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Weather Data (weather + data)
Selected AbstractsBehaviour of male pine sawflies, Neodiprion sertifer, released downwind from pheromone sourcesENTOMOLOGIA EXPERIMENTALIS ET APPLICATA, Issue 2 2000Fredrik Östrand Abstract This study investigated the behaviour of male European pine sawflies, Neodiprion sertifer Geoffroy (Hym., Diprionidae), that were released and observed downwind from pheromone traps baited with 100 ,g of the sex pheromone, (2S,3S,7S)-3,7-dimethyl-2-pentadecyl acetate. Releases were done at three distances; either at 5 m from one trap, or at 50 or 200 m from five traps, placed in a line perpendicular to the current wind direction. As control, males were released identically but without any pheromone source present. The behaviour of the males prior to take-off was studied. A total of 1729 males were released, and 80% of them took flight. Males took off significantly faster in the presence of pheromone. Grooming was significantly more frequent in presence of pheromone compared with control. In all pheromone experiments significantly more males displayed grooming, wing fanning and take-off towards the wind compared with the control. Weather data was simultaneously collected at the study site. Wing fanning was negatively correlated with wind speed. Grooming was not influenced by wind speed. Reduced levels of incoming short-wave radiation lowered the take-off frequency significantly. Pheromone-induced behaviour in diprionids seems to be less distinct than in other insects, e.g., Lepidoptera. [source] Impact of weather on off-flavour episodes at a Louisiana commercial catfish farmAQUACULTURE RESEARCH, Issue 5 2009Barry K Hurlburt Abstract The catfish aquaculture industry is hampered by off-flavour events that affect timely fish sales. In this study, weather data were correlated with geosmin and 2-methylisoborneol (2-MIB) levels in 21 commercial pond's water samples. Samples were collected weekly for 44 weeks. The off-flavour compounds, geosmin and 2-MIB, were quantified using gas chromatography,mass spectrometry. Weather data were collected near the catfish farm and included maximum and minimum air temperature, rainfall, average wind velocity, maximum and minimum humidity, and maximum and minimum soil temperature. Geosmin was weakly and positively correlated with air and soil temperatures, and weakly and negatively correlated with wind velocity. 2-MIB was strongly and positively correlated with air and soil temperatures, moderately and negatively correlated with wind velocity, and weakly and positively correlated with maximum humidity. There were no bivariate relationships between rainfall, minimum humidity or pond size, and levels of either off-flavour compound. Using logistic regression, the best predictors for off-flavour status based on geosmin levels included minimum soil temperature, rainfall and minimum humidity. The best predictors for off-flavour status based on 2-MIB levels included minimum soil temperature and average wind velocity. Soil temperature and rainfall were risk factors for off-flavour, while humidity and wind velocity were protective factors. [source] FC02.4 Meteorological factors and standard series patch test reactionsCONTACT DERMATITIS, Issue 3 2004Janice Hegewald The existence of seasonal patterns to patch test reactions has been described, but with conflicting causal interpretations. The potential seasonality of patch tests may be due to irritation, changes to skin barrier or changes to immunological functions caused by meteorological fluctuations. For example, increased skin irritability due to cold winter weather and low humidity may cause an increase in irritative/doubtful and weak positive (false positive) reactions. To investigate the extent of the association between weather and patch test results, consecutive patients (N = 73691) patch tested with the standard series of the German Contact Dermatitis Research Group (DKG) at German or Austrian IVDK (http://www.ivdk.de) centres were matched with weather data collected at a nearby (30 km radius) weather station. Temperature and absolute humidity (AH) on the day of patch test application and the two preceding days were averaged to represent the environment most likely to have influenced the skin condition at the time of testing. The results of 24 standard series substances were analyzed with multivariate logistic regression. Half of the standard series substances examined, including fragrance mix, nickel sulphate, and formaldehyde, exhibited evidence of a relationship with meteorological conditions. Fragrance mix and p-Phenylene diamine exhibited the strongest evidence of an association to weather, with the odds of the reactions in all three reaction categories (ir/?, +, ++/+++) increasing during winter conditions. Due to the association between weather and patch test reactivity, the potential effect of meteorological conditions should be considered in the interpretation of patch test reactions. [source] Net regional ecosystem CO2 exchange from airborne and ground-based eddy covariance, land-use maps and weather observationsGLOBAL CHANGE BIOLOGY, Issue 3 2007F. MIGLIETTA Abstract Measurements of regional net ecosystem exchange (NEE) were made over a period of 21 days in summer 2002 in the South-Central part of the Netherlands and extrapolated to an area of 13 000 km2 using a combination of flux