Validation of FY-3D MERSI-2 Precipitable Water Vapor (PWV) Datasets Using Ground-Based PWV Data from AERONET
The medium resolution spectral imager-2 (MERSI-2) is one of the most important sensors onboard China’s latest polar-orbiting meteorological satellite, Fengyun-3D (FY-3D). The National Satellite Meteorological Center of China Meteorological Administration has developed four precipitable water vapor (...
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MDPI AG
2021-08-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/16/3246 |
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| author | Yanqing Xie Zhengqiang Li Weizhen Hou Jie Guang Yan Ma Yuyang Wang Siheng Wang Dong Yang |
| author_facet | Yanqing Xie Zhengqiang Li Weizhen Hou Jie Guang Yan Ma Yuyang Wang Siheng Wang Dong Yang |
| author_sort | Yanqing Xie |
| collection | DOAJ |
| description | The medium resolution spectral imager-2 (MERSI-2) is one of the most important sensors onboard China’s latest polar-orbiting meteorological satellite, Fengyun-3D (FY-3D). The National Satellite Meteorological Center of China Meteorological Administration has developed four precipitable water vapor (PWV) datasets using five near-infrared bands of MERSI-2, including the P905 dataset, P936 dataset, P940 dataset and the fusion dataset of the above three datasets. For the convenience of users, we comprehensively evaluate the quality of these PWV datasets with the ground-based PWV data derived from Aerosol Robotic Network. The validation results show that the P905, P936 and fused PWV datasets have relatively large systematic errors (−0.10, −0.11 and −0.07 g/cm<sup>2</sup>), whereas the systematic error of the P940 dataset (−0.02 g/cm<sup>2</sup>) is very small. According to the overall accuracy of these four PWV datasets by our assessments, they can be ranked in descending order as P940 dataset, fused dataset, P936 dataset and P905 dataset. The root mean square error (RMSE), relative error (RE) and percentage of retrieval results with error within <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>±</mo><mrow><mo>(</mo><mrow><mn>0.05</mn><mo>+</mo><mn>0.10</mn><mo>∗</mo><mi>P</mi><mi>W</mi><msub><mi>V</mi><mrow><mi>A</mi><mi>E</mi><mi>R</mi><mi>O</mi><mi>N</mi><mi>E</mi><mi>T</mi></mrow></msub></mrow><mo>)</mo></mrow></mrow></semantics></math></inline-formula> (PER10) of the P940 PWV dataset are 0.24 g/cm<sup>2</sup>, 0.10 and 76.36%, respectively. The RMSE, RE and PER10 of the P905 PWV dataset are 0.38 g/cm<sup>2</sup>, 0.15 and 57.72%, respectively. In order to obtain a clearer understanding of the accuracy of these four MERSI-2 PWV datasets, we compare the accuracy of these four MERSI-2 PWV datasets with that of the widely used MODIS PWV dataset and AIRS PWV dataset. The results of the comparison show that the accuracy of the MODIS PWV dataset is not as good as that of all four MERSI-2 PWV datasets, due to the serious overestimation of the MODIS PWV dataset (0.40 g/cm<sup>2</sup>), and the accuracy of the AIRS PWV dataset is worse than that of the P940 and fused MERSI-2 PWV datasets. In addition, we analyze the error distribution of the four PWV datasets in different locations, seasons and water vapor content. Finally, the reason why the fused PWV dataset is not the one with the highest accuracy among the four PWV datasets is discussed. |
| first_indexed | 2024-03-10T08:25:53Z |
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| language | English |
| last_indexed | 2024-03-10T08:25:53Z |
| publishDate | 2021-08-01 |
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| series | Remote Sensing |
