Emulation for probabilistic weather forecasting

NASA Astrophysics Data System (ADS)

Cornford, Dan; Barillec, Remi

2010-05-01

Numerical weather prediction models are typically very expensive to run due to their complexity and resolution. Characterising the sensitivity of the model to its initial condition and/or to its parameters requires numerous runs of the model, which is impractical for all but the simplest models. To produce probabilistic forecasts requires knowledge of the distribution of the model outputs, given the distribution over the inputs, where the inputs include the initial conditions, boundary conditions and model parameters. Such uncertainty analysis for complex weather prediction models seems a long way off, given current computing power, with ensembles providing only a partial answer. One possible way forward that we develop in this work is the use of statistical emulators. Emulators provide an efficient statistical approximation to the model (or simulator) while quantifying the uncertainty introduced. In the emulator framework, a Gaussian process is fitted to the simulator response as a function of the simulator inputs using some training data. The emulator is essentially an interpolator of the simulator output and the response in unobserved areas is dictated by the choice of covariance structure and parameters in the Gaussian process. Suitable parameters are inferred from the data in a maximum likelihood, or Bayesian framework. Once trained, the emulator allows operations such as sensitivity analysis or uncertainty analysis to be performed at a much lower computational cost. The efficiency of emulators can be further improved by exploiting the redundancy in the simulator output through appropriate dimension reduction techniques. We demonstrate this using both Principal Component Analysis on the model output and a new reduced-rank emulator in which an optimal linear projection operator is estimated jointly with other parameters, in the context of simple low order models, such as the Lorenz 40D system. We present the application of emulators to probabilistic weather forecasting, where the construction of the emulator training set replaces the traditional ensemble model runs. Thus the actual forecast distributions are computed using the emulator conditioned on the ‘ensemble runs' which are chosen to explore the plausible input space using relatively crude experimental design methods. One benefit here is that the ensemble does not need to be a sample from the true distribution of the input space, rather it should cover that input space in some sense. The probabilistic forecasts are computed using Monte Carlo methods sampling from the input distribution and using the emulator to produce the output distribution. Finally we discuss the limitations of this approach and briefly mention how we might use similar methods to learn the model error within a framework that incorporates a data assimilation like aspect, using emulators and learning complex model error representations. We suggest future directions for research in the area that will be necessary to apply the method to more realistic numerical weather prediction models.

Use of observational and model-derived fields and regime model output statistics in mesoscale forecasting

NASA Technical Reports Server (NTRS)

Forbes, G. S.; Pielke, R. A.

1985-01-01

Various empirical and statistical weather-forecasting studies which utilize stratification by weather regime are described. Objective classification was used to determine weather regime in some studies. In other cases the weather pattern was determined on the basis of a parameter representing the physical and dynamical processes relevant to the anticipated mesoscale phenomena, such as low level moisture convergence and convective precipitation, or the Froude number and the occurrence of cold-air damming. For mesoscale phenomena already in existence, new forecasting techniques were developed. The use of cloud models in operational forecasting is discussed. Models to calculate the spatial scales of forcings and resultant response for mesoscale systems are presented. The use of these models to represent the climatologically most prevalent systems, and to perform case-by-case simulations is reviewed. Operational implementation of mesoscale data into weather forecasts, using both actual simulation output and method-output statistics is discussed.

Alternative statistical methods for interpreting airborne Alder (Alnus glutimosa (L.) Gaertner) pollen concentrations.

PubMed

González Parrado, Zulima; Valencia Barrera, Rosa M; Fuertes Rodríguez, Carmen R; Vega Maray, Ana M; Pérez Romero, Rafael; Fraile, Roberto; Fernández González, Delia

2009-01-01

This paper reports on the behaviour of Alnus glutinosa (alder) pollen grains in the atmosphere of Ponferrada (León, NW Spain) from 1995 to 2006. The study, which sought to determine the effects of various weather-related parameters on Alnus pollen counts, was performed using a volumetric method. The main pollination period for this taxon is January-February. Alder pollen is one of the eight major airborne pollen allergens found in the study area. An analysis was made of the correlation between pollen counts and major weather-related parameters over each period. In general, the strongest positive correlation was with temperature, particularly maximum temperature. During each period, peak pollen counts occurred when the maximum temperature fell within the range 9 degrees C-14 degrees C. Finally, multivariate analysis showed that the parameter exerting the greatest influence was temperature, a finding confirmed by Spearman correlation tests. Principal components analysis suggested that periods with high pollen counts were characterised by high maximum temperature, low rainfall and an absolute humidity of around 6 g m(-3). Use of this type of analysis in conjunction with other methods is essential for obtaining an accurate record of pollen-count variations over a given period.

Evapotranspiration based on equilibrated relative humidity (ETRHEQ): Evaluation over the continental U.S.

NASA Astrophysics Data System (ADS)

Rigden, Angela J.; Salvucci, Guido D.

2015-04-01

A novel method of estimating evapotranspiration (ET), referred to as the ETRHEQ method, is further developed, validated, and applied across the U.S. from 1961 to 2010. The ETRHEQ method estimates the surface conductance to water vapor transport, which is the key rate-limiting parameter of typical ET models, by choosing the surface conductance that minimizes the vertical variance of the calculated relative humidity profile averaged over the day. The ETRHEQ method, which was previously tested at five AmeriFlux sites, is modified for use at common weather stations and further validated at 20 AmeriFlux sites that span a wide range of climates and limiting factors. Averaged across all sites, the daily latent heat flux RMSE is ˜26 W·m-2 (or 15%). The method is applied across the U.S. at 305 weather stations and spatially interpolated using ANUSPLIN software. Gridded annual mean ETRHEQ ET estimates are compared with four data sets, including water balance-derived ET, machine-learning ET estimates based on FLUXNET data, North American Land Data Assimilation System project phase 2 ET, and a benchmark product that integrates 14 global ET data sets, with RMSEs ranging from 8.7 to 12.5 cm·yr-1. The ETRHEQ method relies only on data measured at weather stations, an estimate of vegetation height derived from land cover maps, and an estimate of soil thermal inertia. These data requirements allow it to have greater spatial coverage than direct measurements, greater historical coverage than satellite methods, significantly less parameter specification than most land surface models, and no requirement for calibration.

Weather impacts on single-vehicle truck crash injury severity.

PubMed

Naik, Bhaven; Tung, Li-Wei; Zhao, Shanshan; Khattak, Aemal J

2016-09-01

The focus of this paper is on illustrating the feasibility of aggregating data from disparate sources to investigate the relationship between single-vehicle truck crash injury severity and detailed weather conditions. Specifically, this paper presents: (a) a methodology that combines detailed 15-min weather station data with crash and roadway data, and (b) an empirical investigation of the effects of weather on crash-related injury severities of single-vehicle truck crashes. Random parameters ordinal and multinomial regression models were used to investigate crash injury severity under different weather conditions, taking into account the individual unobserved heterogeneity. The adopted methodology allowed consideration of environmental, roadway, and climate-related variables in single-vehicle truck crash injury severity. Results showed that wind speed, rain, humidity, and air temperature were linked with single-vehicle truck crash injury severity. Greater recorded wind speed added to the severity of injuries in single-vehicle truck crashes in general. Rain and warmer air temperatures were linked to more severe crash injuries in single-vehicle truck crashes while higher levels of humidity were linked to less severe injuries. Random parameters ordered logit and multinomial logit, respectively, revealed some individual heterogeneity in the data and showed that integrating comprehensive weather data with crash data provided useful insights into factors associated with single-vehicle truck crash injury severity. The research provided a practical method that combined comprehensive 15-min weather station data with crash and roadway data, thereby providing useful insights into crash injury severity of single-vehicle trucks. Those insights are useful for future truck driver educational programs and for truck safety in different weather conditions. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

Implementation of bayesian model averaging on the weather data forecasting applications utilizing open weather map

NASA Astrophysics Data System (ADS)

Rahmat, R. F.; Nasution, F. R.; Seniman; Syahputra, M. F.; Sitompul, O. S.

2018-02-01

Weather is condition of air in a certain region at a relatively short period of time, measured with various parameters such as; temperature, air preasure, wind velocity, humidity and another phenomenons in the atmosphere. In fact, extreme weather due to global warming would lead to drought, flood, hurricane and other forms of weather occasion, which directly affects social andeconomic activities. Hence, a forecasting technique is to predict weather with distinctive output, particullary mapping process based on GIS with information about current weather status in certain cordinates of each region with capability to forecast for seven days afterward. Data used in this research are retrieved in real time from the server openweathermap and BMKG. In order to obtain a low error rate and high accuracy of forecasting, the authors use Bayesian Model Averaging (BMA) method. The result shows that the BMA method has good accuracy. Forecasting error value is calculated by mean square error shows (MSE). The error value emerges at minumum temperature rated at 0.28 and maximum temperature rated at 0.15. Meanwhile, the error value of minimum humidity rates at 0.38 and the error value of maximum humidity rates at 0.04. Afterall, the forecasting error rate of wind speed is at 0.076. The lower the forecasting error rate, the more optimized the accuracy is.

Constraining climate sensitivity and continental versus seafloor weathering using an inverse geological carbon cycle model.

PubMed

Krissansen-Totton, Joshua; Catling, David C

2017-05-22

The relative influences of tectonics, continental weathering and seafloor weathering in controlling the geological carbon cycle are unknown. Here we develop a new carbon cycle model that explicitly captures the kinetics of seafloor weathering to investigate carbon fluxes and the evolution of atmospheric CO 2 and ocean pH since 100 Myr ago. We compare model outputs to proxy data, and rigorously constrain model parameters using Bayesian inverse methods. Assuming our forward model is an accurate representation of the carbon cycle, to fit proxies the temperature dependence of continental weathering must be weaker than commonly assumed. We find that 15-31 °C (1σ) surface warming is required to double the continental weathering flux, versus 3-10 °C in previous work. In addition, continental weatherability has increased 1.7-3.3 times since 100 Myr ago, demanding explanation by uplift and sea-level changes. The average Earth system climate sensitivity is  K (1σ) per CO 2 doubling, which is notably higher than fast-feedback estimates. These conclusions are robust to assumptions about outgassing, modern fluxes and seafloor weathering kinetics.

Constraining climate sensitivity and continental versus seafloor weathering using an inverse geological carbon cycle model

PubMed Central

Krissansen-Totton, Joshua; Catling, David C.

2017-01-01

The relative influences of tectonics, continental weathering and seafloor weathering in controlling the geological carbon cycle are unknown. Here we develop a new carbon cycle model that explicitly captures the kinetics of seafloor weathering to investigate carbon fluxes and the evolution of atmospheric CO2 and ocean pH since 100 Myr ago. We compare model outputs to proxy data, and rigorously constrain model parameters using Bayesian inverse methods. Assuming our forward model is an accurate representation of the carbon cycle, to fit proxies the temperature dependence of continental weathering must be weaker than commonly assumed. We find that 15–31 °C (1σ) surface warming is required to double the continental weathering flux, versus 3–10 °C in previous work. In addition, continental weatherability has increased 1.7–3.3 times since 100 Myr ago, demanding explanation by uplift and sea-level changes. The average Earth system climate sensitivity is  K (1σ) per CO2 doubling, which is notably higher than fast-feedback estimates. These conclusions are robust to assumptions about outgassing, modern fluxes and seafloor weathering kinetics. PMID:28530231

Development and Application of integrated monitoring platform for the Doppler Weather SA-BAND Radar

NASA Astrophysics Data System (ADS)

Zhang, Q.; Sun, J.; Zhao, C. C.; Chen, H. Y.

2017-10-01

The doppler weather SA-band radar is an important part of modern meteorological observation methods, monitoring the running status of radar and the data transmission is important.This paper introduced the composition of radar system and classification of radar data,analysed the characteristics and laws of the radar when is normal or abnormal. Using Macromedia Dreamweaver and PHP, developed the integrated monitoring platform for the doppler weather SA-band radar which could monitor the real-time radar system running status and important performance indicators such as radar power,status parameters and others on Web page,and when the status is abnormal it will trigger the audio alarm.

Global sensitivity analysis of the BSM2 dynamic influent disturbance scenario generator.

PubMed

Flores-Alsina, Xavier; Gernaey, Krist V; Jeppsson, Ulf

2012-01-01

This paper presents the results of a global sensitivity analysis (GSA) of a phenomenological model that generates dynamic wastewater treatment plant (WWTP) influent disturbance scenarios. This influent model is part of the Benchmark Simulation Model (BSM) family and creates realistic dry/wet weather files describing diurnal, weekend and seasonal variations through the combination of different generic model blocks, i.e. households, industry, rainfall and infiltration. The GSA is carried out by combining Monte Carlo simulations and standardized regression coefficients (SRC). Cluster analysis is then applied, classifying the influence of the model parameters into strong, medium and weak. The results show that the method is able to decompose the variance of the model predictions (R(2)> 0.9) satisfactorily, thus identifying the model parameters with strongest impact on several flow rate descriptors calculated at different time resolutions. Catchment size (PE) and the production of wastewater per person equivalent (QperPE) are two parameters that strongly influence the yearly average dry weather flow rate and its variability. Wet weather conditions are mainly affected by three parameters: (1) the probability of occurrence of a rain event (Llrain); (2) the catchment size, incorporated in the model as a parameter representing the conversion from mm rain · day(-1) to m(3) · day(-1) (Qpermm); and, (3) the quantity of rain falling on permeable areas (aH). The case study also shows that in both dry and wet weather conditions the SRC ranking changes when the time scale of the analysis is modified, thus demonstrating the potential to identify the effect of the model parameters on the fast/medium/slow dynamics of the flow rate. The paper ends with a discussion on the interpretation of GSA results and of the advantages of using synthetic dynamic flow rate data for WWTP influent scenario generation. This section also includes general suggestions on how to use the proposed methodology to any influent generator to adapt the created time series to a modeller's demands.

Acute Low Back Pain? Do Not Blame the Weather-A Case-Crossover Study.

PubMed

Beilken, Keira; Hancock, Mark J; Maher, Chris G; Li, Qiang; Steffens, Daniel

2017-06-01

To investigate the influence of various weather parameters on the risk of developing a low back pain (LBP) episode. Case-crossover study. Primary care clinics in Sydney, Australia. 981 participants with a new episode of acute LBP. Weather parameters were obtained from the Australian Bureau of Meteorology. Odds ratios (OR) and 95% confidence intervals (95% CI) were derived comparing two exposure variables in the case window-(1) the average of the weather variable for the day prior to pain onset and (2) the change in the weather variable from 2 days prior to 1 day prior to pain onset-with exposures in two control windows (1 week and 1 month before the case window). The weather parameters of precipitation, humidity, wind speed, wind gust, wind direction, and air pressure were not associated with the onset of acute LBP. For one of the four analyses, higher temperature slightly increased the odds of pain onset. Common weather parameters that had been previously linked to musculoskeletal pain, such as precipitation, humidity, wind speed, wind gust, wind direction, and air pressure, do not increase the risk of onset for LBP. © 2016 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Using genetic algorithms to achieve an automatic and global optimization of analogue methods for statistical downscaling of precipitation

NASA Astrophysics Data System (ADS)

Horton, Pascal; Weingartner, Rolf; Obled, Charles; Jaboyedoff, Michel

2017-04-01

Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circulation, are likely to result in similar local or regional weather conditions. These methods consist of sampling a certain number of past situations, based on different synoptic-scale meteorological variables (predictors), in order to construct a probabilistic prediction for a local weather variable of interest (predictand). They are often used for daily precipitation prediction, either in the context of real-time forecasting, reconstruction of past weather conditions, or future climate impact studies. The relationship between predictors and predictands is defined by several parameters (predictor variable, spatial and temporal windows used for the comparison, analogy criteria, and number of analogues), which are often calibrated by means of a semi-automatic sequential procedure that has strong limitations. AMs may include several subsampling levels (e.g. first sorting a set of analogs in terms of circulation, then restricting to those with similar moisture status). The parameter space of the AMs can be very complex, with substantial co-dependencies between the parameters. Thus, global optimization techniques are likely to be necessary for calibrating most AM variants, as they can optimize all parameters of all analogy levels simultaneously. Genetic algorithms (GAs) were found to be successful in finding optimal values of AM parameters. They allow taking into account parameters inter-dependencies, and selecting objectively some parameters that were manually selected beforehand (such as the pressure levels and the temporal windows of the predictor variables), and thus obviate the need of assessing a high number of combinations. The performance scores of the optimized methods increased compared to reference methods, and this even to a greater extent for days with high precipitation totals. The resulting parameters were found to be relevant and spatially coherent. Moreover, they were obtained automatically and objectively, which reduces efforts invested in exploration attempts when adapting the method to a new region or for a new predictand. In addition, the approach allowed for new degrees of freedom, such as a weighting between the pressure levels, and non overlapping spatial windows. Genetic algorithms were then used further in order to automatically select predictor variables and analogy criteria. This resulted in interesting outputs, providing new predictor-criterion combinations. However, some limitations of the approach were encountered, and the need of the expert input is likely to remain necessary. Nevertheless, letting GAs exploring a dataset for the best predictor for a predictand of interest is certainly a useful tool, particularly when applied for a new predictand or a new region under different climatic characteristics.

An Illustration of Determining Quantitatively the Rock Mass Quality Parameters of the Hoek-Brown Failure Criterion

NASA Astrophysics Data System (ADS)

Wu, Li; Adoko, Amoussou Coffi; Li, Bo

2018-04-01

In tunneling, determining quantitatively the rock mass strength parameters of the Hoek-Brown (HB) failure criterion is useful since it can improve the reliability of the design of tunnel support systems. In this study, a quantitative method is proposed to determine the rock mass quality parameters of the HB failure criterion, namely the Geological Strength Index (GSI) and the disturbance factor ( D) based on the structure of drilling core and weathering condition of rock mass combined with acoustic wave test to calculate the strength of rock mass. The Rock Mass Structure Index and the Rock Mass Weathering Index are used to quantify the GSI while the longitudinal wave velocity ( V p) is employed to derive the value of D. The DK383+338 tunnel face of Yaojia tunnel of Shanghai-Kunming passenger dedicated line served as illustration of how the methodology is implemented. The values of the GSI and D are obtained using the HB criterion and then using the proposed method. The measured in situ stress is used to evaluate their accuracy. To this end, the major and minor principal stresses are calculated based on the GSI and D given by HB criterion and the proposed method. The results indicated that both methods were close to the field observation which suggests that the proposed method can be used for determining quantitatively the rock quality parameters, as well. However, these results remain valid only for rock mass quality and rock type similar to those of the DK383+338 tunnel face of Yaojia tunnel.

A stability analysis of AVE-4 severe weather soundings

NASA Technical Reports Server (NTRS)

Johnson, D. L.

1982-01-01

The stability and vertical structure of an average severe storm sounding, consisting of both thermodynamic and wind vertical profiles, were investigated to determine if they could be distinguished from an average lag sounding taken 3 to 6 hours prior to severe weather occurrence. The term average is defined here to indicate the arithmetic mean of a parameter, as a function of altitude, determined from a large number of available observations taken either close to severe weather occurrence, or else more than 3 hours before it occurs. The investigative computations were also done to help determine if a severe storm forecast or index could possibly be used or developed. These mean vertical profiles of thermodynamic and wind parameters as a function of severity of the weather, determined from manually digitized radar (MDR) categories are presented. Profile differences and stability index differences are presented along with the development of the Johnson Lag Index (JLI) which is determined entirely upon environmental vertical parameter differences between conditions 3 hours prior to severe weather, and severe weather itself.

Intelligent Weather Agent

NASA Technical Reports Server (NTRS)

Spirkovska, Liljana (Inventor)

2006-01-01

Method and system for automatically displaying, visually and/or audibly and/or by an audible alarm signal, relevant weather data for an identified aircraft pilot, when each of a selected subset of measured or estimated aviation situation parameters, corresponding to a given aviation situation, has a value lying in a selected range. Each range for a particular pilot may be a default range, may be entered by the pilot and/or may be automatically determined from experience and may be subsequently edited by the pilot to change a range and to add or delete parameters describing a situation for which a display should be provided. The pilot can also verbally activate an audible display or visual display of selected information by verbal entry of a first command or a second command, respectively, that specifies the information required.

SPAGETTA, a Gridded Weather Generator: Calibration, Validation and its Use for Future Climate

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Rotach, Mathias W.; Huth, Radan

2017-04-01

Spagetta is a new (started in 2016) stochastic multi-site multi-variate weather generator (WG). It can produce realistic synthetic daily (or monthly, or annual) weather series representing both present and future climate conditions at multiple sites (grids or stations irregularly distributed in space). The generator, whose model is based on the Wilks' (1999) multi-site extension of the parametric (Richardson's type) single site M&Rfi generator, may be run in two modes: In the first mode, it is run as a classical generator, which is calibrated in the first step using weather data from multiple sites, and only then it may produce arbitrarily long synthetic time series mimicking the spatial and temporal structure of the calibration weather data. To generate the weather series representing the future climate, the WG parameters are modified according to the climate change scenario, typically derived from GCM or RCM simulations. In the second mode, the user provides only basic information (not necessarily to be realistic) on the temporal and spatial auto-correlation structure of the surface weather variables and their mean annual cycle; the generator itself derives the parameters of the underlying autoregressive model, which produces the multi-site weather series. In the latter mode of operation, the user is allowed to prescribe the spatially varying trend, which is superimposed to the values produced by the generator; this feature has been implemented for use in developing the methodology for assessing significance of trends in multi-site weather series (for more details see another EGU-2017 contribution: Huth and Dubrovsky, 2017, Evaluating collective significance of climatic trends: A comparison of methods on synthetic data; EGU2017-4993). This contribution will focus on the first (classical) mode. The poster will present (a) model of the generator, (b) results of the validation tests made in terms of the spatial hot/cold/dry/wet spells, and (c) results of the pilot climate change impact experiment, in which (i) the WG parameters representing the spatial and temporal variability are modified using the climate change scenarios and then (ii) the effect on the above spatial validation indices derived from the synthetic series produced by the modified WG is analysed. In this experiment, the generator is calibrated using the E-OBS gridded daily weather data for several European regions, and the climate change scenarios are derived from the selected RCM simulation (taken from the CORDEX database).

Does temperature nudging overwhelm aerosol radiative effects in regional integrated climate models?

EPA Science Inventory

For over two decades, data assimilation (popularly known as nudging) methods have been used for improving regional weather and climate simulations by reducing model biases in meteorological parameters and processes. Similar practice is also popular in many regional integrated met...

Assessment of Slope Stability of Various Cut Slopes with Effects of Weathering by Using Slope Stability Probability Classification (SSPC)

NASA Astrophysics Data System (ADS)

Ersöz, Timur; Topal, Tamer

2017-04-01

Rocks containing pore spaces, fractures, joints, bedding planes and faults are prone to weathering due to temperature differences, wetting-drying, chemistry of solutions absorbed, and other physical and chemical agents. Especially cut slopes are very sensitive to weathering activities because of disturbed rock mass and topographical condition by excavation. During and right after an excavation process of a cut slope, weathering and erosion may act on this newly exposed rock material. These acting on the material may degrade and change its properties and the stability of the cut slope in its engineering lifetime. In this study, the effect of physical and chemical weathering agents on shear strength parameters of the rocks are investigated in order to observe the differences between weathered and unweathered rocks. Also, slope stability assessment of cut slopes affected by these weathering agents which may disturb the parameters like strength, cohesion, internal friction angle, unit weight, water absorption and porosity are studied. In order to compare the condition of the rock materials and analyze the slope stability, the parameters of weathered and fresh rock materials are found with in-situ tests such as Schmidt hammer and laboratory tests like uniaxial compressive strength, point load and direct shear. Moreover, slake durability and methylene blue tests are applied to investigate the response of the rock to weathering and presence of clays in rock materials, respectively. In addition to these studies, both rock strength parameters and any kind of failure mechanism are determined by probabilistic approach with the help of SSPC system. With these observations, the performances of the weathered and fresh zones of the cut slopes are evaluated and 2-D slope stability analysis are modeled with further recommendations for the cut slopes. Keywords: 2-D Modeling, Rock Strength, Slope Stability, SSPC, Weathering

Tethered Satellites as Enabling Platforms for an Operational Space Weather Monitoring System

NASA Technical Reports Server (NTRS)

Krause, L. Habash; Gilchrist, B. E.; Bilen, S.; Owens, J.; Voronka, N.; Furhop, K.

2013-01-01

Space weather nowcasting and forecasting models require assimilation of near-real time (NRT) space environment data to improve the precision and accuracy of operational products. Typically, these models begin with a climatological model to provide "most probable distributions" of environmental parameters as a function of time and space. The process of NRT data assimilation gently pulls the climate model closer toward the observed state (e.g. via Kalman smoothing) for nowcasting, and forecasting is achieved through a set of iterative physics-based forward-prediction calculations. The issue of required space weather observatories to meet the spatial and temporal requirements of these models is a complex one, and we do not address that with this poster. Instead, we present some examples of how tethered satellites can be used to address the shortfalls in our ability to measure critical environmental parameters necessary to drive these space weather models. Examples include very long baseline electric field measurements, magnetized ionospheric conductivity measurements, and the ability to separate temporal from spatial irregularities in environmental parameters. Tethered satellite functional requirements will be presented for each space weather parameter considered in this study.

Extended T-index models for glacier surface melting: a case study from Chorabari Glacier, Central Himalaya, India

NASA Astrophysics Data System (ADS)

Karakoti, Indira; Kesarwani, Kapil; Mehta, Manish; Dobhal, D. P.

2016-10-01

Two enhanced temperature-index (T-index) models are proposed by incorporating meteorological parameters viz. relative humidity, wind speed and net radiation. The models are an attempt to explore different climatic variables other than temperature affecting glacier surface melting. Weather data were recorded at Chorabari Glacier using an automatic weather station during the summers of 2010 (July 10 to September 10) and 2012 (June 10 to October 25). The modelled surface melt is validated against the measured point surface melting at the snout. Performance of the developed models is evaluated by comparing with basic temperature-index model and is quantified through different efficiency criteria. The results suggest that proposed models yield considerable improvement in surface melt simulation . Consequently, the study reveals that glacier surface melt depends not only on temperature but also on weather parameters viz. relative humidity, wind speed and net radiation play a significant role in glacier surface melting. This approach provides a major improvement on basic temperature-index method and offers an alternative to energy balance model.

BLAST: Building energy simulation in Hong Kong

NASA Astrophysics Data System (ADS)

Fong, Sai-Keung

1999-11-01

The characteristics of energy use in buildings under local weather conditions were studied and evaluated using the energy simulation program BLAST-3.0. The parameters used in the energy simulation for the study and evaluation include the architectural features, different internal building heat load settings and weather data. In this study, mathematical equations and the associated coefficients useful to the industry were established. A technology for estimating energy use in buildings under local weather conditions was developed by using the results of this study. A weather data file of Typical Meteorological Years (TMY) has been compiled for building energy studies by analyzing and evaluating the weather of Hong Kong from the year 1979 to 1988. The weather data file TMY and the example weather years 1980 and 1988 were used by BLAST-3.0 to evaluate and study the energy use in different buildings. BLAST-3.0 was compared with other building energy simulation and approximation methods: Bin method and Degree Days method. Energy use in rectangular compartments of different volumes varying from 4,000 m3 to 40,000 m3 with different aspect ratios were analyzed. The use of energy in buildings with concrete roofs was compared with those with glass roofs at indoor temperature 21°C, 23°C and 25°C. Correlation relationships among building energy, space volume, monthly mean temperature and solar radiation were derived and investigated. The effects of space volume, monthly mean temperature and solar radiation on building energy were evaluated. The coefficients of the mathematical relationships between space volume and energy use in a building were computed and found satisfactory. The calculated coefficients can be used for quick estimation of energy use in buildings under similar situations. To study energy use in buildings, the cooling load per floor area against room volume was investigated. The case of an air-conditioned single compartment with 5 m ceiling height was evaluated. It was found that the supply of cool air to the lower portion of the compartment provided significant performance of space cooling. The mathematical relationships between different shading patterns and different glass window to wall ratios of single compartments were established to provide a guide for easy approximation of energy use under similar conditions. In addition, the Overall Thermal Transfer Values (OTTV) for the compartments were studied. The monthly and annual energy use of three realistic buildings were investigated. They were a commercial building, an industrial building and a dual-purpose building. The cooling loads per floor area for the buildings were studied and the OTTV were evaluated by two different methods. Sensitivity analysis was carried out to investigate the impact of the parameters of internal heat gains on the energy use of an academic building. It was found that there was major influence of indoor temperature setting on building energy use The performances of using the local weather data file of TMY and example weather years 1980 and 1989 were evaluated. TMY was found to be the most suitable for energy simulation while the weather years 1980 and 1989 yielded good results.

Changes in fire weather distributions: effects on predicted fire behavior

Treesearch

Lucy A. Salazar; Larry S. Bradshaw

1984-01-01

Data that represent average worst fire weather for a particular area are used to index daily fire danger; however, they do not account for different locations or diurnal weather changes that significantly affect fire behavior potential. To study the effects that selected changes in weather databases have on computed fire behavior parameters, weather data for the...

Linking the Weather Generator with Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Farda, Ales; Skalak, Petr; Huth, Radan

2013-04-01

One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking the stochastic weather generator with the climate model output. The present contribution, in which the parametric daily surface weather generator (WG) M&Rfi is linked to the RCM output, follows two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate Regional Climate Model at 25 km resolution. The WG parameters are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series (including probability of wet day occurrence). (2) Presenting a methodology for linking the WG with RCM output. This methodology, which is based on merging information from observations and RCM, may be interpreted as a downscaling procedure, whose product is a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series in the first step, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with gridded RCM weather series and spatially scarcer observations. The quality of the weather series produced by the resultant gridded WG will be assessed in terms of selected climatic characteristics (focusing on characteristics related to variability and extremes of surface temperature and precipitation). Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

Concept for an International Standard related to Space Weather Effects on Space Systems

NASA Astrophysics Data System (ADS)

Tobiska, W. Kent; Tomky, Alyssa

There is great interest in developing an international standard related to space weather in order to specify the tools and parameters needed for space systems operations. In particular, a standard is important for satellite operators who may not be familiar with space weather. In addition, there are others who participate in space systems operations that would also benefit from such a document. For example, the developers of software systems that provide LEO satellite orbit determination, radio communication availability for scintillation events (GEO-to-ground L and UHF bands), GPS uncertainties, and the radiation environment from ground-to-space for commercial space tourism. These groups require recent historical data, current epoch specification, and forecast of space weather events into their automated or manual systems. Other examples are national government agencies that rely on space weather data provided by their organizations such as those represented in the International Space Environment Service (ISES) group of 14 national agencies. Designers, manufacturers, and launchers of space systems require real-time, operational space weather parameters that can be measured, monitored, or built into automated systems. Thus, a broad scope for the document will provide a useful international standard product to a variety of engineering and science domains. The structure of the document should contain a well-defined scope, consensus space weather terms and definitions, and internationally accepted descriptions of the main elements of space weather, its sources, and its effects upon space systems. Appendices will be useful for describing expanded material such as guidelines on how to use the standard, how to obtain specific space weather parameters, and short but detailed descriptions such as when best to use some parameters and not others; appendices provide a path for easily updating the standard since the domain of space weather is rapidly changing with new advances in scientific and engineering understanding. We present a draft outline that can be used as the basis for such a standard.

Analysis and improved design considerations for airborne pulse Doppler radar signal processing in the detection of hazardous windshear

NASA Technical Reports Server (NTRS)

Lee, Jonggil

1990-01-01

High resolution windspeed profile measurements are needed to provide reliable detection of hazardous low altitude windshear with an airborne pulse Doppler radar. The system phase noise in a Doppler weather radar may degrade the spectrum moment estimation quality and the clutter cancellation capability which are important in windshear detection. Also the bias due to weather return Doppler spectrum skewness may cause large errors in pulse pair spectral parameter estimates. These effects are analyzed for the improvement of an airborne Doppler weather radar signal processing design. A method is presented for the direct measurement of windspeed gradient using low pulse repetition frequency (PRF) radar. This spatial gradient is essential in obtaining the windshear hazard index. As an alternative, the modified Prony method is suggested as a spectrum mode estimator for both the clutter and weather signal. Estimation of Doppler spectrum modes may provide the desired windshear hazard information without the need of any preliminary processing requirement such as clutter filtering. The results obtained by processing a NASA simulation model output support consideration of mode identification as one component of a windshear detection algorithm.

Improved estimation of heavy rainfall by weather radar after reflectivity correction and accounting for raindrop size distribution variability

NASA Astrophysics Data System (ADS)

Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

2015-04-01

Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z-R) and radar reflectivity-specific attenuation (Z-k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the disdrometer information, the best results were obtained in case no differentiation between precipitation type (convective, stratiform and undefined) was made, increasing the event accumulations to more than 80% of those observed by gauges. For the randomly optimized procedure, radar precipitation estimates further improve and closely resemble observations in case one differentiates between precipitation type. However, the optimal parameter sets are very different from those derived from disdrometer observations. It is therefore questionable if single disdrometer observations are suitable for large-scale quantitative precipitation estimation, especially if the disdrometer is located relatively far away from the main rain event, which was the case in this study. In conclusion, this study shows the benefit of applying detailed error correction methods to improve the quality of the weather radar product, but also confirms the need to be cautious using locally obtained disdrometer measurements.

The impact of reflectivity correction and accounting for raindrop size distribution variability to improve precipitation estimation by weather radar for an extreme low-land mesoscale convective system

NASA Astrophysics Data System (ADS)

Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

2014-11-01

Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z - R) and radar reflectivity-specific attenuation (Z - k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the disdrometer information, the best results were obtained in case no differentiation between precipitation type (convective, stratiform and undefined) was made, increasing the event accumulations to more than 80% of those observed by gauges. For the randomly optimized procedure, radar precipitation estimates further improve and closely resemble observations in case one differentiates between precipitation type. However, the optimal parameter sets are very different from those derived from disdrometer observations. It is therefore questionable if single disdrometer observations are suitable for large-scale quantitative precipitation estimation, especially if the disdrometer is located relatively far away from the main rain event, which was the case in this study. In conclusion, this study shows the benefit of applying detailed error correction methods to improve the quality of the weather radar product, but also confirms the need to be cautious using locally obtained disdrometer measurements.

Portfolio optimization for seed selection in diverse weather scenarios.

PubMed

Marko, Oskar; Brdar, Sanja; Panić, Marko; Šašić, Isidora; Despotović, Danica; Knežević, Milivoje; Crnojević, Vladimir

2017-01-01

The aim of this work was to develop a method for selection of optimal soybean varieties for the American Midwest using data analytics. We extracted the knowledge about 174 varieties from the dataset, which contained information about weather, soil, yield and regional statistical parameters. Next, we predicted the yield of each variety in each of 6,490 observed subregions of the Midwest. Furthermore, yield was predicted for all the possible weather scenarios approximated by 15 historical weather instances contained in the dataset. Using predicted yields and covariance between varieties through different weather scenarios, we performed portfolio optimisation. In this way, for each subregion, we obtained a selection of varieties, that proved superior to others in terms of the amount and stability of yield. According to the rules of Syngenta Crop Challenge, for which this research was conducted, we aggregated the results across all subregions and selected up to five soybean varieties that should be distributed across the network of seed retailers. The work presented in this paper was the winning solution for Syngenta Crop Challenge 2017.

Portfolio optimization for seed selection in diverse weather scenarios

PubMed Central

Brdar, Sanja; Panić, Marko; Šašić, Isidora; Despotović, Danica; Knežević, Milivoje; Crnojević, Vladimir

2017-01-01

The aim of this work was to develop a method for selection of optimal soybean varieties for the American Midwest using data analytics. We extracted the knowledge about 174 varieties from the dataset, which contained information about weather, soil, yield and regional statistical parameters. Next, we predicted the yield of each variety in each of 6,490 observed subregions of the Midwest. Furthermore, yield was predicted for all the possible weather scenarios approximated by 15 historical weather instances contained in the dataset. Using predicted yields and covariance between varieties through different weather scenarios, we performed portfolio optimisation. In this way, for each subregion, we obtained a selection of varieties, that proved superior to others in terms of the amount and stability of yield. According to the rules of Syngenta Crop Challenge, for which this research was conducted, we aggregated the results across all subregions and selected up to five soybean varieties that should be distributed across the network of seed retailers. The work presented in this paper was the winning solution for Syngenta Crop Challenge 2017. PMID:28863173

Effects of weathering on performance of intumescent coatings for structure fire protection in the wildland-urban interface

NASA Astrophysics Data System (ADS)

Bahrani, Babak

The objective of this study was to investigate the effects of weathering on the performance of intumescent fire-retardant coatings on wooden products. The weathering effects included primary (solar irradiation, moisture, and temperature) and secondary (environmental contaminants) parameters at various time intervals. Wildland urban interface (WUI) fires have been an increasing threat to lives and properties. Existing solutions to mitigate the damages caused by WUI fires include protecting the structures from ignition and minimizing the fire spread from one structure to another. These solutions can be divided into two general categories: active fire protection systems and passive fire protection systems. Passive systems are either using pre-applied wetting agents (water, gel, or foam) or adding an extra layer (composite wraps or coatings). Fire-retardant coating treatment methods can be divided into impregnated (penetrant) and intumescent categories. Intumescent coatings are easy to apply, economical, and have a better appearance in comparison to other passive fire protection methods, and are the main focus of this study. There have been limited studies conducted on the application of intumescent coatings on wooden structures and their performance after long-term weathering exposure. The main concerns of weathering effects are: 1) the reduction of ignition resistance of the coating layer after weathering; and 2) the fire properties of coatings after weathering since coatings might contribute as a combustible fuel and assist the fire growth after ignition. Three intumescent coatings were selected and exposed to natural weathering conditions in three different time intervals. Two types of tests were performed on the specimens: a combustibility test consisted of a bench-scale performance evaluation using a Cone Calorimeter, and a thermal decomposition test using Simultaneous Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA) method (also known as SDT). For each coating type and weathering period, three different radiative heat flux levels were used in the combustibility tests. Data obtained from the tests, including flammability and thermal properties, were gathered, analyzed, and compared to non-weathered specimens. The results revealed visible effects of weathering on pre (and up to)-ignition flammability and intumescent properties, especially decreases in Time-to-Ignition (TTI), Time-to-Intumescence (tintu.), and (maximum) Intumescence Height (Hintu.) values in weathered specimens. These results showed that the ignition resistance of the coating layers decreased after weathering exposure. On the other hand, the obtained results from weathered specimens for the post-ignition flammability properties, especially Peak Heat Release Rate (PHRR) and Effective Heat of Combustion (EHC) did not show a significant difference in comparison to the non-weathered samples. These results demonstrated that the weathered coating layer would not likely to act as an additional combustible fuel to increase fire spread.

Space Weather and the State of Cardiovascular System of a Healthy Human Being

NASA Astrophysics Data System (ADS)

Samsonov, S. N.; Manykina, V. I.; Krymsky, G. F.; Petrova, P. G.; Palshina, A. M.; Vishnevsky, V. V.

The term "space weather" characterizes a state of the near-Earth environmental space. An organism of human being represents an open system so the change of conditions in the environment including the near-Earth environmental space influences the health state of a human being.In recent years many works devoted to the effect of space weather on the life on the Earth, and the degree of such effect has been represented from a zero-order up to apocalypse. To reveal a real effect of space weather on the health of human being the international Russian- Ukrainian experiment "Geliomed" is carried out since 2005 (http://geliomed.immsp.kiev.ua) [Vishnevsky et al., 2009]. The analysis of observational set of data has allowed to show a synchronism and globality of such effect (simultaneous manifestation of space weather parameters in a state of cardiovascular system of volunteer groups removed from each other at a distance over 6000 km). The response of volunteer' cardiovascular system to the changes of space weather parameters were observed even at insignificant values of the Earth's geomagnetic field. But even at very considerable disturbances of space weather parameters a human being healthy did not feel painful symptoms though measurements of objective physiological indices showed their changes.

