-
Arctic Regional Climate Modelling:Arctic Regional Climate
Modelling:GEMGEM--Arctic, the DGF Process and Arctic, the DGF
Process and
CloudSat CloudSat –– CALIPSO New Perspective CALIPSO New
Perspective
JJ--P Blanchet, E. Girard, C. Jones, P Blanchet, E. Girard, C.
Jones, P. P. GrenierGrenier, R. Munoz, R. Munoz--Alpizar, P. Du, C.
Stefanof, A. Stefanof, D. Alpizar, P. Du, C. Stefanof, A. Stefanof,
D. SimjanovskiSimjanovski
University of Quebec at Montreal (UQAM)University of Quebec at
Montreal (UQAM)
with collaboration fromwith collaboration from
G. Stephens, D. Winker , C. G. Stephens, D. Winker , C.
TrepteTrepte, J. , J. PelonPelon, J. Jiang, E. , J. Jiang, E.
FetzerFetzerCloudSat CloudSat –– CALIPSO CALIPSO –– AURA AURA ––
AIRS TeamsAIRS Teams
Towards a Polar Snowfall Hydrology Mission: Towards a Polar
Snowfall Hydrology Mission: The Science and the GapsThe Science and
the Gaps
2626--28 June 200728 June 2007Montreal, Quebec Montreal,
Quebec
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ObjectivesObjectives
1.1. Summarize the development of the new Summarize the
development of the new GEM GEM –– ClimClim Canadian Regional
Climate Canadian Regional Climate ModelModel
2.2. DehydrationDehydration--Greenhouse Feedback (DGF)Greenhouse
Feedback (DGF)an indirect effect of aerosols on cloud and an
indirect effect of aerosols on cloud and precipitation and climate
in the Arctic.precipitation and climate in the Arctic.
3.3. New results from New results from
CloudSatCloudSat--CALIPSOCALIPSO
-
CRCM CRCM -- ArcticArctic
Two ModelsTwo Models (dynamic kernels) are used:(dynamic
kernels) are used:
NARCMNARCM = CRCM (MC2) + CAM aerosols= CRCM (MC2) + CAM
aerosolsStatus: Mature with 6 years of experimentsStatus: Mature
with 6 years of experimentsStructure: Scalar model (very slow
!!!)Structure: Scalar model (very slow !!!)
GEMGEM--CAMCAM = CRCM (GEM) + CAM aerosols= CRCM (GEM) + CAM
aerosolsStatus: In development from forecast modelStatus: In
development from forecast modelStructure: Parallelised
modelStructure: Parallelised model
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The Canadian Regional Climate Modellingand Diagnostics (CRCMD)
Network
-
GEM can be run in a variety of configurations
● Potential for a common modelling framework for the development
and application of both global & regional climatemodels
● Joint weather forecast, climate and cloud resolving
domains
● Applicable to any regions on a wide range of scales
● One application is the Arctic processes and climate
studies
-
Simulated Annual cycle of 2-metre temperature at 3 distinctly
different climatic locations around the globe.
Ref.: Zav Kothavala, Colin Jones, Katja Winger, Bernard Dugas
& Ayrton Zadra
-
BondvilleckMAGS GAPP BALTEX GAME
LBA LA PLATA CEOP Observation Site
MDB
AMMA
Transferability of GEM-LAM has been assessed through
participation in the GEWEX-CEOP ICTS transferability study.
