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Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

机译:西欧平均降水和强降水的地方尺度变化,气候变化或内部变率?

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摘要

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—‘noise’, intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM–GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in highresolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.
机译:例如,气象局提供的高分辨率气候信息。区域气候模型(RCM)对于探索全球变暖下不断变化的天气以及评估气候变化对当地的影响非常有价值。通常,人们对高分辨率下的模拟过程的代表性更具信心,但气候系统的内部可变性(“噪声”是大气和海洋过程的混沌性质所固有的)在较小的空间尺度上也较大,从而限制了可预测性气候信号。为了量化内部变率并可靠地估算气候信号,使用单个模型进行的大型气候模拟初始条件集合提供了必要的信息。我们以0.11°的分辨率分析了西欧和阿尔卑斯山上由16个成员组成的初始条件集合的区域缩减,这类似于最高分辨率的EURO-CORDEX模拟。我们检查了由于内部变异而导致的平均气候和极端每日降水相对于噪声的强迫气候响应(信号)的强度,并在强迫响应中发现了健壮的小规模地理特征,表明了事件发生概率变化的区域差异。但是,即使对于全球变暖的高水平,单个集体成员也只能提供有限的有关强迫气候响应的信息。尽管结果基于单个RCM–GCM链,但我们认为它们具有普遍价值,可提供对无法还原的高分辨率气候信息不确定性所占的比例的洞察力,并有助于正确解释中国的精细尺度信息。由于内部可变性,多模型集成在强制响应和噪声方面。

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