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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Published in:Geophysical Research Letters
Main Authors: Theodore Langhorst, Konstantinos M. Andreadis, George H. Allen
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2024
Subjects:
Online Access:https://doi.org/10.1029/2024GL110085
https://doaj.org/article/386a8e9ed1f54591b834ae56ae3f1da0
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spelling 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
collection 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
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