@article{Pramet Kaewmesri_Usa Humphries_2020, title={IMPROVING RAINFALL PERFORMANCE BY DECAYING AVERAGE BIAS CORRECTION VIA LYAPUNOV THEORY}, volume={19}, url={https://geomatejournal.com/geomate/article/view/1761}, abstractNote={<p>The bias correction is the main tool for improving the rainfall simulation from the model to<br>improve performance and increasing accuracy with observation. Since, if the good estimate and more accuracy<br>of rainfall simulation are crucial to helping the risk assessment policies for increasing demands from<br>agricultural, industrial and domestic sectors for many countries. So, the aim of this study, to improving<br>decaying average bias correction by using the Lyapunov theorem for simulating rainfall over Indochina<br>Peninsular. The time period for exampling the results were in Mar, April, and May 2015. The results were<br>shown a comparison between standalone model simulation results and bias correction results (Theorem 2 and<br>Theorem 3) as shown in time series and statistical method value. The times series results were shown the results<br>from bias correction improving by Lyapunov (Theorem 2 and Theorem 3) that show good estimates than the<br>standalone model simulation. In statistical analysis, the bias correction improving by the Lyapunov theorem<br>(Theorem 2 and Theorem 3) were shown the highest accuracy (MAE and RMSE) than standalone model<br>simulation. However, the results from the time sires and statistical analysis were guaranteed the bias correction<br>improving by the Lyapunov theorem that can improve the results of the model and increase more accuracy<br>when compared with reanalysis grid observation data.<br><br></p>}, number={73}, journal={GEOMATE Journal}, author={Pramet Kaewmesri and Usa Humphries}, year={2020}, month={Sep.}, pages={49–56} }