4.7 Article

An Iterative ICA-Based Reconstruction Method to Produce Consistent Time-Variable Total Water Storage Fields Using GRACE and Swarm Satellite Data

期刊

REMOTE SENSING
卷 12, 期 10, 页码 -

出版社

MDPI
DOI: 10.3390/rs12101639

关键词

GRACE; GRACE-FO; Swarm; independent component analysis (ICA); data reconstruction; trends of mass changes; world river basins; iterative ICA reconstruction

资金

  1. DAAD [57445178]
  2. Cardiff University's Vice Chancellor fund
  3. ESA's Swarm DISC Project [SW-CO-DTU-GS-111]
  4. Strategic Priority Research Program of the Chinese Academy of Sciences [XDA19070302]
  5. National Key Research & Development Program of China [017YFA0603103]
  6. [LTT18011]

向作者/读者索取更多资源

Observing global terrestrial water storage changes (TWSCs) from (inter-)seasonal to (multi-)decade time-scales is very important to understand the Earth as a system under natural and anthropogenic climate change. The primary goal of the Gravity Recovery And Climate Experiment (GRACE) satellite mission (2002-2017) and its follow-on mission (GRACE-FO, 2018-onward) is to provide time-variable gravity fields, which can be converted to TWSCs with similar to 300 km spatial resolution; however, the one year data gap between GRACE and GRACE-FO represents a critical discontinuity, which cannot be replaced by alternative data or model with the same quality. To fill this gap, we applied time-variable gravity fields (2013-onward) from the Swarm Earth explorer mission with low spatial resolution of similar to 1500 km. A novel iterative reconstruction approach was formulated based on the independent component analysis (ICA) that combines the GRACE and Swarm fields. The reconstructed TWSC fields of 2003-2018 were compared with a commonly applied reconstruction technique and GRACE-FO TWSC fields, whose results indicate a considerable noise reduction and long-term consistency improvement of the iterative ICA reconstruction technique. They were applied to evaluate trends and seasonal mass changes (of 2003-2018) within the world's 33 largest river basins.

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