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WRF Forecasts of Great Plains Nocturnal Low-Level Jet-Driven MCSs. Part I: Correlation between Low-Level Jet Forecast Accuracy and MCS Precipitation Forecast Skill

机译:大平原夜间低空喷气驱动MCS的WRF预报。第一部分:低空急流预报精度与MCS降水预报技能之间的相关性

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The Great Plains low-level jet (LLJ) fosters an environment that supports nocturnal mesoscale convective systems (MCSs) across the central United States during the summer months. The current study examines if LLJ forecast accuracy correlates with MCS precipitation forecast skill in 4-km WRF runs. LLJs were classified based on their synoptic background as either strongly forced, cyclonic flow (type C) or weakly forced, anticyclonic flow inertial oscillation driven (type A). Large-scale variables associated with the LLJ were examined. For all LLJs inclusive and the subset of type C LLJs alone, the forecast accuracy of the LLJ total wind direction significantly correlated with MCS precipitation forecast skill. For type C LLJ cases, where predictive skill for MCSs was higher overall, the LLJ ageostrophic wind direction forecast accuracy significantly correlated with MCS precipitation forecast skill during the LLJ and MCS developmental stages, with potential temperature and moisture forecast accuracy correlating well with the forecast skill of mature MCSs. Statistically significant correlations were mainly absent between MCS precipitation forecast skill and LLJ forecast accuracy for type A cases. It is thus suggested that either non-LLJ factors like most unstable convective available potential energy (MUCAPE) or most unstable convective inhibition (MUCIN) fields within close proximity of MCSs, or factors on smaller scales than analyzed (such as gravity waves or bores), may have the greatest potential influence on MCS precipitation forecast skill in LLJ-induced MCS cases in an ambient weakly forced synoptic regime.
机译:大平原低空喷气式飞机(LLJ)营造了一个在夏季支持美国中部夜间中尺度对流系统(MCS)的环境。当前的研究检查了LLJ预报准确性是否与4 km WRF跑步中的MCS降水预报技巧相关。 LLJ根据天气背景分类为强力气旋流(C型)或弱力反气旋流惯性振荡驱动(A型)。检查了与LLJ相关的大规模变量。对于所有LLJ(包括首尾)和C型LLJ的子集,LLJ总风向的预报准确性与MCS降水预报技能显着相关。对于C型LLJ案例,其MCS的总体预测能力较高,在LLJ和MCS发育阶段,LLJ的年龄营养化风向预测精度与MCS降水预测技能显着相关,而潜在的温度和湿度预测精度与预测技能相关性很好成熟的MCS。对于A型病例,MCS降水预测技能与LLJ预测准确性之间主要不存在统计学上的显着相关性。因此建议,非LLJ因素如MCS附近最不稳定的对流可用势能(MUCAPE)或最不稳定的对流抑制(MUCIN)场,或比分析的尺度小的因素(例如重力波或井筒) ,在环境弱强迫天气条件下,LLJ诱发的MCS病例中,对MCS降水预报技能可能具有最大的潜在影响。

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