measurements made by a Sky Arrow ERA research aircraft, half-hourly eddy covariance data from four towers, half-hourly weather data recorded by three weather stations and detailed information on regional land use. The combination of this type of information allowed to estimate the net contribution of the terrestrial ecosystems to the overall regional carbon flux and to map dynamically the temporal and spatial variability of the fluxes. A regional carbon budget was calculated for the study period and the contributions of the different land uses to the overall regional flux, were assessed. Ecosystems were, overall, a small source of carbon to the atmosphere equivalent to to 0.23±0.025 g C m,2 day,1. When considered separately, arable and grasslands were a source of, respectively, 0.68±0.022 and 1.28±0.026 g C m,2 day,1. Evergreen and deciduous forests were instead a sink of ,1.42±0.015 g C m,2 day,1. During the study period, forests offset approximately 3.5% of anthropogenic carbon emission estimates obtained from inventory data. Lacking of a robust validation, NEE values obtained with this method were compared with independent state of art estimates of the regional carbon balance that were obtained by applying a semi-empirical model of NEE driven by MODIS satellite fAPAR data. The comparison showed an acceptable matching for the carbon balance of forest that was a sink in both cases, while a much larger difference for arable and grassland was found. Those ecosystems were a sink for satellite-based estimates while they were a source for the combined aircraft and tower estimates. Possible causes of such differences are discussed and partly addressed. The importance of new methods for determining carbon balance at the regional scale, is outlined. [source] Model predicting dynamics of biomass, structure and digestibility of herbage in managed permanent pastures.GRASS & FORAGE SCIENCE, Issue 2 2006Abstract To investigate seasonal and annual interactions between management and grassland dynamics, a simple mechanistic model of the dynamics of production, structure and digestibility in permanent pastures was constructed. The model is designed to respond to various defoliation regimes, perform multiple-year simulations and produce simple outputs that are easy to use as inputs for a model of ruminant livestock production. Grassland communities are described using a set of average functional traits of their constituent grass groups. The sward is subdivided into four structural compartments: green leaves and sheath, dead leaves and sheath, green stems and flowers, and dead stems and flowers. Each compartment is characterized by its biomass, age and digestibility. Only above-ground growth is modelled, using a light-utilization efficiency approach modulated by a seasonal pattern of storage and mobilization of reserves. Ageing of plant parts is driven by cumulative thermal time from 1 January and by biomass flows. Age affects senescence, abscission and digestibility of green compartments and, therefore, the quality of green leaves and stems can increase or decrease over time in relation to net growth and defoliation dynamics. The functional traits having the greatest impact on model outputs are seasonal effects, period of reproductive growth and effects of temperature on photosynthetic efficiency. The functional traits of the grass groups were parameterized for temperate pastures of the Auvergne region in France. The other model inputs are few: proportion of functional groups, basic weather data (incident photosynthetically active radiation, mean daily temperature, precipitation and potential evapotranspiration) and site characteristics (nitrogen nutrition index, soil water-holding capacity). In the context of a whole-farm simulator, the model can be applied at a field scale. [source] The Effect of Weather on HeadacheHEADACHE, Issue 6 2004Patricia B. Prince MD Objectives.,To assess headache patients' beliefs about how strongly weather affects their headaches; To objectively investigate the influence of multiple weather variables on headache. Design and Methods.,Our sample consisted of 77 migraineurs seen in a headache clinic, who provided headache calendars for a period ranging from 2 to 24 months. Our study was divided into two phases. First, each patient was given a questionnaire assessing their beliefs about how strongly (if so) weather affected their headaches. Second, weather data were collected from the National Weather Service, from three reporting stations central to the residences of the study participants. Analysis was performed on 43 variables to generate three meteorological factors. Linear regression was used to assess the relationship between headache and these three factors. Factor 1 represents a function of absolute temperature and humidity. Factor 2 represents a changing weather pattern. Factor 3 represents barometric pressure. Results.,Of the 77 subjects in the study, 39 (50.6%), were found to be sensitive to weather, but 48 (62.3%) thought they were sensitive to weather conditions (P < 0.05). Thirty (38.9%) were sensitive to one weather factor and 9 (11.7%) to two factors. Twenty-six (33.7%) were sensitive to factor 1; 11 (14.3%) to factor 2; 10 (12.9%) to factor 3. Conclusions.,Our study supports the influence of weather variables on headache. We showed that patients are susceptible to multiple weather variables and that more