Showing papers on "Weather station published in 2005"

Very high resolution interpolated climate surfaces for global land areas.

Abstract: We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950–2000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a higher spatial resolution (400 times greater or more); more weather station records were used; improved elevation data were used; and more information about spatial patterns of uncertainty in the data is available. Owing to the overall low density of available climate stations, our surfaces do not capture of all variation that may occur at a resolution of 1 km, particularly of precipitation in mountainous areas. In future work, such variation might be captured through knowledgebased methods and inclusion of additional co-variates, particularly layers obtained through remote sensing. Copyright  2005 Royal Meteorological Society.

Weather-based insurance in Southern Africa : the case of Malawi

Abstract: The main purpose of this report is to conceptualize an ex-ante risk management framework for weather risk in the Southern African Development Community (SADC) region. The report lays out an overall food security policy context and analyzes the role of weather risk management techniques for food security at the national level, taking Malawi as a case study, and the regional level for the entire SADC region. The paper sets the context for improving food security and reducing poverty, introduces the one instrument of weather-based insurance, and notes two scenarios how weather insurance could be used as part of a wider national drought risk management strategy by Malawi, namely budget insurance and a weather shock safety net.

An analysis of temperatures and wind speeds above Dome C, Antarctica

Abstract: Department of Geography, University of Idaho, Moscow, Idaho, USA-Abstract. A good astronomical site must fulflll several criteria including low atmospheric turbulence and lowwind speeds. It is therefore important to have a detailed knowledge of the temperature and wind conditions ofa location considered for future astronomical research. Antarctica has unique atmospheric conditions that havealready been exploited at the South Pole station. Dome C, a site located on a local maximum of the Antarcticplateau, is likely to have even better conditions. In this paper we present the analysis of two decades of windspeed measurements taken at Dome C by an automated weather station (AWS). We also present temperature andwind speed proflles taken over four Antarctic summers using balloon-borne weather sondes. We will show that aswell as having one of the lowest average wind speed ever recorded at an existing or potential observatory, DomeC also has an extremely stable upper atmosphere and a very low inversion layer.Key words. Site Testing { Atmospheric afiects { Balloons

Weather station, e.g. consumer weather station, for locally measuring e.g. pressure, has sensor, where station has unit exchanging data with remote server and mobile telephone by using global system for mobile communication type network

Abstract: The station has a sensor (12) e.g. thermometer, measuring temperature. The station has an exchange unit exchanging a data with a remote server (18) and a mobile telephone (50) by using a global system for mobile communication (GSM) type network (20). The station transmits short message service (SMS) type messages, by a data transmission unit (14), during the exchange of the data with the server. The station has a unit (16) receiving the data. The messages have meteorological observations data representing the temperature and data representing date and hour at which measurements are performed.

Daily Weather and Tree Growth at the Tropical Treeline of North America

Abstract: We present here the 2001–2004 results of observational field studies aimed at quantifying tropical timberline climate and radial increment of Pinus hartwegii Lindl. trees on Nevado de Colima, in the middle of the North American Monsoon region. An automated weather station was installed at 3760 m a.s.l., 19°34.778′N latitude, 103°37.180′W longitude, within a forest where multi-century tree-ring records had been previously developed. At the same time, automated electronic sensors for recording tree growth at 30-min intervals were set up at two sites within a 1-km radius from the weather station. Meteorological observations recorded every 30 min were summarized on a daily basis. Time-series patterns are reported for atmospheric pressure, precipitation, incoming solar radiation, air and soil temperature, relative humidity, soil moisture, and wind speed and direction. Of particular interest is the sudden decrease in air temperature after the onset of the monsoon season, which determines very high rela...

Some Concerns when Using Data from the Cooperative Weather Station Networks:A Nebraska Case Study

Abstract: In this study, daily temperature and precipitation amounts that are observed by the Cooperative Observer Program (COOP) were compared among geographically close stations. Hourly observations from nearby Automatic Weather Data Network (AWDN) stations were utilized to resolve the discrepancies between the observations during the same period. The statistics of maximum differences in temperature and precipitation between COOP stations were summarized. In addition, the quantitative measures of the deviations between COOP and AWDN stations were expressed by root-mean-square error, mean absolute error, and an index of agreement. The results indicated that significant discrepancies exist among the daily observations between some paired stations because of varying observation times, observation error, sensor error, and differences in microclimate exposure. The purpose of this note is to bring attention to the problem and offer guidance on the use of daily observations in the comparison and creation of wea...