Some Advances in Downscaling Probabilistic Climate Forecasts for Agricultural Decision Support

NASA Astrophysics Data System (ADS)

Han, E.; Ines, A.

2015-12-01

Seasonal climate forecasts, commonly provided in tercile-probabilities format (below-, near- and above-normal), need to be translated into more meaningful information for decision support of practitioners in agriculture. In this paper, we will present two new novel approaches to temporally downscale probabilistic seasonal climate forecasts: one non-parametric and another parametric method. First, the non-parametric downscaling approach called FResampler1 uses the concept of 'conditional block sampling' of weather data to create daily weather realizations of a tercile-based seasonal climate forecasts. FResampler1 randomly draws time series of daily weather parameters (e.g., rainfall, maximum and minimum temperature and solar radiation) from historical records, for the season of interest from years that belong to a certain rainfall tercile category (e.g., being below-, near- and above-normal). In this way, FResampler1 preserves the covariance between rainfall and other weather parameters as if conditionally sampling maximum and minimum temperature and solar radiation if that day is wet or dry. The second approach called predictWTD is a parametric method based on a conditional stochastic weather generator. The tercile-based seasonal climate forecast is converted into a theoretical forecast cumulative probability curve. Then the deviates for each percentile is converted into rainfall amount or frequency or intensity to downscale the 'full' distribution of probabilistic seasonal climate forecasts. Those seasonal deviates are then disaggregated on a monthly basis and used to constrain the downscaling of forecast realizations at different percentile values of the theoretical forecast curve. As well as the theoretical basis of the approaches we will discuss sensitivity analysis (length of data and size of samples) of them. In addition their potential applications for managing climate-related risks in agriculture will be shown through a couple of case studies based on actual seasonal climate forecasts for: rice cropping in the Philippines and maize cropping in India and Kenya.

Real-time Retrieving Atmospheric Parameters from Multi-GNSS Constellations

NASA Astrophysics Data System (ADS)

Li, X.; Zus, F.; Lu, C.; Dick, G.; Ge, M.; Wickert, J.; Schuh, H.

2016-12-01

The multi-constellation GNSS (e.g. GPS, GLONASS, Galileo, and BeiDou) bring great opportunities and challenges for real-time retrieval of atmospheric parameters for supporting numerical weather prediction (NWP) nowcasting or severe weather event monitoring. In this study, the observations from different GNSS are combined together for atmospheric parameter retrieving based on the real-time precise point positioning technique. The atmospheric parameters retrieved from multi-GNSS observations, including zenith total delay (ZTD), integrated water vapor (IWV), horizontal gradient (especially high-resolution gradient estimates) and slant total delay (STD), are carefully analyzed and evaluated by using the VLBI, radiosonde, water vapor radiometer and numerical weather model to independently validate the performance of individual GNSS and also demonstrate the benefits of multi-constellation GNSS for real-time atmospheric monitoring. Numerous results show that the multi-GNSS processing can provide real-time atmospheric products with higher accuracy, stronger reliability and better distribution, which would be beneficial for atmospheric sounding systems, especially for nowcasting of extreme weather.

Development of an Open Source, Air-Deployable Weather Station

NASA Astrophysics Data System (ADS)

Krejci, A.; Lopez Alcala, J. M.; Nelke, M.; Wagner, J.; Udell, C.; Higgins, C. W.; Selker, J. S.

2017-12-01

We created a packaged weather station intended to be deployed in the air on tethered systems. The device incorporates lightweight sensors and parts and runs for up to 24 hours off of lithium polymer batteries, allowing the entire package to be supported by a thin fiber. As the fiber does not provide a stable platform, additional data (pitch and roll) from typical weather parameters (e.g. temperature, pressure, humidity, wind speed, and wind direction) are determined using an embedded inertial motion unit. All designs are open sourced including electronics, CAD drawings, and descriptions of assembly and can be found on the OPEnS lab website at http://www.open-sensing.org/lowcost-weather-station/. The Openly Published Environmental Sensing Lab (OPEnS: Open-Sensing.org) expands the possibilities of scientific observation of our Earth, transforming the technology, methods, and culture by combining open-source development and cutting-edge technology. New OPEnS labs are now being established in India, France, Switzerland, the Netherlands, and Ghana.

Predicting lodgepole pine site index from climatic parameters in Alberta.

Treesearch

Robert A. Monserud; Shongming Huang; Yuqing Yang

2006-01-01

We sought to evaluate the impact of climatic variables on site productivity of lodgepole pine (Pinus contorta var. latifolia Engelm.) for the province of Alberta. Climatic data were obtained from the Alberta Climate Model, which is based on 30-year normals from the provincial weather station network. Mapping methods were based...

Construction of Gridded Daily Weather Data and its Use in Central-European Agroclimatic Study

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Trnka, M.; Skalak, P.

2013-12-01

The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series, interpolated, and then modified according to the GCM- or RCM-based climate change scenarios. The present contribution, in which the parametric daily weather generator M&Rfi is linked to the high-resolution RCM output (ALADIN-Climate/CZ model) and GCM-based climate change scenarios, consists of two parts: The first part focuses on a methodology. Firstly, the gridded WG representing the baseline climate is created by merging information from observations and high resolution RCM outputs. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with RCM-simulated weather series vs. spatially scarcer observations. To represent the future climate, the WG parameters are modified according to the 'WG-friendly' climate change scenarios. These scenarios are defined in terms of changes in WG parameters and include - apart from changes in the means - changes in WG parameters, which represent the additional characteristics of the weather series (e.g. probability of wet day occurrence and lag-1 autocorrelation of daily mean temperature). The WG-friendly scenarios for the present experiment are based on comparison of future vs baseline surface weather series simulated by GCMs from a CMIP3 database. The second part will present results of climate change impact study based on an above methodology applied to Central Europe. The changes in selected climatic (focusing on the extreme precipitation and temperature characteristics) and agroclimatic (including number of days during vegetation season with heat and drought stresses) characteristics will be analysed. In discussing the results, the emphasis will be put on 'added value' of various aspects of above methodology (e.g. inclusion of changes in 'advanced' WG parameters into the climate change scenarios). Acknowledgements: The present experiment is made within the frame of projects WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR), ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), and VALUE (COST ES 1102 action).

Assessing the implementation of bias correction in the climate prediction

NASA Astrophysics Data System (ADS)

Nadrah Aqilah Tukimat, Nurul

2018-04-01

An issue of the climate changes nowadays becomes trigger and irregular. The increment of the greenhouse gases (GHGs) emission into the atmospheric system day by day gives huge impact to the fluctuated weather and global warming. It becomes significant to analyse the changes of climate parameters in the long term. However, the accuracy in the climate simulation is always be questioned to control the reliability of the projection results. Thus, the Linear Scaling (LS) as a bias correction method (BC) had been applied to treat the gaps between observed and simulated results. About two rainfall stations were selected in Pahang state there are Station Lubuk Paku and Station Temerloh. Statistical Downscaling Model (SDSM) used to perform the relationship between local weather and atmospheric parameters in projecting the long term rainfall trend. The result revealed the LS was successfully to reduce the error up to 3% and produced better climate simulated results.

Uranium adsorption on weathered schist - Intercomparison of modeling approaches

USGS Publications Warehouse

Payne, T.E.; Davis, J.A.; Ochs, M.; Olin, M.; Tweed, C.J.

2004-01-01

Experimental data for uranium adsorption on a complex weathered rock were simulated by twelve modelling teams from eight countries using surface complexation (SC) models. This intercomparison was part of an international project to evaluate the present capabilities and limitations of SC models in representing sorption by geologic materials. The models were assessed in terms of their predictive ability, data requirements, number of optimised parameters, ability to simulate diverse chemical conditions and transferability to other substrates. A particular aim was to compare the generalised composite (GC) and component additivity (CA) approaches for modelling sorption by complex substrates. Both types of SC models showed a promising capability to simulate sorption data obtained across a range of chemical conditions. However, the models incorporated a wide variety of assumptions, particularly in terms of input parameters such as site densities and surface site types. Furthermore, the methods used to extrapolate the model simulations to different weathered rock samples collected at the same field site tended to be unsatisfactory. The outcome of this modelling exercise provides an overview of the present status of adsorption modelling in the context of radionuclide migration as practised in a number of countries worldwide.

Sensitivity of DIVWAG to Variations in Weather Parameters

DTIC Science & Technology

1976-04-01

1 18. SUPPLEMENTARY NOTES 1 19. KEY WORDS (Continue on reverse aide if necessary and Identify by block number) DIVWAG WAR GAME SIMULATION...simulation of a Division Level War Game , to determine the signif- icance of varying battlefield parameters; i.e., artillery parameters, troop and...The only Red artillery weapons doing better in bad weather are the 130MM guns , but this statistic is tempered by the few casualties occuring in

Weatherization and Indoor Air Quality: Measured Impacts in Single Family Homes Under the Weatherization Assistance Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pigg, Scott; Cautley, Dan; Francisco, Paul

2014-09-01

This report summarizes findings from a national field study of indoor air quality parameters in homes treated under the Weatherization Assistance Program (WAP). The study involved testing and monitoring in 514 single-family homes (including mobile homes) located in 35 states and served by 88 local weatherization agencies.

Atmospheric mold spore counts in relation to meteorological parameters

NASA Astrophysics Data System (ADS)

Katial, R. K.; Zhang, Yiming; Jones, Richard H.; Dyer, Philip D.

Fungal spore counts of Cladosporium, Alternaria, and Epicoccum were studied during 8 years in Denver, Colorado. Fungal spore counts were obtained daily during the pollinating season by a Rotorod sampler. Weather data were obtained from the National Climatic Data Center. Daily averages of temperature, relative humidity, daily precipitation, barometric pressure, and wind speed were studied. A time series analysis was performed on the data to mathematically model the spore counts in relation to weather parameters. Using SAS PROC ARIMA software, a regression analysis was performed, regressing the spore counts on the weather variables assuming an autoregressive moving average (ARMA) error structure. Cladosporium was found to be positively correlated (P<0.02) with average daily temperature, relative humidity, and negatively correlated with precipitation. Alternaria and Epicoccum did not show increased predictability with weather variables. A mathematical model was derived for Cladosporium spore counts using the annual seasonal cycle and significant weather variables. The model for Alternaria and Epicoccum incorporated the annual seasonal cycle. Fungal spore counts can be modeled by time series analysis and related to meteorological parameters controlling for seasonallity; this modeling can provide estimates of exposure to fungal aeroallergens.

Human beings' adaptability to extreme environmental changes from medical and physical points of view

NASA Astrophysics Data System (ADS)

Khabarova, Olga; Ragulskaya, Maria; Dimitrova, Svetla; Safaraly-Oghlu Babayev, Elchin; Samsonov, Sergey; Med. Dimitry Markov, Of; Nazarova, Of Med. Olga N.; Rudenchik, Evgeny

The question about features of human reaction on the sharp environmental physical activity (EPA) changes is considered by international group of physicists and physicians on the base of results of monitoring of human health state in different cities spread on latitude and longitude. The typical reaction of human body on the influences, exceeding the organisms' ability to adaptation, is of stress-reaction character. From medical point of view there is no significant difference for human body -what external (EPA) agent shocked an organism (emotional or some physical threats). First attempt of the organism to restore its homeostasis is stress-reaction, being universal for many stress-factors. Its main stages (such as alarm, resistance, and exhaustion) are detectable by different medical equipments, but we tried to find universal, non-traumatic method of daily measurements, enough sensitive and appropriate for observation of people reaction both on weather and space weather (geomagnetic activity) changes. The experiment was based on a method of electrical conductivity measurements of biologically active (acupunctural) points of human skin. The used method (electroacupunctural method by Dr. R.Voll) is very sensitive to current state of an organism and characterize the functional condition of different organs and systems of human body and allows to express so-called "group's health status" in the units, suitable for comparison with meteorological and heliogeophysical parameters. We conduct the parallel investigations as a part of collaborative study in different geographic latitudes-longitudes (Baku:40° 23'43"N -49° 52'56"E, Troitsk (Moscow region): 55° 28'40"N -37° 18'42"E, Yakutsk: 62° 02'00"N -129° 44'00"E). Measurements were carried out on daily basis with permanent group of functionally healthy persons (Moscow -19, Yakutsk -22, CityBaku -12 volunteers). Daily monitoring of nervous, endocrinological, lymphatic systems, blood, lungs, thick and thin intestine, heart and parenhimatic organs, allergy and hypophisis was conducted simultaneously with analyses of space weather (parameters of solar and geomagnetic activities) as well as local meteorological parameters (temperature, atmospheric pressure, humidity, wind speed, etc.). It was proved that it is possible to consider not only weather changes but also geomagnetic field variations as a stressor. It is concluded that : 1. human reaction on the sharp changes of selected external (environmental) physical activity parameters goes like typical stress-reaction; 2. features of stress-reaction depend on history of previous failures of an organism and on state of external background (frequent stresses deplete human organism possibility to adaptation); 3. features of stress-reaction depend on the geographic location (latitude). Possible physi-cal explanation of human organism stress-reaction on changes of geomagnetic oscillatory regime and atmospheric thermobaric variations is discussed.

Severe Weather Environments in Atmospheric Reanalyses

NASA Astrophysics Data System (ADS)

King, A. T.; Kennedy, A. D.

2017-12-01

Atmospheric reanalyses combine historical observation data using a fixed assimilation scheme to achieve a dynamically coherent representation of the atmosphere. How well these reanalyses represent severe weather environments via proxies is poorly defined. To quantify the performance of reanalyses, a database of proximity soundings near severe storms from the Rapid Update Cycle 2 (RUC-2) model will be compared to a suite of reanalyses including: North American Reanalysis (NARR), European Interim Reanalysis (ERA-Interim), 2nd Modern-Era Retrospective Reanalysis for Research and Applications (MERRA-2), Japanese 55-year Reanalysis (JRA-55), 20th Century Reanalysis (20CR), and Climate Forecast System Reanalysis (CFSR). A variety of severe weather parameters will be calculated from these soundings including: convective available potential energy (CAPE), storm relative helicity (SRH), supercell composite parameter (SCP), and significant tornado parameter (STP). These soundings will be generated using the SHARPpy python module, which is an open source tool used to calculate severe weather parameters. Preliminary results indicate that the NARR and JRA55 are significantly more skilled at producing accurate severe weather environments than the other reanalyses. The primary difference between these two reanalyses and the remaining reanalyses is a significant negative bias for thermodynamic parameters. To facilitate climatological studies, the scope of work will be expanded to compute these parameters for the entire domain and duration of select renalyses. Preliminary results from this effort will be presented and compared to observations at select locations. This dataset will be made pubically available to the larger scientific community, and details of this product will be provided.

The impact of reflectivity correction and conversion methods to improve precipitation estimation by weather radar for an extreme low-land Mesoscale Convective System

NASA Astrophysics Data System (ADS)

Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

2014-05-01

Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands. For most of the country this led to over 15 hours of near-continuous precipitation, which resulted in total event accumulations exceeding 150 mm in the eastern part of the Netherlands. Such accumulations belong to the largest sums ever recorded in this country and gave rise to local flooding. Measuring precipitation by weather radar within such mesoscale convective systems is known to be a challenge, since measurements are affected by multiple sources of error. For the current event the operational weather radar rainfall product only estimated about 30% of the actual amount of precipitation as measured by rain gauges. In the current presentation we will try to identify what gave rise to such large underestimations. In general weather radar measurement errors can be subdivided into two different groups: 1) errors affecting the volumetric reflectivity measurements taken, and 2) errors related to the conversion of reflectivity values in rainfall intensity and attenuation estimates. To correct for the first group of errors, the quality of the weather radar reflectivity data was improved by successively correcting for 1) clutter and anomalous propagation, 2) radar calibration, 3) wet radome attenuation, 4) signal attenuation and 5) the vertical profile of reflectivity. Such consistent corrections are generally not performed by operational meteorological services. Results show a large improvement in the quality of the precipitation data, however still only ~65% of the actual observed accumulations was estimated. To further improve the quality of the precipitation estimates, the second group of errors are corrected for by making use of disdrometer measurements taken in close vicinity of the radar. Based on these data the parameters of a normalized drop size distribution are estimated for the total event as well as for each precipitation type separately (convective, stratiform and undefined). These are then used to obtain coherent parameter sets for the radar reflectivity-rainfall rate (Z-R) and radar reflectivity-attenuation (Z-k) relationship, specifically applicable for this event. By applying a single parameter set to correct for both sources of errors, the quality of the rainfall product improves further, leading to >80% of the observed accumulations. However, by differentiating between precipitation type no better results are obtained as when using the operational relationships. This leads to the question: how representative are local disdrometer observations to correct large scale weather radar measurements? In order to tackle this question a Monte Carlo approach was used to generate >10000 sets of the normalized dropsize distribution parameters and to assess their impact on the estimated precipitation amounts. Results show that a large number of parameter sets result in improved precipitation estimated by the weather radar closely resembling observations. However, these optimal sets vary considerably as compared to those obtained from the local disdrometer measurements.

Characterizing severe weather potential in synoptically weakly forced thunderstorm environments

NASA Astrophysics Data System (ADS)

Miller, Paul W.; Mote, Thomas L.

2018-04-01

Weakly forced thunderstorms (WFTs), short-lived convection forming in synoptically quiescent regimes, are a contemporary forecasting challenge. The convective environments that support severe WFTs are often similar to those that yield only non-severe WFTs and, additionally, only a small proportion of individual WFTs will ultimately produce severe weather. The purpose of this study is to better characterize the relative severe weather potential in these settings as a function of the convective environment. Thirty-one near-storm convective parameters for > 200 000 WFTs in the Southeastern United States are calculated from a high-resolution numerical forecasting model, the Rapid Refresh (RAP). For each parameter, the relative odds of WFT days with at least one severe weather event is assessed along a moving threshold. Parameters (and the values of them) that reliably separate severe-weather-supporting from non-severe WFT days are highlighted.Only two convective parameters, vertical totals (VTs) and total totals (TTs), appreciably differentiate severe-wind-supporting and severe-hail-supporting days from non-severe WFT days. When VTs exceeded values between 24.6 and 25.1 °C or TTs between 46.5 and 47.3 °C, odds of severe-wind days were roughly 5 × greater. Meanwhile, odds of severe-hail days became roughly 10 × greater when VTs exceeded 24.4-26.0 °C or TTs exceeded 46.3-49.2 °C. The stronger performance of VT and TT is partly attributed to the more accurate representation of these parameters in the numerical model. Under-reporting of severe weather and model error are posited to exacerbate the forecasting challenge by obscuring the subtle convective environmental differences enhancing storm severity.

The influence of weather conditions on outdoor physical activity among older people with and without osteoarthritis in six European countries

PubMed Central

Timmermans, Erik J; van der Pas, Suzan; Dennison, Elaine M; Maggi, Stefania; Peter, Richard; Castell, Maria Victoria; Pedersen, Nancy L; Denkinger, Michael D; Edwards, Mark H; Limongi, Federica; Herbolsheimer, Florian; Sánchez-Martínez, Mercedes; Siviero, Paola; Queipo, Rocio; Schaap, Laura A; Deeg, Dorly JH

2017-01-01

Objectives Older adults with osteoarthritis (OA) often report that their disease symptoms are exacerbated by weather conditions. This study examines the association between outdoor physical activity (PA) and weather conditions in older adults from six European countries and assesses whether outdoor PA and weather conditions are more strongly associated in older persons with OA than in those without the condition. Methods The American College of Rheumatology classification criteria were used to diagnose OA. Outdoor PA was assessed using the LASA Physical Activity Questionnaire. Data on weather parameters were obtained from weather stations. Results Of the 2,439 participants (65-85 years), 29.6% had OA in knee, hand and/or hip. Participants with OA spent fewer minutes in PA than participants without OA (Median=42.9, IQR=20.0-83.1 versus Median=51.4, IQR=23.6-98.6; p<0.01). In the full sample, temperature (B=1.52; p<0.001) and relative humidity (B=-0.77; p<0.001) were associated with PA. Temperature was more strongly associated with PA in participants without OA (B=1.98; p<0.001) than in those with the condition (B=0.48; p=0.47). Conclusions Weather conditions are associated with outdoor PA in older adults in the general population. Outdoor PA and weather conditions were more strongly associated in older adults without OA than in their counterparts with OA. PMID:27633622

Linking the Weather Generator with Regional Climate Model: Effect of Higher Resolution

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Huth, Radan; Farda, Ales; Skalak, Petr

2014-05-01

This contribution builds on our last year EGU contribution, which followed two aims: (i) validation of the simulations of the present climate made by the ALADIN-Climate Regional Climate Model (RCM) at 25 km resolution, and (ii) presenting a methodology for linking the parametric weather generator (WG) with RCM output (aiming to calibrate a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations). Now we have available new higher-resolution (6.25 km) simulations with the same RCM. The main topic of this contribution is an anser to a following question: What is an effect of using a higher spatial resolution on a quality of simulating the surface weather characteristics? In the first part, the high resolution RCM simulation of the present climate will be validated in terms of selected WG parameters, which are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series. When comparing the WG parameters from the two sources (RCM vs observations), we interpolate the RCM-based parameters into the station locations while accounting for the effect of altitude. In the second part, we will discuss an effect of using the higher resolution: the results of the validation tests will be compared with those obtained with the lower-resolution RCM. Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

System and Method for Providing a Real Time Audible Message to a Pilot

NASA Technical Reports Server (NTRS)

Johnson, Walter W. (Inventor); Lachter, Joel B. (Inventor); Koteskey, Robert W. (Inventor); Battiste, Vernol (Inventor)

2016-01-01

A system and method for providing information to a crew of the aircraft while in-flight. The system includes a module having: a receiver for receiving a message while in-flight; a filter having a set of screening parameters and operative to filter the message based on the set of screening parameters; and a converter for converting the message into an audible message. The message includes a pilot report having at least one of weather information, separation information, congestion information, flight deviation information and destination information. The message is sent to the aircraft by another aircraft or an air traffic controller.

Solar Atmosphere to Earth's Surface: Long Lead Time dB/dt Predictions with the Space Weather Modeling Framework

NASA Astrophysics Data System (ADS)

Welling, D. T.; Manchester, W.; Savani, N.; Sokolov, I.; van der Holst, B.; Jin, M.; Toth, G.; Liemohn, M. W.; Gombosi, T. I.

2017-12-01

The future of space weather prediction depends on the community's ability to predict L1 values from observations of the solar atmosphere, which can yield hours of lead time. While both empirical and physics-based L1 forecast methods exist, it is not yet known if this nascent capability can translate to skilled dB/dt forecasts at the Earth's surface. This paper shows results for the first forecast-quality, solar-atmosphere-to-Earth's-surface dB/dt predictions. Two methods are used to predict solar wind and IMF conditions at L1 for several real-world coronal mass ejection events. The first method is an empirical and observationally based system to estimate the plasma characteristics. The magnetic field predictions are based on the Bz4Cast system which assumes that the CME has a cylindrical flux rope geometry locally around Earth's trajectory. The remaining plasma parameters of density, temperature and velocity are estimated from white-light coronagraphs via a variety of triangulation methods and forward based modelling. The second is a first-principles-based approach that combines the Eruptive Event Generator using Gibson-Low configuration (EEGGL) model with the Alfven Wave Solar Model (AWSoM). EEGGL specifies parameters for the Gibson-Low flux rope such that it erupts, driving a CME in the coronal model that reproduces coronagraph observations and propagates to 1AU. The resulting solar wind predictions are used to drive the operational Space Weather Modeling Framework (SWMF) for geospace. Following the configuration used by NOAA's Space Weather Prediction Center, this setup couples the BATS-R-US global magnetohydromagnetic model to the Rice Convection Model (RCM) ring current model and a height-integrated ionosphere electrodynamics model. The long lead time predictions of dB/dt are compared to model results that are driven by L1 solar wind observations. Both are compared to real-world observations from surface magnetometers at a variety of geomagnetic latitudes. Metrics are calculated to examine how the simulated solar wind drivers impact forecast skill. These results illustrate the current state of long-lead-time forecasting and the promise of this technology for operational use.

Does weather affect daily pain intensity levels in patients with acute low back pain? A prospective cohort study.

PubMed

Duong, Vicky; Maher, Chris G; Steffens, Daniel; Li, Qiang; Hancock, Mark J

2016-05-01

The aim of this study was to investigate the influence of various weather parameters on pain intensity levels in patients with acute low back pain (LBP). We performed a secondary analysis using data from the PACE trial that evaluated paracetamol (acetaminophen) in the treatment of acute LBP. Data on 1604 patients with LBP were included in the analysis. Weather parameters (precipitation, temperature, relative humidity, and air pressure) were obtained from the Australian Bureau of Meteorology. Pain intensity was assessed daily on a 0-10 numerical pain rating scale over a 2-week period. A generalised estimating equation analysis was used to examine the relationship between daily pain intensity levels and weather in three different time epochs (current day, previous day, and change between previous and current days). A second model was adjusted for important back pain prognostic factors. The analysis did not show any association between weather and pain intensity levels in patients with acute LBP in each of the time epochs. There was no change in strength of association after the model was adjusted for prognostic factors. Contrary to common belief, the results demonstrated that the weather parameters of precipitation, temperature, relative humidity, and air pressure did not influence the intensity of pain reported by patients during an episode of acute LBP.

Weather Effects on Crop Diseases in Eastern Germany

NASA Astrophysics Data System (ADS)

Conradt, Tobias

2017-04-01

Since the 1970s there are several long-term monitoring programmes for plant diseases and pests in Germany. Within the framework of a national research project, some otherwise confidential databases comprising 77 111 samples from numerous sites accross Eastern Germany could be accessed and analysed. The pest data covered leaf rust (Puccinia triticina) and powdery mildew (Blumeria graminis) in winter wheat, aphids (Aphididae, four genera) on wheat and other cereal crops, late blight (Phytophthora infestans) in potatoes, and pollen beetles (Brassicogethes aeneus) on rape. These data were complemented by daily weather observations from the German Weather Service (DWD). In a first step, Pearson correlations between weather variables and pest frequencies were calculated for seasonal time periods of different start months and durations and ordered into so-called correlograms. This revealed principal weather effects on disease spread - e. g. that wind is favourable for mildew throughout the year or that rape pollen beetles like it warm, but not during wintertime. Secondly, the pest frequency samples were found to resemble gamma distributions, and a generalised linear model was fitted to describe their parameter shift depending on end-of-winter temperatures for aphids on cereals. The method clearly shows potential for systematic pest risk assessments regarding climate change.

Validating Satellite-Retrieved Cloud Properties for Weather and Climate Applications

NASA Astrophysics Data System (ADS)

Minnis, P.; Bedka, K. M.; Smith, W., Jr.; Yost, C. R.; Bedka, S. T.; Palikonda, R.; Spangenberg, D.; Sun-Mack, S.; Trepte, Q.; Dong, X.; Xi, B.

2014-12-01

Cloud properties determined from satellite imager radiances are increasingly used in weather and climate applications, particularly in nowcasting, model assimilation and validation, trend monitoring, and precipitation and radiation analyses. The value of using the satellite-derived cloud parameters is determined by the accuracy of the particular parameter for a given set of conditions, such as viewing and illumination angles, surface background, and cloud type and structure. Because of the great variety of those conditions and of the sensors used to monitor clouds, determining the accuracy or uncertainties in the retrieved cloud parameters is a daunting task. Sensitivity studies of the retrieved parameters to the various inputs for a particular cloud type are helpful for understanding the errors associated with the retrieval algorithm relative to the plane-parallel world assumed in most of the model clouds that serve as the basis for the retrievals. Real world clouds, however, rarely fit the plane-parallel mold and generate radiances that likely produce much greater errors in the retrieved parameter than can be inferred from sensitivity analyses. Thus, independent, empirical methods are used to provide a more reliable uncertainty analysis. At NASA Langley, cloud properties are being retrieved from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for climate monitoring and model validation as part of the NASA CERES project since 2000 and from AVHRR data since 1978 as part of the NOAA CDR program. Cloud properties are also being retrieved in near-real time globally from both GEO and LEO satellites for weather model assimilation and nowcasting for hazards such as aircraft icing. This paper discusses the various independent datasets and approaches that are used to assessing the imager-based satellite cloud retrievals. These include, but are not limited to data from ARM sites, CloudSat, and CALIPSO. This paper discusses the use of the various datasets available, the methods employed to utilize them in the cloud property retrieval validation process, and the results and how they aid future development of the retrieval algorithms. Future needs are also discussed.

Rapid Assessment of Tree Debris Following Urban Forest Ice Storms

Treesearch

Richard J. Hauer; Angela J. Hauer; Dudley R. Hartel; Jill R. Johnson

2011-01-01

This paper presents a rapid assessment method to estimate urban tree debris following an ice storm. Data were collected from 60 communities to quantify tree debris volumes, mostly from public rights-of-way, following ice storms based on community infrastructure, weather parameters, and urban forest structure. Ice thickness, area of a community, and street distance are...

Upgrade Summer Severe Weather Tool in MIDDS

NASA Technical Reports Server (NTRS)

Wheeler, Mark M.

2010-01-01

The goal of this task was to upgrade the severe weather database from the previous phase by adding weather observations from the years 2004 - 2009, re-analyze the data to determine the important parameters, make adjustments to the index weights depending on the analysis results, and update the MIDDS GUI. The added data increased the period of record from 15 to 21 years. Data sources included local forecast rules, archived sounding data, surface and upper air maps, and two severe weather event databases covering east-central Florida. Four of the stability indices showed increased severe weather predication. The Total Threat Score (TTS) of the previous work was verified for the warm season of 2009 with very good skill. The TTS Probability of Detection (POD) was 88% and the False alarm rate (FAR) of 8%. Based on the results of the analyses, the MIDDS Severe Weather Worksheet GUI was updated to assist the duty forecaster by providing a level of objective guidance based on the analysis of the stability parameters and synoptic-scale dynamics.

Do weather changes influence pain levels in women with fibromyalgia, and can psychosocial variables moderate these influences?

NASA Astrophysics Data System (ADS)

Smedslund, Geir; Eide, Hilde; Kristjansdottir, Ólöf Birna; Nes, Andrea Aparecida Gonçalves; Sexton, Harold; Fors, Egil A.

2014-09-01

The aim of this study was to examine the association between fibromyalgia pain and weather, and to investigate whether psychosocial factors influence this relationship. Women with chronic widespread pain/fibromyalgia ( N = 50) enrolled in a larger study, were recruited from a 4-week inpatient rehabilitation program in Norway ( 2009-2010), and reported their pain and psychological factors up to three times per day (morning, afternoon, evening) for 5 weeks. These ratings were then related to the official local weather parameters. Barometric pressure recorded simultaneously impacted pain significantly while temperature, relative humidity, and solar flux did not. No psychological variables influenced the weather-pain interaction. No weather parameter predicted change in the subsequent pain measures. The magnitude of the inverse association between pain and barometric pressure was very small, and none of the psychological variables studied influenced the association between pain and barometric pressure. All in all, the evidence for a strong weather-pain association in fibromyalgia seems limited at best.

Automatic Determination of the Conic Coronal Mass Ejection Model Parameters

NASA Technical Reports Server (NTRS)

Pulkkinen, A.; Oates, T.; Taktakishvili, A.

2009-01-01

Characterization of the three-dimensional structure of solar transients using incomplete plane of sky data is a difficult problem whose solutions have potential for societal benefit in terms of space weather applications. In this paper transients are characterized in three dimensions by means of conic coronal mass ejection (CME) approximation. A novel method for the automatic determination of cone model parameters from observed halo CMEs is introduced. The method uses both standard image processing techniques to extract the CME mass from white-light coronagraph images and a novel inversion routine providing the final cone parameters. A bootstrap technique is used to provide model parameter distributions. When combined with heliospheric modeling, the cone model parameter distributions will provide direct means for ensemble predictions of transient propagation in the heliosphere. An initial validation of the automatic method is carried by comparison to manually determined cone model parameters. It is shown using 14 halo CME events that there is reasonable agreement, especially between the heliocentric locations of the cones derived with the two methods. It is argued that both the heliocentric locations and the opening half-angles of the automatically determined cones may be more realistic than those obtained from the manual analysis

Using the North American Breeding Bird Survey to assess broad-scale response of the continent's most imperiled avian community, grassland birds, to weather variability

USGS Publications Warehouse

Gorzo, Jessica; Pidgeon, Anna M.; Thogmartin, Wayne E.; Allstadt, Andrew J.; Radeloff, Volker C.; Heglund, Patricia J.; Vavrus, Stephen J.

2016-01-01

Avian populations can respond dramatically to extreme weather such as droughts and heat waves, yet patterns of response to weather at broad scales remain largely unknown. Our goal was to evaluate annual variation in abundance of 14 grassland bird species breeding in the northern mixed-grass prairie in relation to annual variation in precipitation and temperature. We modeled avian abundance during the breeding season using North American Breeding Bird Survey (BBS) data for the U.S. Badlands and Prairies Bird Conservation Region (BCR 17) from 1980 to 2012. We used hierarchical Bayesian methods to fit models and estimate the candidate weather parameters standardized precipitation index (SPI) and standardized temperature index (STI) for the same year and the previous year. Upland Sandpiper (Bartramia longicauda) responded positively to within-year STI (β = 0.101), and Baird's Sparrow (Ammodramus bairdii) responded negatively to within-year STI (β = −0.161) and positively to within-year SPI (β = 0.195). The parameter estimates were superficially similar (STI β = −0.075, SPI β = 0.11) for Grasshopper Sparrow (Ammodramus savannarum), but the best-selected model included an interaction between SPI and STI. The best model for both Eastern Kingbird (Tyrannus tyrannus) and Vesper Sparrow (Pooecetes gramineus) included the additive effects of within-year SPI (β = −0.032 and β = −0.054, respectively) and the previous-year's SPI (β = −0.057 and −0.02, respectively), although for Vesper Sparrow the lag effect was insignificant. With projected warmer, drier weather during summer in the Badlands and Prairies BCR, Baird's and Grasshopper sparrows may be especially threatened by future climate change.

A comparative study of fire weather indices in a semiarid south-eastern Europe region. Case of study: Murcia (Spain).

PubMed

Pérez-Sánchez, Julio; Senent-Aparicio, Javier; Díaz-Palmero, José María; Cabezas-Cerezo, Juan de Dios

2017-07-15

Forest fires are an important distortion in forest ecosystems, linked to their development and whose effects proceed beyond the destruction of ecosystems and material properties, especially in semiarid regions. Prevention of forest fires has to lean on indices based on available parameters that quantify fire risk ignition and spreading. The present study was conducted to compare four fire weather indices in a semiarid region of 11,314km 2 located in southern Spain, characterised as being part of the most damaged area by fire in the Iberian Peninsula. The studied period comprises 3033 wildfires in the region during 15years (2000-2014), of which 80% are >100m 2 and 14% >1000m 2 , resulting around 40km 2 of burnt area in this period. The indices selected have been Angström Index, Forest Fire Drought Index, Forest Moisture Index and Fire Weather Index. Likewise, four selection methods have been applied to compare the results of the studied indices: Mahalanobis distance, percentile method, ranked percentile method and Relative Operating Characteristic curves (ROC). Angström index gives good results in the coastal areas with higher temperatures, low rainfall and wider range of variations while Fire Weather Index has better results in inland areas with higher rainfall, dense forest mass and fewer changes in meteorological conditions throughout the year. ROC space rejects all the indices except Fire Weather Index with good performance all over the region. ROC analysis ratios can be used to assess the success (or lack thereof) of fire indices; thus, it benefits operational wildfire predictions in semiarid regions similar to that of the case study. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptive correction of ensemble forecasts

NASA Astrophysics Data System (ADS)

Pelosi, Anna; Battista Chirico, Giovanni; Van den Bergh, Joris; Vannitsem, Stephane

2017-04-01

Forecasts from numerical weather prediction (NWP) models often suffer from both systematic and non-systematic errors. These are present in both deterministic and ensemble forecasts, and originate from various sources such as model error and subgrid variability. Statistical post-processing techniques can partly remove such errors, which is particularly important when NWP outputs concerning surface weather variables are employed for site specific applications. Many different post-processing techniques have been developed. For deterministic forecasts, adaptive methods such as the Kalman filter are often used, which sequentially post-process the forecasts by continuously updating the correction parameters as new ground observations become available. These methods are especially valuable when long training data sets do not exist. For ensemble forecasts, well-known techniques are ensemble model output statistics (EMOS), and so-called "member-by-member" approaches (MBM). Here, we introduce a new adaptive post-processing technique for ensemble predictions. The proposed method is a sequential Kalman filtering technique that fully exploits the information content of the ensemble. One correction equation is retrieved and applied to all members, however the parameters of the regression equations are retrieved by exploiting the second order statistics of the forecast ensemble. We compare our new method with two other techniques: a simple method that makes use of a running bias correction of the ensemble mean, and an MBM post-processing approach that rescales the ensemble mean and spread, based on minimization of the Continuous Ranked Probability Score (CRPS). We perform a verification study for the region of Campania in southern Italy. We use two years (2014-2015) of daily meteorological observations of 2-meter temperature and 10-meter wind speed from 18 ground-based automatic weather stations distributed across the region, comparing them with the corresponding COSMO-LEPS ensemble forecasts. Deterministic verification scores (e.g., mean absolute error, bias) and probabilistic scores (e.g., CRPS) are used to evaluate the post-processing techniques. We conclude that the new adaptive method outperforms the simpler running bias-correction. The proposed adaptive method often outperforms the MBM method in removing bias. The MBM method has the advantage of correcting the ensemble spread, although it needs more training data.

Total probabilities of ensemble runoff forecasts

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2017-04-01

Ensemble forecasting has a long history from meteorological modelling, as an indication of the uncertainty of the forecasts. However, it is necessary to calibrate and post-process the ensembles as the they often exhibit both bias and dispersion errors. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters varying in space and time, while giving a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, which makes it unsuitable for our purpose. Our post-processing method of the ensembles is developed in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu), where we are making forecasts for whole Europe, and based on observations from around 700 catchments. As the target is flood forecasting, we are also more interested in improving the forecast skill for high-flows rather than in a good prediction of the entire flow regime. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different meteorological forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to estimate the total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but we are adding a spatial penalty in the calibration process to force a spatial correlation of the parameters. The penalty takes distance, stream-connectivity and size of the catchment areas into account. This can in some cases have a slight negative impact on the calibration error, but avoids large differences between parameters of nearby locations, whether stream connected or not. The spatial calibration also makes it easier to interpolate the post-processing parameters to uncalibrated locations. We also look into different methods for handling the non-normal distributions of runoff data and the effect of different data transformations on forecasts skills in general and for floods in particular. Berrocal, V. J., Raftery, A. E. and Gneiting, T.: Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts, Mon. Weather Rev., 135(4), 1386-1402, doi:10.1175/MWR3341.1, 2007. Engeland, K. and Steinsland, I.: Probabilistic postprocessing models for flow forecasts for a system of catchments and several lead times, Water Resour. Res., 50(1), 182-197, doi:10.1002/2012WR012757, 2014. Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T.: Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation, Mon. Weather Rev., 133(5), 1098-1118, doi:10.1175/MWR2904.1, 2005. Hemri, S., Fundel, F. and Zappa, M.: Simultaneous calibration of ensemble river flow predictions over an entire range of lead times, Water Resour. Res., 49(10), 6744-6755, doi:10.1002/wrcr.20542, 2013. Raftery, A. E., Gneiting, T., Balabdaoui, F. and Polakowski, M.: Using Bayesian Model Averaging to Calibrate Forecast Ensembles, Mon. Weather Rev., 133(5), 1155-1174, doi:10.1175/MWR2906.1, 2005.

