Foehn Winds in the McMurdo Dry Valleys: Implications for climate variability and landscape evolution

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Foehn Winds in the McMurdo Dry Valleys: Implications for climate variability and landscape evolution Johanna Speirs and Hamish McGowan Climate Research Group, School of Geography, Planning and Environmental Management University of Queensland, Australia and Daniel Steinhoff and David Bromwich Polar Meteorology Group, Byrd Polar Research Center Ohio State University, USA 1

outline 1. INTRODUCTION Physical setting Background 2. FOEHN VARIABILITY Intra- and inter-annual frequency DATA SOURCES: Effects on temperature regime Influence of SAM and ENSO 3. LANDSCAPE PROCESSES Thermal inputs Melt and stream discharge Snow persistence Automatic weather station (AWS) data: McMurdo LTER program Numerical model products: Antarctic Mesoscale Prediction System (AMPS) Japanese Reanalysis Project (JRA25) Satellite imagery: Landsat 7 ETM+ 2

physical setting Click to edit Master text styles Second level Third level Fourth level Fifth level McMurdo Dry Valleys (MDVs): Largest ice-free area in the Antarctic ~4,800 sq km Three large NE - SW trending valleys Mountain ranges ascending ~2000m above valley floor Slow-moving glaciers Perennially ice-covered lakes Summer meltwater streams Diverse microbial and algal communities Extensive sedimentary deposits 3

background foehn mechanism Sea Level Pressure 24 May 2007 Backward trajectory 24 May 2007 Cross section 24 May 2007 Large cyclones in the Ross Sea region produce strong pressure gradients Flow is forced to cross topographic barriers of MDVs, deflected into valleys Prominent large-amplitude mountain wave pattern develops: levels > 8 km asl Speirs, J., Steinhoff, D., McGowan, H., Bromwich, D., and Monaghan, A. 2010: Foehn Winds in the McMurdo Dry Valleys, Antarctica: The origin of extreme warming events. Journal of Climate, 23 (13), 3577 3598. 4

foehn variability SUMMER WINTER

foehn variability Identification of foehn in AWS records: Foehn criteria identifies onset of foehn events Wind speed > 5 m/s Wind direction from SW Warming > +1 C / hour RH > 5 % / hour Foehn day : Day that has identified foehn onset and foehn conditions > 6 hours AMPS Backward trajectories for 172 foehn days 2006-2007 at Lake Bonney AMPS SLP and near-surface wind vector composites 6 (2006-2007) for: (a) Non-foehn days, (b) Foehn days

foehn variability Lake Hoare (TH), Lake Bonney (TB) Foehn frequency highest in winter Lower in summer due to: reduced cyclonic activity in the Ross Sea (Simmonds et al. 2003) Lake Vanda (WV), Lake Vida (VV) increased frequency of strong easterly sea breeze prevents grounding of foehn? Reduced foehn in Victoria Valley due to cold air pooling (Doran et al. 2002) prevents grounding of foehn Large variability in foehn occurrence Monthly mean, min and max foehn days for 1996 and 2008. 7

foehn variability Foehn effect on monthly temperature anomalies Monthly standardised foehn anomaly and standardised air temperature anomaly for Lake Hoare. Data is smoothed with a 5 month moving average. Foehn winds explain >70% of the variability in monthly mean air temperature Foehn days = 58 % of days with a mean daily air temperature > 0 C 8

foehn variability What drives foehn variability? Cyclone frequency and intensity SAM and ENSO known to affect MSLP and cyclonic activity in the region Foehn Days Air Temp. DJF MAM JJA SON DJF MAM JJA SON SOI SAMI (NOAA CPC) (Marshall 2003) R +0.3709-0.2963 +0.0077 +0.0914-0.0868-0.0703 +0.6818 +0.2292 R +0.7482-0.7724-0.3564 +0.0827 +0.0086-0.4986-0.0965 +0.2921 May expect positive relationship with SOI and SAMI +ve SOI (La Nina), Amundsen Sea Low (e.g. Cullather et al. 1996), Foehn +ve SAM, cyclones around Antarctica (e.g. Pezza et al. 2009), Foehn Positive relationship seen in summer foehn and SAM Positive relationship with winter air temperature and SOI Significant for landscape processes Negative relationship with autumn foehn and SAM 9

