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What is PRECIS?
The Physical Parameters
Boundary Conditions
Why the Mediterranean Basin?
The Sulfur Cycle & Aerosols
Aerosols Impacts
D t A
Data
Analysis
l i
Sulfur Cycle Validation
Future Scenarios
Conclusions
2
2

The PRECIS ((Providing
g REgional
g
Climates for
Impact Studies) RCM is driven by the GCM
HadAM3P. (Gordon et al, 2000)

It is an Atmospheric and a LSM of limited
area.
The model is described in 3 units:
The dynamics;
The physical
ph sical parameterizations;
parameteri ations;
The Sulfur cycle

•
•
•
3
3

•
Clouds & precipitation
Large Scale & Mass flux productive Convective

Radiation includes the seasonal and diurnal cycles of insolation

Boundary layer can occupy up to the bottom 5 model layers – (Smith, 1990)

Land Surface characteristics are prescribed according to climatological
surface
f
types
t

•
Surface exchanges
L d surface
Land
f
scheme
h
is
i MOSES (Met
(M t Office
Offi
Surface
S f
Exchange
E h
Scheme)
S h
)–
(Cox et al, 1999)

Gravity wave drag is applied to momentum components in the free
atmosphere – Palmer et al, 1986)
4
4

Model requires surface boundary conditions from
surface temperatures and ice extents.
extents

Dynamical atmospheric information at the boundary of
the model
model’ss domain are obtained from the LBCs which
include
- standard atmospheric
p
variables of surface p
pressure
- horizontal wind components
- atmospheric temperature and humidity measures

LBCs are updated every 6 hours of the model simulation
time.
time

Surface boundary conditions are updated every day.
5

Mediterranean enclosed by
3 major
continents; surrounded almost entirely by
mountains. This makes the Mediterranean very
unique and sensitive to climate changes.
changes

Si
Simulation
l ti
d t il
details
› GCM-HadAM3P-150km
› PRECIS (v 1.7.2) used
› 1960-1990 (1-year spin up)
› Resolution: 0.44° x 0.44°
› 100 cells x ((50 km x 50 km))
› (57°N, 18°S, 16°W, 46°E)
6
6
Mode
Nucleation
Aitken
Diameter
(μm)
<0.01
Lifetime
Removal Process
Minutes-Hours Coagulation
0.01-0.1
Hours-Days
Coagulation
Accumulation
0.1-1
Weeks
Nucleation
Coarse
1-10
Hours-Days
Gravitation
Gi t
Giant
>10
10
H
Hours-Days
D
G
Gravitation
it ti
The Sulfur Cycle
y
is based 5 variables: SO2, DMS and 3 modes
2
2of SO4 (One dissolved and 2 free modes)
 Model simulates transport of above via horizontal and
g
vertical advection,, convection and turbulent mixing


Aerosols act as CCN
 SO422- increase droplet acidity (acid rain)

Increase in aerosol causes climate impacts
7
7
Aerosol Impacts
8
Indirect: Cloud lifetime effect
CLW
#CCN
Droplet
size
PPN
Cloud
Lifetime
Cloud
Thickness
Indirect: Twomey (Cloud albedo) effect
CLW
(Fixed)
(Fi
d)
#CCN
Droplet
size
Di
Direct:
t Scattering
S tt i
effect
ff t
↓SW
↓Skin
Temp.
Cloud
Albedo/
Thickness
Cloud
Albedo
Day-time
D
ti
Solar
Radiation
Night-time
Thermal
Radiation
Max
TTemp.
Min Temp.
•
•
Direct: LW unaffected: Aerosol Opacity↓ as λ↑
Indirect: RH decreased: water vapour ↓ as condensation ↑
8
Measured
Modelled
ESRL
units
PRECIS
units
Skin Temperature
oC
Surface (Skin) Temperature
K
Net SW Radiation Flux
W m-22
Net Down Surface SW Flux
W m-22
Net LW Radiation Flux
W m-2
Net Down Surface LW Flux
W m-2
DTR at 2 meters
K
DTR at 1.5 meters
K
Convective Precipitation
kg m-2 s-1
Convective Rainfall Rate
kg m-2 s-1
Cloud Water Content
kg m-2
Cloud Liquid Water Content
kg kg-1
R l ti H
Relative
Humidity
idit
%
R l ti H
Relative
Humidity
idit
%
9
Measured
Modelled
Min = 107.4; Max = 234.7
Min = 68.9; Max = 256.4
1961-1990
10
11
12
12
Statistics of Parameters
Parameter
Conv PPN (x10‐6)
DTR
Net LW
Net LW
Net SW
RH Surface T
Correlation
0.47
‐0.11
0 48
0.48
0.59
0.43
0.13
Average Bias
Average
Bias
‐3.08
‐1.98
1 01
1.01
‐10.45
‐5.46
0.82
Max Bias
Max
Bias
‐1.48
‐0.32
3 77
3.77
‐6.99
‐3.01
1.59
Min Bias
Min
Bias
‐5.80
‐3.52
‐1.37
1 37
‐15.63
‐8.38
0.05
› Bias of Conv PPN, DTR, Net LW, Net SW, RH:
 Suggests SO42- over-prediction
› Bias of Surface T:
 Possible result of Net LW over-prediction
› Bias of SO2:
 Suggests over-prediction in chemical reaction: SO2 → SO4213
13
Sulfate Abundance:
1.
2.
3.
Aitken
Accumulation
Dissolved
14
14