Effect of accelerated weathering on surface chemistry of modified wood

NASA Astrophysics Data System (ADS)

Temiz, Ali; Terziev, Nasko; Eikenes, Morten; Hafren, Jonas

2007-04-01

In this study, the effects of UV-light irradiation and water spray on colour and surface chemistry of scots pine sapwood samples were investigated. The specimens were treated with chromated copper arsenate (CCA), a metal-free propiconazol-based formulation, chitosan, furfuryl alcohol and linseed and tall oils. The weathering experiment was performed by cycles of 2 h UV-light irradiation followed by water spray for 18 min. The changes at the surface of the weathered samples were characterised by Fourier transform infrared spectroscopy (FT-IR); colour characterizations were performed by measuring CIELab parameters. The results show that all treatment methods except chitosan treatment provided lower colour changes than the control groups after 800 h exposure in weathering test cycle, but differences between chitosan and control were also small. The lowest colour changes were found on linseed oil (full cell process) and CCA treated wood. FT-IR results show that oil treatment (linseed and tall oil) decreased the intensities of a lignin specific peak (1500-1515 cm -1). Absorption band changes at 1630-1660 cm -1 were reduced by all treatments.

Effect of natural ageing on volume stability of MSW and wood waste incineration residues

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gori, Manuela, E-mail: manuela.gori@dicea.unifi.it; Bergfeldt, Britta; Reichelt, Jürgen

2013-04-15

Highlights: ► Natural weathering on BA from MSW and wood waste incineration was evaluated. ► Type of mineral phases, pH and volume stability were considered. ► Weathering reactions effect in improved stability of the materials. - Abstract: This paper presents the results of a study on the effect of natural weathering on volume stability of bottom ash (BA) from municipal solid waste (MSW) and wood waste incineration. BA samples were taken at different steps of treatment (fresh, 4 weeks and 12 weeks aged) and then characterised for their chemical and mineralogical composition and for volume stability by means of themore » mineralogical test method (M HMVA-StB), which is part of the German quality control system for using aggregates in road construction (TL Gestein-StB 04). Changes of mineralogical composition with the proceeding of the weathering treatment were also monitored by leaching tests. At the end of the 12 weeks of treatment, almost all the considered samples resulted to be usable without restrictions in road construction with reference to the test parameter volume stability.« less

Surrogate Based Uni/Multi-Objective Optimization and Distribution Estimation Methods

NASA Astrophysics Data System (ADS)

Gong, W.; Duan, Q.; Huo, X.

2017-12-01

Parameter calibration has been demonstrated as an effective way to improve the performance of dynamic models, such as hydrological models, land surface models, weather and climate models etc. Traditional optimization algorithms usually cost a huge number of model evaluations, making dynamic model calibration very difficult, or even computationally prohibitive. With the help of a serious of recently developed adaptive surrogate-modelling based optimization methods: uni-objective optimization method ASMO, multi-objective optimization method MO-ASMO, and probability distribution estimation method ASMO-PODE, the number of model evaluations can be significantly reduced to several hundreds, making it possible to calibrate very expensive dynamic models, such as regional high resolution land surface models, weather forecast models such as WRF, and intermediate complexity earth system models such as LOVECLIM. This presentation provides a brief introduction to the common framework of adaptive surrogate-based optimization algorithms of ASMO, MO-ASMO and ASMO-PODE, a case study of Common Land Model (CoLM) calibration in Heihe river basin in Northwest China, and an outlook of the potential applications of the surrogate-based optimization methods.

Data Driven Ionospheric Modeling in Relation to Space Weather: Percent Cloud Coverage

NASA Astrophysics Data System (ADS)

Tulunay, Y.; Senalp, E. T.; Tulunay, E.

2009-04-01

Since 1990, a small group at METU has been developing data driven models in order to forecast some critical system parameters related with the near-Earth space processes. The background on the subject supports new achievements, which contributed the COST 724 activities, which will contribute to the new ES0803 activities. This work mentions one of the outstanding contributions, namely forecasting of meteorological parameters by considering the probable influence of cosmic rays (CR) and sunspot numbers (SSN). The data-driven method is generic and applicable to many Near-Earth Space processes including ionospheric/plasmaspheric interactions. It is believed that the EURIPOS initiative would be useful in supplying wide range reliable data to the models developed. Quantification of physical mechanisms, which causally link Space Weather to the Earth's Weather, has been a challenging task. In this basis, the percent cloud coverage (%CC) and cloud top temperatures (CTT) were forecast one month ahead of time between geographic coordinates of (22.5˚N; 57.5˚N); and (7.5˚W; 47.5˚E) at 96 grid locations and covering the years of 1983 to 2000 using the Middle East Technical University Fuzzy Neural Network Model (METU-FNN-M) [Tulunay, 2008]. The Near Earth Space variability at several different time scales arises from a number of separate factors and the physics of the variations cannot be modeled due to the lack of current information about the parameters of several natural processes. CR are shielded by the magnetosphere to a certain extent, but they can modulate the low level cloud cover. METU-FNN-M was developed, trained and applied for forecasting the %CC and CTT, by considering the history of those meteorological variables; Cloud Optical Depth (COD); the Ionization (I) value that is formulized and computed by using CR data and CTT; SSN; temporal variables; and defuzified cloudiness. The temporal and spatial variables and the cut off rigidity are used to compute the defuzified cloudiness. The forecast %CC and CTT values at uniformly spaced grids over the region of interest are used for mapping by Bezier surfaces. The major advantage of the fuzzy model is that it uses its inputs and the expert knowledge in coordination. Long-term cloud analysis was performed on a region having differences in terms of atmospheric activity, in order to show the generalization capability. Global and local parameters of the process were considered. Both CR Flux and SSN reflect the influence of Space Weather on general planetary situation; but other parameters in the inputs of the model reflect local situation. Error and correlation analysis on the forecast and observed parameters were performed. The correlations between the forecast and observed parameters are very promising. The model contributes to the dependence of the cloud formation process on CR Fluxes. The one-month in advance forecast values of the model can also be used as inputs to other models, which forecast some other local or global parameters in order to further test the hypothesis on possible link(s) between Space Weather and the Earth's Weather. The model based, theoretical and numerical works mentioned are promising and have potential for future research and developments. References Tulunay Y., E.T. Şenalp, Ş. Öz, L.I. Dorman, E. Tulunay, S.S. Menteş and M.E. Akcan (2008), A Fuzzy Neural Network Model to Forecast the Percent Cloud Coverage and Cloud Top Temperature Maps, Ann. Geophys., 26(12), 3945-3954, 2008.

Space-weather Parameters for 1,000 Active Regions Observed by SDO/HMI

NASA Astrophysics Data System (ADS)

Bobra, M.; Liu, Y.; Hoeksema, J. T.; Sun, X.

2013-12-01

We present statistical studies of several space-weather parameters, derived from observations of the photospheric vector magnetic field by the Helioseismic and Magnetic Imager (HMI) aboard the Solar Dynamics Observatory, for a thousand active regions. Each active region has been observed every twelve minutes during the entirety of its disk passage. Some of these parameters, such as energy density and shear angle, indicate the deviation of the photospheric magnetic field from that of a potential field. Other parameters include flux, helicity, field gradients, polarity inversion line properties, and measures of complexity. We show that some of these parameters are useful for event prediction.

Sun-to-Earth simulations of geo-effective Coronal Mass Ejections with EUHFORIA: a heliospheric-magnetospheric model chain approach

NASA Astrophysics Data System (ADS)

Scolini, C.; Verbeke, C.; Gopalswamy, N.; Wijsen, N.; Poedts, S.; Mierla, M.; Rodriguez, L.; Pomoell, J.; Cramer, W. D.; Raeder, J.

2017-12-01

Coronal Mass Ejections (CMEs) and their interplanetary counterparts are considered to be the major space weather drivers. An accurate modelling of their onset and propagation up to 1 AU represents a key issue for more reliable space weather forecasts, and predictions about their actual geo-effectiveness can only be performed by coupling global heliospheric models to 3D models describing the terrestrial environment, e.g. magnetospheric and ionospheric codes in the first place. In this work we perform a Sun-to-Earth comprehensive analysis of the July 12, 2012 CME with the aim of testing the space weather predictive capabilities of the newly developed EUHFORIA heliospheric model integrated with the Gibson-Low (GL) flux rope model. In order to achieve this goal, we make use of a model chain approach by using EUHFORIA outputs at Earth as input parameters for the OpenGGCM magnetospheric model. We first reconstruct the CME kinematic parameters by means of single- and multi- spacecraft reconstruction methods based on coronagraphic and heliospheric CME observations. The magnetic field-related parameters of the flux rope are estimated based on imaging observations of the photospheric and low coronal source regions of the eruption. We then simulate the event with EUHFORIA, testing the effect of the different CME kinematic input parameters on simulation results at L1. We compare simulation outputs with in-situ measurements of the Interplanetary CME and we use them as input for the OpenGGCM model, so to investigate the magnetospheric response to solar perturbations. From simulation outputs we extract some global geomagnetic activity indexes and compare them with actual data records and with results obtained by the use of empirical relations. Finally, we discuss the forecasting capabilities of such kind of approach and its future improvements.

Deriving aerosol parameters from in-situ spectrometer measurements for validation of remote sensing products

NASA Astrophysics Data System (ADS)

Riedel, Sebastian; Janas, Joanna; Gege, Peter; Oppelt, Natascha

2017-10-01

Uncertainties of aerosol parameters are the limiting factor for atmospheric correction over inland and coastal waters. For validating remote sensing products from these optically complex and spatially inhomogeneous waters the spatial resolution of automated sun photometer networks like AERONET is too coarse and additional measurements on the test site are required. We have developed a method which allows the derivation of aerosol parameters from measurements with any spectrometer with suitable spectral range and resolution. This method uses a pair of downwelling irradiance and sky radiance measurements for the extraction of the turbidity coefficient and aerosol Ångström exponent. The data can be acquired fast and reliable at almost any place during a wide range of weather conditions. A comparison to aerosol parameters measured with a Cimel sun photometer provided by AERONET shows a reasonable agreement for the Ångström exponent. The turbidity coefficient did not agree well with AERONET values due to fit ambiguities, indicating that future research should focus on methods to handle parameter correlations within the underlying model.

Atmospheric pressure and suicide attempts in Helsinki, Finland

NASA Astrophysics Data System (ADS)

Hiltunen, Laura; Ruuhela, Reija; Ostamo, Aini; Lönnqvist, Jouko; Suominen, Kirsi; Partonen, Timo

2012-11-01

The influence of weather on mood and mental health is commonly debated. Furthermore, studies concerning weather and suicidal behavior have given inconsistent results. Our aim was to see if daily weather changes associate with the number of suicide attempts in Finland. All suicide attempts treated in the hospitals in Helsinki, Finland, during two separate periods, 8 years apart, were included. Altogether, 3,945 suicide attempts were compared with daily weather parameters and analyzed with a Poisson regression. We found that daily atmospheric pressure correlated statistically significantly with the number of suicide attempts, and for men the correlation was negative. Taking into account the seasonal normal value during the period 1971-2000, daily temperature, global solar radiation and precipitation did not associate with the number of suicide attempts on a statistically significant level in our study. We concluded that daily atmospheric pressure may have an impact on suicidal behavior, especially on suicide attempts of men by violent methods ( P < 0.001), and may explain the clustering of suicide attempts. Men seem to be more vulnerable to attempt suicide under low atmospheric pressure and women under high atmospheric pressure. We show only statistical correlations, which leaves the exact mechanisms of interaction between weather and suicidal behavior open. However, suicidal behavior should be assessed from the point of view of weather in addition to psychiatric and social aspects.

Evaluating the effect of lithology on porosity development in ridgetops in the Appalachian Piedmont

NASA Astrophysics Data System (ADS)

Marcon, V.; Gu, X.; Fisher, B.; Brantley, S. L.

2016-12-01

Together, chemical and physical processes transform fresh bedrock into friable weathered material. Even in systems where lithology, tectonic history, and climatic history are all known, it is challenging to predict the depth of weathering because the mechanisms that control the rate of regolith formation are not understood. In the Appalachian Piedmont, where rates of regolith formation and erosion are thought to be in a rough steady state, the depth of weathering varies with lithology. The Piedmont provides a controlled natural environment to isolate the effects of lithology on weathering processes so we can start to understand the mechanisms that initiate and drive weathering. Weathering is deepest over feldspathic rocks (schist/granite) with regolith 20-30m thick and thinnest over mafic and ultramafic rocks (diabase/serpentinite) with regolith <5m thick (Pavich et al., 1989). We are exploring both chemical and physical controls on weathering. For example, when regolith thickness is plotted versus fracture toughness of each lithology, regolith thickness generally increases with decreasing fracture toughness. However, serpentinite, a rheologically weak rock, does not follow this trend with thin soils. To understand this observation, physical weathering parameters (porosity, connectivity, and surface area) were evaluated using neutron scattering on Piedmont rocks at different degrees of weathering. Samples of both weathered diabase and serpentinite are dominated by small pores (<0.1micron), whereas pores in schist are characteristically larger (1-10microns). As serpentinite weathers, porosity is created by serpentinization reactions and lost from collapse during weathering. Serpentinite consists of easily weathered hydrous minerals with little quartz. Comparatively, rocks with more quartz (e.g. schist) have a supportive skeleton as the rock weathers. This quartz skeleton could prevent the collapse of pores and result in isovolumetric weathering. Non-isovolumetric weathering limits infiltration of reactive fluids deeper into the rock, minimizing regolith formation in serpentinite due to its lack of a quartz skeleton. Given this, fracture toughness may be an important parameter to consider in terms of predicting regolith thickness.

Real-time assessment of fog-related crashes using airport weather data: a feasibility analysis.

PubMed

Ahmed, Mohamed M; Abdel-Aty, Mohamed; Lee, Jaeyoung; Yu, Rongjie

2014-11-01

The effect of reduction of visibility on crash occurrence has recently been a major concern. Although visibility detection systems can help to mitigate the increased hazard of limited-visibility, such systems are not widely implemented and many locations with no systems are experiencing considerable number of fatal crashes due to reduction in visibility caused by fog and inclement weather. On the other hand, airports' weather stations continuously monitor all climate parameters in real-time, and the gathered data may be utilized to mitigate the increased risk for the adjacent roadways. This study aims to examine the viability of using airport weather information in real-time road crash risk assessment in locations with recurrent fog problems. Bayesian logistic regression was utilized to link six years (2005-2010) of historical crash data to real-time weather information collected from eight airports in the State of Florida, roadway characteristics and aggregate traffic parameters. The results from this research indicate that real-time weather data collected from adjacent airports are good predictors to assess increased risk on highways. Copyright © 2014 Elsevier Ltd. All rights reserved.

TSS concentration in sewers estimated from turbidity measurements by means of linear regression accounting for uncertainties in both variables.

PubMed

Bertrand-Krajewski, J L

2004-01-01

In order to replace traditional sampling and analysis techniques, turbidimeters can be used to estimate TSS concentration in sewers, by means of sensor and site specific empirical equations established by linear regression of on-site turbidity Tvalues with TSS concentrations C measured in corresponding samples. As the ordinary least-squares method is not able to account for measurement uncertainties in both T and C variables, an appropriate regression method is used to solve this difficulty and to evaluate correctly the uncertainty in TSS concentrations estimated from measured turbidity. The regression method is described, including detailed calculations of variances and covariance in the regression parameters. An example of application is given for a calibrated turbidimeter used in a combined sewer system, with data collected during three dry weather days. In order to show how the established regression could be used, an independent 24 hours long dry weather turbidity data series recorded at 2 min time interval is used, transformed into estimated TSS concentrations, and compared to TSS concentrations measured in samples. The comparison appears as satisfactory and suggests that turbidity measurements could replace traditional samples. Further developments, including wet weather periods and other types of sensors, are suggested.

A population-based study of the associations of stroke occurrence with weather parameters in Siberia, Russia (1982-92).

PubMed

Feigin, V L; Nikitin, Y P; Bots, M L; Vinogradova, T E; Grobbee, D E

2000-03-01

Previous studies have established a seasonal variation in stroke occurrence, but none have assessed the influence of inclement weather conditions on stroke incidence in a general population of Russia. We performed a stroke population-based study in the Oktiabrsky District of Novosibirsk, Siberia, Russia. Included in the analysis were 1929 patients with their first occurrence of ischemic stroke (IS), 215 patients with their first occurrence of intracerebral hemorrhage (ICH) and 64 patients with their first occurrence of subarachnoid hemorrhage (SAH): all patients were aged between 25 and 74 years. The cumulative daily occurrence of total strokes and stroke subtypes was evaluated in relation to aggregated daily mean values of ambient temperature, relative humidity and air pressure by means of Poisson regression analysis to estimate the rate ratio (RR) with corresponding confidence interval (CI) and to identify the weather parameters of most importance. In a multivariate analysis, with adjustment for the effects of season, solar and geomagnetic activity, and age of the patients, low ambient temperature (RR 1.32; 95% CI 1.05-1.66) and mean value of air pressure (RR 0.986; 95% CI 0.972-0.999) were important predictors of IS occurrence, while mild ambient temperature (RR 1.52; 95% CI 1. 04-2.22) was an important predictor of ICH occurrence. No relationship between SAH occurrence and any one of the weather parameters studied was revealed. There was no interaction between any meteorological variables that was statistically significant. Inclement weather conditions are associated with the occurrence of IS and ICH in Siberia, Russia. Among the meteorological parameters studied, low ambient temperature and mean air pressure are the most important predictors of IS occurrence, whereas the occurrence of ICH is associated with mild ambient temperature. There is no association between any one of the weather parameters studied and the occurrence of SAH.

Stochastic Hourly Weather Generator HOWGH: Validation and its Use in Pest Modelling under Present and Future Climates

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Hirschi, M.; Spirig, C.

2014-12-01

To quantify impact of the climate change on a specific pest (or any weather-dependent process) in a specific site, we may use a site-calibrated pest (or other) model and compare its outputs obtained with site-specific weather data representing present vs. perturbed climates. The input weather data may be produced by the stochastic weather generator. Apart from the quality of the pest model, the reliability of the results obtained in such experiment depend on an ability of the generator to represent the statistical structure of the real world weather series, and on the sensitivity of the pest model to possible imperfections of the generator. This contribution deals with the multivariate HOWGH weather generator, which is based on a combination of parametric and non-parametric statistical methods. Here, HOWGH is used to generate synthetic hourly series of three weather variables (solar radiation, temperature and precipitation) required by a dynamic pest model SOPRA to simulate the development of codling moth. The contribution presents results of the direct and indirect validation of HOWGH. In the direct validation, the synthetic series generated by HOWGH (various settings of its underlying model are assumed) are validated in terms of multiple climatic characteristics, focusing on the subdaily wet/dry and hot/cold spells. In the indirect validation, we assess the generator in terms of characteristics derived from the outputs of SOPRA model fed by the observed vs. synthetic series. The weather generator may be used to produce weather series representing present and future climates. In the latter case, the parameters of the generator may be modified by the climate change scenarios based on Global or Regional Climate Models. To demonstrate this feature, the results of codling moth simulations for future climate will be shown. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).

Role of Winter Weather Conditions and Slipperiness on Tourists' Accidents in Finland.

PubMed

Lépy, Élise; Rantala, Sinikka; Huusko, Antti; Nieminen, Pentti; Hippi, Marjo; Rautio, Arja

2016-08-15

(1) BACKGROUND: In Finland, slippery snowy or icy ground surface conditions can be quite hazardous to human health during wintertime. We focused on the impacts of the variability in weather conditions on tourists' health via documented accidents during the winter season in the Sotkamo area. We attempted to estimate the slipping hazard in a specific context of space and time focusing on the weather and other possible parameters, responsible for fluctuations in the numbers of injuries/accidents; (2) METHODS: We used statistical distributions with graphical illustrations to examine the distribution of visits to Kainuu Hospital by non-local patients and their characteristics/causes; graphs to illustrate the distribution of the different characteristics of weather conditions; questionnaires and interviews conducted among health care and safety personnel in Sotkamo and Kuusamo; (3) RESULTS: There was a clear seasonal distribution in the numbers and types of extremity injuries of non-local patients. While the risk of slipping is emphasized, other factors leading to injuries are evaluated; and (4) CONCLUSIONS: The study highlighted the clear role of wintery weather conditions as a cause of extremity injuries even though other aspects must also be considered. Future scenarios, challenges and adaptive strategies are also discussed from the viewpoint of climate change.

Role of Winter Weather Conditions and Slipperiness on Tourists’ Accidents in Finland

PubMed Central

Lépy, Élise; Rantala, Sinikka; Huusko, Antti; Nieminen, Pentti; Hippi, Marjo; Rautio, Arja

2016-01-01

(1) Background: In Finland, slippery snowy or icy ground surface conditions can be quite hazardous to human health during wintertime. We focused on the impacts of the variability in weather conditions on tourists’ health via documented accidents during the winter season in the Sotkamo area. We attempted to estimate the slipping hazard in a specific context of space and time focusing on the weather and other possible parameters, responsible for fluctuations in the numbers of injuries/accidents; (2) Methods: We used statistical distributions with graphical illustrations to examine the distribution of visits to Kainuu Hospital by non-local patients and their characteristics/causes; graphs to illustrate the distribution of the different characteristics of weather conditions; questionnaires and interviews conducted among health care and safety personnel in Sotkamo and Kuusamo; (3) Results: There was a clear seasonal distribution in the numbers and types of extremity injuries of non-local patients. While the risk of slipping is emphasized, other factors leading to injuries are evaluated; and (4) Conclusions: The study highlighted the clear role of wintery weather conditions as a cause of extremity injuries even though other aspects must also be considered. Future scenarios, challenges and adaptive strategies are also discussed from the viewpoint of climate change. PMID:27537899

Impact of a variational objective analysis scheme on a regional area numerical model: The Italian Air Force Weather Service experience

NASA Astrophysics Data System (ADS)

Bonavita, M.; Torrisi, L.

2005-03-01

A new data assimilation system has been designed and implemented at the National Center for Aeronautic Meteorology and Climatology of the Italian Air Force (CNMCA) in order to improve its operational numerical weather prediction capabilities and provide more accurate guidance to operational forecasters. The system, which is undergoing testing before operational use, is based on an “observation space” version of the 3D-VAR method for the objective analysis component, and on the High Resolution Regional Model (HRM) of the Deutscher Wetterdienst (DWD) for the prognostic component. Notable features of the system include a completely parallel (MPI+OMP) implementation of the solution of analysis equations by a preconditioned conjugate gradient descent method; correlation functions in spherical geometry with thermal wind constraint between mass and wind field; derivation of the objective analysis parameters from a statistical analysis of the innovation increments.

Pattern recognition of satellite cloud imagery for improved weather prediction

NASA Technical Reports Server (NTRS)

Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.

1986-01-01

The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.

Utilizing the social media data to validate 'climate change' indices

NASA Astrophysics Data System (ADS)

Molodtsova, T.; Kirilenko, A.; Stepchenkova, S.

2013-12-01

Reporting the observed and modeled changes in climate to public requires the measures understandable by the general audience. E.g., the NASA GISS Common Sense Climate Index (Hansen et al., 1998) reports the change in climate based on six practically observable parameters such as the air temperature exceeding the norm by one standard deviation. The utility of the constructed indices for reporting climate change depends, however, on an assumption that the selected parameters are felt and connected with the changing climate by a non-expert, which needs to be validated. Dynamic discussion of climate change issues in social media may provide data for this validation. We connected the intensity of public discussion of climate change in social networks with regional weather variations for the territory of the USA. We collected the entire 2012 population of Twitter microblogging activity on climate change topic, accumulating over 1.8 million separate records (tweets) globally. We identified the geographic location of the tweets and associated the daily and weekly intensity of twitting with the following parameters of weather for these locations: temperature anomalies, 'hot' temperature anomalies, 'cold' temperature anomalies, heavy rain/snow events. To account for non-weather related events we included the articles on climate change from the 'prestige press', a collection of major newspapers. We found that the regional changes in parameters of weather significantly affect the number of tweets published on climate change. This effect, however, is short-lived and varies throughout the country. We found that in different locations different weather parameters had the most significant effect on climate change microblogging activity. Overall 'hot' temperature anomalies had significant influence on climate change twitting intensity.

Modelling of 10 Gbps Free Space Optics Communication Link Using Array of Receivers in Moderate and Harsh Weather Conditions

NASA Astrophysics Data System (ADS)

Gupta, Amit; Shaina, Nagpal

2017-08-01

Intersymbol interference and attenuation of signal are two major parameters affecting the quality of transmission in Free Space Optical (FSO) Communication link. In this paper, the impact of these parameters on FSO communication link is analysed for delivering high-quality data transmission. The performance of the link is investigated under the influence of amplifier in the link. The performance parameters of the link like minimum bit error rate, received signal power and Quality factor are examined by employing erbium-doped fibre amplifier in the link. The effects of amplifier are visualized with the amount of received power. Further, the link is simulated for moderate weather conditions at various attenuation levels on transmitted signal. Finally, the designed link is analysed in adverse weather conditions by using high-power laser source for optimum performance.

Effects of atmospheric composition on apparent activation energy of silicate weathering: I. Model formulation

NASA Astrophysics Data System (ADS)

Kanzaki, Yoshiki; Murakami, Takashi

2018-07-01

We have developed a weathering model to comprehensively understand the determining factors of the apparent activation energy of silicate weathering in order to better estimate the silicate-weathering flux in the Precambrian. The model formulates the reaction rate of a mineral as a basis, then the elemental loss by summing the reaction rates of whole minerals, and finally the weathering flux from a given weathering profile by integrating the elemental losses along the depth of the profile. The rate expressions are formulated with physicochemical parameters relevant to weathering, including solution and atmospheric compositions. The apparent activation energies of silicate weathering are then represented by the temperature dependences of the physicochemical parameters based on the rate expressions. It was found that the interactions between individual mineral-reactions and the compositions of solution and atmosphere are necessarily accompanied by those of temperature-dependence counterparts. Indeed, the model calculates the apparent activation energy of silicate weathering as a function of the temperature dependence of atmospheric CO2 (Δ HCO2‧) . The dependence of the apparent activation energy of silicate weathering on Δ HCO2‧ may explain the empirical dependence of silicate weathering on the atmospheric composition. We further introduce a compensation law between the apparent activation energy and the pre-exponential factor to obtain the relationship between the silicate-weathering flux (FCO2), temperature and the apparent activation energy. The model calculation and the compensation law enable us to predict FCO2 as a function of temperature, once Δ HCO2‧ is given. The validity of the model is supported by agreements between the model prediction and observations of the apparent activation energy and FCO2 in the modern weathering systems. The present weathering model will be useful for the estimation of FCO2 in the Precambrian, for which Δ HCO2‧ can be deduced from the greenhouse effect of atmospheric CO2.

NextGen Weather Plan, Version 1.1

DTIC Science & Technology

2009-09-17

values of weather parameters at a station or over an area. In this paper, we often refer to aeronautical climatology, which is the application of the data...Joint Planning and Development Office NEXTGEN Weather Plan Version 1.1 Version 1.1 i September 17, 2009 Report Documentation Page Form...COVERED 00-00-2009 to 00-00-2009 4. TITLE AND SUBTITLE NextGen Weather Plan 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6

Climatic impact on isovolumetric weathering of a coarse-grained schist in the northern Piedmont Province of the central Atlantic states

USGS Publications Warehouse

Cleaves, E.T.

1993-01-01

The possible impact of periglacial climates on the rate of chemical weathering of a coarse-grained plagioclase-muscovite-quartz schist has been determined for a small watershed near Baltimore, Maryland. The isovolumetric chemical weathering model formulated from the geochemical mass balance study of the watershed shows that the weathering front advances at a velocity of 9.1 m/m.y., if the modern environmental parameters remain the same back through time. However, recent surficial geological mapping demonstrates that periglacial climates have impacted the area. Such an impact significantly affects two key chemical weathering parameters, the concentration of CO2 in the soil and groundwater moving past the weathering front. Depending upon the assumptions used in the model, the rate of saprolitization varies from 2.2 to 5.3 m/m.y. The possible impact of periglacial processes suggested by the chemical weathering rates indicates a need to reconsider theories of landscape evolution as they apply to the northern Piedmont Province of the mid-Atlantic states. I suggest that from the Late Miocene to the present that the major rivers have become incised in their present locations; this incision has enhanced groundwater circulation and chemical weathering such that crystalline rocks beneath interfluvial areas remain mantled by saprolite; and the saprolite mantle has been partially stripped as periglacial conditions alternate with humid-temperate conditions. ?? 1993.

Design and realization of an automatic weather station at island

NASA Astrophysics Data System (ADS)

Chen, Yong-hua; Li, Si-ren

2011-10-01

In this paper, the design and development of an automatic weather station monitoring is described. The proposed system consists of a set of sensors for measuring meteorological parameters (temperature, wind speed & direction, rain fall, visibility, etc.). To increase the reliability of the system, wind speed & direction are measured redundantly with duplicate sensors. The sensor signals are collected by the data logger CR1000 at several analog and digital inputs. The CR1000 and the sensors form a completely autonomous system which works with the other systems installed in the container. Communication with the master PC is accomplished over the method of Code Division Multiple Access (CDMA) with the Compact Caimore6550P CDMA DTU. The data are finally stored in tables on the CPU as well as on the CF-Card. The weather station was built as an efficient autonomous system which operates with the other systems to provide the required data for a fully automatic measurement system.

Implicit assimilation for marine ecological models

NASA Astrophysics Data System (ADS)

Weir, B.; Miller, R.; Spitz, Y. H.

2012-12-01

We use a new data assimilation method to estimate the parameters of a marine ecological model. At a given point in the ocean, the estimated values of the parameters determine the behaviors of the modeled planktonic groups, and thus indicate which species are dominant. To begin, we assimilate in situ observations, e.g., the Bermuda Atlantic Time-series Study, the Hawaii Ocean Time-series, and Ocean Weather Station Papa. From there, we estimate the parameters at surrounding points in space based on satellite observations of ocean color. Given the variation of the estimated parameters, we divide the ocean into regions meant to represent distinct ecosystems. An important feature of the data assimilation approach is that it refines the confidence limits of the optimal Gaussian approximation to the distribution of the parameters. This enables us to determine the ecological divisions with greater accuracy.

Inferring silicate weathering rates over recent timescales (less than 100 years) in crystalline aquifers by calibrating lumped parameters models with atmospheric tracers

NASA Astrophysics Data System (ADS)

Marçais, J.; Labasque, T.; Gauvain, A.; De Dreuzy, J. R.; Aquilina, L.; Abbott, B. W.

2016-12-01

Silicate minerals (e.g. feldspars, micas and olivines) are ubiquitous in crystalline rocks such as granite and schist. Groundwater dissolves some of this silica via weathering processes as it passes through the catchment, increasing silica concentration with residence time. However, quantifying weathering rates is complicated by the fact that groundwater residence time distributions (RTD) are typically unknown. Batch experiments can characterize weathering reaction type and provide estimates of dissolution rates, but weathering timescales in the field are far greater than what can be simulated in the laboratory (White and Brantley, 2003). Here we implement a novel approach coupling chlorofluorocarbons (CFC) and dissolved silica concentrations to infer timescales of silica weathering processes at the watershed scale. We investigated 6 crystalline aquifers in Brittany with contrasting lithology. We quantified silicate weathering at the watershed scale based on individual measurements from multiple wells, assuming first-order reaction kinetics. For each well, we used a lumped parameter model to determined RTD with inverse gaussian distributions, which allow two degrees of freedom. Production rate and initial silicate concentration were then optimized at the watershed scale with the calibrated model. Weathering rates were relatively similar among watersheds, varying for most sites from 0.16 to 0.42 mg/L/yr (SD = 0.09 mg/L/yr), and estimates of weathering rates were not significantly influenced by single well measurements. This work demonstrates how atmospheric tracers can be used with dissolved silica concentration to inform both RTD and first order kinetics of weathering reactions. Together these results suggest that dissolved silica could be a robust and cheap groundwater age proxy for recent timescales (less than 100 years). ------------------ White, Art F, and Susan L Brantley. 2003. « The effect of time on the weathering of silicate minerals: why do weathering rates differ in the laboratory and field? » Chemical Geology, Controls on Chemical Weathering, 202 (3-4): 479-506. doi:10.1016/j.chemgeo.2003.03.001.

Meteorological limits on the growth and development of screwworm populations

NASA Technical Reports Server (NTRS)

Phinney, D. E.; Arp, G. K.

1978-01-01

A program to evaluate the use of remotely sensed data as an additional tool in existing and projected efforts to eradicate the screwworm began in 1973. Estimating weather conditions by use of remotely sensed data was part of the study. Next, the effect of weather on screwworm populations was modeled. A significant portion of the variation in screwworm population growth and development has been traced to weather-related parameters. This report deals with the salient points of the weather and the screwworm population interaction.

Generation of Multivariate Surface Weather Series with Use of the Stochastic Weather Generator Linked to Regional Climate Model

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Farda, A.; Huth, R.

2012-12-01

The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series and then modified (in case of simulations for the future climate) according to the GCM- or RCM-based climate change scenarios. The present contribution uses the parametric daily weather generator M&Rfi to follow two aims: (1) Validation of the new simulations of the present climate (1961-1990) made by the ALADIN-Climate/CZ (v.2) Regional Climate Model at 25 km resolution. The WG parameters will be derived from the RCM-simulated surface weather series and compared to those derived from observational data in the Czech meteorological stations. The set of WG parameters will include selected statistics of the surface temperature and precipitation (characteristics of the mean, variability, interdiurnal variability and extremes). (2) Testing a potential of RCM output for calibration of the WG for the ungauged locations. The methodology being examined will consist in using the WG, whose parameters are interpolated from the surrounding stations and then corrected based on a RCM-simulated spatial variability. The quality of the weather series produced by the WG calibrated in this way will be assessed in terms of selected climatic characteristics focusing on extreme precipitation and temperature characteristics (including characteristics of dry/wet/hot/cold spells). Acknowledgements: The present experiment is made within the frame of projects ALARO (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports) and VALUE (COST ES 1102 action).

Effects of Space Weather on Biomedical Parameters during the Solar Activity Cycles 23-24.

PubMed

Ragul'skaya, M V; Rudenchik, E A; Chibisov, S M; Gromozova, E N

2015-06-01

The results of long-term (1998-2012) biomedical monitoring of the biotropic effects of space weather are discussed. A drastic change in statistical distribution parameters in the middle of 2005 was revealed that did not conform to usual sinusoidal distribution of the biomedical data reflecting changes in the number of solar spots over a solar activity cycle. The dynamics of space weather of 2001-2012 is analyzed. The authors hypothesize that the actual change in statistical distributions corresponds to the adaptation reaction of the biosphere to nonstandard geophysical characteristics of the 24th solar activity cycle and the probable long-term decrease in solar activity up to 2067.

Mixture EMOS model for calibrating ensemble forecasts of wind speed.

PubMed

Baran, S; Lerch, S

2016-03-01

Ensemble model output statistics (EMOS) is a statistical tool for post-processing forecast ensembles of weather variables obtained from multiple runs of numerical weather prediction models in order to produce calibrated predictive probability density functions. The EMOS predictive probability density function is given by a parametric distribution with parameters depending on the ensemble forecasts. We propose an EMOS model for calibrating wind speed forecasts based on weighted mixtures of truncated normal (TN) and log-normal (LN) distributions where model parameters and component weights are estimated by optimizing the values of proper scoring rules over a rolling training period. The new model is tested on wind speed forecasts of the 50 member European Centre for Medium-range Weather Forecasts ensemble, the 11 member Aire Limitée Adaptation dynamique Développement International-Hungary Ensemble Prediction System ensemble of the Hungarian Meteorological Service, and the eight-member University of Washington mesoscale ensemble, and its predictive performance is compared with that of various benchmark EMOS models based on single parametric families and combinations thereof. The results indicate improved calibration of probabilistic and accuracy of point forecasts in comparison with the raw ensemble and climatological forecasts. The mixture EMOS model significantly outperforms the TN and LN EMOS methods; moreover, it provides better calibrated forecasts than the TN-LN combination model and offers an increased flexibility while avoiding covariate selection problems. © 2016 The Authors Environmetrics Published by JohnWiley & Sons Ltd.

Extreme weather events in southern Germany - Climatological risk and development of a large-scale identification procedure

NASA Astrophysics Data System (ADS)

Matthies, A.; Leckebusch, G. C.; Rohlfing, G.; Ulbrich, U.

2009-04-01

Extreme weather events such as thunderstorms, hail and heavy rain or snowfall can pose a threat to human life and to considerable tangible assets. Yet there is a lack of knowledge about present day climatological risk and its economic effects, and its changes due to rising greenhouse gas concentrations. Therefore, parts of economy particularly sensitve to extreme weather events such as insurance companies and airports require regional risk-analyses, early warning and prediction systems to cope with such events. Such an attempt is made for southern Germany, in close cooperation with stakeholders. Comparing ERA40 and station data with impact records of Munich Re and Munich Airport, the 90th percentile was found to be a suitable threshold for extreme impact relevant precipitation events. Different methods for the classification of causing synoptic situations have been tested on ERA40 reanalyses. An objective scheme for the classification of Lamb's circulation weather types (CWT's) has proved to be most suitable for correct classification of the large-scale flow conditions. Certain CWT's have been turned out to be prone to heavy precipitation or on the other side to have a very low risk of such events. Other large-scale parameters are tested in connection with CWT's to find out a combination that has the highest skill to identify extreme precipitation events in climate model data (ECHAM5 and CLM). For example vorticity advection in 700 hPa shows good results, but assumes knowledge of regional orographic particularities. Therefore ongoing work is focused on additional testing of parameters that indicate deviations of a basic state of the atmosphere like the Eady Growth Rate or the newly developed Dynamic State Index. Evaluation results will be used to estimate the skill of the regional climate model CLM concerning the simulation of frequency and intensity of the extreme weather events. Data of the A1B scenario (2000-2050) will be examined for a possible climate change signal.

Volcanic Ash Data Assimilation System for Atmospheric Transport Model

NASA Astrophysics Data System (ADS)

Ishii, K.; Shimbori, T.; Sato, E.; Tokumoto, T.; Hayashi, Y.; Hashimoto, A.

2017-12-01

The Japan Meteorological Agency (JMA) has two operations for volcanic ash forecasts, which are Volcanic Ash Fall Forecast (VAFF) and Volcanic Ash Advisory (VAA). In these operations, the forecasts are calculated by atmospheric transport models including the advection process, the turbulent diffusion process, the gravitational fall process and the deposition process (wet/dry). The initial distribution of volcanic ash in the models is the most important but uncertain factor. In operations, the model of Suzuki (1983) with many empirical assumptions is adopted to the initial distribution. This adversely affects the reconstruction of actual eruption plumes.We are developing a volcanic ash data assimilation system using weather radars and meteorological satellite observation, in order to improve the initial distribution of the atmospheric transport models. Our data assimilation system is based on the three-dimensional variational data assimilation method (3D-Var). Analysis variables are ash concentration and size distribution parameters which are mutually independent. The radar observation is expected to provide three-dimensional parameters such as ash concentration and parameters of ash particle size distribution. On the other hand, the satellite observation is anticipated to provide two-dimensional parameters of ash clouds such as mass loading, top height and particle effective radius. In this study, we estimate the thickness of ash clouds using vertical wind shear of JMA numerical weather prediction, and apply for the volcanic ash data assimilation system.

