Descripción del proyecto
Cerrar las brechas de la predicción climática
Las predicciones climáticas estacionales y decenales son fundamentales para la planificación socioeconómica. Sin embargo, mejorar estas predicciones sigue siendo un reto debido a los errores sistemáticos de los modelos existentes, que dificultan sus aplicaciones socioeconómicas. En este contexto, el equipo del proyecto LISTEN, financiado con fondos europeos, desarrollará técnicas innovadoras para mejorar la inicialización de las predicciones, cerrar la brecha entre el clima observado y el modelizado y mejorar las predicciones hasta a unos pocos años de antelación. El proyecto, coordinado por el Programa Mundial de Investigaciones Climáticas, se centra en las predicciones para Europa. Su objetivo es evaluar la capacidad de predicción de fenómenos de escala regional como, por ejemplo, olas de calor, sequías y lluvias torrenciales mediante el análisis de patrones recurrentes de variabilidad a gran escala, conocidos como «regímenes meteorológicos». Las herramientas desarrolladas en el marco del proyecto se pondrán a disposición del público, lo que facilitará los avances en la predicción climática.
Objetivo
Seasonal and decadal climate predictions are routinely carried out, and are widely used for their numerous socio-economic applications. The improvement of the forecast capabilities at these timescales is the focus of the international effort coordinated by the World Climate Research Programme. The strategy of LISTEN to contribute to this challenge is structured to have two stages. First, it aims at enhancing the transfer of observed information to the model during the initialisation of a forecast. This phase of the climate prediction process is of utmost importance, because it has been shown that a correct initialisation can improve the forecasts up to a few years ahead. However, the systematic errors of the models make this task challenging, because of the discrepancy between the observed and model mean climate. The main consequences are incorrect propagation of systems and a quick loss of the observed information. LISTEN will therefore implement innovative initialisation techniques. These are explicitly designed to tackle specific limitations detected in the methods currently in use. The new techniques will be tested at both seasonal and decadal timescales, and their performance will be compared to the standard methods.
The second stage of the project consists in exploiting the data produced by the first stage for an in-depth assessment of the prediction skill, with a special focus over Europe. Large uncertainties remain in predicting events on regional scales, such as heat waves, droughts or heavy rain and snow. LISTEN will aim at a thorough assessment of the model strengths and weaknesses in predicting those events under different initialisation strategies. In particular, the sub-seasonal circulation and extreme weather events will be studied in the framework of circulation patterns, through the analysis of large-scale recurrent patterns of variability (weather regimes). The tools developed to compute these process-based metrics will be made publicly available.
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MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)Coordinador
00185 Roma
Italia