Wind and Temperature Retrievals in the 17 May 1981 Arcadia, Oklahoma, Supercell: Ensemble Kalman Filter Experiments

摘要

The feasibility of using an ensemble Kalman filter (EnKF) to retrieve the wind and temperature fields in an isolated convective storm has been tested by applying the technique to observations of the 17 May 1981 Arcadia, Oklahoma, tornadic supercell. Radial-velocity and reflectivity observations from a single radar were assimilated into a nonhydrostatic, anelastic numerical model initialized with an idealized (horizontally homogeneous) base state. The assimilation results were compared to observations from another Doppler radar, the results of dual-Doppler wind syntheses, and in situ measurements from an instrumented tower. Observation errors make it more difficult to assess EnKF performance than in previous storm-scale EnKF experiments that employed synthetic observations and a perfect model; nevertheless, the comparisons in this case indicate that the locations of the main updraft and mesocyclone in the Arcadia storm were determined rather accurately, especially at midlevels. The magnitudes of vertical velocity and vertical vorticity in these features are similar to those in the dual-Doppler analyses, except that the low-level updraft is stronger in the EnKF analyses than in the dual-Doppler analyses. Several assimilation-scheme parameters are adjustable, including the method of initializing the ensemble, the inflation factor applied to perturbations, the magnitude of the assumed observation-error variance, and the degree of localization of the filter. In the Arcadia storm experiments, in which observations of a mature storm were assimilated over a relatively short (47 min) period, the results depended most on the ensemble-initialization method. In the data assimilation experiments, too much northerly storm-relative outflow along the south side of the low-level cold pool eventually developed during the assimilation period. Assimilation of Doppler observations did little to correct temperature errors near the surface in the cold pool. Both observational limitations (poor spatial resolution in the radar data near the ground) and model errors (coarse resolution and uncertainties in the parameterizations of moist processes) probably contributed to poor low-level temperature analyses in these experiments.