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Considerations in the selection of global climate models for regional climate projections: the Arctic as a case study.

机译:在选择全球气候模型以进行区域气候预测时应考虑的因素:以北极为例。

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Climate projections at regional scales are in increased demand from management agencies and other stakeholders. While global atmosphere-ocean climate models provide credible quantitative estimates of future climate at continental scales and above, individual model performance varies for different regions, variables, and evaluation metrics - a less than satisfying situation. Using the high-latitude Northern Hemisphere as a focus, the authors assess strategies for providing regional projections based on global climate models. Starting with a set of model results obtained from an "ensemble of opportunity," the core of this procedure is to retain a subset of models through comparisons of model simulations with observations at both continental and regional scales. The exercise is more one of model culling than model selection. The continental-scale evaluation is a check on the large-scale climate physics of the models, and the regional-scale evaluation emphasizes variables of ecological or societal relevance. An additional consideration is given to the comprehensiveness of processes included in the models. In many but not all applications, different results are obtained from a reduced set of models compared to relying on the simple mean of all available models. For example, in the Arctic the top-performing models tend to be more sensitive to greenhouse forcing than the poorer-performing models. Because of the mostly unexplained inconsistencies in model performance under different selection criteria, simple and transparent evaluation methods are favored. The use of a single model is not recommended. For some applications, no model may be able to provide a suitable regional projection. The use of model evaluation strategies, as opposed to relying on simple averages of ensembles of opportunity, should be part of future synthesis activities such as the upcoming Fifth Assessment Report of the Intergovernmental Panel on Climate Change.Digital Object Identifier http://dx.doi.org/10.1175/2010JCLI3462.1
机译:管理机构和其他利益相关者对区域规模的气候预测有越来越高的需求。尽管全球大气-海洋气候模型可以提供可靠的定量评估,包括大陆地区及更高级别的未来气候,但各个模型的性能随区域,变量和评估指标的不同而变化,这并不令人满意。作者以北半球的高纬度为重点,评估了基于全球气候模型提供区域预测的策略。从从“机会集合”获得的一组模型结果开始,此过程的核心是通过将模型模拟与大陆和区域尺度的观测值进行比较来保留模型的子集。练习不是模型选择,而是模型选择的一种。大陆尺度的评估是对模式的大规模气候物理学的检验,而区域尺度的评估则强调了生态或社会相关性的变量。还额外考虑了模型中包含的过程的全面性。与依靠所有可用模型的简单均值相比,在许多但不是全部应用中,从减少的模型集中可以获得不同的结果。例如,在北极地区,表现最好的模型比表现较差的模型对温室强迫更敏感。由于在不同的选择标准下,模型性能方面的原因多数是无法解释的,因此倾向于使用简单透明的评估方法。不建议使用单个模型。对于某些应用程序,没有模型可能能够提供合适的区域投影。使用模型评估策略,而不是依赖简单的机会平均值平均值,应该成为未来综合活动的一部分,例如政府间气候变化专门委员会即将发布的《第五次评估报告》。数字对象标识符http:// dx。 doi.org/10.1175/2010JCLI3462.1

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