Abstract
Anevapotranspiration (ET) ensemble composed of 36 land surface model (LSM) experiments and four diagnostic datasets (GLEAM, ALEXI, MOD16, and FLUXNET) is used to investigate uncertainties in ET estimate over five climate regions in West Africa. Diagnostic ET datasets show lower uncertainty estimates and smaller seasonal variations than the LSM-based ET values, particularly in the humid climate regions. Overall, the impact of the choice of LSMs and meteorological forcing datasets on the modeled ET rates increases from north to south. The LSM formulations and parameters have the largest impact on ET in humid regions, contributing to 90% of the ET uncertainty estimates. Precipitation contributes to the ET uncertainty primarily in arid regions. The LSM-based ET estimates are sensitive to the uncertainty of net radiation in arid region and precipitation in humid region. This study serves as support for better determining water availability for agriculture and livelihoods in Africa with earth observations and land surface models.
| Original language | English |
|---|---|
| Article number | 892 |
| Journal | Remote Sensing |
| Volume | 11 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 2019 Apr 1 |
Bibliographical note
Funding Information:Acknowledgments: Computing was supported by the resources at the NASA Center for Climate Simulation (NCCS). We acknowledge C. Hain and M. Anderson for use of the ALEXIS ET data. The MOD16 data are publicly available from http://files.ntsg.umt.edu/data/NTSG_Products/MOD16/, which was supported by the NASA Earth Observing System MODIS project. The GLEAM data are freely accessed from http://www.GLEAM.eu. The FLUXNET data are available from https://www.bgc-jena.mpg.de/geodb/.
Funding Information:
Funding: This study was funded by NASA SERVIR Applied Sciences Program in Earth Science Division (NNH15ZDA001N-SERVIR).
Publisher Copyright:
© 2019 by the authors.
All Science Journal Classification (ASJC) codes
- Earth and Planetary Sciences(all)