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EN
The average daily values of wind speed and wind gust speed in the years 2001–2018 in Siedlce were analyzed. In the study area, the frequency of individual wind directions was determined and, according to criteria set by the Government Centre for Security, the frequency of hazards from damaging wind gusts was evaluated. The following wind gusts were considered: >20 m/s, 25 m/s and 35 m/s. It was found that, in the Siedlce area, the prevailing wind direction was west-south-westerly (WSW), and the average annual wind speed in the long-term study period was 2.99 m/s. March, April and May were the months when the highest speeds of maximum wind gusts (>35 m/s) were recorded. Extreme wind gusts the speed of which poses a hazard to the environment, national economy as well as human life and health, occurred in both the cold and warm seasons of the year.
EN
Urban regions are well known to be warmer than the outlying surrounding regions: this phenomenon is termed an Urban Heat Island (UHI). Depending upon its severity, an UHI can influence human health, the condition of urban vegetation, as well as air and water quality leading to a general decline in the living conditions of the affected urban environments and residents. Some studies have shown that prevailing weather conditions, like wind patterns, can influence UHI magnitudes. These studies suggest that wind speeds may be inversely related to UHI magnitude. However, long-term and high frequency weather and temperature measurements are exceedingly rare, so the exact nature of the relationship between wind speeds and directions as well as UHI magnitudes remain unknown. In order to address this problem, this study investigates how UHI magnitudes in five Australian cities affect wind speed and wind direction. The results of this study revealed that urban–non-urban temperature differences are most pronounced under calm weather conditions. The UHI intensity weakened as wind velocity increased: strong significant negative correlations were found between the mean UHI intensity and mean wind speed magnitudes. The results show that the greatest UHI intensities are recorded when wind is weak (less than 2 ms-1), while the lowest magnitudes are found when wind speeds exceed 6 ms-1. Further, the results show that the critical wind speed value, above which the strength of the UHI is considerably minimized, is around 4–5 ms-1. In addition, the study shows that wind direction in each city is a critical driver factor that determines the intensity of the UHI effect. When winds originate from dry environments, they favour high UHI intensities at all wind speeds, while the winds from the ocean side of coastal cities tend to cool urban regions, reducing UHI intensities or even promoting the urban cool island formation.
EN
This paper provides an overview of wind observations in Romania with historical data, particularly after the establishment of the national meteorological network in 1884. Data on wind directions and velocities is presented, focusing on a sample of fourteen cities including the capital Bucharest. The historical evolution of national zonation maps for wind pressure is shown. A statistical description of the maximum annual wind velocity data is also presented.
PL
Atrykuł przedstawia zbiór danych z obserwacji wiatru w Rumunii wraz z zapisami z poprzedniego stulecia, dokładnie zbieranymi od momentu ustanowienia krajowej sieci meteorologicznej w 1884 roku. Przedstawiono dane dotyczące kierunków i prędkości wiatru. Skupiono się na próbie czternastu miast, w tym stolicy – Bukaresztu. Pokazano historyczną ewolucję map krajowych stref obciążenia wiatrem. Przedstawiono również statystyczny opis danych dotyczących maksymalnej rocznej prędkości wiatru.
4
Content available Wind Power as a Renewable Energy Source
EN
The work presents a description of wind speed and direction in terms of using wind power as a renewable energy source. The wind power in Poland and at the Zawady EF was characterised. Observations were collected from 2002 to 2006 by an automatic meteorological station installed at the Zawady Experimental Farm (EF). Average monthly and yearly frequencies of winds blowing from individual directions were determined, and the average monthly wind speed was analysed. The most frequently recorded wind speed ranged from 2 to 4 m/s (light wind), and the least frequent winds blew at the speed of more than 10 m/s (strong wind). The cold season of the year saw winds blowing at the greatest speed (December, January and February), it being the lightest in the summer months (June, July and August). Wind rose analysis (2002–2006) revealed that at Zawady Experimental Farm, the westerly wind was the most frequent. A wind turbine has a limited capacity of wind power use, so only a small portion of energy supplied by wind may be converted into usable energy.
5
Content available remote Modelowanie wpływu warunków meteorologicznych na pracę siłowni wiatrowej
PL
Artykuł porusza problematykę modelowania wpływu parametrów meteorologicznych na pracę siłowni wiatrowej. W badaniach skupiono się na określeniu wpływu prędkości wiatru, jego podmuchów a także kierunku wiatru na ilość generowanej energii przez siłownię wiatrową. Z wykonanych badań wynika, że przy dużej zmienności warunków pogodowych to kierunek wiatru jest głównym czynnikiem decydującym o wielkości produkcji energii elektrycznej.
