PMID- 31554328
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20190926
LR  - 20191108
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 19
IP  - 19
DP  - 2019 Sep 24
TI  - Bridging Terrestrial Water Storage Anomaly During GRACE/GRACE-FO Gap Using SSA 
      Method: A Case Study in China.
LID - 10.3390/s19194144 [doi]
LID - 4144
AB  - 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 (R), 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 R, NSE, and RMSE 
      compared with those of ARMA. The R 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.
FAU - Li, Wanqiu
AU  - Li W
AD  - Chinese Academy of Surveying & Mapping, Beijing 100830, China.
FAU - Wang, Wei
AU  - Wang W
AUID- ORCID: 0000-0003-2035-7093
AD  - Chinese Academy of Surveying & Mapping, Beijing 100830, China. 
      wangwei@casm.ac.cn.
FAU - Zhang, Chuanyin
AU  - Zhang C
AD  - Chinese Academy of Surveying & Mapping, Beijing 100830, China.
FAU - Wen, Hanjiang
AU  - Wen H
AD  - Chinese Academy of Surveying & Mapping, Beijing 100830, China.
FAU - Zhong, Yulong
AU  - Zhong Y
AUID- ORCID: 0000-0002-6172-2598
AD  - School of Geography and Information Engineering, China University of Geosciences 
      (Wuhan), Wuhan 430074, China.
FAU - Zhu, Yu
AU  - Zhu Y
AD  - Institute of International Rivers and Eco-Security, Yunnan University, Kunming 
      650500, China.
FAU - Li, Zhen
AU  - Li Z
AD  - GNSS Research Center, Wuhan University, Wuhan 430079, China.
LA  - eng
GR  - No. 41374081 and No. 41674024；No. 2016YFB0501702；No. AR1905 and No. 7771806；No. 
      SDKDYC190203/National Natural Science Foundation of China；Key Research and 
      Development Program；the Fundamental Research Funds for Chinese Academy of 
      Surveying and Mapping；Innovation Fund Designated for Graduate Students of 
      Shandong University of Science and Technology/
PT  - Journal Article
DEP - 20190924
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
PMC - PMC6806599
OTO - NOTNLM
OT  - GRACE
OT  - SSA
OT  - TWSA
OT  - data gap
OT  - prediction
COIS- The authors declare no conflict of interest.
EDAT- 2019/09/27 06:00
MHDA- 2019/09/27 06:01
PMCR- 2019/10/01
CRDT- 2019/09/27 06:00
PHST- 2019/07/31 00:00 [received]
PHST- 2019/09/20 00:00 [revised]
PHST- 2019/09/22 00:00 [accepted]
PHST- 2019/09/27 06:00 [entrez]
PHST- 2019/09/27 06:00 [pubmed]
PHST- 2019/09/27 06:01 [medline]
PHST- 2019/10/01 00:00 [pmc-release]
AID - s19194144 [pii]
AID - sensors-19-04144 [pii]
AID - 10.3390/s19194144 [doi]
PST - epublish
SO  - Sensors (Basel). 2019 Sep 24;19(19):4144. doi: 10.3390/s19194144.