Articles | Volume 15, issue 15
Biogeosciences, 15, 4731–4757, 2018
Biogeosciences, 15, 4731–4757, 2018

Research article 08 Aug 2018

Research article | 08 Aug 2018

Evaluating and improving the Community Land Model's sensitivity to land cover

Ronny Meier1, Edouard L. Davin1, Quentin Lejeune1,a, Mathias Hauser1, Yan Li2, Brecht Martens3, Natalie M. Schultz4, Shannon Sterling5, and Wim Thiery1,6 Ronny Meier et al.
  • 1ETH Zurich, Institute for Atmospheric and Climate Science, Universitaetstrasse 16, 8092 Zurich, Switzerland
  • 2University of Illinois at Urbana-Champaign, Department of Natural Resources and Environmental Sciences, 1102 South Goodwin Avenue, Urbana, IL 61801, USA
  • 3Ghent University, Laboratory of Hydrology and Water Management, Coupure links 653, 9000 Ghent, Belgium
  • 4Yale University, School of Forestry and Environmental Studies, 195 Prospect Street, New Haven, CT 06511, USA
  • 5Dalhousie University, Department of Earth Sciences, 1459 Oxford Street, Halifax NS B3H 4R2, Canada
  • 6Vrije Universiteit Brussel, Department of Hydrology and Hydraulic Engineering, Pleinlaan 2, 1050 Brussels, Belgium
  • anow at: Climate Analytics, Ritterstrasse 3, 10969 Berlin, Germany

Abstract. Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remote-sensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate.

Short summary
Deforestation not only releases carbon dioxide to the atmosphere but also affects local climatic conditions by altering energy fluxes at the land surface and thereby the local temperature. Here, we evaluate the local impact of deforestation in a widely used land surface model. We find that the model reproduces the daytime warming effect of deforestation well. On the other hand, the warmer temperatures observed during night in forests are not present in this model.
Final-revised paper