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Uncertainty in land surface temperature simulation over China by CMIP3/CMIP5 models

Hua, Wenjian, Chen, Haishan, Sun, Shanlei
Theoretical and applied climatology 2014 v.117 no.3-4 pp. 463-474
energy, heat transfer, meteorology and climatology, models, surface temperature, uncertainty, China
In this paper, China-based observations are used to evaluate the performance of 24 CMIP3 (phase 3 of the Coupled Model Intercomparison Project) and 10 CMIP5 models in simulating land surface temperature (LST). It is found that all models can generally reproduce the climatology patterns of LST averaged during the period from 1960 to 1999. Further analyses of the regional features of LST show that the discrepancies between the observations and the simulations are smaller in Southwest and East China. Moreover, these models overestimate the temperatures in almost all areas, particularly in July. Although many models have large biases relative to the observations, the spread of the model results is large (i.e., >22 °C in Northwest and Northeast China). For the interannual variations, neither the individual models nor the multi-model mean has a remarkable positive correlation to the observations in the selected subregions. However, most models can capture geographic features during trend evaluations. A multi-model ensemble is believed to be an effective way to limit uncertainties, but the results suggest that its efficiency is restricted to simulating the LST trend. Examination of the surface energy budget indicated that the modeled discrepancies of net shortwave radiation and surface sensible heat flux may be responsible for the LST results, especially in July. It is concluded that the ability of current models in simulating LST over China is still a significant challenge. The spread of the models is large in simulating the climatology, interannual variation, and trend of LSTs. In general, the magnitudes of the spread may be as large as the magnitudes of the observations. Additionally, it is found that multi-model ensembles do not simulate LST with any more skill. Therefore, more work must focus on the limitations of the models' uncertainties in land surface research.