Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite Data
An analysis of fog and low cloud properties and distribution is performed using satellite-based LiDAR. Recent years have seen great progress in the remote sensing of fog and low clouds using passive satellite-based sensors. On this basis, maps of fog distribution and frequency as well as baseline cl...
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doaj-276c756b256745b9912012fef3cddcf52020-11-25T01:43:58ZengMDPI AGRemote Sensing2072-42922018-08-01108120910.3390/rs10081209rs10081209Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite DataJan Cermak0Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), 76128 Karlsruhe, GermanyAn analysis of fog and low cloud properties and distribution is performed using satellite-based LiDAR. Recent years have seen great progress in the remote sensing of fog and low clouds using passive satellite-based sensors. On this basis, maps of fog distribution and frequency as well as baseline climatologies have been constructed. However, no information on fog altitude and vertical extent is available in this way, and fog/low cloud below other clouds cannot be detected in most cases. In this study, ten years of observations by the LiDAR aboard the CALIPSO (Cloud-Aerosol LiDAR and Pathfinder Satellite Observations) platform are used to construct a map and statistical evaluations of fog/low cloud distribution and properties. For the purpose of evaluation, a comparison is made to an evaluation of fog/low cloud distribution in Europe, derived from Meteosat measurements using the Satellite-Based Operation Fog Observation Scheme (SOFOS). Both maps show good agreement in spatial patterns in this region with very diverse fog formation mechanisms. It is found that fog/low cloud layers display distinct spatial differences in terms of geometrical thickness and detection accuracy. The number of fog/low cloud instances missed by passive-sensor retrievals due to multi-layer cloud situations is considerable, with clear regional differences.http://www.mdpi.com/2072-4292/10/8/1209foglow cloudsCALIPSOremote sensingsatelliteLiDARclimatology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jan Cermak |
spellingShingle |
Jan Cermak Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite Data Remote Sensing fog low clouds CALIPSO remote sensing satellite LiDAR climatology |
author_facet |
Jan Cermak |
author_sort |
Jan Cermak |
title |
Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite Data |
title_short |
Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite Data |
title_full |
Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite Data |
title_fullStr |
Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite Data |
title_full_unstemmed |
Fog and Low Cloud Frequency and Properties from Active-Sensor Satellite Data |
title_sort |
fog and low cloud frequency and properties from active-sensor satellite data |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2018-08-01 |
description |
An analysis of fog and low cloud properties and distribution is performed using satellite-based LiDAR. Recent years have seen great progress in the remote sensing of fog and low clouds using passive satellite-based sensors. On this basis, maps of fog distribution and frequency as well as baseline climatologies have been constructed. However, no information on fog altitude and vertical extent is available in this way, and fog/low cloud below other clouds cannot be detected in most cases. In this study, ten years of observations by the LiDAR aboard the CALIPSO (Cloud-Aerosol LiDAR and Pathfinder Satellite Observations) platform are used to construct a map and statistical evaluations of fog/low cloud distribution and properties. For the purpose of evaluation, a comparison is made to an evaluation of fog/low cloud distribution in Europe, derived from Meteosat measurements using the Satellite-Based Operation Fog Observation Scheme (SOFOS). Both maps show good agreement in spatial patterns in this region with very diverse fog formation mechanisms. It is found that fog/low cloud layers display distinct spatial differences in terms of geometrical thickness and detection accuracy. The number of fog/low cloud instances missed by passive-sensor retrievals due to multi-layer cloud situations is considerable, with clear regional differences. |
topic |
fog low clouds CALIPSO remote sensing satellite LiDAR climatology |
url |
http://www.mdpi.com/2072-4292/10/8/1209 |
work_keys_str_mv |
AT jancermak fogandlowcloudfrequencyandpropertiesfromactivesensorsatellitedata |
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