Concours CNRS CR2, Section 19. Meudon, 17 Mars 2010 Irina Gorodetskaya Candidate for Laboratoire de...
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Transcript of Concours CNRS CR2, Section 19. Meudon, 17 Mars 2010 Irina Gorodetskaya Candidate for Laboratoire de...
Concours CNRS CR2, Section 19. Meudon, 17 Mars 2010
Irina Gorodetskaya
Candidate for Laboratoire de Glaciologie et Géophysique de l’Environnement, (UMR 5183 CNRS, Université Joseph Fourier-Grenoble)
Cryosphere
Clouds
Understanding Clouds and Their Effects on Radiative Budget and Precipitation in the Present and
Future Polar Climate
using model simulations and observations
Motivation CLOUDS?
Arctic sea icedecline!
2007x x
2008?
Credit: NSIDC
Arctic September sea ice extent
2009x
Relative annual mean precipitation change on the Antarctic ice sheet during the 21st century
Krinner et al. 2007
Antarctic precipitation increase?
The role of clouds in the Arctic sea ice
decline
Gorodetskaya and Tremblay 2008,AGU monograph “Arctic sea ice decline”
PhD at Lamont-Doherty Earth Observatory, Columbia University2002-2007 :
My Background
CCSM3 A1B CCSM3 A1B
Model simulations of present and future
Antarctic climate andsfc mass balance
My Background
Postdoctorat at Laboratoire de Glaciologieet Géophysique de l’Environnement November 2007 - present:
supervisors: H. Gallée and G. Krinner
Surface air temperaturedifference between the two models:
MAR nested in LMDZ
Gorodetskaya, Gallée, Krinner, in prep
Large-scale model (LMDZ)
Mesoscale model (MAR)
1981-1989 annual mean
Postdoctorat at K. U. Leuven, Belgium August 2009 - present:
Clouds and hydrologic cycle of Antarcticasupervisor: N. van Lipzig
My Background
AWS
• Phase 1 : meteorological and cloud measurements at the new Belgian Antarctic Station (Dronning Maud Land)
Cloud height
Precipitation
x
Cloud base temperature
• Phase 2 : use obtained data for regional model validation
Research project :
Clouds and Radiative Feedbacks in Present and Future Polar Climate
Data and Models :
Model validation Cloud schemeimprovement
Model simulationsand data analysis
Understanding climate change in polar regions
• Arctic sea ice loss• Greenland melt• Antarctic precipitation change
meso-scale (MAR)large-scale (LMDZ)
ground-based and satellite data
Arctic ocean Greenland/Antarctic
Meso => large scale
Model validation
Antarctica:Greenland:Arctic Ocean:
ARM networkSHEBA (1997/98)MPACE (2004)ASTAR (2004/7)ASCOS (2008)
Summit (ARM) (spring 2010+)
South Pole
Pr Elis (new!)
Dome C
DDU
Modèle Atmosphérique Régional (MAR)
Modèle de Laboratoire de Météorologie Dynamique with Zoom
capabilities over the polar regions (LMDZ)
+ CloudSat and CALIPSO => aerosols-clouds-precipitation
MAR validation :energy budget and temperature
Gallée and Gorodetskaya, Clim Dyn 2008
Temperature over Dome C, Antarctica
potential for model validation :clouds and precipitation
Princess Elisabeth station
snowfallevents (g/kg of snow particles)
accumulation, cm
Regional model simulations:
Snow fall event shownby radar reflectivity
Observations at Princess Elisabeth: Feb 1, 2010
Research project :
Clouds and Radiative Feedbacks in Present and Future Polar Climate
Data and Models :
Model validation
meso-scale (MAR)large-scale (LMDZ)
ground-based and satellite data
Arctic ocean Greenld/Antarctic
Cloud schemeimprovement
Model simulationsand data analysis
Understanding climate change in polar regions
• Arctic sea ice loss• Greenland melt• Antarctic precipitation change
Meso => large scale
I. Improve cloud scheme in regional
model:
QuickTime™ and aTIFF (LZW) decompressor
are needed to see this picture.
GISS-ErHadCM3
CCSM3
ocean
land
LMDZ (IPSL)
Clo
ud ic
e fr
actio
n
Cloud temperature
Cloud schemesimprovement II. Improve cloud
phase representation in GCM (LMDZ)
MAR:
- tropospheric clouds are too thin
- ice particle size too large
- improve treatment of ice and snow size spectra
Research project :
Clouds and Radiative Feedbacks in Present and Future Polar Climate
Data and Models :
Model validation
meso-scale (MAR)large-scale (LMDZ)
ground-based and satellite data
Arctic ocean Greenland/Antarctic
Cloud schemeimprovement
Model simulationsand data analysis
Understanding climate change in polar regions
• Arctic sea ice loss• Greenland melt• Antarctic precipitation change
Meso => large scale
Application:understanding cloud-ice feedbacks
planet warming
precipitation
surface sens and latent heat fluxes
atm temperatureand humidity
large-scale advection
MELT
aerosols
?
cloud properties
+
++
radiativefluxes
ICE MASSBALANCE-
?
+/-
+/-+/-
LGGE :
“Climat moderne et observationsglaciologiques”
Climate modeling:
LMD (LMDZ/IPSL) S. Bony, J.-L. Dufresne
MeteoFrance (CNRM)
Cloud modeling:
LaMP MeteoFrance
in Europe :
Polar climate modling:Liege U, KU-Leuven,IMAU-Netherlands
Sea ice modeling:Louvain-la-Neuve
USA/Canada :
Arctic cloud obs and modeling (Rutgers, NCAR,U Montreal)
Arctic climate/sea ice (McGill, U Wash)
Collaborations
Cloud observations:
LaMPNOAAKU-LeuvenIFAC (Italy)
Observational programs:
GLACIOCLIM,CESOA (LGGE)ENEA programs (Italy)
French/European projects: Ice2Sea, COMBINE, HYDRANT, Arctic Observatory
International projects: NOAA’s Arctic Atmospheric Observatory (T. Uttal et al) ICECAP (V. Walden et al/Greenland)