Ensemble sensitivity analysis applied to Southern Plains convection
Bednarczyk, Christopher N.
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The recent increase in use of ensembles in numerical weather prediction has led to new information being available to forecasters, including uncertainty statistics and probabilistic guidance. Ensemble Sensitivity Analysis (ESA) offers additional information that describes the relationship between a forecast metric known as the response function and initial or early forecast errors, and it is capable of revealing features of the flow that are dynamically relevant to the chosen forecast. The applicability of ESA to a high resolution convection forecast of April 2012 is investigated with an Ensemble Kalman Filter based on the Weather Research and Forecasting model. It is shown that forecasts of convection are primarily sensitive to positional differences in the synoptic-scale flow. The selection of the response function is also explored to determine how to choose a convective forecast metric. Sensitivity does vary with the choice of response, but the same features tend to be highlighted in all cases. Sensitivity is also compared with a standardized form in which the raw value is weighted by the ensemble spread in order to determine the merit of each type. The standardized sensitivity provides information on expected forecast error, and it reveals features that are not highlighted in the raw sensitivity. In addition, a cross-grid approach to sensitivity is studied in order to determine if it shows similar results as the same-grid method. Results show them to have differences, but the cross-grid method still reveals realistic features in the context of the event.