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Evaluation of coupled regional climate models in representing the local biophysical effects of afforestation over continental China

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Regional climate models have been widely used to examine the biophysical effects of afforestation, but their performances in this respect have rarely been evaluated. To fill this knowledge gap, an… Click to show full abstract

Regional climate models have been widely used to examine the biophysical effects of afforestation, but their performances in this respect have rarely been evaluated. To fill this knowledge gap, an evaluation method based on the “space for time” strategy is proposed here. Using this method, we validate the performances of three regional models, the Regional Climate Model (RegCM), Weather Research and Forecasting (WRF) model and the WRF model run at a convection-permitting resolution (WRF-CP), in representing the local biophysical effects of afforestation over continental China against satellite observations. The results show that WRF and WRF-CP can not accurately describe afforestation-induced changes in surface biophysical properties, e.g. albedo or leaf area index. Second, all models exhibit poor simulations of afforestation-induced changes in latent and sensible heat fluxes. In particular, the observed increase in the summer latent heat due to afforestation is substantially underestimated by all models. Third, the models are basically reasonable in representing the biophysical impact of afforestation on temperature. The cooling of the daily mean surface temperature and 2-meter temperature in summer are reproduced well. Nevertheless, the mechanism driving the cooling effect may be improperly represented by the models. Moreover, the models perform relatively poorly in representing the response of the daily minimum surface temperature to afforestation. This highlights the necessity of evaluating the representation of the biophysical effects by a model before the model is employed to carry out afforestation experiments. This study serves as a test bed for validating regional model performance in this respect.

Keywords: biophysical effects; effects afforestation; afforestation; regional climate; climate models

Journal Title: Journal of Climate
Year Published: 2021

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