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Resumen. En la actualidad, los modelos de cultivo son una herramienta util a la hora de tomar decisiones, no obstante, pese a su disponibilidad y facilidad de uso, la informacion necesaria para utilizarlos no existe o no tiene la calidad suficiente. Un ejemplo preciso del deficit de calidad en los datos lo constituyen las series meteorologicas diarias en las que predominan faltantes. Para hacer frente a esta situacion y poder utilizar los modelos de cultivo se elaboro un software para llenar espacios vacios en series climaticas diarias, basada en una cadena de Markov de orden dos y dos estados. La herramienta llamada SueMulador, se probo y valido con exito en tres estaciones ubicadas en zonas contrastantes de la geografia colombiana. / Abstract. Currently, crop models are an useful tool for decision making; however, even though they are available and are easy to use, the information needed to use does not exist or not have sufficient quality. A specific example of the lack of quality is the daily weather series, in which there is too much missing data. To address this situation and to use crop models, we developed a software to fill gaps in daily climate series based on a Markov chain of order two and two states. The new tool, called SueMulador, was successfully tested and validated in three contrasting regions of Colombia.

SueMulador: Herramienta para la Simulación de Datos Faltantes en Series Climáticas Diarias de Zonas Ecuatoriales