foehn variability JRA-25 MSLP difference plots 1980-2008 -ve SAMI minus +ve SAMI seasons. Zero line in bold, negative MSLP shown by dashed line only evident for MAM, plots are mainly positive i.e lower MSLP during +ve SAM Large area of pressure differences during SAM summers Likely associated with changes in cyclone frequency Cause for relationship between SAM and foehn winds in summer 10

landscape processes 2001/02 (+ SAM) High stream discharge 32 Foehn Days Ave. Temp -1.86 C 2002/03 (neutral SAM) Low stream discharge 19 Foehn Days Ave. Temp -3.99 C Average daily air temperature and foehn days (red dots) for summer 2001/02 (top) and 2002/03 (bottom). Landsat 7 ETM+ image of MDV region 21Nov 2001 (top) and 17-Nov 2002 (bottom). Snow persists longer into the 2002 summer season with less foehn heating. TIR images 28-Dec 2001 (top) and 31-Dec 2001 Discharge (L/s) of the Onyx River, Wright Valley during 2001/02 (top) and 2002/03 (bottom) summers. 11

landscape processes Small changes in Antarctic circulation and foehn frequency can produce dramatic changes in the climate-landscape system Effects of foehn winds outlive the duration of the event Significant lag effects present in meteorological variables (a) Air temperature (b) Soil temperature (c) Sublimation/evaporation Lag effects of foehn days on meteorological variables in the McMurdo Dry Valleys 1999-2008: - Negative (-1,-2) = days prior to a foehn day. - Positive (+1,+2,+3,+4) = days after a foehn event. 12 - Other = days not occurring in the vicinity of a foehn day.

landscape processes Stream discharge (a) Taylor Valley (b) Wright Valley The influence of foehn on average daily stream discharge for melt-water streams Stream discharge during foehn days in the Taylor Valley is 250% of non-foehn days 680% for the Onyx River in the Wright Valley The 2001/2002 summer known to be a season of particularly high levels of flow [and foehn]. Even when this summer season is removed, foehn days still contribute to 225% of non-foehn flow. Foehn wind regime played a pivotal role in creation and removal of large liquid lakes occupying valley floors in the LGM and early Holocene (e.g. Lyons et al., 1998; Hall et al., 13 2001)

summary & implications Dense AWS network + high resolution modelling allows important aspects of the MDVs climate system to be uncovered Foehn variability caused by: - Variability in synoptic circulation - cyclone tracks in the Ross Sea region - ENSO/SAM signal in MSLP and cyclone activity in Ross/Amundsen Seas - Intraseasonal variability show MJO forcing (Steinhoff et al. in prep) Foehn is a mechanism for tropical and hemispheric influences in the MDVs Future changes in these signals holds important repercussions for the MDVs climate Foehn winds are a vital part of the MDVs environmental system Driver of landscape variability and change 14

Upcoming field work 2011/2012 and 2012/2013 15

Upcoming field work 2011/2012 and 2012/2013 16

acknowledgments McMurdo LTER Program for use of AWS data Steinhoff and Bromwich s contribution are supported by NSF grant ANT-0636523 Financial support of UQ, School of GPEM Speirs, J., Steinhoff, D., McGowan, H., Bromwich, D., and Monaghan, A. 2010: Foehn Winds in the McMurdo Dry Valleys, Antarctica: The origin of extreme warming events. Journal of Climate, 23 (13), 3577 3598. DOI: 10.1175/2010JCLI3382.1 Speirs, J., McGowan, H., Steinhoff, D., and Bromwich, D. 2011: Regional climate variability driven by foehn winds, McMurdo Dry Valleys, Antarctica. International Journal of climatology (Submitted.) Speirs, J., and McGowan, H. 2011: Foehn winds in a polar landscape: a driver of environmental change. Journal of Geophysical Research (In prep.) Johanna C. Speirs, University of Queensland, School of GPEM, Brisbane 4072, QLD, Australia. Email: j.speirs@uq.edu.au 17