Use of meteorological radar to estimate leaf wetness as data input for application of territorial epidemiological model (downy mildew—Plasmopara viticola)

Abstract: The grapevine downy mildew (Plasmopara viticola) represents the most important disease of the grapevine in Friuli-Venezia Giulia Region (Italy). The development of this disease depends from the meteorological conditions and particularly by air humidity, rain and leaf wetness (LW here after). Forecast models can help the technicians of the extension services to predict the timing and the best technique to use in operative programs. Unfortunately these models require data, coming from meteorological stations which are often variable in space (e.g. rain, leaf wetness) and hardly spatializable. In the first part of this work, a case study is presented to show the great difference between maps of daily rain duration, obtained by radar, and those created by spatialization of data and obtained by weather stations. Then the possibility to use the radar rain maps appears very interesting to estimate LW over a large area. LW and daily rain measurements, obtained by 14 weather stations of Friuli-Venezia Giulia plain (Italy), are compared with rain maps obtained by polarimetric radar GPM-500 placed in Fossalon di Grado (Friuli-Venezia Giulia, Italy). The reference measurements are made during two periods: from 1/4/2000 to 30/9/2000 and from 1/4/2001 to 30/9/2001. From radar maps rain measurements estimated are extracted above each weather station and these data are integrated for every hour. These radar data of hourly rain are compared to the corresponding measurementes of LW and rain obtained by weather stations. From this analysis it appears that there is a good correlation between the number of rain hours estimated by radar and the number of LW hours measured by stations: in the observed cases, the error found is lower than 2%; then radar has a good precision to estimate LW due to rain. Therefore the use of Radar is foretold to give meteorological inputs in simulation models that can work to evaluate the development of fungal diseases. In the second part a model to daily display the infections of downy mildew all over the plain of Friuli-Venezia Giulia is described. Elements of this model are: • the creation of a daily grid of rain estimated by a meteorological polarimetric radar (GPM-500) located in Fossalon di Grado; • the creation of a daily grid of temperature, air humidity, solar radiation, wind speed using data coming from 14 synoptic meteorological stations located in the plain of the region; • the creation of a daily grid of leaf-wetness computed using the SWEB model for the data measured or estimated in the previous point; • the estimation of the P. viticola infection level using a forecast model (in this case Goidanich). • The daily graphical output in every point of the grid is: number of the actual cycles of P. viticola infections; number of days required for the next infection; annual amount of infective cycles. The model has been checked in a limited area (about 200 km2) with an high presence of grapevine (DOC Aquileia) in the period from may 2000 to september 2000. In this area the data from eight meteorological automatic stations installed for diseases–defence purposes are used as test, and has been calculated the downy mildew infections using the Goidanich model. These grids have been compared with the maps calculated using data coming from meteorological radar and synoptic stations. The outputs are similar and the proposed method can be considered a good approach in the operative use of radar in the crop protection.

Variabilidade espacial e temporal de dados termopluviométricos diários da rede de estações agrometeorológicas do Instituto Agronômico (IAC)

