Dynamic Downscaling of Rainfall Data for Deduru Oya River Basin using WRF Weather Model

Samarasingha, S. M. T. C.; Sandaruwan, M. S.; Sampath, D. S.; Neluwala, N. G. P. B.

doi:10.4038/engineer.v54i2.7443

Cited by 3 publications

(1 citation statement)

References 6 publications

(12 reference statements)

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“…Numerous scientific researches on weather forecasting have been conducted in Sri Lanka [22,26,27,28]. However, there is still no precise conclusion on physics schemes from the Sri Lankan studies, which calls for further research.…”

Section: Darshika Et Al (mentioning

confidence: 99%

Performance of Different Parameterization Configurations of WRF-ARW Model during Heavy Rainfall over Mi Oya River Basin

et al. 2023

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Short-term intense precipitation is one of the hallmarks of climate change. Mi Oya River basin experiences severe seasonal floods annually, but the damage can be lessened by developing a numerical weather forecasting (NWF) model for the entire basin and incorporating it with effective reservoir management. Several areas in Sri Lanka have undergone NWF studies, however they are insufficient to determine the best physics schemes for the basin. This study investigates the Weather Research and Forecasting (WRF-ARW) model's predictability with varying three microphysics and two cumulus schemes to discover the optimal set of physics parameters for predicting heavy rainfall occurrences throughout the Southwest and Northeast monsoon seasons within a nested domain configuration. The WRF model's forecasting results at 3 km grid resolution were compared with four rainfall gauging stations in the basin for three rainfall events in May 2016, April 2018, and November 2015. Total Model Performance was derived for the evaluation utilizing bias, MAE, RMSE, Correlation Coefficient, and slope of each model's output data with observed rainfall data. After comparing the model output to data, WSM6 microphysics and Betts-Miller-Janjic cumulus with other default physics settings were determined to be the optimal physics combination to forecast weather across the region.

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Section: Darshika Et Al (mentioning

confidence: 99%

Performance of Different Parameterization Configurations of WRF-ARW Model during Heavy Rainfall over Mi Oya River Basin

et al. 2023

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High-resolution WRF simulations of a monsoon event (2019) over the Badulu Oya Catchment, Sri Lanka: Role of cumulus parameterization condition and microphysics schemes

Gimhan,

Neluwala,

Acierto

2023

J Earth Syst Sci

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Assessment of WRF microphysics and cumulus parameterizations in simulating heavy rainfall events over Badulu Oya catchment, Sri Lanka

Gimhan

Neluwala

Acierto³

et al. 2022

Journal of Water and Climate Change

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Extreme rainfall events leading to severe hydrological impacts warrant an accurate prediction of such events not only on time but also in magnitude. Sri Lanka is a South Asian country that is frequently affected by severe tropical storms. The primary aim of this study was to improve heavy rainfall events forecast during the North-east monsoon over the Badulu Oya catchment, Sri Lanka. This aim was accomplished by simulating precipitation for two extreme North-East monsoon rainfall events using the Weather Research and Forecasting (WRF-ARW) model. A detailed comparison was made between the 24-h spatial distribution of model rainfall and observations obtained from rainfall gauges. Verification was evaluated based on three deterministic approaches. Each rainfall event was simulated multiple times using 15 different parameterization scheme combinations including six microphysics and four cumulus schemes at a 3 km grid resolution. The filtered best model combinations were validated using observations from another two heavy North-East monsoon rainfall events. The key finding from these evaluations was that model configurations with WSM5, WSM6, Kessler and WDM6 microphysics, and KF, BMJ and MKF cumulus schemes displayed the overall best performances. Therefore, these combinations have a good potential for operational use in numerical weather prediction over the said catchment.

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Dynamic Downscaling of Rainfall Data for Deduru Oya River Basin using WRF Weather Model

Cited by 3 publications

References 6 publications

Performance of Different Parameterization Configurations of WRF-ARW Model during Heavy Rainfall over Mi Oya River Basin

Performance of Different Parameterization Configurations of WRF-ARW Model during Heavy Rainfall over Mi Oya River Basin

High-resolution WRF simulations of a monsoon event (2019) over the Badulu Oya Catchment, Sri Lanka: Role of cumulus parameterization condition and microphysics schemes

Assessment of WRF microphysics and cumulus parameterizations in simulating heavy rainfall events over Badulu Oya catchment, Sri Lanka

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