Attribution of Forced and internal Chinese climate variability in the Common era (Afiche)

该项目利用气候代理记录和气候模拟重建和分析了中国近一千年的气候变化，主要目的是在正式的探测和归因研究中区分强迫和内部气候变化。我们将汇编分散和未分析的自然和文献代理信息财富，并应用先进的统计重建方法，包括贝叶斯层次模型（BHM）。一个产品将是一个网格化的温度和降水数据集，它允许对过去1000年中国气候演变的一致和区域结构视图。我们将利用IPCC-CMPI5数据库提供的越来越多的全球古气候模拟，并分析申请人已经使用ECHO-G和ECHAM5-MPIOM模式进行的过去千年模拟的集合。该集合提供了一套具有不同规定边界条件的模拟，因此适合于识别和解开过去单个强迫的影响。利用CLM模式进行的高分辨率区域模拟将增强全球模拟，从而更好地表示全球外部强迫、大尺度气候驱动因素（如ENSO、亚洲季风）及其与区域特征（地形、陆海对比、土地利用）之间的相互作用。这些结果将有助于估计中国气候对外部强迫变化的敏感性，并检验气候模式模拟过去气候变化的能力。此外，还将对过去一千年的区域气候变率进行探测和归因分析。该项目将通过考虑外部全球驱动因素、区域强迫和人类活动导致的大规模景观改变，有助于限制中国区域气候预估（包括季风区）的不确定性。

The project reconstructs and analyses the climate variability in China during the last millennium using climate proxy records and climate simulations, with the main goal of separating forced versus internal climatic variations in a formal detection and attribution study. We will compile the scattered and un-analysed wealth of natural and documentary proxy information and apply advanced statistical reconstructions methods, including Bayesian Hierarchical Modelling (BHM). A product will be a gridded temperature and precipitation dataset that allows for a consistent and regionally structured view of climate evolution over the past 1000 years over China.We will make use of the growing number of global palaeoclimate simulations that are available from the IPCC-CMPI5 data base and analyse the ensemble of last millennium simulations already conducted by the applicants with the models ECHO-G and ECHAM5-MPIOM. This ensemble offers a suite of simulations with different prescribed boundary conditions and thus is suitable to identify and disentangle the impact of the past individual forcings. The global simulations will be augmented by one high-resolution regional simulation with the model CLM that allow for a better representation of the interaction between the global external forcing, large-scale climate drivers (e.g. ENSO, the Asian Monsoon, and their interaction with the regional characteristics (topography, land-sea contrast, land-use). The output will allow to estimate the sensitivity of the climate in China to variations in external forcing and to test the skill of climate models in simulating past climate changes. Further, a detection and attribution analysis of regional climate variability for the past millennium will be performed. The project will help constraining the uncertainties in the regional climate projections for China (including the monsoon regions) by taking into account the external global drivers, the regional forcings and the large-scale modification of landscape due to human activities.