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- Title
Global Cloud Biases in Optical Satellite Remote Sensing of Rivers.
- Authors
Langhorst, Theodore; Andreadis, Konstantinos M.; Allen, George H.
- 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. Plain Language Summary: This study examines how optical satellite imagery, which is vital for understanding rivers worldwide, is hindered by clouds specifically when observing rivers. We analyzed 22 years of daily data covering 21,642 sections of rivers of various sizes and climates. Our findings reveal that cloud cover significantly biases the distribution of river discharges we observe, especially for Tropical and Arctic rivers. This means that satellite images do not represent river conditions accurately. Our research provides the first comprehensive analysis of its extent and impact. Ultimately, while satellite technology continues to improve, clouds remain a challenge in obtaining precise river data, highlighting the need for innovative solutions. Key Points: We evaluated the impact of cloud cover on satellite optical remote sensing across a global sample of river reachesDirect optical satellite observations can present a highly biased, and geographically variable, view of river conditionsSeasonal relationships of clouds and discharge predict the ability of optical satellites to observe the distribution of river discharge
- Subjects
REMOTE sensing; REMOTE-sensing images; CLOUDINESS; MULTISENSOR data fusion; OPTICAL sensors
- Publication
Geophysical Research Letters, 2024, Vol 51, Issue 16, p1
- ISSN
0094-8276
- Publication type
Article
- DOI
10.1029/2024GL110085