Statistical Considerations in the Estimation of Divergence From Single-Doppler Radar and Application to Prestorm Boundary-Layer Observations

Abstract

Methods of statistical regression have been applied to single-radar radial velocity fields to map certain mesoscale (20–100 km) kinematic properties (e.g., divergence) of the convective boundary layer (CBL). Several methods, previously proposed, were found to produce estimates that were biased or whose variances were too large. When wind fields are linear on the meso- or larger scale, then single-Doppler velocity accuracies allow the estimation of horizontal divergence with an accuracy of about 4 × 10−5 s−1 and a resolution of ∼30 km, which may be sufficient to sense pre-thunderstorm convergenceA case study for 19 June 1980 suggests that single-Doppler weather radars of modest sensitivity can map the mesoscale divergence patterns within the cloud-free CBL. For this day, convergence zones to the northeast seem to precede cloud development by 1–2 h, and to the west precede thunderstorms by 3–4 h.