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20th- and 21th-century climate changes in western China simulated with a hierarchy of global and regional climate models, including improved scenarios of human activity and reliable observational data for validation

使用一系列全球和区域气候模型模拟中国西部 20 世纪和 21 世纪的气候变化，包括改进的人类活动情景和用于验证的可靠观测数据

基本信息

批准号：
100434939
负责人：
Professor Dr. Heiko Paeth
金额：
--
依托单位：
Nanjing University
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 2015-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/100434939?language=en
关键词：
20th 21th century climate changes

项目摘要

AKSU TARIM-CLIM is funded by the German Research Foundation (DFG) since October 2010. Since then important improvements in the regional assessment of climate change in western China and Central Asia have been achieved. Dynamical downscaling with the regional climate model REMO at different resolutions (0.5° and 0.16°) have been performed, revealing improvements in the model bias compared with the driving global climate model and re-analyses. This achievement enabled a rather detailed picture of future climate change in the mountainous region of Asia. Alternatively, a statistical-dynamical downscaling approach has been developed and compared with REMO results. The latter method first analyses the large-scale weather types affecting the region. For selected and representative episodes for each weather type, dynamical downscaling with the regional climate model CCLM at a resolution of 7 km (0.0625°) is performed. Finally, this information is recombined using the frequencies of weather types from global climate model simulations to obtain high resolution climate projections. In general, the added value of dynamical and statistical downscaling of climate projections in western China could be identified and the simulated climate data will now be applied to impact models within the AKSU TARIM project bundle, assessing changes in glacier mass balance, glacier runoff, permafrost and snow cover in the Tien Shan mountain range. Yet, some model deficiencies still exist which require further investigations in order to improve the interface between climate, glaciological and hydrological models. With this aim, we apply for an additional project year, following the current two-year project phase of AKSU TARIM-CLIM. During this project year we plan to (1) develop and apply a statistical postprocessing of the model data in order to remove systematic biases in REMO and CCLM and to adjust grid box data to local climate information required at level of the individual glaciers. (2) One of the most obvious larger-scale deficiencies in REMO consists of a remarkable summer-time warm bias over the Central Asian plain. We assume that this bias is due to the missing land-use process of irrigation and, hence, intend to carry out sensitivity studies with REMO, systematically modifying land-cover towards irrigation. This would be of particular value for the entire hydrological cycle over Central Asia, since evapo-transpiration from irrigated land surfaces represents a crucial source of water vapor and, thus, also snow accumulation in the region. (3) The statisticaldynamical downscaling has been found to be a quick and valuable option in regional climate change assessment. A new approach will be developed which applies to a spatial scale of 2.8 km, closer to the spatial scale of glaciers, to daily values and to additional meteorological variables, in particular temperature. Additionally, the statistical-dynamical downscaling will be extended by using changing weather type frequencies from different GCMs, in order to gain better estimation of the uncertainties associated with the climate projections for the target region.

阿克苏塔里木-克利姆项目自2010年10月起由德国研究基金会(DFG)资助。自那时以来，在对中国西部和中亚地区气候变化的区域评估方面取得了重大改进。对不同分辨率(0.5°和0.16°)的区域气候模式REMO进行了动力降尺度试验，结果表明，与驱动全球气候模式和再分析相比，模式偏差有所改善。这一成就使得人们能够对亚洲山区未来的气候变化有一个相当详细的了解。或者，发展了一种统计-动力降尺度方法，并与REMO结果进行了比较。后一种方法首先分析影响该地区的大尺度天气类型。对于每种天气类型的精选和代表性事件，使用区域气候模式CCLm在7公里(0.0625°)的分辨率下进行了动力降尺度。最后，使用来自全球气候模型模拟的天气类型的频率对这些信息进行重新组合，以获得高分辨率的气候预测。总体而言，可以确定中国西部气候预测的动力和统计下调的附加值，模拟的气候数据现在将应用于阿克苏-塔里木项目束中的影响模型，评估天山山脉冰川物质平衡、冰川径流、永冻土和积雪的变化。然而，模型仍然存在一些不足之处，需要进一步研究，以改善气候、冰川和水文模型之间的接口。为了实现这一目标，我们在阿克苏塔里木-克利姆项目目前为期两年的阶段之后，申请再申请一个项目年。在本项目年期间，我们计划(1)开发和应用模型数据的统计后处理，以消除REMO和CCLM中的系统偏差，并根据个别冰川所需的当地气候信息调整网格箱数据。(2)REMO最明显的大尺度不足之一是夏季在中亚平原存在显著的暖偏向。我们认为，这种偏差是由于缺少灌溉的土地利用过程，因此，我们打算与REMO进行敏感性研究，系统地修改土地覆盖以适应灌溉。这对于整个中亚的水文循环将具有特别的价值，因为灌溉地表的蒸散是水蒸气的一个重要来源，因此也是该地区积雪的一个重要来源。(3)统计动力降尺度在区域气候变化评估中是一种快速而有价值的选择。将开发一种新的方法，适用于2.8公里的空间尺度，更接近冰川的空间尺度，更接近每日数值和其他气象变量，特别是温度。此外，为了更好地估计与目标区域气候预测有关的不确定性，将通过使用不同GCM变化的天气类型频率来扩大统计-动力降尺度。