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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Bibliographic Details
Main Author: Jan Cermak
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:Remote Sensing
Subjects:
fog
Online Access:http://www.mdpi.com/2072-4292/10/8/1209
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spelling 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
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