An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data
Precipitable water vapor (PWV) is one of the most variable components of the atmosphere in both space and time. In this study, a passive microwave-based retrieval algorithm for PWV over land without land surface temperature (LST) data was developed. To build the algorithm, two assumptions exist: (1)...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2016/4126393 |
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| author | Fang-Cheng Zhou Xiaoning Song Pei Leng Hua Wu Bo-Hui Tang |
| author_facet | Fang-Cheng Zhou Xiaoning Song Pei Leng Hua Wu Bo-Hui Tang |
| author_sort | Fang-Cheng Zhou |
| collection | DOAJ |
| description | Precipitable water vapor (PWV) is one of the most variable components of the atmosphere in both space and time. In this study, a passive microwave-based retrieval algorithm for PWV over land without land surface temperature (LST) data was developed. To build the algorithm, two assumptions exist: (1) land surface emissivities (LSE) at two adjacent frequencies are equal and (2) there are simple parameterizations that relate transmittance, atmospheric effective radiating temperature, and PWV. Error analyses were performed using radiosonde sounding observations from Zhangye, China, and CE318 measurements of Dalanzadgad (43°34′37′′N, 104°25′8′′E) and Singapore (1°17′52′′N, 103°46′48′′E) sites from Aerosol Robotic Network (AERONET), respectively. In Zhangye, the algorithm had a Root Mean Square Error (RMSE) of 4.39 mm and a bias of 0.36 mm on cloud-free days, while on cloudy days there was an RMSE of 4.84 mm and a bias of 0.52 mm because of the effect of liquid water in clouds. The validations in Dalanzadgad and Singapore sites showed that the retrieval algorithm had an RMSE of 4.73 mm and a bias of 0.84 mm and the bigger errors appeared when the water vapor was very dry or very moist. |
| format | Article |
| id | doaj-art-d697d78c6b544deda8484f5e26391653 |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-d697d78c6b544deda8484f5e263916532025-02-03T06:06:56ZengWileyAdvances in Meteorology1687-93091687-93172016-01-01201610.1155/2016/41263934126393An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite DataFang-Cheng Zhou0Xiaoning Song1Pei Leng2Hua Wu3Bo-Hui Tang4State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaUniversity of Chinese Academy of Sciences, Beijing 100049, ChinaKey Laboratory of Agri-Informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, ChinaState Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaPrecipitable water vapor (PWV) is one of the most variable components of the atmosphere in both space and time. In this study, a passive microwave-based retrieval algorithm for PWV over land without land surface temperature (LST) data was developed. To build the algorithm, two assumptions exist: (1) land surface emissivities (LSE) at two adjacent frequencies are equal and (2) there are simple parameterizations that relate transmittance, atmospheric effective radiating temperature, and PWV. Error analyses were performed using radiosonde sounding observations from Zhangye, China, and CE318 measurements of Dalanzadgad (43°34′37′′N, 104°25′8′′E) and Singapore (1°17′52′′N, 103°46′48′′E) sites from Aerosol Robotic Network (AERONET), respectively. In Zhangye, the algorithm had a Root Mean Square Error (RMSE) of 4.39 mm and a bias of 0.36 mm on cloud-free days, while on cloudy days there was an RMSE of 4.84 mm and a bias of 0.52 mm because of the effect of liquid water in clouds. The validations in Dalanzadgad and Singapore sites showed that the retrieval algorithm had an RMSE of 4.73 mm and a bias of 0.84 mm and the bigger errors appeared when the water vapor was very dry or very moist.http://dx.doi.org/10.1155/2016/4126393 |
| spellingShingle | Fang-Cheng Zhou Xiaoning Song Pei Leng Hua Wu Bo-Hui Tang An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data Advances in Meteorology |
| title | An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data |
| title_full | An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data |
| title_fullStr | An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data |
| title_full_unstemmed | An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data |
| title_short | An Algorithm for Retrieving Precipitable Water Vapor over Land Based on Passive Microwave Satellite Data |
| title_sort | algorithm for retrieving precipitable water vapor over land based on passive microwave satellite data |
| url | http://dx.doi.org/10.1155/2016/4126393 |
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