Towards a typology for constrained climate model forecasts
Towards a typology for constrained climate model forecasts
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DOI：
10.1007/s10584-014-1292-z
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发表时间：
2015-09
期刊：
影响因子：
4.8
通讯作者：
Ana Lopez;Ana Lopez;E. Suckling;F. Otto;A. Lorenz;D. Rowlands;M. Allen
中科院分区：
文献类型：
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作者：
Ana Lopez;Ana Lopez;E. Suckling;F. Otto;A. Lorenz;D. Rowlands;M. Allen
近年来，已经开发了几种方法来组合和解释气候模型集合，目的是量化气候预测中的不确定性。通过将用于对单个集合成员加权的各种度量选择与对集合进行采样的不同方法相结合，生成了受约束的气候模型预报。即使基于相同的模型输出，得到的预测往往也有很大的不同。因此，气候模式预报分类系统可以发挥两种作用：为预报制作者提供一种对其预报进行自我分类的方法；以及提供关于预报产生的方法假设及其在预报用于影响研究时的不确定性的信息。在这篇综述中，我们提出了一种可能的基于度量和抽样策略选择的分类系统。我们说明了一些可能的选择在温度和降水变化的大尺度预测的不确定性量化中的影响，并简要讨论了气候变化背景下气候预测不确定性量化和决策方法之间的可能联系。
In recent years several methodologies have been developed to combine and interpret ensembles of climate models with the aim of quantifying uncertainties in climate projections. Constrained climate model forecasts have been generated by combining various choices of metrics used to weight individual ensemble members, with diverse approaches to sampling the ensemble. The forecasts obtained are often significantly different, even when based on the same model output. Therefore, a climate model forecast classification system can serve two roles: to provide a way for forecast producers to self-classify their forecasts; and to provide information on the methodological assumptions underlying the forecast generation and its uncertainty when forecasts are used for impacts studies. In this review we propose a possible classification system based on choices of metrics and sampling strategies. We illustrate the impact of some of the possible choices in the uncertainty quantification of large scale projections of temperature and precipitation changes, and briefly discuss possible connections between climate forecast uncertainty quantification and decision making approaches in the climate change context.