Abstract: Ensuring continuous, good quality data from weather station networks requires a knowledge of spatial and temporal variability. This knowledge is essential to identify suspect data and provide estimates for data gaps. This study was conducted aiming to quantify and contrast the spatial and temporal variability for daily weather variables for a tropical climatic condition of the Instituto Agronomico (IAC) weather station network, located in the State of Sao Paulo, Brazil. For a period of 20 years (1981-2000) data were available from 19 weather stations. The daily meteorological variables studied were maximum and minimum air temperature and precipitation. In the spatial analysis, a central station was paired with each of the other stations in the area. The coefficient of variation (R2) and standard error of estimate (SEE) were calculated by regression of daily measurements between pairs of the same weather variables for various station within the area. The SEE and R2 were plotted against linear distance from the central station. Best fit lines were determined for the variograms (R2) and errograms (SEE). Analysis were performed for each month. Generally, the R2 decreased while the SEE increased with distance of separation between sites. A significant seasonal cycle was found in the SEE data for maximum and minimum air temperature and precipitation. Results indicated that the accuracy of estimated data and associated confidence limits varied with time of the year. As linear distance between sites increased, the SEE for maximum and minimum air temperature were greater, especially during the spring and winter seasons, respectively. The SEE data for precipitation were greater during the summer season. For 150 km of distance, the maximum air temperature presented SEE data values up to 3.0°C and 2.3°C during the spring and summer seasons, respectivelly, while precipitation presented SEE data values up to 4 and 15mm during winter and summer seasons, respectivelly. Based on the analysis of climate data from the tropical conditions of the State of Sao Paulo, spacing requirements varied with time of the year. An 80 km spacing is required to explain 90% of the variation between sites, for maximum daily air temperature during the spring and summer months, and 90 km for autumn and winter; while for minimum air temperature that spacing reduces to 55 km during the summer, 75 km for winter and spring, and increases to more than 90 km during the autumn. A 27 km spacing is required to explain the variation for precipitation during the winter season, up to 20 km for spring and autumn, but during the summer the spacing reduces to 12 km.

Improvement and Application of SWAT—A Physically Based,Distributed Hydrological Model

Abstract: SWAT(Soil and Water Assessment Tool) model is an advanced,physically based,distributed hydrological model that is integrated with Remote Sensing(RS),Geographic Information System(GIS) and Digital Elevation Model(DEM) techniques.In order to impel its application study in China and improve the simulation precision of the model in hydrological process studies,some expansions and improvements were made to the modeling system for the real conditions on arid,semi-arid Heihe River Basin in the northwestern China and humid Hanjiang River Basin in middle-western China.Firstly,soil grain size transferring module and data pre-processing module for weather generator(WGEN) were added to original SWAT model to encounter the inconsistent problems existed in data standard utilized in Euramerican and Chinese systems.And then the further improvements to the model were done focusing on: 1) three new spatial interpolation methods, including Inverse Distance Weighing method(IDW),Thiessen polygonal method and DEM-based PRISM method,were used as a new choice to replace the original interpolation method that takes the meteorological data from the nearest weather station as the representative weather data for each sub-basin.2) An advanced approach was proposed to modify the original method in daily maximum and minimum temperature estimations in SWAT for avoiding the logical mistakes in temperature simulations.3) An areal evapotranspiration estimation module based on improved Penman-Monteith method was developed to replace the original approaches used in SWAT.At last the offline experiment on rainfall-runoff simulations were conducted using the meteorological,land use/cover and soil data from the Jiangkou Basin,the Hanjiang River by means of the improved SWAT model and its original version.The detailed study suggested a significant improvement of modeling performance by the fact that in model calibration period,the Nash-Sutcliffe Criterion (NSC) and correlation coefficient were improved from 0.47 and 0.79 to 0.92 and 0.98 respectively,while in validation period,they were improved from 0.08 and 0.68 to 0.94 and 0.97 accordingly.The improved SWAT model and its software packs will impel the application studies in the relevant disciplines in China.

Interactive Exercises for an Introductory Weather and Climate Course

Abstract: Students learn more from introductory weather and climate courses when they can relate theoretical material to personal experience. The ubiquity of weather should make the link obvious, but instructors can foster this connection with a variety of simple methods. Here we describe traditional and web-based techniques that encourage students to document daily weather observations and to explore the processes underlying their observations. Our methods employ weather journals, web-based graphics and interactive exercises, as well as a radio transmission system that provides Internet access to near real-time observations from a campus weather station.

Integrated mirror and weather station

Abstract: A system for planning wardrobe and activities includes a weather sensing unit configured to wirelessly transmit weather conditions, a weather condition display module configured to receive the transmitted weather conditions, and a reflective surface integrally coupled to the weather condition display.

Underground water resource monitoring and management system

Abstract: An underground water resource monitoring and management system is described. The station is a complete hydrological and weather station and/or network capable of measuring, analyzing, storing and/or transmitting hundreds of parameters, such as but not limited to, quality and/or quantity of water and surroundings, and weather factors (e.g., rain, wind, etc), or any combination thereof.

