9.2 Importance of horizontally inhomogeneous environmental initial conditions to very short range thunderstorm forecasts

Tuesday, 18 August 2009: 2:00 PM
The Canyons (Sheraton Salt Lake City Hotel)
David J. Stensrud, NOAA/NSSL, Norman, OK; and J. Gao

The assimilation of operational Doppler radar observations into convection-resolving numerical weather prediction models for very short-range forecasting represents a significant scientific and technological challenge. Numerical experiments over the past few years indicate that convective-scale forecasts are sensitive to the details of the data assimilation methodology, the quality of the radar data, the parameterized microphysics, and the storm environment. In this study, we investigate the importance of horizontal environmental variability to very short-range (0 – 1 h) convective-scale ensemble forecasts initialized using Doppler radar observations for the 4-5 May 2007 Greensburg, Kansas, tornadic thunderstorm event.

Radar observations of reflectivity and radial velocity from the operational Doppler radar network at 0230 UTC 5 May 2007, during the time of the first large tornado, are assimilated into each ensemble member using a three-dimensional variational data assimilation system (3DVAR) developed at the Center for Analysis and Prediction of Storms (CAPS). Very short-range forecasts are made using the nonhydrostatic Advanced Regional Prediction System (ARPS) model from each ensemble member and results compared with observations. Explicit three-dimensional environmental variability information is provided to the convective-scale ensemble using analyses from a 30-km mesoscale ensemble data assimilation system. Comparisons between convective-scale ensembles with a) initial conditions that are horizontally homogeneous but vertically inhomogeneous (i.e., have different vertical environmental profiles), and b) initial conditions that are horizontally and vertically inhomogeneous are undertaken. Results show that the ensemble with horizontally and vertically inhomogeneous initial conditions provides improved predictions of thunderstorm structure, mesocyclone track, and low-level circulation track than the ensemble with horizontally homogeneous initial conditions. This suggests that knowledge of horizontal environmental variability is important to successful convective-scale ensemble predictions and needs to be included in real data experiments.

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