patients thought weather was a trigger than was the case. [source] Missing data estimation for 1,6,h gaps in energy use and weather data using different statistical methodsINTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 13 2006David E. Claridge Abstract Analysing hourly energy use to determine retrofit savings or diagnose system problems frequently requires rehabilitation of short periods of missing data. This paper evaluates four methods for rehabilitating short periods of missing data. Single variable regression, polynomial models, Lagrange interpolation, and linear interpolation models are developed, demonstrated, and used to fill 1,6,h gaps in weather data, heating data and cooling data for commercial buildings. The methodology for comparing the performance of the four different methods for filling data gaps uses 11 1-year data sets to develop different models and fill over 500 000 ,pseudo-gaps' 1,6,h in length for each model. These pseudo-gaps are created within each data set by assuming data is missing, then these gaps are filled and the ,filled' values compared with the measured values. Comparisons are made using four statistical parameters: mean bias error (MBE), root mean square error, sum of the absolute errors, and coefficient of variation of the sum of the absolute errors. Comparison based on frequency within specified error limits is also used. A linear interpolation model or a polynomial model with hour-of-day as the independent variable both fill 1,6 missing hours of cooling data, heating data or weather data, with accuracy clearly superior to the single variable linear regression model and to the Lagrange model. The linear interpolation model is the simplest and most convenient method, and generally showed superior performance to the polynomial model when evaluated using root mean square error, sum of the absolute errors, or frequency of filling within set error limits as criteria. The eighth-order polynomial model using time as the independent variable is a relatively simple, yet powerful approach that provided somewhat superior performance for filling heating data and cooling data if MBE is the criterion as is often the case when evaluating retrofit savings. Likewise, a tenth-order polynomial model provided the best performance when filling dew-point temperature data when MBE is the criterion. It is possible that the results would differ somewhat for other data sets, but the strength of the linear and polynomial models relative to the other models evaluated seems quite robust. Copyright © 2006 John Wiley & Sons, Ltd. [source] On the technical feasibility of gas turbine inlet air cooling utilizing thermal energy storageINTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 5 2006Y. H. Zurigat Abstract The potential of using thermal energy storage (TES) in the form of ice or chilled water to cool gas turbine inlet air is evaluated for a remote oil field location in the Sultanate of Oman using local hourly typical meteorological year weather data. It is found that under the conditions investigated seasonal TES in chilled water storage tanks or ice bins for the location considered is prohibitively expensive and thus not recommended. Application of partial TES option shows that the cool storage does not result in any noticeable reduction in the chiller size. Hence, TES whether seasonal, partial, or full storage is not a viable option for the considered location, especially in the absence of time-of-use utility rate structure. Copyright © 2005 John Wiley & Sons, Ltd. [source] Metabolic correlates of leg length in breeding arctic shorebirds: the cost of getting highJOURNAL OF BIOGEOGRAPHY, Issue 3 2005Ralph V. Cartar Abstract Aim, We test the hypothesis that tarsus length in all shorebirds breeding in the Canadian arctic shows an evolutionary response to average metabolic stress encountered across the breeding range, such that birds nesting in metabolically stressful environments have relatively shorter legs. Longer-legged birds living in colder environments will experience greater metabolic costs because their torsos are elevated farther away from the ground's wind-dampening boundary layer. Methods, We use weather data (temperature, wind speed, global solar radiation) from 27 arctic weather stations measured over 37 years, and a previously published model of heat transfer, to characterize the metabolic harshness over the breeding season of the ranges of each of the 17 shorebirds of the family Charadriidae nesting in the Canadian arctic. Results, After controlling for the lengths of two other body extremities (wing and bill), there was a significant negative relationship between tarsus length and mean metabolic harshness. This result was obtained whether species were treated as independent data points, or in a comparative analysis using standardized independent contrasts. Main conclusions, We support a unique extension of Allen's rule: body-supporting appendages of homeotherms may be shorter in colder environments so as to take advantage of a boundary layer effect, thereby reducing metabolic costs. [source] Seasonal patterns of sucrose concentration in relation to other quality parameters of sugar beet (Beta vulgaris L.)JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE, Issue 1 2006Christine Kenter Abstract The chemical composition of sugar beet is the most important parameter affecting its processing. Sugar