1. The role of atmospheric rivers in anomalous snow accumulation in East Antarctica European Geosciences Union General Assembly 2014 Vienna | Austria | 27 April – 02 May 2014 Irina Gorodetskaya, Nicole Van Lipzig, Kim Claes (KU Leuven, Belgium) Maria Tsukernik (Brown University, USA) F. Martin Ralph (UCSD/Scripps, USA) William Neff (NOAA, USA)

2. A few strong snowfall events over Dronning Maud Land (DML) in 2009 and 2011 have been responsible for an anomalously high mass load over the East Antarctica counterbalancing the negative total mass trend over the Antarctic ice sheet (Boening et al. 2012, King et al. 2012). Boening et al. 2012 Introduction GRACE mass average over 30W- 60E, 65S-80S Integrated net precipitation (ERA- Interim) CloudSat accumulated snowfall

3. 2009 snowfall amount was unprecedented since 1979 and resulting surface mass balance anomaly was measured the first time for at least 60 years. Lenaerts et al. (2013) Introduction

4. Data and methods: 1. Accumulation from AWS Daily snow accumulation near the Princess Elisabeth (PE) base (Dronning Maud Land, 72 o S, 23 o E, 1420 m asl (Gorodetskaya et al. 2013) The AWS accumulation data are compared to the 180-km long accumulation stake line from PE to the coast installed within GLACIOCLIM-SAMBA program (Favier et al. 2012). PE Glacioclim stake line

5. PE located at the ascent to the E Antarctic plateau (orographic precip!) x PE Density of cyclones in winter 1420 m asl. Pattyn et al. 2009 Princess Elisabeth base location PE (Utsteinen) 180 km MODIS image of the Sør Rondane Mountains Noone et al 1998

6. Data and methods: 2. Snowfall rate from radar  Snowfall rate is derived from the Micro Rain Radar 2 (MRR) reflectivity vertical profiles, installed within cloud-precipitation observatory at PE Radar Ze derived using method by Maahn and Kollias (2012) Snowfall rate uncertainty – using Z-S relationships for dry snow from Matrosov (2007) Metek’s MRR 24 GHz precipitation radar HYDRANT observatory at PE

7. Data and methods: 3. IWV and MT from ERA-Interim Integrated water vapor (IWV), saturated IWV and total moisture transport (MT) are calculated using the European Centre for Medium- range Weather Forecasting (ECMWF) Interim (ERA-Interim) re-analysis data interpolated on 0.25ºx0.25º horizontal grid Input fields: -vertical profiles of T, q, U, V -500 hPa geopotential heights -daily sea ice concentration -surface geopotential for topography Equations: q sat (p) = f(T(p)) (Clausius-Clap)

8. Daily snow accumulation (black line) and snowfall rate (blue bars) at PE during 2009- 2012. Periods with missing snowfall data are indicated by blue crosses and thick line. 2009 and 2011: Two anomalously high accumulation years (yea total 230 and 227 mm w.e.) Compare: long-term stake measurements in the vicinity of Sør Rondane mountains => year total accumulation ~50-150 mm w.e. (Takahashi et al. 1994) 230 mm w.e.227 mm w.e.23 mm w.e. 52 mm w.e.

9. Daily snow accumulation (black line) and snowfall rate (blue bars) at PE during 2009- 2012. Periods with missing snowfall data are indicated by blue crosses and thick line. Two major accumulation events during 2009 and 2011  18-19 May 2009 (51 mm w.e. => 22 % to the total 2009 accumulation)  14-16 Feb 2011 (48 mm w.e. => 21 % to the total 2011 accumulation ) 230 mm w.e.227 mm w.e.23 mm w.e. 52 mm w.e. 18-19 May 14-16 Feb snow fall!

