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A Preliminary Examination of WRF Ensemble Prediction of Convective Mode Evolution

机译:对流模式演化的WRF集合预测初探

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Accurately simulating convective mode evolution can assist forecasters in the severe weather warning process. A few prior studies have examined the skill of simulating convective modes using single, deterministic forecasts. The present study extends the earlier evaluations to a small, four-member ensemble, with each member incorporating varying initial and lateral boundary conditions, microphysics schemes, and planetary boundary layer schemes. Simulated convective modes from thirty-two 12-h simulations were categorized into nine classifications using a classification scheme developed from previous studies. Multiple methods were used to derive forecasts of these convective classifications, creating an hourly deterministic ensemble mode forecast and probabilistic forecasts for 1-, 6-, and 12-h periods. Forecasts were compared with observed radar reflectivity for verification. In general, hourly deterministic ensemble mode forecasts showed improvement over individual member forecasts. The small ensemble produced more skillful individual cellular convective mode forecasts than individual linear mode forecasts, with the least skill present for bow echoes and squall lines with trailing stratiform precipitation. In contrast, the ensemble was more skillful at forecasting the broader linear convective group than the broader cellular convective group. For a limited number of these cases, a test was performed using a larger 10-member ensemble run by the National Center for Atmospheric Research (NCAR) to examine what impacts the small ensemble size might have. The results did not differ substantially, suggesting the findings from the small ensemble can be generalized. Probabilistic forecasts for longer time periods were more skillful than shorter-term probabilistic forecasts.
机译:准确模拟对流模式演化可以帮助预测员在恶劣的天气警告过程中。几个先前的研究已经检查了使用单个确定性预测模拟对流模式的技能。本研究将前面的评估延伸到小的四个成员集合,每个构件包含不同的初始和横向边界条件,微专体方案和行星边界层方案。使用从先前研究开发的分类方案分类为来自32个12-H模拟的模拟对流模式。多种方法用于导出这些对流分类的预测,创建每小时的确定性集合模式预测和1-,6-和12-H周期的概率预测。将预测与观察到的雷达反射率进行了比较。一般来说,每小时确定的集合模式预测显示了对个别成员预测的改进。小型集团生产比单独的线性模式预测更熟练的单个蜂窝对流模式预测,具有弓形回波的最低技能和具有尾随层状沉淀的痕迹线。相比之下,该集合在预测比较大细胞对流组比较广泛的线性对流组方面更加熟练。对于有限数量的这些情况,使用国家大气研究中心(NCAR)的较大的10构件合奏进行测试,以检查小型集合规模可能的影响。结果没有大幅差异,表明可以广泛化的小集合的发现。对于较短时间段的概率预测比较短的概率预测更熟练。

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