1. Present and Future Antarctic climate simulations using Modèle Atmosphérique Régional forced with LMDZ GCM
Irina Gorodetskaya, Hubert Gallée, Gerhard Krinner
Laboratoire de Glaciologie et Géophysique
de l’Environnement, Grenoble,France
MOCA, Montreal 23 July, 2009

2. Antarctica warming? mean annual trends mean annual trends 1969-2000
sfc temperature from IR sat data
mean annual trends
mean annual trends
Steig et al 2009

3. Changes in precipitation?
Linear trends of annual snowfall accumulation
(mm yr -1 decade -1) for
This we cannot really measure : Changes in snow fall predicted by RACMO ANT2 model:
higher coastal precip adn wetter West Antarctica and the western Peninsula (van den Berg)
Monaghan et al 2008

4. Surface mass balance from a GCM: Laboratoire de Meteorologie Dynamique general circulation model (LMDZ)
(S20)
mmwe
Krinner et al. 2007

5. Ratio between simulated SMB in S20 and estimates by Vaughan et al. 1999
Ratio between LMDZ-simulated SMB
and observed SMB in selected locations
Krinner et al. 2007

6. SMB components: LMDZ 1981-2000 Precip Melt Krinner et al. 2007 mmwe
Sublimation/
deposition
Precip
Melt
Krinner et al. 2007

7. Nesting: MAR forced with LMDZ output
Large-scale model (ECMWF or GCM)
Mesoscale model (MAR)
forced at the boundary by LMDZ4 output. 40 km resolution

8. Modèle Atmosphérique Régional (MAR)
Atmospheric model: mesoscale hydrostatic primitive equation model (Gallée 1994, 1995)
Terrain following vertical coordinates (normalized pressure)
Turbulence: 1 1/2 closure (Duynkerke 1988)
Bulk cloud microphysics (Kessler 1962 and Lin et al improvements of
Meyers et al and Levkov et al. 1992)
Solar and infrared radiative transfer scheme (Morcrette 2002, Ebert and Curry 1992)
Snow fall included into infrared radiation scheme
Snow model: conservation of heat and water (solid and liquid), description of snow
properties (density, dendricity, sphericity and size of the grains), melting/freezing
Blowing snow model (Gallée et al, 2001) FS
FS FL
T4
HLat
HSen
Snow
HMelt
HFreez
HCond
Tsfc
Percolati on
Liquid water  
Blowing snow
coupling to sea ice, land ice, vegetation...
Horizontal resolution 40 km
33 vertical levels
(lowest ~9m, one level each 10 m below 50 m; top = 10hPa)
Initial and boundary conditions:
LMDZ4

9. MAR validation : Dome C (ECMWF forcing)
Surface air temperature
over Dome C, East Antarctica
Model validation shows which processes the models represent correctly and which not and can show us which changes must be done in the model.
Validation of MAR over Dome C showed that the cloud scheme has to be tuned in order to correctly represent synoptic-scale variability in surface energy budget and temperature. Here red curve is from the model with adjusted cloud scheme which shows a much better fit with the observed values in black compared to the model with the old cloud scheme. Thus cloud scheme has to be modified to be able to simulate sfc radiative budget and temperature.
Currently I am also doing MAR validation over South Pole together with Michael Town and Hubert Gallée.
Old notes:
MAR validation over Dome C showed that small changes in cloud scheme (in this case solid line shows simulation where the lack of the ice/water content in the tropospheric clouds is compensated by including part of the precipited snow in the radiative scheme
Gallée and Gorodetskaya, Clim Dyn 2008

10. Model validation : South Pole (ECMWF forcing)
Power spectrum (units2/time)
MAR simulates well synoptic-scale variability in temperature and wind speed. However, not in clouds
Town, Gorodetskaya, Walden, Warren, in prep

11. Snow accumulation, mm.w.e
Snow accumulation at South Pole (MAR forced with ERA-40)
warm events
PSCs
Snow accumulation, mm.w.e
54%
24% 7% 4%
11%
Gorodetskaya, Town, Gallée, in prep
Integrated snow, mm.w.e
1994

12. MAR forced with LMDZ vs LMDZ itself :
MAR - larger amplitude!
r=0.6

13. Annual mean precipitation: MAR(lmdz forced) - LMDZ
LMDZ:
only snow fall
(no erosion)
MAR:
precip-erosion (blowing snow
parameterization)
mmwe

14. Surface mass balance: MAR (lmdz forced) 1982
mmwe
Simulates the typical distribution pattern with a maximum over AP. Note: LMDZ showed the maximum over Mary Byrd Land which is much smoothed in MAR (moderate precip mmwe (no direct comparison to observed values yet but expecting a better perfomance oer this area).
Strong feature: mass removal from the coastal areas. Strong erosion!

15. SMB components: MAR (lmdz forced) 1982
Snow fall minus erosion
Sublimation/deposition
Blowing snow flux
SMB components: MAR (lmdz forced) 1982
Melt
units: mmwe

16. SMB changes: from 1982 to 2082 Diff: 2082-1982 Ratio: 2082/1982
MAR forced with LMDZ
SMB changes: from 1982 to 2082
Ratio: 2082/1982
mmwe

17. Relative annual mean precipitation change:
LMDZ (IPSL): /
MAR (lmdz forced):
2082 / 1982
Some areas - similar trends however obvious differences (note: MAR is for one year while LMDZ is a climatology). MAr - much more pronounced (some places double or triple increase in precip). Also in MAR - some areas along the coast with negative values of accumulation due to precipitation (removal of snow due to erosion) now have positive accumulation (white areas = negative values).
Similarities: increased of precipitation over the major ice shelves and along the coasts. The pattern might be related to SIC decrease in the Weddell Sea -> increase in lee cyclogenesis and increase of precip further down the cyclone passage (while the Ronne/Filchner ice shelf is more affected by teh cold outflow from the EAIS)
Differences: LMDZ shows overall decrease in P in Mary Byrd Land, and MAR shows a slight increase (for 1982).
Krinner et al. 2007

18. Annual mean surface temperature change: 2082-1982
MAR forced with LMDZ
Annual mean surface temperature change:
Precipitation change:
2082/1982 ratio
The temperature and precipitation changes are related: the areas with increased precipitation are associated also with a strong increase in annual mean temperatures. Alarmingly large increases in surface temperature are predicted over the large ice shelves - Ross and Filchner/Ronne.

19. Annual mean sea ice concentration change LMDZ [2081-2100] - [1981-2000]%
Krinner et al. 2007

20. Conclusions Modeling Antarctic surface mass balance and
precipitation in particular is challenging...
LMDZ and MAR : reasonable performance
High spatial variability in the future changes
in SMB and temperature simulated by LMDZ and
MAR forced with LMDZ
MAR: local differences compared with LMDZ
(blowing snow parameterization => snow redistribution,
larger amplitude synoptic-scale variability in temperature,
humidity and precip)
Different spatial pattern in future T and precip predicted
for the end of 21st century compared to recent changes
Gorodetskaya, Gallée, Krinner MOCA-09, Montreal

21. Thank you! ? ? Comments welcome: iragor@lgge.obs.ujf-grenoble.fr
1982->2082 ?
1982->2082 ?