HRRR-AK: A High-resolution, Rapidly Cycled Forecast Model For Alaska

Abstract

The 3-km convection-allowing High-Resolution Rapid Refresh (HRRR), Alaska version (HRRR-AK) is a rapidly updating weather forecast model that uses a specially configured version of the Advanced Research WRF (ARW) model and assimilates many novel and conventional observations using Gridpoint Statistical Interpolation (GSI). HRRR-AK incorporates recent enhancements of the HRRR model physics suite, including improved land-surface and boundary layer prediction using the updated Mellor-Yamada-Nakanishi-Niino (MYNN) parameterization scheme, aerosol-aware Thompson microphysics and an upgraded Rapid Update Cycle (RUC) land-surface model. HRRR-AK is cycled every 3 h with a forecast length of 36 h, following a 1-h pre-forecast, data assimilation cycle. Initial and boundary conditions come from an experimental version of the 13-km Rapid Refresh (RAP) model, which was recently expanded in geographic area. Future plans include assimilation of radar reflectivity from the Multi-Radar, Multi-Sensor (MRMS) system to better initialize ongoing precipitation structures, and use of additional satellite- and surface-based datasets to improve the model initial state. This presentation will highlight the potential for HRRR-AK to improve weather prediction over the vast and varied terrain of Alaska, including processes associated with complex terrain (e.g., gap flows, downslope windstorms), the arctic environment (e.g., nocturnal and persistent temperature inversions), and coastal/offshore areas (e.g., sea ice). In addition to objective verification statistics, several case study examples will be presented to showcase forecasts for particularly challenging regions and weather phenomena.