Showing papers on "Weather station published in 2012"

Development of a Combined Drought Indicator to detect agricultural drought in Europe

Abstract: . This study proposes a drought indicator that combines the Standardized Precipitation Index (SPI), the anomalies of soil moisture and the anomalies of the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). Computed at the European level, the Combined Drought Indicator (CDI) gives a synthetic and synoptic overview of the drought situation using a classification scheme. Derived from the integration of the three individual indices, this classification scheme is composed of three warning levels: "watch" when a relevant precipitation shortage is observed, "warning" when this precipitation shortage translates into a soil moisture anomaly, and "alert" when these two conditions are accompanied by an anomaly in the vegetation condition. The design of the CDI includes the study of the relationship between the three individual indices. To achieve this, the SPI-3 (3-month SPI) was computed using the precipitation data obtained from a set of weather stations located in different agricultural areas of Europe, while the soil moisture and fAPAR data were extracted from the pixels of the respective grids surrounding these stations. The CDI is assessed for the main drought episodes of Europe between 2000 and 2011, using reported data from different sources, such as the EM-DAT Emergency Events Database and Eurostat annual yield estimates. The capability of the CDI to serve for drought early warning is evaluated as well as its robustness against false alarms. The indicator has been spatially implemented for the entire continent using different information layers of the European Drought Observatory. These layers correspond to SPI-3 grids derived from interpolated weather station precipitation data, anomalies of fAPAR from the MERIS Global Vegetation Index and anomalies of soil moisture obtained using the LISFLOOD distributed hydrological model. Maps of the CDI obtained for the European drought event in spring 2011 are shown and discussed, evaluating its operational applicability. To conclude, the main limitations of the indicator are presented and possible avenues for improvement are discussed.

On the use of weather data in ecological studies along altitudinal and latitudinal gradients

Abstract: Global warming has created a need for studies along climatic gradients to assess the effects of temperature on ecological processes. Altitudinal and latitudinal gradients are often used as such, usually in combination with air temperature data from the closest weather station recorded at 1.52 m above the ground. However, many ecological processes occur in, at, or right above the soil surface. To evaluate how representative the commonly used weather station data are for the microclimate relevant for soil surface biota, we compared weather station temperatures for an altitudinal (500900 m a.s.l.) and a latitudinal gradient (4968 degrees N) with data obtained by temperature sensors placed right below the soil surface at five sites along these gradients. The mean annual temperatures obtained from weather stations and adjusted using a lapse rate of -5.5 degrees C km-1 were between 3.8 degrees C lower and 1.6 degrees C higher than those recorded by the temperature sensors at the soil surface, depending on the position along the gradients. The monthly mean temperatures were up to 10 degrees C warmer or 5 degrees C colder at the soil surface. The within-site variation in accumulated temperature was as high as would be expected from a 300 m change in altitude or from a 4 degrees change in latitude or a climate change scenario corresponding to warming of 1.63.8 degrees C. Thus, these differences introduced by the decoupling are significant from a climate change perspective, and the results demonstrate the need for incorporating microclimatic variation when conducting studies along altitudinal or latitudinal gradients. We emphasize the need for using relevant temperature data in climate impact studies and further call for more studies describing the soil surface microclimate, which is crucial for much of the biota.

Weather and child health in rural Nigeria

Abstract: The effect of weather shocks on children's anthropometrics is investigated using the two most recent rounds of the Nigeria Demographic and Health Survey. For this purpose, climate data for each survey cluster are interpolated using daily weather-station records from the national network. The findings reveal that rainfall shocks have a statistically significant and robust impact on child health in the short run for both weight-for-height and height-for-age, and the incidence of diarrhea. The impacts of weather shocks on health are of considerable magnitude; however, children seem to catch up with their cohort rapidly after experiencing a shock. The paper does not find any evidence of nonlinear impacts of weather variability on children's health, suggesting that a moderate increase in future rainfall variability is not likely to bring additional health costs. Finally, it appears that the impact of these shocks is the same for young boys and girls, which suggests that there is no gender-based discrimination in the allocation of resources within households.

