Predicting mean depth and area fraction of Antarctic supraglacial melt lakes with physics-based parameterizations
Abstract Despite the importance of supraglacial melt lakes to the future evolution of polar ice sheets, they are not represented in current large-scale climate and ice sheet models. In this study, we use ICESat-2 satellite surface elevation measurements to show that roughness on the Antarctic Ice Sh...
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Nature Portfolio
2025-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-61798-8 |
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| author | Danielle Grau Azeez Hussain Alexander A. Robel |
| author_facet | Danielle Grau Azeez Hussain Alexander A. Robel |
| author_sort | Danielle Grau |
| collection | DOAJ |
| description | Abstract Despite the importance of supraglacial melt lakes to the future evolution of polar ice sheets, they are not represented in current large-scale climate and ice sheet models. In this study, we use ICESat-2 satellite surface elevation measurements to show that roughness on the Antarctic Ice Sheet surface is largely self-affine. Estimation of ice sheet surface roughness statistics then enables the development of a set of simple mathematical expressions parameterizing the average supraglacial melt lake area fraction and lake depth from statistical fitting of large simulation ensembles of water flow on random, self-affine surfaces. These parameterizations provide predictions that are generally consistent with observations, with some exceptions. Finally, we predict that on large portions of Antarctic ice shelves supraglacial lakes are likely to, on average, stay less than one meter deep and occupy less than 40% of the ice area, absent changes in ice shelf surface roughness. |
| format | Article |
| id | doaj-art-5de8c5e95139404fbd8d4fd2b5d5a1ec |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-5de8c5e95139404fbd8d4fd2b5d5a1ec2025-08-20T03:42:52ZengNature PortfolioNature Communications2041-17232025-07-0116111310.1038/s41467-025-61798-8Predicting mean depth and area fraction of Antarctic supraglacial melt lakes with physics-based parameterizationsDanielle Grau0Azeez Hussain1Alexander A. Robel2School of Earth and Atmospheric Sciences, Georgia Institute of TechnologySchool of Physics, Georgia Institute of TechnologySchool of Earth and Atmospheric Sciences, Georgia Institute of TechnologyAbstract Despite the importance of supraglacial melt lakes to the future evolution of polar ice sheets, they are not represented in current large-scale climate and ice sheet models. In this study, we use ICESat-2 satellite surface elevation measurements to show that roughness on the Antarctic Ice Sheet surface is largely self-affine. Estimation of ice sheet surface roughness statistics then enables the development of a set of simple mathematical expressions parameterizing the average supraglacial melt lake area fraction and lake depth from statistical fitting of large simulation ensembles of water flow on random, self-affine surfaces. These parameterizations provide predictions that are generally consistent with observations, with some exceptions. Finally, we predict that on large portions of Antarctic ice shelves supraglacial lakes are likely to, on average, stay less than one meter deep and occupy less than 40% of the ice area, absent changes in ice shelf surface roughness.https://doi.org/10.1038/s41467-025-61798-8 |
| spellingShingle | Danielle Grau Azeez Hussain Alexander A. Robel Predicting mean depth and area fraction of Antarctic supraglacial melt lakes with physics-based parameterizations Nature Communications |
| title | Predicting mean depth and area fraction of Antarctic supraglacial melt lakes with physics-based parameterizations |
| title_full | Predicting mean depth and area fraction of Antarctic supraglacial melt lakes with physics-based parameterizations |
| title_fullStr | Predicting mean depth and area fraction of Antarctic supraglacial melt lakes with physics-based parameterizations |
| title_full_unstemmed | Predicting mean depth and area fraction of Antarctic supraglacial melt lakes with physics-based parameterizations |
| title_short | Predicting mean depth and area fraction of Antarctic supraglacial melt lakes with physics-based parameterizations |
| title_sort | predicting mean depth and area fraction of antarctic supraglacial melt lakes with physics based parameterizations |
| url | https://doi.org/10.1038/s41467-025-61798-8 |
| work_keys_str_mv | AT daniellegrau predictingmeandepthandareafractionofantarcticsupraglacialmeltlakeswithphysicsbasedparameterizations AT azeezhussain predictingmeandepthandareafractionofantarcticsupraglacialmeltlakeswithphysicsbasedparameterizations AT alexanderarobel predictingmeandepthandareafractionofantarcticsupraglacialmeltlakeswithphysicsbasedparameterizations |