factories require beet with high concentrations of sucrose and low concentrations of melassigenic substances to maximise the amount of extractable sugar. In order to plan the processing campaign, forecasts of root and sugar yield by prediction models are possible but there are no means to predict the technical quality of the beet. In the present study, the seasonal development and physiological relationships of different parameters of sugar beet quality were analysed. In order to estimate possibilities for quality forecasts, the concentrations of beet quality variables in October were correlated with corresponding quality measurements in late summer and to weather variables during the growing season by linear regressions. In 2000 and 2001, 27 field trials were conducted on commercial farm fields in all sugar beet growing areas in Germany. From June to October, sequential samples were taken every 4 weeks and the concentrations of sucrose, potassium, sodium, total soluble nitrogen, ,-amino nitrogen, nitrate, betaine, reducing sugars and marc in the beet were determined. The sucrose concentration increased progressively until the final harvest date in autumn, whereas the concentrations of the melassigenic substances decreased markedly until late summer and remained fairly constant as the season progressed. Marc concentration was the most stable of the parameters analysed. The sucrose concentration was positively correlated with the concentrations of dry matter, betaine and marc, but negatively with nitrate concentration and leaf yield throughout the season. The correlation between the concentrations of sucrose and nitrogenous compounds measured in summer and their final concentrations in autumn was rather weak. However, it was close for potassium, sodium and marc and a satisfactory prediction of their final concentrations was possible by the end of August. Based on weather data, beet quality was not predictable. Therefore, it seems to be difficult to integrate beet quality parameters into prediction models. Copyright © 2005 Society of Chemical Industry [source] Numerical simulation of particle trajectory and atmospheric dispersion of airborne releasesMETEOROLOGICAL APPLICATIONS, Issue 3 2009S. Shoaib Raza Abstract Numerical simulation of particle trajectory and atmospheric dispersion has been performed for an airborne accidental release from a nuclear power plant site. A Long-range Particle transport and Dispersion Model (LPDM) based on a Lagrangian approach is developed and tested in this work. The Lagrangian transport/dispersion model is directly coupled with an atmospheric prediction model, RAMS (Regional Atmospheric Modeling System), to provide necessary meteorological fields in a three-dimensional domain. An advantage of this direct coupling is that the meteorological data generated by RAMS can be used directly for trajectory calculations without storage, thus reducing the CPU time consumed in the data storage and retrieval. This effort was done to be able to use this directly coupled modelling system for real-time predictions in case of an accidental release from a potential site. The simulated Lagrangian trajectories were compared with those obtained using observed hourly weather data obtained from an on-site meteorological tower. The results indicated that this one-way coupling between LPDM-RAMS provided almost identical trajectories when compared with those obtained using LPDM alone driven by hourly observed wind data. The comparison demonstrated the reliability of the RAMS meteorological predictions for the site under consideration. The comparison also indicated that LPDM (run in a stand alone mode), with hourly-observed wind data, could also be used for trajectory calculations over flat terrain. The model was developed on a parallel processing computer (SGI workstation, ORIGIN 2000 computer with eight processors) for use in real-time forecast mode. The computational time was about one-third of the simulation time, while using four processors. The model options need to be explored to reduce the computational time further and test its performance for real-time atmospheric dispersion applications. Copyright © 2009 Royal Meteorological Society [source] Weather-based prediction of anthracnose severity using artificial neural network modelsPLANT PATHOLOGY, Issue 4 2004S. Chakraborty Data were collected and analysed from seven field sites in Australia, Brazil and Colombia on weather conditions and the severity of anthracnose disease of the tropical pasture legume Stylosanthes scabra caused by Colletotrichum gloeosporioides. Disease severity and weather data were analysed using artificial neural network (ANN) models developed using data from some or all field sites in Australia and/or South America to predict severity at other sites. Three series of models were developed using different weather summaries. Of these, ANN models with weather for the day of disease assessment and the previous 24 h period had the highest prediction success, and models trained on data from all sites within one continent correctly predicted disease severity in the other continent on more than 75% of days; the overall prediction error was 21·9% for the Australian and 22·1% for the South American model. Of the six cross-continent ANN models trained on pooled data for five sites from two continents to predict severity for the remaining sixth site, the model