Weather and mortality: a 10 year retrospective analysis of the Nouna Health and Demographic Surveillance System, Burkina Faso

Abstract: Background: A growing body of evidence points to the emission of greenhouse gases from human activity as a key factor in climate change. This in turn affects human health and wellbeing through consequential changes in weather extremes. At present, little is known about the effects of weather on the health of sub-Saharan African populations, as well as the related anticipated effects of climate change partly due to scarcity of good quality data. We aimed to study the association between weather patterns and daily mortality in the Nouna Health and Demographic Surveillance System (HDSS) area during 1999-2009. Methods: Meteorological data were obtained from a nearby weather station in the Nouna HDSS area and linked to mortality data on a daily basis. Time series Poisson regression models were established to estimate the association between the lags of weather and daily population-level mortality, adjusting for time trends. The analyses were stratified by age and sex to study differential population susceptibility. Results: We found profound associations between higher temperature and daily mortality in the Nouna HDSS, Burkina Faso. The short-term direct heat effect was particularly strong on the under-five child mortality rate. We also found independent coherent effects and strong associations between rainfall events and daily mortality, particularly in elderly populations. Conclusion: Mortality patterns in the Nouna HDSS appear to be closely related to weather conditions. Further investigation on cause-specific mortality, as well as on vulnerability and susceptibility is required. Studies on local adaptation and mitigation measures to avoid health impacts from weather and climate change is also needed to reduce negative effects from weather and climate change on population health in rural areas of the sub-Saharan Africa. Keywords: weather; mortality; Burkina Faso; sub-Saharan Africa; Nouna HDSS; lag; time series; precipitation; temperature; climate change; vulnerability; susceptibility (Published: 23 November 2012) Citation: Glob Health Action 2012, 5 : 19078 - http://dx.doi.org/10.3402/gha.v5i0.19078

Ground–atmosphere interaction modelling for long-term prediction of soil moisture and temperature

Abstract: Land surface and subsurface variables, such as soil moisture–suction and temperature, are among the most important components to study the behaviour of expansive soil, geothermal energy, and climate change. A more accurate and long-term series of soil moisture and temperature prediction, due to ground–atmosphere interaction, is very important for real-time drought monitoring for understanding and improving the behaviour of soil, buried structures, and climate prediction. In this study, ground–atmosphere interaction is numerically modelled using Vadose/W software for two instrumented sites in Melbourne, Australia. Soil moisture and temperature down to 2 m depth were monitored over 2 years at discrete locations and the meteorological variables including air temperature, air humidity, wind speed, precipitation, and solar radiation were measured from a weather station installed at the sites. Further, laboratory and field tests were performed to establish initial conditions and soil characteristics such as the...

Irrigation controller with weather station

Abstract: An irrigation control module is described that adjusts a watering schedule for a connected irrigation controller based on weather data provided by a local weather station. The irrigation control module can add additional weather-based irrigation schedule adjustments to an irrigation controller that may otherwise lack the hardware (e.g., wireless transmitter, sufficient memory) and software (e.g., evapotranspiration algorithms) to store and interpret weather data from a weather station.

The weather observer's handbook

Abstract: The Weather Observer's Handbook provides a comprehensive, practical and independent guide to all aspects of making weather observations. Automatic weather stations today form the mainstay of both amateur and professional weather observing networks around the world and yet – prior to this book – there existed no independent guide to their selection and use. Traditional and modern weather instruments are covered, including how best to choose and to site a weather station, how to get the best out of your equipment, how to store and analyse your records and how to share your observations with other people and across the Internet. From amateur observers looking for help in choosing their first weather instruments on a tight budget to professional observers looking for a comprehensive and up-to-date guide covering World Meteorological Organization recommendations on observing methods and practices, all will welcome this handbook.

The algae raceway integrated design for optimal temperature management

Abstract: The Algae Raceway Integrated Design (ARID) minimizes diurnal and seasonal temperature fluctuations and maintains temperature within the optimal range, between 15 and 30 °C, during day and night and during all seasons in Tucson, Arizona. The system regulates temperature by adjusting the water surface area and thus regulates the energy transfer to and from the atmosphere and raceway. A temperature model of the raceway was developed and was based on a standardized energy balance model for agricultural crops. The model includes the Penman–Monteith evapotranspiration equation, long wave radiation, short wave radiation, sensible heat transfer (convection) and soil heat flux. The temperature model predicted minimum daily raceway water temperature within 1–2 °C over a range of atmospheric conditions during a 21 day algae growth experiment. Because the model is based on standard agricultural weather station data, it can be used in any location that is in proximity to an agricultural weather station. The model automatically downloads data from any weather station in Arizona, allows specification of various cover and liner conditions, specifies the timing of circulation, and has a dynamic simulation mode.