Rainfall extremes, weather and climatic characterization over complex terrain: A data-driven approach based on signal enhancement methods and extreme value modeling

NASA Astrophysics Data System (ADS)

Pineda, Luis E.; Willems, Patrick

2017-04-01

Weather and climatic characterization of rainfall extremes is both of scientific and societal value for hydrometeorogical risk management, yet discrimination of local and large-scale forcing remains challenging in data-scarce and complex terrain environments. Here, we present an analysis framework that separate weather (seasonal) regimes and climate (inter-annual) influences using data-driven process identification. The approach is based on signal-to-noise separation methods and extreme value (EV) modeling of multisite rainfall extremes. The EV models use a semi-automatic parameter learning [1] for model identification across temporal scales. At weather scale, the EV models are combined with a state-based hidden Markov model [2] to represent the spatio-temporal structure of rainfall as persistent weather states. At climatic scale, the EV models are used to decode the drivers leading to the shift of weather patterns. The decoding is performed into a climate-to-weather signal subspace, built via dimension reduction of climate model proxies (e.g. sea surface temperature and atmospheric circulation) We apply the framework to the Western Andean Ridge (WAR) in Ecuador and Peru (0-6°S) using ground data from the second half of the 20th century. We find that the meridional component of winds is what matters for the in-year and inter-annual variability of high rainfall intensities alongside the northern WAR (0-2.5°S). There, low-level southerly winds are found as advection drivers for oceanic moist of the normal-rainy season and weak/moderate the El Niño (EN) type; but, the strong EN type and its unique moisture surplus is locally advected at lowlands in the central WAR. Moreover, the coastal ridges, south of 3°S dampen meridional airflows, leaving local hygrothermal gradients to control the in-year distribution of rainfall extremes and their anomalies. Overall, we show that the framework, which does not make any prior assumption on the explanatory power of the weather and climate drivers, allows identification of well-known features of the regional climate in a purely data-driven fashion. Thus, this approach shows potential for characterization of precipitation extremes in data-scarce and orographically complex regions in which model reconstructions are the only climate proxies References [1] Mínguez, R., F.J. Méndez, C. Izaguirre, M. Menéndez, and I.J. Losada (2010), Pseudooptimal parameter selection of non-stationary generalized extreme value models for environmental variables, Environ. Modell. Softw. 25, 1592-1607. [2] Pineda, L., P. Willems (2016), Multisite Downscaling of Seasonal Predictions to Daily Rainfall Characteristics over Pacific-Andean River Basins in Ecuador and Peru using a non-homogenous hidden Markov model, J. Hydrometeor, 17(2), 481-498, doi:10.1175/JHM-D-15-0040.1, http://journals.ametsoc.org/doi/full/10.1175/JHM-D-15-0040.1

Calls Forecast for the Moscow Ambulance Service. The Impact of Weather Forecast

NASA Astrophysics Data System (ADS)

Gordin, Vladimir; Bykov, Philipp

2015-04-01

We use the known statistics of the calls for the current and previous days to predict them for tomorrow and for the following days. We assume that this algorithm will work operatively, will cyclically update the available information and will move the horizon of the forecast. Sure, the accuracy of such forecasts depends on their lead time, and from a choice of some group of diagnoses. For comparison we used the error of the inertial forecast (tomorrow there will be the same number of calls as today). Our technology has demonstrated accuracy that is approximately two times better compared to the inertial forecast. We obtained the following result: the number of calls depends on the actual weather in the city as well as on its rate of change. We were interested in the accuracy of the forecast for 12-hour sum of the calls in real situations. We evaluate the impact of the meteorological errors [1] on the forecast errors of the number of Ambulance calls. The weather and the Ambulance calls number both have seasonal tendencies. Therefore, if we have medical information from one city only, we should separate the impacts of such predictors as "annual variations in the number of calls" and "weather". We need to consider the seasonal tendencies (associated, e. g. with the seasonal migration of the population) and the impact of the air temperature simultaneously, rather than sequentially. We forecasted separately the number of calls with diagnoses of cardiovascular group, where it was demonstrated the advantage of the forecasting method, when we use the maximum daily air temperature as a predictor. We have a chance to evaluate statistically the influence of meteorological factors on the dynamics of medical problems. In some cases it may be useful for understanding of the physiology of disease and possible treatment options. We can assimilate some personal archives of medical parameters for the individuals with concrete diseases and the relative meteorological archive. As a result we hope to evaluate how weather can influence the intensity of the disease. Thus, the knowledge of the weather forecast for several days will help us to predict a state of health. The person will be able to take some proactive actions to avoid the anticipated worsening of his health. Literature 1. A. N. Bagrov, F. L. Bykov, V. A. Gordin. Complex Forecast of Surface Meteorological Parameters. Meteorology and Hydrology, 2014, N 5, 5-16 (Russian), 283-291 (English). 2. Bykov, Ph.L., Gordin, V.A., Objective Analysis of the Structure of Three-Dimensional Atmospheric Fronts. Izvestia of Russian Academy of Sciences. Ser. The Physics of Atmosphere and Ocean, 48 (2) (2012), 172-188 (Russian), 152-168 (English), http://dx.doi.org/10.1134/S0001433812020053 3. V.A.Gordin. Mathematical Problems and Methods in Hydrodynamical Weather Forecasting. Amsterdam etc.: Gordon & Breach Publ. House, 2000. 4. V.A.Gordin. Mathematics, Computer, Weather Forecasting, and Other Mathematical Physics' Scenarios. Moscow, Fizmatlit, 2010, 2012 (Russian).

SPAGETTA: a Multi-Purpose Gridded Stochastic Weather Generator

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Huth, R.; Rotach, M. W.; Dabhi, H.

2017-12-01

SPAGETTA is a new multisite/gridded multivariate parametric stochastic weather generator (WG). Site-specific precipitation occurrence and amount are modelled by Markov chain and Gamma distribution, the non-precipitation variables are modelled by an autoregressive (AR) model conditioned on precipitation occurrence, and the spatial coherence of all variables is modelled following the Wilks' (2009) approach. SPAGETTA may be run in two modes. Mode 1: it is run as a classical WG, which is calibrated using weather series from multiple sites, and only then it may produce arbitrarily long synthetic series mimicking the spatial and temporal structure of the calibration data. To generate the weather series representing the future climate, the WG parameters are modified according to the climate change scenario, typically derived from GCM or RCM simulations. Mode 2: the user provides only basic information (not necessarily to be realistic) on the temporal and spatial auto-correlation structure of the weather variables and their mean annual cycle; the generator itself derives the parameters of the underlying AR model, which produces the multi-site weather series. Optionally, the user may add the spatially varying trend, which is superimposed to the synthetic series. The contribution consists of following parts: (a) Model of the WG. (b) Validation of WG in terms of the spatial temperature and precipitation characteristics, including characteristics of spatial hot/cold/dry/wet spells. (c) Results of the climate change impact experiment, in which the WG parameters representing the spatial and temporal variability are modified using the climate change scenarios and the effect on the above spatial validation indices is analysed. In this experiment, the WG is calibrated using the E-OBS gridded daily weather data for several European regions, and the climate change scenarios are derived from the selected RCM simulations (CORDEX database). (d) The second mode of operation will be demonstrated by results obtained while developing the methodology for assessing collective significance of trends in multi-site weather series. The performance of the proposed test statistics is assessed based on large number of realisations of synthetic series produced by WG assuming a given statistical structure and trend of the weather series.

Comparison of water absorption methods: testing the water absorption of recently quarried and weathered porous limestone on site and under laboratory conditions

NASA Astrophysics Data System (ADS)

Rozgonyi-Boissinot, Nikoletta; Agárdi, Tamás; Karolina Cebula, Ágnes; Török, Ákos

2017-04-01

The water absorption of weathering sensitive stones is a critical parameter that influences durability. The current paper compares different methods of water absorption tests by using on site and laboratory tests. The aims of the tests were to assess the water absorption of un-weathered quarry stones and various weathering forms occurring on porous limestone monuments. For the tests a Miocene porous limestone was used that occurs in Central and Western Hungary and especially near and in Budapest. Besides the Hungarian occurrences the same or very similar porous limestones are found in Austria, Slovakia and in the Czech Republic. Several quarries were operating in these countries. Due to the high workability the stone have been intensively used as construction material from the Roman period onward. The most prominent monuments made of this stone were built in Vienna and in Budapest during the 18th -19th century and in the early 20th century. The high porosity and the micro-fabric of the stone make it prone to frost- and salt weathering. Three different limestone types were tested representing coarse-, medium- and fine grained lithologies. The test methods included Rilem tube (Karsten tube) tests and capillary water absorption tests. The latter methodology has been described in detail in EN 1925:2000. The test results of on-site tests of weathered porous limestone clearly show that the water absorption of dissolved limestone surfaces and crumbling or micro-cracked limestone is similar. The water absorption curves have similar inclinations marking high amount of absorbed water. To the contrary, the white weathering crusts covered stone blocks and black crusts have significantly lower water absorptions and many of these crusts are considered as very tight almost impermeable surfaces. Capillary water absorption tests in the laboratory allowed the determination of maximum water absorption of quarried porous limestone. Specimens were placed in 3 mm of water column and the absorbed amount of water was detected. The obtained 29-30m% water absorption values compared to the 30-35m% of the total porosity of the stone, clearly suggest that the pores can be saturated with water under standard barometric pressure and therefore the tested porous Miocene limestones are very prone to salt attack.

Bayesian quantitative precipitation forecasts in terms of quantiles

NASA Astrophysics Data System (ADS)

Bentzien, Sabrina; Friederichs, Petra

2014-05-01

Ensemble prediction systems (EPS) for numerical weather predictions on the mesoscale are particularly developed to obtain probabilistic guidance for high impact weather. An EPS not only issues a deterministic future state of the atmosphere but a sample of possible future states. Ensemble postprocessing then translates such a sample of forecasts into probabilistic measures. This study focus on probabilistic quantitative precipitation forecasts in terms of quantiles. Quantiles are particular suitable to describe precipitation at various locations, since no assumption is required on the distribution of precipitation. The focus is on the prediction during high-impact events and related to the Volkswagen Stiftung funded project WEX-MOP (Mesoscale Weather Extremes - Theory, Spatial Modeling and Prediction). Quantile forecasts are derived from the raw ensemble and via quantile regression. Neighborhood method and time-lagging are effective tools to inexpensively increase the ensemble spread, which results in more reliable forecasts especially for extreme precipitation events. Since an EPS provides a large amount of potentially informative predictors, a variable selection is required in order to obtain a stable statistical model. A Bayesian formulation of quantile regression allows for inference about the selection of predictive covariates by the use of appropriate prior distributions. Moreover, the implementation of an additional process layer for the regression parameters accounts for spatial variations of the parameters. Bayesian quantile regression and its spatially adaptive extension is illustrated for the German-focused mesoscale weather prediction ensemble COSMO-DE-EPS, which runs (pre)operationally since December 2010 at the German Meteorological Service (DWD). Objective out-of-sample verification uses the quantile score (QS), a weighted absolute error between quantile forecasts and observations. The QS is a proper scoring function and can be decomposed into reliability, resolutions and uncertainty parts. A quantile reliability plot gives detailed insights in the predictive performance of the quantile forecasts.

Objective classification of atmospheric circulation over southern Scandinavia

NASA Astrophysics Data System (ADS)

Linderson, Maj-Lena

2001-02-01

A method for calculating circulation indices and weather types following the Lamb classification is applied to southern Scandinavia. The main objective is to test the ability of the method to describe the atmospheric circulation over the area, and to evaluate the extent to which the pressure patterns determine local precipitation and temperature in Scania, southernmost Sweden. The weather type classification method works well and produces distinct groups. However, the variability within the group is large with regard to the location of the low pressure centres, which may have implications for the precipitation over the area. The anticyclonic weather type dominates, together with the cyclonic and westerly types. This deviates partly from the general picture for Sweden and may be explained by the southerly location of the study area. The cyclonic type is most frequent in spring, although cloudiness and amount of rain are lowest during this season. This could be explained by the occurrence of weaker cyclones or low air humidity during this time of year. Local temperature and precipitation were modelled by stepwise regression for each season, designating weather types as independent variables. Only the winter season-modelled temperature and precipitation show a high and robust correspondence to the observed temperature and precipitation, even though <60% of the precipitation variance is explained. In the other seasons, the connection between atmospheric circulation and the local temperature and precipitation is low. Other meteorological parameters may need to be taken into account. The time and space resolution of the mean sea level pressure (MSLP) grid may affect the results, as many important features might not be covered by the classification. Local physiography may also influence the local climate in a way that cannot be described by the atmospheric circulation pattern alone, stressing the importance of using more than one observation series.

AWE: Aviation Weather Data Visualization

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Lodha, Suresh K.

2001-01-01

The two official sources for aviation weather reports both require the pilot to mentally visualize the provided information. In contrast, our system, Aviation Weather Environment (AWE) presents aviation specific weather available to pilots in an easy to visualize form. We start with a computer-generated textual briefing for a specific area. We map this briefing onto a grid specific to the pilot's route that includes only information relevant to his flight route that includes only information relevant to his flight as defined by route, altitude, true airspeed, and proposed departure time. By modifying various parameters, the pilot can use AWE as a planning tool as well as a weather briefing tool.

Numerical simulation of raindrop scattering for C-band dual-polarization Doppler weather radar parameters

NASA Astrophysics Data System (ADS)

Teng, Shiwen; Hu, Hanfeng; Liu, Chao; Hu, Fangchao; Wang, Zhenhui; Yin, Yan

2018-07-01

The dual-polarization Doppler weather radar plays an important role in precipitation estimation and weather monitoring. For radar applications, the retrieval of precipitation microphysical characteristics is of great importance, and requires assumed scattering properties of raindrops. This study numerically investigates the scattering properties of raindrops and considers the capability of numerical models for raindrop scattering simulations. Besides the widely used spherical and oblate spheroid models, a non-spheroidal model based on realistic raindrop geometries with a flattened base and a smoothly rounded top is also considered. To study the effects of scattering simulations on radar applications, the polarization radar parameters are modeled based on the scattering properties calculated by different scattering models (i.e. the extended boundary condition T-matrix (EBCM) method and discretize dipole approximation (DDA)) and given size distributions, and compared with observations of a C-band dual-polarization radar. Note that, when the spatial resolution of the DDA simulation is large enough, the DDA results can be very close to those of the EBCM. Most simulated radar variables, except copolar correlation coefficient, match closely with radar observations, and the results based on different non-spheroidal models considered in this study show little differences. The comparison indicates that, even for the C-band radar, the effects of raindrop shape and canting angle on scattering properties are relatively minor due to relatively small size parameters. However, although more realistic particle geometry model may provide better representation on raindrop shape, considering the relatively time-consuming and complex scattering simulations for those particles, the oblate spheroid model with appropriate axis ratio variation is suggested for polarization radar applications.

Epidemiological, clinical and climatic characteristics of dengue fever in Kaohsiung City, Taiwan with implication for prevention and control.

PubMed

Chang, Chiu-Jung; Chen, Colin S; Tien, Chien-Jung; Lu, Mei-Rou

2018-01-01

The early identification of dengue infection is essential for timely and effective quarantine and vector control measures for preventing outbreaks of the disease. Kaohsiung City is responsible for most of the dengue cases in Taiwan. Thus, this study aims to identify major factors involved in the prevalence of dengue fever by analyzing the epidemiological and clinical characteristics, and to establish associations between weather parameters and dengue occurrence in this City. A retrospective study was conducted with 3,322 confirmed dengue cases. Appropriate statistical methods were used to compare differences and correlations between dengue occurrence and demographic, clinical and weather parameters. The outbreak of dengue fever was found to be initiated by imported cases of dengue viruses from other endemic countries. Most of the confirmed cases were not reported to the health authority during the first visit to a doctor, and it took a median of 5 days after the appearance of the first syndromes for medical personnel to report suspected dengue cases. Accordingly, Aedes mosquitoes would have enough time to be infected and transmit the dengue virus. The diagnosis and notification criteria should not only include common symptoms of fever, myalgia, headache, skin rash and arthralgia, but should also be adjusted to include the most frequent symptoms of loss of appetite and feeling thirsty to shorten the notification time. Significantly positive correlations were found between the number of confirmed cases and weather parameters (i.e., temperature, rainfall and relative humidity) at a time lag of 1 month and 2 months. The predictive models for dengue occurrence using these three parameters at a 2-month lag time were established. The surveillance of imported cases, adjustment of notification criteria and application of climatic predictive models would be helpful in strengthening the dengue early warning surveillance system.

Environmental impact on construction limestone at humid regions with an emphasis on salt weathering, Al-hambra islamic archaeological site, Granada City, Spain: case study

NASA Astrophysics Data System (ADS)

Kamh, G. M. E.

2007-08-01

Al-hambra is an immense and valuable archaeological site in Spain built on Sabika hill with red brick and natural sandy limestone. It exhibits weathering features indicating salt weathering process. The main aim of this study is to examine weathering processes and intensity acting on Al-hambra. Rock petrography and mineralogical composition have been examined using thin sections, scanning electron microscope, X-ray diffraction and X-ray fluorescence; limits of rock’s physical parameters using ultrasonic waves and mercury porosimeter; rock salt content through hydrochemical analysis. Salts attacking this structure are mainly from wet deposition of air pollutants on the long term chemical alteration of rock’s carbonate content to its equivalent salts. The salts’ concentration limit within the examined rock samples is considerably low but it is effective on the long run through hydration of sulphate salts and/or crystallization of chloride salts. Rock texture type and its silica as well as clay content reduces its resistance to internal stresses by salts as well as wetting and drying cycles at such humid area. The recession in limits of physical parameters examined for deep seated and weathered limestone samples quantitatively reflects weathering intensity on Al-hambra.

A Coupled Surface Nudging Scheme for use in Retrospective ...

EPA Pesticide Factsheets

A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem modeling. This scheme is known as the flux-adjusting surface data assimilation system (FASDAS) developed by Alapaty et al. (2008). This scheme provides continuous adjustments for soil moisture and temperature (via indirect nudging) and for surface air temperature and water vapor mixing ratio (via direct nudging). The simultaneous application of indirect and direct nudging maintains greater consistency between the soil temperature–moisture and the atmospheric surface layer mass-field variables. The new method, FASDAS, consistently improved the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as well as for high resolution regional climate predictions. This new capability has been released in WRF Version 3.8 as option grid_sfdda = 2. This new capability increased the accuracy of atmospheric inputs for use air quality, hydrology, and ecosystem modeling research to improve the accuracy of respective end-point research outcome. IMPACT: A new method, FASDAS, was implemented into the WRF model to consistently improve the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as wel

Significance of settling model structures and parameter subsets in modelling WWTPs under wet-weather flow and filamentous bulking conditions.

PubMed

Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen; Plósz, Benedek Gy

2014-10-15

Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D) SST model structures and parameters. We identify the critical sources of uncertainty in WWTP models through global sensitivity analysis (GSA) using the Benchmark simulation model No. 1 in combination with first- and second-order 1-D SST models. The results obtained illustrate that the contribution of settling parameters to the total variance of the key WWTP process outputs significantly depends on the influent flow and settling conditions. The magnitude of the impact is found to vary, depending on which type of 1-D SST model is used. Therefore, we identify and recommend potential parameter subsets for WWTP model calibration, and propose optimal choice of 1-D SST models under different flow and settling boundary conditions. Additionally, the hydraulic parameters in the second-order SST model are found significant under dynamic wet-weather flow conditions. These results highlight the importance of developing a more mechanistic based flow-dependent hydraulic sub-model in second-order 1-D SST models in the future. Copyright © 2014 Elsevier Ltd. All rights reserved.

NWP model forecast skill optimization via closure parameter variations

NASA Astrophysics Data System (ADS)

Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.

2012-04-01

We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.

Space Weather Activities of IONOLAB Group: TEC Mapping

NASA Astrophysics Data System (ADS)

Arikan, F.; Yilmaz, A.; Arikan, O.; Sayin, I.; Gurun, M.; Akdogan, K. E.; Yildirim, S. A.

2009-04-01

Being a key player in Space Weather, ionospheric variability affects the performance of both communication and navigation systems. To improve the performance of these systems, ionosphere has to be monitored. Total Electron Content (TEC), line integral of the electron density along a ray path, is an important parameter to investigate the ionospheric variability. A cost-effective way of obtaining TEC is by using dual-frequency GPS receivers. Since these measurements are sparse in space, accurate and robust interpolation techniques are needed to interpolate (or map) the TEC distribution for a given region in space. However, the TEC data derived from GPS measurements contain measurement noise, model and computational errors. Thus, it is necessary to analyze the interpolation performance of the techniques on synthetic data sets that can represent various ionospheric states. By this way, interpolation performance of the techniques can be compared over many parameters that can be controlled to represent the desired ionospheric states. In this study, Multiquadrics, Inverse Distance Weighting (IDW), Cubic Splines, Ordinary and Universal Kriging, Random Field Priors (RFP), Multi-Layer Perceptron Neural Network (MLP-NN), and Radial Basis Function Neural Network (RBF-NN) are employed as the spatial interpolation algorithms. These mapping techniques are initially tried on synthetic TEC surfaces for parameter and coefficient optimization and determination of error bounds. Interpolation performance of these methods are compared on synthetic TEC surfaces over the parameters of sampling pattern, number of samples, the variability of the surface and the trend type in the TEC surfaces. By examining the performance of the interpolation methods, it is observed that both Kriging, RFP and NN have important advantages and possible disadvantages depending on the given constraints. It is also observed that the determining parameter in the error performance is the trend in the Ionosphere. Optimization of the algorithms in terms of their performance parameters (like the choice of the semivariogram function for Kriging algorithms and the hidden layer and neuron numbers for MLP-NN) mostly depend on the behavior of the ionosphere at that given time instant for the desired region. The sampling pattern and number of samples are the other important parameters that may contribute to the higher errors in reconstruction. For example, for all of the above listed algorithms, hexagonal regular sampling of the ionosphere provides the lowest reconstruction error and the performance significantly degrades as the samples in the region become sparse and clustered. The optimized models and coefficients are applied to regional GPS-TEC mapping using the IONOLAB-TEC data (www.ionolab.org). Both Kriging combined with Kalman Filter and dynamic modeling of NN are also implemented as first trials of TEC and space weather predictions.

Development of a standard accelerated weathering test for aggregates using dimethyl sulfoxide (DMSO) : final report.

DOT National Transportation Integrated Search

1986-09-01

A standard accelerated weathering test using Dimethyl Sulfoxide (DMSO) was developed to simulate the chemical degradation of basaltic rocks. After a thorough study of the parameters affecting the current procedure, such as container geometry, aggrega...

Estimation of radiocesium dietary intake from time series data of radiocesium concentrations in sewer sludge.

PubMed

Pratama, Mochamad Adhiraga; Takahara, Shogo; Munakata, Masahiro; Yoneda, Minoru

2018-06-01

After the Fukushima accident, it became important to determine the quantity of radionuclide ingested by inhabitants. The most common methods currently used to obtain such data are the "market basket" (MB) and "duplicate" (DP) methods. However, it is difficult to conduct monitorings using these methods with sufficient frequency as they are high cost and time-consuming. The present study proposes a new method to estimate the ingestion of radionuclides, based on the time-dependent concentrations of radiocesium in sewer sludge, which addresses the uncertainties of the two common methods. The newly proposed method, which we designate as SL, consists of three steps: (1) the separation of wet weather and dry weather data, (2) determining the mass balance of the wastewater treatment plant (WWTP), and (3) developing a reverse biokinetic model to relate the amount of radionuclides ingested to the amounts contained in the sewer sludge. We tested the new method using the time-dependent radiocesium concentrations in sewer sludge from the WWTP in Fukushima City. The results from the SL method agreed to those from the MB while overestimated those from DP method. The trend lines for all three methods, however, are in good agreement. Sensitivity analyses of SL method indicate further studies on uncertainties of sensitive parameters are deemed necessary to improve the accuracy of the method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Approaches to Improve the Performances of the Sea Launch System Performances

NASA Astrophysics Data System (ADS)

Tatarevs'kyy, K.

2002-01-01

The paper dwells on the outlines of the techniques of on-line pre-launch analysis on possibility of safe and reliable LV launch off floating launch system, when actual launch conditions (weather, launcher motion parameters) are beyond design limitations. The technique guarantees to follow the take-off LV trajectory limitations (the shock-free launch) and allows the improvement of the operat- ing characteristics of the floating launch systems at the expense of possibility to authorize the launch even if a number of weather and launcher motion parameters restrictions are exceeded. This paper ideas are applied for LV of Zenit-type launches off tilting launch platform, operative within Sea Launch. The importance, novelty and urgency of the approach under consideration is explained by the fact that the application during floating launch systems operation allows the bringing down of the num- ber of weather-conditioned launch abort cases. And this, in its part, increases the trustworthiness of the mission fulfillment on specific spacecraft injection, since, in the long run, the launch abort may cause the crossing of allowable wait threshold and accordingly the mission abort. All previous launch kinds for these LV did not require the development of the special technique of pre-launch analysis on launch possibility, since weather limitations for stationary launcher condi- tions are basically reduced to the wind velocity limitations. This parameter is reliably monitored and is sure to influence the launch dynamics. So the measured wind velocity allows the thorough picture on the possibility of the launch off the ground-based launcher. Since the floating launch systems commit complex and continuous movements under the exposure of the wind and the waves, the number of parameters is increased and, combined differently, they do not always make the issue on shockless launch critical. The proposed technique of the pre-launch analysis of the forthcoming launch dynamics with the consideration of the launch conditions (weather, launcher motion parameters, actual LV and carried SC performance) allow the evaluation of the actual combination of launch environment influence on the possibility of shockless launch. On the basis of the analysis the launch permissibility deci- sion is taken, even if some separate parameters are beyond the design range.

Process-based modeling of silicate mineral weathering responses to increasing atmospheric CO2 and climate change

NASA Astrophysics Data System (ADS)

Banwart, Steven A.; Berg, Astrid; Beerling, David J.

2009-12-01

A mathematical model describes silicate mineral weathering processes in modern soils located in the boreal coniferous region of northern Europe. The process model results demonstrate a stabilizing biological feedback mechanism between atmospheric CO2 levels and silicate weathering rates as is generally postulated for atmospheric evolution. The process model feedback response agrees within a factor of 2 of that calculated by a weathering feedback function of the type generally employed in global geochemical carbon cycle models of the Earth's Phanerozoic CO2 history. Sensitivity analysis of parameter values in the process model provides insight into the key mechanisms that influence the strength of the biological feedback to weathering. First, the process model accounts for the alkalinity released by weathering, whereby its acceleration stabilizes pH at values that are higher than expected. Although the process model yields faster weathering with increasing temperature, because of activation energy effects on mineral dissolution kinetics at warmer temperature, the mineral dissolution rate laws utilized in the process model also result in lower dissolution rates at higher pH values. Hence, as dissolution rates increase under warmer conditions, more alkalinity is released by the weathering reaction, helping maintain higher pH values thus stabilizing the weathering rate. Second, the process model yields a relatively low sensitivity of soil pH to increasing plant productivity. This is due to more rapid decomposition of dissolved organic carbon (DOC) under warmer conditions. Because DOC fluxes strongly influence the soil water proton balance and pH, this increased decomposition rate dampens the feedback between productivity and weathering. The process model is most sensitive to parameters reflecting soil structure; depth, porosity, and water content. This suggests that the role of biota to influence these characteristics of the weathering profile is as important, if not more important, than the role of biota to influence mineral dissolution rates through changes in soil water chemistry. This process-modeling approach to quantify the biological weathering feedback to atmospheric CO2 demonstrates the potential for a far more mechanistic description of weathering feedback in simulations of the global geochemical carbon cycle.

Quantifying rainfall-derived inflow and infiltration in sanitary sewer systems based on conductivity monitoring

NASA Astrophysics Data System (ADS)

Zhang, Mingkai; Liu, Yanchen; Cheng, Xun; Zhu, David Z.; Shi, Hanchang; Yuan, Zhiguo

2018-03-01

Quantifying rainfall-derived inflow and infiltration (RDII) in a sanitary sewer is difficult when RDII and overflow occur simultaneously. This study proposes a novel conductivity-based method for estimating RDII. The method separately decomposes rainfall-derived inflow (RDI) and rainfall-induced infiltration (RII) on the basis of conductivity data. Fast Fourier transform was adopted to analyze variations in the flow and water quality during dry weather. Nonlinear curve fitting based on the least squares algorithm was used to optimize parameters in the proposed RDII model. The method was successfully applied to real-life case studies, in which inflow and infiltration were successfully estimated for three typical rainfall events with total rainfall volumes of 6.25 mm (light), 28.15 mm (medium), and 178 mm (heavy). Uncertainties of model parameters were estimated using the generalized likelihood uncertainty estimation (GLUE) method and were found to be acceptable. Compared with traditional flow-based methods, the proposed approach exhibits distinct advantages in estimating RDII and overflow, particularly when the two processes happen simultaneously.

Tethered Satellites as an Enabling Platform for Operational Space Weather Monitoring Systems

NASA Technical Reports Server (NTRS)

Gilchrist, Brian E.; Krause, Linda Habash; Gallagher, Dennis Lee; Bilen, Sven Gunnar; Fuhrhop, Keith; Hoegy, Walt R.; Inderesan, Rohini; Johnson, Charles; Owens, Jerry Keith; Powers, Joseph;

Uncertainty analysis of scintillometers methods in measuring sensible heat fluxes of forest ecosystem

NASA Astrophysics Data System (ADS)

Zheng, N.

2017-12-01

Sensible heat flux (H) is one of the driving factors of surface turbulent motion and energy exchange. Therefore, it is particularly important to measure sensible heat flux accurately at the regional scale. However, due to the heterogeneity of the underlying surface, hydrothermal regime, and different weather conditions, it is difficult to estimate the represented flux at the kilometer scale. The scintillometer have been developed into an effective and universal equipment for deriving heat flux at the regional-scale which based on the turbulence effect of light in the atmosphere since the 1980s. The parameter directly obtained by the scintillometer is the structure parameter of the refractive index of air based on the changes of light intensity fluctuation. Combine with parameters such as temperature structure parameter, zero-plane displacement, surface roughness, wind velocity, air temperature and the other meteorological data heat fluxes can be derived. These additional parameters increase the uncertainties of flux because the difference between the actual feature of turbulent motion and the applicable conditions of turbulence theory. Most previous studies often focused on the constant flux layers that are above the rough sub-layers and homogeneous flat surfaces underlying surfaces with suitable weather conditions. Therefore, the criteria and modified forms of key parameters are invariable. In this study, we conduct investment over the hilly area of northern China with different plants, such as cork oak, cedar-black and locust. On the basis of key research on the threshold and modified forms of saturation with different turbulence intensity, modified forms of Bowen ratio with different drying-and-wetting conditions, universal function for the temperature structure parameter under different atmospheric stability, the dominant sources of uncertainty will be determined. The above study is significant to reveal influence mechanism of uncertainty and explore influence degree of uncertainty with quantitative analysis. The study can provide theoretical basis and technical support for accurately measuring sensible heat fluxes of forest ecosystem with scintillometer method, and can also provide work foundation for further study on role of forest ecosystem in energy balance and climate change.

Land-surface influences on weather and climate

NASA Technical Reports Server (NTRS)

Baer, F.; Mintz, Y.

1984-01-01

Land-surface influences on weather and climate are reviewed. The interrelationship of vegetation, evapotranspiration, atmospheric circulation, and climate is discussed. Global precipitation, soil moisture, the seasonal water cycle, heat transfer, and atmospheric temperature are among the parameters considered in the context of a general biosphere model.

Relationship between fine particulate matter, weather condition and daily non-accidental mortality in Shanghai, China: A Bayesian approach.

PubMed

Fang, Xin; Fang, Bo; Wang, Chunfang; Xia, Tian; Bottai, Matteo; Fang, Fang; Cao, Yang

2017-01-01

There are concerns that the reported association of ambient fine particulate matter (PM2.5) with mortality might be a mixture of PM2.5 and weather conditions. We evaluated the effects of extreme weather conditions and weather types on mortality as well as their interactions with PM2.5 concentrations in a time series study. Daily non-accidental deaths, individual demographic information, daily average PM2.5 concentrations and meteorological data between 2012 and 2014 were obtained from Shanghai, China. Days with extreme weather conditions were identified. Six synoptic weather types (SWTs) were generated. The generalized additive model was set up to link the mortality with PM2.5 and weather conditions. Parameter estimation was based on Bayesian methods using both the Jeffreys' prior and an informative normal prior in a sensitivity analysis. We estimate the percent increase in non-accidental mortality per 10 μg/m3 increase in PM2.5 concentration and constructed corresponding 95% credible interval (CrI). In total, 336,379 non-accidental deaths occurred during the study period. Average daily deaths were 307. The results indicated that per 10 μg/m3 increase in daily average PM2.5 concentration alone corresponded to 0.26-0.35% increase in daily non-accidental mortality in Shanghai. Statistically significant positive associations between PM2.5 and mortality were found for favorable SWTs when considering the interaction between PM2.5 and SWTs. The greatest effect was found in hot dry SWT (percent increase = 1.28, 95% CrI: 0.72, 1.83), followed by warm humid SWT (percent increase = 0.64, 95% CrI: 0.15, 1.13). The effect of PM2.5 on non-accidental mortality differed under specific extreme weather conditions and SWTs. Environmental policies and actions should take into account the interrelationship between the two hazardous exposures.

Relationship between fine particulate matter, weather condition and daily non-accidental mortality in Shanghai, China: A Bayesian approach

PubMed Central

Wang, Chunfang; Xia, Tian; Bottai, Matteo; Fang, Fang; Cao, Yang

2017-01-01

There are concerns that the reported association of ambient fine particulate matter (PM2.5) with mortality might be a mixture of PM2.5 and weather conditions. We evaluated the effects of extreme weather conditions and weather types on mortality as well as their interactions with PM2.5 concentrations in a time series study. Daily non-accidental deaths, individual demographic information, daily average PM2.5 concentrations and meteorological data between 2012 and 2014 were obtained from Shanghai, China. Days with extreme weather conditions were identified. Six synoptic weather types (SWTs) were generated. The generalized additive model was set up to link the mortality with PM2.5 and weather conditions. Parameter estimation was based on Bayesian methods using both the Jeffreys’ prior and an informative normal prior in a sensitivity analysis. We estimate the percent increase in non-accidental mortality per 10 μg/m3 increase in PM2.5 concentration and constructed corresponding 95% credible interval (CrI). In total, 336,379 non-accidental deaths occurred during the study period. Average daily deaths were 307. The results indicated that per 10 μg/m3 increase in daily average PM2.5 concentration alone corresponded to 0.26–0.35% increase in daily non-accidental mortality in Shanghai. Statistically significant positive associations between PM2.5 and mortality were found for favorable SWTs when considering the interaction between PM2.5 and SWTs. The greatest effect was found in hot dry SWT (percent increase = 1.28, 95% CrI: 0.72, 1.83), followed by warm humid SWT (percent increase = 0.64, 95% CrI: 0.15, 1.13). The effect of PM2.5 on non-accidental mortality differed under specific extreme weather conditions and SWTs. Environmental policies and actions should take into account the interrelationship between the two hazardous exposures. PMID:29121092

Using Satellite Data in Weather Forecasting: I

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Suggs, Ronnie J.; Lecue, Juan M.

2006-01-01

The GOES Product Generation System (GPGS) is a set of computer codes and scripts that enable the assimilation of real-time Geostationary Operational Environmental Satellite (GOES) data into regional-weather-forecasting mathematical models. The GPGS can be used to derive such geophysical parameters as land surface temperature, the amount of precipitable water, the degree of cloud cover, the surface albedo, and the amount of insolation from satellite measurements of radiant energy emitted by the Earth and its atmosphere. GPGS incorporates a priori information (initial guesses of thermodynamic parameters of the atmosphere) and radiometric measurements from the geostationary operational environmental satellites along with mathematical models of physical principles that govern the transfer of energy in the atmosphere. GPGS solves the radiative-transfer equation and provides the resulting data products in formats suitable for use by weather-forecasting computer programs. The data-assimilation capability afforded by GPGS offers the potential to improve local weather forecasts ranging from 3 hours to 2 days - especially with respect to temperature, humidity, cloud cover, and the probability of precipitation. The improvements afforded by GPGS could be of interest to news media, utility companies, and other organizations that utilize regional weather forecasts.

Sensor performance and weather effects modeling for intelligent transportation systems (ITS) applications

NASA Astrophysics Data System (ADS)

Everson, Jeffrey H.; Kopala, Edward W.; Lazofson, Laurence E.; Choe, Howard C.; Pomerleau, Dean A.

1995-01-01

Optical sensors are used for several ITS applications, including lateral control of vehicles, traffic sign recognition, car following, autonomous vehicle navigation, and obstacle detection. This paper treats the performance assessment of a sensor/image processor used as part of an on-board countermeasure system to prevent single vehicle roadway departure crashes. Sufficient image contrast between objects of interest and backgrounds is an essential factor influencing overall system performance. Contrast is determined by material properties affecting reflected/radiated intensities, as well as weather and visibility conditions. This paper discusses the modeling of these parameters and characterizes the contrast performance effects due to reduced visibility. The analysis process first involves generation of inherent road/off- road contrasts, followed by weather effects as a contrast modification. The sensor is modeled as a charge coupled device (CCD), with variable parameters. The results of the sensor/weather modeling are used to predict the performance on an in-vehicle warning system under various levels of adverse weather. Software employed in this effort was previously developed for the U.S. Air Force Wright Laboratory to determine target/background detection and recognition ranges for different sensor systems operating under various mission scenarios.

Space weather modeling using artificial neural network. (Slovak Title: Modelovanie kozmického počasia umelou neurónovou sietou)

NASA Astrophysics Data System (ADS)

Valach, F.; Revallo, M.; Hejda, P.; Bochníček, J.

2010-12-01

Our modern society with its advanced technology is becoming increasingly vulnerable to the Earth's system disorders originating in explosive processes on the Sun. Coronal mass ejections (CMEs) blasted into interplanetary space as gigantic clouds of ionized gas can hit Earth within a few hours or days and cause, among other effects, geomagnetic storms - perhaps the best known manifestation of solar wind interaction with Earth's magnetosphere. Solar energetic particles (SEP), accelerated to near relativistic energy during large solar storms, arrive at the Earth's orbit even in few minutes and pose serious risk to astronauts traveling through the interplanetary space. These and many other threats are the reason why experts pay increasing attention to space weather and its predictability. For research on space weather, it is typically necessary to examine a large number of parameters which are interrelated in a complex non-linear way. One way to cope with such a task is to use an artificial neural network for space weather modeling, a tool originally developed for artificial intelligence. In our contribution, we focus on practical aspects of the neural networks application to modeling and forecasting selected space weather parameters.

Biocide leaching during field experiments on treated articles.

PubMed

Schoknecht, Ute; Mathies, Helena; Wegner, Robby

2016-01-01

Biocidal products can be sources of active substances in surface waters caused by weathering of treated articles. Marketing and use of biocidal products can be limited according to the European Biocidal Products Regulation if unacceptable risks to the environment are expected. Leaching of active substances from treated articles was observed in field experiments to obtain information on leaching processes and investigate the suitability of a proposed test method. Leaching under weathering conditions proceeds discontinuously and tends to decrease with duration of exposure. It does not only mainly depend on the availability of water but is also controlled by transport processes within the materials and stability of the observed substances. Runoff amount proved to be a suitable basis to compare results from different experiments. Concentrations of substances are higher in runoff collected from vertical surfaces compared to horizontal ones, whereas the leached amounts per surface area are higher from horizontal surfaces. Gaps in mass balances indicate that additional processes such as degradation and evaporation may be relevant to the fate of active substances in treated articles. Leached amounts of substances were considerably higher when the materials were exposed to intermittent water contact under laboratory conditions as compared to weathering of vertically exposed surfaces. Experiences from the field experiments were used to define parameters of a procedure that is now provided to fulfil the requirements of the Biocidal Products Regulation. The experiments confirmed that the amount of water which is in contact with exposed surfaces is the crucial parameter determining leaching of substances.

