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Challenges of Modelling Surface Mass Balance

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Challenges of Modelling Surface Mass Balance 9/15/16 Advanced Training Course on Remote Sensing of the Cryosphere Leeds (UK), 12-16 September 2016 Challenges of modelling surface mass balance Michiel van den Broeke Institute for Marine and Atmospheric Research, Utrecht University (IMAU) How do we define surface mass balance (SMB)? Here: the sum of surface and internal mass balance (climatic mass balance or firn mass balance) Ligtenberg, PhD thesis, 2014 1 9/15/16 Mass Balance = Surface Mass Balance – Discharge MB = dM/dt = SMB – D SMB is challenging: not one, but three balances! Ice sheet mass balance (MB) MB = Surface mass balance – Discharge [Gt yr-1] Surface mass balance (SMB) SMB = Precipitation – Sublimation – Runoff - Erosion [Gt yr-1] LiQuid water balance (LWB) Runoff = Rain + Condensation + Melt – Refreezing – Retention [Gt yr-1] Surface energy balance (SEB) -2 M = SWnet + LW net + H + L + Gs [W m ] J. Paul Getty Museum 2 9/15/16 Combine EO, in situ observations and SMB modelling Remote sensing Firn model In situ observations Evaluation Calibration Spatial/temporal extension Climate model GRACE mass trends (2003-2012) Courtesy: Bert Wouters 3 9/15/16 13 years of ice sheet mass changes from GRACE SMB: snowfall driven SMB: snowfall and runoff driven Antarctic ice sheet Greenland ice sheet Velicogna and others, 2015 The ‘simpler’ case: Antarctica NASA/MODIS 4 9/15/16 Added value of SMB modelling: a case study for Antarctica Mass changes in 2009 from GRACE Martin Horwath Added value of SMB modelling: a case study for Antarctica Elevation changes in 2009 from Envisat Martin Horwath 5 Future SMB of Antarctica is forced using fields of temperature, specific humidity, trade-off between computational expense and spatial detail; zonal and meridional wind components, and surface pres- doubling the grid resolution would multiply the computa- sure from either GCM or re-analysis output. Relaxation of tional time by a factor 10. Moreover, the annual integrated RACMO2 prognostic variables towards external forcings is SMB of the AIS at 55 km resolution (Van de Berg et al. restricted to the boundary relaxation zone (Fig. 1). External 2006) is similar to that at 27 km resolution (Lenaerts et al. forcings are updated every six hours and linearly interpo- 2012a). For the scenario runs, the largest uncertainty there- lated in time to yield accurate values in between. Sea fore derives not from the model resolution but from the surface temperatures and sea-ice extent are also prescribed chosen forcing model and scenario. Given this information, from the forcing model. The version of RACMO2 used for and the fact that a 27 km resolution run is ten times as this study includes a snow model that calculates tempera- expensive as a 27 km run, we chose 55 km as final resolu- ture, density and meltwater processes (percolation, reten- tion. The model topography, grid resolution and lateral tion, refreezing and runoff) in the snow (Ettema et al. relaxation boundary of the domain are shown in Fig. 1. 2009), and an improved albedo scheme, where the snow For the period 1980–1999, a RACMO2 reference sim- albedo depends on snow grain size (Kuipers Munneke ulation, forced by ERA-40 re-analysis data from the et al. 2011). For this study, contributions from drifting European Centre for Medium-Range Weather Forecasts snow processes have not been included, because the (Uppala et al. 2005), was performed in order to check the module of Lenaerts and Van den Broeke (2012) was not yet reliability of the GCM-forced RACMO2 simulations. In 9/15/16 fully implemented when we started the simulations. this paper, ERA-40 has been used as forcing instead of its For contemporary climate studies of the AIS (1–30 years), successor ERA-Interim (Dee and et al. 2011), since the RACMO2 has been run on grids with 27 and 5.5 km hori- latter only covered the period 1989–2009 at the time the zontal resolution (Lenaerts et al. 2012a, b). However, for the RACMO2 simulations were started. Other RACMO2 number of simulation years considered here (660 years in simulations forced by re-analysis data (ERA-40 or ERA- total), a horizontal resolution of 55 km is considered a good Interim) yielded realistic SMB results over Antarctica Fig. 1 Map of Antarctica showingRegional the model domain, the boundary relaxation zone (dottedclimate model area) and model topography in meters above sea level domain 27 km resolution 123 Modelled 3-hourly precipitation Run: RACMO2.3/ANT Resolution: 27 km Courtesy: Melchior van Wessem 6 9/15/16 Ekstrom & Automatic Weather Stations Ekstrom Shelf Ice !