Numerical weather forecast with variational data assimilation in the Andes

The ARW version of the WRF model is used to explore the impact of both 3DVAR and 4DVAR data assimilation schemes in weather forecasts for the Andean countries (Venezuela, Colombia, Ecuador, Perú, Bolivia and Chile). The dataset for the assimilation process includes local SYNOP, METAR and TEMP observations, and the first guess fields are provided by the GFS. Both assimilation methods are discussed for different geographical sub-regions in terms of forecast improvements but also in terms of execution times. The performance of the model simulating precipitation amounts in the region is analyzed. The model underestimates rainfall amounts over the Andes and the errors are maximize on orographic complex regions. Simulations are improved when the 4DVAR scheme is applied with measurements from different sources (weather stations and satellites). Wind speed at low levels are evaluated to determine potential areas for wind energy generation.