-
We have made some tests of GEM-LAM over North Americaon a common
domain at 0.45º, 0.3º and 0.15º resolution
-
Barrow: Native domain freq. distribution (Precipitation)
Ref.: Zav Kothavala, Colin Jones, Katja Winger, Bernard Dugas
& Ayrton Zadra
Winter Summer
-
GEM Evaluation vs SHEABARef.: D. Simjanovski and C. Jones
PRECIPITABLE_WATER
0
2
4
6
8
10
12
14
16
18
20
Aug/97 Sep/97 Nov/97 Jan/98 Feb/98 Apr/98 Jun/98 Jul/98
Sep/98
PREC
IPIT
AB
LE_W
ATE
R [K
g/m
2 ]
CLOUD_COVER
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Aug/97 Sep/97 Nov/97 Jan/98 Feb/98 Apr/98 Jun/98 Jul/98
Sep/98
CLO
UD
_CO
VER
SW_DOWN
0
50
100
150
200
250
300
350
Aug/97 Sep/97 Nov/97 Jan/98 Feb/98 Apr/98 Jun/98 Jul/98
Sep/98
SWD
[W/m
2 ]
LW_DOWN
0
50
100
150
200
250
300
350
Aug/97 Sep/97 Nov/97 Jan/98 Feb/98 Apr/98 Jun/98 Jul/98
Sep/98
LWD
[W/m
2 ]
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NARCM: Aerosol SizeNARCM: Aerosol Size--Specie ResolvedSpecie
ResolvedS ectiona l S ize R epresen ta tion
A eroso l R ad ius [μm ]
0.001 0 .01 0 .1 1 10 100
Dis
tribu
tion
0
2
4
6
8
10
12
3
4
5
6
7
89
10
11
12
• Flexible model structure• Multi-components Simulations•
Physically based size distribution• Numeric diffusion for particle
growth• Computational intensive (large bin no.)
Gong, Barrie and Blanchet et al. 2003, JGR
Mas
s
CanadianAerosol ModuleGong et al (1997, 2003)
DynamicsPhysics
Semi-lagrangiantracer transport
CRCMCanadian Regional Climat Model
Aerosol sourcefunction
Aerosol processes
CAMCanadian Aerosol Module
NARCMNorthern Aerosol Climate Model
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DehydrationDehydration GreenhouseGreenhouse Feedback Feedback
DGF DGF -- ProcessProcess
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Sulphur Injection into the ArcticSulphur Injection into the
Arctic
AMAP Assessment Report: Arctic Pollution Issues. Arctic
Monitoring and Assessment Programme (AMAP), Oslo, Norway. Xii+859
pp
64%
from
Rus
sia
Noril’skA point source
within the Arctic Circle
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Evidences of Evidences of aerosol alterations in the
Arcticaerosol alterations in the Arctic
BiggBigg (1980) observed (1980) observed sulfuric sulfuric acid
coatingacid coating on nearly all on nearly all other aerosol
particles during other aerosol particles during winterwinter
Boris observed Boris observed reduced ice reduced ice nuclei
activitynuclei activity by 100 to by 100 to 10000 fold in crystal
counts 10000 fold in crystal counts during anthropogenic Arctic
during anthropogenic Arctic haze event.haze event.
New laboratory observationsNew laboratory observations(Bertram
and Girard) confirm (Bertram and Girard) confirm the reduced IFN
activity of the reduced IFN activity of sulfuric acid coated
aerosolssulfuric acid coated aerosols
Reaction on calcium fluorideRef.: Bigg, 1980
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Size (μm)
Tim
e (d
ays)
Cold CloudsCold Clouds Regime (Arctic FallRegime (Arctic
Fall--WinterWinter--Spring)Spring)
Ref.: Girard, Blanchet, JAS 2001
Radius (microns)0.01 0.1 1 10
Con
cent
ratio
n
Sulphate Enriched Mixture
• Fewer but larger ice crystals• Cooling positive feedback
(colder)• Radar: visible• Thin Ice Cloud type 2
Radius (microns)0.01 0.1 1 10
Con
cent
ratio
nPristine Aerosols
• Numerous and small ice crystals• Long cloud lifetime (warmer)•
Radar: no or weak return• Thin Ice Cloud type 1
20µm 200µm Mas
s Fl
ux >
100
00X
DG
F ef
fect
Lesserosion
H2SO4shell
-
Ice and Snow layers
Two Opposite States: Diamond Dust or Ice Fog
Dehydration-Greenhouse Feedback (DGF)
Less H2O vapour
Acid Aerosols **
* ** ** **
**
* **
**
***
* ***
*
* *** *
* *** * *
**Low Acid AerosolsHydrophilic
WarmerColder
Reduced Greenhouse
Increased Greenhouse
Clouds forming on acidic ice nuclei precipitate more
effectively, dehydrate the air, reduce greenhouse effect and cool
the surface
Slow Cooling Process adiabatic cooling and IR lost
Thin Ice Clouds type 1Thin Ice Clouds type 2
Cold Ice and Snow Surface
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AVHRR T 20 yr Summer Temperature Trend NASA/Goddard Space Flight
