Global Cloud Biases in Optical Satellite Remote Sensing of Rivers
Abstract Satellite imagery provides a global perspective for studying river hydrology and water quality, but clouds remain a fundamental limitation of optical sensors. Explicit studies of this problem were limited to specific locations or regions. In this study, we characterize the global severity o...
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Online Access: | https://doi.org/10.1029/2024GL110085 https://doaj.org/article/386a8e9ed1f54591b834ae56ae3f1da0 |
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ftdoajarticles:oai:doaj.org/article:386a8e9ed1f54591b834ae56ae3f1da0 2024-09-30T14:30:58+00:00 Global Cloud Biases in Optical Satellite Remote Sensing of Rivers Theodore Langhorst Konstantinos M. Andreadis George H. Allen 2024-08-01T00:00:00Z https://doi.org/10.1029/2024GL110085 https://doaj.org/article/386a8e9ed1f54591b834ae56ae3f1da0 EN eng Wiley https://doi.org/10.1029/2024GL110085 https://doaj.org/toc/0094-8276 https://doaj.org/toc/1944-8007 1944-8007 0094-8276 doi:10.1029/2024GL110085 https://doaj.org/article/386a8e9ed1f54591b834ae56ae3f1da0 Geophysical Research Letters, Vol 51, Iss 16, Pp n/a-n/a (2024) river discharge optical remote sensing remote sensing clouds river width bias Geophysics. Cosmic physics QC801-809 article 2024 ftdoajarticles https://doi.org/10.1029/2024GL110085 2024-09-02T15:34:38Z Abstract Satellite imagery provides a global perspective for studying river hydrology and water quality, but clouds remain a fundamental limitation of optical sensors. Explicit studies of this problem were limited to specific locations or regions. In this study, we characterize the global severity of this limitation by analyzing 22 years of daily satellite cloud cover data and modeled river discharge for a global sample 21,642 river reaches of diverse sizes and climates. Our results show that the bias in observed river discharge is highly organized in space, particularly affecting Tropical and Arctic rivers. Given the fundamental nature of this cloud limitation, optical satellites will always provide a biased representation of river conditions. We discuss several strategies to mitigate bias, including modeling, data fusion, and temporal averaging, yet these methods introduce their own challenges and uncertainties. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Geophysical Research Letters 51 16 |
institution |
Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
river discharge optical remote sensing remote sensing clouds river width bias Geophysics. Cosmic physics QC801-809 |
spellingShingle |
river discharge optical remote sensing remote sensing clouds river width bias Geophysics. Cosmic physics QC801-809 Theodore Langhorst Konstantinos M. Andreadis George H. Allen Global Cloud Biases in Optical Satellite Remote Sensing of Rivers |
topic_facet |
river discharge optical remote sensing remote sensing clouds river width bias Geophysics. Cosmic physics QC801-809 |
description |
Abstract Satellite imagery provides a global perspective for studying river hydrology and water quality, but clouds remain a fundamental limitation of optical sensors. Explicit studies of this problem were limited to specific locations or regions. In this study, we characterize the global severity of this limitation by analyzing 22 years of daily satellite cloud cover data and modeled river discharge for a global sample 21,642 river reaches of diverse sizes and climates. Our results show that the bias in observed river discharge is highly organized in space, particularly affecting Tropical and Arctic rivers. Given the fundamental nature of this cloud limitation, optical satellites will always provide a biased representation of river conditions. We discuss several strategies to mitigate bias, including modeling, data fusion, and temporal averaging, yet these methods introduce their own challenges and uncertainties. |
format |
Article in Journal/Newspaper |
author |
Theodore Langhorst Konstantinos M. Andreadis George H. Allen |
author_facet |
Theodore Langhorst Konstantinos M. Andreadis George H. Allen |
author_sort |
Theodore Langhorst |
title |
Global Cloud Biases in Optical Satellite Remote Sensing of Rivers |
title_short |
Global Cloud Biases in Optical Satellite Remote Sensing of Rivers |
title_full |
Global Cloud Biases in Optical Satellite Remote Sensing of Rivers |
title_fullStr |
Global Cloud Biases in Optical Satellite Remote Sensing of Rivers |
title_full_unstemmed |
Global Cloud Biases in Optical Satellite Remote Sensing of Rivers |
title_sort |
global cloud biases in optical satellite remote sensing of rivers |
publisher |
Wiley |
publishDate |
2024 |
url |
https://doi.org/10.1029/2024GL110085 https://doaj.org/article/386a8e9ed1f54591b834ae56ae3f1da0 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Geophysical Research Letters, Vol 51, Iss 16, Pp n/a-n/a (2024) |
op_relation |
https://doi.org/10.1029/2024GL110085 https://doaj.org/toc/0094-8276 https://doaj.org/toc/1944-8007 1944-8007 0094-8276 doi:10.1029/2024GL110085 https://doaj.org/article/386a8e9ed1f54591b834ae56ae3f1da0 |
op_doi |
https://doi.org/10.1029/2024GL110085 |
container_title |
Geophysical Research Letters |
container_volume |
51 |
container_issue |
16 |
_version_ |
1811635673856212992 |