Evaluation of Optimized WRF Precipitation Forecast over a Complex Topography Region during Flood Season

Li, Yuan; Liu, Guihua; Wu, Zhiyong; He, Honglin; Shi, Jun; Ma, Yuexiong; Weng, Shichuang

doi:10.3390/atmos7110145

Cited by 20 publications

(16 citation statements)

References 33 publications

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“…The statistical results indicate that the model results from the smaller outer domains and shorter lead times perform better statistically than those from larger domains and longer lead times. Goswami et al [13] investigated this issue using >10 km resolutions and the Fifth-generation Penn State/NCAR Mesoscale Model (MM5) simulations for three high-impact weather (heavy rainfall) events over the Tropics to establish the best model performance. Their results showed that domain size is as important as grid spacing and initial conditions in the simulating high-impact weather events.…”

Section: Discussionmentioning

confidence: 99%

“…Dravitzki and McGregor [10] investigated heavy rainfall events over the Waikato River Basin of New Zealand generated with higher-resolution WRF, and Goswami et al [11,12] showed that domain size is as important as grid spacing and initial conditions for heavy rainfall events. Additionally, Li et al [13] analyzed the influence of horizontal resolution, domain size, and physical parameterization schemes to evaluate an optimized WRF precipitation forecast over a region of complex topography during the flood season. The research-grade and storm-scaled operational Numerical Weather Prediction (NWP) models of the Korea Meteorology Administration (KMA) regularly produce simulations with a horizontal grid spacing as fine as 1 km over the megacity of Seoul and its surrounding cities, and have been used to obtain new insights to develop a high-resolution model configuration based on WRF [14,15].…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity Study on High-Resolution WRF Precipitation Forecast for a Heavy Rainfall Event

Jee

Kim

2017

Atmosphere

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A high-resolution Weather Research and Forecasting (WRF) model for a heavy rainfall case is configured and the performance of the precipitation forecasting is evaluated. Sensitivity tests were carried out by changing the model configuration, such as domain size, sea surface temperature (SST) data, initial conditions, and lead time. The numerical model employs one-way nesting with horizontal resolutions of 5 km and 1 km for the outer and inner domains, respectively. The model domain includes the capital city of Seoul and its suburban megacities in South Korea. The model performance is evaluated via statistical analysis using the correlation coefficient, deviation, and root mean squared error by comparing with observational data including, but not limited to, those from ground-based instruments. The sensitivity analysis conducted here suggests that SST data show negligible influence for a short range forecasting model, the data assimilated initial conditions show the more effective results rather than the non-assimilated high resolution initial conditions, and for a given domain size of the forecasting model, an appropriate outer domain size and lead time of <6 h for a 1-km high-resolution domain should be taken into consideration when optimizing the WRF configuration for regional torrential rainfall events around Seoul and its suburban area, Korea.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sensitivity Study on High-Resolution WRF Precipitation Forecast for a Heavy Rainfall Event

Jee

Kim

2017

Atmosphere

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“…A fully compressible, non-hydrostatic dynamic framework is adopted in the ARW module. In recent years, WRF has been widely used in both academic research and industry [32][33][34]. Many studies show that WRF can simulate lower boundary conditions well over complex orography [35,36], which can help WRF to couple with CFD accurately.…”

Section: Wrf Model Setupmentioning

confidence: 99%

A Study on Microscale Wind Simulations with a Coupled WRF–CFD Model in the Chongli Mountain Region of Hebei Province, China

