2014 GSA Annual Meeting in Vancouver, British Columbia (19–22 October 2014)

Paper No. 19-14
Presentation Time: 11:15 AM

EVALUATING THE PERFORMANCE OF LAND SURFACE MODELS USING GRACE DATA OVER AFRICA  


AHMED, Mohamed1, SULTAN, Mohamed1, WAHR, John2 and YAN, Eugene3, (1)Geosciences, Western Michigan University, 1903 West Michigan Ave, Kalamazoo, MI 49008, (2)Physics, University of Colorado at Boulder, 2000 Colorado Avenue, Boulder, CO 80309, (3)Environment Science Division, Argonne National Laboratory, 9700 South Cass Ave, Argonne, IL 60439-4843

We utilize the Gravity Recovery and Climate Experiment (GRACE) and land surface models (LSM: GLDAS and CLM4.5) in conjunction with other readily-available datasets for monitoring the spatial and temporal trends in Terrestrial Water Storage (TWS) over a time period of 10 years (01/2003–12/2012) and to investigate the nature of, and the factors controlling , these variations over Africa. Spatial and temporal correlations of the trends extracted from processed (smoothed [Gaussian: 200km] and destriped) GRACE-derived (TWSGRACE) and LSM-derived (TWSLSM) TWS indicate the following: (1) Large (≥ 90 % by area) sectors of Africa are undergoing statistically significant TWSGRACE and TWSLSM variations due to natural and anthropogenic causes; (2) a general correspondence between TWSGRACE and TWSLSM over areas (e.g., Niger and Mozambique NE basins in eastern and western Africa) largely controlled by natural (i.e., increase/decrease in precipitation and/or temperature) causes; (3) discrepancies are observed over areas that witnessed extensive anthropogenic effects measured by TWSGRACE but unaccounted for by TWSLSM. Examples include: (a) strong (compared to that observed by TWSLSM) negative TWSGRACE trends were observed over areas that witnessed heavy groundwater extraction (e.g., Western, Desert, Egypt); (b) strong (compared to that observed by TWSLSM) positive TWSGRACE over Lake Volta reservoir; and (c) strong (compared to that observed by TWSLSM) negative trends over areas undergoing heavy deforestation (e.g., northern and NW Congo Basin); (4) additional discrepancies in other areas (e.g., Zambezi and the Okavango basins) are attributed to models being uncalibrated and not not simulating all of the TWS components (e.g., river storage and groundwater in GLDAS; lakes and reservoirs in GLDAS and CLM4.5) . Future work should focus on using TWSGRACE to calibrate TWSLSM.