Validación de un modelo de análogos para la predicción de precipitación y nieve en la Sierra de Guadarrama

1. Álvaro Subias ¹
2. Álvaro Pascual ¹
3. María Luisa Martín ²
4. Francisco Valero ¹
5. María Yolanda Luna ³

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Abstract

Dynamic meteorological models have drawbacks in forecasting highly dependent variables of parameterizations or local processes, such as precipitation and snow. Alternatively, statistical models give estimations based on statistical relationships between input variables and output variables without information about related (lineal or non lineal) physical processes. The statistical analog models are based on finding similar atmospheric situations in an historical data base to any particular atmospheric situation to be modeled. The addition of different variables in the analog searching, includes heterogeneity that should be taken into account in the mathematical methodology in order to optimize the analog model. The present work shows the calibration process of an analog model for forecasting of precipitation and snow in a complex terrain. Several probabilistic results are shown in an area with 38 stations in the Sierra of Guadarrama (inner area of the Iberian Peninsula).

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