MALTA CLIM
MATE TEAM
Department of Physiccs, Faculty of Science
E: climate‐physics.sci@um..edu.mt T: +356 2340 3036
I
Investigating relationshi
ti ti
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O ill ti P tt
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d th i i fl
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transport using a Regional Climate Model (RegCM4)
transport using a Regional Climate Model (RegCM4)
Models Operated by the MCT
PRECIS
Type: Regional Climate Model
Name: Providing REgional Climate for Impact Studies (PRECIS) Name: Providing REgional
Climate for Impact Studies (PRECIS)
Maintained at: Met Office UK (License‐based)
Different Schemes
Different Schemes • Planetary Boundary Layer
• Radiation
• Precipitation • Chemistry model (Sulfate only)
y
(
y)
• 2 Land Surface (MOSES 1 & 2.2)
•
•
•
Used to generate high‐resolution climate change information for many
regions.
The intention was to make PRECIS freely available to groups of developing
countries.
Th
These
scenarios
i can be
b used
d in
i impact,
i
t vulnerability
l
bilit and
d adaptation
d t ti studies.
t di
The Department of Physics is active in the PRECIS Community, contributing to its The
Department of Physics is active in the PRECIS Community contributing to its
development.
RegCM4 Type: Regional Climate Model
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g
Name: Regional Climate Model 4 (RegCM4) Maintained at: International Centre for Theoretical Physics (Community‐based) Different Schemes
• Planetary Boundary Layer • Radiation
• Precipitation • Chemistry model (Dust, Sulfate Organic Carbon, Black Carbon)
Ch i
d l (D
S lf
O
i C b
Bl k C b )
• Clouds Ocean Flux • Pressure Gradient Force Pressure Gradient Force
• Lake model
• 2 Land Surface (BATS & CLM) 2 Land Surface (BATS & CLM)
The Department of Physics has recently embarked on projects leading to further
validation of the model.
Mr. James Ciarlo`
E: jcia0004@um.edu.mt
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Introduction
d
Teleconnections ‐ two or more distant semi‐permanent points
of atmospheric pressure (“nodes”) with
h strong negative
relationship with one another.
 Example:
p teleconnection between the Icelandic Low and
the Azores High ‐ 3600 km apart.
Oscillation Pattern ‐ a set of teleconnections as a whole
 vary almost in an oscillating manner,
 Example: the North Atlantic Oscillation (NAO).
(
(NAO)
Aerosols are solid and liquid particles suspended in the
atmosphere.
Transportation: suspended particles are movved with air motion
Oscillation Patterns have a strong influence on
o movement of air.
Behaviour of patterns can influence aerosol transportation
t
transportation.
The NAO is an important Oscillation Patterrns in the Northern
Hemisphere.
This study focusses on various patterns.
patterns
Patterns at Sea Level:
 NAO,
NAO Southern Europe North Atlantic (SENA),
(SENA) Western
Mediterranean Oscillation (WeMO), and Central African‐
Caspian Oscillation (CACO).
Patterns at higher atmospheric levels:
 Mediterranean Oscillation ((MO)) and
d the North Sea‐
Caspian Pattern (NCP).
Influence of NAO on Jet Stream
Positive Index
Large Pressure differences
p
Pushes Jet Stream to N. Europe
Negative Index
Small Pressure differences
“Blocks” Jet Stream
Pushes Jet Stream to Mediterranean
Source
http://www.newx forecasts.com/nao.html
http://www.newx‐forecasts.com/nao.html
Data Analysis
Data Analysis
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North Atlantic Oscillation Index (Walker & Bliss, 1935)
Defining Wind Components:
u‐wind is the wind speed in the West to East direction.
v‐wind
i d is the
h wind
d speed
d in the
h South
h to Norrth
h direction.
d
RegCM4
2
Type: Numerical Weather Prediction Model
Type:
Numerical Weather Prediction Model
Name: Weather Research and Forecasting (WRF) Maintained at: National Centre for Atmospheric Research (NCAR)
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A mesoscale model designed to serve both operational forecasting and atmospheric research needs.
It features multiple dynamic cores, a 3D variational (3DVAR) data assimilation system.
A software architecture allowing for computational parallelism and system extensibility.
ibili
Suitable for a broad spectrum of applications across scales going down to 1km.
1km
Has an easy to use GUI and excellent for training in meteorology.
The Department of Physics intends to update the WRF version to WRF‐CHEM and WRF‐LES
WRF
LES for specific applications.
for specific applications.
All these models have been successfully installed and are currently operational on y
y p
the Computer Cluster Facility, ALBERT at the University of Malta.
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Considering the NAO Variant of Walker & Blisss (1935).
Correlation of the NAOI with wind componen
nts defines how the
NAO affects the wind in the study region.
Central chart shows the average
g dust ((<0.1 µ
µm)) p
present in the
region between 1982‐2000 as outputted from
m RegCM4.
IIndex Value
1
WRF
NCEP
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3
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0
-1
-2
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Time series describes the NAOI according to NCEP measured
data and RegCM4 modelled data.
RegCM4 index is very similar to NCEP index.
index
Positive NAO pushes African dust to SW, away from the
Mediterranean.
Negative NAO pushes African dust to NE, towards the
Mediterranean.