Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic
This study evaluates the potential use of the Microwave Humidity Sounder (MHS) for snowfall detection in the Arctic. Using two years of colocated MHS and CloudSat observations, we develop an algorithm that is able to detect up to 90% of the most intense snowfall events (snow water path ≥400 g m −2 a...
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Online Access: | https://doi.org/10.3390/rs11192200 https://doaj.org/article/ff2b82ecabe94949bfddaefb56869023 |
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ftdoajarticles:oai:doaj.org/article:ff2b82ecabe94949bfddaefb56869023 2023-05-15T14:51:35+02:00 Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic Léo Edel Jean-François Rysman Chantal Claud Cyril Palerme Christophe Genthon 2019-09-01T00:00:00Z https://doi.org/10.3390/rs11192200 https://doaj.org/article/ff2b82ecabe94949bfddaefb56869023 EN eng MDPI AG https://www.mdpi.com/2072-4292/11/19/2200 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs11192200 https://doaj.org/article/ff2b82ecabe94949bfddaefb56869023 Remote Sensing, Vol 11, Iss 19, p 2200 (2019) snowfall Arctic passive microwaves CloudSat machine learning Science Q article 2019 ftdoajarticles https://doi.org/10.3390/rs11192200 2022-12-31T16:08:46Z This study evaluates the potential use of the Microwave Humidity Sounder (MHS) for snowfall detection in the Arctic. Using two years of colocated MHS and CloudSat observations, we develop an algorithm that is able to detect up to 90% of the most intense snowfall events (snow water path ≥400 g m −2 and 50% of the weak snowfall rate events (snow water path ≤50 g m −2 . The brightness temperatures at 190.3 GHz and 183.3 ± 3 GHz, the integrated water vapor, and the temperature at 2 m are identified as the most important variables for snowfall detection. The algorithm tends to underestimate the snowfall occurrence over Greenland and mountainous areas (by as much as −30%), likely due to the dryness of these areas, and to overestimate the snowfall occurrence over the northern part of the Atlantic (by up to 30%), likely due to the occurrence of mixed phase precipitation. An interpretation of the selection of the variables and their importance provides a better understanding of the snowfall detection algorithm. This work lays the foundation for the development of a snowfall rate quantification algorithm. Article in Journal/Newspaper Arctic Greenland Directory of Open Access Journals: DOAJ Articles Arctic Greenland Remote Sensing 11 19 2200 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
snowfall Arctic passive microwaves CloudSat machine learning Science Q |
spellingShingle |
snowfall Arctic passive microwaves CloudSat machine learning Science Q Léo Edel Jean-François Rysman Chantal Claud Cyril Palerme Christophe Genthon Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic |
topic_facet |
snowfall Arctic passive microwaves CloudSat machine learning Science Q |
description |
This study evaluates the potential use of the Microwave Humidity Sounder (MHS) for snowfall detection in the Arctic. Using two years of colocated MHS and CloudSat observations, we develop an algorithm that is able to detect up to 90% of the most intense snowfall events (snow water path ≥400 g m −2 and 50% of the weak snowfall rate events (snow water path ≤50 g m −2 . The brightness temperatures at 190.3 GHz and 183.3 ± 3 GHz, the integrated water vapor, and the temperature at 2 m are identified as the most important variables for snowfall detection. The algorithm tends to underestimate the snowfall occurrence over Greenland and mountainous areas (by as much as −30%), likely due to the dryness of these areas, and to overestimate the snowfall occurrence over the northern part of the Atlantic (by up to 30%), likely due to the occurrence of mixed phase precipitation. An interpretation of the selection of the variables and their importance provides a better understanding of the snowfall detection algorithm. This work lays the foundation for the development of a snowfall rate quantification algorithm. |
format |
Article in Journal/Newspaper |
author |
Léo Edel Jean-François Rysman Chantal Claud Cyril Palerme Christophe Genthon |
author_facet |
Léo Edel Jean-François Rysman Chantal Claud Cyril Palerme Christophe Genthon |
author_sort |
Léo Edel |
title |
Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic |
title_short |
Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic |
title_full |
Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic |
title_fullStr |
Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic |
title_full_unstemmed |
Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic |
title_sort |
potential of passive microwave around 183 ghz for snowfall detection in the arctic |
publisher |
MDPI AG |
publishDate |
2019 |
url |
https://doi.org/10.3390/rs11192200 https://doaj.org/article/ff2b82ecabe94949bfddaefb56869023 |
geographic |
Arctic Greenland |
geographic_facet |
Arctic Greenland |
genre |
Arctic Greenland |
genre_facet |
Arctic Greenland |
op_source |
Remote Sensing, Vol 11, Iss 19, p 2200 (2019) |
op_relation |
https://www.mdpi.com/2072-4292/11/19/2200 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs11192200 https://doaj.org/article/ff2b82ecabe94949bfddaefb56869023 |
op_doi |
https://doi.org/10.3390/rs11192200 |
container_title |
Remote Sensing |
container_volume |
11 |
container_issue |
19 |
container_start_page |
2200 |
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1766322708906246144 |