Model simulations and satellite microwave observations of moist processes in extratropical oceanic cyclones

Douglas Kirby Miller, Purdue University

Abstract

Coincident satellite passive microwave (SSM/I) observations and 48 h numerical simulations using a hydrostatic limited-area mesoscale model of 23 intensifying extratropical cyclones located over the North Atlantic or North Pacific Oceans during a single cold season have been examined in an attempt to discern systematic differences in the moist processes of storms exhibiting rapid and ordinary intensification rates. Analysis of the observations and simulations focused on the 24 h period of most rapid intensification for each case as determined from European Centre for Medium-Range Weather Forecasts (ECMWF) 12 h mean sea level pressure analyses. Comparisons between the two sets of data highlight inadequacies in model moisture physics and suggest possibilities for improvement. Multiple tests of a single cyclone showed that the final forecast cyclone intensity and position was highly sensitive to the chosen convective parameterization scheme, which determines sub-grid scale warming and drying processes and their effects on storm evolution. SSM/I observations of area-averaged precipitation and an index that responds to cold-cloud (convective) precipitation to the northeast of surface cyclone centers correlated well ($\sim$0.80) with the latitude-normalized deepening rate (NDR) of the study sample. This large correlation was replicated by the numerical model, although the area-averaged precipitation region yielding the maximum coefficient differed significantly from that determined using microwave imagery. A similar correlation emerged between model-derived area- and vertically-averaged vertical motion fields and NDR. The similarity of these correlations for nearly coincident averaging regions relative to the storm center implicates unrealistic patterns in vertical motion fields as the reason for the failure of the model to accurately capture the observed optimal area-averaging region. This region was located near the storm triple point and occluded (bent-back) front, both potentially strongly convective environments. The contribution to cyclone evolution by vorticity and thermal forcing mechanisms was examined by applying a derived Pettersen-Sutcliffe diagnostic equation to dynamic and thermodynamic model output fields. Comparisons of time-averaged instantaneous filtered and unfiltered surface pressure tendency fields indicated storms having strong intensification rates had significant contributions from small-scale features. All storms experienced greatest development during the middle period of the most rapidly deepening phase (from 33-39 h). Examination of unfiltered and filtered contributions to surface pressure deepening by vorticity and thermal forcing mechanisms yielded no useful information due to the existence of "spikes" in the unfiltered fields at isolated grid points (pseudo-singularities). Finally, composites were produced for three classes of observed and simulated cyclone deepening rate showing horizontal and vertical distributions of moist, dynamic and thermodynamic processes. Composites of conditional symmetric instability (CSI) using a parameterization scheme external to the model indicated the presence of CSI, which was unaccounted for by the model, primarily in the proximity of the warm front for all types of cyclone intensification rates. Accounting for CSI in such a location relative to the storm center could potentially provide additional intensification through diabatic heating resulting from latent heat release, which would act to amplify the upper-level ridge. Comparisons of composites located at the 850, 500, and 300 hPa levels indicated greater low-level baroclinicity during the antecedent deepening phase (from 12-24 h) and deeper upper-level geopotential troughs during the most rapidly deepening phase (from 24-48 h) for storms exhibiting strong intensification rates.

Degree

Ph.D.

Advisors

Petty, Purdue University.

Subject Area

Atmosphere|Remote sensing

COinS