Probabilistic Precipitation Forecast Skill as a Function of Ensemble Size and Spatial Scale in a Convection-Allowing Ensemble
Probabilistic Precipitation Forecast Skill as a Function of Ensemble Size and Spatial Scale in a Convection-Allowing Ensemble
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DOI：
10.1175/2010mwr3624.1
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发表时间：
2011-05
影响因子：
3.2
通讯作者：
Adam J. Clark;J. Kain;D. Stensrud;Ming Xue;F. Kong;M. Coniglio;K. Thomas;Yunheng Wang;Keith Brewster;Jidong Gao;Xuguang Wang;S. Weiss;Jun Du
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文献类型：
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作者：
Adam J. Clark;J. Kain;D. Stensrud;Ming Xue;F. Kong;M. Coniglio;K. Thomas;Yunheng Wang;Keith Brewster;Jidong Gao;Xuguang Wang;S. Weiss;Jun Du
使用相对工作特征曲线（ROC区域）下，使用面积评估了2009年春季分析和预测暴风雨中心运行的风暴尺度合奏预测系统（ROC面积），从风暴规模的整体预测系统（ROC区域）评估了概率定量降水预测（PQPF）。 ROC面积测量了区分能力，对整体尺寸N的尺寸从1到17个成员进行了检查，并且空间尺度为4至200 km。预计，随着n的增加，技能降低的增量增长。将每个n的ROC区域与整个17人组成的ROC区域进行比较的显着性测试表明，随着预测提前时间的增加和空间规模的减少，需要更多成员才能达到统计上无法区分的PQPF技能。这些结果似乎反映了未来大气状态的预测概率分布函数（PDF）的扩大，与空间尺度降低和预测提前时间增加有关。他们还说明，有效分配计算资源用于对流的合奏需要仔细考虑空间尺度和所需的预测长度。
Probabilistic quantitative precipitation forecasts (PQPFs) from the storm-scale ensemble forecast system run by the Center for Analysis and Prediction of Storms during the spring of 2009 are evaluated using area under the relative operating characteristic curve (ROC area). ROC area, which measures discriminating ability, is examined for ensemble size n from 1 to 17 members and for spatial scales ranging from 4 to 200 km. Expectedly, incremental gains in skill decrease with increasing n. Significance tests comparing ROC areas for each n to those of the full 17-member ensemble revealed that more members are required to reach statistically indistinguishable PQPF skill relative to the full ensemble as forecast lead time increases and spatial scale decreases. These results appear to reflect the broadening of the forecast probability distribution function (PDF) of future atmospheric states associated with decreasing spatial scale and increasing forecast lead time. They also illustrate that efficient allocation of computing resources for convection-allowing ensembles requires careful consideration of spatial scale and forecast length desired.