scholarly journals Temporal variation of wind speed and wind direction and interrelationship between air temperature and wind speed for different climatic seasons Northern State, Sudan

2021 ◽  
Vol 6 (4) ◽  
pp. 164-173
Author(s):  
Mohammed Ahmed Haj Alzubair ◽  
Motasim Hyder Abdelwahab
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Wind Direction ◽  
Climatic Data ◽  
Prevailing Wind Direction ◽  
Prevailing Direction ◽  
Simple Regression Analysis ◽  
The Mean ◽  
Northern State ◽  
Temperature Correlations

The research aims to study the temporal variability of wind speed and direction and their correlation with air temperature in different climatic seasons in Northern State, to produce broad data base on winds variability and interrelationship between air temperature and wind speed for different climatic seasons. Mean monthly and daily climatic data dating back to 2001(first season) and 2011(second season) were obtained from Karima meteorological station representing three different climatic seasons namely: April for summer, August for autumn and December for winter. Data were subjected to simple regression analysis, statistical analysis and computations were done by “Excel 2000”. The results showed that the wind speed varied widely during each month and day even within the same climatic season. In two seasons, the diurnal variation for different climatic seasons Apr., Aug. and Dec. was much lower than the monthly; due to the higher monthly variability of wind speed. The results also revealed that the prevailing direction of winds was generally northwards. The results of April in the first season are presented as an example; the mean daily wind speed (Va) ranged from 0.6 to 17m/s, with a mean of 7.2m/s, a STD of 4.3 and a CV of 60%. The daily mean data ranged from 5.4 (3hrs) to 8.2 (24hrs), with a mean of 7.2m/s, a STD of 1.1 and a CV of 15.3%.The prevailing wind direction decreases in the following order: N>NE=NNE>NNW. The monthly variability of the air temperature in the two seasons decreased in the following order: winter> summer> autumn. Significant, inversely proportional and cubic wind speed-temperature correlations in the two seasons for Aug. and Dec. were (P<0.05, r=0.362); (P<0.01, r= 0.488); (P<0.001, R=585) and (P<0.001, r= 0.679), respectively.

scholarly journals Spatiotemporal Characteristics of Near-Surface Wind in Shenzhen

2020 ◽  
Vol 12 (2) ◽  
pp. 739 ◽  
Author(s):  
Cheng Liu ◽  
Qinglan Li ◽  
Wei Zhao ◽  
Yuqing Wang ◽  
Riaz Ali ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Surface Wind ◽  
Prevailing Wind ◽  
Average Wind Speed ◽  
Near Surface ◽  
Average Wind ◽  
Prevailing Wind Direction ◽  
Seasonal Wind ◽  
The Mean

The spatiotemporal characteristics of near-surface wind in Shenzhen were investigated in this study by using hourly observations at 92 automatic weather stations (AWSs) from 2009 to 2018. The results show that during the past 10 years, most of the stations showed a decreasing trend in the annual mean of the 10 min average wind speed (avg-wind) and the mean of the 3 s average wind speed (gust wind). Over half of the decreasing trends at the stations were statistically significant (p < 0.05). Seasonally, the decrease in wind speed was the most severe in spring, followed by autumn, winter, and summer. The distribution of wind speed tends to be greater in the east and coastal areas for both avg-wind and gust wind. From September to March of the following year, the prevailing wind direction in Shenzhen was northerly, and from April to August, the prevailing wind direction was southerly. The seasonal wind speed distribution exhibited two different types, spring–summer type and autumn–winter type, which may be induced by their different prevailing wind directions. The analysis by the empirical orthogonal function (EOF) method confirmed the previous findings that the mean wind speed was decreasing in Shenzhen and that two different seasonal wind speed spatial distribution patterns existed. Such a study could provide references for wind forecasting and risk assessment in the study area.

Wind analysis at Ganja International Airport

2020 ◽  
Vol 61 (12) ◽  
pp. 162-165
Author(s):  
Ulker Faig Bayramova ◽  
Keyword(s):  
Wind Speed ◽  
Key Words ◽  
Wind Direction ◽  
Maximum Speed ◽  
Prevailing Wind ◽  
Wind Rose ◽  
International Airport ◽  
Wind Analysis ◽  
Prevailing Wind Direction ◽  
The Mean

The article reviews wind conditions at Ganja International Airport and specifies the maximum winds observed during the month and the direction of the winds. The direction of the mean, maximum wind speed of the prevailing wind was analyzed. Based on our analysis, we can see that the prevailing wind direction isnortheast and the maximum speed was recorded in March. Key words: wind, temperature, aviation, wind rose, visibility