(!( Halvfarryggen Atka & !( !( Antarctica - 2016 Atka Bay !( Troll Soerasen Camp Maudheimvida !( !( Molodeznaya Joinville Is Nordenskiold Utsteinen !( !( Gerlache Strait !( Kohnen Base Neko Harbor Mizuho AWS 17 *# Cierva Cove AWS 14 Larsen Ice Shelf !(!( !. Halley V JASE2007*# Arelis Amsler Island *#*# *# Relay Station Bonaparte Pt *#!. !( !( AWS 18 Windy *# !( AWS 1 Inset Map A Hugo Is !( !. *#!( Dome Fuji (JPN) Bisco Island !( Butler Is Dome Fuji Whitlock *# *# Dismal Is !( Site 8 Filchner !( !( !( *# Baldrick AGO-3 Fossil Bluff Limbert $+ !( Druznaja-4 Whoop !( Korff Ice Rise Whoop China !( PANDA-North !( Lucia !( Sky-Blu !( Manuela $+AGO-2 Eagle !( Virginia *#!( Dome A PANDA-South*# !( Mt Brown Eneide !(!( "/ Union Glacier !( Rita !( Maria Austin*# *# Henry "/ Thiel Mountains *# Jang Bogo Zoraida Nico AGO-4 !( !( *# Penguin !( Kathie# Kominko- Thurston Island * Lola *# *# Slade (WAIS) *#Theresa Evans Knoll *# Erin AGO-1 !( *# Harry*# $+ Lindsey Island *# Sabrina Alessandra !( Byrd *# *# Elizabeth *#*# Emma Haupt Snyder Bear Peninsula AGO-5 Concordia Rocks *# Dome C II Nunatak Janet *# Siple Dome *# Lettau Elaine $+ !( *# Skinner Saddle Dome C *#!(!( DC N Casey Schwerdtfeger !( Marilyn !( !(!(!( Skiway Silvia!( Dome C (FRA) !( 0 50 km *# *# !( Darwin Gl !( 0 500 km Margaret Gill*# *# Central Valley Law Dome Summit/A Cape !( Vito *#*#!( Poinsett Russkaya *#*#*#*#$1*#$1!(!(!.!. *#$1$1*#$1*#$1$1$1*#!(.$1!.(!.(!!( !( Giulia Wilkins Runway *# *# !( West 4m / East ICAO *# Alexander Inset Map B See Inset Map B *# D-85 *# !( Modesta Tall Tower *#!( !(!( !( Sofia-B !( !( Irene Minna Bluff See Inset Map A !( !( *# !( Paola D-47*# !( Minna Bluff *# D-0 Linda Cape Hallett *# *#!( *#*# D-3 # Herbie Alley N Miers Valley Possession Is D-10 Emilia * !( Port Martin D-17 White Is !( Leningradskaya Garwood Valley !. 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Other US !( Japan Coastline: ADD v4.1, 2003; Cartography: April 2016 Sam Batzli, SSEC, University of Wisconsin-Madison; Funding: National Science Foundation ANT-0944018 University of Wisconsin, Madison Observation-based accumulation map kg m-2 y-1 Circles: ≈ 1200 obs. Data: Arthern and others, 2006 7 9/15/16 Modeled Antarctic surface mass balance kg m-2 y-1 Run: RACMO2.1/ANT Period: 1979-2011 Resolution: 27 km Circles: ≈ 1200 obs. Data: Lenaerts and others, 2012 Compare SMB to GRACE mass anomalies Filter SMB field from regional climate model RACMO to same resolution as GRACE Martin Horwath 8 9/15/16 Compare modelled snow depth change to altimetry Convert snowfall anomalies to firn thickness change, using a firn model Martin Horwath Compare modelled snow depth change to altimetry Dronning Maud Land Amundsen Sea embayment Convert snowfall anomalies to firn thickness change, using a firn model Martin Horwath 9 9/15/16 Dronning Maud Land, East Antarctica a) SMB from regional climate model b) Cumulative SMB anomaly vs. GRACE Lenaerts and others, 2013 Compare modelled snow depth change to altimetry Dronning Maud Land Amundsen Sea embayment Convert snowfall anomalies to firn thickness change, using a firn model Martin Horwath 10 9/15/16 Amundsen Sea embayment, West Antarctica a) SMB and D b) MB = SMB – D c) Cumulative MB Sutterley and others, 2014 The ‘harder’ case: Greenland NASA/MODIS 11 9/15/16 13 years of ice sheet mass changes from GRACE SMB: snowfall driven SMB: snowfall and runoff driven Antarctic ice sheet Greenland ice sheet Velicogna and others, 2015 SMB is challenging: not one, but three balances! Ice sheet mass balance (MB) MB = Surface mass balance – Discharge [Gt yr-1] Surface mass balance (SMB) SMB = Precipitation – Sublimation – Runoff - Erosion [Gt yr-1] LiQuid water balance (LWB) Runoff = Rain + Condensation + Melt – Refreezing – Retention [Gt yr-1] Surface energy balance (SEB) -2 M = SWnet + LW net + H + L + Gs [W m ] J. Paul Getty Museum 12 9/15/16 Greenland automatic and manned weather stations Adapted from GEUS K-transect, west Greenland S10 NASA/MODIS 13 9/15/16 S5: 500 m asl Greenland surface energy balance S6: 1000 m asl S9: 1500 m asl Station S6 (1000 m asl) S10: 1850 m asl Courtesy: Peter Kuipers Munneke Regional climate model 11 km resolution 14 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | TCD 9, 1177–1208, 2015 Impact of summer (a) (b) snowfall events on GrIS SMB 9/15/16 B. Noël et al. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (c) (d) Title Page Model evaluation: surface energy TCD Abstract Introduction balance 9, 1177–1208, 2015Conclusions References Tables Figures Impact of summer 500 m asl 1000 m asl (a) (e) (b) (f) snowfall events on J I GrIS SMB J I B.
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