Retrieving all-weather precipitable water vapor using near-infrared and thermal infrared observations
Near-infrared (NIR) and thermal infrared (TIR) remote sensing are primary methods for monitoring large-scale, high-resolution precipitable water vapor (PWV); however, their application is limited to clear-sky conditions. To overcome this limitation and enable all-weather PWV retrieval, this study de...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
|
| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225003462 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849240746275635200 |
|---|---|
| author | Zheng Du Bao Zhang Yibin Yao Qingzhi Zhao Chaoqian Xu Qi Zhang Hongming Li Quanyu Chen |
| author_facet | Zheng Du Bao Zhang Yibin Yao Qingzhi Zhao Chaoqian Xu Qi Zhang Hongming Li Quanyu Chen |
| author_sort | Zheng Du |
| collection | DOAJ |
| description | Near-infrared (NIR) and thermal infrared (TIR) remote sensing are primary methods for monitoring large-scale, high-resolution precipitable water vapor (PWV); however, their application is limited to clear-sky conditions. To overcome this limitation and enable all-weather PWV retrieval, this study develops a new satellite-based PWV retrieval model to derive all-weather PWV at a spatial resolution of 300 m based on the synergistic use of NIR and TIR data from the Ocean and Land Colour Instrument (OLCI) and Sea and Land Surface Temperature Radiometer (SLSTR) instruments onboard the Sentinel-3B satellite. The proposed model consists of two sub-models for PWV derivation: one each for clear- and cloudy-sky conditions. The clear-sky PWV retrieval model integrates water vapor information from both NIR and TIR observations, whereas the cloudy-sky PWV retrieval model uses cloud-top properties derived from TIR data to correct the NIR water vapor within or above the clouds to the ground. Tested against the GNSS PWV, the new model has a root-mean-square error (RMSE) of 1.01 mm and bias of 0.09 mm for clear-sky conditions, representing a 51 % improvement in accuracy over the operational OLCI NIR products. For cloudy-sky conditions, the RMSE and bias are 2.66 mm and 0.02 mm, respectively, thereby filling the gap in high-quality PWV retrieval products under cloudy-sky conditions. The combined all-weather PWV product demonstrates robust spatiotemporal performance, with an RMSE and Bias of 1.92 mm and 0.16 mm, respectively. Given that the GNSS PWV has an accuracy of 1.37 mm, the accuracy achieved in this study is satisfactory. |
| format | Article |
| id | doaj-art-9ea9aa25a056459eb7b5fa02012bccdc |
| institution | Kabale University |
| issn | 1569-8432 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj-art-9ea9aa25a056459eb7b5fa02012bccdc2025-08-20T04:00:27ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322025-08-0114210469910.1016/j.jag.2025.104699Retrieving all-weather precipitable water vapor using near-infrared and thermal infrared observationsZheng Du0Bao Zhang1Yibin Yao2Qingzhi Zhao3Chaoqian Xu4Qi Zhang5Hongming Li6Quanyu Chen7School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China; Hubei Luojia Laboratory, Wuhan 430079, China; Corresponding author.School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China; Hubei Luojia Laboratory, Wuhan 430079, ChinaCollege of Geomatics, Xi’an University of Science and Technology, Xi’an 710054, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaSchool of Geodesy and Geomatics, Wuhan University, Wuhan 430079, ChinaGuangxi Transportation Science and Technology Group Co., Ltd., Nanning 530007, ChinaGuangxi Transportation Science and Technology Group Co., Ltd., Nanning 530007, ChinaNear-infrared (NIR) and thermal infrared (TIR) remote sensing are primary methods for monitoring large-scale, high-resolution precipitable water vapor (PWV); however, their application is limited to clear-sky conditions. To overcome this limitation and enable all-weather PWV retrieval, this study develops a new satellite-based PWV retrieval model to derive all-weather PWV at a spatial resolution of 300 m based on the synergistic use of NIR and TIR data from the Ocean and Land Colour Instrument (OLCI) and Sea and Land Surface Temperature Radiometer (SLSTR) instruments onboard the Sentinel-3B satellite. The proposed model consists of two sub-models for PWV derivation: one each for clear- and cloudy-sky conditions. The clear-sky PWV retrieval model integrates water vapor information from both NIR and TIR observations, whereas the cloudy-sky PWV retrieval model uses cloud-top properties derived from TIR data to correct the NIR water vapor within or above the clouds to the ground. Tested against the GNSS PWV, the new model has a root-mean-square error (RMSE) of 1.01 mm and bias of 0.09 mm for clear-sky conditions, representing a 51 % improvement in accuracy over the operational OLCI NIR products. For cloudy-sky conditions, the RMSE and bias are 2.66 mm and 0.02 mm, respectively, thereby filling the gap in high-quality PWV retrieval products under cloudy-sky conditions. The combined all-weather PWV product demonstrates robust spatiotemporal performance, with an RMSE and Bias of 1.92 mm and 0.16 mm, respectively. Given that the GNSS PWV has an accuracy of 1.37 mm, the accuracy achieved in this study is satisfactory.http://www.sciencedirect.com/science/article/pii/S1569843225003462Precipitable water vaporNear-infraredThermal infraredGNSSSentinel-3B |
| spellingShingle | Zheng Du Bao Zhang Yibin Yao Qingzhi Zhao Chaoqian Xu Qi Zhang Hongming Li Quanyu Chen Retrieving all-weather precipitable water vapor using near-infrared and thermal infrared observations International Journal of Applied Earth Observations and Geoinformation Precipitable water vapor Near-infrared Thermal infrared GNSS Sentinel-3B |
| title | Retrieving all-weather precipitable water vapor using near-infrared and thermal infrared observations |
| title_full | Retrieving all-weather precipitable water vapor using near-infrared and thermal infrared observations |
| title_fullStr | Retrieving all-weather precipitable water vapor using near-infrared and thermal infrared observations |
| title_full_unstemmed | Retrieving all-weather precipitable water vapor using near-infrared and thermal infrared observations |
| title_short | Retrieving all-weather precipitable water vapor using near-infrared and thermal infrared observations |
| title_sort | retrieving all weather precipitable water vapor using near infrared and thermal infrared observations |
| topic | Precipitable water vapor Near-infrared Thermal infrared GNSS Sentinel-3B |
| url | http://www.sciencedirect.com/science/article/pii/S1569843225003462 |
| work_keys_str_mv | AT zhengdu retrievingallweatherprecipitablewatervaporusingnearinfraredandthermalinfraredobservations AT baozhang retrievingallweatherprecipitablewatervaporusingnearinfraredandthermalinfraredobservations AT yibinyao retrievingallweatherprecipitablewatervaporusingnearinfraredandthermalinfraredobservations AT qingzhizhao retrievingallweatherprecipitablewatervaporusingnearinfraredandthermalinfraredobservations AT chaoqianxu retrievingallweatherprecipitablewatervaporusingnearinfraredandthermalinfraredobservations AT qizhang retrievingallweatherprecipitablewatervaporusingnearinfraredandthermalinfraredobservations AT hongmingli retrievingallweatherprecipitablewatervaporusingnearinfraredandthermalinfraredobservations AT quanyuchen retrievingallweatherprecipitablewatervaporusingnearinfraredandthermalinfraredobservations |