On the reliability of seasonal climate forecasts.
On the reliability of seasonal climate forecasts.
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DOI：
10.1098/rsif.2013.1162
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发表时间：
2014-07-06
期刊：
影响因子：
--
通讯作者：
Palmer TN
中科院分区：
文献类型：
--
作者：
Weisheimer A;Palmer TN
季节性气候预测越来越多地应用于一系列应用领域。最近的一份英国政府报告问道：季节性预测在 1-5 级（其中 5 级非常好）的范围内有多好，以及我们预计 30 年后它们会有多好？季节性预测是根据气候数值模型的集成进行的。我们认为，首先应该根据这些基于集合的预测的概率可靠性来评估“良好性”；可靠的输入对于任何基于预测的决策都至关重要。我们建议，“5”应该保留给不仅总体可靠，而且特别是小集合展差是低集合预报误差的可靠指标的系统。我们研究欧洲中期天气预报中心当前业务季节性预报系统的区域温度和降水预报的可靠性，该中心被普遍认为是世界领先的季节性气候预报业务机构之一。根据地区和变量的不同，我们发现了各种各样的“良好”排名（北欧夏季降雨量预测表现非常差）。最后，我们讨论了 30 年后所有地区和变量达到“5”的前景。
Seasonal climate forecasts are being used increasingly across a range of application sectors. A recent UK governmental report asked: how good are seasonal forecasts on a scale of 1–5 (where 5 is very good), and how good can we expect them to be in 30 years time? Seasonal forecasts are made from ensembles of integrations of numerical models of climate. We argue that ‘goodness’ should be assessed first and foremost in terms of the probabilistic reliability of these ensemble-based forecasts; reliable inputs are essential for any forecast-based decision-making. We propose that a ‘5’ should be reserved for systems that are not only reliable overall, but where, in particular, small ensemble spread is a reliable indicator of low ensemble forecast error. We study the reliability of regional temperature and precipitation forecasts of the current operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts, universally regarded as one of the world-leading operational institutes producing seasonal climate forecasts. A wide range of ‘goodness’ rankings, depending on region and variable (with summer forecasts of rainfall over Northern Europe performing exceptionally poorly) is found. Finally, we discuss the prospects of reaching ‘5’ across all regions and variables in 30 years time.
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影响因子：
5.2
作者：
Dawson, A.;Palmer, T. N.;Corti, S.
通讯作者：
Corti, S.
影响因子：
8
作者：
Palmer, T. N.;Doblas-Reyes, F. J.;Rodwell, M. J.
通讯作者：
Rodwell, M. J.
影响因子：
8.9
作者：
Buizza, R;Miller, M;Palmer, TN
通讯作者：
Palmer, TN
影响因子：
3
作者：
Dutra, E.;Diamantakis, M.;Pappenberger, F.
通讯作者：
Pappenberger, F.
影响因子：
4.9
作者：
Jung, T.;Miller, M. J.;Hodges, K. I.
通讯作者：
Hodges, K. I.