Aerosol-sensitive parameters
Effect
Direct
Direct
Direct
Direct
Direct

Aitken v SW
Accum v SW
SW v Skin T
Aitken v Skin T
Accum v Skin T
Correlation
-0.76
-0.82
0.69
-0.60
0 60
-0.64
Expected
Relationship
g
Negative
Negative
Positive
Negative
Negative
Direct Effect
› Strong correlations
› Expected relationships
› Strong
St
evidence
id
off effect
ff t
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15

Aerosol sensitive parameters
Aerosol-sensitive

Indirect Effects:
› Low detectability
off effect
ff t
› Expected due to
complex
interactions

“Incorrect”
correlations:
› Model errors?
Effect
Indirect
Indirect
Indirect
Indirect
Indirect
Indirect
Indirect
Cloud
lifetime
Cloud
lifetime
Indirect
Indirect
Indirect
Diss v Skin T
Diss v SW
SW v DTR
Expected
Correlation Relationship
-0.77
Negative
-0.82
0 82
Negative
0.50
Positive
CLW v DTR
Diss v CLW
CLW v SW
Diss v DTR
-0.59
0.39
-0.28
-0.40
Negative
Positive
Negative
g
Negative
Diss v PPN
0.43
Negative
CLW v PPN
CLW v LW
Diss v LW
LW v DTR
0.18
-0.26
-0.60
0.47
Negative
Positive
Positive
Negative
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16
Effect
Cloud
lifetime
Cl d
Cloud
lifetime
Expected
Correlation Relationship
Diss v PPN
0.43
(Negative)
Negative
CLW v PPN
0.18
Negative
Positive
Consider a cloud of increasing CLW

Cloud lifetime effect
Increasing
Aerosol

“Water-cycle effect”
Constant Aerosol
↓ Droplet
p size
↓ Precipitation
↑ Droplet size
↑ Precipitation
“Water-cycle effect” >> Cloud lifetime effect
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17
Effect
Indirect
Indirect
CLW v LW
Diss v LW
Indirect
LW v DTR
Expected
p
Correlation Relationship
-0.26
Negative
Positive
-0
0.60
60
Negative
Positive
0.47
Negative
Positive
Consider a cloud with dissolved aerosol
› Influenced by the indirect effect (↑ CLW/thickness/albedo)
↓ LW
↓ Max T.
↓ DTR
↑ LW
↑ Min T.
↓ DTR
LW
LW
18
19
19
SO2 mass mixing ratio at model level 5
20
20
SO2 mass mixing ratio (ppb) at various model levels at grid point (37.45°N, 14.59°E) – Location of Etna
(dashed lines – non volcanic activity)
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21
SO2 mass mixing ratio (ppb) at various model levels at grid point (37.20°N, 15.84°E) – Location of Plume
(dashed lines – non volcanic activity)
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22
Scenario Economic
growth
Population growth
Focus
A2
Slow
High
Slow technological change
B2
Intermediate Intermediate
Sustainability:
economy society,
economy,
society
environment
A1B
Very Rapid
Efficient technology;
Non/Fossil balance
Peaks mid-century;
declines after
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24
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25
› Model is able to produce topographical detail
› Effect evidence and correlation:
 Direct: High evidence & Acceptable correlation
Low-Moderate
Moderate evidence & correlation
 Indirect: Low
› Bias suggests problems with the Sulfur cycle:
2 emissions
 Possible
i
over-estimation
i
i
off direct
i
SO42i i
 Possible over-estimation of SO2 → SO42› More validation and ensemble simulations are needed for
confidence with climate change scenarios as based on
the Sulfur cycle
› More detailed analysis is needed for chemistry in the
vertical layers
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26
Mr. Adam Gauci
Mr
 Mr. Pierre-Sandre Farrugia
 Dr.
Dr Louis Zammit Mangion

David Hein
 David Hassell
 http://precis.metoffice.com/

27
Noell Aquilina
N
A ili
E: noel.aquilina@um.edu.mt
T +356 2340 3036
T:
PRECIS
MONITORING STATIONS
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PRECIS
MONITORING STATIONS
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