Genetically optimizing weather predictions

NASA Astrophysics Data System (ADS)

Potter, S. B.; Staats, Kai; Romero-Colmenero, Encarni

2016-07-01

humidity, air pressure, wind speed and wind direction) into a database. Built upon this database, we have developed a remarkably simple approach to derive a functional weather predictor. The aim is provide up to the minute local weather predictions in order to e.g. prepare dome environment conditions ready for night time operations or plan, prioritize and update weather dependent observing queues. In order to predict the weather for the next 24 hours, we take the current live weather readings and search the entire archive for similar conditions. Predictions are made against an averaged, subsequent 24 hours of the closest matches for the current readings. We use an Evolutionary Algorithm to optimize our formula through weighted parameters. The accuracy of the predictor is routinely tested and tuned against the full, updated archive to account for seasonal trends and total, climate shifts. The live (updated every 5 minutes) SALT weather predictor can be viewed here: http://www.saao.ac.za/ sbp/suthweather_predict.html

The Pedestrian Detection Method Using an Extension Background Subtraction about the Driving Safety Support Systems

NASA Astrophysics Data System (ADS)

Muranaka, Noriaki; Date, Kei; Tokumaru, Masataka; Imanishi, Shigeru

In recent years, the traffic accident occurs frequently with explosion of traffic density. Therefore, we think that the safe and comfortable transportation system to defend the pedestrian who is the traffic weak is necessary. First, we detect and recognize the pedestrian (the crossing person) by the image processing. Next, we inform all the drivers of the right or left turn that the pedestrian exists by the sound and the image and so on. By prompting a driver to do safe driving in this way, the accident to the pedestrian can decrease. In this paper, we are using a background subtraction method for the movement detection of the movement object. In the background subtraction method, the update method in the background was important, and as for the conventional way, the threshold values of the subtraction processing and background update were identical. That is, the mixing rate of the input image and the background image of the background update was a fixation value, and the fine tuning which corresponded to the environment change of the weather was difficult. Therefore, we propose the update method of the background image that the estimated mistake is difficult to be amplified. We experiment and examines in the comparison about five cases of sunshine, cloudy, evening, rain, sunlight change, except night. This technique can set separately the threshold values of the subtraction processing and background update processing which suited the environmental condition of the weather and so on. Therefore, the fine tuning becomes possible freely in the mixing rate of the input image and the background image of the background update. Because the setting of the parameter which suited an environmental condition becomes important to minimize mistaking percentage, we examine about the setting of a parameter.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Chang; Deng, Na; Wang, Haimin

Adverse space-weather effects can often be traced to solar flares, the prediction of which has drawn significant research interests. The Helioseismic and Magnetic Imager (HMI) produces full-disk vector magnetograms with continuous high cadence, while flare prediction efforts utilizing this unprecedented data source are still limited. Here we report results of flare prediction using physical parameters provided by the Space-weather HMI Active Region Patches (SHARP) and related data products. We survey X-ray flares that occurred from 2010 May to 2016 December and categorize their source regions into four classes (B, C, M, and X) according to the maximum GOES magnitude ofmore » flares they generated. We then retrieve SHARP-related parameters for each selected region at the beginning of its flare date to build a database. Finally, we train a machine-learning algorithm, called random forest (RF), to predict the occurrence of a certain class of flares in a given active region within 24 hr, evaluate the classifier performance using the 10-fold cross-validation scheme, and characterize the results using standard performance metrics. Compared to previous works, our experiments indicate that using the HMI parameters and RF is a valid method for flare forecasting with fairly reasonable prediction performance. To our knowledge, this is the first time that RF has been used to make multiclass predictions of solar flares. We also find that the total unsigned quantities of vertical current, current helicity, and flux near the polarity inversion line are among the most important parameters for classifying flaring regions into different classes.« less

Exploring Model Error through Post-processing and an Ensemble Kalman Filter on Fire Weather Days

NASA Astrophysics Data System (ADS)

Erickson, Michael J.

The proliferation of coupling atmospheric ensemble data to models in other related fields requires a priori knowledge of atmospheric ensemble biases specific to the desired application. In that spirit, this dissertation focuses on elucidating atmospheric ensemble model bias and error through a variety of different methods specific to fire weather days (FWDs) over the Northeast United States (NEUS). Other than a handful of studies that use models to predict fire indices for single fire seasons (Molders 2008, Simpson et al. 2014), an extensive exploration of model performance specific to FWDs has not been attempted. Two unique definitions for FWDs are proposed; one that uses pre-existing fire indices (FWD1) and another from a new statistical fire weather index (FWD2) relating fire occurrence and near-surface meteorological observations. Ensemble model verification reveals FWDs to have warmer (> 1 K), moister (~ 0.4 g kg-1) and less windy (~ 1 m s-1) biases than the climatological average for both FWD1 and FWD2. These biases are not restricted to the near surface but exist through the entirety of the planetary boundary layer (PBL). Furthermore, post-processing methods are more effective when previous FWDs are incorporated into the statistical training, suggesting that model bias could be related to the synoptic flow pattern. An Ensemble Kalman Filter (EnKF) is used to explore the effectiveness of data assimilation during a period of extensive FWDs in April 2012. Model biases develop rapidly on FWDs, consistent with the FWD1 and FWD2 verification. However, the EnKF is effective at removing most biases for temperature, wind speed and specific humidity. Potential sources of error in the parameterized physics of the PBL are explored by rerunning the EnKF with simultaneous state and parameter estimation (SSPE) for two relevant parameters within the ACM2 PBL scheme. SSPE helps to reduce the cool temperature bias near the surface on FWDs, with the variability in parameter estimates exhibiting some relationship to model bias for temperature. This suggests the potential for structural model error within the ACM2 PBL scheme and could lead toward the future development of improved PBL parameterizations.

A comparison of weather variables linked to infectious disease patterns using laboratory addresses and patient residence addresses.

PubMed

Djennad, Abdelmajid; Lo Iacono, Giovanni; Sarran, Christophe; Fleming, Lora E; Kessel, Anthony; Haines, Andy; Nichols, Gordon L

2018-04-27

To understand the impact of weather on infectious diseases, information on weather parameters at patient locations is needed, but this is not always accessible due to confidentiality or data availability. Weather parameters at nearby locations are often used as a proxy, but the accuracy of this practice is not known. Daily Campylobacter and Cryptosporidium cases across England and Wales were linked to local temperature and rainfall at the residence postcodes of the patients and at the corresponding postcodes of the laboratory where the patient's specimen was tested. The paired values of daily rainfall and temperature for the laboratory versus residence postcodes were interpolated from weather station data, and the results were analysed for agreement using linear regression. We also assessed potential dependency of the findings on the relative geographic distance between the patient's residence and the laboratory. There was significant and strong agreement between the daily values of rainfall and temperature at diagnostic laboratories with the values at the patient residence postcodes for samples containing the pathogens Campylobacter or Cryptosporidium. For rainfall, the R-squared was 0.96 for the former and 0.97 for the latter, and for maximum daily temperature, the R-squared was 0.99 for both. The overall mean distance between the patient residence and the laboratory was 11.9 km; however, the distribution of these distances exhibited a heavy tail, with some rare situations where the distance between the patient residence and the laboratory was larger than 500 km. These large distances impact the distributions of the weather variable discrepancies (i.e. the differences between weather parameters estimated at patient residence postcodes and those at laboratory postcodes), with discrepancies up to ±10 °C for the minimum and maximum temperature and 20 mm for rainfall. Nevertheless, the distributions of discrepancies (estimated separately for minimum and maximum temperature and rainfall), based on the cases where the distance between the patient residence and the laboratory was within 20 km, still exhibited tails somewhat longer than the corresponding exponential fits suggesting modest small scale variations in temperature and rainfall. The findings confirm that, for the purposes of studying the relationships between meteorological variables and infectious diseases using data based on laboratory postcodes, the weather results are sufficiently similar to justify the use of laboratory postcode as a surrogate for domestic postcode. Exclusion of the small percentage of cases where there is a large distance between the residence and the laboratory could increase the precision of estimates, but there are generally strong associations between daily weather parameters at residence and laboratory.

Estimates of atmospheric O2 in the Paleoproterozoic from paleosols

NASA Astrophysics Data System (ADS)

Kanzaki, Yoshiki; Murakami, Takashi

2016-02-01

A weathering model was developed to constrain the partial pressure of atmospheric O2 (PO2) in the Paleoproterozoic from the Fe records in paleosols. The model describes the Fe behavior in a weathering profile by dissolution/precipitation of Fe-bearing minerals, oxidation of dissolved Fe(II) to Fe(III) by oxygen and transport of dissolved Fe by water flow, in steady state. The model calculates the ratio of the precipitated Fe(III)-(oxyhydr)oxides from the dissolved Fe(II) to the dissolved Fe(II) during weathering (ϕ), as a function of PO2 . An advanced kinetic expression for Fe(II) oxidation by O2 was introduced into the model from the literature to calculate accurate ϕ-PO2 relationships. The model's validity is supported by the consistency of the calculated ϕ-PO2 relationships with those in the literature. The model can calculate PO2 for a given paleosol, once a ϕ value and values of the other parameters relevant to weathering, namely, pH of porewater, partial pressure of carbon dioxide (PCO2), water flow, temperature and O2 diffusion into soil, are obtained for the paleosol. The above weathering-relevant parameters were scrutinized for individual Paleoproterozoic paleosols. The values of ϕ, temperature, pH and PCO2 were obtained from the literature on the Paleoproterozoic paleosols. The parameter value of water flow was constrained for each paleosol from the mass balance of Si between water and rock phases and the relationships between water saturation ratio and hydraulic conductivity. The parameter value of O2 diffusion into soil was calculated for each paleosol based on the equation for soil O2 concentration with the O2 transport parameters in the literature. Then, we conducted comprehensive PO2 calculations for individual Paleoproterozoic paleosols which reflect all uncertainties in the weathering-relevant parameters. Consequently, robust estimates of PO2 in the Paleoproterozoic were obtained: 10-7.1-10-5.4 atm at ∼2.46 Ga, 10-5.0-10-2.5 atm at ∼2.15 Ga, 10-5.2-10-1.7 atm at ∼2.08 Ga and more than 10-4.6-10-2.0 atm at ∼1.85 Ga. Comparison of the present PO2 estimates to those in the literature suggests that a drastic rise of oxygen would not have occurred at ∼2.4 Ga, supporting a slightly rapid rise of oxygen at ∼2.4 Ga and a gradual rise of oxygen in the Paleoproterozoic in long term.

Catchment-wide weathering and erosion rates of mafic, ultramafic, and granitic rock from cosmogenic meteoric 10Be/9Be ratios

NASA Astrophysics Data System (ADS)

Dannhaus, N.; Wittmann, H.; Krám, P.; Christl, M.; von Blanckenburg, F.

2018-02-01

Quantifying rates of weathering and erosion of mafic rocks is essential for estimating changes to the oceans alkalinity budget that plays a significant role in regulating atmospheric CO2 levels. In this study, we present catchment-wide rates of weathering, erosion, and denudation measured with cosmogenic nuclides in mafic and ultramafic rock. We use the ratio of the meteoric cosmogenic nuclide 10Be, deposited from the atmosphere onto the weathering zone, to stable 9Be, a trace metal released by silicate weathering. We tested this approach in stream sediment and water from three upland forested catchments in the north-west Czech Republic. The catchments are underlain by felsic (granite), mafic (amphibolite) and ultramafic (serpentinite) lithologies. Due to acid rain deposition in the 20th century, the waters in the granite catchment exhibit acidic pH, whereas waters in the mafic catchments exhibit neutral to alkaline pH values due to their acid buffering capability. The atmospheric depositional 10Be flux is estimated to be balanced with the streams' dissolved and particulate meteoric 10Be export flux to within a factor of two. We suggest a correlation method to derive bedrock Be concentrations, required as an input parameter, which are highly heterogeneous in these small catchments. Derived Earth surface metrics comprise (1) Denudation rates calculated from the 10Be/9Be ratio of the "reactive" Be (meaning sorbed to mineral surfaces) range between 110 and 185 t km-2 y-1 (40 and 70 mm ky-1). These rates are similar to denudation rates we obtained from in situ-cosmogenic 10Be in quartz minerals present in the bedrock or in quartz veins in the felsic and the mafic catchment. (2) The degree of weathering, calculated from the fraction of 9Be released from primary minerals as a new proxy, is about 40-50% in the mafic catchments, and 10% in the granitic catchment. Lastly, (3) erosion rates were calculated from 10Be concentrations in river sediment and corrected for sorting and dissolved loss. These amount to 50% of denudation rates from 10Be/9Be in the mafic and ultramafic catchments, the remainder being mass loss in the dissolved form by weathering. In contrast, erosion comprises most of the mass loss in the granitic catchment. These first results are encouraging, given that we find overall good agreement between in situ and meteoric cosmogenic methods, that our denudation rates are in the range of those published for middle European river catchments, and that degrees of weathering are as expected for these diverse lithologies. This method allows quantifying rates of erosion and weathering in mafic rock over the time scale of weathering that are, unlike in situ cosmogenic 10Be, independent from the presence of quartz. 10Be/9Be therefore offers to quantify Earth surface processes in a wide range of landscapes underlain by mafic rock - rates that are of high importance for exploring climate-weathering feedbacks but that have been inaccessible to date.

Assessment of Areal Recharge to the Spokane Valley-Rathdrum Prairie Aquifer, Spokane County, Washington, and Bonner and Kootenai Counties, Idaho

USGS Publications Warehouse

Bartolino, James R.

2007-01-01

A numerical flow model of the Spokane Valley-Rathdrum Prairie aquifer currently (2007) being developed requires the input of values for areally-distributed recharge, a parameter that is often the most uncertain component of water budgets and ground-water flow models because it is virtually impossible to measure over large areas. Data from six active weather stations in and near the study area were used in four recharge-calculation techniques or approaches; the Langbein method, in which recharge is estimated on the basis of empirical data from other basins; a method developed by the U.S. Department of Agriculture (USDA), in which crop consumptive use and effective precipitation are first calculated and then subtracted from actual precipitation to yield an estimate of recharge; an approach developed as part of the Eastern Snake Plain Aquifer Model (ESPAM) Enhancement Project in which recharge is calculated on the basis of precipitation-recharge relations from other basins; and an approach in which reference evapotranspiration is calculated by the Food and Agriculture Organization (FAO) Penman-Monteith equation, crop consumptive use is determined (using a single or dual coefficient approach), and recharge is calculated. Annual recharge calculated by the Langbein method for the six weather stations was 4 percent of annual mean precipitation, yielding the lowest values of the methods discussed in this report, however, the Langbein method can be only applied to annual time periods. Mean monthly recharge calculated by the USDA method ranged from 53 to 73 percent of mean monthly precipitation. Mean annual recharge ranged from 64 to 69 percent of mean annual precipitation. Separate mean monthly recharge calculations were made with the ESPAM method using initial input parameters to represent thin-soil, thick-soil, and lava-rock conditions. The lava-rock parameters yielded the highest recharge values and the thick-soil parameters the lowest. For thin-soil parameters, calculated monthly recharge ranged from 10 to 29 percent of mean monthly precipitation and annual recharge ranged from 16 to 23 percent of mean annual precipitation. For thick-soil parameters, calculated monthly recharge ranged from 1 to 5 percent of mean monthly precipitation and mean annual recharge ranged from 2 to 4 percent of mean annual precipitation. For lava-rock parameters, calculated mean monthly recharge ranged from 37 to 57 percent of mean monthly precipitation and mean annual recharge ranged from 45 to 52 percent of mean annual precipitation. Single-coefficient (crop coefficient) FAO Penman-Monteith mean monthly recharge values were calculated for Spokane Weather Service Office (WSO) Airport, the only station for which the necessary meteorological data were available. Grass-referenced values of mean monthly recharge ranged from 0 to 81 percent of mean monthly precipitation and mean annual recharge was 21 percent of mean annual precipitation; alfalfa-referenced values of mean monthly recharge ranged from 0 to 85 percent of mean monthly precipitation and mean annual recharge was 24 percent of mean annual precipitation. Single-coefficient FAO Penman-Monteith calculations yielded a mean monthly recharge of zero during the eight warmest and driest months of the year (March-October). In order to refine the mean monthly recharge estimates, dual-coefficient (basal crop and soil evaporation coefficients) FAO Penman-Monteith dual-crop evapotranspiration and deep-percolation calculations were applied to daily values from the Spokane WSO Airport for January 1990 through December 2005. The resultant monthly totals display a temporal variability that is absent from the mean monthly values and demonstrate that the daily amount and timing of precipitation dramatically affect calculated recharge. The dual-coefficient FAO Penman-Monteith calculations were made for the remaining five stations using wind-speed values for Spokane WSO Airport and other assumptions regarding

Downscaling NASA Climatological Data to Produce Detailed Climate Zone Maps

NASA Technical Reports Server (NTRS)

Chandler, William S.; Hoell, James M.; Westberg, David J.; Whitlock, Charles H.; Zhang, Taiping; Stackhouse, P. W.

2011-01-01

The design of energy efficient sustainable buildings is heavily dependent on accurate long-term and near real-time local weather data. To varying degrees the current meteorological networks over the globe have been used to provide these data albeit often from sites far removed from the desired location. The national need is for access to weather and solar resource data accurate enough to use to develop preliminary building designs within a short proposal time limit, usually within 60 days. The NASA Prediction Of Worldwide Energy Resource (POWER) project was established by NASA to provide industry friendly access to globally distributed solar and meteorological data. As a result, the POWER web site (power.larc.nasa.gov) now provides global information on many renewable energy parameters and several buildings-related items but at a relatively coarse resolution. This paper describes a method of downscaling NASA atmospheric assimilation model results to higher resolution and maps those parameters to produce building climate zone maps using estimates of temperature and precipitation. The distribution of climate zones for North America with an emphasis on the Pacific Northwest for just one year shows very good correspondence to the currently defined distribution. The method has the potential to provide a consistent procedure for deriving climate zone information on a global basis that can be assessed for variability and updated more regularly.

Aircraft measurements of electrified clouds at Kennedy Space Center

NASA Technical Reports Server (NTRS)

Jones, J. J.; Winn, W. P.; Hunyady, S. J.; Moore, C. B.; Bullock, J. W.

1990-01-01

The space-vehicle launch commit criteria for weather and atmospheric electrical conditions in us at Cape Canaveral Air Force Station and Kennedy Space Center (KSC) have been made restrictive because of the past difficulties that have arisen when space vehicles have triggered lightning discharge after their launch during cloudy weather. With the present ground-base instrumentation and our limited knowledge of cloud electrification process over this region of Florida, it has not been possible to provide a quantitative index of safe launching conditions. During the fall of 1988, a Schweizer 845 airplane equipped to measure electric field and other meteorological parameters flew over KSC in a program to study clouds defined in the existing launch restriction criteria. All aspects of this program are addressed including planning, method, and results. A case study on the November 4, 1988 flight is also presented.

Weather and Atmospheric Effects on the Measurement and Use of Electro-Optical Signature Data

DTIC Science & Technology

2017-02-01

and the problem of correcting and applying measured data. It provides glossaries of electro-optical and weather terms related to EO/ IR test... IR infrared LWIR long-wave infrared MG Meteorology Group mm millimeter MWIR mid-wave infrared NIR near infrared nm nanometer O2 oxygen O3...applying measured data. It provides glossaries of EO and weather terms related to EO/infrared ( IR ) test environments (parameters, quantity names, symbols

Simulating large-scale crop yield by using perturbed-parameter ensemble method

NASA Astrophysics Data System (ADS)

Iizumi, T.; Yokozawa, M.; Sakurai, G.; Nishimori, M.

2010-12-01

Toshichika Iizumi, Masayuki Yokozawa, Gen Sakurai, Motoki Nishimori Agro-Meteorology Division, National Institute for Agro-Environmental Sciences, Japan Abstract One of concerning issues of food security under changing climate is to predict the inter-annual variation of crop production induced by climate extremes and modulated climate. To secure food supply for growing world population, methodology that can accurately predict crop yield on a large scale is needed. However, for developing a process-based large-scale crop model with a scale of general circulation models (GCMs), 100 km in latitude and longitude, researchers encounter the difficulties in spatial heterogeneity of available information on crop production such as cultivated cultivars and management. This study proposed an ensemble-based simulation method that uses a process-based crop model and systematic parameter perturbation procedure, taking maize in U.S., China, and Brazil as examples. The crop model was developed modifying the fundamental structure of the Soil and Water Assessment Tool (SWAT) to incorporate the effect of heat stress on yield. We called the new model PRYSBI: the Process-based Regional-scale Yield Simulator with Bayesian Inference. The posterior probability density function (PDF) of 17 parameters, which represents the crop- and grid-specific features of the crop and its uncertainty under given data, was estimated by the Bayesian inversion analysis. We then take 1500 ensemble members of simulated yield values based on the parameter sets sampled from the posterior PDF to describe yearly changes of the yield, i.e. perturbed-parameter ensemble method. The ensemble median for 27 years (1980-2006) was compared with the data aggregated from the county yield. On a country scale, the ensemble median of the simulated yield showed a good correspondence with the reported yield: the Pearson’s correlation coefficient is over 0.6 for all countries. In contrast, on a grid scale, the correspondence is still high in most grids regardless of the countries. However, the model showed comparatively low reproducibility in the slope areas, such as around the Rocky Mountains in South Dakota, around the Great Xing'anling Mountains in Heilongjiang, and around the Brazilian Plateau. As there is a wide-ranging local climate conditions in the complex terrain, such as the slope of mountain, the GCM grid-scale weather inputs is likely one of major sources of error. The results of this study highlight the benefits of the perturbed-parameter ensemble method in simulating crop yield on a GCM grid scale: (1) the posterior PDF of parameter could quantify the uncertainty of parameter value of the crop model associated with the local crop production aspects; (2) the method can explicitly account for the uncertainty of parameter value in the crop model simulations; (3) the method achieve a Monte Carlo approximation of probability of sub-grid scale yield, accounting for the nonlinear response of crop yield to weather and management; (4) the method is therefore appropriate to aggregate the simulated sub-grid scale yields to a grid-scale yield and it may be a reason for high performance of the model in capturing inter-annual variation of yield.

A Coupled Surface Nudging Scheme for use in Retrospective Weather and Climate Simulations for Environmental Applications

EPA Science Inventory

A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem mo...

The potential benefits of location-specific biometeorological indexes

NASA Astrophysics Data System (ADS)

Wong, Ho Ting; Wang, Jinfeng; Yin, Qian; Chen, Si; Lai, Poh Chin

2017-09-01

It is becoming popular to use biometeorological indexes to study the effects of weather on human health. Most of the biometeorological indexes were developed decades ago and only applicable to certain locations because of different climate types. Merely using standard biometeorological indexes to replace typical weather factors in biometeorological studies of different locations may not be an ideal research direction. This research is aimed at assessing the difference of statistical power between using standard biometeorological indexes and typical weather factors on describing the effects of extreme weather conditions on daily ambulance demands in Hong Kong. Results showed that net effective temperature and apparent temperature did not perform better than typical weather factors in describing daily ambulance demands in this study. The maximum adj- R 2 improvement was only 0.08, whereas the maximum adj- R 2 deterioration was 0.07. In this study, biometeorological indexes did not perform better than typical weather factors, possibly due to the differences of built environments and lifestyles in different locations and eras. Regarding built environments, the original parameters for calculating the index values may not be applicable to Hong Kong as buildings in Hong Kong are extremely dense and most are equipped with air conditioners. Regarding lifestyles, the parameters, which were set decades ago, may be outdated and not suitable to modern lifestyles as using hand-held electrical fans on the street to help reduce heat stress are popular. Hence, it is ideal to have tailor-made updated location-specific biometeorological indexes to study the effects of weather on human health.

Space Environment Modelling with the Use of Artificial Intelligence Methods

NASA Astrophysics Data System (ADS)

Lundstedt, H.; Wintoft, P.; Wu, J.-G.; Gleisner, H.; Dovheden, V.

1996-12-01

Space based technological systems are affected by the space weather in many ways. Several severe failures of satellites have been reported at times of space storms. Our society also increasingly depends on satellites for communication, navigation, exploration, and research. Predictions of the conditions in the satellite environment have therefore become very important. We will here present predictions made with the use of artificial intelligence (AI) techniques, such as artificial neural networks (ANN) and hybrids of AT methods. We are developing a space weather model based on intelligence hybrid systems (IHS). The model consists of different forecast modules, each module predicts the space weather on a specific time-scale. The time-scales range from minutes to months with the fundamental time-scale of 1-5 minutes, 1-3 hours, 1-3 days, and 27 days. Solar and solar wind data are used as input data. From solar magnetic field measurements, either made on the ground at Wilcox Solar Observatory (WSO) at Stanford, or made from space by the satellite SOHO, solar wind parameters can be predicted and modelled with ANN and MHD models. Magnetograms from WSO are available on a daily basis. However, from SOHO magnetograms will be available every 90 minutes. SOHO magnetograms as input to ANNs will therefore make it possible to even predict solar transient events. Geomagnetic storm activity can today be predicted with very high accuracy by means of ANN methods using solar wind input data. However, at present real-time solar wind data are only available during part of the day from the satellite WIND. With the launch of ACE in 1997, solar wind data will on the other hand be available during 24 hours per day. The conditions of the satellite environment are not only disturbed at times of geomagnetic storms but also at times of intense solar radiation and highly energetic particles. These events are associated with increased solar activity. Predictions of these events are therefore also handled with the modules in the Lund Space Weather Model. Interesting Links: Lund Space Weather and AI Center

Mining key elements for severe convection prediction based on CNN

NASA Astrophysics Data System (ADS)

Liu, Ming; Pan, Ning; Zhang, Changan; Sha, Hongzhou; Zhang, Bolei; Liu, Liang; Zhang, Meng

2017-04-01

Severe convective weather is a kind of weather disasters accompanied by heavy rainfall, gust wind, hail, etc. Along with recent developments on remote sensing and numerical modeling, there are high-volume and long-term observational and modeling data accumulated to capture massive severe convective events over particular areas and time periods. With those high-volume and high-variety weather data, most of the existing studies and methods carry out the dynamical laws, cause analysis, potential rule study, and prediction enhancement by utilizing the governing equations from fluid dynamics and thermodynamics. In this study, a key-element mining method is proposed for severe convection prediction based on convolution neural network (CNN). It aims to identify the key areas and key elements from huge amounts of historical weather data including conventional measurements, weather radar, satellite, so as numerical modeling and/or reanalysis data. Under this manner, the machine-learning based method could help the human forecasters on their decision-making on operational weather forecasts on severe convective weathers by extracting key information from the real-time and historical weather big data. In this paper, it first utilizes computer vision technology to complete the data preprocessing work of the meteorological variables. Then, it utilizes the information such as radar map and expert knowledge to annotate all images automatically. And finally, by using CNN model, it cloud analyze and evaluate each weather elements (e.g., particular variables, patterns, features, etc.), and identify key areas of those critical weather elements, then help forecasters quickly screen out the key elements from huge amounts of observation data by current weather conditions. Based on the rich weather measurement and model data (up to 10 years) over Fujian province in China, where the severe convective weathers are very active during the summer months, experimental tests are conducted with the new machine-learning method via CNN models. Based on the analysis of those experimental results and case studies, the proposed new method have below benefits for the severe convection prediction: (1) helping forecasters to narrow down the scope of analysis and saves lead-time for those high-impact severe convection; (2) performing huge amount of weather big data by machine learning methods rather relying on traditional theory and knowledge, which provide new method to explore and quantify the severe convective weathers; (3) providing machine learning based end-to-end analysis and processing ability with considerable scalability on data volumes, and accomplishing the analysis work without human intervention.

Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial prediction of these attributes also showed a high performance (validations with R2> 0.78). These models allowed to increase spatial resolution of soil weathering information. On the other hand, the comparison between the analog and digital soil maps showed a global accuracy of 69% for the ASC-N map and 62% in the ASC-H map, with kappa indices of 0.52 and 0.45 respectively.

Advancing the climate data driven crop-modeling studies in the dry areas of Northern Syria and Lebanon: an important first step for assessing impact of future climate.

PubMed

Dixit, Prakash N; Telleria, Roberto

2015-04-01

Inter-annual and seasonal variability in climatic parameters, most importantly rainfall, have potential to cause climate-induced risk in long-term crop production. Short-term field studies do not capture the full nature of such risk and the extent to which modifications to crop, soil and water management recommendations may be made to mitigate the extent of such risk. Crop modeling studies driven by long-term daily weather data can predict the impact of climate-induced risk on crop growth and yield however, the availability of long-term daily weather data can present serious constraints to the use of crop models. To tackle this constraint, two weather generators namely, LARS-WG and MarkSim, were evaluated in order to assess their capabilities of reproducing frequency distributions, means, variances, dry spell and wet chains of observed daily precipitation, maximum and minimum temperature, and solar radiation for the eight locations across cropping areas of Northern Syria and Lebanon. Further, the application of generated long-term daily weather data, with both weather generators, in simulating barley growth and yield was also evaluated. We found that overall LARS-WG performed better than MarkSim in generating daily weather parameters and in 50 years continuous simulation of barley growth and yield. Our findings suggest that LARS-WG does not necessarily require long-term e.g., >30 years observed weather data for calibration as generated results proved to be satisfactory with >10 years of observed data except in area with higher altitude. Evaluating these weather generators and the ability of generated weather data to perform long-term simulation of crop growth and yield is an important first step to assess the impact of future climate on yields, and to identify promising technologies to make agricultural systems more resilient in the given region. Copyright © 2015 Elsevier B.V. All rights reserved.

Accelerated weathering of fire-retardant-treated wood for fire testing

Treesearch

Robert H. White

2009-01-01

Fire-retardant-treated products for exterior applications must be subjected to actual or accelerated weathering prior to fire testing. For fire-retardant-treated wood, the two accelerated weathering methods have been Method A and B of ASTM D 2898. The rain test is Method A of ASTM D 2898. Method B includes exposures to ultraviolet (UV) sunlamps in addition to water...

RZWQM predicted effects of soil N testing with incorporated automatic parameter optimization software (PEST) and weather input quality control

USDA-ARS?s Scientific Manuscript database

Among the most promising tools available for determining precise N requirements are soil mineral N tests. Field tests that evaluated this practice, however, have been conducted under only limited weather and soil conditions. Previous research has shown that using agricultural systems models such as ...

A high-fidelity weather time series generator using the Markov Chain process on a piecewise level

NASA Astrophysics Data System (ADS)

Hersvik, K.; Endrerud, O.-E. V.

2017-12-01

A method is developed for generating a set of unique weather time-series based on an existing weather series. The method allows statistically valid weather variations to take place within repeated simulations of offshore operations. The numerous generated time series need to share the same statistical qualities as the original time series. Statistical qualities here refer mainly to the distribution of weather windows available for work, including durations and frequencies of such weather windows, and seasonal characteristics. The method is based on the Markov chain process. The core new development lies in how the Markov Process is used, specifically by joining small pieces of random length time series together rather than joining individual weather states, each from a single time step, which is a common solution found in the literature. This new Markov model shows favorable characteristics with respect to the requirements set forth and all aspects of the validation performed.

A review of the effect of traffic and weather characteristics on road safety.

PubMed

Theofilatos, Athanasios; Yannis, George

2014-11-01

Taking into consideration the increasing availability of real-time traffic data and stimulated by the importance of proactive safety management, this paper attempts to provide a review of the effect of traffic and weather characteristics on road safety, identify the gaps and discuss the needs for further research. Despite the existence of generally mixed evidence on the effect of traffic parameters, a few patterns can be observed. For instance, traffic flow seems to have a non-linear relationship with accident rates, even though some studies suggest linear relationship with accidents. On the other hand, increased speed limits have found to have a straightforward positive relationship with accident occurrence. Regarding weather effects, the effect of precipitation is quite consistent and leads generally to increased accident frequency but does not seem to have a consistent effect on severity. The impact of other weather parameters on safety, such as visibility, wind speed and temperature is not found straightforward so far. The increasing use of real-time data not only makes easier to identify the safety impact of traffic and weather characteristics, but most importantly makes possible the identification of their combined effect. The more systematic use of these real-time data may address several of the research gaps identified in this research. Copyright © 2014 Elsevier Ltd. All rights reserved.

A dental myth bites the dust--no observable relation between the incidence of dental abscess and the weather and lunar phase: an ecological study.

PubMed

Ristow, Oliver; Koerdt, Steffen; Stelzner, Ruben; Stelzner, Matthias; Johannes, Christoph; Ristow, Melanie; Hohlweg-Majert, Bettina; Pautke, Christoph

2015-02-11

Anecdotal reports assert a relationship between weather and lunar activity and the odontogenic abscess (OA) incidence, but this relationship has not been validated. Therefore, the present study investigated the relationship between oral pain caused by OA and a variety of meteorological parameters and cyclic lunar activity. The records of all dental emergency patients treated at the AllDent Zahnzentrum Emergency Unit in Munich, Germany during 2012 were retrospectively reviewed. Patients with oral pain who were diagnosed with OA and treated surgically (n = 1211) were included in the analysis. The OA incidence was correlated to daily meteorological data, biosynoptic weather analysis, and cyclic lunar activity. There was no seasonal variation in the OA incidence. None of the meteorological parameters, lunar phase, or biosynoptic weather class were significantly correlated with the OA incidence, except the mean barometric pressure, which was weakly correlated (rho = -0.204). The OA incidence showed a decreasing trend as barometric pressure increased (p < 0.001). On multiple linear regression, the barometric pressure accounted for approximately 4% of the OA incidence. There is no evidence supporting a correlation between the incidence of odontogenic abscess and the weather and lunar activities.

Estimation and correction of different flavors of surface observation biases in ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Lorente-Plazas, Raquel; Hacker, Josua P.; Collins, Nancy; Lee, Jared A.

2017-04-01

The impact of assimilating surface observations has been shown in several publications, for improving weather prediction inside of the boundary layer as well as the flow aloft. However, the assimilation of surface observations is often far from optimal due to the presence of both model and observation biases. The sources of these biases can be diverse: an instrumental offset, errors associated to the comparison of point-based observations and grid-cell average, etc. To overcome this challenge, a method was developed using the ensemble Kalman filter. The approach consists on representing each observation bias as a parameter. These bias parameters are added to the forward operator and they extend the state vector. As opposed to the observation bias estimation approaches most common in operational systems (e.g. for satellite radiances), the state vector and parameters are simultaneously updated by applying the Kalman filter equations to the augmented state. The method to estimate and correct the observation bias is evaluated using observing system simulation experiments (OSSEs) with the Weather Research and Forecasting (WRF) model. OSSEs are constructed for the conventional observation network including radiosondes, aircraft observations, atmospheric motion vectors, and surface observations. Three different kinds of biases are added to 2-meter temperature for synthetic METARs. From the simplest to more sophisticated, imposed biases are: (1) a spatially invariant bias, (2) a spatially varying bias proportional to topographic height differences between the model and the observations, and (3) bias that is proportional to the temperature. The target region characterized by complex terrain is the western U.S. on a domain with 30-km grid spacing. Observations are assimilated every 3 hours using an 80-member ensemble during September 2012. Results demonstrate that the approach is able to estimate and correct the bias when it is spatially invariant (experiment 1). More complex bias structure in experiments (2) and (3) are more difficult to estimate, but still possible. Estimated the parameter in experiments with unbiased observations results in spatial and temporal parameter variability about zero, and establishes a threshold on the accuracy of the parameter in further experiments. When the observations are biased, the mean parameter value is close to the true bias, but temporal and spatial variability in the parameter estimates is similar to the parameters used when estimating a zero bias in the observations. The distributions are related to other errors in the forecasts, indicating that the parameters are absorbing some of the forecast error from other sources. In this presentation we elucidate the reasons for the resulting parameter estimates, and their variability.

Chemical weathering of a marine terrace chronosequence, Santa Cruz, California I: Interpreting rates and controls based on soil concentration-depth profiles

USGS Publications Warehouse

White, A.F.; Schulz, M.S.; Vivit, D.V.; Blum, A.E.; Stonestrom, David A.; Anderson, S.P.

2008-01-01

The spatial and temporal changes in element and mineral concentrations in regolith profiles in a chronosequence developed on marine terraces along coastal California are interpreted in terms of chemical weathering rates and processes. In regoliths up to 15 m deep and 226 kyrs old, quartz-normalized mass transfer coefficients indicate non-stoichiometric preferential release of Sr > Ca > Na from plagioclase along with lesser amounts of K, Rb and Ba derived from K-feldspar. Smectite weathering results in the loss of Mg and concurrent incorporation of Al and Fe into secondary kaolinite and Fe-oxides in shallow argillic horizons. Elemental losses from weathering of the Santa Cruz terraces fall within the range of those for other marine terraces along the Pacific Coast of North America. Residual amounts of plagioclase and K-feldspar decrease with terrace depth and increasing age. The gradient of the weathering profile bs is defined by the ratio of the weathering rate, R to the velocity at which the profile penetrates into the protolith. A spreadsheet calculator further refines profile geometries, demonstrating that the non-linear regions at low residual feldspar concentrations at shallow depth are dominated by exponential changes in mineral surface-to-volume ratios and at high residual feldspar concentrations, at greater depth, by the approach to thermodynamic saturation. These parameters are of secondary importance to the fluid flux qh, which in thermodynamically saturated pore water, controls the weathering velocity and mineral losses from the profiles. Long-term fluid fluxes required to reproduce the feldspar weathering profiles are in agreement with contemporary values based on solute Cl balances (qh = 0.025-0.17 m yr-1). During saturation-controlled and solute-limited weathering, the greater loss of plagioclase relative to K-feldspar is dependent on the large difference in their respective solubilities instead of the small difference between their respective reaction kinetics. The steady-state weathering rate under such conditions is defined asR = fenced(qh ?? frac(msol, Mtotal)) ?? fenced(frac(1, Sv ?? bs)) ??. The product of qh and the ratio of solubilized to solid state feldspar (msat/Mtotal) define the weathering velocity. The weathering gradient bs reflects the kinetic rate of reaction where Sv is the volumetric surface area of the residual feldspar. Both this rate expression and the spreadsheet calculations produce similar plagioclase weathering rates (R = 5-14 ?? 10-16 mol m-2 s-1) which agree with those reported for other environments of comparable climate and age. Weathering-dependent concentration profiles are commonly described in literature. The present paper provides methods by which these data can yield a more fundamental understanding of the weathering processes involved.

Upgrade Summer Severe Weather Tool

NASA Technical Reports Server (NTRS)

Watson, Leela

2011-01-01

The goal of this task was to upgrade to the existing severe weather database by adding observations from the 2010 warm season, update the verification dataset with results from the 2010 warm season, use statistical logistic regression analysis on the database and develop a new forecast tool. The AMU analyzed 7 stability parameters that showed the possibility of providing guidance in forecasting severe weather, calculated verification statistics for the Total Threat Score (TTS), and calculated warm season verification statistics for the 2010 season. The AMU also performed statistical logistic regression analysis on the 22-year severe weather database. The results indicated that the logistic regression equation did not show an increase in skill over the previously developed TTS. The equation showed less accuracy than TTS at predicting severe weather, little ability to distinguish between severe and non-severe weather days, and worse standard categorical accuracy measures and skill scores over TTS.

Total probabilities of ensemble runoff forecasts

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2016-04-01

Ensemble forecasting has for a long time been used as a method in meteorological modelling to indicate the uncertainty of the forecasts. However, as the ensembles often exhibit both bias and dispersion errors, it is necessary to calibrate and post-process them. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters which are different in space and time, but still can give a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, and cannot directly be regionalized in the way we would like, so we suggest a different path below. The target of our work is to create a mean forecast with uncertainty bounds for a large number of locations in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu) We are therefore more interested in improving the forecast skill for high-flows rather than the forecast skill of lower runoff levels. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to find a total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but assuring that they have some spatial correlation, by adding a spatial penalty in the calibration process. This can in some cases have a slight negative impact on the calibration error, but makes it easier to interpolate the post-processing parameters to uncalibrated locations. We also look into different methods for handling the non-normal distributions of runoff data and the effect of different data transformations on forecasts skills in general and for floods in particular. Berrocal, V. J., Raftery, A. E. and Gneiting, T.: Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts, Mon. Weather Rev., 135(4), 1386-1402, doi:10.1175/MWR3341.1, 2007. Engeland, K. and Steinsland, I.: Probabilistic postprocessing models for flow forecasts for a system of catchments and several lead times, Water Resour. Res., 50(1), 182-197, doi:10.1002/2012WR012757, 2014. Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T.: Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation, Mon. Weather Rev., 133(5), 1098-1118, doi:10.1175/MWR2904.1, 2005. Hemri, S., Fundel, F. and Zappa, M.: Simultaneous calibration of ensemble river flow predictions over an entire range of lead times, Water Resour. Res., 49(10), 6744-6755, doi:10.1002/wrcr.20542, 2013. Raftery, A. E., Gneiting, T., Balabdaoui, F. and Polakowski, M.: Using Bayesian Model Averaging to Calibrate Forecast Ensembles, Mon. Weather Rev., 133(5), 1155-1174, doi:10.1175/MWR2906.1, 2005.

