CloudSat-based assessment of GPM Microwave Imager snowfall observation capabilities
The sensitivity of Global Precipitation Measurement (GPM) Microwave Imager (GMI) high-frequency channels to snowfall at higher latitudes (around 60◦N/S) is investigated using coincident CloudSat observations. The 166 GHz channel is highlighted throughout the study due to its ice scattering sensitivi...
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ftmichigantuniv:oai:digitalcommons.mtu.edu:geo-fp-1185 2023-05-15T18:18:31+02:00 CloudSat-based assessment of GPM Microwave Imager snowfall observation capabilities Panegrossi, Giulia Rysman, Jean-François Casella, Daniele Marra, Anna Cinzia Kulie, Mark 2017-12-06T08:00:00Z application/pdf https://digitalcommons.mtu.edu/geo-fp/184 https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=1185&context=geo-fp unknown Digital Commons @ Michigan Tech https://digitalcommons.mtu.edu/geo-fp/184 https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=1185&context=geo-fp http://creativecommons.org/licenses/by/4.0/ CC-BY Department of Geological and Mining Engineering and Sciences Publications snowfall detection GPM CloudSat CPR CALIPSO high latitudes passive microwave remote sensing of precipitation Earth Sciences Engineering text 2017 ftmichigantuniv 2022-01-23T10:33:38Z The sensitivity of Global Precipitation Measurement (GPM) Microwave Imager (GMI) high-frequency channels to snowfall at higher latitudes (around 60◦N/S) is investigated using coincident CloudSat observations. The 166 GHz channel is highlighted throughout the study due to its ice scattering sensitivity and polarization information. The analysis of three case studies evidences the important combined role of total precipitable water (TPW), supercooled cloud water,and background surface composition on the brightness temperature (TB) behavior for different snow-producing clouds. A regression tree statistical analysis applied to the entire GMI-CloudSat snowfall dataset indicates which variables influence the 166 GHz polarization difference (166∆TB)and its relation to snowfall. Critical thresholds of various parameters (sea ice concentration (SIC), TPW, ice water path (IWP)) are established for optimal snowfall detection capabilities. The 166∆TB can identify snowfall events over land and sea when critical thresholds are exceeded (TPW > 3.6 kg·m−2, IWP > 0.24 kg·m−2 over land, and SIC > 57%, TPW > 5.1 kg·m−2 over sea). The complex combined 166∆TB-TB relationship at higher latitudes and the impact of supercooled water vertical distribution are also investigated. The findings presented in this study can be exploited to improve passive microwave snowfall detection algorithms. Text Sea ice Michigan Technological University: Digital Commons @ Michigan Tech |
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Open Polar |
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Michigan Technological University: Digital Commons @ Michigan Tech |
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ftmichigantuniv |
language |
unknown |
topic |
snowfall detection GPM CloudSat CPR CALIPSO high latitudes passive microwave remote sensing of precipitation Earth Sciences Engineering |
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snowfall detection GPM CloudSat CPR CALIPSO high latitudes passive microwave remote sensing of precipitation Earth Sciences Engineering Panegrossi, Giulia Rysman, Jean-François Casella, Daniele Marra, Anna Cinzia Kulie, Mark CloudSat-based assessment of GPM Microwave Imager snowfall observation capabilities |
topic_facet |
snowfall detection GPM CloudSat CPR CALIPSO high latitudes passive microwave remote sensing of precipitation Earth Sciences Engineering |
description |
The sensitivity of Global Precipitation Measurement (GPM) Microwave Imager (GMI) high-frequency channels to snowfall at higher latitudes (around 60◦N/S) is investigated using coincident CloudSat observations. The 166 GHz channel is highlighted throughout the study due to its ice scattering sensitivity and polarization information. The analysis of three case studies evidences the important combined role of total precipitable water (TPW), supercooled cloud water,and background surface composition on the brightness temperature (TB) behavior for different snow-producing clouds. A regression tree statistical analysis applied to the entire GMI-CloudSat snowfall dataset indicates which variables influence the 166 GHz polarization difference (166∆TB)and its relation to snowfall. Critical thresholds of various parameters (sea ice concentration (SIC), TPW, ice water path (IWP)) are established for optimal snowfall detection capabilities. The 166∆TB can identify snowfall events over land and sea when critical thresholds are exceeded (TPW > 3.6 kg·m−2, IWP > 0.24 kg·m−2 over land, and SIC > 57%, TPW > 5.1 kg·m−2 over sea). The complex combined 166∆TB-TB relationship at higher latitudes and the impact of supercooled water vertical distribution are also investigated. The findings presented in this study can be exploited to improve passive microwave snowfall detection algorithms. |
format |
Text |
author |
Panegrossi, Giulia Rysman, Jean-François Casella, Daniele Marra, Anna Cinzia Kulie, Mark |
author_facet |
Panegrossi, Giulia Rysman, Jean-François Casella, Daniele Marra, Anna Cinzia Kulie, Mark |
author_sort |
Panegrossi, Giulia |
title |
CloudSat-based assessment of GPM Microwave Imager snowfall observation capabilities |
title_short |
CloudSat-based assessment of GPM Microwave Imager snowfall observation capabilities |
title_full |
CloudSat-based assessment of GPM Microwave Imager snowfall observation capabilities |
title_fullStr |
CloudSat-based assessment of GPM Microwave Imager snowfall observation capabilities |
title_full_unstemmed |
CloudSat-based assessment of GPM Microwave Imager snowfall observation capabilities |
title_sort |
cloudsat-based assessment of gpm microwave imager snowfall observation capabilities |
publisher |
Digital Commons @ Michigan Tech |
publishDate |
2017 |
url |
https://digitalcommons.mtu.edu/geo-fp/184 https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=1185&context=geo-fp |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
Department of Geological and Mining Engineering and Sciences Publications |
op_relation |
https://digitalcommons.mtu.edu/geo-fp/184 https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=1185&context=geo-fp |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_rightsnorm |
CC-BY |
_version_ |
1766195110764085248 |