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Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet
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| Zeitschriftentitel: | Journal of Geophysical Research: Atmospheres |
|---|---|
| Personen und Körperschaften: | , , , , , , , , , |
| In: | Journal of Geophysical Research: Atmospheres, 125, 2020, 4 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
American Geophysical Union (AGU)
|
| Schlagwörter: |
| 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. 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 |
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. |
| spellingShingle |
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. Journal of Geophysical Research: Atmospheres Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet Space and Planetary Science Earth and Planetary Sciences (miscellaneous) Atmospheric Science Geophysics |
| author_sort |
ryan, jonathan c. |
| spelling |
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. 2169-897X 2169-8996 American Geophysical Union (AGU) Space and Planetary Science Earth and Planetary Sciences (miscellaneous) Atmospheric Science Geophysics http://dx.doi.org/10.1029/2019jd031411 <jats:title>ABSTRACT</jats:title><jats:p>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.</jats:p> Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet Journal of Geophysical Research: Atmospheres |
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| title |
Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet |
| title_unstemmed |
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_short |
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 |
| topic |
Space and Planetary Science Earth and Planetary Sciences (miscellaneous) Atmospheric Science Geophysics |
| url |
http://dx.doi.org/10.1029/2019jd031411 |
| publishDate |
2020 |
| physical |
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| description |
<jats:title>ABSTRACT</jats:title><jats:p>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.</jats:p> |
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| 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., 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. |
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| description | <jats:title>ABSTRACT</jats:title><jats:p>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.</jats:p> |
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| spelling | 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. 2169-897X 2169-8996 American Geophysical Union (AGU) Space and Planetary Science Earth and Planetary Sciences (miscellaneous) Atmospheric Science Geophysics http://dx.doi.org/10.1029/2019jd031411 <jats:title>ABSTRACT</jats:title><jats:p>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.</jats:p> Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet Journal of Geophysical Research: Atmospheres |
| spellingShingle | 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., Journal of Geophysical Research: Atmospheres, Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet, Space and Planetary Science, Earth and Planetary Sciences (miscellaneous), Atmospheric Science, Geophysics |
| title | 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_short | 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 |
| title_unstemmed | Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet |
| topic | Space and Planetary Science, Earth and Planetary Sciences (miscellaneous), Atmospheric Science, Geophysics |
| url | http://dx.doi.org/10.1029/2019jd031411 |