Wind tunnel tests on the characteristics of wind fields over a simplified gorge

2016 ◽  
Vol 20 (10) ◽  
pp. 1599-1611 ◽  
Author(s):  
Peng Hu ◽  
Yongle Li ◽  
Yan Han ◽  
CS Cai ◽  
Guoji Xu
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Direction ◽  
Wind Field ◽  
Small Range ◽  
Wind Fields ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Characteristics ◽  
The Mean

Characteristics of wind fields over the gorge or valley terrains are becoming more and more important to the structural wind engineering. However, the studies on this topic are very limited. To obtain the fundamental characteristics information about the wind fields over a typical gorge terrain, a V-shaped simplified gorge, which was abstracted from some real deep-cutting gorges where long-span bridges usually straddle, was introduced in the present wind tunnel studies. Then, the wind characteristics including the mean wind speed, turbulence intensity, integral length scale, and the wind power spectrum over the simplified gorge were studied in a simulated atmospheric boundary layer. Furthermore, the effects of the oncoming wind field type and oncoming wind direction on these wind characteristics were also investigated. The results show that compared with the oncoming wind, the wind speeds at the gorge center become larger, but the turbulence intensities and the longitudinal integral length scales become smaller. Generally, the wind fields over the gorge terrain can be approximately divided into two layers, that is, the gorge inner layer and the gorge outer layer. The different oncoming wind field types have remarkable effects on the mean wind speed ratios near the ground. When the angle between the oncoming wind and the axis of the gorge is in a certain small range, such as smaller than 10°, the wind fields are very close to those associated with the wind direction of 0°. However, when the angle is in a larger range, such as larger than 20°, the wind fields in the gorge will significantly change. The research conclusions can provide some references for civil engineering practices regarding the characteristics of wind fields over the real gorge terrains.

scholarly journals The Large-eddy Observatory Voitsumra Experiment 2019 (LOVE19) with high-resolution, spatially-distributed observations of air temperature, wind speed, and wind direction from fiber-optic distributed sensing, towers, and ground-based remote sensing

2021 ◽  
Author(s):  
Karl Lapo ◽  
Anita Freundorfer ◽  
Antonia Fritz ◽  
Johann Schneider ◽  
Johannes Olesch ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Wind Speed ◽  
Air Temperature ◽  
Wind Direction ◽  
Fiber Optic ◽  
Layer Structure ◽  
Distributed Sensing ◽  
Near Surface ◽  
Large Eddy

Abstract. The weak-wind Stable Boundary Layer (wwSBL) is poorly described by theory and breaks basic assumptions necessary for observations of turbulence. Understanding the wwSBL requires distributed observations capable of separating between submeso and turbulent scales. To this end, we present the Large Eddy Observatory, Voitsumra Experiment 2019 (LOVE19) which featured 1350 m of fiber optic distributed sensing (FODS) of air temperature and wind speed, as well as an experimental wind direction method, at scales as fine as 1 s and 0.127 m in addition to a suite of point observations of turbulence and ground-based remote sensing. Additionally, flights with a fiber optic cable attached to a tethered balloon provide an unprecedented detailed view of the boundary layer structure with a resolution of 0.254 m and 10 s between 1–200 m height. Two examples are provided demonstrating the unique capabilities of the LOVE19 data for examining boundary layer processes: 1) FODS observations between 1m and ~200 m height during a period of gravity waves propagating across the entire boundary layer and 2) tracking a near-surface, transient submeso structure that causes an intermittent burst of turbulence. All data can be accessed at Zenodo through the DOI https://doi.org/10.5281/zenodo.4312976 (Lapo et al., 2020a).

scholarly journals Hoar crystal development and disappearance at Dome C, Antarctica: observation by near-infrared photography and passive microwave satellite

2013 ◽  
Vol 7 (1) ◽  
pp. 175-217 ◽  
Author(s):  
N. Champollion ◽  
G. Picard ◽  
L. Arnaud ◽  
E. Lefebvre ◽  
M. Fily
Keyword(s):  
Wind Speed ◽  
Satellite Data ◽  
Wind Direction ◽  
Near Infrared ◽  
Microwave Remote Sensing ◽  
Passive Microwave ◽  
Infrared Photography ◽  
Surface Mass ◽  
Prevailing Direction ◽  
Strong Winds

