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Predictive-analysis-of-GRACE-satellite-data

This is the combines Deep Learning for fusing GRACE Satellite data and reseach done on the following paper.

Research paper: "Combining physically based modeling and Deep Learning for fusing GRACE satellite data: Can we learn from mismatch?"

Data used:

GRACE-> Gravity recovery and climate experiment (GRACE) enabled remote sensing of TWS anomalies, i.e., variations from a long-term mean, at regional to continental scales. This study uses the monthly mascon TWSA product released by Jet Propulsion Laboratory (JPL).

NOAH-> (Available from 2000-2019) The NOAH LSM from NASA's global land data assimilation system maintains surface energy and water balances and simulate the exchange of water and energy fluxes at a soil-atmosphere interface. The NOAH simulated TWS is calculated by summing soil moisture in all four soil layers (0-200 cm depth), accumulative snow water, and total canopy water storage.

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