This paper presents the results of a forecast skill score comparison for the popular two semester weather forecast game played at University of Missouri, Columbia, MO, United States, for a total of 106 days, during the autumn 2006 and winter 2007 semesters. A relatively less experienced/first time student forecaster (SF) skill, based upon the funnel approach to weather forecasting, is compared with the then state-of-the-art mesoscale operational numerical weather prediction (NWP) model outputs and the observations. Several measures of the forecast skills are employed to illustrate the intercomparison of the different aspects of performance of the game players for a conventional forecast game setup in an educational environment, after paying particular attention to the associated sampling uncertainty in the analysis of the forecast game. Bootstrap resampling based confidence intervals are computed and compared for the SF and NWP model forecasts and the observations to quantify the relative accuracies of the forecasts. The SF performed quite comparable to the NWP models, and better than the climatology and the persistence, for the next-day forecasts of temperature and precipitation, when the forecast skill scores of the game players were averaged over the period of the forecast game. These observations support the judgement that the contribution of human forecasters, even in the contemporary era of progressively improving and fully automated NWP model outputs, remained a crucial one.
RESUMENDebido al interés creciente del público general por acceder a servicios comerciales de pronóstico meteorológico a través de diversos medios de comunicación, y al impulso que ha cobrado la promoción del turismo en Arabia Saudita (AS), se hace un primer intento de comparar aptitudes para el pronóstico de la temperatura superficial en cuatro ciudades situadas en la costa oeste de AS (Wejh, Yenbo, Jeddah, y Giza), centrado en la fase de transición de 61 días (del 16 de enero al 16 de marzo) entre los periodos diciembre-enero-febrero y marzo-abril-mayo. Se utiliza un método sencillo de comparación de puntajes para evaluar los pronósticos de temperatura superficial de 24 h realizados por seis proveedores comerciales de pronósticos del tiempo basados en un modelo numérico. Todos los proveedores que utilizaron el modelo numérico de predicción del tiempo obtuvieron mejores resultados que la climatología diaria para la estación correspondiente. Dependiendo del proveedor y la estación, la diferencia absoluta en los promedios de temperatura máxima entre los pronósticos y las observaciones fue menor a 2 ºC. Los pronósticos diarios de temperatura superficial obtenidos a partir de dos versiones de un modelo de circulación general océano-atmósfera también se comparan para evaluar su desempeño en estas localidades costeras. ABSTRACTGiven the growing interest of the general public in accessing commercial weather forecasts through various media outlets and the available impetuses for promoting tourism in Saudi Arabia (SA), a first attempt is made to present a forecast skill comparison for surface temperature in four cities (Wejh, Yenbo, Jeddah, and Gizan) along the west coast of SA, for the 61-day transitional period (from January 16 to March 16) between the December-January-February (DJF) and the March-April-May (MAM) seasons. A simple skill score comparison method is used to assess the next-day city forecasts for surface temperature from six commercial weather forecast providers based on the operational numerical weather prediction (NWP) model outputs. All the NWP model forecast providers performed better than the respective daily climatology (Clm) for each station. Depending upon the station and the provider, the absolute average maximum daily surface temperature difference between the forecasts and the observations was less than 2 ºC. Daily surface temperature forecasts from two versions of an atmospheric-ocean general circulation model are also compared to assess their performance for these coastal locations.
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