Long‐Term (1979‐Present) Total Water Storage Anomalies Over the Global Land Derived by Reconstructing GRACE Data. Issue 8 (26th April 2021)

• Record Type: Journal Article
• Authors: Li, Fupeng; Kusche, Jürgen; Chao, Nengfang; Wang, Zhengtao; Löcher, Anno
• Is Part Of: Geophysical research letters. Volume 48:Issue 8(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-04-26
• Subjects: Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2021GL093492
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: The Gravity Recovery and Climate Experiment (GRACE) mission has monitored global total water storage anomalies (TWSA) with an unprecedented accuracy since 2002. Yet, many applications require a longer record, that is, extending prior to the GRACE period. Here, we present a new global reconstruction of long‐term (1979–2020) TWSA fields by combining machine learning with time series decomposition and statistical decomposition techniques. We find that the long‐term TWSA reconstructed from GRACE fits well with the GRACE‐FO observation over most grids (0.5° resolution) of the global land and successfully reproduces the strong El Niño signal. Comparisons to Satellite Laser Ranging solutions and to observed global mean sea level change suggest our reconstruction (doi: https://doi.org/10.5061/dryad.z612jm6bt ) is more reliable than previously published products. This study provides a viable approach for both reconstructing past TWSA and filling the GRACE data gap at the global scale. Plain Language Summary: Since 2002, temporal changes of vertically integrated water storage have been detected globally with unprecedented accuracy via satellite gravimetry, as first implemented with the Gravity Recovery and Climate Experiment (GRACE) satellites. However, no similar observation system has been in place before 2002, that could have used to measure the total water storage anomalies (TWSA) with an accuracy comparable to GRACE. Several approaches, such as machine learning, have been proposed in previous studies to reconstruct past TWSA based on their empirical relationships with the climatic/hydrological drivers (e.g., precipitation and soil moisture). Different from traditional approaches, we here combine machine learning with statistical decomposition techniques to reconstruct GRACE‐like TWSA (0.5° resolution) for the period 1979–2020 over the global land. We find that the reconstructed TWSA shows strong abnormal signals during El Niño years. In addition, we compare our reconstruction to recent TWSA data obtained using Satellite Laser Ranging analysis to five satellites, that is, Lageos‐1, Lageos‐2, Ajisai, Stella, and Starlette, in the period since 1993, and to the observed global mean sea level change as validations. The comparison suggests that our reconstruction is more accurate than previously published products. We suggest our method provides a viable alternative for reconstructing long‐term TWSA. Key Points: We reconstruct Gravity Recovery and Climate Experiment‐like (GRACE) total water storage anomaly (TWSA) fields over the global land surface for the period 1979–2020 TWSA reconstructed from GRACE fit well with GRACE Follow‐On data and correctly reproduce strong El Niño signals Outside the GRACE period, our reconstruction fits better with satellite laser ranging solutions and global mean sea level than previous reconstruction