Linking weather generators and crop models for assessment of climate forecast outcomes

• Autores: Apipattanavis, Somkiat; Bert, Federico Esteban; Podestá, Guillermo; Rajagopalan, Balaji
• Año de publicación: 2010
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Climate Impacts; Seasonal Forecasting; Risk Assessment; Statistical Downscaling; Maize; Argentina
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

Agricultural production responses to climate variability require salient information to support decisions. We coupled a new hybrid stochastic weather generator (combining parametric and nonparametric components) with a crop simulation model to assess yields and economic returns relevant to maize production in two contrasting regions (Pergamino and Pilar) of the Pampas of Argentina. The linked models were used to assess likely outcomes and production risks for seasonal forecasts of dry and wet climate. Forecasts involving even relatively small deviations from climatological probabilities of precipitation may have large impacts on agricultural outcomes. Furthermore, yield changes under alternative scenarios have a disproportionate effect on economic risks. Additionally, we show that regions receiving the same seasonal forecast may experience fairly different outcomes: a forecast of dry conditions did not change appreciably the expected distribution of economic margins in Pergamino (a climatically optimal location) but modified considerably economic expectations (and thus production risk) in Pilar (a more marginal location).
Fil: Apipattanavis, Somkiat. State University Of Colorado Boulder; Estados Unidos
Fil: Bert, Federico Esteban. Universidad de Buenos Aires. Facultad de Agronomia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Podestá, Guillermo. University of Miami; Estados Unidos
Fil: Rajagopalan, Balaji. State University Of Colorado Boulder; Estados Unidos