Calibration Indonesian-Numerical Weather Prediction using Geostatistical Output Perturbation

Abstract

Indonesian-Numerical Weather Prediction (INA-NWP) is a numerical-based weather forecast method that has been developed by the Meteorology, Climatology and Geophysics Agency. However, the forecast is still unable to produce accurate weather forecasts. Geostatistical Output Perturbation (GOP) is a weather forecast method derived from only one deterministic output. GOP takes into consideration the spatial correlation among multiple locations simultaneously. GOP is capable to identify spatial dependency patterns that are associated with error models. This study aims to obtain calibrated forecasts for daily maximum and minimum temperature variables using GOP at 10 meteorological stations in Surabaya and surrounding areas. The stages in performing temperature forecasts using GOP are obtaining regression coefficient estimators, then calculating empirical semivariograms and estimating spatial parameters. Based on several weather forecast indicators, such as RMSE and CRPS, GOP is better than INA-NWP in terms of precision and accuracy.