Weather data for simplified energy calculation methods. Volume IV. United States: WYEC data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olsen, A.R.; Moreno, S.; Deringer, J.

The objective of this report is to provide a source of weather data for direct use with a number of simplified energy calculation methods available today. Complete weather data for a number of cities in the United States are provided for use in the following methods: degree hour, modified degree hour, bin, modified bin, and variable degree day. This report contains sets of weather data for 23 cities using Weather Year for Energy Calculations (WYEC) source weather data. Considerable overlap is present in cities (21) covered by both the TRY and WYEC data. The weather data at each city hasmore » been summarized in a number of ways to provide differing levels of detail necessary for alternative simplified energy calculation methods. Weather variables summarized include dry bulb and wet bulb temperature, percent relative humidity, humidity ratio, wind speed, percent possible sunshine, percent diffuse solar radiation, total solar radiation on horizontal and vertical surfaces, and solar heat gain through standard DSA glass. Monthly and annual summaries, in some cases by time of day, are available. These summaries are produced in a series of nine computer generated tables.« less

Evaluation of weather-based rice yield models in India.

PubMed

Sudharsan, D; Adinarayana, J; Reddy, D Raji; Sreenivas, G; Ninomiya, S; Hirafuji, M; Kiura, T; Tanaka, K; Desai, U B; Merchant, S N

2013-01-01

The objective of this study was to compare two different rice simulation models--standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])--with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India. Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models. Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India. Initially, the results were obtained using 4 years (1994-1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values. Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield. Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values. Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system. These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis. These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner. However, SIMRIW requires fine tuning for better results/decision making.

Continuous monitoring of high-rise buildings using seismic interferometry

NASA Astrophysics Data System (ADS)

Mordret, A.; Sun, H.; Prieto, G. A.; Toksoz, M. N.; Buyukozturk, O.

2016-12-01

The linear seismic response of a building is commonly extracted from ambient vibration measurements. Seismic deconvolution interferometry performed on ambient vibration measurements can also be used to estimate the dynamic characteristics of a building, such as the velocity of shear-waves travelling inside the building as well as a damping parameter depending on the intrinsic attenuation of the building and the soil-structure coupling. The continuous nature of the ambient vibrations allows us to measure these parameters repeatedly and to observe their temporal variations. We used 2 weeks of ambient vibration recorded by 36 accelerometers installed in the Green Building on the Massachusetts Institute of Technology campus (Cambridge, MA) to continuously monitor the shear-wave speed and the attenuation factor of the building. Due to the low strain of the ambient vibrations, the observed changes are totally reversible. The relative velocity changes between a reference deconvolution function and the current deconvolution functions are measured with two different methods: 1) the Moving Window Cross-Spectral technique and 2) the stretching technique. Both methods show similar results. We show that measuring the stretching coefficient for the deconvolution functions filtered around the fundamental mode frequency is equivalent to measuring the wandering of the fundamental frequency in the raw ambient vibration data. By comparing these results with local weather parameters, we show that the relative air humidity is the factor dominating the relative seismic velocity variations in the Green Building, as well as the wandering of the fundamental mode. The one-day periodic variations are affected by both the temperature and the humidity. The attenuation factor, measured as the exponential decay of the fundamental mode waveforms, shows a more complex behaviour with respect to the weather measurements.

Psychological mechanisms in outdoor place and weather assessment: towards a conceptual model

NASA Astrophysics Data System (ADS)

Knez, Igor; Thorsson, Sofia; Eliasson, Ingegärd; Lindberg, Fredrik

2009-01-01

The general aim has been to illuminate the psychological mechanisms involved in outdoor place and weather assessment. This reasoning was conceptualized in a model, tentatively proposing direct and indirect links of influence in an outdoor place-human relationship. The model was subsequently tested by an empirical study, performed in a Nordic city, on the impact of weather and personal factors on participants’ perceptual and emotional estimations of outdoor urban places. In line with our predictions, we report significant influences of weather parameters (air temperature, wind, and cloudlessness) and personal factors (environmental attitude and age) on participants’ perceptual and emotional estimations of outdoor urban places. All this is a modest, yet significant, step towards an understanding of the psychology of outdoor place and weather assessment.

A Comparison of Atmospheric Quantities Determined from Advanced WVR and Weather Analysis Data

NASA Astrophysics Data System (ADS)

Morabito, D.; Wu, L.; Slobin, S.

2017-05-01

Lower frequency bands used for deep space communications (e.g., 2.3 GHz and 8.4 GHz) are oversubscribed. Thus, NASA has become interested in using higher frequency bands (e.g., 26 GHz and 32 GHz) for telemetry, making use of the available wider bandwidth. However, these bands are more susceptible to atmospheric degradation. Currently, flight projects tend to be conservative in preparing their communications links by using worst-case or conservative assumptions, which result in nonoptimum data return. We previously explored the use of weather forecasting over different weather condition scenarios to determine more optimal values of atmospheric attenuation and atmospheric noise temperature for use in telecommunications link design. In this article, we present the results of a comparison of meteorological parameters (columnar water vapor and liquid water content) estimated from multifrequency Advanced Water Vapor Radiometer (AWVR) data with those estimated from weather analysis tools (FNL). We find that for the Deep Space Network's Goldstone and Madrid tracking sites, the statistics are in reasonable agreement between the two methods. We can then use the statistics of these quantities based on FNL runs to estimate statistics of atmospheric signal degradation for tracking sites that do not have the benefit of possessing multiyear WVR data sets, such as those of the NASA Near-Earth Network (NEN). The resulting statistics of atmospheric attenuation and atmospheric noise temperature increase can then be used in link budget calculations.

Analysis of biases from parallel observations of co-located manual and automatic weather stations in Indonesia

NASA Astrophysics Data System (ADS)

Sopaheluwakan, Ardhasena; Fajariana, Yuaning; Satyaningsih, Ratna; Aprilina, Kharisma; Astuti Nuraini, Tri; Ummiyatul Badriyah, Imelda; Lukita Sari, Dyah; Haryoko, Urip

2017-04-01

Inhomogeneities are often found in long records of climate data. These can occur because of various reasons, among others such as relocation of observation site, changes in observation method, and the transition to automated instruments. Changes to these automated systems are inevitable, and it is taking place worldwide in many of the National Meteorological Services. However this shift of observational practice must be done cautiously and a sufficient period of parallel observation of co-located manual and automated systems should take place as suggested by the World Meteorological Organization. With a sufficient parallel observation period, biases between the two systems can be analyzed. In this study we analyze the biases of a yearlong parallel observation of manual and automatic weather stations in 30 locations in Indonesia. The location of the sites spans from east to west of approximately 45 longitudinal degrees covering different climate characteristics and geographical settings. We study measurements taken by both sensors for temperature and rainfall parameters. We found that the biases from both systems vary from place to place and are more dependent to the setting of the instrument rather than to the climatic and geographical factors. For instance, daytime observations of the automatic weather stations are found to be consistently higher than the manual observation, and vice versa night time observations of the automatic weather stations are lower than the manual observation.

On the Nature of People's Reaction to Space Weather and Meteorological Weather Changes

NASA Astrophysics Data System (ADS)

Khabarova, O. V.; Dimitrova, S.

2009-12-01

Our environment includes many natural and artificial agents affecting any person on the Earth in one way or other. This work is focused on two of them - weather and space weather, which are permanently effective. Their cumulative effect is proved by means of the modeling. It is shown that combination of geomagnetic and solar indices and weather strength parameter (which includes six main meteorological parameters) correlates with health state significantly better (up to R=0.7), than separate environmental parameters do. The typical shape of any health characteristics' time-series during human body reaction to any negative impact represents a curve, well-known in medicine as a General Adaptation Syndrome curve by Hans Selye. We demonstrate this on the base of blood pressure time-series and acupunctural experiment data, averaged by group. The first stage of adaptive stress-reaction (resistance to stress) is sometimes observed 1-2 days before geomagnetic storm onset. The effect of "outstripping reaction to magnetic storm", named Tchizhevsky- Velkhover effect, had been known for many years, but its explanation was obtained recently due to the consideration of the near-Earth space plasma processes. It was shown that lowfrequency variations of the solar wind density on a background of the density growth can stimulate the development of the geomagnetic filed (GMF) variations of the wide frequency range. These variations seem to have "bioeffective frequencies", resonant with own frequencies of body organs and systems. The mechanism of human body reaction is supposed to be a parametrical resonance in low-frequency range (which is determined by the resonance in large-scale organs and systems) and a simple forced resonance in GHz-range of variations (the resonance of micro-objects in the organism such as DNA, cell membranes, blood ions etc.) Given examples of mass-reaction of the objects to ULF-range GMF variations during quiet space weather time prove this hypothesis.

Systems and methods for supplemental weather information presentation on a display

NASA Technical Reports Server (NTRS)

Bunch, Brian (Inventor)

2010-01-01

An embodiment of the supplemental weather display system presents supplemental weather information on a display in a craft. An exemplary embodiment receives the supplemental weather information from a remote source, determines a location of the supplemental weather information relative to the craft, receives weather information from an on-board radar system, and integrates the supplemental weather information with the weather information received from the on-board radar system.

Critical Zone structure inferred from multiscale near surface geophysical and hydrological data across hillslopes at the Eel River CZO

NASA Astrophysics Data System (ADS)

Lee, S. S.; Rempe, D. M.; Holbrook, W. S.; Schmidt, L.; Hahm, W. J.; Dietrich, W. E.

2017-12-01

Except for boreholes and road cut, landslide, and quarry exposures, the subsurface structure of the critical zone (CZ) of weathered bedrock is relatively invisible and unmapped, yet this structure controls the short and long term fluxes of water and solutes. Non-invasive geophysical methods such as seismic refraction are widely applied to image the structure of the CZ at the hillslope scale. However, interpretations of such data are often limited due to heterogeneity and anisotropy contributed from fracturing, moisture content, and mineralogy on the seismic signal. We develop a quantitative framework for using seismic refraction tomography from intersecting geophysical surveys and hydrologic data obtained at the Eel River Critical Zone Observatory (ERCZO) in Northern California to help quantify the nature of subsurface structure across multiple hillslopes of varying topography in the area. To enhance our understanding of modeled velocity gradients and boundaries in relation to lithological properties, we compare refraction tomography results with borehole logs of nuclear magnetic resonance (NMR), gamma and neutron density, standard penetration testing, and observation drilling logs. We also incorporate laboratory scale rock characterization including mineralogical and elemental analyses as well as porosity and density measurements made via pycnometry, helium and mercury porosimetry, and laboratory scale NMR. We evaluate the sensitivity of seismically inferred saprolite-weathered bedrock and weathered-unweathered bedrock boundaries to various velocity and inversion parameters in relation with other macro scale processes such as gravitational and tectonic forces in influencing weathered bedrock velocities. Together, our sensitivity analyses and multi-method data comparison provide insight into the interpretation of seismic refraction tomography for the quantification of CZ structure and hydrologic dynamics.

AEGIS: a wildfire prevention and management information system

NASA Astrophysics Data System (ADS)

Kalabokidis, K.; Ager, A.; Finney, M.; Athanasis, N.; Palaiologou, P.; Vasilakos, C.

2015-10-01

A Web-GIS wildfire prevention and management platform (AEGIS) was developed as an integrated and easy-to-use decision support tool (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing access to information that is essential for wildfire management. Databases were created with spatial and non-spatial data to support key system functionalities. Updated land use/land cover maps were produced by combining field inventory data with high resolution multispectral satellite images (RapidEye) to be used as inputs in fire propagation modeling with the Minimum Travel Time algorithm. End users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations; i.e. single-fire propagations, conditional burn probabilities and at the landscape-level, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANN) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps produced an integrated output map for fire danger prediction. The system also incorporates weather measurements from remote automatic weather stations and weather forecast maps. The structure of the algorithms relies on parallel processing techniques (i.e. High Performance Computing and Cloud Computing) that ensure computational power and speed. All AEGIS functionalities are accessible to authorized end users through a web-based graphical user interface. An innovative mobile application, AEGIS App, acts as a complementary tool to the web-based version of the system.

What is the weather like today

NASA Astrophysics Data System (ADS)

Jovic, Sladjana

2017-04-01

Meteorology is the study of all changes in the atmosphere that surround the Earth. In this project, students will design and build some of the instruments that meteorologists use and make two school Weather Stations and placed them in different school yards so that results of weather parameters date can be follow during three months and be compared. Poster will present a procedure and a preparation how to work with weather stations that contain 1. Barometer (Air pressure) 2. Rain Gauge (Precipitation) 3. Thermometer (Temperature ) 4. Wind Vane (Wind Direction) By collecting their own data, the students found out more about weather through a process similar to the one that professional meteorologists used. Finally students compared differences between two school weather station and used these results to presented how different places had different climate and how climate changed during the months in a year. This was opportunity for cooperation between students from different schools and different grades when older students from secondary school helped younger student to make their weather station and shared knowledge and experience while they followed weather condition during the project .

Weather and emotional state

NASA Astrophysics Data System (ADS)

Spasova, Z.

2010-09-01

Introduction Given the proven effects of weather on the human organism, an attempt to examine its effects on a psychic and emotional level has been made. Emotions affect the bio-tonus, working ability and concentration, hence their significance in various domains of economic life, such as health care, education, transportation, tourism, etc. Data and methods The research has been made in Sofia City within a period of 8 months, using 5 psychological methods (Eysenck Personality Questionnaire (EPQ), State-Trait Anxiety Inventory (STAI), Test for Self-assessment of the emotional state (developed by Wessman and Ricks), Test for evaluation of moods and Test "Self-confidence - Activity - Mood" (developed by the specialists from the Military Academy in Saint Petersburg). The Fiodorov-Chubukov's complex-climatic method was used to characterize meteorological conditions because of the purpose to include in the analysis a maximal number of meteorological elements. 16 weather types are defined in dependence of the meteorological elements values according to this method. Abrupt weather changes from one day to another, defined by the same method, were considered as well. Results and discussions The results obtained by t-test show that the different categories of weather lead to changes in the emotional status, which indicates a character either positive or negative for the organism. The abrupt weather changes, according to expectations, have negative effect on human emotions but only when a transition to the cloudy weather or weather type, classified as "unfavourable" has been realized. The relationship between weather and human emotions is rather complicated since it depends on individual characteristics of people. One of these individual psychological characteristics, marked by the dimension "neuroticism", has a strong effect on emotional reactions in different weather conditions. Emotionally stable individuals are more "protected" to the weather influence on their emotions, while those who are emotionally unstable have a stronger dependence to the impacts of the weather.

The effect of weather and its changes on emotional state - individual characteristics that make us vulnerable

NASA Astrophysics Data System (ADS)

Spasova, Z.

2011-03-01

Given the proven effects of weather on the human organism, an attempt to examine its effects on a psychological and emotional level has been made. Emotions affect the bio tone, working ability, and concentration; hence their significance in various domains of economic life such as health care, education, transportation, and tourism. The present pilot study was conducted in Sofia, Bulgaria over a period of eight months, using five psychological methods: Eysenck Personality Questionnaire, State-Trait Anxiety Inventory, Test for Self-assessment of the emotional state, Test for evaluation of moods and Test ''Self-confidence-Activity-Mood''. The Fiodorov-Chubukov's complex-climatic method was used to characterize meteorological conditions in order to include a maximal number of meteorological elements in the analysis. Sixteen weather types are defined depending on the meteorological elements values according to this method. Abrupt weather changes from one day to another, defined by the same method, were also considered. The results obtained by t-test showed that the different categories of weather led to changes in the emotional status, which indicates a character either positive or negative for the organism. The abrupt weather changes, according to expectations, have negative effects on human emotions - but only when a transition to the cloudy weather or weather type, classified as ''unfavorable'', has been realized. The relationship between weather and human emotions is rather complicated since it depends on individual characteristics of people. One of these individual psychological characteristics, marked by the dimension ''neuroticism'', has a strong effect on emotional reactions in different weather conditions. Emotionally stable individuals are more ''resistant'' to the weather influence on their emotions, while those who are emotionally unstable have a stronger dependence on the impacts of weather.

Meteorological risks are drivers of environmental innovation in agro-ecosystem management

NASA Astrophysics Data System (ADS)

Gobin, Anne; Van de Vijver, Hans; Vanwindekens, Frédéric; de Frutos Cachorro, Julia; Verspecht, Ann; Planchon, Viviane; Buyse, Jeroen

2017-04-01

Agricultural crop production is to a great extent determined by weather conditions. The research hypothesis is that meteorological risks act as drivers of environmental innovation in agro-ecosystem management. The methodology comprised five major parts: the hazard, its impact on different agro-ecosystems, vulnerability, risk management and risk communication. Generalized Extreme Value (GEV) theory was used to model annual maxima of meteorological variables based on a location-, scale- and shape-parameter that determine the center of the distribution, the deviation of the location-parameter and the upper tail decay, respectively. Spatial interpolation of GEV-derived return levels resulted in spatial temperature extremes, precipitation deficits and wet periods. The temporal overlap between extreme weather conditions and sensitive periods in the agro-ecosystem was realised using a bio-physically based modelling framework that couples phenology, a soil water balance and crop growth. 20-year return values for drought and waterlogging during different crop stages were related to arable yields. The method helped quantify agricultural production risks and rate both weather and crop-based agricultural insurance. The spatial extent of vulnerability is developed on different layers of geo-information to include meteorology, soil-landscapes, crop cover and management. Vulnerability of agroecosystems was mapped based on rules set by experts' knowledge and implemented by Fuzzy Inference System modelling and Geographical Information System tools. The approach was applied for cropland vulnerability to heavy rain and grassland vulnerability to drought. The level of vulnerability and resilience of an agro-ecosystem was also determined by risk management which differed across sectors and farm types. A calibrated agro-economic model demonstrated a marked influence of climate adapted land allocation and crop management on individual utility. The "chain of risk" approach allowed for investigating the hypothesis that meteorological risks act as drivers for agricultural innovation. Risk types were quantified in terms of probability and distribution, and further distinguished according to production type. Examples of strategies and options were provided at field, farm and policy level using different modelling methods.

Air traffic management evaluation tool

NASA Technical Reports Server (NTRS)

Sridhar, Banavar (Inventor); Chatterji, Gano Broto (Inventor); Schipper, John F. (Inventor); Bilimoria, Karl D. (Inventor); Grabbe, Shon (Inventor); Sheth, Kapil S. (Inventor)

2012-01-01

Methods for evaluating and implementing air traffic management tools and approaches for managing and avoiding an air traffic incident before the incident occurs. A first system receives parameters for flight plan configurations (e.g., initial fuel carried, flight route, flight route segments followed, flight altitude for a given flight route segment, aircraft velocity for each flight route segment, flight route ascent rate, flight route descent route, flight departure site, flight departure time, flight arrival time, flight destination site and/or alternate flight destination site), flight plan schedule, expected weather along each flight route segment, aircraft specifics, airspace (altitude) bounds for each flight route segment, navigational aids available. The invention provides flight plan routing and direct routing or wind optimal routing, using great circle navigation and spherical Earth geometry. The invention provides for aircraft dynamics effects, such as wind effects at each altitude, altitude changes, airspeed changes and aircraft turns to provide predictions of aircraft trajectory (and, optionally, aircraft fuel use). A second system provides several aviation applications using the first system. Several classes of potential incidents are analyzed and averted, by appropriate change en route of one or more parameters in the flight plan configuration, as provided by a conflict detection and resolution module and/or traffic flow management modules. These applications include conflict detection and resolution, miles-in trail or minutes-in-trail aircraft separation, flight arrival management, flight re-routing, weather prediction and analysis and interpolation of weather variables based upon sparse measurements. The invention combines these features to provide an aircraft monitoring system and an aircraft user system that interact and negotiate changes with each other.

Weather data for simplified energy calculation methods. Volume II. Middle United States: TRY data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olsen, A.R.; Moreno, S.; Deringer, J.

1984-08-01

The objective of this report is to provide a source of weather data for direct use with a number of simplified energy calculation methods available today. Complete weather data for a number of cities in the United States are provided for use in the following methods: degree hour, modified degree hour, bin, modified bin, and variable degree day. This report contains sets of weather data for 22 cities in the continental United States using Test Reference Year (TRY) source weather data. The weather data at each city has been summarized in a number of ways to provide differing levels ofmore » detail necessary for alternative simplified energy calculation methods. Weather variables summarized include dry bulb and wet bulb temperature, percent relative humidity, humidity ratio, wind speed, percent possible sunshine, percent diffuse solar radiation, total solar radiation on horizontal and vertical surfaces, and solar heat gain through standard DSA glass. Monthly and annual summaries, in some cases by time of day, are available. These summaries are produced in a series of nine computer generated tables.« less

Objective calibration of numerical weather prediction models

NASA Astrophysics Data System (ADS)

Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.

2017-07-01

Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.

Rates of biotite weathering, and clay mineral transformation and neoformation, determined from watershed geochemical mass-balance methods for the Coweeta Hydrologic Laboratory, Southern Blue Ridge Mountains, North Carolina, USA

Treesearch

Jason R. Price; Michael A. Velbel

2013-01-01

Biotite is a common constituent of silicate bedrock. Its weathering releases plant nutrients and consumes atmospheric CO2. Because of its stoichiometric relationship with its transformational weathering product and sensitivity to botanical activity, calculating biotite weathering rates using watershed mass-balance methods has proven challenging....

European In-Situ Snow Measurements: Practices and Purposes.

PubMed

Pirazzini, Roberta; Leppänen, Leena; Picard, Ghislain; Lopez-Moreno, Juan Ignacio; Marty, Christoph; Macelloni, Giovanni; Kontu, Anna; von Lerber, Annakaisa; Tanis, Cemal Melih; Schneebeli, Martin; de Rosnay, Patricia; Arslan, Ali Nadir

2018-06-22

In-situ snow measurements conducted by European institutions for operational, research, and energy business applications were surveyed in the framework of the European Cooperation in Science and Technology (COST) Action ES1404, called "A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology, and numerical weather prediction". Here we present the results of this survey, which was answered by 125 participants from 99 operational and research institutions, belonging to 38 European countries. The typologies of environments where the snow measurements are performed range from mountain to low elevated plains, including forests, bogs, tundra, urban areas, glaciers, lake ice, and sea ice. Of the respondents, 93% measure snow macrophysical parameters, such as snow presence, snow depth (HS), snow water equivalent (SWE), and snow density. These describe the bulk characteristics of the whole snowpack or of a snow layer, and they are the primary snow properties that are needed for most operational applications (such as hydrological monitoring, avalanche forecast, and weather forecast). In most cases, these measurements are done with manual methods, although for snow presence, HS, and SWE, automatized methods are also applied by some respondents. Parameters characterizing precipitating and suspended snow (such as the height of new snow, precipitation intensity, flux of drifting/blowing snow, and particle size distribution), some of which are crucial for the operational services, are measured by 74% of the respondents. Parameters characterizing the snow microstructural properties (such as the snow grain size and shape, and specific surface area), the snow electromagnetic properties (such as albedo, brightness temperature, and backscatter), and the snow composition (such as impurities and isotopes) are measured by 41%, 26%, and 13% of the respondents, respectively, mostly for research applications. The results of this survey are discussed from the perspective of the need of enhancing the efficiency and coverage of the in-situ observational network applying automatic and cheap measurement methods. Moreover, recommendations for the enhancement and harmonization of the observational network and measurement practices are provided.

Determining mineral weathering rates based on solid and solute weathering gradients and velocities: Application to biotite weathering in saprolites

USGS Publications Warehouse

White, A.F.

2002-01-01

Chemical weathering gradients are defined by the changes in the measured elemental concentrations in solids and pore waters with depth in soils and regoliths. An increase in the mineral weathering rate increases the change in these concentrations with depth while increases in the weathering velocity decrease the change. The solid-state weathering velocity is the rate at which the weathering front propagates through the regolith and the solute weathering velocity is equivalent to the rate of pore water infiltration. These relationships provide a unifying approach to calculating both solid and solute weathering rates from the respective ratios of the weathering velocities and gradients. Contemporary weathering rates based on solute residence times can be directly compared to long-term past weathering based on changes in regolith composition. Both rates incorporate identical parameters describing mineral abundance, stoichiometry, and surface area. Weathering gradients were used to calculate biotite weathering rates in saprolitic regoliths in the Piedmont of Northern Georgia, USA and in Luquillo Mountains of Puerto Rico. Solid-state weathering gradients for Mg and K at Panola produced reaction rates of 3 to 6 x 10-17 mol m-2 s-1 for biotite. Faster weathering rates of 1.8 to 3.6 ?? 10-16 mol m-2 s-1 are calculated based on Mg and K pore water gradients in the Rio Icacos regolith. The relative rates are in agreement with a warmer and wetter tropical climate in Puerto Rico. Both natural rates are three to six orders of magnitude slower than reported experimental rates of biotite weathering. ?? 2002 Elsevier Science B.V. All rights reserved.

Local Infrasound Variability Related to In Situ Atmospheric Observation

NASA Astrophysics Data System (ADS)

Kim, Keehoon; Rodgers, Arthur; Seastrand, Douglas

2018-04-01

Local infrasound is widely used to constrain source parameters of near-surface events (e.g., chemical explosions and volcanic eruptions). While atmospheric conditions are critical to infrasound propagation and source parameter inversion, local atmospheric variability is often ignored by assuming homogeneous atmospheres, and their impact on the source inversion uncertainty has never been accounted for due to the lack of quantitative understanding of infrasound variability. We investigate atmospheric impacts on local infrasound propagation by repeated explosion experiments with a dense acoustic network and in situ atmospheric measurement. We perform full 3-D waveform simulations with local atmospheric data and numerical weather forecast model to quantify atmosphere-dependent infrasound variability and address the advantage and restriction of local weather data/numerical weather model for sound propagation simulation. Numerical simulations with stochastic atmosphere models also showed nonnegligible influence of atmospheric heterogeneity on infrasound amplitude, suggesting an important role of local turbulence.

Dependence of cerebral-cortex activation in women on environmental factors

NASA Astrophysics Data System (ADS)

Pavlov, K. I.; Mukhin, V. N.; Kamenskaya, V. G.; Klimenko, V. M.

2016-12-01

The investigation of female physiological reactions to different meteorological conditions and space weather is relevant, since there are little experimental findings in this field. The purpose of this work is to determine how the level of cerebral-cortex activity in women depends on the meteorological and cosmophysical parameters of weather and space processes. We studied electroencephalograms (EEGs) recorded at rest in the sitting position and with eyes closed. We performed four series of measurements of brain bioelectrical activity from February to June 2013. We found that the level of cortical activity recorded by EEG changed significantly during these 6 months. Significant differences were detected between the cortical activity and the parameters of weather and space processes; namely, an increase in the air temperature and a decrease in the wind speed and cosmic-ray energy result in a decrease in the activity rate of the right occipital lobe.

Investigations On Limestone Weathering Of El-Tuba Minaret El Mehalla, Egypt: A Case Study.

NASA Astrophysics Data System (ADS)

El-Gohary; A, M.

The weathering phenomena that have affected El-TUBA Minaret, one of the most important Islamic stone minarets in middle delta in Egypt; that has suffered from several factors of deterioration due to weathering phenomenon. The present investigations concern the weathering factors that may have affected the minaret via the following methods and techniques: a) Contact-free methods used to study the chemical and mineralogical composition of building materials before and after weathering effects such as SEM-EDX and XRD, b) Non-destructive methods to find out percentage of range of decay which has affected these materials as well as the deteriorating roles of the surrounding environment. This method has been used to make an anatomical scheme of these features especially to specific deteriorated parts by GIS and other digital imaging techniques. All results confirm that the degradation factors affecting the minaret building materials are essentially attributed to direct effects of weathering phenomena. These weathering phenomena arise from physical and chemical mechanisms which have lead to many deterioration forms on the following two scales: a) Macro scale of weathering phenomena (e.g. structural damages, crakes, loss of plumb and walls bulging), b) Micro scale of weathering phenomena (e.g. hydrated salts, bursting, flaking, coloration, scaling, skinning, exfoliation and soiling). Discussion on the management and rehabilitation of this monument is made, since it is one of the religious shrines in Egypt.

The Synoptic Climatology of Severe Thunderstorms in Manitoba.

NASA Astrophysics Data System (ADS)

Ladochy, Stephen Eugene Gabriel

The thesis presents the climatologies for Manitoba thunderstorms, hailstorms and tornadoes as well as investigates the synoptic weather conditions conducive for their development. The study not only uses standard meteorological information, but also various kinds of proxy data, in the form of damage reports. These damage reports complement the meteorological data by providing a higher resolution of observations, particularly in the sparsely populated regions. The synoptic conditions are relatively similar for all forms of severe thunderstorms, though the upper level jet stream (ULJ) is stronger for tornadoes, in general. Composite charts, drawn for 50 larger, more damaging hail days and 48 tornado days in the 1970's, helped identify important surface and upper air weather parameters and their inter -relationships with each other and the location of the storm. Time sequence composite charts were used to also show the development process in severe weather occurrences. From the composites, a synoptic weather type classification was devised with 10 categories to identify each storm by type. The most common pattern for severe weather has a strong southwesterly ULJ, with the storm occurring ahead of an advancing cold front. The ULJ patterns were drawn for each synoptic type days, showing differences between categories. The average conditions during tornado touchdowns were also seen from composite maps of surface and upper air isobaric charts. While severe thunderstorms are seen to occur under the "ideal" conditions, often described for U.S. severe weather, they can also be produced under other weather patterns and combinations of atmospheric parameters thought less favorable. The ULJ and LLJ (low-level jet stream) models used in U.S. studies do not always fit Manitoba storms, however, less favorable jet positions, at specific levels, can be compensated for by low-level advection of warm, and moist air.

A joint method to retrieve directional ocean wave spectra from SAR and wave spectrometer data

NASA Astrophysics Data System (ADS)

Ren, Lin; Yang, Jingsong; Zheng, Gang; Wang, Juan

2016-07-01

This paper proposes a joint method to simultaneously retrieve wave spectra at different scales from spaceborne Synthetic Aperture Radar (SAR) and wave spectrometer data. The method combines the output from the two different sensors to overcome retrieval limitations that occur in some sea states. The wave spectrometer sensitivity coefficient is estimated using an effective significant wave height (SWH), which is an average of SAR-derived and wave spectrometer-derived SWH. This averaging extends the area of the sea surface sampled by the nadir beam of the wave spectrometer to improve the accuracy of the estimated sensitivity coefficient in inhomogeneous sea states. Wave spectra are then retrieved from SAR data using wave spectrometer-derived spectra as first guess spectra to complement the short waves lost in SAR data retrieval. In addition, the problem of 180° ambiguity in retrieved spectra is overcome using SAR imaginary cross spectra. Simulated data were used to validate the joint method. The simulations demonstrated that retrieved wave parameters, including SWH, peak wave length (PWL), and peak wave direction (PWD), agree well with reference parameters. Collocated data from ENVISAT advanced SAR (ASAR), the airborne wave spectrometer STORM, the PHAROS buoy, and the European Centre for Medium-Range Weather Forecasting (ECMWF) were then used to verify the proposed method. Wave parameters retrieved from STORM and two ASAR images were compared to buoy and ECMWF wave data. Most of the retrieved parameters were comparable to reference parameters. The results of this study show that the proposed joint retrieval method could be a valuable complement to traditional methods used to retrieve directional ocean wave spectra, particularly in inhomogeneous sea states.

Mixture and method for simulating soiling and weathering of surfaces

DOEpatents

Sleiman, Mohamad; Kirchstetter, Thomas; Destaillats, Hugo; Levinson, Ronnen; Berdahl, Paul; Akbari, Hashem

2018-01-02

This disclosure provides systems, methods, and apparatus related to simulated soiling and weathering of materials. In one aspect, a soiling mixture may include an aqueous suspension of various amounts of salt, soot, dust, and humic acid. In another aspect, a method may include weathering a sample of material in a first exposure of the sample to ultraviolet light, water vapor, and elevated temperatures, depositing a soiling mixture on the sample, and weathering the sample in a second exposure of the sample to ultraviolet light, water vapor, and elevated temperatures.

Predicted Weather Display and Decision Support Interface for Flight Deck

NASA Technical Reports Server (NTRS)

Johnson, Walter W. (Inventor); Wong, Dominic G. (Inventor); Koteskey, Robert W. (Inventor); Wu, Shu-Chieh (Inventor)

2017-01-01

A system and method for providing visual depictions of a predictive weather forecast for in-route vehicle trajectory planning. The method includes displaying weather information on a graphical display, displaying vehicle position information on the graphical display, selecting a predictive interval, displaying predictive weather information for the predictive interval on the graphical display, and displaying predictive vehicle position information for the predictive interval on the graphical display, such that the predictive vehicle position information is displayed relative to the predictive weather information, for in-route trajectory planning.

Mechanical behavior and shape optimization of lining structure for subsea tunnel excavated in weathered slot

NASA Astrophysics Data System (ADS)

Li, Peng-fei; Zhou, Xiao-jun

2015-12-01

Subsea tunnel lining structures should be designed to sustain the loads transmitted from surrounding ground and groundwater during excavation. Extremely high pore-water pressure reduces the effective strength of the country rock that surrounds a tunnel, thereby lowering the arching effect and stratum stability of the structure. In this paper, the mechanical behavior and shape optimization of the lining structure for the Xiang'an tunnel excavated in weathered slots are examined. Eight cross sections with different geometric parameters are adopted to study the mechanical behavior and shape optimization of the lining structure. The hyperstatic reaction method is used through finite element analysis software ANSYS. The mechanical behavior of the lining structure is evidently affected by the geometric parameters of crosssectional shape. The minimum safety factor of the lining structure elements is set to be the objective function. The efficient tunnel shape to maximize the minimum safety factor is identified. The minimum safety factor increases significantly after optimization. The optimized cross section significantly improves the mechanical characteristics of the lining structure and effectively reduces its deformation. Force analyses of optimization process and program are conducted parametrically so that the method can be applied to the optimization design of other similar structures. The results obtained from this study enhance our understanding of the mechanical behavior of the lining structure for subsea tunnels. These results are also beneficial to the optimal design of lining structures in general.

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

PubMed

Eisinga, Rob; Te Grotenhuis, Manfred; Pelzer, Ben

2012-07-01

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.

46 CFR 160.077-5 - Incorporation by reference.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., Breaking of Woven Cloth; Grab Method. (ii) Method 5132, Strength of Cloth, Tearing; Falling-Pendulum Method. (iii) Method 5134, Strength of Cloth, Tearing; Tongue Method. (iv) Method 5804.1, Weathering Resistance of Cloth; Accelerated Weathering Method. (v) Method 5762, Mildew Resistance of Textile Materials...

46 CFR 160.077-5 - Incorporation by reference.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Elongation, Breaking of Woven Cloth; Grab Method. (2) Method 5132, Strength of Cloth, Tearing; Falling-Pendulum Method. (3) Method 5134, Strength of Cloth, Tearing; Tongue Method. (4) Method 5804.1, Weathering Resistance of Cloth; Accelerated Weathering Method. (5) Method 5762, Mildew Resistance of Textile Materials...

46 CFR 160.077-5 - Incorporation by reference.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., Breaking of Woven Cloth; Grab Method. (ii) Method 5132, Strength of Cloth, Tearing; Falling-Pendulum Method. (iii) Method 5134, Strength of Cloth, Tearing; Tongue Method. (iv) Method 5804.1, Weathering Resistance of Cloth; Accelerated Weathering Method. (v) Method 5762, Mildew Resistance of Textile Materials...

46 CFR 160.077-5 - Incorporation by reference.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Elongation, Breaking of Woven Cloth; Grab Method. (2) Method 5132, Strength of Cloth, Tearing; Falling-Pendulum Method. (3) Method 5134, Strength of Cloth, Tearing; Tongue Method. (4) Method 5804.1, Weathering Resistance of Cloth; Accelerated Weathering Method. (5) Method 5762, Mildew Resistance of Textile Materials...

Bridging the Transition from Mesoscale to Microscale Turbulence in Numerical Weather Prediction Models

NASA Astrophysics Data System (ADS)

Muñoz-Esparza, Domingo; Kosović, Branko; Mirocha, Jeff; van Beeck, Jeroen

2014-12-01

With a focus towards developing multiscale capabilities in numerical weather prediction models, the specific problem of the transition from the mesoscale to the microscale is investigated. For that purpose, idealized one-way nested mesoscale to large-eddy simulation (LES) experiments were carried out using the Weather Research and Forecasting model framework. It is demonstrated that switching from one-dimensional turbulent diffusion in the mesoscale model to three-dimensional LES mixing does not necessarily result in an instantaneous development of turbulence in the LES domain. On the contrary, very large fetches are needed for the natural transition to turbulence to occur. The computational burden imposed by these long fetches necessitates the development of methods to accelerate the generation of turbulence on a nested LES domain forced by a smooth mesoscale inflow. To that end, four new methods based upon finite amplitude perturbations of the potential temperature field along the LES inflow boundaries are developed, and investigated under convective conditions. Each method accelerated the development of turbulence within the LES domain, with two of the methods resulting in a rapid generation of production and inertial range energy content associated to microscales that is consistent with non-nested simulations using periodic boundary conditions. The cell perturbation approach, the simplest and most efficient of the best performing methods, was investigated further under neutral and stable conditions. Successful results were obtained in all the regimes, where satisfactory agreement of mean velocity, variances and turbulent fluxes, as well as velocity and temperature spectra, was achieved with reference non-nested simulations. In contrast, the non-perturbed LES solution exhibited important energy deficits associated to a delayed establishment of fully-developed turbulence. The cell perturbation method has negligible computational cost, significantly accelerates the generation of realistic turbulence, and requires minimal parameter tuning, with the necessary information relatable to mean inflow conditions provided by the mesoscale solution.

A probabilistic model framework for evaluating year-to-year variation in crop productivity

NASA Astrophysics Data System (ADS)

Yokozawa, M.; Iizumi, T.; Tao, F.

2008-12-01

Most models describing the relation between crop productivity and weather condition have so far been focused on mean changes of crop yield. For keeping stable food supply against abnormal weather as well as climate change, evaluating the year-to-year variations in crop productivity rather than the mean changes is more essential. We here propose a new framework of probabilistic model based on Bayesian inference and Monte Carlo simulation. As an example, we firstly introduce a model on paddy rice production in Japan. It is called PRYSBI (Process- based Regional rice Yield Simulator with Bayesian Inference; Iizumi et al., 2008). The model structure is the same as that of SIMRIW, which was developed and used widely in Japan. The model includes three sub- models describing phenological development, biomass accumulation and maturing of rice crop. These processes are formulated to include response nature of rice plant to weather condition. This model inherently was developed to predict rice growth and yield at plot paddy scale. We applied it to evaluate the large scale rice production with keeping the same model structure. Alternatively, we assumed the parameters as stochastic variables. In order to let the model catch up actual yield at larger scale, model parameters were determined based on agricultural statistical data of each prefecture of Japan together with weather data averaged over the region. The posterior probability distribution functions (PDFs) of parameters included in the model were obtained using Bayesian inference. The MCMC (Markov Chain Monte Carlo) algorithm was conducted to numerically solve the Bayesian theorem. For evaluating the year-to-year changes in rice growth/yield under this framework, we firstly iterate simulations with set of parameter values sampled from the estimated posterior PDF of each parameter and then take the ensemble mean weighted with the posterior PDFs. We will also present another example for maize productivity in China. The framework proposed here provides us information on uncertainties, possibilities and limitations on future improvements in crop model as well.

A graphical weather system design for the NASA transport systems research vehicle B-737

NASA Technical Reports Server (NTRS)

Scanlon, Charles H.