Experimental and casework validation of ambient temperature corrections in forensic entomology.

Abstract: This paper expands on Archer (J Forensic Sci 49, 2004, 553), examining additional factors affecting ambient temperature correction of weather station data in forensic entomology. Sixteen hypothetical body discovery sites (BDSs) in Victoria and New South Wales (Australia), both in autumn and in summer, were compared to test whether the accuracy of correlation was affected by (i) length of correlation period; (ii) distance between BDS and weather station; and (iii) periodicity of ambient temperature measurements. The accuracy of correlations in data sets from real Victorian and NSW forensic entomology cases was also examined. Correlations increased weather data accuracy in all experiments, but significant differences in accuracy were found only between periodicity treatments. We found that a >5°C difference between average values of body in situ and correlation period weather station data was predictive of correlations that decreased the accuracy of ambient temperatures estimated using correlation. Practitioners should inspect their weather data sets for such differences.

Weather conditions and voter turnout in Dutch national parliament elections, 1971-2010.

Abstract: While conventional wisdom assumes that inclement weather on election day reduces voter turnout, there is remarkably little evidence available to support truth to such belief. This paper examines the effects of temperature, sunshine duration and rainfall on voter turnout in 13 Dutch national parliament elections held from 1971 to 2010. It merges the election results from over 400 municipalities with election-day weather data drawn from the nearest weather station. We find that the weather parameters indeed affect voter turnout. Election-day rainfall of roughly 25 mm (1 inch) reduces turnout by a rate of one percent, whereas a 10-degree-Celsius increase in temperature correlates with an increase of almost one percent in overall turnout. One hundred percent sunshine corresponds to a one and a half percent greater voter turnout compared to zero sunshine.

Modeling and investigation of the wind resource in the gulf of Tunis, Tunisia

Abstract: The development of wind energy conversion systems becomes one of the most important aims of many developing countries such as Tunisia. This is due to the reduction in wind turbine costs, and fossil fuel atmospheric pollution. The evaluation of wind power potential is necessary to estimate wind resource and therefore conduct the suitable decisions for the wind power generation projects, technical and economical feasibility. The presented work in this paper was to investigate the potential of wind resource in the Gulf of Tunis in Tunisia. The hourly mean wind speed and wind direction with a 10-min time step provided by the NRG (National Resources Group) weather station were used to analyze the wind speed characteristics and the wind power potential. Weibull parameters are estimated based on the most frequently used methods in which their accuracy was compared based on different goodness of fit tests. Those wind characteristics are required to give the picture of wind potential distribution in the Gulf of Tunis.

Injury Severity of Multivehicle Crash in Rainy Weather

Abstract: As part of the Wisconsin road weather safety initiative, the objective of this study was to microscopically assess the factor effects on the severities of multivehicle-involved crashes on high-speed roadways during rainfall utilizing a sequential logistic regression approach. Research began by considering interstate freeways in Wisconsin. Weather-related factors considered in the research included estimated rainfall intensity, water film depth, temperature, wind speed and direction, and the car-following distance at the time of crash. With each crash observation, weather data were obtained through the three most adjacent weather station locations and the inverse-squared distance method. Nonweather factors such as roadway geometries, traffic conditions, collision manners, vehicle types, and driver and temporal attributes were also considered. Sequential logistic regression was applied to predict multivehicle crash severities in ascending (forward) and descending (backward) orders, respectively. The final model was selected on the basis of a combination of model performance, parameter significance, and prediction accuracies. The backward sequential logistic regression model produced the most desirable results for predicting crash severities in rainy weather in which deficiency of car following, wind speed, the first harmful spot, vehicle types, temporal, and at-fault driver-related actions at the crash moment were found to be statistically significant. These findings can be used to provide quantitative support of road weather safety improvements via weather warning systems, highway infrastructure enhancements, and traffic management.

