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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/gmd-2020-193
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-193
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: development and technical paper 19 Aug 2020

Submitted as: development and technical paper | 19 Aug 2020

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This preprint is currently under review for the journal GMD.

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 Glotfelty1, Diana Ramírez-Mejía2, Jared Bowden3, Adrián Ghilardi2, and J. Jason West1 Timothy Glotfelty et al.
  • 1Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
  • 2Centre for Research in Environmental Geography, Universidad Nacional Autónoma de México, Morelia, 58190, Mexico
  • 3Department of Applied Ecology, North Carolina State University, Raleigh, NC 27695, USA

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 CLM LSMs in the Weather Research and Forecasting Model (WRF) 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 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 signals. 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 climate signals. Differences in thermal climate signals 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.

Timothy Glotfelty et al.

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Timothy Glotfelty et al.

Data sets

Africa-Bioclimate Regions Glotfelty, Timothy; Ramirez, Diana; Bowden, Jared; Ghilardi, Adrian; West, J. Jason https://doi.org/10.15139/S3/WHNILT

MODIS DinamicaEGO Land Use Data Glotfelty, Timothy; Ramirez, Diana; Bowden, Jared; Ghilardi, Adrian; West, J. Jason https://doi.org/10.15139/S3/BEA55Z

Model code and software

CLM-AF v 1.0 Code Glotfelty, Timothy; Ramirez, Diana; Bowden, Jared; Ghilardi, Adrian; West, J. Jason https://doi.org/10.15139/S3/DZ7XS3

CLM-AF Updated Radiation Codes Glotfelty, Timothy; Ramirez, Diana; Bowden, Jared; Ghilardi, Adrian; West, J. Jason https://doi.org/10.15139/S3/W2LWJV

Default WRF-CLM LAI Output Code Glotfelty, Timothy; Ramirez, Diana; Bowden, Jared; Ghilardi, Adrian; West, J. Jason https://doi.org/10.15139/S3/JGIQOE

Timothy Glotfelty et al.

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Latest update: 28 Sep 2020
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Short summary
Land use and land cover change is a major contributor to climate change in Africa. Here we document deficiencies in how a weather model represents the land surface of Africa and how we modify a common land surface model to overcome these deficiencies. Our tests reveal that the default weather model does not accurately predict and transition the properties of different African biomes and growing cycles. The manuscript demonstrates that our modified model addresses these limitations.
Land use and land cover change is a major contributor to climate change in Africa. Here we...
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