1.2 Operational Forecast–Based Estimates of the Practical Predictability of Weather

Monday, 13 January 2020: 9:15 AM
104C (Boston Convention and Exhibition Center)
Istvan Szunyogh, Texas A&M Univ., College Station, TX; and N. Zagar

The talk investigates the practical predictability of weather based on deterministic and ensemble forecasts from the leading operational numerical weather prediction centers of the world. It defines the practical predictability limit of a meteorological field (e.g., 500 hPa wind) or event (e.g., the location of a precipitation event) by the forecast time at which the rms forecast error normalized by its saturation value reaches a prescribed threshold value (e.g., 60%). The investigative technique fits a parametric function to the curve that describes the growth of the rms error of the forecasts with forecast time for a sample of forecasts. This function both provides an estimate of the magnitude of the initial condition (analysis) error and describes the functional dependence of the magnitude of the forecast error on the magnitude of the analysis error. Thus, it can be used for the estimation of the forecast error reduction that can be achieved by reducing the magnitude of the analysis error by a presumed percentage. In addition, for a pair of samples from two different years, it can be used for the quantitative attribution of the forecast improvements between the years to analysis or model improvements. In the case of meteorological fields, the calculations are carried out for the different spatial scales (wave numbers) separately.
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