Understanding Atmospheric Motion Vector Vertical Representativity Using a Simulation Study and First-Guess Departure Statistics

Abstract

tmospheric motion vectors (AMVs) have been produced for decades and remain an important source of wind information. Many studies have suggested that the traditional interpretation of AMVs as representative of the wind at cloud top is suboptimal and that they are more representative of the winds within the cloud. This paper investigates the vertical representativity of cloudy AMVs using both first-guess departure [observation ? background (O ? B)] statistics and the simulation-study technique. A state-of-the-art convection-permitting mesoscale model (?UKV?) is used in conjunction with a radiative transfer model and the Nowcasting Satellite Application Facility (NWCSAF) AMV package to produce synthetic AMVs over a 1-month period. The simulated upper-level AMVs suffered from large height-assignment errors uncharacteristic of those in reality; these issues were partially alleviated by using the model cloud top instead of the assigned height. In agreement with previous studies, both the simulated and real AMVs were found to have the closest fit to a layer mean of the model winds with the majority of the layer below the estimated cloud top. However, improvements in the fit between the AMVs and the model were also found by simply lowering the assigned height. A short NWP trial hinted that height reassignment might lead to short-range forecast improvements. The results of this study indicate that the simulation technique was able to match the usefulness of O ? B statistics for AMVs associated with low- and medium-level clouds (albeit at a higher computational cost); however, challenges remain in the simulation of upper-level clouds.