Abstract
In this study, the performance of two different Microphysics Scheme options in Weather Research and Forecasting (WRF) model were evaluated for the estimating the precipitation forecast. The schemes WRF single moment class-3 (WSM-3) and single moment class-6 (WSM-6) were employed to produce the minimum, medium and maximum precipitation for the selected events over the Kuantan River Basin (KRB). The obtained simulated results were compared with the observed data from eight different rainfall gauging stations. The results comparison indicate that WRF model provides better forecasting at some rainfall stations for minimum and medium rainfall events but did not produce good result during maximum rainfall overall. The WSM-6 scheme is found to produce better result compared to WSM-3. The study also found that to acquire accurate precipitation results, it is also required to test some other physics scheme parameterization to enhance the model performance.
Highlights
The new generation Weather Research and Forecasting (WRF) model is the collaborative product of National Central of Atmospheric Research (NCAR) the mesoscale division, the national environmental prediction and forecast system lab (FSL) of Nation Oceanic and Atmospheric Administration (NOAA), the Naval Research Laboratory (NRL), the Department of Defence’s Airforce Weather Agency (AFWA) and the Centre for Analysis and Prediction of Storms (CAPS) from the University of Oklahoma and the contribution of number of research scientists along with Federal Aviation Administration (FAA)
The impact of two-available microphysics schemes in WRF model were tested for three different rainfall scenarios
Microphysics scheme plays a vital role in atmospheric science
Summary
The model is designed for both operational forecasting and weather research [1]. WRF contains many configured physics schemes to be implemented by the model user which include the advantages such as economical computation, existing default parameters, and relatively large spatial resolution grid. The definition of parameterization refers to the process of selecting required parameters for a specific model. A significant amount of research has been conducted to evaluate the influence of physics parameterization and sensitivity of WRF in meteorological scenarios [3,4,5,6,7,8]. The parameterization of schemes is an important aspect related to the model forecasting accuracy. The blending of schemes depends on the domain of the research selection
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