Evaluation of CloudSat's Cloud-Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet
The Greenland Ice Sheet is now the single largest cryospheric contributor to global sea-level rise yet uncertainty remains about its future contribution due to complex interactions between increasing snowfall and surface melt. Reducing uncertainty in future snowfall predictions requires sophisticate...
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ftunivutrecht:oai:dspace.library.uu.nl:1874/409033 2023-11-12T04:17:46+01:00 Evaluation of CloudSat's Cloud-Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet Ryan, Jonathan C. Smith, Laurence C. Wu, Mengxi Cooley, Sarah W. Miège, Clément Montgomery, Lynn N. Koenig, Lora S. Fettweis, Xavier Noel, Brice P.Y. van den Broeke, Michiel R. Sub Dynamics Meteorology Marine and Atmospheric Research 2020-02-27 application/pdf https://dspace.library.uu.nl/handle/1874/409033 en eng 2169-897X https://dspace.library.uu.nl/handle/1874/409033 info:eu-repo/semantics/OpenAccess CloudSat Greenland Ice Sheet remote sensing snowfall surface mass balance Taverne Geophysics Forestry Oceanography Aquatic Science Ecology Water Science and Technology Soil Science Geochemistry and Petrology Earth-Surface Processes Atmospheric Science Earth and Planetary Sciences (miscellaneous) Space and Planetary Science Palaeontology Article 2020 ftunivutrecht 2023-11-01T23:24:18Z The Greenland Ice Sheet is now the single largest cryospheric contributor to global sea-level rise yet uncertainty remains about its future contribution due to complex interactions between increasing snowfall and surface melt. Reducing uncertainty in future snowfall predictions requires sophisticated, physically based climate models evaluated with present-day observations. The accuracy of modeled snowfall rates, however, has yet to be systematically assessed because observations are sparse. Here, we produce high spatial resolution (15 km) snowfall climatologies (2006–2016) derived from CloudSat's 2C-SNOW-PROFILE product to evaluate climate model simulations of snowfall across the Greenland Ice Sheet. In comparison to accumulation datasets acquired from ice cores and airborne accumulation radar, we find that our CloudSat climatologies capture broad spatial patterns of snowfall in both the accumulation and ablation zones. By comparing our CloudSat snowfall climatologies with the Regional Atmospheric Climate Model Version 2.3p2 (RACMO2.3p2), Modèle Atmosphérique Régional 3.9 (MAR3.9), ERA5, and Community Earth System Model version 1 (CESM1), we demonstrate that climate models likely overestimate snowfall rates at the margins of the ice sheet, particularly in South, Southeast, and Northwest Greenland during autumn and winter. Despite this overestimation, there are few areas of the ice sheet where the models and CloudSat substantially disagree about the spatial pattern and seasonality of snowfall rates. We conclude that a combination of CloudSat snowfall observations and the latest generation of climate models has the potential to improve understanding of how snowfall rates respond to increasing air temperatures, thereby constraining one of the largest sources of uncertainty in Greenland's future contribution to global sea levels. Article in Journal/Newspaper Greenland Ice Sheet Utrecht University Repository Greenland |
institution |
Open Polar |
collection |
Utrecht University Repository |
op_collection_id |
ftunivutrecht |
language |
English |
topic |
CloudSat Greenland Ice Sheet remote sensing snowfall surface mass balance Taverne Geophysics Forestry Oceanography Aquatic Science Ecology Water Science and Technology Soil Science Geochemistry and Petrology Earth-Surface Processes Atmospheric Science Earth and Planetary Sciences (miscellaneous) Space and Planetary Science Palaeontology |
spellingShingle |
