Bridging Terrestrial Water Storage Anomaly During GRACE/GRACE-FO Gap Using SSA Method: A Case Study in China
The terrestrial water storage anomaly (TWSA) gap between the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) is now a significant issue for scientific research in high-resolution time-variable gravity fields. This paper proposes the use of singular spectrum analy...
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MDPI AG
2019-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/19/4144 |
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| author | Wanqiu Li Wei Wang Chuanyin Zhang Hanjiang Wen Yulong Zhong Yu Zhu Zhen Li |
| author_facet | Wanqiu Li Wei Wang Chuanyin Zhang Hanjiang Wen Yulong Zhong Yu Zhu Zhen Li |
| author_sort | Wanqiu Li |
| collection | DOAJ |
| description | The terrestrial water storage anomaly (TWSA) gap between the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) is now a significant issue for scientific research in high-resolution time-variable gravity fields. This paper proposes the use of singular spectrum analysis (SSA) to predict the TWSA derived from GRACE. We designed a case study in six regions in China (North China Plain (NCP), Southwest China (SWC), Three-River Headwaters Region (TRHR), Tianshan Mountains Region (TSMR), Heihe River Basin (HRB), and Lishui and Wenzhou area (LSWZ)) using GRACE RL06 data from January 2003 to August 2016 for inversion, which were compared with Center for Space Research (CSR), Helmholtz-Centre Potsdam-German Research Centre for Geosciences (GFZ), Jet Propulsion Laboratory (JPL)’s Mascon (Mass Concentration) RL05, and JPL’s Mascon RL06. We evaluated the accuracy of SSA prediction on different temporal scales based on the correlation coefficient (<i>R</i>), Nash−Sutcliffe efficiency (NSE), and root mean square error (RMSE), which were compared with that of an auto-regressive and moving average (ARMA) model. The TWSA from September 2016 to May 2019 were predicted using SSA, which was verified using Mascon RL06, the Global Land Data Assimilation System model, and GRACE-FO results. The results show that: (1) TWSA derived from GRACE agreed well with Mascon in most regions, with the highest consistency with Mascon RL06 and (2) prediction accuracy of GRACE in TRHR and SWC was higher. SSA reconstruction improved <i>R</i>, NSE, and RMSE compared with those of ARMA. The <i>R</i> values for predicting TWS in the six regions using the SSA method were 0.34−0.98, which was better than those for ARMA (0.26−0.97), and the RMSE values were 0.03−5.55 cm, which were better than the 2.29−5.11 cm RMSE for ARMA as a whole. (3) The SSA method produced better predictions for obvious periodic and trending characteristics in the TWSA in most regions, whereas the detailed signal could not be effectively predicted. (4) The predicted TWSA from September 2016 to May 2019 were basically consistent with Global Land Data Assimilation System (GLDAS) results, and the predicted TWSA during June 2018 to May 2019 agreed well with GRACE-FO results. The research method in this paper provides a reference for bridging the gap in the TWSA between GRACE and GRACE-FO. |
| first_indexed | 2024-04-11T12:19:34Z |
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| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T12:19:34Z |
| publishDate | 2019-09-01 |
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| spelling | doaj.art-9e1af9d4e7354b6eb4f96b82a30bc03d2022-12-22T04:24:10ZengMDPI AGSensors1424-82202019-09-011919414410.3390/s19194144s19194144Bridging Terrestrial Water Storage Anomaly During GRACE/GRACE-FO Gap Using SSA Method: A Case Study in ChinaWanqiu Li0Wei Wang1Chuanyin Zhang2Hanjiang Wen3Yulong Zhong4Yu Zhu5Zhen Li6Chinese Academy of Surveying & Mapping, Beijing 100830, ChinaChinese Academy of Surveying & Mapping, Beijing 100830, ChinaChinese Academy of Surveying & Mapping, Beijing 100830, ChinaChinese Academy of Surveying & Mapping, Beijing 100830, ChinaSchool of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, ChinaInstitute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, ChinaGNSS Research Center, Wuhan University, Wuhan 430079, ChinaThe terrestrial water storage anomaly (TWSA) gap between the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) is now a significant issue for scientific research in high-resolution time-variable gravity fields. This paper proposes the use of singular spectrum analysis (SSA) to predict the TWSA derived from GRACE. We designed a case study in six regions in China (North China Plain (NCP), Southwest China (SWC), Three-River Headwaters Region (TRHR), Tianshan Mountains Region (TSMR), Heihe River Basin (HRB), and Lishui and Wenzhou area (LSWZ)) using GRACE RL06 data from January 2003 to August 2016 for inversion, which were compared with Center for Space Research (CSR), Helmholtz-Centre Potsdam-German Research Centre for Geosciences (GFZ), Jet Propulsion Laboratory (JPL)’s Mascon (Mass Concentration) RL05, and JPL’s Mascon RL06. We evaluated the accuracy of SSA prediction on different temporal scales based on the correlation coefficient (<i>R</i>), Nash−Sutcliffe efficiency (NSE), and root mean square error (RMSE), which were compared with that of an auto-regressive and moving average (ARMA) model. The TWSA from September 2016 to May 2019 were predicted using SSA, which was verified using Mascon RL06, the Global Land Data Assimilation System model, and GRACE-FO results. The results show that: (1) TWSA derived from GRACE agreed well with Mascon in most regions, with the highest consistency with Mascon RL06 and (2) prediction accuracy of GRACE in TRHR and SWC was higher. SSA reconstruction improved <i>R</i>, NSE, and RMSE compared with those of ARMA. The <i>R</i> values for predicting TWS in the six regions using the SSA method were 0.34−0.98, which was better than those for ARMA (0.26−0.97), and the RMSE values were 0.03−5.55 cm, which were better than the 2.29−5.11 cm RMSE for ARMA as a whole. (3) The SSA method produced better predictions for obvious periodic and trending characteristics in the TWSA in most regions, whereas the detailed signal could not be effectively predicted. (4) The predicted TWSA from September 2016 to May 2019 were basically consistent with Global Land Data Assimilation System (GLDAS) results, and the predicted TWSA during June 2018 to May 2019 agreed well with GRACE-FO results. The research method in this paper provides a reference for bridging the gap in the TWSA between GRACE and GRACE-FO.https://www.mdpi.com/1424-8220/19/19/4144GRACETWSASSApredictiondata gap |
| spellingShingle | Wanqiu Li Wei Wang Chuanyin Zhang Hanjiang Wen Yulong Zhong Yu Zhu Zhen Li Bridging Terrestrial Water Storage Anomaly During GRACE/GRACE-FO Gap Using SSA Method: A Case Study in China Sensors GRACE TWSA SSA prediction data gap |
| title | Bridging Terrestrial Water Storage Anomaly During GRACE/GRACE-FO Gap Using SSA Method: A Case Study in China |
| title_full | Bridging Terrestrial Water Storage Anomaly During GRACE/GRACE-FO Gap Using SSA Method: A Case Study in China |
| title_fullStr | Bridging Terrestrial Water Storage Anomaly During GRACE/GRACE-FO Gap Using SSA Method: A Case Study in China |
| title_full_unstemmed | Bridging Terrestrial Water Storage Anomaly During GRACE/GRACE-FO Gap Using SSA Method: A Case Study in China |
| title_short | Bridging Terrestrial Water Storage Anomaly During GRACE/GRACE-FO Gap Using SSA Method: A Case Study in China |
| title_sort | bridging terrestrial water storage anomaly during grace grace fo gap using ssa method a case study in china |
| topic | GRACE TWSA SSA prediction data gap |
| url | https://www.mdpi.com/1424-8220/19/19/4144 |
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