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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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uture 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 !"#$"#% fully implemented when we started the simulations. this paper, ERA-40 has been used as forcing instead of its For contemporary climate studies of the AIS (1–30 years), successor ERA-Interim (Dee and et al. 2011), since the RACMO2 has been run on grids with 27 and 5.5 km hori- latter only covered the period 1989–2009 at the time the zontal resolution (Lenaerts et al. 2012a, b). However, for the RACMO2 simulations were started. Other RACMO2 number of simulation years considered here (660 years in simulations forced by re-analysis data (ERA-40 or ERA- total), a horizontal resolution of 55 km is considered a good Interim) yielded realistic SMB results over Antarctica Fig. 1 Map of Antarctica showingN%'.*&#$) the model domain, the boundary relaxation zone (dotted1$.,#>%),*-%$) area) and model topography in meters above sea level -*,#.& U_)6,)0%(*$/>.*& 123 3*-%$$%- ZI"*/0$H) M0%1.M.>#>.*& N/&=)NX!3VU`ZBXa[ N%(*$/>.*&=)U_)6, =*&+$'#8Q(,'G32%*+(7-"(S'##'0 % !"#$"#% 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 !(!( !. 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Noël et al. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (c) (d) Title Page 3*-%$)%4#$/#>.*&=) (/0+#1%)%&%0'H) TCD Abstract Introduction 2#$#&1% 9, 1177–1208, 2015Conclusions References Tables Figures Impact of summer UFF(0(-#G AFFF(0(-#G (a) (e) (b) (f) snowfall events on J I GrIS SMB J I B. Noël et al. Back Close Full Screen / Esc AUFF(0(-#G(c) A]UF(0(-#G(g) (d) (h) Title Page V*^G(-".(*$2'+#5(BFAU Printer-friendly Version Figure 5.
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