| 英文摘要: | The Intergovernmental Panel on Climate Change’s Fifth Assessment Report largely depends on simulations, predictions and projections by climate models1. Most models, however, have deficiencies and biases that raise large uncertainties in their products. Over the past several decades, a tremendous effort has been made to improve model performance in the simulation of special regions and aspects of the climate system2, 3, 4. Here we show that biases or errors in special regions can be linked with others at far away locations. We find in 22 climate models that regional sea surface temperature (SST) biases are commonly linked with the Atlantic meridional overturning circulation (AMOC), which is characterized by the northward flow in the upper ocean and returning southward flow in the deep ocean. A simulated weak AMOC is associated with cold biases in the entire Northern Hemisphere with an atmospheric pattern that resembles the Northern Hemisphere annular mode. The AMOC weakening is also associated with a strengthening of Antarctic Bottom Water formation and warm SST biases in the Southern Ocean. It is also shown that cold biases in the tropical North Atlantic and West African/Indian monsoon regions during the warm season in the Northern Hemisphere have interhemispheric links with warm SST biases in the tropical southeastern Pacific and Atlantic, respectively. The results suggest that improving the simulation of regional processes may not suffice for overall better model performance, as the effects of remote biases may override them. The United Nations Intergovernmental Panel on Climate Change’s Fifth Assessment Report updates the knowledge and understanding of the scientific, technical and socio-economic aspects of climate change. The report relies heavily on the products of climate models. These, however, have serious systematic errors that challenge the reliability of climate predictions. Hence, climate model bias identification and reduction are topics of great importance. One major reason for such biases is the misrepresentations of physical processes, which can be amplified by feedbacks among climate components especially in the tropics. Much effort, therefore, is dedicated to the better representation of physical processes in coordination with intense process studies5. This paper focuses on the SST simulations by 22 participants in the Coupled Model Intercomparison Project phase 5 (CMIP5; Supplementary Information). We target the global connections among regional SST biases. The existence of such connections means that efforts to improve model performance cannot be narrowly focused on particular regions. SSTs simulated by CMIP5 models generally show too low values in the Northern Hemisphere and too high values in the Southern Hemisphere. Annual-mean SST error (that is, mean SST bias for the period from 1900 to 2005) magnitudes can be several degrees Celsius (Fig. 1a). SSTs are clearly too high in the tropical southeastern Pacific and Atlantic and too low in the equatorial and tropical southwestern Pacific. In general, these biases have patterns that are largely independent of season, but amplitudes can vary with season (Supplementary Fig. 1). For example, the warm SST bias in the Southern Ocean is present throughout the year but is much stronger during the austral summer and autumn. It is noted that the SST biases in these models are quite stable during the 1900–2005 period and the models do not show a significant SST bias trend.
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