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SUMMARY:High-resolution modelling of polar climates using the regional cli
 mate model RACMO2.3 - Brice Noël (Utrecht University)
DTSTART:20160315T163000Z
DTEND:20160315T173000Z
UID:TALK64998@talks.cam.ac.uk
CONTACT:Poul Christoffersen
DESCRIPTION:Monitoring the current climate in polar regions such as the Gr
 eenland (GrIS) and Antarctic ice sheets (AIS)\, encompasses many limitatio
 ns. Automatic weather stations\, stake sites\, firn and ice cores located 
 all over the accumulation and ablation zones of the GrIS and AIS only meas
 ure point climate conditions\, not necessarily representative of larger ar
 eas. Since the late 50s\, airborne and satellite measurements provide spat
 ially continuous coverage of the ice sheets at relatively low resolutions.
  These limitations can be solved using regional climate models (RCMs)\, co
 vering the entire ice sheets at high spatial and temporal resolutions\, ty
 pically 5 km to 30 km at a hourly-to-daily time scale.  The polar version 
 of the Regional Atmospheric Climate Model (RACMO2) is adapted to specifica
 lly model the surface mass balance (SMB) and energy budget (SEB) over Gree
 nland\, Antarctica and other glaciated regions. RACMO2 incorporates a mult
 ilayer snow module\, interactively coupled to the atmosphere\, that simula
 tes meltwater percolation\, refreezing and runoff\; an albedo scheme based
  on prognostic snow grain size\, and a drifting snow routine\, accounting 
 for interactions between drifting snow\, the surface and the lower atmosph
 ere. RACMO2 has been thoroughly evaluated in many glaciated regions includ
 ing Greenland\, Canadian Arctic\, Svalbard\, Patagonia and Antarctica.\n\n
 Recently\, RACMO2 has been updated from version 2.1 to 2.3. These updates 
 include major modifications in the description of cloud microphysics\, sur
 face and boundary layer turbulence\, and radiation transport. Most notably
 \, the new cloud scheme enables ice supersaturation\, which prolongs the v
 apour phase at low temperatures and delays cloud formation at higher eleva
 tions. Furthermore\, the auto-conversion coefficient\, controlling the con
 version rate of water-vapour into precipitation in convective clouds\, has
  been modified to favour solid at the expense of liquid precipitation. The
  implications of these physics updates on modelled SMB components are disc
 ussed for Greenland (1958-2014\, 11 km) and Antarctica (1979-2014\, 27 km)
 . In addition\, RACMO2.3 performances improve on the previous version 2.1\
 ; the evaluation against observations shows a better agreement for both th
 e GrIS and AIS.\n\nDespite physics improvements\, the current spatial reso
 lution in RACMO2.3 remains too coarse to represent the local variability i
 n SMB components\, especially over narrow glaciated features\, i.e. the An
 tarctic Peninsula (AP)\, the GrIS and surrounding ice caps (GICs). The rel
 atively low-resolution surface elevation prescribed in RACMO2.3 contribute
 s to underestimate topographically-forced precipitation over the mountaino
 us regions of the AP. In Greenland\, underestimated elevation and thus nea
 r-surface temperature result in too low surface melt and runoff at the GrI
 S rough margins. To address these issues\, a high-resolution simulation at
  5 km is carried out over the AP for the period 1979-2014\, allowing for a
  better representation of local precipitation patterns. Another approach i
 s applied in Greenland\, where the data of RACMO2.3 at 11 km (1958-2014) a
 re statistically downscaled to the topography and ice mask of a down-sampl
 ed version of the GIMP DEM at 1 km\, using a daily specific elevation depe
 ndent technique. This method allows to provide more realistic SMB patterns
  over Greenland narrow ablation zones\, marginal outlet glaciers and perip
 heral ice caps\, owing to enhanced runoff at the GrIS margins. These high-
 resolution SMB products are evaluated against ablation/accumulation measur
 ements collected in the AP and Greenland. Finally\, the current GICs contr
 ibution to the total GrIS mass loss is estimated based on the 1 km dataset
  of daily downscaled SMB components. 
LOCATION:Scott Polar Research Institute\, Seminar Room
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