Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)

Timothy Glotfelty, Diana Ramírez-Mejía, Jared Bowden, Adrian Ghilardi, J. Jason West

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Land use and land cover change (LULCC) impacts local and regional climates through various biogeophysical processes. Accurate representation of land surface parameters in land surface models (LSMs) is essential to accurately predict these LULCC-induced climate signals. In this work, we test the applicability of the default Noah, Noah-MP, and Community Land Model (CLM) LSMs in the Weather Research and Forecasting (WRF) model over Sub-Saharan Africa. We find that the default WRF LSMs do not accurately represent surface albedo, leaf area index, and surface roughness in this region due to various flawed assumptions, including the treatment of the MODIS woody savanna land use and land cover (LULC) category as closed shrubland. Consequently, we developed a WRF CLM version with more accurate African land surface parameters (CLM-AF), designed such that it can be used to evaluate the influence of LULCC. We evaluate meteorological performance for the default LSMs and CLM-AF against observational datasets, gridded products, and satellite estimates. Further, we conduct LULCC experiments with each LSM to determine if differences in land surface parameters impact the LULCC-induced climate responses. Despite clear deficiencies in surface parameters, all LSMs reasonably capture the spatial pattern and magnitude of near-surface temperature and precipitation. However, in the LULCC experiments, inaccuracies in the default LSMs result in illogical localized temperature and precipitation changes. Differences in thermal changes between Noah-MP and CLM-AF indicate that the temperature impacts from LULCC are dependent on the sensitivity of evapotranspiration to LULCC in Sub-Saharan Africa. Errors in land surface parameters indicate that the default WRF LSMs considered are not suitable for LULCC experiments in tropical or Southern Hemisphere regions and that proficient meteorological model performance can mask these issues. We find CLM-AF to be suitable for use in Sub-Saharan Africa LULCC studies, but more work is needed by the WRF community to improve its applicability to other tropical and Southern Hemisphere climates.
Original languageEnglish
Pages (from-to)3215-3249
JournalGeoscientific Model Development
Volume14
Issue number6
DOIs
Publication statusPublished - 3 Jun 2021
Externally publishedYes

Funding

Financial support. This research has been supported by the Na- Acknowledgements. Special thanks are due to Tanya Spero, Jonathan Pleim, and Limei Ran of the United States Environmental Protection Agency for their valuable feedback on the development of CLM-AF. Computational resources were provided by Extreme Science and Engineering Discovery Environment (XSEDE) (Towns et al., 2014), which is supported by National Science Foundation (grant no. ACI-1548562). Simulations were conducted on the XSEDE stampede2 cluster provided by the Texas Advanced Computing Center, through allocation TG-ATM180014.

FundersFunder number
Extreme Science and Engineering Discovery Environment
XSEDE
National Science FoundationACI-1548562
Foundation for the National Institutes of HealthT32ES007018

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