Biases of Sentinel-5P and Suomi-NPP Cloud Top Height Retrievals: A Global Comparison

Cloud Top Height (CTH) is a fundamental parameter in atmospheric science, critically influencing Earth’s radiation budget and hydrological cycle. Satellite-based passive remote sensing provides the primary means of monitoring CTH on a global scale due to its extensive spatial coverage. However, these passive retrieval techniques often rely on idealized physical assumptions, leading to significant systematic biases. To quantify these biases, this study provides an evaluation of two prominent passive CTH products, i.e., Sentinel-5P (S5P, O2 A-band) and Suomi-NPP (NPP, thermal infrared), by comparing their global data from July 2018 to June 2019 against the active CloudSat/CALIPSO (CC) reference. The results reveal stark and complementary error patterns. For single-layer liquid clouds over land, the products exhibit opposing biases, with S5P underestimating CTH while NPP overestimates it. For ice clouds, both products show a general underestimation, but NPP is more accurate. In challenging two-layer scenes, both retrieval methods show large systematic biases, with S5P often erroneously detecting the lower cloud layer. These distinct error characteristics highlight the fundamental limitations of single-sensor retrievals and reveal the potential to organically combine the advantages of different products to improve CTH accuracy.

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Publication Details

Journal
Remote Sensing
Published
2025-10-24
DOI
https://doi.org/10.3390/rs17213526
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

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article

Biases of Sentinel-5P and Suomi-NPP Cloud Top Height Retrievals: A Global Comparison

Hao Lin, Jie Yang, Lechao Dong, Zhe-Wen Zheng et al.
Remote Sensing
Atmospheric aerosols and clouds
article

Biases of Sentinel-5P and Suomi-NPP Cloud Top Height Retrievals: A Global Comparison

Hao Lin, Jie Yang, Lechao Dong, Zhe-Wen Zheng, Siwei Li, Qingxin Wang
article en

Abstract

Cloud Top Height (CTH) is a fundamental parameter in atmospheric science, critically influencing Earth’s radiation budget and hydrological cycle. Satellite-based passive remote sensing provides the primary means of monitoring CTH on a global scale due to its extensive spatial coverage. However, these passive retrieval techniques often rely on idealized physical assumptions, leading to significant systematic biases. To quantify these biases, this study provides an evaluation of two prominent passive CTH products, i.e., Sentinel-5P (S5P, O2 A-band) and Suomi-NPP (NPP, thermal infrared), by comparing their global data from July 2018 to June 2019 against the active CloudSat/CALIPSO (CC) reference. The results reveal stark and complementary error patterns. For single-layer liquid clouds over land, the products exhibit opposing biases, with S5P underestimating CTH while NPP overestimates it. For ice clouds, both products show a general underestimation, but NPP is more accurate. In challenging two-layer scenes, both retrieval methods show large systematic biases, with S5P often erroneously detecting the lower cloud layer. These distinct error characteristics highlight the fundamental limitations of single-sensor retrievals and reveal the potential to organically combine the advantages of different products to improve CTH accuracy.

Remote SensingVol. 17(21)
Xinyang Normal University (CN), Zhejiang Normal University (CN), China Meteorological Administration (CN), Wuhan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 71%
Atmospheric aerosols and clouds
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