Ensemble versus Deterministic Performance at the Kilometer Scale
Ensemble versus Deterministic Performance at the Kilometer Scale
复制标题
公里级的集成与确定性性能
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
G. Csima
中科院分区：
文献类型：
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作者：
M. Mittermaier;G. Csima
AbstractWhat是一个近对流分辨集合的好处超过一个近对流分辨确定性预报？在本文中，集合和确定性数值天气预报（NWP）系统可以比较的方式是使用概率验证框架。英国气象局统一模型（UM）12个成员的2.2公里英国气象局全球和区域环绕预报系统（MOGREPS-UK）集合和1.5公里英国气象局的三年原始预报。变分辨率（UKV）的确定性配置进行了比较，利用一系列的预测邻域大小集中在地面天气观测站点的位置。六个表面变量进行了评估：温度，10米风速，能见度，云底高度，总云量和每小时降水量。确定性预报受益于邻域的应用，虽然集合预报技巧也可以提高。这证实，虽然邻里可以提高技能，通过采样莫…
AbstractWhat is the benefit of a near-convection-resolving ensemble over a near-convection-resolving deterministic forecast? In this paper, a way in which ensemble and deterministic numerical weather prediction (NWP) systems can be compared is demonstrated using a probabilistic verification framework. Three years’ worth of raw forecasts from the Met Office Unified Model (UM) 12-member 2.2-km Met Office Global and Regional Ensemble Prediction System (MOGREPS-UK) ensemble and 1.5-km Met Office U.K. variable resolution (UKV) deterministic configuration were compared, utilizing a range of forecast neighborhood sizes centered on surface synoptic observing site locations. Six surface variables were evaluated: temperature, 10-m wind speed, visibility, cloud-base height, total cloud amount, and hourly precipitation. Deterministic forecasts benefit more from the application of neighborhoods, though ensemble forecast skill can also be improved. This confirms that while neighborhoods can enhance skill by sampling mo...