CloudSat Greenland Ice Sheet remote sensing snowfall surface mass balance Taverne Geophysics Forestry Oceanography Aquatic Science Ecology Water Science and Technology Soil Science Geochemistry and Petrology Earth-Surface Processes Atmospheric Science Earth and Planetary Sciences (miscellaneous) Space and Planetary Science Palaeontology Ryan, Jonathan C. Smith, Laurence C. Wu, Mengxi Cooley, Sarah W. Miège, Clément Montgomery, Lynn N. Koenig, Lora S. Fettweis, Xavier Noel, Brice P.Y. van den Broeke, Michiel R. Evaluation of CloudSat's Cloud-Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet |
topic_facet |
CloudSat Greenland Ice Sheet remote sensing snowfall surface mass balance Taverne Geophysics Forestry Oceanography Aquatic Science Ecology Water Science and Technology Soil Science Geochemistry and Petrology Earth-Surface Processes Atmospheric Science Earth and Planetary Sciences (miscellaneous) Space and Planetary Science Palaeontology |
description |
The Greenland Ice Sheet is now the single largest cryospheric contributor to global sea-level rise yet uncertainty remains about its future contribution due to complex interactions between increasing snowfall and surface melt. Reducing uncertainty in future snowfall predictions requires sophisticated, physically based climate models evaluated with present-day observations. The accuracy of modeled snowfall rates, however, has yet to be systematically assessed because observations are sparse. Here, we produce high spatial resolution (15 km) snowfall climatologies (2006–2016) derived from CloudSat's 2C-SNOW-PROFILE product to evaluate climate model simulations of snowfall across the Greenland Ice Sheet. In comparison to accumulation datasets acquired from ice cores and airborne accumulation radar, we find that our CloudSat climatologies capture broad spatial patterns of snowfall in both the accumulation and ablation zones. By comparing our CloudSat snowfall climatologies with the Regional Atmospheric Climate Model Version 2.3p2 (RACMO2.3p2), Modèle Atmosphérique Régional 3.9 (MAR3.9), ERA5, and Community Earth System Model version 1 (CESM1), we demonstrate that climate models likely overestimate snowfall rates at the margins of the ice sheet, particularly in South, Southeast, and Northwest Greenland during autumn and winter. Despite this overestimation, there are few areas of the ice sheet where the models and CloudSat substantially disagree about the spatial pattern and seasonality of snowfall rates. We conclude that a combination of CloudSat snowfall observations and the latest generation of climate models has the potential to improve understanding of how snowfall rates respond to increasing air temperatures, thereby constraining one of the largest sources of uncertainty in Greenland's future contribution to global sea levels. |
author2 |
Sub Dynamics Meteorology Marine and Atmospheric Research |
format |
Article in Journal/Newspaper |
author |
Ryan, Jonathan C. Smith, Laurence C. Wu, Mengxi Cooley, Sarah W. Miège, Clément Montgomery, Lynn N. Koenig, Lora S. Fettweis, Xavier Noel, Brice P.Y. van den Broeke, Michiel R. |
author_facet |
Ryan, Jonathan C. Smith, Laurence C. Wu, Mengxi Cooley, Sarah W. Miège, Clément Montgomery, Lynn N. Koenig, Lora S. Fettweis, Xavier Noel, Brice P.Y. van den Broeke, Michiel R. |
author_sort |
Ryan, Jonathan C. |
title |
Evaluation of CloudSat's Cloud-Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet |
title_short |
Evaluation of CloudSat's Cloud-Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet |
title_full |
Evaluation of CloudSat's Cloud-Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet |
title_fullStr |
Evaluation of CloudSat's Cloud-Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet |
title_full_unstemmed |
Evaluation of CloudSat's Cloud-Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet |
title_sort |
evaluation of cloudsat's cloud-profiling radar for mapping snowfall rates across the greenland ice sheet |
publishDate |
2020 |
url |
https://dspace.library.uu.nl/handle/1874/409033 |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland Ice Sheet |
genre_facet |
Greenland Ice Sheet |
op_relation |
2169-897X https://dspace.library.uu.nl/handle/1874/409033 |
op_rights |
info:eu-repo/semantics/OpenAccess |
_version_ |
1782334545633214464 |