Toward seamless prediction: Calibration of climate change projections using seasonal forecasts
Toward seamless prediction: Calibration of climate change projections using seasonal forecasts
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DOI：
10.1175/bams-89-4-459
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发表时间：
2008-04-01
影响因子：
8
通讯作者：
Rodwell, M. J.
中科院分区：
文献类型：
--
作者：
Palmer, T. N.;Doblas-Reyes, F. J.;Rodwell, M. J.
可信的区域气候概率预测对于社会规划未来气候变化至关重要，然而，由于气候的非线性性质，有限的气候计算模型在完全准确地模拟区域气候变率的能力方面存在固有的缺陷。鉴于这些普遍的缺陷，我们如何确定具体的区域气候预测是否不可信？提出了一种校准方法，其基础在于无缝预测的新兴概念。具体而言，基于集合的气候变化概率的校准来自基于集合的预测概率在季节时间尺度上的统计可靠性分析。该方法是通过校准概率预测的多模式合奏中使用的第四次评估报告（AR4）的政府间气候变化专门委员会（IPCC），基于可靠性分析，从季节性预测欧洲多模式合奏系统的发展季节到年际预测（DEMETER）数据集。本文的重点是区域降水的气候变化预测，虽然方法更一般。
Trustworthy probabilistic projections of regional climate are essential for society to plan for future climate change, and yet, by the nonlinear nature of climate, finite computational models of climate are inherently deficient in their ability to simulate regional climatic variability with complete accuracy. How can we determine whether specific regional climate projections may be untrustworthy in the light of such generic deficiencies? A calibration method is proposed whose basis lies in the emerging notion of seamless prediction. Specifically, calibrations of ensemble-based climate change probabilities are derived from analyses of the statistical reliability of ensemble-based forecast probabilities on seasonal time scales. The method is demonstrated by calibrating probabilistic projections from the multimodel ensembles used in the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), based on reliability analyses from the seasonal forecast Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) dataset. The focus in this paper is on climate change projections of regional precipitation, though the method is more general.