Water Saving-Irrigation Automatic Agricultural Controller

Abstract: For weather monitoring system and irrigation controller, we need to measure different parameters i.e. Atmospheric temperature, Humidity, Wind speed, Wind direction, Radiation, Soil temperature, Sunshine and Rain fall etc. The key objective of this project is to report on a developed indigenous low cost time based microcontroller based irrigation scheduler who performs user defined functions and outputs com mands to derive appropriate actuators (relay, solenoid valves, motor). A soil moisture sensor was modeled, simulated and tested for achieving, with low-cost, accurate and reliable measurements. A low-cost high-performance and small temperature sensor is used, with the same PCB circuit it can measure humidity also. The tipping bucket rain gauge is used to measure rain fall. After a pre-set amount of precipitation falls, the lever tips, dumping the collected water and sending an electrical signal. An anemometer is a device used for measuring wind speed, and is a common weather station instrument. Hence current research focuses on precision agriculture, soil conservation and crop irrigation scheduling and water quantity control for increasing water use efficiency. There is a need to develop new indigenous irrigation controller to improve farm productivity and input use efficiency of water and other nutrients. This system presents the design and development of Irrigation controller System built around PIC16F877A microcontroller. The system consists of microcontroller, peripherals including RTC, LCD and driver circuit relay to switch on/off a motor.

Sensitivity of grass- and alfalfa-reference evapotranspiration to weather station sensor accuracy

Abstract: A sensitivity analysis was conducted to determine the relative effects of measurement errors in climate data input parameters on the accuracy of calculated reference crop evapotranspiration (ET) using the ASCE-EWRI Standardized Reference ET Equation. Data for the period of 1995 to 2008 from an automated weather station located at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas were used for the analysis. Results indicated that grass (ETos) and alfalfa (ETrs) reference crop ET were most sensitive to measurement errors in wind speed and air temperature followed by incoming shortwave (solar) radiation, and that data sensitivity was greater during the mid-summer growing season in this semi-arid region. Given the highly advective conditions of the Texas High Plains and the relative sensitivity of ET calculations to errors in wind speed, special care is recommended in siting, sensor placement, and sensor maintenance for agriculturally-based ET weather stations.

The association of meteorological factors and mortality in rural Bangladesh, 1983-2009

Abstract: Introduction: While the association of weather and mortality has been well documented for moderate climate zones, little is known about sub-tropical zones, particularly Bangladesh. This study aims to assess the shortterm relationship of temperature and rainfall on daily mortality after controlling for seasonality and timetrends. The study used data from Matlab, Bangladesh, where a rigorous health and demographic surveillance system (HDSS) has been operational since 1966. Material and methods: Matlab HDSS data on mortality and population for the period 1983-2009 were used. Weather data for the same period were obtained from a nearby government weather station. Time series Poisson regression with cubic spline functions was applied allowing for lagged effects of weather and extreme weather events on mortality, and controlling for time trends and seasonal patterns. Analysis was carried out using R statistical software. Results: Both temperature and rainfall showed strong seasonal patterns, explaining a significant part of mortality in all age groups. After adjusting for seasonality and trend, mortality and temperature show a Ushaped pattern; below a temperature of around 29°C, a decrease in temperature resulted in an increase in mortality, whereas above 29°C, increased temperature resulted in increased mortality. The strongest negative mortality temperature association was observed in the elderly (5.4% increase with every 1°C decrease in temperature at temperatures below 23°C), and the opposite trendwas observed in the age groups 1-4 and 5-19 years old. At aggregate level, the rainfallmortality association is statistically weak. However in the age group 5-19, a 0.6% increase in mortality per 1 mm additional rainfall was found, at rainfall levels over 100 mm per day. Multivariate analysis showed high mortality risks for women aged 20-59 years of age during cyclone episodes. Discussion: Weather and extreme weather were associated with mortality with differential impacts in age and sex sub-groups. Further studies should investigate these findings more closely and develop policy recommendations targeted at improving public health and protecting population groups susceptible to environmental stressors. Keywords: climate change; mortality; Matlab (Published: 23 November 2012) Citation: Glob Health Action 2012, 5 : 19063 - http://dx.doi.org//10.3402/gha.v5i0.19063