The Value of Weather Station Metadata

Abstract: The Oklahoma Mesonet (Brock et al. 1995) is a network comprised of over 110 automated weather stations. During the past 11 years, Mesonet personnel have learned the crucial importance of obtaining accurate weather station, instrument, and data quality metadata and have adopted several principles for maintaining and recording those data. These guidelines are essential to the end-to-end quality assurance (QA) system at the Oklahoma Mesonet. The principles described here involve metadata for: 1) station names, 2) contact information for the land owner, 3) station geographical information, 4) station photographs, 5) sensors, 6) sensor calibrations and coefficients, 7) site visitation reports, 8) field inter-comparisons, 9) station trouble tickets, and 10) quality control information.

Zur Reduzierung niederschlagsbedingter Produktionsrisiken mit Wetterderivaten

Abstract: In this paper we price a precipitation option based on empirical weather data from Germany using different pricing methods, among them the burn analysis, index value simulation and daily simulation. For that purpose we develop a daily precipitation model. Moreover, a decorrelation analysis is proposed to analyse the spatial basis risk that is inherent to rainfall derivatives. The models are applied to precipitation data in Brandenburg, Germany. Based on simplifying assumptions of the production function we quantify and compare the risk exposure of grain producers with and without rainfall insurance. It turns out that a considerable risk remains with producers who are located remotely from the weather station. Another finding is that significant differences may occur between the pricing methods. We identify the strengths and weaknesses of the pricing methods and give some recommendations for their application. Our results are relevant for producers as well as for potential sellers of weather derivatives.

Method for obtaining near ground layer sand dust particle quantity deep time-space distribution

Abstract: The ivnention discloses a method of obtaining spatiotemporal distribution of sand particle mass concentration near the ground, which includes the following steps: 1) Firstly to choose the same time to observe in each weather station under sand weather condition and obtain the data of weather visibility; 2) statistical data of weather visibility from observation data, analyze and calculate to convert visibility observed in each weather station into mass concentration of particulates; 3) to build up mass concentration visibility relationship figure fitting a curve mass concentration- visibility relationship curve, using mass concentration of particle as ordinate and visibility as abscissa; 4) to acquire spatiotemporal distribution of mass concentration figure according to mass concentration- visibility relationship curve. The invention has solves the problem that density spatiotemporal distribution of particle in sand weather cannot be observed in our nation, and supplied effective observition method for sandstorm alarm and sand prevention and harnesing research.

Application of a virtual watershed in academic education

Abstract: . Hydrologic models of watersheds often represent complex systems which are difficult to understand regarding to their structure and dynamics. Virtual watersheds, i.e. watersheds which exist only in the virtual reality of a computer system, are an approach to simplify access to this real-world complexity. In this study we present the virtual watershed KIELSHED-1, a 117 km2 v-shaped valley with grassland on a "Cambisol" soil type. Two weather scenarios are delivered with the watershed: a simplified artificial weather scenario based on long-term data of a German weather station as well as an unmodified data record. The input data and parameters are compiled according to the conventions of the SWAT 2000 hydrological model. KIELSHED-1 is mainly used for education, and illustrative application examples, i.e. calculation of water balance, model calibration, development of land use scenarios, give an insight to the capabilities of the virtual watershed.

Characterization of the Shuttle Landing Facility as a laser range for testing and evaluation of EO systems

Abstract: The Shuttle Landing Facility runway at the Kennedy Space Center in Cape Canaveral, Florida is almost 5 km long and 100 m wide. Its homogeneous environment makes it a unique and ideal place for testing and evaluating EO systems. An experiment, with the goal of characterizing atmospheric parameters on the runway, was conducted in June 2005. Weather data was collected and the refractive index structure parameter was measured with a commercial scintillometer. The inner scale of turbulence was inferred from wind speed measurements and surface roughness. Values of the crosswind speed obtained from the scintillometer were compared with wind measurements taken by a weather station.

