IMPROVING RAINFALL PERFORMANCE BY DECAYING AVERAGE BIAS CORRECTION VIA LYAPUNOV THEORY (GEOMATE Journal, 2020)
The bias correction is the main tool for improving the rainfall simulation from the model toimprove performance and increasing accuracy with observation. Since, if the good estimate and more accuracyof rainfall simulation are crucial to helping the risk assessment policies for increasing demands fromagricultural, industrial and domestic sectors for many countries. So, the aim of this study, to improvingdecaying average bias correction by using the Lyapunov theorem for simulating rainfall over IndochinaPeninsular. The time period for exampling the results were in Mar, April, and May 2015. The results wereshown a comparison between standalone model simulation results and bias correction results (Theorem 2 andTheorem 3) as shown in time series and statistical method value. The times series results were shown the resultsfrom bias correction improving by Lyapunov (Theorem 2 and Theorem 3) that show good estimates than thestandalone model simulation. In statistical analysis, the bias correction improving by the Lyapunov theorem(Theorem 2 and Theorem 3) were shown the highest accuracy (MAE and RMSE) than standalone modelsimulation. However, the results from the time sires and statistical analysis were guaranteed the bias correctionimproving by the Lyapunov theorem that can improve the results of the model and increase more accuracywhen compared with reanalysis grid observation data.