| spelling | doaj.art-edd58781cb6e4e1388ff80da92e900d92023-11-22T09:34:28ZengMDPI AGRemote Sensing2072-42922021-08-011316324610.3390/rs13163246Validation of FY-3D MERSI-2 Precipitable Water Vapor (PWV) Datasets Using Ground-Based PWV Data from AERONETYanqing Xie0Zhengqiang Li1Weizhen Hou2Jie Guang3Yan Ma4Yuyang Wang5Siheng Wang6Dong Yang7State Environment Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaState Environment Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaState Environment Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaState Environment Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaState Environment Protection Key Laboratory of Satellite Remote Sensing, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaInstitute of Remote Sensing Satellite, China Academy of Space Technology, Beijing 100094, ChinaInstitute of Remote Sensing Satellite, China Academy of Space Technology, Beijing 100094, ChinaInstitute of Remote Sensing Satellite, China Academy of Space Technology, Beijing 100094, ChinaThe medium resolution spectral imager-2 (MERSI-2) is one of the most important sensors onboard China’s latest polar-orbiting meteorological satellite, Fengyun-3D (FY-3D). The National Satellite Meteorological Center of China Meteorological Administration has developed four precipitable water vapor (PWV) datasets using five near-infrared bands of MERSI-2, including the P905 dataset, P936 dataset, P940 dataset and the fusion dataset of the above three datasets. For the convenience of users, we comprehensively evaluate the quality of these PWV datasets with the ground-based PWV data derived from Aerosol Robotic Network. The validation results show that the P905, P936 and fused PWV datasets have relatively large systematic errors (−0.10, −0.11 and −0.07 g/cm<sup>2</sup>), whereas the systematic error of the P940 dataset (−0.02 g/cm<sup>2</sup>) is very small. According to the overall accuracy of these four PWV datasets by our assessments, they can be ranked in descending order as P940 dataset, fused dataset, P936 dataset and P905 dataset. The root mean square error (RMSE), relative error (RE) and percentage of retrieval results with error within <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>±</mo><mrow><mo>(</mo><mrow><mn>0.05</mn><mo>+</mo><mn>0.10</mn><mo>∗</mo><mi>P</mi><mi>W</mi><msub><mi>V</mi><mrow><mi>A</mi><mi>E</mi><mi>R</mi><mi>O</mi><mi>N</mi><mi>E</mi><mi>T</mi></mrow></msub></mrow><mo>)</mo></mrow></mrow></semantics></math></inline-formula> (PER10) of the P940 PWV dataset are 0.24 g/cm<sup>2</sup>, 0.10 and 76.36%, respectively. The RMSE, RE and PER10 of the P905 PWV dataset are 0.38 g/cm<sup>2</sup>, 0.15 and 57.72%, respectively. In order to obtain a clearer understanding of the accuracy of these four MERSI-2 PWV datasets, we compare the accuracy of these four MERSI-2 PWV datasets with that of the widely used MODIS PWV dataset and AIRS PWV dataset. The results of the comparison show that the accuracy of the MODIS PWV dataset is not as good as that of all four MERSI-2 PWV datasets, due to the serious overestimation of the MODIS PWV dataset (0.40 g/cm<sup>2</sup>), and the accuracy of the AIRS PWV dataset is worse than that of the P940 and fused MERSI-2 PWV datasets. In addition, we analyze the error distribution of the four PWV datasets in different locations, seasons and water vapor content. Finally, the reason why the fused PWV dataset is not the one with the highest accuracy among the four PWV datasets is discussed.https://www.mdpi.com/2072-4292/13/16/3246precipitable water vapor (PWV)validationMERSI-2FY-3DAERONET |
| spellingShingle | Yanqing Xie Zhengqiang Li Weizhen Hou Jie Guang Yan Ma Yuyang Wang Siheng Wang Dong Yang Validation of FY-3D MERSI-2 Precipitable Water Vapor (PWV) Datasets Using Ground-Based PWV Data from AERONET Remote Sensing precipitable water vapor (PWV) validation MERSI-2 FY-3D AERONET |
| title | Validation of FY-3D MERSI-2 Precipitable Water Vapor (PWV) Datasets Using Ground-Based PWV Data from AERONET |
| title_full | Validation of FY-3D MERSI-2 Precipitable Water Vapor (PWV) Datasets Using Ground-Based PWV Data from AERONET |
| title_fullStr | Validation of FY-3D MERSI-2 Precipitable Water Vapor (PWV) Datasets Using Ground-Based PWV Data from AERONET |
| title_full_unstemmed | Validation of FY-3D MERSI-2 Precipitable Water Vapor (PWV) Datasets Using Ground-Based PWV Data from AERONET |
| title_short | Validation of FY-3D MERSI-2 Precipitable Water Vapor (PWV) Datasets Using Ground-Based PWV Data from AERONET |
| title_sort | validation of fy 3d mersi 2 precipitable water vapor pwv datasets using ground based pwv data from aeronet |
| topic | precipitable water vapor (PWV) validation MERSI-2 FY-3D AERONET |
| url | https://www.mdpi.com/2072-4292/13/16/3246 |
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