Potential Of Inducing Natural Ventilation For Low Rised House Under Tropical Climate

Abstract: This project is titled "The Potential of Inducing Natural Ventilation for Low Rise Buildings Under Tropical Climate' where it explains the fundamentals of natural ventilation and focuses in determining wind speed, temperature and humidity for different types of dwellings. Three experiments have been carried out in three different types of residential building to determine wind speed,temperature and humidity. The first experiment is carried out using only Anemometer where else the second and third experiment uses more equipments such as the MKII Weather Station, Ambient Weather Software and Wolfsense VeloCical Meters. Analyses are done to estimate the natural wind driven potential, temperature, and humidity for the three houses. Comparison is done between the second and third house as both these houses uses the same equipuients. This study is limited to an experimental approach where possible factors that affect the wind speed, temperature and humidity in the three houses are discussed. Recommendation based on past works and journals is inserted together with this report where it explains possible steps that can be taken to induce natural ventilation for low rise buildings.

How Well Does Sky Harbor International Airport Characterize Winter Precipitation in the Phoenix Area

Abstract: Sky Harbor International Airport (SKA) is the first-order weather station in the Phoenix metropolitan area. Meteorological variables from the weather station, including precipitation, are reported by the media to the general public as the official weather results for the Phoenix metropolitan area, which measures more than 15,000 square miles. While temperature is a continuous meteorological parameter that does not vary much spatially across Phoenix, precipitation is a discrete and more variable weather phenomenon, even during winter, when mid-latitude storms bring wide swaths of precipitation to Arizona. Does the precipitation measured at Sky Harbor International Airport spatially characterize precipitation in the rest of the Phoenix area during winter? Have correlations between Sky Harbor winter precipitation and the rest of the Phoenix area changed over time? Precipitation data for the months of December to March were compiled for 28 Phoenix area weather stations for the time period 1990–2004 a...

An ATMS Accident Prediction Model Using Traffic and Rain Data

Abstract: Growing concern over traffic safety has led to research efforts directed towards predicting freeway accidents in ATMS (advanced traffic management systems) environment. This study aims at developing accident likelihood prediction model using real-time traffic flow variables and rain data potentially associated with accident occurrence. Archived loop detector and rain data and historical accident data have been used to calibrate the model. This model can be implemented using on-line loop and rain data to identify high accident potential in real-time. Principal Component Analysis (PCA) and Logistic Regression have been used to estimate a weather model that determines a rain index based on the rain readings at the weather station in the proximity of the freeway. A logit model has also been used to model the accident potential based on traffic loop data and the rain index. The 5-minute average occupancy and standard deviation of volume observed at the downstream station, and the 5-minute coefficient of variation in speed at the station closest to the accident, all during 5-10 minutes prior to the accident occurrence along with the rain index have been found to affect the accident occurrence most significantly.

Distributed Clustering in practice

Abstract: This paper, which is a project report, is realised within the scope of the course "Datamining, Machine Learning and Scientific Dis- covery". Since the amount of data on the databases nowadays is increas- ing, to the size of tera bytes, the need of understanding and analysing them increases as well. In the field of data mining and knowledge dis- covery there are a lot of techniques that are used to analyse the data. We focus here only on one of them, the clustering. Clustering classifies the data into groups according to their similarities. Imagine a group of scientists sitting at a central location, the "base". They want to analyse the data about the weather forecast that was collected at the weather station centres around the world. To do that, they would need to bring all this data together to the "base" and there then analyse it. But, the time and the transmission cost should be taken into account when transferring the data from the weather station centres to the "base" and analysing it, especially when huge amounts of data are involved (which normaly is the case). Considering this the scientists would try to use fast and ecient

A versatile weather station engineering design from the viewpoint of a first-year team

Abstract: The theme of the Spring 2004 EPICS Challenge was "A Versatile Weather Station." Over 60 first-year teams exhibited designs of weather stations required operating a climate network to be placed in local high schools along the front range of the Rocky Mountains. A short-term goal of this project was to have students develop and demonstrate innovative concepts for weather stations. A longer-term goal was to identify and to select the most promising stations for development both on Earth and for planetary exploration. These students will describe their processes for constructing a weather station based on a project-based curriculum in engineering design. They will discuss the design of their station to gather climate data for land use decisions as well as the potential for a weather network for planetary exploration.