The generate of initial conditions for weather predictions

Abstract

Weather forecasts are very necessary to predict the future weather conditions. The important thing in forecasting is the model and variables. The model used in the forecasting must be accurate and effective. In addition, the variables used in forecasting must be comprehensive and appropriate to be able to represent the forecast. The initial conditions for forecasting must be appropriate and reliable. There are many methods to generate the initial conditions in forecasting. To generate the initial conditions for winter monsoon prediction with Kalman Filtering method, which is a method, used to predict the status of various systems and able to create values of variables used in forecasting to have a variety of similarities, can be used as a starting variable in forecasting very well. In this research the winter monsoon prediction by the Shallow Water Model and validating the initial conditions by Root Mean Square Error (RMSE). The result of weather prediction in the winter monsoon can be used the Kalman Filtering method for generate the initial conditions.