1992-01-01

A graphical weather system was designed for testing in the NASA Transport Systems Research Vehicle B-737 airplane and simulator. The purpose of these tests was to measure the impact of graphical weather products on aircrew decision processes, weather situation awareness, reroute clearances, workload, and weather monitoring. The flight crew graphical weather interface is described along with integration of the weather system with the flight navigation system, and data link transmission methods for sending weather data to the airplane.

Assessing Fire Weather Index using statistical downscaling and spatial interpolation techniques in Greece

NASA Astrophysics Data System (ADS)

Karali, Anna; Giannakopoulos, Christos; Frias, Maria Dolores; Hatzaki, Maria; Roussos, Anargyros; Casanueva, Ana

2013-04-01

Forest fires have always been present in the Mediterranean ecosystems, thus they constitute a major ecological and socio-economic issue. The last few decades though, the number of forest fires has significantly increased, as well as their severity and impact on the environment. Local fire danger projections are often required when dealing with wild fire research. In the present study the application of statistical downscaling and spatial interpolation methods was performed to the Canadian Fire Weather Index (FWI), in order to assess forest fire risk in Greece. The FWI is used worldwide (including the Mediterranean basin) to estimate the fire danger in a generalized fuel type, based solely on weather observations. The meteorological inputs to the FWI System are noon values of dry-bulb temperature, air relative humidity, 10m wind speed and precipitation during the previous 24 hours. The statistical downscaling methods are based on a statistical model that takes into account empirical relationships between large scale variables (used as predictors) and local scale variables. In the framework of the current study the statistical downscaling portal developed by the Santander Meteorology Group (https://www.meteo.unican.es/downscaling) in the framework of the EU project CLIMRUN (www.climrun.eu) was used to downscale non standard parameters related to forest fire risk. In this study, two different approaches were adopted. Firstly, the analogue downscaling technique was directly performed to the FWI index values and secondly the same downscaling technique was performed indirectly through the meteorological inputs of the index. In both cases, the statistical downscaling portal was used considering the ERA-Interim reanalysis as predictands due to the lack of observations at noon. Additionally, a three-dimensional (3D) interpolation method of position and elevation, based on Thin Plate Splines (TPS) was used, to interpolate the ERA-Interim data used to calculate the index. Results from this method were compared with the statistical downscaling results obtained from the portal. Finally, FWI was computed using weather observations obtained from the Hellenic National Meteorological Service, mainly in the south continental part of Greece and a comparison with the previous results was performed.

Detection of mesoscale zones of atmospheric instabilities using remote sensing and weather forecasting model data

NASA Astrophysics Data System (ADS)

Winnicki, I.; Jasinski, J.; Kroszczynski, K.; Pietrek, S.

2009-04-01

The paper presents elements of research conducted in the Faculty of Civil Engineering and Geodesy of the Military University of Technology, Warsaw, Poland, concerning application of mesoscale models and remote sensing data to determining meteorological conditions of aircraft flight directly related with atmospheric instabilities. The quality of meteorological support of aviation depends on prompt and effective forecasting of weather conditions changes. The paper presents a computer module for detecting and monitoring zones of cloud cover, precipitation and turbulence along the aircraft flight route. It consists of programs and scripts for managing, processing and visualizing meteorological and remote sensing databases. The application was developed in Matlab® for Windows®. The module uses products of COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) mesoscale non-hydrostatic model of the atmosphere developed by the US Naval Research Laboratory, satellite images acquisition system from the MSG-2 (Meteosat Second Generation) of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and meteorological radars data acquired from the Institute of Meteorology and Water Management (IMGW), Warsaw, Poland. The satellite images acquisition system and the COAMPS model are run operationally in the Faculty of Civil Engineering and Geodesy. The mesoscale model is run on an IA64 Feniks multiprocessor 64-bit computer cluster. The basic task of the module is to enable a complex analysis of data sets of miscellaneous information structure and to verify COAMPS results using satellite and radar data. The research is conducted using uniform cartographic projection of all elements of the database. Satellite and radar images are transformed into the Lambert Conformal projection of COAMPS. This facilitates simultaneous interpretation and supports decision making process for safe execution of flights. Forecasts are based on horizontal distributions and vertical profiles of meteorological parameters produced by the module. Verification of forecasts includes research of spatial and temporal correlations of structures generated by the model, e.g.: cloudiness, meteorological phenomena (fogs, precipitation, turbulence) and structures identified on current satellite images. The developed module determines meteorological parameters fields for vertical profiles of the atmosphere. Interpolation procedures run at user selected standard (pressure) or height levels of the model enable to determine weather conditions along any route of aircraft. Basic parameters of the procedures determining e.g. flight safety include: cloud base, visibility, cloud cover, turbulence coefficient, icing and precipitation intensity. Determining icing and turbulence characteristics is based on standard and new methods (from other mesoscale models). The research includes also investigating new generation mesoscale models, especially remote sensing data assimilation. This is required by necessity to develop and introduce objective methods of forecasting weather conditions. Current research in the Faculty of Civil Engineering and Geodesy concerns validation of the mesoscale module performance.

Weathering steel as a potential source for metal contamination: Metal dissolution during 3-year of field exposure in a urban coastal site.

PubMed

Raffo, Simona; Vassura, Ivano; Chiavari, Cristina; Martini, Carla; Bignozzi, Maria C; Passarini, Fabrizio; Bernardi, Elena

2016-06-01

Surface and building runoff can significantly contribute to the total metal loading in urban runoff waters, with potential adverse effects on the receiving ecosystems. The present paper analyses the corrosion-induced metal dissolution (Fe, Mn, Cr, Ni, Cu) from weathering steel (Cor-Ten A) with or without artificial patinas, exposed for 3 years in unsheltered conditions at a marine urban site (Rimini, Italy). The influence of environmental parameters, atmospheric pollutants and surface finish on the release of dissolved metals in rain was evaluated, also by means of multivariate analysis (two-way and three-way Principal Component Analysis). In addition, surface and cross-section investigations were performed so as to monitor the patina evolution. The contribution provided by weathering steel runoff to the dissolved Fe, Mn and Ni loading at local level is not negligible and pre-patination treatments seem to worsen the performance of weathering steel in term of metal release. Metal dissolution is strongly affected by extreme events and shows seasonal variations, with different influence of seasonal parameters on the behaviour of bare or artificially patinated steel, suggesting that climate changes could significantly influence metal release from this alloy. Therefore, it is essential to perform a long-term monitoring of the performance, the durability and the environmental impact of weathering steel. Copyright © 2016 Elsevier Ltd. All rights reserved.

Progress in space weather predictions and applications

NASA Astrophysics Data System (ADS)

Lundstedt, H.

The methods of today's predictions of space weather and effects are so much more advanced and yesterday's statistical methods are now replaced by integrated knowledge-based neuro-computing models and MHD methods. Within the ESA Space Weather Programme Study a real-time forecast service has been developed for space weather and effects. This prototype is now being implemented for specific users. Today's applications are not only so many more but also so much more advanced and user-oriented. A scientist needs real-time predictions of a global index as input for an MHD model calculating the radiation dose for EVAs. A power company system operator needs a prediction of the local value of a geomagnetically induced current. A science tourist needs to know whether or not aurora will occur. Soon we might even be able to predict the tropospheric climate changes and weather caused by the space weather.

Evaluation of weather-based rice yield models in India

NASA Astrophysics Data System (ADS)

Sudharsan, D.; Adinarayana, J.; Reddy, D. Raji; Sreenivas, G.; Ninomiya, S.; Hirafuji, M.; Kiura, T.; Tanaka, K.; Desai, U. B.; Merchant, S. N.

2013-01-01

The objective of this study was to compare two different rice simulation models—standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])—with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India. Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models. Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India. Initially, the results were obtained using 4 years (1994-1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values. Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield. Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values. Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system. These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis. These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner. However, SIMRIW requires fine tuning for better results/decision making.

Weather conditions and political party vote share in Dutch national parliament elections, 1971-2010.

PubMed

Eisinga, Rob; Te Grotenhuis, Manfred; Pelzer, Ben

2012-11-01

Inclement weather on election day is widely seen to benefit certain political parties at the expense of others. Empirical evidence for this weather-vote share hypothesis is sparse however. We examine the effects of rainfall and temperature on share of the votes of eight political parties that participated in 13 national parliament elections, held in the Netherlands from 1971 to 2010. This paper merges the election results for all Dutch municipalities with election-day weather observations drawn from all official weather stations well distributed over the country. We find that the weather parameters affect the election results in a statistically and politically significant way. Whereas the Christian Democratic party benefits from substantial rain (10 mm) on voting day by gaining one extra seat in the 150-seat Dutch national parliament, the left-wing Social Democratic (Labor) and the Socialist parties are found to suffer from cold and wet conditions. Cold (5°C) and rainy (10 mm) election day weather causes the latter parties to lose one or two parliamentary seats.

Weather conditions and political party vote share in Dutch national parliament elections, 1971-2010

NASA Astrophysics Data System (ADS)

Eisinga, Rob; Te Grotenhuis, Manfred; Pelzer, Ben

2012-11-01

Inclement weather on election day is widely seen to benefit certain political parties at the expense of others. Empirical evidence for this weather-vote share hypothesis is sparse however. We examine the effects of rainfall and temperature on share of the votes of eight political parties that participated in 13 national parliament elections, held in the Netherlands from 1971 to 2010. This paper merges the election results for all Dutch municipalities with election-day weather observations drawn from all official weather stations well distributed over the country. We find that the weather parameters affect the election results in a statistically and politically significant way. Whereas the Christian Democratic party benefits from substantial rain (10 mm) on voting day by gaining one extra seat in the 150-seat Dutch national parliament, the left-wing Social Democratic (Labor) and the Socialist parties are found to suffer from cold and wet conditions. Cold (5°C) and rainy (10 mm) election day weather causes the latter parties to lose one or two parliamentary seats.

Middle Atmosphere Program. Handbook for MAP, volume 20

NASA Technical Reports Server (NTRS)

Bowhill, S. A. (Editor); Edwards, B. (Editor)

1986-01-01

Various topics related to investigations of the middle atmosphere are discussed. Numerical weather prediction, performance characteristics of weather profiling radars, determination of gravity wave and turbulence parameters, case studies of gravity-wave propagation, turbulence and diffusion due to gravity waves, the climatology of gravity waves, mesosphere-stratosphere-troposphere radar, antenna arrays, and data management techniques are among the topics discussed.

Comparison of Cone Model Parameters for Halo Coronal Mass Ejections

NASA Astrophysics Data System (ADS)

Na, Hyeonock; Moon, Y.-J.; Jang, Soojeong; Lee, Kyoung-Sun; Kim, Hae-Yeon

2013-11-01

Halo coronal mass ejections (HCMEs) are a major cause of geomagnetic storms, hence their three-dimensional structures are important for space weather. We compare three cone models: an elliptical-cone model, an ice-cream-cone model, and an asymmetric-cone model. These models allow us to determine three-dimensional parameters of HCMEs such as radial speed, angular width, and the angle [ γ] between sky plane and cone axis. We compare these parameters obtained from three models using 62 HCMEs observed by SOHO/LASCO from 2001 to 2002. Then we obtain the root-mean-square (RMS) error between the highest measured projection speeds and their calculated projection speeds from the cone models. As a result, we find that the radial speeds obtained from the models are well correlated with one another ( R > 0.8). The correlation coefficients between angular widths range from 0.1 to 0.48 and those between γ-values range from -0.08 to 0.47, which is much smaller than expected. The reason may be the different assumptions and methods. The RMS errors between the highest measured projection speeds and the highest estimated projection speeds of the elliptical-cone model, the ice-cream-cone model, and the asymmetric-cone model are 376 km s-1, 169 km s-1, and 152 km s-1. We obtain the correlation coefficients between the location from the models and the flare location ( R > 0.45). Finally, we discuss strengths and weaknesses of these models in terms of space-weather application.

Sorptive removal of nickel onto weathered basaltic andesite products: kinetics and isotherms.

PubMed

Shah, Bhavna A; Shah, Ajay V; Singh, Rajesh R; Patel, Nayan B

2009-07-15

The suitability of weathered basaltic andesite products (WBAP) as a potential sorbent was assessed for the removal of Ni (II) from electroplating industrial wastewater. A model study based on the batch mode of operation was carried out for Ni (II) removal from aqueous solution. The effect of various parameters such as hydronium ion concentration, shaking time, sorbent dose, initial Ni (II) concentration, and temperature on the sorption process was studied. At optimised conditions of the various parameters, the industrial wastewater loaded with Ni (II) was sorbed onto WBAP. Thermodynamic parameters for the sorption process were evaluated. Freundlich, Langmuir, Temkin, and Dubinin-Kaganer-Radushkevich isotherms were applied to the sorption pattern on the WBAP. The sorption dynamics of the process was evaluated by applying Lagergren, Bangham, and Weber & Morris equations. The sorption process follows Pseudo-second-order rate of surface diffusion which is identified as the predominating mechanism. The sorption process was found to be reversible by the recovery of sorbed Ni (II) upon extraction with 0.5 MHNO3. The sorbent before and after sorption, was characterized by Fourier transform infrared (FTIR), Powder X-Ray diffraction PXRD), and Thermogravimetric analysis (TGA) methods. The change in surface morphology and crystallanity of the mineral after sorption was analyzed by Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM). Based on the previous model study, an electroplating industrial effluent was successfully treated with WBAP to minimize the pollution load caused by Ni (II).

Weathering phases recorded by gnammas developed since last glaciation at Serra da Estrela, Portugal

NASA Astrophysics Data System (ADS)

Domínguez-Villar, David; Razola, Laura; Carrasco, Rosa M.; Jennings, Carrie E.; Pedraza, Javier

2009-09-01

The morphometrical analysis of gnammas (weathering pits) in granite landscapes has been used to establish the relative chronology of recent erosive surfaces and to provide the weathering history in a region. To test the validity of gnammas as relative chronometer indicators, and the reliability of the obtained weathering record, two sites have been studied in Serra da Estrela, Portugal. The first site is within the limits of the glacier that existed in these mountains during the last glaciation, whereas the second site is located in an unglaciated sector of the mountains, which preserves a longer record of weathering in the bedrock surface. The number of gnamma weathering phases recorded in the latter site (8) is larger than those from the former (6). Correlation between both measurement stations based on morphometrical criteria is excellent for the younger six weathering phases (1 to 6). Consequently, the parameter used for relative chronology ( δ-value) has been verified to be age dependent, although absolute values are modulated by microclimate due to altitude variations. The weathering record was essentially duplicated once the surfaces at both sites were exposed, demonstrating the reliability of gnamma evolution as a post-glacial environmental indicator for the region.

Testing the reliability of ice-cream cone model

NASA Astrophysics Data System (ADS)

Pan, Zonghao; Shen, Chenglong; Wang, Chuanbing; Liu, Kai; Xue, Xianghui; Wang, Yuming; Wang, Shui

2015-04-01

Coronal Mass Ejections (CME)'s properties are important to not only the physical scene itself but space-weather prediction. Several models (such as cone model, GCS model, and so on) have been raised to get rid of the projection effects within the properties observed by spacecraft. According to SOHO/ LASCO observations, we obtain the 'real' 3D parameters of all the FFHCMEs (front-side full halo Coronal Mass Ejections) within the 24th solar cycle till July 2012, by the ice-cream cone model. Considering that the method to obtain 3D parameters from the CME observations by multi-satellite and multi-angle has higher accuracy, we use the GCS model to obtain the real propagation parameters of these CMEs in 3D space and compare the results with which by ice-cream cone model. Then we could discuss the reliability of the ice-cream cone model.

Working Group 1 "Advanced GNSS Processing Techniques" of the COST Action GNSS4SWEC: Overview of main achievements

NASA Astrophysics Data System (ADS)

Douša, Jan; Dick, Galina; Kačmařík, Michal; Václavovic, Pavel; Pottiaux, Eric; Zus, Florian; Brenot, Hugues; Moeller, Gregor; Hinterberger, Fabian; Pacione, Rosa; Stuerze, Andrea; Eben, Kryštof; Teferle, Norman; Ding, Wenwu; Morel, Laurent; Kaplon, Jan; Hordyniec, Pavel; Rohm, Witold

2017-04-01

The COST Action ES1206 GNSS4SWEC addresses new exploitations of the synergy between developments in GNSS and meteorological communities. The Working Group 1 (Advanced GNSS processing techniques) deals with implementing and assessing new methods for GNSS tropospheric monitoring and precise positioning exploiting all modern GNSS constellations, signals, products etc. Besides other goals, WG1 coordinates development of advanced tropospheric products in support of weather numerical and non-numerical nowcasting. These are ultra-fast and high-resolution tropospheric products available in real time or in a sub-hourly fashion and parameters in support of monitoring an anisotropy of the troposphere, e.g. horizontal gradients and tropospheric slant path delays. This talk gives an overview of WG1 activities and, particularly, achievements in two activities, Benchmark and Real-time demonstration campaigns. For the Benchmark campaign a complex data set of GNSS observations and various meteorological data were collected for a two-month period in 2013 (May-June) which included severe weather events in central Europe. An initial processing of data sets from GNSS and numerical weather models (NWM) provided independently estimated reference parameters - ZTDs and tropospheric horizontal gradients. The comparison of horizontal tropospheric gradients from GNSS and NWM data demonstrated a very good agreement among independent solutions with negligible biases and an accuracy of about 0.5 mm. Visual comparisons of maps of zenith wet delays and tropospheric horizontal gradients showed very promising results for future exploitations of advanced GNSS tropospheric products in meteorological applications such as severe weather event monitoring and weather nowcasting. The Benchmark data set is also used for an extensive validation of line-of-sight tropospheric Slant Total Delays (STD) from GNSS, NWM-raytracing and Water Vapour Radiometer (WVR) solutions. Seven institutions delivered their STDs estimated based on GNSS observations processed using different software and strategies. STDs from NWM ray-tracing came from three institutions using four different NWM models. Results show generally a very good mutual agreement among all solutions from all techniques. The influence of adding not cleaned GNSS post-fit residuals, i.e. residuals that still contains non-tropospheric systematic effects such as multipath, to estimated STDs will be presented. The Real-time demonstration campaign aims at enhancing and assessing ultra-fast GNSS tropospheric products for severe weather and NWM nowcasting. Results are showed from real-time demonstrations as well as offline production simulating real-time using Benchmark campaign.

Studies regarding the quality of numerical weather forecasts of the WRF model integrated at high-resolutions for the Romanian territory

DOE PAGES

Iriza, Amalia; Dumitrache, Rodica C.; Lupascu, Aurelia; ...

2016-01-01

Our paper aims to evaluate the quality of high-resolution weather forecasts from the Weather Research and Forecasting (WRF) numerical weather prediction model. The lateral and boundary conditions were obtained from the numerical output of the Consortium for Small-scale Modeling (COSMO) model at 7 km horizontal resolution. Furthermore, the WRF model was run for January and July 2013 at two horizontal resolutions (3 and 1 km). The numerical forecasts of the WRF model were evaluated using different statistical scores for 2 m temperature and 10 m wind speed. Our results showed a tendency of the WRF model to overestimate the valuesmore » of the analyzed parameters in comparison to observations.« less

Studies regarding the quality of numerical weather forecasts of the WRF model integrated at high-resolutions for the Romanian territory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iriza, Amalia; Dumitrache, Rodica C.; Lupascu, Aurelia

Our paper aims to evaluate the quality of high-resolution weather forecasts from the Weather Research and Forecasting (WRF) numerical weather prediction model. The lateral and boundary conditions were obtained from the numerical output of the Consortium for Small-scale Modeling (COSMO) model at 7 km horizontal resolution. Furthermore, the WRF model was run for January and July 2013 at two horizontal resolutions (3 and 1 km). The numerical forecasts of the WRF model were evaluated using different statistical scores for 2 m temperature and 10 m wind speed. Our results showed a tendency of the WRF model to overestimate the valuesmore » of the analyzed parameters in comparison to observations.« less

Dynamically Evolving Sectors for Convective Weather Impact

NASA Technical Reports Server (NTRS)

Drew, Michael C.

2010-01-01

A new strategy for altering existing sector boundaries in response to blocking convective weather is presented. This method seeks to improve the reduced capacity of sectors directly affected by weather by moving boundaries in a direction that offers the greatest capacity improvement. The boundary deformations are shared by neighboring sectors within the region in a manner that preserves their shapes and sizes as much as possible. This reduces the controller workload involved with learning new sector designs. The algorithm that produces the altered sectors is based on a force-deflection mesh model that needs only nominal traffic patterns and the shape of the blocking weather for input. It does not require weather-affected traffic patterns that would have to be predicted by simulation. When compared to an existing optimal sector design method, the sectors produced by the new algorithm are more similar to the original sector shapes, resulting in sectors that may be more suitable for operational use because the change is not as drastic. Also, preliminary results show that this method produces sectors that can equitably distribute the workload of rerouted weather-affected traffic throughout the region where inclement weather is present. This is demonstrated by sector aircraft count distributions of simulated traffic in weather-affected regions.

Handling the unknown soil hydraulic parameters in data assimilation for unsaturated flow problems

NASA Astrophysics Data System (ADS)

Lange, Natascha; Erdal, Daniel; Neuweiler, Insa

2017-04-01

Model predictions of flow in the unsaturated zone require the soil hydraulic parameters. However, these parameters cannot be determined easily in applications, in particular if observations are indirect and cover only a small range of possible states. Correlation of parameters or their correlation in the range of states that are observed is a problem, as different parameter combinations may reproduce approximately the same measured water content. In field campaigns this problem can be helped by adding more measurement devices. Often, observation networks are designed to feed models for long term prediction purposes (i.e. for weather forecasting). A popular way of making predictions with such kind of observations are data assimilation methods, like the ensemble Kalman filter (Evensen, 1994). These methods can be used for parameter estimation if the unknown parameters are included in the state vector and updated along with the model states. Given the difficulties related to estimation of the soil hydraulic parameters in general, it is questionable, though, whether these methods can really be used for parameter estimation under natural conditions. Therefore, we investigate the ability of the ensemble Kalman filter to estimate the soil hydraulic parameters. We use synthetic identical twin-experiments to guarantee full knowledge of the model and the true parameters. We use the van Genuchten model to describe the soil water retention and relative permeability functions. This model is unfortunately prone to the above mentioned pseudo-correlations of parameters. Therefore, we also test the simpler Russo Gardner model, which is less affected by that problem, in our experiments. The total number of unknown parameters is varied by considering different layers of soil. Besides, we study the influence of the parameter updates on the water content predictions. We test different iterative filter approaches and compare different observation strategies for parameter identification. Considering heterogeneous soils, we discuss the representativeness of different observation types to be used for the assimilation. G. Evensen. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. Journal of Geophysical Research: Oceans, 99(C5):10143-10162, 1994

Space weather monitoring and forecasting in South America: products from the user requests to the development of regional magnetic indices and GNSS vertical error maps

NASA Astrophysics Data System (ADS)

Denardini, Clezio Marcos; Padilha, Antonio; Takahashi, Hisao; Souza, Jonas; Mendes, Odim; Batista, Inez S.; SantAnna, Nilson; Gatto, Rubens; Costa, D. Joaquim

On August 2007 the National Institute for Space Research started a task force to develop and operate a space weather program, which is kwon by the acronyms Embrace that stands for the Portuguese statement “Estudo e Monitoramento BRAasileiro de Clima Espacial” Program (Brazilian Space Weather Study and Monitoring program). The main purpose of the Embrace Program is to monitor the space climate and weather from sun, interplanetary space, magnetosphere and ionosphere-atmosphere, and to provide useful information to space related communities, technological, industrial and academic areas. Since then we have being visiting several different space weather costumers and we have host two workshops of Brazilian space weather users at the Embrace facilities. From the inputs and requests collected from the users the Embrace Program decided to monitored several physical parameters of the sun-earth environment through a large ground base network of scientific sensors and under collaboration with space weather centers partners. Most of these physical parameters are daily published on the Brazilian space weather program web portal, related to the entire network sensors available. A comprehensive data bank and an interface layer are under development to allow an easy and direct access to the useful information. Nowadays, the users will count on products derived from a GNSS monitor network that covers most of the South American territory; a digisonde network that monitors the ionospheric profiles in two equatorial sites and in one low latitude site; several solar radio telescopes to monitor solar activity, and a magnetometer network, besides a global ionospheric physical model. Regarding outreach, we publish a daily bulletin in Portuguese with the status of the space weather environment on the Sun, in the Interplanetary Medium and close to the Earth. Since December 2011, all these activities are carried out at the Embrace Headquarter, a building located at the INPE's main campus. Recently, we have release brand new products, among them, some regional magnetic indices and the GNSS vertical error map over South America. Contacting Author: C. M. Denardini (clezio.denardin@inpe.br)

Road weather information for travelers : improving road weather messages and dissemination methods.

DOT National Transportation Integrated Search

2010-01-01

The Federal Highway Administration (FHWA) Road Weather Management Program (RWMP) recently completed a study titled Human Factors Analysis of Road Weather Advisory and Control Information (Publication No. FHWAJPO- 10-053). The goal of the study was to...

Heat and Moisture Transport and Storage Parameters of Bricks Affected by the Environment

NASA Astrophysics Data System (ADS)

Kočí, Václav; Čáchová, Monika; Koňáková, Dana; Vejmelková, Eva; Jerman, Miloš; Keppert, Martin; Maděra, Jiří; Černý, Robert

2018-05-01

The effect of external environment on heat and moisture transport and storage properties of the traditional fired clay brick, sand-lime brick and highly perforated ceramic block commonly used in the Czech Republic and on their hygrothermal performance in building envelopes is analyzed by a combination of experimental and computational techniques. The experimental measurements of thermal, hygric and basic physical parameters are carried out in the reference state and after a 3-year exposure of the bricks to real climatic conditions of the city of Prague. The obtained results showed that after 3 years of weathering the porosity of the analyzed bricks increased up to five percentage points which led to an increase in liquid and gaseous moisture transport parameters and a decrease in thermal conductivity. Computational modeling of hygrothermal performance of building envelopes made of the studied bricks was done using both reference and weather-affected data. The simulated results indicated an improvement in the annual energy balances and a decrease in the time-of-wetness functions as a result of the use of data obtained after the 3-year exposure to the environment. The effects of weathering on both heat and moisture transport and storage parameters of the analyzed bricks and on their hygrothermal performance were found significant despite the occurrence of warm winters in the time period of 2012-2015 when the brick specimens were exposed to the environment.

The association of weather and mortality in Bangladesh from 1983–2009

PubMed Central

Alam, Nurul; Begum, Dilruba; Streatfield, Peter Kim

2012-01-01

Introduction The association of weather and mortality have not been widely studied in subtropical monsoon regions, particularly in Bangladesh. This study aims to assess the association of weather and mortality (measured with temperature and rainfall), adjusting for time trend and seasonal patterns in Abhoynagar, Bangladesh. Material and methods A sample vital registration system (SVRS) was set up in 1982 to facilitate operational research in family planning and maternal and child health. SVRS provided data on death counts and population from 1983–2009. The Bangladesh Meteorological Department provided data on daily temperature and rainfall for the same period. Time series Poisson regression with cubic spline functions was used, allowing for over-dispersion, including lagged weather parameters, and adjusting for time trends and seasonal patterns. Analysis was carried out using R statistical software. Results Both weekly mean temperature and rainfall showed strong seasonal patterns. After adjusting for seasonal pattern and time trend, weekly mean temperatures (lag 0) below the 25th percentile and between the 25th and 75th percentiles were associated with increased mortality risk, particularly in females and adults aged 20–59 years by 2.3–2.4% for every 1°C decrease. Temperature above the 75th percentile did not increase the risk. Every 1 mm increase in rainfall up to 14 mm of weekly average rainfall over lag 0–4 weeks was associated with decreased mortality risks. Rainfall above 14 mm was associated with increased mortality risk. Conclusion The relationships between temperature, rainfall and mortality reveal the importance of understanding the current factors contributing to adaptation and acclimatization, and how these can be enhanced to reduce negative impacts from weather. PMID:23195512

3D Exploration of Meteorological Data: Facing the challenges of operational forecasters

NASA Astrophysics Data System (ADS)

Koutek, Michal; Debie, Frans; van der Neut, Ian

2016-04-01

In the past years the Royal Netherlands Meteorological Institute (KNMI) has been working on innovation in the field of meteorological data visualization. We are dealing with Numerical Weather Prediction (NWP) model data and observational data, i.e. satellite images, precipitation radar, ground and air-borne measurements. These multidimensional multivariate data are geo-referenced and can be combined in 3D space to provide more intuitive views on the atmospheric phenomena. We developed the Weather3DeXplorer (W3DX), a visualization framework for processing and interactive exploration and visualization using Virtual Reality (VR) technology. We managed to have great successes with research studies on extreme weather situations. In this paper we will elaborate what we have learned from application of interactive 3D visualization in the operational weather room. We will explain how important it is to control the degrees-of-freedom during interaction that are given to the users: forecasters/scientists; (3D camera and 3D slicing-plane navigation appear to be rather difficult for the users, when not implemented properly). We will present a novel approach of operational 3D visualization user interfaces (UI) that for a great deal eliminates the obstacle and the time it usually takes to set up the visualization parameters and an appropriate camera view on a certain atmospheric phenomenon. We have found our inspiration in the way our operational forecasters work in the weather room. We decided to form a bridge between 2D visualization images and interactive 3D exploration. Our method combines WEB-based 2D UI's, pre-rendered 3D visualization catalog for the latest NWP model runs, with immediate entry into interactive 3D session for selected visualization setting. Finally, we would like to present the first user experiences with this approach.

Impact of aerosols, dust, water vapor and clouds on fair weather PG and implications for the Carnegie curve

NASA Astrophysics Data System (ADS)

Kourtidis, Konstantinos; Georgoulias, Aristeidis

2017-04-01

We studied the impact of anthropogenic aerosols, fine mode natural aerosols, Saharan dust, atmospheric water vapor, cloud fraction, cloud optical depth and cloud top height on the magnitude of fair weather PG at the rural station of Xanthi. Fair weather PG was measured in situ while the other parameters were obtained from the MODIS instrument onboard the Terra and Aqua satellites. All of the above parameteres were found to impact fair weather PG magnitude. Regarding aerosols, the impact was larger for Saharan dust and fine mode natural aerosols whereas regarding clouds the impact was larger for cloud fraction while less than that of aerosols. Water vapour and ice precipitable water were also found to influence fair weather PG. Since aerosols and water are ubiquitous in the atmosphere and exhibit large spatial and temporal variability, we postulate that our understanding of the Carnegie curve might need revision.

Weathering Characteristics of Wood Plastic Composites Reinforced with Extracted or Delignified Wood Flour

PubMed Central

Chen, Yao; Stark, Nicole M.; Tshabalala, Mandla A.; Gao, Jianmin; Fan, Yongming

2016-01-01

This study investigated weathering performance of an HDPE wood plastic composite reinforced with extracted or delignified wood flour (WF). The wood flour was pre-extracted with three different solvents, toluene/ethanol (TE), acetone/water (AW), and hot water (HW), or sodium chlorite/acetic acid. The spectral properties of the composites before and after artificial weathering under accelerated conditions were characterized by Fourier transform infrared (FTIR) spectroscopy, the surface color parameters were analyzed using colorimetry, and the mechanical properties were determined by a flexural test. Weathering of WPC resulted in a surface lightening and a decrease in wood index (wood/HDPE) and flexural strength. WPCs that were reinforced with delignified wood flour showed higher ΔL* and ΔE* values, together with lower MOE and MOR retention ratios upon weathering when compared to those with non-extracted control and extracted WF. PMID:28773732

Relationships between nocturnal winter road slipperiness, cloud cover and surface temperature

NASA Astrophysics Data System (ADS)

Grimbacher, T.; Schmid, W.

2003-04-01

Ice and Snow are important risks for road traffic. In this study we show several events of slipperiness in Switzerland, mainly caused by rain or snow falling on a frozen surface. Other reasons for slippery conditions are frost or freezing dew in clear nights and nocturnal clearing after precipitation, which goes along with radiative cooling. The main parameters of road weather forecasts are precipitation, cloudiness and surface temperature. Precipitation is well predictable with weather radars and radar nowcasting algorithms. Temperatures are often taken from numerical weather prediction models, but because of changes in cloud cover these model values are inaccurate in terms of predicting the onset of freezing. Cloudiness, especially the advection, formation and dissipation of clouds and their interaction with surface temperatures, is one of the major unsolved problems of road weather forecasts. Cloud cover and the temperature difference between air and surface temperature are important parameters of the radiation balance. In this contribution, we show the relationship between them, proved at several stations all over Switzerland. We found a quadratic correlation coefficient of typically 60% and improved it considering other meteorological parameters like wind speed and surface water. The acquired relationship may vary from one station to another, but we conclude that temperature difference is a signature for nocturnal cloudiness. We investigated nocturnal cloudiness for two cases from winters 2002 and 2003 in the canton of Lucerne in central Switzerland. There, an ultra-dense combination of two networks with together 55 stations within 50x50 km^2 is operated, measuring air and surface temperature, wind and other road weather parameters. With the aid of our equations, temperature differences detected from this network were converted into cloud maps. A comparison between precipitation seen by radar, cloud maps and surface temperatures shows that there are similar structures in all data. Depending on the situation, we also identified additional effects influencing the temperature differences, for instance the advection of could air or the influence of melting heat at or after a snow event. All these findings help to further understand the phenomena, and hence will contribute to a better predictability of winter road slipperiness.

A Generalized Simple Formulation of Convective Adjustment ...

EPA Pesticide Factsheets

Convective adjustment timescale (τ) for cumulus clouds is one of the most influential parameters controlling parameterized convective precipitation in climate and weather simulation models at global and regional scales. Due to the complex nature of deep convection, a prescribed value or ad hoc representation of τ is used in most global and regional climate/weather models making it a tunable parameter and yet still resulting in uncertainties in convective precipitation simulations. In this work, a generalized simple formulation of τ for use in any convection parameterization for shallow and deep clouds is developed to reduce convective precipitation biases at different grid spacing. Unlike existing other methods, our new formulation can be used with field campaign measurements to estimate τ as demonstrated by using data from two different special field campaigns. Then, we implemented our formulation into a regional model (WRF) for testing and evaluation. Results indicate that our simple τ formulation can give realistic temporal and spatial variations of τ across continental U.S. as well as grid-scale and subgrid scale precipitation. We also found that as the grid spacing decreases (e.g., from 36 to 4-km grid spacing), grid-scale precipitation dominants over subgrid-scale precipitation. The generalized τ formulation works for various types of atmospheric conditions (e.g., continental clouds due to heating and large-scale forcing over la

Lithologic composition and rock weathering potential of forested, glacial-till soils

Treesearch

Scott W. Bailey; James W. Hornbeck; James W. Hornbeck

1992-01-01

Describes methods for predicting lithologies present in soils developed on glacial till, and the potential weathering contributions from rock particles >2 mm in diameter. The methods are not quantitative in terms of providing weathering rates, but provide information that can further the understanding of forest nutrient cycles, and possibly assist with decisions...

Impacts from urban water systems on receiving waters - How to account for severe wet-weather events in LCA?

PubMed

Risch, Eva; Gasperi, Johnny; Gromaire, Marie-Christine; Chebbo, Ghassan; Azimi, Sam; Rocher, Vincent; Roux, Philippe; Rosenbaum, Ralph K; Sinfort, Carole

2018-01-01

Sewage systems are a vital part of the urban infrastructure in most cities. They provide drainage, which protects public health, prevents the flooding of property and protects the water environment around urban areas. On some occasions sewers will overflow into the water environment during heavy rain potentially causing unacceptable impacts from releases of untreated sewage into the environment. In typical Life Cycle Assessment (LCA) studies of urban wastewater systems (UWS), average dry-weather conditions are modelled while wet-weather flows from UWS, presenting a high temporal variability, are not currently accounted for. In this context, the loads from several storm events could be important contributors to the impact categories freshwater eutrophication and ecotoxicity. In this study we investigated the contributions of these wet-weather-induced discharges relative to average dry-weather conditions in the life cycle inventory for UWS. In collaboration with the Paris public sanitation service (SIAAP) and Observatory of Urban Pollutants (OPUR) program researchers, this work aimed at identifying and comparing contributing flows from the UWS in the Paris area by a selection of routine wastewater parameters and priority pollutants. This collected data is organized according to archetypal weather days during a reference year. Then, for each archetypal weather day and its associated flows to the receiving river waters (Seine), the parameters of pollutant loads (statistical distribution of concentrations and volumes) were determined. The resulting inventory flows (i.e. the potential loads from the UWS) were used as LCA input data to assess the associated impacts. This allowed investigating the relative importance of episodic wet-weather versus "continuous" dry-weather loads with a probabilistic approach to account for pollutant variability within the urban flows. The analysis at the scale of one year showed that storm events are significant contributors to the impacts of freshwater eutrophication and ecotoxicity compared to those arising from treated effluents. At the rain event scale the wet-weather contributions to these impacts are even more significant, accounting for example for up to 62% of the total impact on freshwater ecotoxicity. This also allowed investigating and discussing the ecotoxicity contribution of each class of pollutants among the broad range of inventoried substances. Finally, with such significant contributions of pollutant loads and associated impacts from wet-weather events, further research is required to better include temporally-differentiated emissions when evaluating eutrophication and ecotoxicity. This will provide a better understanding of how the performance of an UWS system affects the receiving environment for given local weather conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fire occurrence prediction in the Mediterranean: Application to Southern France

NASA Astrophysics Data System (ADS)

Papakosta, Panagiota; Öster, Jan; Scherb, Anke; Straub, Daniel

2013-04-01

The areas that extend in the Mediterranean basin have a long fire history. The climatic conditions of wet winters and long hot drying summers support seasonal fire events, mainly ignited by humans. Extended land fragmentation hinders fire spread, but seasonal winds (e.g. Mistral in South France or Meltemia in Greece) can drive fire events to become uncontrollable fires with severe impacts to humans and the environment [1]. Prediction models in these areas should incorporate both natural and anthropogenic factors. Several indices have been developed worldwide to express fire weather conditions. The Canadian Fire Weather Index (FWI) is currently adapted by many countries in Europe due to the easily observable input weather parameters (temperature, wind speed, relative humidity, precipitation) and the easy-to-implement algorithms of the Canadian formulation describing fuel moisture relations [2],[3]. Human influence can be expressed directly by human presence (e.g. population density) or indirectly by proxy indicators (e.g. street density [4], land cover type). The random nature of fire occurrences and the uncertainties associated with the influencing factors motivate probabilistic prediction models. The aim of this study is to develop a prediction model of fire occurrence probability under natural and anthropogenic influence in Southern France and to compare it with earlier developed predictions in other Mediterranean areas [5]. Fire occurrence is modeled as a Poisson process. Two interpolation methods (Kriging and Inverse Distance Weighting) are used to interpolate daily weather observations from weather stations to a 1 km² spatial grid and their results are compared. Poisson regression estimates the parameters of the model and the resulting daily predictions are provided in terms of maps displaying fire occurrence rates. The model is applied to the regions Provence-Alpes-Côtes D'Azur und Languedoc-Roussillon in the South of France. Weather data are obtained from the German and French Weather Services (Deutscher Wetterdienst and Météo-France). Historical fire events are taken from Prométhée database. Time series 2000-2010 are used as learning data and data from 2011 is used as the validation data. The resulting model can support real-time fire risk estimation for improved allocation of firefighting resources and planning of other mitigation actions. [1] Keeley, J.E.; Bond, W.J.; Bradstock, R.A.; Pausas, J.G.; Rundel, P.W. (2012): Fire in Mediterranean ecosystems: ecology, evolution and management. Cambridge University Press, New York, USA, pp.515 [2] Lawson, B.D.; Armitage, O.B. (2008): Weather Guide for the Canadian Forest Fire Danger Rating System. Natural Resources Canada, Canadian Forest Service, Northern Forestry Centre, Edmonton, Alberta, Canada. [3] Van Wagner, C.E.; Pickett, T.L. (1985): Equations and FORTRAN Program for the Canadian Forest Fire Weather Index System. Forestry Technical Report 33. Canadian Forestry Service, Government of Canada, Ottawa, Ontario, Canada [4] Syphard, A.D.; Radeloff, V.C.; Keuler, N.S.; Taylor, R.S.; Hawbaker, T.J.; Stewart, S.I.; Clayton, M.K. (2008): Predicting spatial patterns of fire on a southern California landscape. International Journal of Wildland Fire, 17, pp.602-613 [5] Papakosta, P.; Klein, F.; König, S.; Straub, D. (2012): Linking spatio-temporal data to the Fire Weather Index to estimate the probability of wildfire in the Mediterranean. Geophysical Research Abstracts, Vol.14, EGU2012-12737, EGU General Assembly 2012

On the interest of combining an analog model to a regression model for the adaptation of the downscaling link. Application to probabilistic prediction of precipitation over France.