EN
This article addresses the problem of modeling the influence of meteorological parameters on the work of wind turbines. The study focused on determining the influence of wind speed, wind gusts and wind direction on the amount of energy generated by the wind turbine. The research shows that the conditions of high variability of weather conditions is the direction of wind is the main factor deciding the volume of electricity production.
PL
Elementem meteorologicznym bardzo istotnym z punktu widzenia mieszkańców miast jest wiatr, wpływający m.in. na temperaturę odczuwalną, zasięg miejskiej wyspy ciepła czy stężenie zanieczyszczeń w atmosferze. Na podstawie badań przeprowadzonych w Toruniu w 2012 roku stwierdzono duże deformacje kierunku oraz zmniejszenie prędkości wiatru w stosunku do terenów podmiejskich. Najmniejsze średnie prędkości wiatru odnotowano na terenach leśnych (0,2 m·s–1 ) oraz parkowych (0,6 m·s–1 ), a największe wystąpiły na obszarze o zabudowie wielorodzinnej (1,1 m·s–1 ). Analizie poddano również modyfi kacje kierunków wiatru. Największe wystąpiły na obszarze leśnym, a najmniejsze na obszarze o zabudowie zróżnicowanej.
EN
Wind is a particularly significant meteorological element from the point of view of the residents of cities, as it affects, for example, the subjective temperature, the extent of the Urban Heat Island or the concentration of atmospheric pollution. On the basis of observations carried out in Toruń in 2012, great deformations of wind directions and reduction of its speed were found as compared to suburban areas. The lowest values of annual mean speed were recorded in forest areas (0.2 m·s–1 ) and in parks (0.6 m·s–1 ). The highest winds, on the other hand, occurred in the area of multi-apartment buildings (1.1 m·s–1 ). Modifications of wind directions were also analysed and were found to occur to the greatest extent in forest areas, and in areas of diversified land development, the least.
EN
The article deals with the problem of ship’s ocean route programming. For masters during planning the ocean most convenient route lots of factors are very important such as among others: current, forecast weather, criteria and restriction, speed and fuel characteristic of ships on waves and wind and so on. These elements when are properly identify and adopted allow the master for making an effective ship’s course and speed decision. The aim of research is to show how the SPOS system is treated during the ocean’s ship route. 39 captains of PŻM ships during the year of 2014 answered on 9 questions of questionnaire which were concerned the degree of utilization of SPOS (Ship Performance Optimization System) during the operation of their ships. All the masters confirmed that they use of SPOS system as a browser weather, while only 25.6% of masters confirmed that they also use the SPOS system as a tool in planning the route. They also repeatedly pointed out, however, that SPOS has some of limitations such as not limited information about ice cover or tropical cyclones, etc. In conclusion, it can be assess that the SPOS system is satisfactorily used on ships as a browser forecast, but does not work well in planning the trip by navigators.
PL
W pracy przedstawiono główne czynniki wpływające na prędkość rozprzestrzeniania się pożaru pokrywy gleby. Szczególną uwagę poświęcono wpływowi zmienności kierunku wiatru, oraz wtórnej emisji promieniowania podczerwonego. Wskazano, ze w przypadku pożaru ścierniska, zmiana kierunku wiatru ma istotny wpływ na przyrosty powierzchni spalonej a, prędkość przemieszczania się frontu pożaru pozostaje bez zmian.
EN
The paper presents the main factors affecting the speed of soil cover fire spreading. Particular attention was paid to the influence of the variability of wind direction and secondary emission of infrared radiation. It was pointed out that in case of stubble fire, change of wind direction has a significant impact on growth of the burnt area, while the speed of the fire front remains unchanged.
PL
Praca charakteryzuje związki temperatury powietrza z kierunkami wiatru obserwowanymi na stacji w Hornsundzie w wieloleciu 1978-2009. Na stacji najczęściej wieje wiatr ze wschodu, od 38.3% w czerwcu do 59.4% wszystkich obserwacji w marcu. Subdominuje wiatr z NE (od 5.3% w lipcu do 30.9% w październiku). Przy wiatrach z N, NE i E średnia temperatura powietrza w okresie grudzień-marzec jest niższa od -10°C. Najcieplejsze są wiatry południowe (od -2.4°C w grudniu do 4.5°C w sierpniu). W okresie dnia polarnego (czerwiec-wrzesień) wieloletnie średnie miesięczne temperatury powietrza są dodatnie niezależnie od kierunku wiatru. Występujące na stacji w Hornsundzie wiatry cechują się dużą stałością struktury termicznej. W okresie chłodnym (listopad-maj) 'trwale' ciepłe są wiatry z sektora od W przez SW, S do SE, a 'trwale' zimne są wiatry z N, NE i E. Od listopada do stycznia największy wpływ na temperaturę powietrza w danym miesiącu wywierają wiatry z NE, a od lutego do maja - wiatry wschodnie.