Instability indices and forecasting thunderstorms: the case of 30 April 2009

Abstract: . In this paper, one meteorological case study for two Iranian airports are presented. Attempts have been made to study the predefined threshold amounts of some instability indices such as vertical velocity and relative humidity. Two important output variables from a numerical weather prediction model have been used to survey thunderstorms. The climatological state of thunder days in Iran has been determined to aid in choosing the airports for the case studies. The synoptic pattern, atmospheric thermodynamics and output from a numerical weather prediction model have been studied to evaluate the occurrence of storms and to verify the threshold instability indices that are based on Gordon and Albert (2000) and Miller (1972). Using data from the Statistics and Data Center of the Iran Meteorological Organization, 195 synoptic stations were used to study the climatological pattern of thunderstorm days in Iran during a 15-yr period (1991–2005). Synoptic weather maps and thermodynamic diagrams have been drawn using data from synoptic stations and radiosonde data. A 15-km resolution version of the WRF numerical model has been implemented for the Middle East region with the assistance of global data from University Corporation for Atmospheric Research (UCAR). The Tabriz airport weather station has been selected for further study due to its high frequency of thunderstorms (more than 35 thunderstorm days per year) and the existence of an upper air station. Despite the fact that storms occur less often at the Tehran weather station, the station has been chosen as the second case study site due to its large amount of air traffic. Using these two case studies (Tehran at 00:00 UTC, 31 April 2009 and Tabriz at 12:00 UTC, 31 April 2009), the results of this research show that the threshold amounts of 30 °C for KI, −2 °C for LI and −3 °C for SI suggests the occurrence and non-occurrence of thunderstorms at the Tehran and Tabriz stations, respectively. The WRF model output of vertical velocity and relative humidity are the two most important indices for examining storm occurrence, and they have a numerical threshold of 1 m s−1 and 80%, respectively. These results are comparable to other studies that have examined thunderstorm occurrence.

Comparison of MODIS land surface temperature and ground-based observed air temperature in complex topography

Abstract: Near-ground air temperature T a and land surface temperature T s are important parameters in studies related to variations in hydrology, biodiversity and climate change. However, complicated mountainous terrain tends to hinder observations in such areas. The scarce observations from mountainous areas can be augmented with data from a 1 km high spatial resolution data set. This data set is obtained from the land surface temperature element of the Moderate Resolution Imaging Spectroradiometer MODIS instruments installed on the Aqua and Terra Earth observation satellites from NASA. This study used regional monthly mean T a data for Taiwan as a reference to assess the monthly mean T s data set. The results showed that the two sets of data had correlation coefficients of 0.91–0.96, and the standard deviations of the differences between the two sets were 1.25–1.77°C. These results could serve as a reference for research related to climate and ecology. Further analysis indicated some possible sources of bias between T s and T a: 1 the significant influences caused by soil moisture between wet and dry seasons; 2 the difference between ground-based weather station elevation and 1 km grid-averaged elevation; and 3 interaction among the satellite view, solar zenith angle and terrain gradient. When the T s product V005 is used directly in ecological study and application, it is essential to have a clear knowledge of the bias and its possible causes.

The Association of Trail Use With Weather-Related Factors on an Urban Greenway

Abstract: Purpose:To study the association between weather-related measures and objectively measured trail use across 3 seasons. Background:Weather has been reported as a barrier to outdoor physical activity (PA), but previous studies have explained only a small amount of the variance in PA using weather-related measures. Methods:The dependent variable of this study was trail use measured as mean hourly trail counts by an infrared trail counter located on a greenway. Each trail count represents 1 person breaking the infrared beam of the trail counter. Two sources of weather-related measures were obtained by a site-specific weather station and a public domain weather source. Results:Temperature, relative humidity, and precipitation were significantly correlated with trail counts recorded during daylight hours. More precise hourly weather-related measures explained 42% of the variance in trail counts, regardless of the weather data source with temperature alone explaining 18% of the variance in trail counts. After co...

