Global analysis of approaches for deriving total water storage changes from GRACE satellites. Issue 4 (18th April 2015)

• Record Type: Journal Article
• Authors: Long, Di; Longuevergne, Laurent; Scanlon, Bridget R.
• Is Part Of: Water resources research. Volume 51:Issue 4(2015:Apr.)
• Page Start: 2574
• Page End: 2594
• Publication Date: 2015-04-18
• Subjects: GRACE -- global analysis -- scaling factor approach -- bias and leakage correction; Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2014WR016853
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: Increasing interest in use of GRACE satellites and a variety of new products to monitor changes in total water storage (TWS) underscores the need to assess the reliability of output from different products. The objective of this study was to assess skills and uncertainties of different approaches for processing GRACE data to restore signal losses caused by spatial filtering based on analysis of 1° × 1° grid‐scale data and in 60 river basins globally. Results indicate that scaling factors from six LSMs, including GLDAS‐1 four models (Noah2.7, Mosaic, VIC, and CLM 2.0), CLM 4.0, and WGHM, are similar over most of humid, subhumid, and high‐latitude regions but can differ by up to 100% over arid and semiarid basins and areas with intensive irrigation. Temporal variability in scaling factors is generally minor at the basin scale except in arid and semiarid regions, but can be appreciable at the 1° × 1° grid scale. Large differences in TWS anomalies from three processing approaches (scaling factor, additive, and multiplicative corrections) were found in arid and semiarid regions, areas with intensive irrigation, and relatively small basins (e.g., ≤200, 000 km 2 ). Furthermore, TWS anomaly products from gridded data with CLM4.0 scaling factors and the additive correction approach more closely agree with WGHM output than the multiplicative correction approach. This comprehensive evaluation of GRACE processing approaches should provide valuable guidance on applicability of different processing approaches with different climate settings and varying levels of irrigation. Key Points: Model dependence of scaling factors was examined using six land surface models Temporal variability of scaling factors was examined using GLDAS‐1 Noah Total water storage changes from three approaches were compared with WGHM output