Sensitivity of the WRF model to the lower boundary in an extreme precipitation event – Madeira island case study

Teixeira, J.; Carvalho, Ana Cristina; Carvalho, M. J.; Luna, T.

doi:10.5194/nhess-14-2009-2014

Cited by 28 publications

(19 citation statements)

References 27 publications

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“…Aside from under-resolved terrain height in modeled grids, which is essentially an oversimplification of the source terrain height data, we show in this paper that uncertainty in source terrain height data sets themselves can be significant enough to result in fundamental differences in simulated orographic flow mechanics. This finding illustrates that the sensitivity of NWP models can be more complex than first-order biases recently documented by Teixeira et al (2014).…”

Section: Introductionsupporting

confidence: 64%

“…The windward islands of the LA are generally lower than GC but are, nonetheless, predominately mountainous with peak elevations near 1 km for each island (see Table 1). The corresponding near-surface wind retrievals from the ASCAT (Advanced Scatterometer) instrument (Vogelzang et al, 2011) on the MetOp-B (Meteorological Operational) satellite are shown in Fig. 2 (right panel).…”

Section: Case Studies and Modeling Detailsmentioning

confidence: 99%

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High-resolution numerical modeling of mesoscale island wakes and sensitivity to static topographic relief data

2015

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Abstract. Recent decades have witnessed a drastic increase in the fidelity of numerical weather prediction (NWP) modeling. Currently, both research-grade and operational NWP models regularly perform simulations with horizontal grid spacings as fine as 1 km. This migration towards higher resolution potentially improves NWP model solutions by increasing the resolvability of mesoscale processes and reducing dependency on empirical physics parameterizations. However, at the same time, the accuracy of high-resolution simulations, particularly in the atmospheric boundary layer (ABL), is also sensitive to orographic forcing which can have significant variability on the same spatial scale as, or smaller than, NWP model grids. Despite this sensitivity, many high-resolution atmospheric simulations do not consider uncertainty with respect to selection of static terrain height data set. In this paper, we use the Weather Research and Forecasting (WRF) model to simulate realistic cases of lower tropospheric flow over and downstream of mountainous islands using the default global 30 s United States Geographic Survey terrain height data set (GTOPO30), the Shuttle Radar Topography Mission (SRTM), and the Global Multi-resolution Terrain Elevation Data set (GMTED2010) terrain height data sets. While the differences between the SRTM-based and GMTED2010-based simulations are extremely small, the GTOPO30-based simulations differ significantly. Our results demonstrate cases where the differences between the source terrain data sets are significant enough to produce entirely different orographic wake mechanics, such as vortex shedding vs. no vortex shedding. These results are also compared to MODIS visible satellite imagery and ASCAT near-surface wind retrievals. Collectively, these results highlight the importance of utilizing accurate static orographic boundary conditions when running high-resolution mesoscale models.

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Section: Introductionsupporting

confidence: 64%

Section: Case Studies and Modeling Detailsmentioning

confidence: 99%

High-resolution numerical modeling of mesoscale island wakes and sensitivity to static topographic relief data

2015

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“…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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“…To solve this problem, meteorological models can be applied in a grid with very high resolution (horizontal grid spacing around 1 km), and physiographic high resolution data may be introduced in the model, allowing incorporating the physical characteristics of the region with greater accuracy and representativeness. In this sense, numerous studies have demonstrated how the incorporation of topography [8]- [12] and land uses [13]- [15] databases with higher resolution significantly improve the forecast performance. Topography and land cover influence on wind patterns, land surface atmosphere interactions, such as low level turbulence and transport, convection, precipitation, runoff, etc.…”

Section: Introductionmentioning

confidence: 99%

Defining a Standard Methodology to Obtain Optimum WRF Configuration for Operational Forecast: Application over the Port of Huelva (Southern Spain)

Arasa¹,

Porras²,

Domingo-Dalmau³

et al. 2016

ACS

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In this contribution, we calibrate the meteorological model weather and research forecasting (WRF) for operational forecasting in the Port of Huelva managed by the Authority Port of Huelva. Meteorological forecasting will allow reducing the impact of the meteorological phenomena over weather sensitive activities in the region. Concretely, the meteorological modeling developed will be used to analyze meteorological hazard impacts and to improve the management of the local air quality. To achieve these goals, numerous sensitive analyses corresponding to different model options have been developed. These analyses consider different physical and dynamical options, the coupling of very high resolution physiographic database (topography and land uses), and data assimilation. Comparing experiments, results with observational measures provide us by the Spanish National Meteorology Agency (AEMET). During a representative period, the optimum WRF configuration for the region is obtained. Calibration has been focused on wind due to this is the main risk factor in the region. When the model is satisfactorily calibrated, WRF is evaluated using whole modeling years 2012 and 2013, working with very high horizontal resolution, up to 0.333 km of horizontal grid resolution. Results obtained from the evaluation indicate that the numerical weather prediction system developed has a confidence level of 70% for the temperature, 81% and 66% for the wind speed and wind direction respectively, and 90% for the relative humidity. Methodology designed defines the quality control assurance of high-accuracy forecasting services of Meteosim S.L. R. Arasa et al.330

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Sensitivity of the WRF model to the lower boundary in an extreme precipitation event – Madeira island case study

Cited by 28 publications

References 27 publications

High-resolution numerical modeling of mesoscale island wakes and sensitivity to static topographic relief data

High-resolution numerical modeling of mesoscale island wakes and sensitivity to static topographic relief data

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

Defining a Standard Methodology to Obtain Optimum WRF Configuration for Operational Forecast: Application over the Port of Huelva (Southern Spain)

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