scholarly journals Evaluation of Different WRF Parametrizations over the Region of Iași with Remote Sensing Techniques

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 559 ◽  
Author(s):  
Iulian-Alin Roșu ◽  
Silvia Ferrarese ◽  
Irina Radinschi ◽  
Vasilica Ciocan ◽  
Marius-Mihai Cazacu

This article aims to present an evaluation of the Weather Research and Forecasting (WRF) model with multiple instruments when applied to a humid continental region, in this case, the region around the city of Iași, Romania. A series of output parameters are compared with observed data, obtained on-site, with a focus on the Planetary Boundary Layer Height (PBLH) and on PBLH-related parametrizations used by the WRF model. The impact of each different parametrization on physical quantities is highlighted during the two chosen measurement intervals, both of them in the warm season of 2016 and 2017, respectively. The instruments used to obtain real data to compare to the WRF simulations are: a lidar platform, a photometer, and ground-level (GL) meteorological instrumentation for the measurement of temperature, average wind speed, and pressure. Maps of PBLH and 2   m above ground-level (AGL) atmospheric temperature are also presented, compared to a topological and relief map of the inner nest of the WRF simulation. Finally, a comprehensive simulation performance evaluation of PBLH, temperature, wind speed, and pressure at the surface and total precipitable water vapor is performed.

2020 ◽  
Author(s):  
Simon Jacobsen ◽  
Aksel Walløe Hansen

<p>The Weather Research and Forecasting (WRF) model fitted with the Fitch et al. (2012) scheme for parameterization of the effect of wind energy extraction is used to study the effects of very large wind farms on regional weather. Two real data cases have been run in a high spatial resolution (grid size 500 m). Both cases are characterized by a convective westerly flow. The inner model domain covers the North Sea and Denmark. The largest windfarm consists of 200.000 wind turbines each with a capacity of 8MW. The model is run for up to 12 hours with and without the wind farm. The impact on the regional weather of these very large wind farms are studied and presented. Furthermore, the effect of horizontal spacing between wind turbines is investigated. Significant impact on the regional weather from the very large wind farms was found. Horizontal wind speed changes occur up to 3500m above the surface. The precipitation pattern is greatly affected by the very large wind farms due to the enhanced mixing in the boundary layer. Increased precipitation occurs at the front? within the wind farm, thus leaving the airmass relatively dry downstream when it reaches the Danish coast, resulting in a decrease in precipitation here compared to the control run. The formation of a small low level jet is found above the very large wind farm. Furthermore, wake effects from individual wind turbines decrease the total power production. The wind speed in the real data cases are well above the speed of maximum power production of the wind turbines. Yet most of the 200.000 wind turbines are producing only 1MW due the wake effects. A simulation run with a wind farm of 50.000 8MW wind turbines was also run. This windfarm covers the same area as the previous one, but horizontal distance between wind turbines are 1000m instead of 500m. This configuration was found to produce a similar amount of power as the 200.000 configuration. However, the atmospheric impact on regional weather is smaller but still large with 50.000 wind turbines.</p>


Author(s):  
Oskar Wiśniewski ◽  
Wiesław Kozak ◽  
Maciej Wiśniewski

AbstractCOVID-19, which is a consequence of infection with the novel viral agent SARS-CoV-2, first identified in China (Hubei Province), has been declared a pandemic by the WHO. As of September 10, 2020, over 70,000 cases and over 2000 deaths have been recorded in Poland. Of the many factors contributing to the level of transmission of the virus, the weather appears to be significant. In this work, we analyze the impact of weather factors such as temperature, relative humidity, wind speed, and ground-level ozone concentration on the number of COVID-19 cases in Warsaw, Poland. The obtained results show an inverse correlation between ground-level ozone concentration and the daily number of COVID-19 cases.