EN
This work characterises correlations between air temperatures and the wind directions observed at the Hornsund station over the many-year period 1978-2009. The wind direction most frequently observed at this station is east and it is noted in 38.3% of all observations in June and in 59.4% in March. NE wind prevails (form 5.3% in July to 30.9% in October). When N, NE and E winds are observed then the mean air temperature in the period December- March is lower than -10°C (from -10°C with E winds in December to -13.3°C with NE winds in January). Warmest are S wind (from -2.4°C in December to 4.5°C in August). During the polar day (June -September) the many-year mean monthly air temperatures are positive regardless of wind direction and in the middle of summer they are characterized by similar values: in July from 4.0°C with winds from SW to 5.1°C with NE winds, in August from 3.5°C with N winds to 4.5°C S winds. Winds occurring at the Hornsund station are characterized by high stability of thermal structures. During the cold (November-May) winds from the sector by W, S to SE are 'permanently' warm and winds from the N, NE and E are 'permanently' cold. From November to January the biggest impact on air temperature in the month have winds from the NE and from February to May - easterly winds.
EN
The study assesses the accuracy of 24-hour weather forecasts on the Klaipeda (Lithuania) - Bayonne (France) navigational route emitted in NAVTEX system. There were analysed the parts of the forecasts concerning wind direction and force, visibility and precipitation. The verification was based on the real state of these factors, stated the next day on areas concerned. A high degree of forecast accuracy was stated in all five broadcasting stations of the NAVTEX system, particularly with reference to visibility and precipitation.
PL
Badania wykonano na podstawie 30-minutowych danych pochodzących z sieci automatycznego Regionalnego Systemu Monitoringu Powietrza w Województwie Katowickim, obejmujących lata 1994-1996. Analizie poddano wartości stężeń O3 oraz NOx, SO2, CO pochodzące ze stacji pomiarowych w Katowicach, Zabrzu, Kuźni Nieborowskiej i Olkuszu. W analizie porównano również wartości potencjału oksydacyjnego atmosfery Ox, zdefiniowanego jako suma stężeń O3 i NO2 wyrażonych w μg/m3: COx=CO3+CNO2. W tym równaniu stężenie NO2 przeliczono na stężenie ozonu niezbędnego do powstania tej ilości NO2 w reakcji: NO + O3 → NO2 + O2. Dla każdej stacji pomiarowej obliczono średnie wartości stężeń: O3, Ox, NOx, SO2 i CO w 12 sektorach kierunkowych wiatru. Porównano wartości stężeń zanieczyszczeń otrzymanych dla terenów silnie zurbanizowanych (Katowice, Zabrze) z wartościami uzyskanymi dla terenów oddalonych od silnych lokalnych źródeł zanieczyszczeń (Olkusz, Kuźnia Nieborowska). Ze względu na różnicę charakteru zanieczyszczeń sezonu grzewczego i niegrzewczego sporządzono osobne wykresy kołowe dla poszczególnych stacji pomiarowych w obu tych sezonach.
EN
Studies were performed based on data derived from Regional Air Monitoring System in Katowice, Poland, from the years 1994-1996. The concentration values of O3, NOx, SO2, CO from the measuring sites in Katowice, Zabrze, Kuźnia Nieborowska and Olkusz were analysed. In these studies the concentration of oxidants Ox type were taken into consideration as well. Concentration Ox was defined as the sum of concentrations of O3 and NO2 in μg /m3: COx=Co3+CNO2. In that formula NO2 concentration was recalculated on ozone concentration consumed to create the same NO2 amount in the reaction: NO + O3 → NO2 + O2. Average values of O3, Ox, NOx, SO2 and CO concentrations in 12 wind direction sectors were counted for each measuring station. The pollutants concentration values for typical urban areas (Katowice, Zabrze) and nonurban ones (Olkusz, Kuźnia Nieborowska) were compared. Different circle diagrams for heating and nonheating seasons were showed for the monitoring stations specified above.
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