Suppr超能文献

利用 SSA 方法弥合 GRACE/GRACE-FO 期间的陆地水储量异常:以中国为例。

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

机构信息

Chinese Academy of Surveying & Mapping, Beijing 100830, China.

School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China.

出版信息

Sensors (Basel). 2019 Sep 24;19(19):4144. doi: 10.3390/s19194144.

Abstract

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.

摘要

陆地水存储异常(TWSA)是重力恢复和气候实验(GRACE)及其后续任务(GRACE-FO)之间的一个重大问题,这对高分辨率时变重力场的科学研究具有重要意义。本文提出了利用奇异谱分析(SSA)来预测 GRACE 衍生的 TWSA。我们使用 2003 年 1 月至 2016 年 8 月的 GRACE RL06 数据,在中国六个地区(华北平原(NCP)、西南地区(SWC)、三江源地区(TRHR)、天山山脉地区(TSMR)、黑河流域(HRB)和丽水、温州地区(LSWZ))进行了反演,与空间研究中心(CSR)、亥姆霍兹波茨坦地球科学研究中心(GFZ)、喷气推进实验室(JPL)的质量浓度(Mascon)RL05 和 JPL 的 Mascon RL06 进行了比较。我们基于相关系数()、纳什-斯屈特效率(NSE)和均方根误差(RMSE),对 SSA 在不同时间尺度上的预测精度进行了评估,并与自回归和移动平均(ARMA)模型进行了比较。利用 SSA 对 2016 年 9 月至 2019 年 5 月的 TWSA 进行了预测,并利用 Mascon RL06、全球陆地数据同化系统模型和 GRACE-FO 结果进行了验证。结果表明:(1)大多数地区 GRACE 衍生的 TWSA 与 Mascon 吻合较好,与 Mascon RL06 的一致性最高;(2)TRHR 和 SWC 地区 GRACE 的预测精度较高。SSA 重建提高了预测的相关系数、纳什-斯屈特效率和均方根误差,优于 ARMA。利用 SSA 方法预测六个地区的 TWS,其相关系数为 0.34-0.98,优于 ARMA(0.26-0.97),均方根误差为 0.03-5.55cm,优于 ARMA 的 2.29-5.11cm 整体均方根误差。(3)SSA 方法对大多数地区 TWSA 的明显周期性和趋势性特征产生了更好的预测效果,而对详细信号则无法进行有效预测。(4)2016 年 9 月至 2019 年 5 月的预测 TWSA 与全球陆地数据同化系统(GLDAS)的结果基本一致,2018 年 6 月至 2019 年 5 月的预测 TWSA 与 GRACE-FO 的结果吻合较好。本文的研究方法为弥合 GRACE 和 GRACE-FO 之间的 TWSA 差距提供了参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31e1/6806599/2de467600521/sensors-19-04144-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验