RegCM4.0对一个全球模式20世纪气候变化试验的中国区域降尺度:温室气体和自然变率的贡献

Abstract

China has experienced warming and a pattern of southern flood and northern drought in precipitation in recent decades. Attributable contributions of greenhouse gas emissions and natural climate variability to these phenomena are discussed for China and the main hydrological basins, based on a comparison of historical and attribution simulation tests using a regional climate model (RegCM4.0). Two tests are performed at a resolution of 50 km, driven by the results of BCC_CSM1.1 historical and attribution simulation tests of CMIP5 in 1961-2005, respectively. The forcing of greenhouse gas emissions and natural climate variability are included in the historical test, and greenhouse gas emission is excluded in the attribution test. Results show that the simulated trends of temperature and precipitation from RegCM4.0 are more reasonable than from BCC_CSM1.1 for 1961-2005, and the warming during this period was mainly caused by the emission of greenhouse gases, although natural climate variability also led to regional warming in most areas except the Tibetan Plateau. The warming magnitude from greenhouse gas emissions was much larger than from natural climate variability over most basins and China as a whole, with 80% of the warming attributable to forcing by greenhouse gases. The southern flood and northern drought pattern of precipitation in Eastern China may be largely due to natural climate variability, and greenhouse gas emission to some extent weakens the strength of this change; increased precipitation in Northwest China is mainly induced by increased greenhouse gas emission, while natural climate variability, in contrast, leads to reduced precipitation. The assessments of temperature are more reliable than those of precipitation, because model limitations and the complex relationship between precipitation and external factors result in large remaining uncertainties in precipitation assessments. It should be pointed out that attribution studies of climate change on the regional scale are very complex, and only preliminary modeling results of aerosol and land use forcing in the absence are shown in this study. An ensemble of multiple models and samples with statistical significance and confidence is needed for comprehensive detection and attribution studies, and the limitations associated with all these factors lead to large uncertainties in the conclusions. The aim of this study is to provide a detection and attribution method for studying regional climate change. A more comprehensive and accurate understanding of the causes of climate change in China would require further regional climate simulations and analyses.