Arctic cloud characteristics as derived from MODIS, CALIPSO, and cloudsat

The Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and CloudSat Cloud Profiling Radar (CPR) set of sensors, all in the Afternoon Constellation (A-Train), has been regarded as among the most powerful tools for characterizing the cloud...

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Main Authors: Chan, Mark Aaron, Comiso, Josefino C.
Format: Text
Language:unknown
Published: Animo Repository 2013
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/4125
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spelling ftdelasalleuniv:oai:animorepository.dlsu.edu.ph:faculty_research-5006 2023-05-15T14:51:09+02:00 Arctic cloud characteristics as derived from MODIS, CALIPSO, and cloudsat Chan, Mark Aaron Comiso, Josefino C. 2013-05-01T07:00:00Z https://animorepository.dlsu.edu.ph/faculty_research/4125 unknown Animo Repository https://animorepository.dlsu.edu.ph/faculty_research/4125 Faculty Research Work Clouds Sea ice Remote-sensing Optical radar Environmental Sciences text 2013 ftdelasalleuniv 2022-07-31T19:38:13Z The Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and CloudSat Cloud Profiling Radar (CPR) set of sensors, all in the Afternoon Constellation (A-Train), has been regarded as among the most powerful tools for characterizing the cloud cover. While providing good complementary information, the authors also observed that, at least for the Arctic region, the different sensors provide significantly different statistics about cloud cover characteristics. Data in 2007 and 2010 were analyzed, and the annual averages of cloud cover in the Arctic region were found to be 66.8%, 78.4%, and 63.3% as derived from MODIS, CALIOP, and CPR, respectively. A large disagreement between MODIS and CALIOP over sea ice and Greenland is observed, with a cloud percentage difference of 30.9% and 31.5%, respectively. In the entire Arctic, the average disagreement between MODIS and CALIOP increased from 13.1% during daytime to 26.7% during nighttime. Furthermore, the MODIS cloud mask accuracy has a high seasonal dependence, in that MODIS-CALIOP disagreement is the lowest during summertime at 10.7% and worst during winter at 28.0%. During nighttime the magnitude of the bias is higher because cloud detection is limited to the use of infrared bands. The clouds not detected by MODIS are typically low-level (top height <2 >km) and high-level clouds (top height.6 km) and, especially, those that are geometrically thin (<2 >km). Geometrically thin clouds (<2 >km) accounted for about 95.5% of all clouds that CPR misses. As reported in a similar study, very low and thin clouds ( Text Arctic Greenland Sea ice Animo Repository - De La Salle University Research Arctic Greenland
institution Open Polar
collection Animo Repository - De La Salle University Research
op_collection_id ftdelasalleuniv
language unknown
topic Clouds
Sea ice
Remote-sensing
Optical radar
Environmental Sciences
spellingShingle Clouds
Sea ice
Remote-sensing
Optical radar
Environmental Sciences
Chan, Mark Aaron
Comiso, Josefino C.
Arctic cloud characteristics as derived from MODIS, CALIPSO, and cloudsat
topic_facet Clouds
Sea ice
Remote-sensing
Optical radar
Environmental Sciences
description The Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and CloudSat Cloud Profiling Radar (CPR) set of sensors, all in the Afternoon Constellation (A-Train), has been regarded as among the most powerful tools for characterizing the cloud cover. While providing good complementary information, the authors also observed that, at least for the Arctic region, the different sensors provide significantly different statistics about cloud cover characteristics. Data in 2007 and 2010 were analyzed, and the annual averages of cloud cover in the Arctic region were found to be 66.8%, 78.4%, and 63.3% as derived from MODIS, CALIOP, and CPR, respectively. A large disagreement between MODIS and CALIOP over sea ice and Greenland is observed, with a cloud percentage difference of 30.9% and 31.5%, respectively. In the entire Arctic, the average disagreement between MODIS and CALIOP increased from 13.1% during daytime to 26.7% during nighttime. Furthermore, the MODIS cloud mask accuracy has a high seasonal dependence, in that MODIS-CALIOP disagreement is the lowest during summertime at 10.7% and worst during winter at 28.0%. During nighttime the magnitude of the bias is higher because cloud detection is limited to the use of infrared bands. The clouds not detected by MODIS are typically low-level (top height <2 >km) and high-level clouds (top height.6 km) and, especially, those that are geometrically thin (<2 >km). Geometrically thin clouds (<2 >km) accounted for about 95.5% of all clouds that CPR misses. As reported in a similar study, very low and thin clouds (
format Text
author Chan, Mark Aaron
Comiso, Josefino C.
author_facet Chan, Mark Aaron
Comiso, Josefino C.
author_sort Chan, Mark Aaron
title Arctic cloud characteristics as derived from MODIS, CALIPSO, and cloudsat
title_short Arctic cloud characteristics as derived from MODIS, CALIPSO, and cloudsat
title_full Arctic cloud characteristics as derived from MODIS, CALIPSO, and cloudsat
title_fullStr Arctic cloud characteristics as derived from MODIS, CALIPSO, and cloudsat
title_full_unstemmed Arctic cloud characteristics as derived from MODIS, CALIPSO, and cloudsat
title_sort arctic cloud characteristics as derived from modis, calipso, and cloudsat
publisher Animo Repository
publishDate 2013
url https://animorepository.dlsu.edu.ph/faculty_research/4125
geographic Arctic
Greenland
geographic_facet Arctic
Greenland
genre Arctic
Greenland
Sea ice
genre_facet Arctic
Greenland
Sea ice
op_source Faculty Research Work
op_relation https://animorepository.dlsu.edu.ph/faculty_research/4125
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