Articles | Volume 17, issue 12
https://doi.org/10.5194/tc-17-5061-2023
https://doi.org/10.5194/tc-17-5061-2023
Research article
 | 
30 Nov 2023
Research article |  | 30 Nov 2023

A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR

Marco Tedesco, Paolo Colosio, Xavier Fettweis, and Guido Cervone

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Cited articles

Alexander, P. M., Tedesco, M., Fettweis, X., van de Wal, R. S. W., Smeets, C. J. P. P., and van den Broeke, M. R.: Assessing spatio-temporal variability and trends in modelled and measured Greenland Ice Sheet albedo (2000–2013), The Cryosphere, 8, 2293–2312, https://doi.org/10.5194/tc-8-2293-2014, 2014. 
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, 1992. 
Collection 2 Landsat 8-9 OLI: (Operational Land Imager) and TIRS (Thermal Infrared Sensor) Level-2 Science Product Digital Object Identifier (DOI) https://doi.org/10.5066/P9OGBGM6, 2023. 
Colosio, P., Tedesco, M., Ranzi, R., and Fettweis, X.: Surface melting over the Greenland ice sheet derived from enhanced resolution passive microwave brightness temperatures (1979–2019), The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, 2021. 
De Ridder, K. and Galleìe, H.: Land Surface-Induced Regional Climate Change in Southern Israel, J. Appl. Meteorol., 37, 1470–1485, 1998. 
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Short summary
We developed a technique to improve the outputs of a model that calculates the gain and loss of Greenland and consequently its contribution to sea level rise. Our technique generates “sharper” images of the maps generated by the model to better understand and quantify where losses occur. This has implications for improving models, understanding what drives the contributions of Greenland to sea level rise, and more.