" In this contribution, we present a post-process analysis of the Weather Research and Forecasting (WRF) model which combines a Kalman Filter with Model Output Statistics for bias correction in order to improve the overall predicted values of GHI simulations over Paraguay. The hourly GHI is simulated at 4x4 km2 of spatial resolution. The annual evaluation of the hourly WRF model without post process shows relative mean bias error (rMBE) of 21% and relative root mean square error (rRMSE) of 81%. The results using several ground stations and combinations of post-process show an annual correction of systematic errors with rMBE of -0.7% and rRMSE of 70%."CONACYT - Consejo Nacional de Ciencias y TecnologíaPROCIENCI
