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Bridging Terrestrial Water Storage Anomaly During GRACE/GRACE-FO Gap Using SSA Method: A Case Study in China

机译:使用SSA方法弥合GRACE / GRACE-FO间隙中的陆地储水异常:以中国为例

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摘要

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 ( ), 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 , NSE, and RMSE compared with those of ARMA. The 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.
机译:重力恢复和气候实验(GRACE)及其后续任务(GRACE-FO)之间的陆地储水异常(TWSA)差距现在已成为高分辨率时变重力场科学研究的重要课题。本文提出使用奇异频谱分析(SSA)来预测源自GRACE的TWSA。我们在中国六个地区(华北平原(NCP),西南地区(SWC),三河源头地区(TRHR),天山地区(TSMR),黑河流域(HRB)以及丽水和温州地区(LSWZ)使用2003年1月至2016年8月的GRACE RL06数据进行反演,并与空间研究中心(CSR),亥姆霍兹中心波茨坦-德国地球科学研究中心(GFZ)和喷气推进实验室(JPL)进行了比较)的Mascon(质量浓度)RL05和JPL的Mascon RL06。我们根据相关系数(),纳什-苏克利夫效率(NSE)和均方根误差(RMSE)评估了不同时间尺度上SSA预测的准确性,并与自回归和移动平均值( ARMA)模型。使用SSA预测了2016年9月至2019年5月的TWSA,并使用Mascon RL06,全球土地数据同化系统模型和GRACE-FO结果进行了验证。结果表明:(1)GRACE衍生的TWSA在大多数地区与Mascon吻合良好,与Mascon RL06的一致性最高,(2)GRACE在TRHR和SWC中的预测精度较高。与ARMA相比,SSA重建,NSE和RMSE有所改善。使用SSA方法在六个区域中预测的TWS值是0.34–0.98,优于ARMA的值(0.26-0.97),RMSE值是0.03–5.55 cm,优于2.29–5.11 cm整个ARMA的RMSE。 (3)SSA方法对大多数地区的TWSA中明显的周期性和趋势特征产生了更好的预测,而详细的信号却无法得到有效的预测。 (4)2016年9月至2019年5月的TWSA预测与全球土地数据同化系统(GLDAS)结果基本一致,2018年6月至2019年5月的TWSA预测与GRACE-FO结果吻合得很好。本文的研究方法为缩小TWSA在GRACE和GRACE-FO之间的差距提供了参考。

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