Distribution-Oriented Verification of Limited-Area Model Forecasts in a Perfect-Model Framework

Abstract

Abstract Nested limited-area models (LAMs) have been used by the scientific community for a long time, with the implicit assumption that they are able to generate meaningful small-scale features that were absent in the lateral boundary conditions and sometimes even in the initial conditions. This hypothesis has never been seriously challenged in spite of reservations expressed by part of the scientific community. In order to study this hypothesis, a perfect-model approach is followed. A high-resolution LAM driven by global analyses is used over a large domain to generate a “reference run.” These fields are filtered afterward to remove small scales in order to mimic low-resolution nesting data. The same high-resolution LAM, but over a small domain, is nested with these filtered fields and run for several days. The ability of the LAM to regenerate the small scales that were absent in the initial and lateral boundary conditions is estimated by comparing both runs over the same region. The simulations are ana...