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Comparison of Metrics for Probabilistic Climate Change Projections of Mediterranean Precipitation (COMEPRO)

地中海降水概率气候变化预测指标比较 (COMEPRO)

基本信息

批准号：
256844028
负责人：
Professor Dr. Jucundus Jacobeit
金额：
--
依托单位：
Arbeitsbereich Physische Geographie
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2014
资助国家：
德国
起止时间：
2013-12-31 至 2018-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/256844028?language=en
关键词：
Comparison Metrics Probabilistic Climate Change

项目摘要

Climate mitigation and adaptation strategies require reliable estimates of future climate change for which coupled atmosphere-ocean general circulation models (AOGCMs) still represent the state-of-the-art tool. However, climate projections from different climate models vary considerably in some regions of the Earth and in terms of some climatic variables like for instance precipitation, implying important uncertainties on the side of climate impact research. The differences between climate model simulations arise from the unknown initial conditions, different resolutions and forcing agents, different physical parameterizations and the assumed emission scenarios. As it cannot be anticipated which model projection is most realistic, the most comprehensive climate change information is composed of all available climate change simulations. By transforming this multi-model information into a probability density function (PDF) the probability above or below a given level of climate change can directly be assessed. Such probabilistic predictions are indeed relevant for planning processes because they provide a multi-model mean estimate of climate change which represents expectation, and a quantitative measure of model uncertainty. The proposed project aims at evaluating such probabilistic predictions of future precipitation changes from the CMIP3, CMIP5, EMSEMBLES and CORDEX multi-model ensembles and from statistical downscaling approaches. The focus is on the Mediterranean region as a so-called hot spot of climate change and on the comparison of PDFs between seasonal means and extremes. The major novel aspect is to investigate to what extent the width of the multi-model PDFs can be reduced by appropriate weighting factors of the participating climate change projections. This implies that some amount of model uncertainty has to be accepted because it is an intrinsic problem arising from the unknown initial conditions or from uncertain empirical parameters. The weighting factors are assessed by various comparative metrics like Bayesian statistics, regression analysis, spatio-temporal filtering, optimal fingerprinting, and model performance concerning the representation of dynamical modes, circulation types and important predictors for statistical downscaling techniques. In addition, the PDFs over the multi-model ensembles are also assessed for various phenomena in the process chain towards the generation of precipitation, including radiation, evaporation, advection and cloudiness. This will help to identify the level at which the dispersion between different climate model projections begins.

气候减缓和适应战略需要对未来气候变化进行可靠的估计，而大气-海洋环流耦合模式仍然是最先进的工具。然而，不同气候模式的气候预测在地球的某些地区和某些气候变量（如降水量）方面差异很大，这意味着气候影响研究方面存在重大的不确定性。气候模式模拟之间的差异源于未知的初始条件、不同的分辨率和强迫因子、不同的物理参数化和假设的排放情景。由于无法预测哪种模式预测最现实，最全面的气候变化信息由所有可用的气候变化模拟组成。通过将这种多模式信息转换为概率密度函数（PDF），可以直接评估高于或低于给定气候变化水平的概率。这种概率预测确实与规划过程有关，因为它们提供了代表预期的气候变化的多模式平均估计，以及对模式不确定性的定量测量。拟议项目的目的是评价CMIP 3、CMIP 5、EMSEMBLES和CORDEX多模式集合以及统计降尺度方法对未来降水变化的概率预测。重点是地中海地区作为所谓的气候变化热点，以及季节平均值和极端值之间的PDF比较。主要的新的方面是调查在何种程度上的宽度的多模式PDF可以减少参与气候变化预测的适当加权因子。这意味着必须接受一定量的模型不确定性，因为它是由未知的初始条件或不确定的经验参数引起的内在问题。权重因子通过各种比较指标进行评估，如贝叶斯统计，回归分析，时空滤波，最佳指纹识别，以及关于动态模式，循环类型和统计降尺度技术的重要预测因子的表示的模型性能。此外，还评估了多模式集合上的PDF，用于生成降水的过程链中的各种现象，包括辐射、蒸发、平流和云量。这将有助于确定不同气候模式预测之间开始出现差异的程度。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A comparison of metrics for assessing state-of-the-art climate models and implications for probabilistic projections of climate change

DOI：
10.1007/s00382-017-3737-3
发表时间：
2018-03
期刊：
Climate Dynamics
影响因子：
4.6
作者：
Christoph Ring;F. Pollinger;Irena Kaspar‐Ott;E. Hertig;J. Jacobeit;H. Paeth
通讯作者：
Christoph Ring;F. Pollinger;Irena Kaspar‐Ott;E. Hertig;J. Jacobeit;H. Paeth

Weighted multi-model ensemble projection of extreme precipitation in the Mediterranean region using statistical downscaling

使用统计降尺度对地中海地区极端降水进行加权多模式集合预测