
weather
mast of
the
FinnishChinese
winter
expedition
. All the
field
measurem
ents were
made
within a
radius of
200 m of
the mast
(Seinä &
al. 1991).
The Observed and modeled
evolution of (a) snow
thickness Hs, (b) ice
freeboard, (c) superimposed
ice thickness (granular ice)
Hsui, and (d) total ice
thickness Hi.
The observed
precipitation (a),
total ice
thickness (b),
snow thickness
and freeboard
(c), and granular
ice growth (d) in
the Baltic Sea
(Granskog, et al,
2006, J. Glaciol,
The observed (symbols) and
modelled (lines) snow
temperature profiles (a) on day
79 and (b) day 88. The zero
depth refers to the snow/ice
interface. (Cheng et al, 2006
Ann. Glaciol.)
The time series
of modelled
snow thickness.
The white area
below the
surface indicates
the region of
active surface
and sub-surface
melting.
27 -28 October, Sino-Finnish Arctic Seminar
Model experiments on snow and ice thermodynamics in the Arctic Ocean with CHINARE 2003 data (Cheng, et al, 2008, JGR)
27 -28 October, Sino-Finnish Arctic Seminar
HIGHTSI modeled snow and ice mass
balance (Cheng et al, 2008, CJPR) with
external forcing data proposed by SIMIP2
(Huwald et al, 2005)
- Precipitation x 1.5
Less calculated surface melting
against observation
The Observed ice thickness and temperature
regime during SHEBA annual cycle (Perovich et
al, 2003, JGR)
27 -28 October, Sino-Finnish Arctic Seminar
Albedo from SIMIP2 (melt pond effect?).
Oceanic heat flux was 11W/m2 on the average during
the SHEBA year.
Overestimated surface melting with coarse spatial
resolution. Improved results with superimposed ice
formation taken into account, The modeling errors are
related to the uncertainties of the snow/ice thermal
properties.
27 -28 October, Sino-Finnish Arctic Seminar
Tara’s drift started in September 2006 in
the Laptev Sea north of Siberia. Tara
passed near the North Pole to the Fram
Strait, where it broke free of the ice on
21st January 2008.
Tara drift trajectory from NW to SE
between 1 April and 30 September. On
18, April, 2007, Tara was located in
the center of the large cross
27 -28 October, Sino-Finnish Arctic Seminar
HIGHTSI modelled snow and ice thicknesses;
in snow and ice temperature field and surface
skin temperature
27 -28 October, Sino-Finnish Arctic Seminar
Downward shortwave radiative flux
Wind speed difference
Exp. 4: Hirlam albedo
Exp. 5: Tara albedo
Difference= Exp. 4– Exp. 5
Albedo: Exp. 4,
Exp. 5
Downward longwave radiative flux
Temperature difference
J-day 160 == 9, June
27 -28 October, Sino-Finnish Arctic Seminar
Surface temperature difference
o
-9
-12
-15
0.0
o
Calculated surface temperature ( C)
-6
0.05m
0.1m
0.15m
0.25m
0.3m
0.35m
0.4m
0.5m
1.0m
mean values
Calculated surface temperature ( C)
(b)
(a) -3
-0.3
-0.6
-0.9
-1.2
0.1m
0.2m
0.3m
0.4m
0.5m
1m
mean value
-1.5
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Simulated ice thickness (m)
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Simulated ice thickness (m)
Surface temperature versus different ice thickness category:
(a) a cold period between 3 Jan 0:00 - 5 Jan 23:00 (b) a warm period between 8 April 0:00 11 April 13:00 (Yang et al, 2012, Tellus)
Surface temperature response strongly for thin ice category (<0.5m) in cold condition
27 -28 October, Sino-Finnish Arctic Seminar
27 -28 October, Sino-Finnish Arctic Seminar
KaraX sea ice product area
Red dots are
weather stations.
Coverage 1500
by 1350 km.
27 -28 October, Sino-Finnish Arctic Seminar
Thin ice thickness from MODIS
• Physical basis: Thin ice thickness from ice surface temperature can be
estimated on the basis of surface heat balance equation. Major assumptions
here are that the heat flux through the ice and snow is equal to the
atmospheric flux and temperature profiles are linear in ice and snow. Method
presented e.g. in:
Yu & Rothrock (1996). Thin ice thickness from satellite thermal imagery. Geophys.
Res. 101(C10), 25753-25766.
• Requirement: The approach works only under cold cloud-free weather
conditions (air temperature < -10°C).
• Using only nighttime data: Uncertainties related to the effects of the solar
shortwave radiation and surface albedo are excluded.
• Reliable method for MODIS cloud masking needed.
• HIRLAM as weather forcing data.
• Parametrizations needed: snow vs. ice thickness, snow and ice thermal
conductivity etc.
27 -28 October, Sino-Finnish Arctic Seminar
Doronin (1971):
hs = 0 for hi < 5 cm; hs = 0.05xhi for 5 cm≤ hi ≤ 20 cm; hs = 0.1xhi for hi > 20 cm
Mäkynen and others (2012):
hs = 0 for hi < 5 cm; hs = 0.05xhi for 5 cm≤ hi ≤ 20 cm; hs = 0.09xhi for hi > 20 cm
Cheng and others (2012):
Problems:
1.Snow effect: MODIS surface temperature inverses ice thickness
2.The input of snow thickness for ice modelling
MODIS and HIRLAM based ice thickness
SAR/MODIS/AMSR-E and HIGHTSI
based thickness chart, 4 March 2009
Mäkynen and others Ann. Glaciol (2012)
Similä and others Ann. Glaciol (2012)
27 -28 October, Sino-Finnish Arctic Seminar
A method for sea ice thickness and concentration analysis based on SAR
data and a thermodynamic model
Karvonen, Cheng, Vihma, Arkett, and Carrieres, 2012, TCD
27 -28 October, Sino-Finnish Arctic Seminar
Fig. 10. Ice thickness for the Jan 5, Feb 5, March 5, and Apr 5 2009 (from top to
bottom), from HIGHTSI model (middle column), from the CIS ice charts (left
column) and based on our SAR algorithm (right column).
