Numerical Weather Prediction at 200 m Local Resolution Based on an Unstructured Grid Global Model

Abstract

AbstractIt is a great challenge to reach sub‐km resolution in numerical weather prediction models without using domain nesting techniques. The Model for Prediction Across Scales – Atmosphere (MPAS‐A) uses an unstructured grid to achieve smooth transition of resolution in a global model. However, a number of model physical parameterization schemes and methods to enhance computational efficiency assume resolution down to about 3 km only. We extended the MPAS‐A model to support resolution down to 200 m and carried out idealized and hindcast numerical experiments over a domain covering Hong Kong. The Shin‐Hong Planetary Boundary Layer scheme was integrated to parameterize partially resolved turbulence in a scale‐aware sense. The quality of static geographical data and land‐water boundary for a coastal urban locale are found to be vital to the forecast accuracy of ground temperature and humidity forecast. Resolving terrain to 200 m, the model is found to be able to simulate the sheltering effect of mountains as well as high wind speed at hill top comparable to station observation. Our results indicate that global model simulations with an unstructured grid can realistically reproduce local weather conditions, suitable for ultra‐high‐resolution predictions and studies.