Sun

Zhang

et al. 2019

Atmosphere

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To ensure successful hosting of the 2022 Olympic Winter Games, a comprehensive understanding of the wind field characteristics in the Chongli Mountain region is essential. The purpose of this research was to accurately simulate the microscale wind in the Chongli Mountain region. Coupling the Weather Research and Forecasting (WRF) model with a computational fluid dynamics (CFD) model is a method for simulating the microscale wind field over complex terrain. The performance of the WRF-CFD model in the Chongli Mountain region was enhanced from two aspects. First, as WRF offers multiple physical schemes, a sensitivity analysis was performed to evaluate which scheme provided the best boundary condition for CFD. Second, to solve the problem of terrain differences between the WRF and CFD models, an improved method capable of coupling these two models is proposed. The results show that these improvements can enhance the performance of the WRF-CFD model and produce a more accurate microscale simulation of the wind field in the Chongli Mountain region.Atmosphere 2019, 10, 731 2 of 21 models [9][10][11]. Therefore, great terrain differences exist between reality and the mesoscale models, and nearly no mesoscale model can work over extremely steep terrain. Some scholars applied WRF in the large eddy simulation (LES) mode to increase model resolution [12][13][14], but the low vertical resolution and the need for a smoothing process for terrain data still exist. Moreover, the computational cost of a WRF-LES simulation is relative high. Fortunately, the computational fluid dynamics (CFD) model can partially compensate for the shortcomings of the mesoscale model. First, CFD can simulate the wind field with higher spatial resolutions (a few meters to tens of meters) than those of the mesoscale models [15][16][17][18]. Moreover, most CFD models are based on the finite volume method, which can improve their ability to depict realistic terrain [19]. However, CFD has its shortcoming in coping with the boundary conditions, and usually uses a simple wind profile as the boundary condition in some research. The mesoscale model can be initialized using global-scale data, such as the National Centers for Environmental Prediction (NCEP) reanalysis data. Therefore, coupling the mesoscale models with the CFD models is one way of simulating the microscale wind field over complex terrain. In this coupled system, the mesoscale and CFD models are combined in an off-line way, and the boundary condition that drives the CFD simulation is taken from the outputs of the mesoscale model [20]. First, the wind field with low spatial resolution is simulated by the WRF model. Second, the WRF wind data are imposed on the boundary of the CFD model. Finally, a wind field with higher spatial resolution is simulated by the CFD model. The advantages of this system is that the mesoscale model can provide more realistic boundary conditions and CFD can provide a wind field simulation with much higher spatial resolution.In recent years, a large amount of research on ...

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“…The NWP model used in this research is the WRF model, which is widely used in the atmospheric and oceanic community. In the present case, we adopted version 3.8 of the Advanced Research WRF (WRF-ARW), which is widely applied in atmospheric and oceanic research [13][14][15]. The WRF-ARW model is driven by the National Centers for Environmental Prediction (NCEP)-NCAR reanalysis data, with a 0.25 • × 0.25 • global latitude-longitude grid.…”

Section: Nwp Model-wrfmentioning

confidence: 99%

A Feasibility Study of Simulating the Micro-Scale Wind Field for Wind Energy Applications by NWP/CFD Model with Improved Coupling Method and Data Assimilation

Sun

Zhang³

et al. 2019

Energies

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Understanding the details of micro-scale wind fields is important in the development of wind energy. Research has proven that coupling Numerical Weather Prediction (NWP) and Computational Fluid Dynamics (CFD) models is a better approach for micro-scale wind field simulation. The main purpose of this work is to improve the NWP/CFD model performance in two parts: (i) developing a new coupling method that is more suitable for complex terrain between the NWP and CFD models, and (ii) applying a data assimilation system in the CFD model. Regarding part (i), in order to solve the problem of great topographical difference at the domain boundaries between the two models, Cressman interpolation is utilized to impose the NWP model wind on the CFD model boundaries. In part (ii), an assimilation method, nudging, to apply assimilation of observations into the CFD model is explored. Based on the Cressman interpolation coupling method, a preliminary implementation of data assimilation is performed. The results show that the NWP/CFD model with the improved coupling method may capture the details of micro-scale wind fields more accurately. Using data assimilation, the NWP/CFD model performance may be further improved by cooperating observation data.

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Evaluation of Optimized WRF Precipitation Forecast over a Complex Topography Region during Flood Season

Cited by 20 publications

References 33 publications

Sensitivity Study on High-Resolution WRF Precipitation Forecast for a Heavy Rainfall Event

Sensitivity Study on High-Resolution WRF Precipitation Forecast for a Heavy Rainfall Event

A Study on Microscale Wind Simulations with a Coupled WRF–CFD Model in the Chongli Mountain Region of Hebei Province, China

A Feasibility Study of Simulating the Micro-Scale Wind Field for Wind Energy Applications by NWP/CFD Model with Improved Coupling Method and Data Assimilation

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