Quality of Mobile Air Temperature and Atmospheric Pressure Observations from the 2010 Development Test Environment Experiment

Abstract: The 2010 Development Test Environment Experiment (DTE10) took place from 28 January to 29 March 2010 in the Detroit, Michigan, metropolitan area for the purposes of collecting and evaluating mobile data from vehicles. To examine the quality of these data, over 239 000 air temperature and atmospheric pressure observations were obtained from nine vehicles and were compared with a weather station set up at the testing site.TheobservationsfromthevehicleswerefirstrunthroughtheNCARVehicleDataTranslator (VDT). As part of the VDT, quality-checking (QCh) tests were applied; pass rates from these tests were examined and were stratified by meteorological and nonmeteorological factors. Statistics were then calculated for air temperature and atmospheric pressure in comparison with the weather station, and the effects of different meteorological and nonmeteorological factors on the statistics were examined. Overall, temperature measurements showed consistent agreement with the weather station, and there was little impact from the QCh process or stratifications—a result that demonstrated the feasibility of collecting mobile temperature observations from vehicles. Atmospheric pressure observations were less well matched with surface validation, the degree of which varied with the make and model of vehicle. Therefore, more work must be done to improve the quality of these observations if atmospheric pressure from vehicles is to be useful.

Performance analysis of a hybrid photovoltaic thermal double pass air collector using ANN

Abstract: This paper presents the performance analysis of semi transparent hybrid photovoltaic single pass air collector considering four weather conditions (a, b, c and d type) of New Delhi weather station of India using ANN technique. The MATLAB 7.1 neural networks toolbox has been used for defining and training of ANN for calculations of thermal, electrical, overall thermal energy and overall exergy. The ANN models use ambient temperature, number of clear days, global and diffuse radiation as input parameters. The transfer function, neural network configuration and learning parameters have been selected based on highest convergence during training and testing of networks. About 3000 sets of data from four weather stations (Bangalore, Mumbai, Srinagar, and Jodhpur) have been given as input for training and data of the fifth weather station (New Delhi) has been used for testing purpose. ANN model has been tested with Levenberg-Marquardt training algorithm to select the best training algorithm. The feedforward back-propagation algorithm with logsig transfer function has been used in this analysis. The results of ANN model have been compared with analytical values on the basis of root mean square error.

Homogeneity assessment of a station climate series (1933–2005) in the Metropolitan Area of São Paulo: instruments change and urbanization effects

Abstract: This work assessed homogeneity of the Institute of Astronomy, Geophysics and Atmospheric Sciences (IAG) weather station climate series, using various statistical techniques. The record from this target station is one of the longest in Brazil, having commenced in 1933 with observations of precipitation, and temperatures and other variables later in 1936. Thus, it is one of the few stations in Brazil with enough data for long-term climate variability and climate change studies. There is, however, a possibility that its data may have been contaminated by some artifacts over time. Admittedly, there was an intervention on the observations in 1958, with the replacement of instruments, for which the size of impact has not been yet evaluated. The station transformed in the course of time from rural to urban, and this may also have influenced homogeneity of the observations and makes the station less representative for climate studies over larger spatial scales. Homogeneity of the target station was assessed applying both absolute, or single station tests, and tests relatively to regional climate, in annual scale, regarding daily precipitation, relative humidity, maximum (TMax), minimum (TMin), and wet bulb temperatures. Among these quantities, only precipitation does not exhibit any inhomogeneity. A clear signal of change of instruments in 1958 was detected in the TMax and relative humidity data, the latter certainly because of its strong dependence on temperature. This signal is not very clear in TMin, but it presents non-climatic discontinuities around 1953 and around 1970. A significant homogeneity break is found around 1990 for TMax and wet bulb temperature. The discontinuities detected after 1958 may have been caused by urbanization, as the observed warming trend in the station is considerably greater than that corresponding to regional climate.

ICT approaches to integrating institutional and non-institutional data services for better understanding of hydro-meteorological phenomena

Abstract: . It is widely recognised that an effective exploitation of Information and Communication Technologies (ICT) is an enabling factor to achieve major advancements in Hydro-Meteorological Research (HMR). Recently, a lot of attention has been devoted to the use of ICT in HMR activities, e.g. in order to facilitate data exchange and integration, to improve computational capabilities and consequently model resolution and quality. Nowadays, ICT technologies have demonstrated that it is possible to extend monitoring networks by integrating sensors and other sources of data managed by volunteer's communities. These networks are constituted by peers that span a wide portion of the territory in many countries. The peers are "location aware" in the sense that they provide information strictly related with their geospatial location. The coverage of these networks, in general, is not uniform and the location of peers may follow random distribution. The ICT features used to set up the network are lightweight and user friendly, thus, permitting the peers to join the network without the necessity of specialised ICT knowledge. In this perspective it is of increasing interest for HMR activities to elaborate of Personal Weather Station (PWS) networks, capable to provide almost real-time, location aware, weather data. Moreover, different big players of the web arena are now providing world-wide backbones, suitable to present on detailed map location aware information, obtained by mashing up data from different sources. This is the case, for example, with Google Earth and Google Maps. This paper presents the design of a mashup application aimed at aggregating, refining and visualizing near real-time hydro-meteorological datasets. In particular, we focused on the integration of instant precipitation depths, registered either by widespread semi-professional weather stations and official ones. This sort of information has high importance and usefulness in decision support systems and Civil Protection applications. As a significant case study, we analysed the rainfall data observed during the severe flash-flood event of 4 November 2011 over Liguria region, Italy. The joint use of official observation network with PWS networks and meteorological radar allowed for the making of evident finger-like convection structure.