CenterScientific Visualization Studio, Larry Stock, Robert
Gerstenbased on data analysis by Joey Comiso (NASA)
Sea ice-albedo feedback (+)
Snow-albedo feedback (+)
A rapidly declining perennial sea ice cover in the Arctic,
Geophysical Research Letters, Vol. 29, No. 20, October 2002
http://svs.gsfc.nasa.gov/search/Keyword/Arctic.html
Mean Annual Trend °C / yr
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AVHRR T 20 yr Winter Temperature Trend 1982-2002 NASA/Goddard
Space Flight CenterScientific Visualization Studio, Larry Stock,
Robert Gersten (2003)
CGCM1/IS92a-Winter
2040-60 minus 1975-95
Mean Annual Trend °C / yr
Raatz, 1991H
L
LL
H
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AVHRR T 20 yr Winter Trend near Noril’sk,Russiaemits 2.8Mt
SO2/yr at 69°N 88°E in the Arctic Circle
Main flow Acid shadow?
Acid shadow? Acid shadow?
Noril’sk(coldest trend!)
Ref.: NASA Goddard
Mean Annual Trend °C / yr
-
AVHRR T 20 yr Autumn Trend near Noril’sk,Russiaemits 2.8Mt
SO2/yr at 69°N 88°E in the Arctic Circle
Acid shadow?Noril’sk(cold trend)
Ref.: NASA Goddard
Mean Annual Trend °C / yr
-
AVHRR T 20 yr Spring Trend near Noril’sk,Russiaemits 2.8Mt
SO2/yr at 69°N 88°E in the Arctic Circle
Noril’sk
Ref.: NASA Goddard
http://svs.gsfc.nasa.gov/search/Keyword/Arctic.html
Mean Annual Trend °C / yr
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WhatWhat do do wewe seesee in the in the ArcticArcticfromfrom
CloudSat CloudSat –– CalipsoCalipso ??
Can Can wewe detectdetect DGF type of DGF type of processprocess
??On On whatwhat scalescale ??
Do Do wewe seesee anyany possible possible responseresponse
??
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Typical Winter ConditionsTypical Winter ConditionsJanuary 1,
2007 January 1, 2007 –– CALIPSO + CloudSatCALIPSO + CloudSat
CloudSat
-
Case Case StudyStudy: : KyrillKyrill StormStormJanuaryJanuary
18, 200718, 2007
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KyrillKyrill StormStormJanuaryJanuary 19, 200719, 2007
Surface Pressure(black lines mb)
and
Geopotential Heights(color contours m)
-
KyrillKyrill Storm Storm –– System Through ExtensionSystem
Through Extension
-
AerosolAerosol Simulation Simulation duringduring KyrillKyrill
StormStormJanuaryJanuary 1515--21, 200721, 2007
CAM – segmented aerosol model: 12 size bins from 0.005 to 20 µm5
species: sea salt, soil, organics, soot and sulfate
Scale: Log Concentration in kg.m-3
Total Aerosol – 854mb Sulfate Aerosol – 923mb
Horizontal resolution: 45kmModel NARCM
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ViewView fromfrom CalipsoCalipso –– CloudSat CloudSat
JanuaryJanuary 19, 200719, 2007
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U.S.A. U.S.A. –– ArcticArctic ComparisonComparison
2007/01/19 08:25:37.4350 UTC 2007/01/19 01:50:03.2330 UTC
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Frequent Arctic Overpass Frequent Arctic Overpass Compact Time
Sampling and near 3D Horizon ViewCompact Time Sampling and near 3D
Horizon View
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«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
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«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
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«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
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«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
-
«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
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«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
-
«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
-
«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
-
«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
-
«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
-
«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
-
«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
-
«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
-
«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
-
«« Tour Tour dd’’horizonhorizon »» around the Polearound the
