Processing of high-resolution temporal climate data for daily simulations of a complex agro-ecosystem.

Ecosystem services, such as natural pest control, are essential tools to be incorporated in future agricultural methodologies. In this paper we focus on the processing of climate data series that feed to a system of computer models simulating daily interactions of a pest and its predator, in a dynamic landscape, the olive grove. We filled hourly climate data series and converted them to daily climate series using R language. The methodology used produces acceptable climate data series for the system to run and allows to segregate specific periods of the day while maintaining daily temporal resolution. We expect this paper can be helpful when dealing with similar data and purpose.