Improving modelled albedo over the Greenland ice sheet through parameter optimisation and MODIS snow albedo retrievals

• Published in: The Cryosphere
• Main Authors: Raoult, Nina, Charbit, Sylvie, Dumas, Christophe, Maignan, Fabienne, Ottle, Catherine, Bastrikov, Vladislav
• Other Authors: Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Modélisation du climat (CLIM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Science Partners, Paris
• Format: Article in Journal/Newspaper
• Language: English
• Published: CCSD 2023
• Subjects: [SDU]Sciences of the Universe [physics]; Greenland; Ice Sheet; The Cryosphere
• Online Access: https://hal.science/hal-04172792; https://hal.science/hal-04172792v1/document; https://hal.science/hal-04172792v1/file/tc-17-2705-2023.pdf; https://doi.org/10.5194/tc-17-2705-2023

International audience Greenland ice sheet mass loss continues to accelerate as global temperatures increase. The surface albedo of the ice sheet determines the amount of absorbed solar energy, which is a key factor in driving surface snow and ice melting. Satellite-retrieved snow albedo allows us to compare and optimise modelled albedo over the entirety of the ice sheet. We optimise the parameters of the albedo scheme in the ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) land surface model for 3 random years taken over the 2000-2017 period and validate over the remaining years. In particular, we want to improve the albedo at the edges of the ice sheet, since they correspond to ablation areas and show the greatest variations in runoff and surface mass balance. By giving a larger weight to points at the ice sheet's edge, we improve the model-data fit by reducing the root-mean-square deviation by over 25 % for the whole ice sheet for the summer months. This improvement is consistent for all years, even those not used in the calibration step. We also show the optimisation successfully improves the model-data fit at 87.5 % of in situ sites from the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) network. We conclude by showing which additional model outputs are impacted by changes to the albedo parameters, encouraging future work using multiple data streams when optimising these parameters.