The Impact of Additional Weather Inputs on Gas Load Forecasting

Abstract: THE IMPACT OF ADDITIONAL WEATHER INPUTS ON GAS LOAD FORECASTING Bo Pang, B.S. Marquette University, 2012 Natural gas utilities need to estimate their customers’ gas demand accurately. This thesis develops a number of daily forecasting models for test the possibility to extend the weather inputs in the current method for three different operating areas. Our goal is to improve the accuracy of our forecast by extending the number of inputs used by the existing GasDay model. We present a detailed explanation of the identification of the significance for each of the new weather input candidates. The significance of the new weather inputs was tested by statistical hypothesis testing, by forecasting performance testing, and by unusual day evaluation. We show that with some combinations of additional weather instruments, the accuracy of the forecast is improved. For most gas utilities, the primary use of natural gas is for space heating, so temperature is a critical factor when we build forecast models. In this thesis, we develop a method to split the Heating Degree Day (HDD) term into smaller pieces and generate the forecast based on these small factors. We name the method that developed as Multiple Weather Station (MWS) model in Chapter 4. We show that the MWS model yields better results compared to the existing method.

Area-wide dynamic line ratings based on weather measurements

Abstract: SUMMARY The load of overhead lines has increased due to raised transmission of electrical energy within Europe as well as in the consequence of a growing feed-in from regenerative energy resources. The transmission capacities of overhead lines (OHL) are limited and already in many cases the bottlenecks which restrict the power flows. Dynamic rating is a measure to increase the ampacity of overhead lines depending on the actual weather situation. In the first section this paper focuses on the description and evaluation of different methods and tools for OHL ampacity determination. The conductor temperature is measured directly with a sensor as well as determined indirectly using a weather station close to the line and commercially available weather data. Different scenarios where the measured wind speed is higher than the wind at the line due to shadowing effects are taken into account. The results show that the conductor temperature determination from weather data may be done with a maximal adequacy of about 5 K in the conductor temperature range up to 50°C. This fact means that the dynamic line rating is applicable but some safety margins have to be implemented. It is also shown that investigations on the thermal behaviour at low wind speeds seem to be necessary. In the second section the focus is on the implementation of a dynamic rating system into the 380 kV transmission grid and the necessary measures to increase the ampacity up to 3,150 A. This dynamic rating system uses the ambient temperature and the wind speed to determine the dynamic ampacity of the line. Retrofitting in substations such as replacing circuit breakers and current transformers as well as measures at overhead lines such as inspecting joints and raising towers had to be taken. Dynamic aspects of the transmission system are discussed. The protection concept was revised in order to allow a quick location of faults even in the case of a single technical component failure. The operational experience using the dynamic rating system proves that it fits very well with the existing control centre’s technology. The distinct increase in dynamic current rating compared to static rating verifies the technical and economical capability.

Method and system for forecasting pollutant source

Abstract: The invention relates to a method and a system for forecasting a pollutant source. The method comprises the following steps: establishing a first established number of pollution-wind direction data according to pollution concentration data measured by a first pollution monitoring instrument arranged in a first position and first wind direction data measured by a weather station; establishing a second established number of pollution-wind direction data according to pollution concentration data measured by a second pollution monitoring instrument arranged in a second position and second wind direction data measured by the weather station; and constructing pollution probability regional distribution information according to the first established number of pollution-wind direction data and the second established number of pollution-wind direction data; and judging the pollutant source according to the pollution probability regional distribution information.