Published March 9, 2021 | Version v2
Dataset Open

Predictions of the GRACE-derived terrestrial water storage anomalies generated by a Bayesian convolutional neural network

Authors/Creators

  • 1. Nanjing University

Description

This dataset provides predictions of the GRACE-derived terrestrial water storage anomalies (TWSAs) to fill the approximately one-year gap (July 2017-May 2018) between GRACE and its successor GRACE Follow-On. The predictions were obtained by a Bayesian convolutional neural network driven by the ERA5-land data (monthly precipitation, temperature, TWSAs, and cumulative water storage changes). The training period is April 2002-March 2014, the test periods are April 2014-June 2017 and June 2018-August 2020. 

Files

BCNN_Predictions4TestMonths.gif

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Additional details

Related works

Is supplement to
https://github.com/njujinchun/bcnn4gracev1.0.0 (URL)