Weather station

About: Weather station is a research topic. Over the lifetime, 1789 publications have been published within this topic receiving 42864 citations. The topic is also known as: meteorological station & meteorological observation post.

Vertical Precipitation Estimation Using Microwave Links in Conjunction with Weather Radar

Abstract: When monitoring rain rates by weather radar in semi-arid regions and when measuring precipitation at an arid region; precipitation particles, rain, or snowflakes may evaporate before reaching the ground. This evaporation is regarded as the Virga phenomenon and may cause a false representation of the precipitation amount that actually reaches the ground. The Virga occurs naturally when the air below the cloud is relatively dry, and continues until humidity below the base of the cloud is high enough to decrease the evaporation. This paper suggests a method of combining near ground Commercial Microwave Links (CMLs) attenuation measurements, in conjunction with data from several weather radar beams, observing different heights, in order to produce estimates of the vertical profile of the rain-rate values and of the Cloud Base level (ClB). We propose an estimation method and demonstrate it using real-data measurements of two major storm events in the dead-sea area. We verify the validity of the estimation near ground by comparing the results with Rain Gauges’ (RGs) actual measurements in addition to comparing the estimated ClB with real ClB observations of a nearby weather station. While the storm events selected indeed show great evaporation, the suggested method provides excellent results, with a correlation of up to 0.9615, when correlated with real measurements of RGs of two storms from 2014 to 2016.

Updated Typical Weather Years for the Energy Simulation of Buildings in Mediterranean Climate. A Case Study for Sicily

Abstract: Building energy simulations are normally run through Typical Weather Years (TWYs) that reflect the average trend of local long-term weather data. This paper presents a research aimed at generating updated typical weather files for the city of Catania (Italy), based on 18 years of records (2002–2019) from a local weather station. The paper reports on the statistical analysis of the main recorded variables, and discusses the difference with the data included in a weather file currently available for the same location based on measurements taken before the 1970s but still used in dynamic energy simulation tools. The discussion also includes a further weather file, made available by the Italian Thermotechnical Committee (CTI) in 2015 and built upon the data registered by the same weather station but covering a much shorter period. Three new TWYs are then developed starting from the recent data, according to well-established procedures reported by ASHRAE and ISO standards. The paper discusses the influence of the updated TWYs on the results of building energy simulations for a typical residential building, showing that the cooling and heating demand can differ by 50% or even 65% from the simulations based on the outdated weather file.

Wind Resource Assessment in the City of N'djamena in Chad

Abstract: The aim of this study is to evaluate the wind energy potential of the city of N'Djamena, and to evaluate of the annual energy produced at an altitude of 100 m by simulating wind data using the wind speeds data collected at N'Djamena airport’s weather station for a twelve months period. In this perspective, we start with the description of the site through the determination of parameters related to the wind, the mathematical modeling of the frequency distribution of the wind: Weibull distribution and processing and numerical simulation of the actual wind data collected on a selected site of the city of N’Djamena. We then estimate its wind potential, the prediction of the electrical energy production and, determine the direction of the wind on the site. We conduct an analysis of wind turbulence considering different factors such as surrounding obstacles near the measurement tower of the airport in N'Djamena, topography, roughness of the site and choice of wind mill. As a result, the installation of a wind farm of 10 wind mill Vestas V80 / 1.8 MW at 100 meters would produce 50,420 MWh of energy.

Using climate change models to assess the probability of weather extremes events: a local scale study based on the generalized extreme value distribution

Abstract: Regional climate models (e.g. Eta) nested to global climate models (e.g. HadGEM2-ES and MIROC5) have been used to assess potential impacts of climate change at regional scales. This study used the generalized extreme value distribution (GEV) to evaluate the ability of two nested models (Eta-HadGEM2-ES and Eta-MIROC5) to assess the probability of daily extremes of air temperature and precipitation in the location of Campinas, state of Sao Paulo, Brazil. Within a control run (1961-2005), correction factors based on the GEV parameters have been proposed to approach the distributions generated from the models to those built from the weather station of Campinas. Both models were also used to estimate the probability of daily extremes of air temperature (maximum and minimum) and precipitation for the 2041-2070 period. Two concentration paths of greenhouse gases (RCP 4.5 and 8.5) have been considered. Although both models project changes to warmer conditions, the responses of Eta-Hadgem2-ES to both RCPs are significantly larger than that of Eta-Miroc5. While Eta-Hadgem2-ES suggests the location of Campinas will be free from agronomic frost events, Eta-Miroc5 indicates that air temperature values equal to or lower than 5 and 2 °C are expected to present a cumulative probabilityof ~0.20 and ~0.05, respectively (RCP 8.5). Moreover, while the Eta-Miroc5 projected a reduction in the extreme-precipitation amounts, the Eta-Hadgem2-ES projected implausible large daily precipitation amounts. The Eta-Miroc5 performed better than the Eta-Hadgem2-ES for assessing the probability of air temperature and precipitation in Campinas. This latter statement holds particularly true for daily-extreme precipitation data.

Performance sensitivity of a wind farm power curve model to different signals of the input layer of ANNs: Case studies in the Canary Islands

Abstract: Improving the estimation of the power output of a wind farm enables greater integration of this type of energy source in electrical systems. The development of accurate models that represent the real operation of a wind farm is one way to attain this objective. A wind farm power curve model is proposed in this paper which is developed using artificial neural networks, and a study is undertaken of the influence on model performance when parameters such as the meteorological conditions (wind speed and direction) of areas other than the wind farm location are added as signals of the input layer of the neural network. Using such information could be of interest, either to study possible improvements that could be obtained in the performance of the original model, which uses exclusively the meteorological conditions of the area where the wind farm is located, or simply because no reliable meteorological data for the area of the wind farm are available. In the study developed it is deduced that the incorporation of meteorological data from an additional weather station other than that of the wind farm site can improve by up to 17.6% the performance of the original model.