10. Radar reflectivity used to estimate snowfall during high accumulation event in 2011 dBz 14 Feb15 Feb16 Feb 17 Feb18 Feb Height agl, m Hours

11. Integrated Water Vapor derived from SSM/I  a narrow band of enhanced IWV from Indian Ocean towards East Antarctica  SSM/I is used for identification of atmospheric rivers in middle latitudes and tropics  SSM/I is available only over ocean and shows falsely high values over sea ice, thus difficult to recognize if the band of IWV reached the ice sheet  => we use ERA-Interim to calculate IWV and MT Figure courtesy of Gary Wick, NOAA

12. ARs – important for the coastal precipitation in mid latitudes: California: ARs frequently => severe precipitation events causing floods (Ralph et al. 2006, Bao et al. 2006) ARs contribute up to 50% of the state's total annual precipitation (Dettinger et al. 2011) South American Andes ARs => most of the heavy orographic precipitation (Viale et al. 2011) Europe: Recent flooding and extreme precipitation in Europe was linked to AR events (Lavers and Villarini, 2013) Ralph et al 2004: definition of AR using IWV as proxy and determining AR boundaries

13. Identifying Antarctic ARs: 1) Maps of IWV and IWV sat are calculated for each day 2009-2012 cm grey line = daily mean 50% sea ice concentration

14. 2) IWV threshold to find excessive IWV within ARs is calculated for each latitude:  Instead of using a fixed threshold of 2 cm suitable for mid-latitudes (Ralph et al. 2004), our IWV threshold varies with latitude depending on the temperature and saturation capacity AR coeff determines relative strength of an AR (= 0.2 in this study) Identifying Antarctic ARs:

15. 3) Find excessive IWV based on IWVthresh: 4) Identify ARs with the potential to influence DML and neighboring sectors (20W-90ºE):  identify location where band of excessive IWV hits the coast : (longitude dependent) => average (L mean )  define sector within which AR should be located: L mean +/- 15º longitude, lat coast + 20º latitude  if IWV>IWV thresh continuously at each latitude within this sector => AR cm Identifying Antarctic ARs:

16. Atmospheric river is identified and is plotted using IWV (colors) and total MT (arrows) + 500 hPa geopotential height 19 May 2009

17. Atmospheric river is identified and is plotted using IWV (colors) and total MT (arrows) + 500 hPa geopotential height 19 May 200915 Feb 2011

18. x Maps courtesy of Matthew Lazzara, U Wisconsin-Madison 18 May 2009 18 UTC Water vapor composite based on passive satellite imagery

19. Snow height and snowfall rate during 2009-2012

20. Compare 2009 and 2011 to longer time series of total meridional moisture fluxes towards DML  2009 and 2011 years stand out as anomalous during 1979-2012 period Meridional moisture flux (ERA-Interim, seasonal cycle removed) towards the East Antarctic ice sheet averaged over 50-72ºS, 0-90ºE sector Meridional moisture flux, kg m -1 s -1 2009 2011 PE measur ements

21. Conclusions A new definition of ARs influencing Antarctic precipitation  This is the first study of the role of ARs in high accumulation events over the Antarctic ice sheet Atmospheric rivers are responsible for the most extreme among high accumulation events (between 24 and 51 mm w. e./event) and contributed 74%, 80% and 46% to the total annual accumulation during 2009, 2011, and 2012, respectively. MRR measurements in 2011 and 2012 confirm that high accumulation events are related to extreme snowfall rates. In total within 20ºW-90ºE longitudinal sector there were identified 13, 8, and 3 ARs during 2009, 2011, and 2012, and only a part of them was associated with high accumulation at PE => look at other stations in DML during these events? modeling of the events (spatial distribution of snowfall) Atmospheric rivers reaching the Antarctic coast within 7-60ºE longitudinal sector A few extreme accumulation events High accumulation in DML (at PE) in 2009 and 2011

22. The most extreme accumulation events (24-51 mm w. e./event) are found to be associated with ARs Table: all high Acc events with ARs during 2009-2012