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

Raoult, Nina; Charbit, Sylvie; Dumas, Christophe; Maignan, Fabienne; Ottlé, Catherine; Bastrikov, Vladislav

doi:https://doi.org/10.5194/tc-17-2705-2023

Articles | Volume 17, issue 7

https://doi.org/10.5194/tc-17-2705-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-17-2705-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 7

Research article

|

12 Jul 2023

Research article |

| 12 Jul 2023

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

Nina Raoult, Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, and Vladislav Bastrikov

Data sets

MODIS Greenland albedo Jason E. Box https://doi.org/10.22008/FK2/6JAQPK

AWS one boom tripod Edition 3 Robert S. Fausto, Dirk Van As, and Kenneth D. Mankoff https://doi.org/10.22008/FK2/8SS7EW

Model code and software

ORCHIDEE-ICE_AlbedoOptimisation IPSL Data Catalogue https://doi.org/10.14768/e59644bf-2ab2-4826-8409-7ec83f9c56e3

Short summary

Greenland ice sheet melting due to global warming could significantly impact global sea-level rise. The ice sheet's albedo, i.e. how reflective the surface is, affects the melting speed. The ORCHIDEE computer model is used to simulate albedo and snowmelt to make predictions. However, the albedo in ORCHIDEE is lower than that observed using satellites. To correct this, we change model parameters (e.g. the rate of snow decay) to reduce the difference between simulated and observed values.