Abstract. Hoar crystals episodically cover the snow surface in Antarctica and affect the roughness and reflective properties of the air-snow interface. However, little is known about their evolution and the processes responsible for their development and disappearance despite a probable influence on the surface mass balance and energy budget. To investigate hoar evolution, we use continuous observations of the surface by in-situ near-infrared photography and by passive microwave remote sensing at Dome C in Antarctica. From the photography data, we retrieved a daily indicator of the presence/absence of hoar crystals using a texture analysis algorithm. The analysis of this 2-yr long time series shows that Dome C surface is covered almost half of the time by hoar. The development of hoar crystals takes a few days and seems to occur whatever the meteorological conditions. In contrast, the disappearance of hoar is rapid (a few hours) and coincident with either strong winds or with moderate winds associated with a change in wind direction from Southwest (the prevailing direction) to Southeast. From the microwave satellite data, we computed the polarisation ratio (i.e. horizontal over vertical polarised brightness temperatures), an indicator known to be sensitive to hoar in Greenland. Photography data and microwave polarisation ratio are correlated, i.e. high values of polarisation ratio which theoretically correspond to low snow density values near the surface are associated with the presence of hoar crystals in the photography data. Satellite data over nearly ten years (2002–2011) confirm that a strong decrease of the polarisation ratio (i.e. signature of hoar disappearance) is associated with an increase of wind speed or a change in wind direction from the prevailing direction. The photography data provides, in addition, evidence of interactions between hoar and snowfall. Further adding the combined influence of wind speed and wind direction results in a complex picture of the snow-atmosphere interactions in Antarctica which deserves further quantification and modelling.

Analysis of Atmospheric Pollutants in Bucharest in Correlation with Meteorological Parameters

2018 ◽  
Vol 69 (8) ◽  
pp. 2005-2011
Author(s):  
Marin Rusanescu ◽  
Carmen Otilia Rusanescu ◽  
Gigel Paraschiv
Keyword(s):  
Wind Speed ◽  
Sulfur Dioxide ◽  
Relative Humidity ◽  
Air Temperature ◽  
Wind Direction ◽  
Meteorological Parameters ◽  
Vertical Mixing ◽  
Average Concentration ◽  
Atmospheric Pollutants ◽  
Traffic Pollutants

In this paper we analyze the correlation between meteorological parameters (wind speed and direction, relative humidity, air temperature) and atmospheric pollutants in Bucharest during the cold period 26.02.2018-02.03.2018, which was based on the monitoring of the concentrations of nitrogen oxides, NO2, O3 and SO2 sulfur dioxide within 24 h and the occurrence of exceedances above the prescribed limit. It was found based on the results obtained that the wind direction influences not only the concentrations of pollutants but also the correlation between the pollutants. Traffic pollutants were at the highest concentration when the wind speed was low. We have found that the highest average concentration for NO2, NOx, NO, O3 occurred at 90% indicative humidity for vertical mixing of strong pollutants. Sulfur dioxide did not record exceeding over the limit standard in the analyzed period.

scholarly journals Wind turbine wake measurements with automatically adjusting scanning trajectories in a multi-Doppler lidar setup

2018 ◽  
Vol 11 (6) ◽  
pp. 3801-3814 ◽  
Author(s):  
Norman Wildmann ◽  
Nikola Vasiljevic ◽  
Thomas Gerz
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Direction ◽  
Sonic Anemometer ◽  
Prevailing Wind Direction ◽  
Wide Range ◽  
Novel Method ◽  
Approach Velocity ◽  
German Aerospace ◽  
First Time

Abstract. In the context of the Perdigão 2017 experiment, the German Aerospace Center (DLR) deployed three long-range scanning Doppler lidars with the dedicated purpose of investigating the wake of a single wind turbine at the experimental site. A novel method was tested for the first time to investigate wake properties with ground-based lidars over a wide range of wind directions. For this method, the three lidars, which were space- and time-synchronized using the WindScanner software, were programmed to measure with crossing beams at individual points up to 10 rotor diameters downstream of the wind turbine. Every half hour, the measurement points were adapted to the current wind direction to obtain a high availability of wake measurements in changing wind conditions. The linearly independent radial velocities where the lidar beams intersect allow the calculation of the wind vector at those points. Two approaches to estimating the prevailing wind direction were tested throughout the campaign. In the first approach, velocity azimuth display (VAD) scans of one of the lidars were used to calculate a 5 min average of wind speed and wind direction every half hour, whereas later in the experiment 5 min averages of sonic anemometer measurements of a meteorological mast close to the wind turbine became available in real time and were used for the scanning adjustment. Results of wind speed deficit measurements are presented for two measurement days with varying northwesterly winds, and it is evaluated how well the lidar beam intersection points match the actual wake location. The new method allowed wake measurements to be obtained over the whole measurement period, whereas a static scanning setup would only have captured short periods of wake occurrences.

scholarly journals High-Resolution Numerical Modelling of Near-Surface Atmospheric Fields in the Complex Terrain of James Ross Island, Antarctic Peninsula

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 360
Author(s):  
Michael Matějka ◽  
Kamil Láska ◽  
Klára Jeklová ◽  
Jiří Hošek
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Antarctic Peninsula ◽  
Wind Direction ◽  
Wrf Model ◽  
Lower Altitude ◽  
Near Surface ◽  
James Ross Island ◽  
The Antarctic ◽  
The Impact

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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