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New insights in the capability of climate models to simulate the impact of LUC based on temperature decomposition of paired site observations
Author(s) -
Vanden Broucke Sam,
Luyssaert Sebastiaan,
Davin Edouard L.,
Janssens Ivan,
Lipzig Nicole
Publication year - 2015
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2015jd023095
Subject(s) - environmental science , deforestation (computer science) , albedo (alchemy) , sensible heat , climate model , climatology , daytime , longwave , atmospheric sciences , latent heat , coupled model intercomparison project , climate change , flux (metallurgy) , downwelling , downscaling , weather research and forecasting model , eddy covariance , meteorology , precipitation , geography , ecosystem , radiative transfer , geology , art , materials science , ecology , oceanography , computer science , performance art , biology , quantum mechanics , upwelling , metallurgy , art history , programming language , physics
In this study, we present a new methodology for evaluating the biogeophysical impact of land use change (LUC) in regional climate models. For this, we use observational data from paired eddy covariance flux towers in Europe, representing a LUC from forest to open land (deforestation). Two model simulations with the regional climate model COSMO‐CLM 2 (The Consortium for Small‐Scale Modelling model in climate mode COSMO‐CLM coupled to the Community Land Model CLM) are performed which differ only in prescribed land use for site pair locations. The model is evaluated by comparing the observed and simulated difference in surface temperature ( T s ) between open land and forests. Next, we identify the biogeophysical mechanisms responsible for T s differences by applying a decomposition method to both observations and model simulations. This allows us to determine which LUC‐related mechanisms were well represented in COSMO‐CLM 2 , and which were not. Results from observations show that deforestation leads to a significant cooling at night, which is severely underestimated by COSMO‐CLM 2 . It appears that the model is missing one crucial impact of deforestation on the nighttime surface energy budget: a reduction in downwelling longwave radiation. Results are better for daytime, as the model is able to simulate the increase in albedo and associated surface cooling following deforestation reasonably well. Also well simulated, albeit underestimated slightly, is the decrease in sensible heat flux caused by reduced surface roughness. Overall, these results stress the importance of differentiating between daytime and nighttime climate when discussing the effect of LUC on climate. Finally, we believe that they provide new insights supporting a wider application of the methodology (to other regional climate models).