2005/2006
1990/1991
27 -28 October, Sino-Finnish Arctic Seminar
2006/2007
2005/2006
Ice mass balance buoys
invented by SAMS (Scottish Association for Marine Science)
Continuous measurements at one location
Monitor high resolution temperature profile (sensor interval: 2cm)
81.8N,130.9E
Heater element
Temperature chain
in ‘Hot-Wire’ mode
Data-buoy
with Iridium
Link
Data + power
bus
Data +
Air
Power bus
Chip Resistor
Digital
(heater element)
temperature
sensor
Ice-air
interface
@Marcel Nicolaus, AWI, 05/09/2012
Sea-Ice
Digital
Thermistor
Ice-water
interface
88.8N,57.4E
Ocean
Schematic of the temperature chain used to measure the iceair and ice-water interface.(by Jeremy Wilkinson)
27 -28 October, Sino-Finnish Arctic Seminar
@Marcel Nicolaus, AWI, 22/09/2012
19, 12, 2011
22, 2, 2012
12, 4, 2012
27 -28 October, Sino-Finnish Arctic Seminar
Snow surface, snow/ice interface and ice bottom
detected by the IMB data.
Temperature profiles (air-snow-ice) and
temperature field (snow, ice) from IMB.
27 -28 October, Sino-Finnish Arctic Seminar
Snow and ice thicknesses detected from IMB data (lines) and in situ
measurement (symbols) in lake Orajärvi. The snow/ice interface is
used as reference level; Snow and ice temperature regimes
11,3,2012
12,4,2012
Ice core samples collected from lake Orajärvi in March and April, winter 2011/2012.
27 -28 October, Sino-Finnish Arctic Seminar
27 -28 October, Sino-Finnish Arctic Seminar
27 -28 October, Sino-Finnish Arctic Seminar
Proposal title:
Advancing Modelling and Observing solar Radiation of Arctic sea-ice –
understanding changes and processes
Project acronym:
AMORA (2009 – 2012)
NFR Norklima: Climate change - research cooperation with China
Project was coordinated by Norwegian Polar Institute (NPI), Tromsø, Norway
Partners
Polar Research Institute of China (PRIC), Shanghai, China
Dalian University of Technology (DUT), Dalian, China
Finnish Meteorological Institute (FMI), Helsinki, Finland
Cold Regions Research and Engineering Laboratory (CRREL), Hanover, USA
The Alfred Wegener Institute (AWI), Germany
27 -28 October, Sino-Finnish Arctic Seminar
Project Title: Bilateral Collaboration on multi-source satellite
remote sensing data analysis to monitoring sea ice and oceanic
environment in the Arctic Ocean (2011DFA22260)
2012 – 2015 funded by MoST, China
国家卫星海洋应用中心 (National Satellite Ocean
Application Service Centre, Beijing)



Oversea partner: Finnish Meteorological Institute
Chinese partner: Dalian University of Technology
Project period: 2012.5.1~2015.4.30
27 -28 October, Sino-Finnish Arctic Seminar
Conclusions and outlook
 Model validation is good.
 Evaluation of external forcing (in situ measurement & NWP
results).
 Improvement of understanding on snow and ice thermodynamics.
 Multidisciplinary methodology on ice thickness analysis
 Snow parameterization for Arctic conditions.
 Sustainable field measurements is important and will continue in the
future.




Operational services
Seasonal forecasts
Inter-annual and decadal climate forecasts
Close collaborations with Chinese colleagues
27 -28 October, Sino-Finnish Arctic Seminar
Current research activities at FMI
• Analysing variability and change of the ice covered seas
• Examining ocean-ice-atmosphere heat, momentum and gas
exchanges
• Developing numerical models for climate and operational
applications
• Developing retrieval algorithms for satellite data
35
REGIONS OF IN-SITU RESEARCH DURING 1997-2011
Sea-ice research
FRAMZY, CRYOVEX, NO-ICE, DAMOCLES
CHINARE2003, CRYOVEX, CHINARE2008
DAMOCLES/TARA
Physical oceanography research
VEINS, ASOF-W, THOR, Arctic Ocean 2002
VEINS, ASOF-N
36
DAMOCLES, SPACE, HOTRAX, LOMROG, CHINARE2008:
Acknowledgement to colleagues in China
雷瑞波, 郭井学, 张占海
Dr. Reibo Lei, Dr. Jingxue Guo and Prof. Zhanhai Zhang
Polar Research Institute of China (PRIC)
杨宇，李志军，卢鹏
Dr candidate:Yu Yang, Prof. Zhijun Li and Dr. Peng Lu,
Dalian University of Technology (DUT)
杨清华，吴辉碇
Ms. Qinghua Yang, Prof. Huiding Wu
National Marine Environmental Forecasting Centre (NMEFC)
石立坚，王齐茂
Dr. Lijian Shi, Prof. QimaoWang
National Satellite Ocean Application Service Centre (NSOAS)
27 -28 October, Sino-Finnish Arctic Seminar