2019 ◽  
Vol 12 (1) ◽  
pp. 34
Author(s):  
Long Wang ◽  
Cheng Chen ◽  
Tongguang Wang ◽  
Weibin Wang

A new simulation method for the aeroelastic response of wind turbines under typhoons is proposed. The mesoscale Weather Research and Forecasting (WRF) model was used to simulate a typhoon’s average wind speed field. The measured power spectrum and inverse Fourier transform method were coupled to simulate the pulsating wind speed field. Based on the modal method and beam theory, the wind turbine model was constructed, and the GH-BLADED commercial software package was used to calculate the aerodynamic load and aeroelastic response. The proposed method was applied to assess aeroelastic response characteristics of a commercial 6 MW offshore wind turbine under different wind speeds and direction variation patterns for the case study of typhoon Hagupit (2008), with a maximal wind speed of 230 km/h. The simulation results show that the typhoon’s average wind speed field and turbulence characteristics simulated by the proposed method are in good agreement with the measured values: Their difference in the main flow direction is only 1.7%. The scope of the wind turbine blade in the typhoon is significantly larger than under normal wind, while that under normal operation is higher than that under shutdown, even at low wind speeds. In addition, an abrupt change in wind direction has a significant impact on wind turbine response characteristics. Under normal operation, a sharp variation of the wind direction by 90 degrees in 6 s increases the wind turbine (WT) vibration scope by 27.9% in comparison with the case of permanent wind direction. In particular, the maximum deflection of the wind tower tip in the incoming flow direction reaches 28.4 m, which significantly exceeds the design standard safety threshold.


2019 ◽  
Vol 76 (11) ◽  
pp. 3529-3552
Author(s):  
Giuseppe Torri ◽  
David K. Adams ◽  
Huiqun Wang ◽  
Zhiming Kuang

Abstract Convective processes in the atmosphere over the Maritime Continent and their diurnal cycles have important repercussions for the circulations in the tropics and beyond. In this work, we present a new dataset of precipitable water vapor (PWV) obtained from the Sumatran GPS Array (SuGAr), a dense network of GPS stations principally for examining seismic and tectonic activity along the western coast of Sumatra and several offshore islands. The data provide an opportunity to examine the characteristics of convection over the area in greater detail than before. In particular, our results show that the diurnal cycle of PWV on Sumatra has a single late afternoon peak, while that offshore has both a midday and a nocturnal peak. The SuGAr data are in good agreement with GPS radio occultation data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission, as well as with imaging spectrometer data from the Ozone Measuring Instrument (OMI). A comparison between SuGAr and the NASA Water Vapor Project (NVAP), however, shows significant differences, most likely due to discrepancies in the temporal and spatial resolutions. To further understand the diurnal cycle contained in the SuGAr data, we explore the impact of the Madden–Julian oscillation (MJO) on the diurnal cycle with the aid of the Weather Research and Forecasting (WRF) Model. Results show that the daily mean and the amplitude of the diurnal cycle appear smaller during the suppressed phase relative to the developing/active MJO phase. Furthermore, the evening/nighttime peaks of PWV offshore appear later during the suppressed phase of the MJO compared to the active phase.


2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Alhassan A. Teyabeen ◽  
Fathi R. Akkari ◽  
Ali E. Jwaid ◽  
Ashraf Zaghwan ◽  
Rehab Abodelah

To assess the wind energy potential at any site, the wind power density should be estimated; it evaluates the wind resource and indicates the amount of available wind energy. The purpose of this study is to estimate the monthly and annual wind power density based on the Weibull distribution using wind speed data collected in Zwara, Libya during 2007. The wind date are measured at the three hub heights of 10m, 30m, and 50m above ground level, and recorded every 10 minutes. The analysis showed that the annual average wind speed are 4.51, 5.86, 6.26 m/s for the respective mentioned heights. The average annual wind power densities at the mentioned heights were 113.71, 204.19, 243.48 , respectively.


2020 ◽  
Author(s):  
Oskar Wisniewski ◽  
Wieslaw Kozak ◽  
Maciej Wisniewski

COVID-19, which is a consequence of infection with the novel viral agent SARS-CoV-2, first identified in China (Hubei Province), has been declared a pandemic by the WHO. As of September 10, 2020, over 70,000 cases and over 2,000 deaths have been recorded in Poland. Of the many factors contributing to the level of transmission of the virus, the weather appears to be significant. In this work we analyse the impact of weather factors such as temperature, relative humidity, wind speed and ground level ozone concentration on the number of COVID-19 cases in Warsaw, Poland. The obtained results show an inverse correlation between ground level ozone concentration and the daily number of COVID-19 cases.


