Improving the Temporal Resolution Problem by Localized Gridpoint Nudging in Regional Weather and Climate Models

Most regional numerical models in the atmospheric sciences use temporally interpolated data provided by other low-resolution models, either for a gridpoint coupling at their lateral boundaries or for a spectral nudging of the large scales in the entire domain. In some cases, such as fast-propagating storms, these interpolations can seriously corrupt the meteorological fields. This article shows how to use an operational high-pass filter of the surface pressure field to detect and to localize a propagating storm, and to use this information to locally reinject the available uncorrupted storm in the coupled model. This is achieved by applying a technique of gridpoint nudging in a subarea of the domain, limited to a compact region around the eye of the depression. As an application it is shown that this restores the strength of the storm, while leaving the model state in the rest of the domain quasi intact. It is then discussed how this can improve numerical weather prediction and regional climate models.