Assessing and Improving Land Surface Model Outputs Over Africa Using GRACE, Field, and Remote Sensing Data

The Gravity Recovery and Climate Experiment (GRACE), along with other relevant field and remote sensing datasets, was used to assess the performance of two land surface models (LSMs: CLM4.5-SP and GLDAS-Noah) over the African continent and improve the outputs of the CLM4.5-SP model. Spatial and temporal analysis of monthly (January 2003–December 2010) Terrestrial Water Storage (TWS) estimates extracted from GRACE (TWSGRACE), CLM4.5-SP (TWSCLM4.5), and GLDAS-Noah (TWSGLDAS) indicates the following: (1) compared to GRACE, LSMs overestimate TWS in winter months and underestimate them in summer months; (2) the amplitude of annual cycle (AAC) of TWSGRACE is higher than that of TWSLSM (AAC: TWSGRACE > TWSGLDAS > TWSCLM4.5); (3) higher, and statistically significant correlations were observed between TWSGRACE and TWSGLDAS compared to those between TWSGRACE and TWSCLM4.5; (4) differences in forcing precipitation and temperature datasets for GLDAS-Noah and CLM4.5-SP models are unlikely to be the main cause for the observed discrepancies between TWSGRACE and TWSLSM; and (5) the CLM4.5-SP model overestimates evapotranspiration (ET) values in summer months and underestimates them in winter months compared to ET estimates extracted from field-based (FLUXNET-MTE) and satellite-based (MOD16 and GLEAM) ET measurements. A first-order correction was developed and applied to correct the CLM4.5-derived ET, soil moisture, groundwater, and TWS. The corrections improved the correspondence (i.e., higher correlation and comparable AAC) between TWSCLM4.5 and TWSGRACE over various climatic settings. Our findings suggest that similar straightforward correction approaches could potentially be developed and used to assess and improve the performance of a wide range of LSMs.

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