Evaluation of Weather Research and Forecasting (WRF) Microphysics single moment class-3 and class-6 in Precipitation Forecast

Zaidi, Syeda Maria; Gisen, Jacqueline Isabella Anak

doi:10.1051/matecconf/201815003007

Cited by 6 publications

(4 citation statements)

References 11 publications

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“…For all simulations, the same parameterization of physics and model dynamics was used. We applied a single-moment microphysics scheme with six hydrometeor classes (WSM6) (Zaidi, Gisen 2018), which is the most suitable for high-resolution simulations (see, e.g., Hong et al 2010;Parodi et al 2019). For domain 1, parameterization of convective processes was performed using the Grell-Freitas method (Grell, Freitas 2014), while for domains 2 and 3, explicit wet process physics was used.…”

Section: Wrf Modelmentioning

confidence: 99%

The impact of initial and boundary conditions on severe weather event simulations using a high-resolution WRF model. Case study of the derecho event in Poland on 11 August 2017

Figurski¹,

Nykiel²,

Jaczewski³

et al. 2021

Meteorol. Hydrol. Water Manage.

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Precise simulations of severe weather events are a challenge in the era of changing climate. By performing simulations correctly and accurately, these phenomena can be studied and better understood. In this paper, we have verified how different initial and boundary conditions affect the quality of simulations performed using the Weather Research and Forecasting Model (WRF). For our analysis, we chose a derecho event that occurred in Poland on 11 August 2017, the most intense and devastating event in recent years. High-resolution simulations were conducted with initialization at 00 and 12 UTC (11 August 2017) using initial and boundary conditions derived from the four global models: Global Forecast System (GFS) from the National Centers for Environmental Prediction (NCEP), Integrated Forecast System (IFS) developed by the European Center for Medium-Range Weather Forecasts (ECMWF), Global Data Assimilation System (GDAS) and ERA5. For the last, we made separate calculations using data at the pressure and model levels. The results were evaluated against surface and radar data. We found that the simulations that used data from the GDAS and GFS models at 12 UTC were the more accurate, while ERA5 gave the worst predictions. However, all models were characterized by a low probability of detection and a high number of false alarms for simulations of extreme precipitation and wind gusts.

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Section: Wrf Modelmentioning

confidence: 99%

The impact of initial and boundary conditions on severe weather event simulations using a high-resolution WRF model. Case study of the derecho event in Poland on 11 August 2017

Figurski¹,

Nykiel²,

Jaczewski³

et al. 2021

Meteorol. Hydrol. Water Manage.

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show abstract

“…Therefore, this study adopted only MP and CU schemes. Currently, there are 13 microphysics and 14 cumulus schemes available for model simulation [44]. It is to be noted that not every scheme is suitable for all regions and climatic conditions.…”

Section: Selection Of Schemes For Model Sensitivity Testmentioning

confidence: 99%

Assessment of Weather Research and Forecasting (WRF) Physical Schemes Parameterization to Predict Moderate to Extreme Rainfall in Poorly Gauged Basin

et al. 2022

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Incomplete hydro-meteorological data and insufficient rainfall gauges have caused difficulties in establishing a reliable flood forecasting system. This study attempted to adopt the remotely sensed hydro-meteorological data as an alternative to the incomplete observed rainfall data in the poorly gauged Kuantan River Basin (KRB), the main city at the east coast of Peninsula Malaysia. Performance of Weather Research and Forecasting (WRF) schemes’ combinations, including eight microphysics (MP) and six cumulus, were evaluated to determine the most suitable combination of WRF MPCU in simulating rainfall over KRB. All the obtained results were validated against observed moderate to extreme rainfall events. Among all, the combination scheme Stony Brook University and Betts–Miller–Janjic (SBUBMJ) was found to be the most suitable to capture both spatial and temporal rainfall, with average percentage error of about ±17.5% to ±25.2% for heavy and moderate rainfall. However, the estimated PE ranges of −58.1% to 68.2% resulted in uncertainty while simulating extreme rainfall events, requiring more simulation tests for the schemes’ combinations using different boundary layer conditions and domain configurations. Findings also indicate that for the region where hydro-meteorological data are limited, WRF, as an alternative approach, can be used to achieve more sustainable water resource management and reliable hydrological forecasting.

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“…We used a single-moment microphysics scheme with six hydrometeor classes (WSM6) (Zaidi and Gisen 2018), Grell-Freitas convective parameterisation (Grell and Freitas 2014) for the 12.5-km domain, and explicit wet process physics for the 2.5-km domain. The model used RRTMG radiative scheme (Iacono et al 2008), the Mellor Yamada Nakanishi Niino (MYNN) turbulence scheme (Nakanishi and Niino 2009) with 2.5-order closure for boundary layer processes, and the MYNN level 3 scheme for parametrisation of the near-surface layer (Nakanishi and Niino 2006).…”

Section: Weather Research and Forecasting Model Datamentioning

confidence: 99%

High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model

Mandal

Nykiel

Strzyżewski

et al. 2021

Int. J. Wildland Fire

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Due to climate change and associated longer and more frequent droughts, the risk of forest fires increases. To address this, the Institute of Meteorology and Water Management implemented a system for forecasting fire weather in Poland. The Fire Weather Index (FWI) system, developed in Canada, has been adapted to work with meteorological fields derived from the high-resolution (2.5 km) Weather Research and Forecasting (WRF) model. Forecasts are made with 24- and 48-h lead times. The purpose of this work is to present the validation of the implemented system. First, the results of the WRF model were validated using in situ observations from ~70 synoptic stations. Second, we used the correlation method and Eastaugh’s percentile analysis to assess the quality of the FWI index. The data covered the 2019 fire season and were analysed for the whole forest area in Poland. Based on the presented results, it can be concluded that the FWI index (calculated based on the WRF model) has a very high predictive ability of fire risk. However, the results vary by region, distance from human habitats, and size of fire.

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Evaluation of Weather Research and Forecasting (WRF) Microphysics single moment class-3 and class-6 in Precipitation Forecast

Cited by 6 publications

References 11 publications

The impact of initial and boundary conditions on severe weather event simulations using a high-resolution WRF model. Case study of the derecho event in Poland on 11 August 2017

The impact of initial and boundary conditions on severe weather event simulations using a high-resolution WRF model. Case study of the derecho event in Poland on 11 August 2017

Assessment of Weather Research and Forecasting (WRF) Physical Schemes Parameterization to Predict Moderate to Extreme Rainfall in Poorly Gauged Basin

High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model

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