A Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS Measurements
Tropospheric delay is a major error source in the Global Navigation Satellite System (GNSS), and the weighted mean temperature (T<sub>m</sub>) is a key parameter in precipitable water vapor (PWV) retrieval. Although reanalysis products like the National Centers for Environmental Predicti...
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| Format: | Article |
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MDPI AG
2021-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/15/3008 |
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| author | Lijie Guo Liangke Huang Junyu Li Lilong Liu Ling Huang Bolin Fu Shaofeng Xie Hongchang He Chao Ren |
| author_facet | Lijie Guo Liangke Huang Junyu Li Lilong Liu Ling Huang Bolin Fu Shaofeng Xie Hongchang He Chao Ren |
| author_sort | Lijie Guo |
| collection | DOAJ |
| description | Tropospheric delay is a major error source in the Global Navigation Satellite System (GNSS), and the weighted mean temperature (T<sub>m</sub>) is a key parameter in precipitable water vapor (PWV) retrieval. Although reanalysis products like the National Centers for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-Interim) data have been used to calculate and model the tropospheric delay, T<sub>m</sub>, and PWV, the limitations of the temporal and spatial resolutions of the reanalysis data have affected their performance. The release of the fifth-generation accurate global atmospheric reanalysis (ERA5) and the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) provide the opportunity to overcome these limitations. The performances of the zenith tropospheric delay (ZTD), zenith wet delay (ZWD), T<sub>m</sub>, and zenith hydrostatic delay (ZHD) of ERA5 and MERRA-2 data from 2016 to 2017 were evaluated in this work using GNSS ZTD and radiosonde data over the globe. Taking GNSS ZTD as a reference, the ZTD calculated from MERRA-2 and ERA5 pressure-level data were evaluated in temporal and spatial scales, with an annual mean bias and root mean square (RMS) of 2.3 and 10.9 mm for ERA5 and 4.5 and 13.1 mm for MERRA-2, respectively. Compared to radiosonde data, the ZHD, ZWD, and T<sub>m</sub> derived from ERA5 and MERRA-2 data were also evaluated on temporal and spatial scales, with annual mean bias values of 1.1, 1.7 mm, and 0.14 K for ERA5 and 0.5, 4.8 mm, and –0.08 K for MERRA-2, respectively. Meanwhile, the annual mean RMS was 4.5, 10.5 mm, and 1.03 K for ERA5 and 4.4, 13.6 mm, and 1.17 K for MERRA-2, respectively. Tropospheric parameters derived from MERRA-2 and ERA5, with improved temporal and spatial resolutions, can provide a reference for GNSS positioning and PWV retrieval. |
| first_indexed | 2024-03-10T09:08:55Z |
| format | Article |
| id | doaj.art-284d8aa8673f4531b87211e497e7ff58 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T09:08:55Z |
| publishDate | 2021-07-01 |
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| series | Remote Sensing |
| spelling | doaj.art-284d8aa8673f4531b87211e497e7ff582023-11-22T06:07:28ZengMDPI AGRemote Sensing2072-42922021-07-011315300810.3390/rs13153008A Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS MeasurementsLijie Guo0Liangke Huang1Junyu Li2Lilong Liu3Ling Huang4Bolin Fu5Shaofeng Xie6Hongchang He7Chao Ren8College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, ChinaTropospheric delay is a major error source in the Global Navigation Satellite System (GNSS), and the weighted mean temperature (T<sub>m</sub>) is a key parameter in precipitable water vapor (PWV) retrieval. Although reanalysis products like the National Centers for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-Interim) data have been used to calculate and model the tropospheric delay, T<sub>m</sub>, and PWV, the limitations of the temporal and spatial resolutions of the reanalysis data have affected their performance. The release of the fifth-generation accurate global atmospheric reanalysis (ERA5) and the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) provide the opportunity to overcome these limitations. The performances of the zenith tropospheric delay (ZTD), zenith wet delay (ZWD), T<sub>m</sub>, and zenith hydrostatic delay (ZHD) of ERA5 and MERRA-2 data from 2016 to 2017 were evaluated in this work using GNSS ZTD and radiosonde data over the globe. Taking GNSS ZTD as a reference, the ZTD calculated from MERRA-2 and ERA5 pressure-level data were evaluated in temporal and spatial scales, with an annual mean bias and root mean square (RMS) of 2.3 and 10.9 mm for ERA5 and 4.5 and 13.1 mm for MERRA-2, respectively. Compared to radiosonde data, the ZHD, ZWD, and T<sub>m</sub> derived from ERA5 and MERRA-2 data were also evaluated on temporal and spatial scales, with annual mean bias values of 1.1, 1.7 mm, and 0.14 K for ERA5 and 0.5, 4.8 mm, and –0.08 K for MERRA-2, respectively. Meanwhile, the annual mean RMS was 4.5, 10.5 mm, and 1.03 K for ERA5 and 4.4, 13.6 mm, and 1.17 K for MERRA-2, respectively. Tropospheric parameters derived from MERRA-2 and ERA5, with improved temporal and spatial resolutions, can provide a reference for GNSS positioning and PWV retrieval.https://www.mdpi.com/2072-4292/13/15/3008MERRA-2ERA5GNSSradiosondetropospheric parameters |
| spellingShingle | Lijie Guo Liangke Huang Junyu Li Lilong Liu Ling Huang Bolin Fu Shaofeng Xie Hongchang He Chao Ren A Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS Measurements Remote Sensing MERRA-2 ERA5 GNSS radiosonde tropospheric parameters |
| title | A Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS Measurements |
| title_full | A Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS Measurements |
| title_fullStr | A Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS Measurements |
| title_full_unstemmed | A Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS Measurements |
| title_short | A Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS Measurements |
| title_sort | comprehensive evaluation of key tropospheric parameters from era5 and merra 2 reanalysis products using radiosonde data and gnss measurements |
| topic | MERRA-2 ERA5 GNSS radiosonde tropospheric parameters |
| url | https://www.mdpi.com/2072-4292/13/15/3008 |
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