深入研究以极端气温事件为代表的高影响天气气候现象的变化对人类应对气候变化具有重要的现实意义。但是目前对我国极端气温的发展变化规律及归因的研究工作开展有限。本项目将利用高分辨率格点化观测数据和CMIP5实验的多模式集合模拟数据开展对我国1961-2007年极端气温事件变化的发展规律量化和归因研究工作。一方面，项目将在申请人已有工作基础上验证人类活动，即温室气体排放、气溶胶排放和土地利用变化等因子对区域极端气温变化的影响；另一方面，项目将利用一般化极值理论，为我国格点化极端气温指数发展一种将观测数据与模式模拟数据相结合的建模方法，详细刻画区域二十年一遇、五十年一遇等极端气温事件发生的概率，并通过对模型的参数估计和假设检验，揭示这些灾害性事件在过去五十年里的发展变化规律，量化人类活动和自然活动对这些灾害天气发展变化的影响，为政府部门制定区域气候变化的适应政策提供重要的科学依据。

Detecting and attributing changes of extreme weather and climate events such as heat waves and cold waves are important, not only for being the frontier of climate change studies, but also for its role of providing key scientific evidence for our adaptation to climate change. In this study, we will employ gridded observational data and simulation results of multi-model ensembles (MME) from the latest CMIP5 experiments to detect and attribute natural and anthropogenic influences on changes of extreme temperatures during 1961-2007 in China. On one hand, under the framework of optimal fingerprint, CMIP5 MME will be used to verify findings in applicant's previous work on detecting human influence on extreme temperatures in China (Wen et al., 2013); on the other hand, based on the theory of Generalized Extreme Value (GEV), an innovative probability model will be proposed to describe changes in extreme temperatures in finer spatial resolution. Thus, influences of natural and anthropogenic forcings on changes of local extreme temperatures can be quantified through studying the statistical inference of the proposed model.This study attemps to provide scientific justifications on climate changes adaptation for local/provincial governments.