developed without data from Planaltina in Brazil was the most accurate, with >85% prediction success, and the model without Carimagua in Colombia was the least accurate, with only 54% success. In common with multiple regression models, moisture-related variables such as rain, leaf surface wetness and variables that influence moisture availability such as radiation and wind on the day of disease severity assessment or the day before assessment were the most important weather variables in all ANN models. A set of weights from the ANN models was used to calculate the overall risk of anthracnose for the various sites. Sites with high and low anthracnose risk are present in both continents, and weather conditions at centres of diversity in Brazil and Colombia do not appear to be more conducive than conditions in Australia to serious anthracnose development. [source] HDD and CDD option pricing with market price of weather risk for TaiwanTHE JOURNAL OF FUTURES MARKETS, Issue 8 2008Hung-Hsi Huang This study extends the long-term temperature model proposed by Alaton et al. (2002) by taking into account ARCH/GARCH effects to reflect the clustering of volatility in temperature. The fixed variance model and the ARCH model are estimated using Taiwan weather data from 1974 through 2003. The results show that for HDD/CDD the call price is higher under ARCH-effects variance than under fixed variance, while the put price is lower. Although different pricing methods are employed in pricing weather options, the effects of mean and standard deviation on option prices are mathematically proved to be the same as those in pricing traditional financial derivatives using the Black-Scholes formula. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:790,814, 2008 [source] Impact of weather on off-flavour episodes at a Louisiana commercial catfish farmAQUACULTURE RESEARCH, Issue 5 2009Barry K Hurlburt Abstract The catfish aquaculture industry is hampered by off-flavour events that affect timely fish sales. In this study, weather data were correlated with geosmin and 2-methylisoborneol (2-MIB) levels in 21 commercial pond's water samples. Samples were collected weekly for 44 weeks. The off-flavour compounds, geosmin and 2-MIB, were quantified using gas chromatography,mass spectrometry. Weather data were collected near the catfish farm and included maximum and minimum air temperature, rainfall, average wind velocity, maximum and minimum humidity, and maximum and minimum soil temperature. Geosmin was weakly and positively correlated with air and soil temperatures, and weakly and negatively correlated with wind velocity. 2-MIB was strongly and positively correlated with air and soil temperatures, moderately and negatively correlated with wind velocity, and weakly and positively correlated with maximum humidity. There were no bivariate relationships between rainfall, minimum humidity or pond size, and levels of either off-flavour compound. Using logistic regression, the best predictors for off-flavour status based on geosmin levels included minimum soil temperature, rainfall and minimum humidity. The best predictors for off-flavour status based on 2-MIB levels included minimum soil temperature and average wind velocity. Soil temperature and rainfall were risk factors for off-flavour, while humidity and wind velocity were protective factors. [source] Modellierung von kurzwelliger solarer Strahlung bei der hygrothermischen Bauteilsimulation , numerische Lösung und analytischer AnsatzBAUPHYSIK, Issue 1 2006Doktorandin Claudia Finkenstein Dipl.-Ing. Der vorliegende Beitrag präsentiert ein Modell zur Bestimmung der kurzwelligen solaren Strahlung an Bauteilen, das , basierend auf gemessenen Wetterdaten der direkten und diffusen solaren Strahlung auf die Horizontalfläche , für die Einbindung in numerische Simulationsprogramme geeignet ist. Damit wurde ein geschlossenes Konzept erarbeitet, das es erlaubt, die Strahlungswärmestromdichte infolge kurzwelliger direkter und diffuser Sonnenstrahlung auf beliebig orientierte und geneigte Wand- und Dachflächen unter Beachtung der Eigenverschattung an einem beliebigen Ort zu berechnen. Weiterhin stellt der Beitrag einen analytischen Ansatz für das gleiche Problem vor, mit dessen Hilfe auf einfache Weise z. B. Wirkungsanalysen durchgeführt werden können. Den Abschluß des Beitrags bildet die beispielhafte Berechnung einer nach verschiedenen Himmelsrichtungen orientierten Wandkonstruktion. Modelling of shortwave solar radiation within the hygrothermal simulation of building envelope parts , numerical solution and analytical approach. This article presents a model for the determination of shortwave solar radiation on building envelope parts, which is , based on measured weather data of direct and diffuse solar radiation on a horizontal surface , suitable to be integrated in computercodes for hygrothermal building part simulation. Therewith, firstly a well-rounded concept has been worked out, which allows to calculate the radiation flux on any orientated and sloped wall or roof construction at any location taking into account the self-shading. Furthermore, there is presented an analytical approach for the same problem that is suitable to perform sensitivity analyses with in an easy way. At the end of the article, an example calculation of a wall construction orientated into different directions is presented. [source] | |||||||||||||||||||