Model Configuration versus Driving Model: Influences on Next-Day Regional Convection-Allowing Model Forecasts during a Real-Time Experiment Weather and Forecasting

As part of NOAA’s Hazardous Weather Testbed Spring Forecasting Experiment (SFE) in 2020, an international collaboration yielded a set of real-time convection-allowing model (CAM) forecasts over the contiguous United States in which the model configurations and initial/boundary conditions were varied in a controlled manner. Three model configurations were employed, among which the Finite Volume Cubed-Sphere (FV3), Unified Model (UM), and Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model dynamical cores were represented. Two runs were produced for each configuration: one driven by NOAA’s Global Forecast System for initial and boundary conditions, and the other driven by the Met Office’s operational global UM. For 32 cases during SFE2020, these runs were initialized at 0000 UTC and integrated for 36 h. Objective verification of model fields relevant to convective forecasting illuminates differences in the influence of configuration versus driving model pertinent to the ongoing problem of optimizing spread and skill in CAM ensembles. The UM and WRF configurations tend to outperform FV3 for forecasts of precipitation, thermodynamics, and simulated radar reflectivity; using a driving model with the native CAM core also tends to produce better skill in aggregate. Reflectivity and thermodynamic forecasts were found to cluster more by configuration than by driving model at lead times greater than 18 h. The two UM configuration experiments had notably similar solutions that, despite competitive aggregate skill, had large errors in the diurnal convective cycle. Grant no. NA21OAR4320204

2020年，作为美国国家海洋和大气管理局（NOAA）危险天气试验台春季预报试验（SFE）的组成部分，一项国际合作项目生成了一套覆盖美国本土的实时对流允许模式（CAM）预报数据集，该数据集以受控方式调整模式配置与初始/边界条件。本次试验采用三种模式配置，分别对应有限体积立方球面（Finite Volume Cubed-Sphere, FV3）动力核心、统一模式（Unified Model, UM）动力核心，以及天气研究与预报模式先进研究版（WRF-ARW）动力核心。每种配置均开展两组预报试验：一组以NOAA全球预报系统作为初始与边界条件驱动，另一组以英国气象局业务化全球统一模式作为驱动源。针对SFE2020中的32个预报个例，所有试验均于协调世界时0000时启动初始化，并连续积分36小时。针对对流预报相关的模式场开展客观检验，可揭示模式配置与驱动模式对对流允许模式集合的扩散度与预报技巧优化这一核心问题的影响差异。研究结果表明：在降水、热力学场以及模拟雷达反射率的预报中，UM与WRF配置的整体表现优于FV3配置；采用与对流允许模式动力核心同源的驱动模式，整体预报技巧也相对更优。当预报时效超过18小时后，反射率与热力学场的预报结果更多依据模式配置聚类，而非驱动模式。两组UM配置试验的预报结果整体相似度极高，尽管其整体预报技巧颇具竞争力，但在日周期对流循环的预报中存在显著误差。本研究受资助编号NA21OAR4320204。