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.

IoT based weather station

Abstract: A weather station can be described as an instrument or device, which provides us with the information of the weather in our neighbouring environment. For example it can provide us with details about the surrounding temperature, barometric pressure, humidity, etc. Hence, this device basically senses the temperature, pressure, humidity, light intensity, rain value. There are various types of sensors present in the prototype, using which all the aforementioned parameters can be measured. It can be used to monitor the temperature or humidity of a particular room/place. With the help of temperature and humidity we can calculate other data parameters, such as the dew point. In addition to the above mentioned functionalities, we can monitor the light intensity of the place as well. We have also enabled to monitor the atmospheric pressure of the room. We can also monitor the rain value. The brain of the prototype is the ESP8266 based Wi-fi module Nodemcu (12E). Four sensors are connected to the NodeMCU namely temperature and humidity sensor(DHT11), pressure sensor(BMP180), raindrop module, and light dependent resistor(LDR). Whenever these values exceed a chosen threshold limit for each an SMS, an E-mail and a Tweet post is published alerting the owner of the appliance to take necessary measures.

Multilevel Assessment of the Impact of Rain on Drivers’ Behavior: Standardized Methodology and Empirical Analysis

Abstract: For all road managers, inclement weather events are a source of uncertainty that can affect traffic operations and safety. Regarding safety, various studies reveal significant effects of adverse weather conditions on the frequency and severity of crashes. Regarding mobility, because of a lack of data, there are few comprehensive studies, although the quantification of the effects of adverse weather on traffic represents the first step toward the development of weather-responsive traffic management strategies. This study deals with the analysis of the impact of rain on drivers' behavior and traffic operations. First, a generic methodology for assessing the effect of weather on traffic is proposed through a multilevel approach: from individual traffic data, the rain impact is assessed at a microscopic level (time headways, spacing). Next, the same data were used to extend the study to a mesoscopic and a macroscopic level. The mesoscopic level deals with the effects of rain on platoons, and the macroscopic level resides in the analysis of the impact of rain on the fundamental diagram enabling weather-responsive macroscopic traffic simulation. Second, following this approach, an empirical study is carried out from individual data collected on a French interurban motorway. Weather data were provided by a weather station located near the test site. The results exhibit a significant impact of rain on drivers' behavior and traffic operations, which increases with the intensity of rainfall.

Wireless weather station

Abstract: A wireless weather station for measuring a number of weather parameters over an extended time at a data collection location. The weather data can be transmitted to a remote location using substantially less total power than would be necessary to provide real time continuous transmission, yet provide the appearance of real time continuous transmission. A sensor assembly is positioned at the data collection location, powered by a battery that is recharged using a solar panel. A clock controlled microprocessing unit controls the data transducers to provide a data sampling rate and a data transmission interval. The data sampling rate for a parameter corresponds to the rate of change of the parameter. The microprocessor unit provides a plurality of data transmission intervals, with each of the data transmission intervals having a predetermined length of time corresponding to the power requirements of the sensor assembly and the current power status of the battery. In this manner, the data output that is provided to the remote receiving station appears to be real time continuous transmission but is actually delayed by the length of time of the data transmission interval. While the invention is particularly well suited for use with a weather station, it can also be used in any situation where power requirements need to be conserved and data needs to be transmitted to a remote location.

Using LCZ data to run an urban energy balance model

Abstract: In recent years a number of models have been developed that describe the urban surface and simulate its climatic effects. Their great advantage is that they can be applied in environments outside the cities in which they have been developed and evaluated. Thus, they may be applied to cities in the economically developing world, which are growing rapidly, and where the results of such models may have greatest impact with respect to informing planning decisions. However, data requirements, particularly for the more complex urban models, represent a major obstacle to their employment. Here, we examine the potential for running the Surface Urban Energy and Water Balance model (SUEWS) using readily obtained data. SUEWS was designed to simulate energy and water balance terms at a neighbourhood scale (⩾1 km2) and requires site-specific meteorological data and a detailed description of the surface. Here, its simulations are evaluated by comparison with measurements made over a seven month (approximately 3 seasons) period (April–October) at two flux tower sites (representing urban and suburban landscapes) in Dublin, Ireland. However, the main purpose of this work is to test the performance of the model under ‘ideal’ and ‘imperfect’ circumstances in relation to the input data required to run SUEWS. The ideal case uses detailed urban land cover data and meteorological data from the tower sites. The imperfect cases use parameters derived from the Local Climate Zone (LCZ) classification scheme and meteorological data from a standard weather station located beyond the urban area. For the period of record examined, the simulations show good agreement with the observations in both ideal and imperfect cases, suggesting that the model can be used with data that is more easily derived. The comparison also shows the importance of including vegetative cover and of the initial moisture state in simulating the urban energy budget.

Linking beach recreation to weather conditions: a case study in Zandvoort, Netherlands.

Abstract: Beach recreation is one of the most weather-sensitive leisure activities. However, there is a lack of scientific knowledge about how the different weather/climate variables influence beach visitation levels, and the role of other factors such as the hour of the day or the day of the week. This study, carried out during the summer of 2006, uses webcams in combination with real-time weather data as an innovative approach to study the relationship between weather and beach use in Zandvoort, a seaside town in The Netherlands. Over a period of 6 weeks, images were taken hourly and for every day, and then compared to the specific weather conditions from a nearby weather station to assess the relationship between beach visitation and atmospheric conditions. Precipitation has an overriding effect over other weather variables while high temperatures lead to higher beach visitation. These results indicate that webcam-based research is a promising field that can provide important information for coastal planning and climate change research.