1. Irina Gorodetskaya, Michael S. Town, Hubert Gallée Laboratoire de Glaciologie et Géophysique de l’Environnement, Grenoble,France EGU, Vienna 23 Apr. 2009 Mechanisms behind synoptic-scale variability in South Pole meteorology from observations and a regional model

2. acknowledgements: Gerhard Krinner for support and discussions Von P. Walden for providing computer time and space Stephen G. Warren for antarctic cloud discussions Ells Dutton and Tom Mefford of NOAA-GMD, and BSRN for radiation and meteorology data and advice. Gorodetskaya, Town, Gallée, LGGE : EGU 2009

3. importance of synoptic activity over Antarctica data sets and model description the climate of the South Pole model evaluation: wavelets cluster analysis conclusions Gorodetskaya, Town, Gallée, LGGE : EGU 2009 Outline

4. 1911 19601970198019902000 1950 1957 19752003 surface meteorology/observations radiosondes radiation accumulation clouds snow temperatures NOAA CMDL/GMD South Pole climate data set: A review See poster M. Town and V. Walden, Session AS2.4, XY105

5. 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 1983 + improvements of Meyers et al. 1992 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) FSFS FSFS FLFL T4T4 H Lat H Sen Snow H Melt H Freez H Cond Tsfc Percolati on Liquid water             Blowing snow coupling to sea ice, land ice, vegetation...  Horizontal resolution 80 km  33 vertical levels (lowest ~9m, one level each 10 m below 50 m; top = 10hPa)  Initial and boundary conditions: ECMWF ERA-40 Modèle Atmosphérique Régional (MAR) Gorodetskaya, Town, Gallée, LGGE : EGU 2009

6. The climate of the South Pole altitude = 2835 m accumulation rate = 8 cm yr -1 mean temperature = -50 o C Gorodetskaya, Town, Gallée, LGGE : EGU 2009

7. Sfc air temperature MAR. ERA40. South Pole. 1994 a..-65 o C..-45 o C Gorodetskaya, Town, Gallée, LGGE : EGU 2009

8. Importance of synoptic activity over Antarctic interior Time series of the five snow accumulation events close to the South Pole (86 0 S, 46 0 W) from acoustic depth gauge Braaten 2000 Normalized w.e. Accumulation (10 -3 m) Gorodetskaya, Town, Gallée, LGGE : EGU 2009

9. Importance of synoptic activity over Antarctic interior The 700hPa height and 500hPa wind field at 1200 UTC on Nov 5, 1997 Noone, Turner, Mulvaney 1999 Gorodetskaya, Town, Gallée, LGGE : EGU 2009

10. Directional distribution of hourly near surface winds during warm and cold events Isobaric temperature advection when 300 hPa wind is from SW or NW (warm events) and from SE (cold events) Neff, JGR (104) 1999 Warming events Cooling events Down-slope (“East”)Along-slope (“North”) WarmingCooling SE SW NW Thermal advection ( 0 C/day)Direction Class Intervals Number in interval Height, m Gorodetskaya, Town, Gallée, LGGE : EGU 2009

11. Convolve wavelets of increasing size with time series to obtain scaling coefficients. T(a,b) = w(a) x(t)  dt Wavelets applied to time series: t-b a power spectrum time b a T(a,b) Wavelets give information in temporal and frequency domains. Gorodetskaya, Town, Gallée, LGGE : EGU 2009

12. Model validation : wavelet analysis Power spectrum (units 2 /time) Gorodetskaya, Town, Gallée, LGGE : EGU 2009

13. Variables measured at South Pole:  Sfc temperature  Water vapor pressure (from frost point)  Sfc wind speed  downwelling LW flux  downwelling SW flux 6 hour time step, 1994 5 variables... Cluster analysis applied to time series: Gorodetskaya, Town, Gallée, LGGE : EGU 2009 Sfc air temperature amplitude is good in MAR (both synoptic and seasonal) Wind speed underestimated during some warm events Increased humidity and LW fluxes during warm events in obs and MAR

14. Variables simulated by MAR:  Sfc temperature  Sfc pressure  tropospheric water vapor  downwelling LW flux  downwelling SW flux  U,V near surface  U,V at 300 hPa  tropospheric cloud liquid  tropospheric cloud ice  stratospheric cloud ice 6 hour time step, 1994 Cluster analysis applied to time series: 12 variables... Gorodetskaya, Town, Gallée, LGGE : EGU 2009

15. MAR : 6 meteorological regimes T air, 0 C RadTrop Hum Trop Clds Strat Clds Sfc wind 300 hPa wind Cold -60 - - - Warm-I -40LW - Warm-II -45.. -50 LW - Warm-III -40.. -60 LW - Summer -20.. -40 SW LW - - E NWNE E E SW SE NWN SES E SW... Gorodetskaya, Town, Gallée, LGGE : EGU 2009 7% 24% 54% 11% 4% Accum, %

16. warm events Snow accumulation, mm.w.e Integrated snow, mm.w.e Snow accumulation Gorodetskaya, Town, Gallée, LGGE : EGU 2009

17. Conclusions III. warm events correlated with high stratospheric ice content together with slight increase in tropospheric moisture content 7% snow accumulation Gorodetskaya, Town, Gallée, LGGE : EGU 2009  Modèle Atmosphérique Régional (MAR): shows good skill in synoptic-scale simulations  Cold events are more or less similar: - low tropospheric humidity, clear sky, low downwelling LW flux - NE-E near surface wind (“inversion” wind) - weak SE wind at 300 hPa 11% snow accumulation  Warm events happen for a variety of reasons: I. warm air advection from W-SW (West Antarctica) with increase in tropospheric humidity and tropospheric cloud liquid 54% snow accumulation II. warm air advection from N-NW (Weddell Sea) - slight increase in tropospheric moisture content - no tropospheric clouds but stratospheric clouds form 24% snow accumulation

18. Plans Gorodetskaya, Town, Gallée, LGGE : EGU 2009  Extend cluster analysis to the entire period (1994-2000)  Upper air charts for each type of warm event