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Reconstruction Dataset of Spatial and Temporal Global Terrestrial Water Storage Anomalies (1981-2020)


DENG Shanshan1,2LIU Suxia*1,2,3MO Xingguo1,2,3JIANG Liguang4BAUER—GOTTWEIN Peter4
1 Key Laboratory of Water Cycle and Related Land Surface Processes,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China.2 College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100190,China.3 Sino-Danish College,University of Chinese Academy of Sciences,Beijing 100049,China.4 Department of Environmental Engineering,Technical University of Denmark,Bygningstorvet 2800,Kgs. Lyngby,Denmark

DOI:10.3974/geodb.2023.02.03.V1

Published:Feb. 2023

Visitors:4503       Data Files Downloaded:221      
Data Downloaded:11695.85 MB      Citations:

Key Words:

Terrestrial water storage,reconstruction,Global scale,1°,1981-2020

Abstract:

Terrestrial Water Storage (TWS) is the sum of water stored in all forms on the surface and underground, including snow, ice, soil water, groundwater, surface water, and vegetation water. TWS anomaly, i.e., the difference between instantaneous TWS values and an average, is an important variable for studying water cycle processes. Before the launch of the Gravity Recovery and Climate Experiment (GRACE) mission and its follow-on mission (GRACE-FO) satellites (2002), observations of TWS anomaly and its components were scarce. This dataset was developed based on multi-source data, including soil moisture, snow depth, precipitation, temperature, glacial water mass changes, and GRACE/GRACE-FO-derived TWS anomalies. Firstly, the soil water and snow depth data from ECMWF ERA 5-Land reanalysis were simply summed to estimate the TWS anomalies preliminarily; Secondly, considering the lack of polar data, preliminary estimation in the polar region was performed based on the precipitation and temperature data from ECMWF ERA 5 reanalysis using multiple linear regression model; Finally, these preliminary estimates were bias corrected by combining the glacial water mass change observations and the short-term GRACE/GRACE-FO-derived TWS anomaly data using the empirical orthogonal function decomposition and the linear regression model approaches, to obtain the reconstruction dataset of the spatial-temporal TWS anomalies for the period from January 1981 to June 2020. The dataset is consisted of the following data from January 1981 to June 2020: (1) reconstructed monthly TWS anomaly data in 1° resolution. The baseline is given as the average for the period of January 1981 to June 2020 in each grid; (2) monthly data of the global mean TWS anomaly. The dataset is archived in .mat and .xlsx formats, and consists of 3 data files with a total data size of 53.5 MB (compressed to one single file with 52.9 MB). The discovery publications based on this dataset were published at Journal of Climate, Vol. 33, No. 2, 2020 and Geophysical Research Letters, Vol. 48, No. 7, 2021.

Foundation Item:

Ministry of Science and Technology of P. R. China (2018YFE0106500, 2021xjkk0803, 2012CB957802); Danish International Development Agency (18-M01-DTU); Ministry of Education of P. R. China (201804910733)

Data Citation:

DENG Shanshan, LIU Suxia*, MO Xingguo, JIANG Liguang, BAUER—GOTTWEIN Peter. Reconstruction Dataset of Spatial and Temporal Global Terrestrial Water Storage Anomalies (1981-2020)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2023. https://doi.org/10.3974/geodb.2023.02.03.V1.

References:

[1] Yu, Y., Lin, Z. H., Qin, Z. K. Improved EOF-based bias correction method for seasonal forecasts and its application in IAP AGCM4.1 [J]. Atmospheric and Oceanic Science Letters, 2018, 11(6): 499-508.
     [2] Zemp, M., Huss, M., Thibert, E., et al. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016 [J]. Nature, 2019, 568(7752): 382-386.
     

Data Product:

ID Data Name Data Size Operation
1 TWSA_198101-202006.rar 54192.52KB
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