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

公元元年中国强迫气候变率和内部气候变率的归因（Afiche）

• 批准号: 241164240
• 负责人: Dr. Johann Jungclaus
• 金额: --
• 依托单位: Max-Planck-Institut für Meteorologie (MPI-M)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2013
• 资助国家: 德国
• 起止时间: 2012-12-31 至 2016-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/241164240?language=en
• 关键词: Attribution; Forced; internal; Chinese; climate

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.

该项目利用气候代用记录和气候模拟重建和分析了中国上个千年的气候变率，主要目标是在正式的检测和归因研究中将强迫气候变化与内部气候变化分开。我们将汇编分散的和未分析的丰富的自然和文献代理信息，并应用先进的统计重建方法，包括贝叶斯分层模型（BHM）。我们将利用IPCC-CMPI 5数据库中越来越多的全球古气候模拟数据，分析申请人已经使用ECHO-G和ECHAM 5-MPIOM模式进行的上千年模拟的集合。该集合提供了一套具有不同规定边界条件的模拟，因此适合于识别和理清过去单个强迫的影响。全球模拟将得到一个高分辨率区域模拟的补充，该模拟使用CLM模式，能够更好地反映全球外部强迫、大规模气候驱动因素（如厄尔尼诺/南方涛动、亚洲季风）之间的相互作用及其与区域特征（地形、陆海对比、土地利用）的相互作用。其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化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对景观的大规模改变，帮助限制中国区域气候预测（包括季风区）的不确定性。

项目成果

Cooling and societal change during the Late Antique Little Ice Age from 536 to around 660 AD

• DOI: 10.1038/ngeo2652
• 发表时间: 2016-03-01
• 期刊: NATURE GEOSCIENCE
• 影响因子: 18.3
• 作者: Buentgen, Ulf;Myglan, Vladimir S.;Kirdyanov, Alexander V.
• 通讯作者: Kirdyanov, Alexander V.

Ranking of tree-ring based temperature reconstructions of the past millennium

• DOI: 10.1016/j.quascirev.2016.05.009
• 发表时间: 2016-08-01
• 期刊: QUATERNARY SCIENCE REVIEWS
• 影响因子: 4
• 作者: Esper, Jan;Krusic, Paul J.;Buntgen, Ulf
• 通讯作者: Buntgen, Ulf

European summer temperatures since Roman times

• DOI: 10.1088/1748-9326/11/2/024001
• 发表时间: 2016-02-01
• 期刊: ENVIRONMENTAL RESEARCH LETTERS
• 影响因子: 6.7
• 作者: Luterbacher, J.;Werner, J. P.;Zerefos, C.
• 通讯作者: Zerefos, C.

Comparing proxy and model estimates of hydroclimate variability and change over the Common Era

比较公元元时期水文气候变率和变化的代理估计和模型估计

• DOI: 10.5194/cp-13-1851-2017
• 发表时间: 2017-12
• 期刊: Climate Past
• 作者: PAGES Hydro2k Consortium

Internal and external forcing of multidecadal Atlantic climate variability over the past 1,200 years

过去1200年大西洋数十年气候变化的内部和外部强迫

• DOI: 10.1038/ngeo2962
• 发表时间: 2017-05
• 期刊: Nature Geoscience
• 影响因子: 18.3
• 作者: Jianglin Wang;Bao Yang;Fredrik Charpentier Ljungqvist;Juerg Luterbacher;Timothy J. Osborn;Keith R. Briffa;Eduardo Zorita
• 通讯作者: Eduardo Zorita