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Extreme events in the past and future - A comparative assessment for the Hai He river and the Poyang lake basins

过去和未来的极端事件——海河与鄱阳湖流域的比较评估

基本信息

批准号：
162142802
负责人：
Dr. Christian Ohlwein
金额：
--
依托单位：
Meteorologisches Institut (aufgelöst)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2010
资助国家：
德国
起止时间：
2009-12-31 至 2014-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/162142802?language=en
关键词：
Extreme events past future comparative

项目摘要

The impact of future climate change on land-use and water resource management is strongly dependent on the related changes in weather extremes. The future can only be assessed by the use of global climate models, which currently lack the necessary spatial resolution to represent such events. Moreover, global climate models are not able to incorporate all processes leading to extremes because of their low resolution. Thus downscaling of such runs is necessary, and only dynamical downscaling with high-resolution regional models is able to catch the necessary non-linear processes and process chains leading to extremes. The goal of this joint proposal is to provide estimates including their uncertainties of the behaviour of extreme weather events impacting land-use and water management for the 21st century for two climatically very different catchments, namely the Hai He river and the Poyang lake basins. To this goal we will first analyse the past of extreme events in both regions on the basis of observations and reanalysis data sets using state of the art extreme value statistics. Dynamical downscaling of global climate runs will be performed in order to evaluate the future of extreme events in the catchments. This necessitates first an evaluation of simulations of the current climate and its extremes by comparison with observations on a statistical basis. This will enable us to use the most appropriate regional climate model and to select the parametrisation setup most suitable for both regions, which might be different. While the Chinese partners will provide the observation data sets and perform the dynamical downscaling of global climate runs, the German partners will install the dynamical downscaling procedure at the Chinese partner institute, and generate the statistics of extremes both from observations and the simulations. The evaluation towards trends and uncertainties will be performed in close cooperation.

未来气候变化对土地利用和水资源管理的影响在很大程度上取决于极端天气的相关变化。未来只能通过使用全球气候模型来评估，目前该模型缺乏必要的空间分辨率来表示此类事件。此外，全球气候模型由于分辨率低而无法纳入导致极端事件的所有过程。因此，有必要对此类运行进行缩小尺度，并且只有使用高分辨率区域模型进行动态缩小尺度才能捕获导致极端情况的必要非线性过程和过程链。该联合提案的目标是提供估计，包括影响 21 世纪两个气候截然不同的流域（即海河和鄱阳湖流域）土地利用和水资源管理的极端天气事件行为的不确定性。为了实现这一目标，我们将首先根据观察和使用最先进的极值统计数据重新分析数据集来分析这两个地区过去发生的极端事件。将进行全球气候运行的动态降尺度，以评估流域极端事件的未来。这就需要首先通过与统计基础上的观测结果进行比较来评估当前气候及其极端情况的模拟。这将使我们能够使用最合适的区域气候模型，并选择最适合两个区域的参数化设置，这两个区域可能有所不同。中国合作伙伴将提供观测数据集并执行全球气候运行的动态降尺度，而德国合作伙伴将在中国合作伙伴研究所安装动态降尺度程序，并根据观测和模拟生成极端统计数据。对趋势和不确定性的评估将在密切合作下进行。