Evaluation of surface wind using WRF in complex terrain: Atmospheric input data and grid spacing

Solbakken, Kine; Birkelund, Yngve; Samuelsen, Eirik Mikal

doi:10.1016/j.envsoft.2021.105182

Cited by 21 publications

(5 citation statements)

References 33 publications

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“…The correlation coefficients between the FENZ stations and the data obtained from the gridded weather model are within the range found in comparative literature, which have ranges 0.2-0.53 and 0.78-0.94 for wind speed and air temperature respectively as compared with 0.63 and 0.93 calculated for the present analysis (Pan et al 2012;Banks and Baldasano 2016;Boadh et al 2016;Avolio et al 2017). Similarly, the RMSE is also comparable with other studies using WRF modelling in complex terrain, at 2.21 and 2.13 for wind speed and temperature, respectively (Avolio et al 2017;Mughal et al 2017;Solbakken et al 2021). Based on the meteorological inputs, the FWI calculated for the station data and the WRF data has a correlation coefficient of 0.78, and an RMSE of 5.63.…”

Section: Validation Of Wrf Model Gridded Data For Fire Danger Metricssupporting

confidence: 89%

Wind vector change and fire weather index in New Zealand as a modified metric in evaluating fire danger

Brody-Heine

Zhang

Katurji

et al. 2023

Int. J. Wildland Fire

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Background. Wildfire spread is influenced significantly by the weather variability. Wind speed and direction changes, resulting from synoptic weather systems and small-scale meteorological processes in complex terrain, can drastically alter fire intensity and spread. Aims. To investigate the use of vector wind change (VWC) integrated with the Fire Weather Index (FWI) as a new metric in fire danger. Methods. A 20-year FWI and modified FWI was calculated from weather station and gridded numerical weather simulation data. Key results. High VWC is found primarily on the South Island, inland and in areas of complex terrain. After incorporating VWC into the FWI, data from the modified FWI show spatiotemporal patterns that highlight the impact of wind variability in the fire danger. Conclusions. High VWC station data mapped with synoptic type suggest the primary factor in determining high VWC is meso-and micro-scale terrain-driven meteorology, not larger synoptic regimes. Implications. The current fire danger metric, the Fire Weather Index (FWI), does not include wind direction changes for high wind speeds. Therefore, the inclusion of VWC as an additional metric in fire danger calculations in a modified FWI could increase operational understanding of high-danger locations and terrain impacts on extreme and unpredictable fire behaviour.

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Section: Validation Of Wrf Model Gridded Data For Fire Danger Metricssupporting

confidence: 89%

Wind vector change and fire weather index in New Zealand as a modified metric in evaluating fire danger

Brody-Heine

Zhang

Katurji

et al. 2023

Int. J. Wildland Fire

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“…To thoroughly examine the effect of topography on local-scale wind speed, we calculate and analyze six crucial topographic metrics: elevation, slope, aspect, small and large-scale topographic position index (TPI), and terrain diversity index (TDI). These metrics offer insight into the complexities of the terrain and provide a comprehensive picture of its impact on wind dynamics [20,34,37].…”

Section: Topographic Metricsmentioning

confidence: 99%

Downscaling ERA5 wind speed data: a machine learning approach considering topographic influences

Scholz

Yeligeti

et al. 2023

Environ. Res. Lett.

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Energy system modeling and analysis can provide comprehensive guidelines to integrate renewable energy sources into the energy system. Modeling renewable energy potential, such as wind energy, typically involves the use of wind speed time series in the modeling process. One of the most widely utilized datasets in this regard is ERA5, which provides global meteorological information. Despite its broad coverage, the coarse spatial resolution of ERA5 data presents challenges in examining local-scale effects on energy systems, such as battery storage for small-scale wind farms or community energy systems. In this study, we introduce a robust statistical downscaling approach that utilizes a machine learning approach to improve the resolution of ERA5 wind speed data from around 31 km x 31 km to 1 km x 1 km. To ensure optimal results, a comprehensive preprocessing step is performed to classify regions into three classes based on the quality of ERA5 wind speed estimates. Subsequently, a regression method is applied to each class to downscale the ERA5 wind speed time series by considering the relationship between ERA5 data, observations from weather stations, and topographic metrics. Our results indicate that this approach significantly improves the performance of ERA5 wind speed data in complex terrain. To ensure the effectiveness and robustness of our model, we also perform thorough evaluations by comparing our results with the reference dataset COSMO-REA6 and validating with independent datasets.

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“…Northern territories have substantial wind energy resources and could become an area for expanding the use of renewable wind energy to meet the world's energy needs [3][4]. Another way of using wind energy in the north is energy supply for remote northern settlements that are not connected to the central energy supply systems and are dependent on imported fuel [5].…”

Section: Introductionmentioning

confidence: 99%

Investigation of ice accretion effect on the aerodynamic characteristics of a wind turbine blade tip after a short icing event

Kangash

Pankratov

Kosarev

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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The paper investigates the flow behavior near the NACA 64-618 airfoil profile of the blade tip section of a wind turbine for electric power production after a short icing event. The flow simulation considering the rotation speed of the wind turbine blade is performed to assess the effect of icing on the aerodynamic characteristics. Degradation of aerodynamic characteristics affects the electrical energy production of the wind turbine. The aerodynamic lift and drag coefficients are calculated for different angles of attack. The flow velocity fields near the airfoil are analyzed. The pressure coefficient distributions along the profile surface are obtained. The points of flow stall and changes of aerodynamic characteristics at different angles of attack are determined.

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Evaluation of surface wind using WRF in complex terrain: Atmospheric input data and grid spacing

Cited by 21 publications

References 33 publications

Wind vector change and fire weather index in New Zealand as a modified metric in evaluating fire danger

Wind vector change and fire weather index in New Zealand as a modified metric in evaluating fire danger

Downscaling ERA5 wind speed data: a machine learning approach considering topographic influences

Investigation of ice accretion effect on the aerodynamic characteristics of a wind turbine blade tip after a short icing event

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