2017 ◽  
Vol 10 (11) ◽  
pp. 4229-4244 ◽  
Author(s):  
Joseph C. Y. Lee ◽  
Julie K. Lundquist

Abstract. Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind–downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.


2017 ◽  
Author(s):  
Joseph C. Y. Lee ◽  
Julie K. Lundquist

Abstract. Forecasts of wind power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind turbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate that a vertical grid with nominally 12-m vertical resolution is necessary for reproducing the observed power production, with statistical significance. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed and low turbulence conditions. We also find the WFP performance is independent of atmospheric stability, the number of wind turbines per model grid cell, and the upwind-downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.


1999 ◽  
Vol 16 (2) ◽  
pp. 167-174 ◽  
Author(s):  
L. Valenziano ◽  
G. Dall'Oglio

AbstractPreliminary site testing results at Dome C (Antarctica) are presented, using both Automatic Weather Station (AWS) meteorological data (1986–1993) and Precipitable Water Vapour (PWV) measurements made by the authors. A comparison with the South Pole and other sites is made. The South Pole is a well established astrophysical observing site, where extremely good conditions are reported for a large fraction of time during the year. Dome C, where Italy and France are building a new scientific station, is a potential observing site in the millimetre and submillimetre range. AWS are operating at both sites and they have been continuously monitoring temperature, pressure and wind speed and direction for more than ten years. Site testing instruments are already operating at the South Pole (AASTO, Automated Astrophysical Site-Testing Observatory), while light experiments have been running at Dome C (APACHE, Antarctic Plateau Anisotropy CHasing Experiment) during summertime. A direct comparison between the two sites is planned in the near future, using the AASTO. The present analysis shows that the average wind speed is lower at Dome C (∼1 ms−1) than at the South Pole (∼2 ms−1), while temperature and PWV are comparable.


Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 360
Author(s):  
Michael Matějka ◽  
Kamil Láska ◽  
Klára Jeklová ◽  
Jiří Hošek

The Antarctic Peninsula belongs to the regions of the Earth that have seen the highest increase in air temperature in the past few decades. The warming is reflected in degradation of the cryospheric system. The impact of climate variability and interactions between the atmosphere and the cryosphere can be studied using numerical atmospheric models. In this study, the standard version of the Weather Research and Forecasting (WRF) model was validated on James Ross Island in the northern part of the Antarctic Peninsula. The aim of this study was to verify the WRF model output at 700 m horizontal resolution using air temperature, wind speed and wind direction observations from automatic weather stations on the Ulu Peninsula, the northernmost part of James Ross Island. Validation was carried out for two contrasting periods (summer and winter) in 2019/2020 to assess possible seasonal effects on model accuracy. Simulated air temperatures were in very good agreement with measurements (mean bias −1.7 °C to 1.4 °C). The exception was a strong air temperature inversion during two of the winter days when a significant positive bias occurred at the coastal and lower-altitude locations on the Ulu Peninsula. Further analysis of the WRF estimates showed a good skill in simulating near-surface wind speed with higher correlation coefficients in winter (0.81–0.93) than in summer (0.41–0.59). However, bias and RMSE for wind speed tended to be better in summer. The performance of three WRF boundary layer schemes (MYJ, MYNN, QNSE) was further evaluated. The QNSE scheme was generally more accurate than MYNN and MYJ, but the differences were quite small and varied with time and place. The MYNN and QNSE schemes tended to achieve better wind speed simulation quality than the MYJ scheme. The model successfully captured wind direction, showing only slight differences to the observed values. It was shown that at lower altitudes the performance of the model can vary greatly with time. The model results were more accurate during high wind speed southwestern flow, while the accuracy decreased under weak synoptic-scale forcing, accompanied by an occurrence of mesoscale atmospheric processes.


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