PoleJanuary 19, 2007January 19, 2007
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Weather Weather SynopticsSynoptics of of KyrillKyrill
StormStormJanuary 16 January 16 –– 29, 200729, 2007
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Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
Surface Pressure & 500mb HeightSurface Pressure & 500mb
Height( ~ Mean Temperature in lowest 5 km)( ~ Mean Temperature in
lowest 5 km)
-
DGF Process in ActionDGF Process in Action
-
EnhencedCold Dome
Airmass
TIC type 2: Cold TIC type 2: Cold LowLow PenetrationPenetration
in in thethe ArcticArctic andandSlowlySlowly Lifting Lifting
AcidicAcidic AerosolAerosol withwith DGFDGF
IRNET
LSCALE: A 5 to 8 day dehydration- IR cooling process1000 – 3000
km
Radar VisibleLarge Ice Crystals
Higher Precipitation Rate
-
Day 1January 18, 2007
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Day 2January 19, 2007
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Day 3January 20, 2007
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Day 4January 21, 2007
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Day 5January 22, 2007
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Day 6January 23, 2007
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Day 7January 24, 2007
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O3
CO2
H2O H2OTrace Gases
Greenhouse Atmospheric Radiation at the groundGreenhouse
Atmospheric Radiation at the groundWater Vapour is the Strongest
Greenhouse GasWater Vapour is the Strongest Greenhouse Gas
Downward IR spectral radiance (53° zenith angle) using
LOWTRAN
-
ArcticArctic EquinoxEquinoxJuneJune 21, 200721, 2007
3200 km
-
TIC type 1: Cold TIC type 1: Cold LowLow PenetrationPenetration
in in thethe ArcticArctic andandSlowlySlowly Lifting Lifting
PristinePristine Air Air withoutwithout DGF DGF EffectEffect
L
IR
IR
Radar TransparentSmall Ice Crystals
Low Precipitation Rate
-
Arctic Winter: Thin Ice Clouds Type 1 (pristine) over
GreenlandJanuary 19, 2007
-
TIC-1
Thin Ice Clouds Thick Ice CloudsMid-latitudesAntarctic
Antarctica Winter: Thin Ice Clouds Type 1 (pristine)July 15,
2006
-
Summary: Cloud Types Summary: Cloud Types –– IFN AerosolIFN
AerosolJanuary 19, 2007January 19, 2007
Thin Ice Cloud type 2 high [aerosols] (acidic),
large ice crystalsand fast sedimentation
Thin Ice Cloud type 1low [aerosol] (pristine),
small crystalsslow sedimentation
DGF-DeepDGF-PBL
No DGF
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ThinThin IceIce Cloud (TIC) TypesCloud (TIC) Types
TICTIC--11Pristine environmentPristine environment
Active IFN (low acid) Active IFN (low acid) Small ice
crystalsSmall ice crystalsWeak sedimentation rateWeak sedimentation
rateRandomly orientationRandomly orientationLower IR
emissivityLower IR emissivityRadar transparentRadar transparentEx:
thin cirrus (pristine)Ex: thin cirrus (pristine)
Ice Ice stratusstratus or ice fogor ice fog
TICTIC--22Anthropogenic effectAnthropogenic effect
Low activity IFN Low activity IFN (high acid content)(high acid
content)Large ice crystalsLarge ice crystalsLarge sedimentation
rateLarge sedimentation rateHorizontal orientationHorizontal
orientationLarger IR emissivityLarger IR emissivityRadar
visibleRadar visibleEx: diamond dust (acid)Ex: diamond dust
(acid)
deep arctic cirrus deep arctic cirrus (4 (4 -- 10 km deep)10 km
deep)
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Two Important Climate Feedbacks Two Important Climate Feedbacks
are Interlinked during Arctic Winter :are Interlinked during Arctic
Winter :
Vertical :Vertical : Acid aerosols alter thin ice cloud Acid
aerosols alter thin ice cloud microphysics, enhancing IR cooling
and microphysics, enhancing IR cooling and dehydration dehydration
lower temperatureslower temperatures
Horizontal :Horizontal : Lower temperatureLower temperature
generates generates APE enhancing midAPE enhancing mid--latitude
storms which latitude storms which transport aerosols into the
Arctic and further transport aerosols into the Arctic and further
cools in the cools in the vertical vertical process.process.
