HNMMB: Weaving the Proven Successes of HWRF into the NEMS Framework

The complex interactions between tropical cyclones and land surfaces are difficult to model. Current operational high-resolution mesoscale models for hurricanes, such as the HWRF system, tend to focus on the wind intensity predictions rather than landfall related issues, such as the fresh water flooding and storm surge which are responsible for more than 80% of all deaths due to tropical cyclones. The topic of this talk is the development of a multiscale hurricane prediction system operating at a resolution of 3 km or finer to provide improved predictions of land-falling tropical cyclones.

Supported by NOAA's High Impact Weather Prediction Project (HIWPP)-- funded by Hurricane Sandy Disaster Relief Supplemental Appropriations, the Atlantic Oceanographic and Meteorological Laboratory's Hurricane Research Division (AOML/HRD); the National Centers for Environmental Prediction's Environmental Modeling Center (NCEP/EMC); and the Developmental Testbed Center (DTC) have collaborated to create a nested configuration of the Nonhydrostatic Multiscale Model on B-grid within the framework of NOAA's Environmental Modeling System (NMMB/NEMS).

Hurricane-specific modeling components from the HWRF system (grid-nesting, cloud-resolving physics, and vortex initialization) have been transitioned to NMMB/NEMS. The nesting scheme is designed to operate at 3 km or finer resolution, desirable for resolving physical processes within the inner core of the cyclone, while the ‘basin-scale' outer domain captures the storm's interactions with the large-scale environment. This multiscale approach is critical, not only for improving track and intensity predictions, but also for improving predictions of rainfall and storm size, factors which are largely responsible for flooding and storm surge.

Results from select storms of the 2015 hurricane season will be presented to demonstrate the feasibility of the model to be transitioned to operational status. The talk will especially emphasize on advantages and challenges of this system relative to existing operational models.