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Ensemble experiments on numerical weather prediction error and uncertainty for a North Pacific forecast failure

机译:关于北太平洋天气预报失败的数值天气预报误差和不确定性的综合实验

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An intense maritime cyclone off the northwest coast of North America during 9-14 February 1999 was remarkable in the repeated inability of numerical weather prediction (NWP) models to forecast its evolution. Each day during that period, the operational and research models of the United States and Canada were initialized with new analysis fields. Each day, the new short-term NWP forecasts predicted the storm to strike the densely populated Lower Mainland (Vancouver) area of southwest British Columbia, Canada, during the next 24-48 h. NWP guidance prompted the local forecast office to issue storm warnings including one or more of the following for Vancouver: heavy snow, heavy rain, and strong winds. Satellite imagery clearly showed the storm off the coast, but the storm did not strike Vancouver until much later and in a decayed state. This synoptic case is studied with an aim to understand the source of the NWP error, and an ensemble of research model runs is made to address three possibilities for failure: 1) initial condition (IC) error, 2) model error for a particularly nonlinear or sensitive event, and 3) sympathetic data denial. To estimate the effect of IC uncertainty, a short-range ensemble system is developed and tested on a limited-area model for a sequence of successive 3-day reforecasts covering the 10-day period surrounding the storm. This IC ensemble shows some correlation between spread and skill and provides one estimate of IC uncertainty. To estimate the effect of model uncertainty, a physics-based ensemble is run for the same period. The effect of data denial is investigated by comparing forecasts made with the same model but from analyses created at different operational centers. Results suggest that if the runs initialized at 0000 UTC 10 February 1999 were used for guidance, model uncertainty was likely responsible for the forecast failure. It had larger-than-average model error but lower-than-average IC error. Subsequent forecast errors were likely dominated by IC uncertainty. An attempt at assessing sympathetic data denial is inconclusive. [References: 19]
机译:1999年2月9日至14日,北美洲西北海岸发生了强烈的海上飓风,这是由于数值天气预报(NWP)模型反复无法预测其演变而引起的。在此期间的每一天,都会使用新的分析字段初始化美国和加拿大的运营和研究模型。每天,新的NWP短期预报都预测,接下来的24-48小时内,风暴将袭击加拿大不列颠哥伦比亚省西南部人口稠密的低陆平原(温哥华)地区。 NWP的指导促使当地预报办公室发布暴风警告,其中包括针对温哥华的以下一项或多项警告:大雪,大雨和强风。卫星图像清楚地显示了海岸附近的暴风雨,但是暴风雨直到很久以后才进入温哥华,并且处于衰退状态。为了了解NWP误差的根源,对这种天气情况进行了研究,并进行了研究模型的整合以解决三种可能的失效:1)初始条件(IC)误差,2)特定非线性的模型误差或敏感事件,以及3)同情数据被拒绝。为了估计IC不确定性的影响,开发了一个短距离合奏系统,并在有限区域模型上进行了测试,以进行连续三天的连续预报,涵盖风暴前后10天的时间。这种IC集成显示了传播和技能之间的某种关联,并提供了IC不确定性的一种估计。为了估计模型不确定性的影响,在同一时期运行了基于物理的集成。通过比较使用相同模型但来自不同运营中心创建的分析的预测来研究数据拒绝的影响。结果表明,如果使用1999年2月10日0000 UTC初始化的运行作为指导,则模型不确定性很可能是导致预测失败的原因。它的模型误差大于平均水平,但IC误差小于平均水平。随后的预测误差很可能由IC不确定性所主导。评估同情数据否认的尝试尚无定论。 [参考:19]

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