“Arctic Thermal Pumping”
-
Temperature Trend: Temperature Trend: Simulation Simulation vsvs
ObservationObservation
Hansen, et al (GISS)
70 year observed trend
Ref.: Pavlovic and Blanchet, 2002
SimulationNARCM + Girard - Curry Cloud
NorilskKola
AVHRR 20 year Trend
-
CorrelationCorrelation betweenbetweenRelative Relative
HumidityHumidity andand
AcidAcid FractionFraction fromfrom AIRS AIRS Data Data andand
NARCM NARCM
SimulatedSimulated AerosolsAerosols
Correlation between rw and sulfate ratioin function of
temperature
-1
-0,8
-0,6-0,4
-0,2
0
0,2
-33 -30 -27 -24 -21 -18 -15 -12 -9 -6 -3
temperature (oC)
corr
elat
ion
700 mb850 mb925 mb
Ref.: Grenier, Blanchet and Fetzer (2006)
-
Example: ensemble of 12 January Example: ensemble of 12 January
Simulations (perturbed Simulations (perturbed ––
reference)reference)
[ Aerosol (µg/m3 ] IWC annomaly
Precipitation annomaly IR down at sfc annomaly (W/m2)
Temperature annomaly °C
Ref.: Stefanof A., 2005 (MSc)Girard E. et al, 2006
Dehydration Efficiency
-
1900 1920 1940 1960 1980 2000
Years
0
20
40
60
80
Eve
nts
Num ber o f Intense W inte r C yc lones pe r YearsNorthern Hem
is phere (Lam bert, 1997)
Observed Trend in the Winter StormsObserved Trend in the Winter
StormsNorthern HemisphereNorthern Hemisphere
-
Model Model StudiesStudiesWe have done We have done several
simulationsseveral simulations of this process of this process
using the CRCM and CAM models.using the CRCM and CAM models.Results
show consistently that Results show consistently that reduction of
IFN reduction of IFN activityactivity increase light precipitation,
dehydration increase light precipitation, dehydration and cooling
efficiencyand cooling efficiency..Efforts are needed to Efforts are
needed to improve improve parameterisationparameterisation of of
DGF process.DGF process.3D Prognostic precipitation3D Prognostic
precipitation fields are requiredfields are requiredCloud resolving
simulationsCloud resolving simulations are needed to bridge are
needed to bridge scale gaps.scale gaps.Improving the Improving the
PBL schemePBL scheme in cold climate is in cold climate is needed
needed
-
SummarySummaryTwo types of thin ice cloudsTwo types of thin ice
clouds can occur depending on IFN can occur depending on IFN
activity.activity.
DGF can be driven by DGF can be driven by IR coolingIR cooling
(PBL) or deep slow (PBL) or deep slow adiabatic ascendadiabatic
ascend in decaying low pressure systems entering in decaying low
pressure systems entering the Arctic.the Arctic.
TypeType--2 (acidic) 2 (acidic) IRIR-- cools a deep cools a deep
tropospherictropospheric layerlayer in 5in 5--8 8 days over
1000days over 1000--3000 km scale. 3000 km scale.
Colder pole fuel intense stormsColder pole fuel intense storms
transporting new aerosols transporting new aerosols into the
Arctic.into the Arctic.
CloudSat and CALIPSOCloudSat and CALIPSO reveal the complex
interactions reveal the complex interactions between aerosols,
clouds, precipitation, radiative cooling and between aerosols,
clouds, precipitation, radiative cooling and large scale
circulation.large scale circulation.
We are developing new We are developing new atmospheric
modelatmospheric model to simulate these to simulate these
interactions in climate models. interactions in climate models.
-
«« DGF may be the largest DGF may be the largest man mademan
made
cloud seeding experiment cloud seeding experiment and and
weather modification in the weather modification in the world
.world .»»
-
AntarcticaAntarctica EarlyEarly WinterWinterJuneJune 18, 2007
(18, 2007 (lastlast weekweek!)!)