Diagnostic tools using a mesoscale NWP model for the early warning of convection

Abstract

A mesoscale numerical weather prediction model and its associated diagnostics are evaluated to gauge their ability to forecast convection and the convective environment for ten case-study days. The diagnostic indices and parameters evaluated are those used to assess atmospheric instability, mesoscale forcing, inhibition and low-level moisture supply. In addition, bulk Richardson number and helicity diagnostics are examined for convection organisation. Convection over mountainous regions is not considered. The case-study days are grouped according to their synoptic type in order to evaluate the usefulness of the forecast diagnostics. In the evaluation it is found that by combining the CAPE (convective available potential energy) and low-level relative humidity diagnostics one can delineate quite large areas where convective triggering is possible and outside which convection will not develop. Organisation of the mesoscale convective systems is also considered. It is found that forecast strong low-level shears tend to be well correlated with observed linear convective systems. A set of stability indices are evaluated quantitatively and qualitatively by comparing the forecast stability indices with observations at a sounding location. CAPE and a simple index based on a moist temperature difference between two layers (Adedokun₂) are identified as the most useful forecast stability indices for all of the cases.