NASA Astrophysics Data System (ADS)

Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

2016-04-01

Scenarios of surface weather required for the impact studies have to be unbiased and adapted to the space and time scales of the considered hydro-systems. Hence, surface weather scenarios obtained from global climate models and/or numerical weather prediction models are not really appropriated. Outputs of these models have to be post-processed, which is often carried out thanks to Statistical Downscaling Methods (SDMs). Among those SDMs, approaches based on regression are often applied. For a given station, a regression link can be established between a set of large scale atmospheric predictors and the surface weather variable. These links are then used for the prediction of the latter. However, physical processes generating surface weather vary in time. This is well known for precipitation for instance. The most relevant predictors and the regression link are also likely to vary in time. A better prediction skill is thus classically obtained with a seasonal stratification of the data. Another strategy is to identify the most relevant predictor set and establish the regression link from dates that are similar - or analog - to the target date. In practice, these dates can be selected thanks to an analog model. In this study, we explore the possibility of improving the local performance of an analog model - where the analogy is applied to the geopotential heights 1000 and 500 hPa - using additional local scale predictors for the probabilistic prediction of the Safran precipitation over France. For each prediction day, the prediction is obtained from two GLM regression models - for both the occurrence and the quantity of precipitation - for which predictors and parameters are estimated from the analog dates. Firstly, the resulting combined model noticeably allows increasing the prediction performance by adapting the downscaling link for each prediction day. Secondly, the selected predictors for a given prediction depend on the large scale situation and on the considered region. Finally, even with such an adaptive predictor identification, the downscaling link appears to be robust: for a same prediction day, predictors selected for different locations of a given region are similar and the regression parameters are consistent within the region of interest.

Quantitative Morphologic Analysis of Boulder Shape and Surface Texture to Infer Environmental History: A Case Study of Rock Breakdown at the Ephrata Fan, Channeled Scabland, Washington

NASA Technical Reports Server (NTRS)

Ehlmann, Bethany L.; Viles, Heather A.; Bourke, Mary C.

2008-01-01

Boulder morphology reflects both lithology and climate and is dictated by the combined effects of erosion, transport, and weathering. At present, morphologic information at the boulder scale is underutilized as a recorder of environmental processes, partly because of the lack of a systematic quantitative parameter set for reporting and comparing data sets. We develop such a parameter set, incorporating a range of measures of boulder form and surface texture. We use standard shape metrics measured in the field and fractal and morphometric classification methods borrowed from landscape analysis and applied to laser-scanned molds. The parameter set was pilot tested on three populations of basalt boulders with distinct breakdown histories in the Channeled Scabland, Washington: (1) basalt outcrop talus; (2) flood-transported boulders recently excavated from a quarry; and (3) flood-transported boulders, extensively weathered in situ on the Ephrata Fan surface. Size and shape data were found to distinguish between flood-transported and untransported boulders. Size and edge angles (approximately 120 degrees) of flood-transported boulders suggest removal by preferential fracturing along preexisting columnar joints, and curvature data indicate rounding relative to outcrop boulders. Surface textural data show that boulders which have been exposed at the surface are significantly rougher than those buried by fan sediments. Past signatures diagnostic of flood transport still persist on surface boulders, despite ongoing overprinting by processes in the present breakdown environment through roughening and fracturing in situ. Further use of this quantitative boulder parameter set at other terrestrial and planetary sites will aid in cataloging and understanding morphologic signatures of environmental processes.

Measuring weather for aviation safety in the 1980's

NASA Technical Reports Server (NTRS)

Wedan, R. W.

1980-01-01

Requirements for an improved aviation weather system are defined and specifically include the need for (1) weather observations at all airports with instrument approaches, (2) more accurate and timely radar detection of weather elements hazardous to aviation, and (3) better methods of timely distribution of both pilot reports and ground weather data. The development of the discrete address beacon system data link, Doppler weather radar network, and various information processing techniques are described.

Prediction of Weather Impacted Airport Capacity using Ensemble Learning

NASA Technical Reports Server (NTRS)

Wang, Yao Xun

2011-01-01

Ensemble learning with the Bagging Decision Tree (BDT) model was used to assess the impact of weather on airport capacities at selected high-demand airports in the United States. The ensemble bagging decision tree models were developed and validated using the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) data and weather forecast at these airports. The study examines the performance of BDT, along with traditional single Support Vector Machines (SVM), for airport runway configuration selection and airport arrival rates (AAR) prediction during weather impacts. Testing of these models was accomplished using observed weather, weather forecast, and airport operation information at the chosen airports. The experimental results show that ensemble methods are more accurate than a single SVM classifier. The airport capacity ensemble method presented here can be used as a decision support model that supports air traffic flow management to meet the weather impacted airport capacity in order to reduce costs and increase safety.

Annual incidence of mortality related to hypertensive disease in Canada and associations with heliophysical parameters.

PubMed

Caswell, Joseph M; Carniello, Trevor N; Murugan, Nirosha J

2016-01-01

Increasing research into heliobiology and related fields has revealed a myriad of potential relationships between space weather factors and terrestrial biology. Additionally, many studies have indicated cyclicity in incidence of various diseases along with many aspects of cardiovascular function. The current study examined annual mortality associated with hypertensive diseases in Canada from 1979 to 2009 for periodicities and linear relationships with a range of heliophysical parameters. Analyses indicated a number of significant lagged correlations between space weather and hypertensive mortality, with solar wind plasma beta identified as the likely source of these relationships. Similar periodicities were observed for geomagnetic activity and hypertensive mortality. A significant rhythm was revealed for hypertensive mortality centered on a 9.6-year cycle length, while geomagnetic activity was fit with a 10.1-year cycle. Cross-correlograms of mortality with space weather demonstrated a 10.67-year periodicity coinciding with the average 10.6-year solar cycle length for the time period examined. Further quantification and potential implications are discussed.

Scatterometer capabilities in remotely sensing geophysical parameters over the ocean: The status and the possibilities

NASA Technical Reports Server (NTRS)

Brown, R. A.

1984-01-01

Extensive comparison between surface measurements and satellite Scatt signal and predicted winds show successful wind and weather analysis comparable with conventional weather service analyses. However, in regions often of the most interest, e.g., fronts and local storms, inadequacies in the latter fields leaves an inability to establish the satellite sensor capabilities. Thus, comparisons must be made between wind detecting measurements and other satellite measurements of clouds, moisture, waves or any other parameter which responds to sharp gradients in the wind. At least for the windfields and the derived surface pressure field analysis, occasional surface measurements are required to anchor and monitor the satellite analyses. Their averaging times must be made compatible with the satellite sensor measurement. Careful attention must be paid to the complex fields which contain many scales of turbulence and coherent structures affecting the averaging process. The satellite microwave system is capable of replacing the conventional point observation/numerical analysis for the ocean weather.

Annual incidence of mortality related to hypertensive disease in Canada and associations with heliophysical parameters

NASA Astrophysics Data System (ADS)

Caswell, Joseph M.; Carniello, Trevor N.; Murugan, Nirosha J.

2016-01-01

Increasing research into heliobiology and related fields has revealed a myriad of potential relationships between space weather factors and terrestrial biology. Additionally, many studies have indicated cyclicity in incidence of various diseases along with many aspects of cardiovascular function. The current study examined annual mortality associated with hypertensive diseases in Canada from 1979 to 2009 for periodicities and linear relationships with a range of heliophysical parameters. Analyses indicated a number of significant lagged correlations between space weather and hypertensive mortality, with solar wind plasma beta identified as the likely source of these relationships. Similar periodicities were observed for geomagnetic activity and hypertensive mortality. A significant rhythm was revealed for hypertensive mortality centered on a 9.6-year cycle length, while geomagnetic activity was fit with a 10.1-year cycle. Cross-correlograms of mortality with space weather demonstrated a 10.67-year periodicity coinciding with the average 10.6-year solar cycle length for the time period examined. Further quantification and potential implications are discussed.

Effect of processing method on surface and weathering characteristics of wood-flour/HDPE composites

Treesearch

Nicole M. Stark; Laurent M. Matuana; Craig M. Clemons

2004-01-01

Wood-plastic lumber is promoted as a low maintenance high-durability product. When exposed to accelerated weathering, however, wood-plastic composites may experience a color change and/or loss in mechanical properties. Different methods of manufacturing wood-plastic composites lead to different surface characteristics, which can influence weathering, In this study, 50...

Effect of processing method on accelerated weathering of wood-flour/HDPE composites

Treesearch

Nicole M. Stark; Laurent M. Matuana; Craig M. Clemons

2003-01-01

Wood-plastic lumber is promoted as a low maintenance high-durability product. When exposed to accelerated weathering, however, wood-plastic composites may experience a color change and/or loss in mechanical properties. Different methods of manufacturing wood-plastic composites lead to different surface characteristics, which can influence weathering, In this study, 50...

Determination of HCME 3-D parameters using a full ice-cream cone model

NASA Astrophysics Data System (ADS)

Na, Hyeonock; Moon, Yong-Jae; Lee, Harim

2016-05-01

It is very essential to determine three dimensional parameters (e.g., radial speed, angular width, source location) of Coronal Mass Ejections (CMEs) for space weather forecast. Several cone models (e.g., an elliptical cone model, an ice-cream cone model, an asymmetric cone model) have been examined to estimate these parameters. In this study, we investigate which cone type is close to a halo CME morphology using 26 CMEs: halo CMEs by one spacecraft (SOHO or STEREO-A or B) and as limb CMEs by the other ones. From cone shape parameters of these CMEs such as their front curvature, we find that near full ice-cream cone type CMEs are much closer to observations than shallow ice-cream cone type CMEs. Thus we develop a new cone model in which a full ice-cream cone consists of many flat cones with different heights and angular widths. This model is carried out by the following steps: (1) construct a cone for given height and angular width, (2) project the cone onto the sky plane, (3) select points comprising the outer boundary, and (4) minimize the difference between the estimated projection speeds with the observed ones. By applying this model to 12 SOHO/LASCO halo CMEs, we find that 3-D parameters from our method are similar to those from other stereoscopic methods (a geometrical triangulation method and a Graduated Cylindrical Shell model) based on multi-spacecraft data. We are developing a general ice-cream cone model whose front shape is a free parameter determined by observations.

Generating Dynamic Persistence in the Time Domain

NASA Astrophysics Data System (ADS)

Guerrero, A.; Smith, L. A.; Smith, L. A.; Kaplan, D. T.

2001-12-01

Many dynamical systems present long-range correlations. Physically, these systems vary from biological to economical, including geological or urban systems. Important geophysical candidates for this type of behaviour include weather (or climate) and earthquake sequences. Persistence is characterised by slowly decaying correlation function; that, in theory, never dies out. The Persistence exponent reflects the degree of memory in the system and much effort has been expended creating and analysing methods that successfully estimate this parameter and model data that exhibits persistence. The most widely used methods for generating long correlated time series are not dynamical systems in the time domain, but instead are derived from a given spectral density. Little attention has been drawn to modelling persistence in the time domain. The time domain approach has the advantage that an observation at certain time can be calculated using previous observations which is particularly suitable when investigating the predictability of a long memory process. We will describe two of these methods in the time domain. One is a traditional approach using fractional ARIMA (autoregressive and moving average) models; the second uses a novel approach to extending a given series using random Fourier basis functions. The statistical quality of the two methods is compared, and they are contrasted with weather data which shows, reportedly, persistence. The suitability of this approach both for estimating predictability and for making predictions is discussed.

Application of troposphere model from NWP and GNSS data into real-time precise positioning

NASA Astrophysics Data System (ADS)

Wilgan, Karina; Hadas, Tomasz; Kazmierski, Kamil; Rohm, Witold; Bosy, Jaroslaw

2016-04-01

The tropospheric delay empirical models are usually functions of meteorological parameters (temperature, pressure and humidity). The application of standard atmosphere parameters or global models, such as GPT (global pressure/temperature) model or UNB3 (University of New Brunswick, version 3) model, may not be sufficient, especially for positioning in non-standard weather conditions. The possible solution is to use regional troposphere models based on real-time or near-real time measurements. We implement a regional troposphere model into the PPP (Precise Point Positioning) software GNSS-WARP (Wroclaw Algorithms for Real-time Positioning) developed at Wroclaw University of Environmental and Life Sciences. The software is capable of processing static and kinematic multi-GNSS data in real-time and post-processing mode and takes advantage of final IGS (International GNSS Service) products as well as IGS RTS (Real-Time Service) products. A shortcoming of PPP technique is the time required for the solution to converge. One of the reasons is the high correlation among the estimated parameters: troposphere delay, receiver clock offset and receiver height. To efficiently decorrelate these parameters, a significant change in satellite geometry is required. Alternative solution is to introduce the external high-quality regional troposphere delay model to constrain troposphere estimates. The proposed model consists of zenith total delays (ZTD) and mapping functions calculated from meteorological parameters from Numerical Weather Prediction model WRF (Weather Research and Forecasting) and ZTDs from ground-based GNSS stations using the least-squares collocation software COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays) developed at ETH Zurich.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters

USGS Publications Warehouse

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters.

PubMed

Grisham, Blake A; Boal, Clint W; Haukos, David A; Davis, Dawn M; Boydston, Kathy K; Dixon, Charles; Heck, Willard R

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

Uncertainty Comparison of Visual Sensing in Adverse Weather Conditions†

PubMed Central

Lo, Shi-Wei; Wu, Jyh-Horng; Chen, Lun-Chi; Tseng, Chien-Hao; Lin, Fang-Pang; Hsu, Ching-Han

2016-01-01

This paper focuses on flood-region detection using monitoring images. However, adverse weather affects the outcome of image segmentation methods. In this paper, we present an experimental comparison of an outdoor visual sensing system using region-growing methods with two different growing rules—namely, GrowCut and RegGro. For each growing rule, several tests on adverse weather and lens-stained scenes were performed, taking into account and analyzing different weather conditions with the outdoor visual sensing system. The influence of several weather conditions was analyzed, highlighting their effect on the outdoor visual sensing system with different growing rules. Furthermore, experimental errors and uncertainties obtained with the growing rules were compared. The segmentation accuracy of flood regions yielded by the GrowCut, RegGro, and hybrid methods was 75%, 85%, and 87.7%, respectively. PMID:27447642

Advancing land surface model development with satellite-based Earth observations

NASA Astrophysics Data System (ADS)

Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

2017-04-01

The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

Accelerated Weathering of Waste Glass at 90°C with the Pressurized Unsaturated Flow (PUF) Apparatus: Implications for Predicting Glass Corrosion with a Reactive Transport Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pierce, Eric M.; Bacon, Diana H.

2009-09-21

The interest in the long-term durability of waste glass stems from the need to predict radionuclide release rates from the corroding glass over geologic time-scales. Several long-term test methods have been developed to accelerate the glass-water reaction [drip test, vapor hydration test, product consistency test-B, and pressurized unsaturated flow (PUF)]. Currently, the PUF test is the only method that can mimic the unsaturated hydraulic properties expected in a subsurface disposal facility and simultaneously monitor the glass-water reaction. PUF tests are being conducted to accelerate the weathering of glass and validate the model parameters being used to predict long-term glass behavior.more » One dimensional reactive chemical transport simulations of glass dissolution and secondary phase formation during a 1.5-year long PUF experiment was conducted with the subsurface transport over reactive multi-phases (STORM) code. Results show that parameterization of the computer model by combining direct laboratory measurements and thermodynamic data provides an integrated approach to predicting glass behavior over geologic-time scales.« less

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

NASA Astrophysics Data System (ADS)

Stromqvist Vetelino, Frida; Borbath, Michael R.; Andrews, Larry C.; Phillips, Ronald L.; Burdge, Geoffrey L.; Chin, Peter G.; Galus, Darren J.; Wayne, David; Pescatore, Robert; Cowan, Doris; Thomas, Frederick

2005-08-01

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.

Association of global weather changes with acute coronary syndromes: gaining insights from clinical trials data

NASA Astrophysics Data System (ADS)

Bakal, Jeffrey A.; Ezekowitz, Justin A.; Westerhout, Cynthia M.; Boersma, Eric; Armstrong, Paul W.

2013-05-01

The aim of this study was to develop a method for the identification of global weather parameters and patient characteristics associated with a type of heart attack in which there is a sudden partial blockage of a coronary artery. This type of heart attack does not demonstrate an elevation of the ST segment on an electrocardiogram and is defined as a non-ST elevation acute coronary syndrome (NSTE-ACS). Data from the Global Summary of the Day database was linked with the enrollment and baseline data for a phase III international clinical trial in NSTE-ACS in four 48-h time periods covering the week prior to the clinical event that prompted enrollment in the study. Meteorological events were determined by standardizing the weather data from enrollment dates against an empirical distribution from the month prior. These meteorological events were then linked to the patients' geographic region, demographics and comorbidities to identify potential susceptible populations. After standardization, changes in temperature and humidity demonstrated an association with the enrollment event. Additionally there appeared to be an association with gender, region and a history of stroke. This methodology may provide a useful global insight into assessing the biometeorologic component of diseases from international data.

Disentangling oil weathering using GC x GC. 2. Mass transfer calculations.

PubMed

Arey, J Samuel; Nelson, Robert K; Plata, Desiree L; Reddy, Christopher M

2007-08-15

Hydrocarbon mass transfers to the atmosphere and water column drive the early weathering of oil spills and also control the chemical exposures of many coastal wildlife species. However, in the field, mass transfer rates of individual hydrocarbons to air and water are often uncertain. In the Part 1 companion to this paper, we used comprehensive two-dimensional gas chromatography (GC x GC) to identify distinct signatures of evaporation and dissolution encoded in the compositional evolution of weathered oils. In Part 2, we further investigate patterns of mass removal in GC x GC chromatograms using a mass transfer model. The model was tailored to conditions at a contaminated beach on Buzzards Bay, MA, after the 2003 Bouchard 120 oil spill. The model was applied to all resolved hydrocarbon compounds in the C11-C24 boiling range, based on their GC x GC-estimated vapor pressures and aqueous solubilities. With no fitted parameters, the model successfully predicted GC x GC chromatogram patterns of mass removal associated with evaporation, water-washing, and diffusion-limited transport. This enabled a critical field evaluation of the mass transfer model and also allowed mass apportionment estimates of hundreds of individual hydrocarbon compounds to air and water. Ultimately, this method should improve assessments of wildlife exposures to oil spill hydrocarbons.

Relationship of EUV Irradiance Coronal Dimming Slope and Depth to Coronal Mass Ejection Speed and Mass

NASA Technical Reports Server (NTRS)

Mason, James Paul; Woods, Thomas N.; Webb, David F.; Thompson, Barbara J.; Colaninno, Robin C.; Vourlidas, Angelos

2016-01-01

Extreme ultraviolet (EUV) coronal dimmings are often observed in response to solar eruptive events. These phenomena can be generated via several different physical processes. For space weather, the most important of these is the temporary void left behind by a coronal mass ejection (CME). Massive, fast CMEs tend to leave behind a darker void that also usually corresponds to minimum irradiance for the cooler coronal emissions. If the dimming is associated with a solar are, as is often the case, the are component of the irradiance light curve in the cooler coronal emission can be isolated and removed using simultaneous measurements of warmer coronal lines. We apply this technique to 37dimming events identified during two separate two-week periods in 2011, plus an event on 2010 August 7 analyzed in a previous paper, to parameterize dimming in terms of depth and slope. We provide statistics on which combination of wavelengths worked best for the flare-removal method, describe the fitting methods applied to the dimming light curves, and compare the dimming parameters with corresponding CME parameters of mass and speed. The best linear relationships found are nu(sub CME) [km/s] approx. equals 2.36 x 10 6 [km/%] x s(sub dim) [%/s] m(sub CME) [g] approx. equals 2.59 x 10(exp.15 [g/%] x the square root of d(sub dim) [%].These relationships could be used for space weather operations of estimating CME mass and speed using near-real-time irradiance dimming measurements.

Weathering trend characterization of medium-molecular weight polycyclic aromatic disulfur heterocycles by Fourier transform ion cyclotron resonance mass spectrometry.

PubMed

Hegazi, Abdelrahman H; Fathalla, Eiman M; Andersson, Jan T

2014-09-01

Different weathering factors act to change petroleum composition once it is spilled into the environment. n-Alkanes, biomarkers, low-molecular weight polyaromatic hydrocarbons and sulfur heterocycles compositional changing in the environment have been extensively studied by different researchers and many parameters have been used for oil source identification and monitoring of weathering and biological degradation processes. In this work, we studied the fate of medium-molecular weight polycyclic aromatic disulfur heterocycles (PAS2Hs), up to ca. 900Da, of artificially weathered Flotta North Sea crude oil by ultra high-resolution Fourier transform ion cyclotron resonance mass spectrometry. It was found that PAS2Hs in studied crude oil having double bond equivalents (DBE) from 5 to 8 with a mass range from ca 316 to 582Da were less influenced even after six months artificial weathering experiment. However, compounds having DBEs 12, 11 and 10 were depleted after two, four and six months weathering, respectively. In addition, DBE 9 series was more susceptible to weathering than those of DBE 7 and 8. Copyright © 2014 Elsevier Ltd. All rights reserved.

A resampling procedure for generating conditioned daily weather sequences

USGS Publications Warehouse

Clark, Martyn P.; Gangopadhyay, Subhrendu; Brandon, David; Werner, Kevin; Hay, Lauren E.; Rajagopalan, Balaji; Yates, David

2004-01-01

A method is introduced to generate conditioned daily precipitation and temperature time series at multiple stations. The method resamples data from the historical record “nens” times for the period of interest (nens = number of ensemble members) and reorders the ensemble members to reconstruct the observed spatial (intersite) and temporal correlation statistics. The weather generator model is applied to 2307 stations in the contiguous United States and is shown to reproduce the observed spatial correlation between neighboring stations, the observed correlation between variables (e.g., between precipitation and temperature), and the observed temporal correlation between subsequent days in the generated weather sequence. The weather generator model is extended to produce sequences of weather that are conditioned on climate indices (in this case the Niño 3.4 index). Example illustrations of conditioned weather sequences are provided for a station in Arizona (Petrified Forest, 34.8°N, 109.9°W), where El Niño and La Niña conditions have a strong effect on winter precipitation. The conditioned weather sequences generated using the methods described in this paper are appropriate for use as input to hydrologic models to produce multiseason forecasts of streamflow.

Performance of the Hydrological Portion of a Simple Water Quality Model in Different Climatic Regions

NASA Astrophysics Data System (ADS)

Moore, K.; Pierson, D.; Pettersson, K.; Naden, P.; Allott, N.; Jennings, E.; Tamm, T.; Järvet, A.; Nickus, U.; Thies, H.; Arvola, L.; Järvinen, M.; Schneiderman, E.; Zion, M.; Lounsbury, D.

2004-05-01

We are applying an existing watershed model in the EU CLIME (Climate and Lake Impacts in Europe) project to evaluate the effects of weather on seasonal and annual delivery of N, P, and DOC to lakes. Model calibration is based on long-term records of weather and water quality data collected from sites in different climatic regions spread across Europe and in New York State. The overall aim of the CLIME project is to develop methods and models to support lake and catchment management under current climate conditions and make predictions under future climate scenarios. Scientists from 10 partner countries are collaborating on developing a consistent approach to defining model parameters for the Generalized Watershed Loading Functions (GWLF) model, one of a larger suite of models used in the project. An example of the approach for the hydrological portion of the GWLF model will be presented, with consideration of the balance between model simplicity, ease of use, data requirements, and realistic predictions.

[Influence of weather in the incidence of acute myocardial infarction in Galicia (Spain)].

PubMed

Fernández-García, José Manuel; Dosil Díaz, Olga; Taboada Hidalgo, Juan José; Fernández, José Ramón; Sánchez-Santos, Luis

2015-08-07

To assess the interactions between weather and the impact of each individual meteorological parameters in the incidence of acute myocardial infarctions (AMI) in Galicia. Retrospective study analyzing the number of AMI diagnosed and transferred to the hospital by the Emergencies Sanitary System of Galicia between 2002 and 2009. We included patients with clinical and ECG findings of AMI. The correlation between 10-minute meteorological variables (temperature, humidity, pressure, accumulated rainfall and wind speed) recorded by MeteoGalicia and the incidence of AMI was assessed. A total of 4,717 AMI were registered (72.8% men, 27.2% women). No seasonal variations were found. No significant correlations were detected with regard to average daily temperature (P=.683) or wind speed (P=.895). Correlation between atmospheric pressure and incidence of AMI was significant (P<.005), as well as with the daily relative humidity average (P=.005). Our study showed a statistical significant association with atmospheric pressure and with the daily relative humidity average. Since the local conditions of weather are widely variable, future studies should establish the relationship between weather patterns (including combinations of meteorological parameters), rather than seasonal variations, and the incidence of AMI. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids

PubMed Central

Ali, S. M.; Mehmood, C. A; Khan, B.; Jawad, M.; Farid, U; Jadoon, J. K.; Ali, M.; Tareen, N. K.; Usman, S.; Majid, M.; Anwar, S. M.

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion. PMID:27314229

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids.

PubMed

Ali, S M; Mehmood, C A; Khan, B; Jawad, M; Farid, U; Jadoon, J K; Ali, M; Tareen, N K; Usman, S; Majid, M; Anwar, S M

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion.

Utilization of GPS Tropospheric Delays for Climate Research

NASA Astrophysics Data System (ADS)

Suparta, Wayan

2017-05-01

The tropospheric delay is one of the main error sources in Global Positioning Systems (GPS) and its impact plays a crucial role in near real-time weather forecasting. Accessibility and accurate estimation of this parameter are essential for weather and climate research. Advances in GPS application has allowed the measurements of zenith tropospheric delay (ZTD) in all weather conditions and on a global scale with fine temporal and spatial resolution. In addition to the rapid advancement of GPS technology and informatics and the development of research in the field of Earth and Planetary Sciences, the GPS data has been available free of charge. Now only required sophisticated processing techniques but user friendly. On the other hand, the ZTD parameter obtained from the models or measurements needs to be converted into precipitable water vapor (PWV) to make it more useful as a component of weather forecasting and analysis atmospheric hazards such as tropical storms, flash floods, landslide, pollution, and earthquake as well as for climate change studies. This paper addresses the determination of ZTD as a signal error or delay source during the propagation from the satellite to a receiver on the ground and is a key driving force behind the atmospheric events. Some results in terms of ZTD and PWV will be highlighted in this paper.

Modeling High-Impact Weather and Climate: Lessons From a Tropical Cyclone Perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Done, James; Holland, Greg; Bruyere, Cindy

2013-10-19

Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding of the underlying physical processes. This challenge is driving fresh approaches to assess high-impact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias inmore » the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be guided by the need to: include relevant regional climate physical processes; resolve key impact parameters; and to accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters. Finally, through the example of a tropical cyclone damage index, direct impact assessments are resented as powerful tools that distill complex datasets into concise statements on likely impact, and as highly effective communication devices.« less

Enhancing the Awareness of the Interaction of the Space Weather and Public: Some Case Studies in Turkey

NASA Astrophysics Data System (ADS)

Tulunay, Y.; Tulunay, E.; Kocabas, Z.; Altuntas, E.; Yapici, T.; Senalp, E. T.; Hippler, R.

2009-04-01

Space Weather has important effects on many systems and peripherals that human interacts with. However, most of the people are not aware of those interactions. During the FP6 SWEETS, COST 724 and the ‘I love my Sun' activities it was aimed to create basis to bring together academicians from universities, experts from industry, scientific institutes, and the public, especially the school children of age 7-11, in order to enhance the awareness of space weather effects and to discuss appropriate countermeasures by different education and promotion methods including non-technical ones. This work mentions the activities performed in Turkey within the framework. Since 1990, a small group at METU has been developing data driven models in order to forecast some critical system parameters related with the near-Earth space processes. With the background on the subject the group feels responsible to organise activities in Turkey to inform public on enhancing the awareness of space weather effects. In order to inform and educate public on their interaction with the Space Weather, distinct social activities which take quick and strong attention were organised. Those include art shows and workshops, quizes, movies and entertainments, special programs for school children of age 7-11 under the ‘I love my Sun' activities, press releases, audio-visual media including webpages [Tulunay, 2007]. The impact of the activities can be evaluated considering the before and after activity record materials of the participants. For instance, under the ‘I love my Sun' activities, the school children drew pictures related with Sun before and after the informative programs. The performance of reaching the school children on the subject is very promising. Sub-activities conducted under the action are: 1. Space Weather Dance Show "Sonnensturm" 2. Web Quiz all over Europe: In Türkiye 3. Space Weather / Sun / Heliospheric Public Science Festivals in 27 Countries: In Türkiye 4. Space Weather on Tour-Mobile Bus 5. Rocket / balloon launch participation for European web quiz winner and journalists 6. Space Weather / Solar / Aurora / Rocket / Balloon movie production for TV 7. Space Weather / Sun /Heliospheric public science festival & public fair in Schwerin castle (main SWEETS festival during ESW 2007) 8. Space Weather telescope video link with Australian (Antarctic Mawson station) and Japanese locations for Schwerin castle festival (no. 7 deliverable) 9. Space Weather planetarium show in Poland, Finland, France and Portugal (4 new languages) 10. Updated Space Weather / Solar CD-Rom / DVD in 7 new languages, poster / flyer 11. Cosmic ray spark chambers 12. Space Weather storm forecast map 13. Mirror system for solar movie 14. FP6 SWEETS / IHY / COST 724 Case Sub-project: "I LOVE MY SUN" (An outreach Activity in Turkey: The Space Weather and the Sun as conceived by the School Children of age 7-11) 15. Press Releases 16. FP6 SWEETS Related Art 17. Turkish Translations in IHY and COST webpages 18. Impact of the SWEETS References Tulunay Y. (2007), FP6 SWEETS (SSA) Activity Report of the Participant No. 16: the METU in Ankara, Türkiye, 31 December 2007, www.ae.metu.edu.tr/~cost.

Introduction of the Mobile Platform for the Meteorological Observations in Seoul Metropolitan City of Korea

NASA Astrophysics Data System (ADS)

Baek, K. T.; Lee, S.; Kang, M.; Lee, G.

2016-12-01

Traffic accidents due to adverse weather such as fog, heavy rainfall, flooding and road surface freezing have been increasing in Korea. To reduce damages caused by the severe weather on the road, a forecast service of combined real-time road-wise weather and the traffic situation is required. Conventional stationary meteorological observations in sparse location system are limited to observe the detailed road environment. For this reason, a mobile meteorological observation platform has been coupled in Weather Information Service Engine (WISE) which is the prototype of urban-scale high resolution weather prediction system in Seoul metropolitan area of Korea in early August 2016. The instruments onboard are designed to measure 15 meteorological parameters; pressure, temperature, relative humidity, precipitation, up/down net radiation, up/down longwave radiation, up/down shortwave radiation, road surface condition, friction coefficient, water depth, wind direction and speed. The observations from mobile platform show a distinctive advantage of data collection in need for road conditions and inputs for the numerical forecast model. In this study, we introduce and examine the feasibility of mobile observations in urban weather prediction and applications.

A Framework to Understand Extreme Space Weather Event Probability.

PubMed

Jonas, Seth; Fronczyk, Kassandra; Pratt, Lucas M

2018-03-12

An extreme space weather event has the potential to disrupt or damage infrastructure systems and technologies that many societies rely on for economic and social well-being. Space weather events occur regularly, but extreme events are less frequent, with a small number of historical examples over the last 160 years. During the past decade, published works have (1) examined the physical characteristics of the extreme historical events and (2) discussed the probability or return rate of select extreme geomagnetic disturbances, including the 1859 Carrington event. Here we present initial findings on a unified framework approach to visualize space weather event probability, using a Bayesian model average, in the context of historical extreme events. We present disturbance storm time (Dst) probability (a proxy for geomagnetic disturbance intensity) across multiple return periods and discuss parameters of interest to policymakers and planners in the context of past extreme space weather events. We discuss the current state of these analyses, their utility to policymakers and planners, the current limitations when compared to other hazards, and several gaps that need to be filled to enhance space weather risk assessments. © 2018 Society for Risk Analysis.

Optimizing Placement of Weather Stations: Exploring Objective Functions of Meaningful Combinations of Multiple Weather Variables

NASA Astrophysics Data System (ADS)

Snyder, A.; Dietterich, T.; Selker, J. S.

2017-12-01

Many regions of the world lack ground-based weather data due to inadequate or unreliable weather station networks. For example, most countries in Sub-Saharan Africa have unreliable, sparse networks of weather stations. The absence of these data can have consequences on weather forecasting, prediction of severe weather events, agricultural planning, and climate change monitoring. The Trans-African Hydro-Meteorological Observatory (TAHMO.org) project seeks to address these problems by deploying and operating a large network of weather stations throughout Sub-Saharan Africa. To design the TAHMO network, we must determine where to place weather stations within each country. We should consider how we can create accurate spatio-temporal maps of weather data and how to balance the desired accuracy of each weather variable of interest (precipitation, temperature, relative humidity, etc.). We can express this problem as a joint optimization of multiple weather variables, given a fixed number of weather stations. We use reanalysis data as the best representation of the "true" weather patterns that occur in the region of interest. For each possible combination of sites, we interpolate the reanalysis data between selected locations and calculate the mean average error between the reanalysis ("true") data and the interpolated data. In order to formulate our multi-variate optimization problem, we explore different methods of weighting each weather variable in our objective function. These methods include systematic variation of weights to determine which weather variables have the strongest influence on the network design, as well as combinations targeted for specific purposes. For example, we can use computed evapotranspiration as a metric that combines many weather variables in a way that is meaningful for agricultural and hydrological applications. We compare the errors of the weather station networks produced by each optimization problem formulation. We also compare these errors to those of manually designed weather station networks in West Africa, planned by the respective host-country's meteorological agency.

How to introduce climate change into extreme precipitation predetermination? First attempts to tamper with the MEWP method.

NASA Astrophysics Data System (ADS)

Gérardin, Maxime; Brigode, Pierre; Bernardara, Pietro; Gailhard, Joël; Garçon, Rémy; Paquet, Emmanuel; Ribstein, Pierre

2013-04-01

The MEWP (Multi-Exponential Weather Pattern, Garavaglia et al. 2010) distribution is part of the operational method in use at EDF (Electricité de France) for computing dam spillways design floods, i.e. the magnitude of the flood that occurs at a given return period. The return periods of interest lie in the 100 - 10,000 years range. Relying on a purposely-designed classification of atmospheric circulations into weather patterns, and assigning a catchment-specific asymptotical coefficient to each of these patterns, the MEWP distribution provides the daily areal rainfall as a function of the return period. In its current state, the method relies on the implicit assumption of climate stationnarity. In this work we seek to introduce climate change into the MEWP framework. Since the MEWP distribution basically contains two sorts of parameters, namely frequencies of the weather patterns, and magnitudes of the events occurring within each of these patterns, we examine the plausible evolution of these two sets of parameters under climate change, and the sensitivity of the final result to these two sorts of changes. On the one hand, the future frequencies are assessed thanks to GCM outputs from CMIP5, and significant, albeit not greater than the internal variability, changes are observed. On the other hand, the future magnitudes can be suspected to follow the Clausius-Clapeyron relationship (e.g. Pall et al., 2007, and Lenderink et van Meijgaard, 2008). We assess the validity of this hypothesis on the observed daily areal precipitation series for more than a hundred catchments in France. The sensitivity analysis shows that, for the return periods at stake, the impact of frequency changes is small relative to that of magnitude changes, while this would not be true for smaller return periods. Therefore, we propose to incorporate climate change into the MEWP distribution in a simple but realistic way, by taking account of the magnitude change only. We conclude with some insights into the next steps that will allow a more sophisticated representation of climate change in the MEWP distribution. References: Garavaglia, F., J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara. 2010. "Introducing a Rainfall Compound Distribution Model Based on Weather Patterns Sub-sampling." Hydrology and Earth System Sciences 14 (6): 951-964. doi:10.5194/hess-14-951-2010. Lenderink, Geert, and Erik van Meijgaard. 2008. "Increase in Hourly Precipitation Extremes Beyond Expectations from Temperature Changes." Nature Geoscience 1 (8) (July 20): 511-514. doi:10.1038/ngeo262. Pall, P., MR Allen, and DA Stone. 2007. "Testing the Clausius-Clapeyron Constraint on Changes in Extreme Precipitation Under CO 2 Warming." Climate Dynamics 28 (4): 351-363.

Space Weather Forecasting at IZMIRAN

NASA Astrophysics Data System (ADS)

Gaidash, S. P.; Belov, A. V.; Abunina, M. A.; Abunin, A. A.

2017-12-01

Since 1998, the Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation (IZMIRAN) has had an operating heliogeophysical service—the Center for Space Weather Forecasts. This center transfers the results of basic research in solar-terrestrial physics into daily forecasting of various space weather parameters for various lead times. The forecasts are promptly available to interested consumers. This article describes the center and the main types of forecasts it provides: solar and geomagnetic activity, magnetospheric electron fluxes, and probabilities of proton increases. The challenges associated with the forecasting of effects of coronal mass ejections and coronal holes are discussed. Verification data are provided for the center's forecasts.

Outcome of the third cloud retrieval evaluation workshop

NASA Astrophysics Data System (ADS)

Roebeling, Rob; Baum, Bryan; Bennartz, Ralf; Hamann, Ulrich; Heidinger, Andy; Thoss, Anke; Walther, Andi

2013-05-01

Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and interannual variations are needed to improve understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role for such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics must be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), held from 15-18 Nov. 2011 in Madison, Wisconsin, USA, is to enhance knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimizing these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods used to prepare daily and monthly cloud parameter climatologies. An important workshop component is discussion on results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on reasons for observed differences. More in depth discussions were held on retrieval principles and validation, and utilization of cloud parameters for climate research. This was done in parallel breakout sessions on cloud vertical placement, cloud physical properties, and cloud climatologies. We present the recommendations of these sessions, propose a way forward to establish international partnerships on cloud research, and summarize actions defined to tailor CREW activities to missions of international programs, such as the Global Energy and Water Cycle Experiment (GEWEX) and Sustained, Co-Ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM). Finally, attention is given to increase the traceability and uniformity of different longterm and homogeneous records of cloud parameters.

AEGIS: a wildfire prevention and management information system

NASA Astrophysics Data System (ADS)

Kalabokidis, Kostas; Ager, Alan; Finney, Mark; Athanasis, Nikos; Palaiologou, Palaiologos; Vasilakos, Christos

2016-03-01

We describe a Web-GIS wildfire prevention and management platform (AEGIS) developed as an integrated and easy-to-use decision support tool to manage wildland fire hazards in Greece (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing online access to information that is essential for wildfire management. The system uses a number of spatial and non-spatial data sources to support key system functionalities. Land use/land cover maps were produced by combining field inventory data with high-resolution multispectral satellite images (RapidEye). These data support wildfire simulation tools that allow the users to examine potential fire behavior and hazard with the Minimum Travel Time fire spread algorithm. End-users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations, i.e., single-fire propagation, point-scale calculation of potential fire behavior, and burn probability analysis, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANNs) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps are used to generate integrated output map of fire hazard prediction. The system also incorporates weather information obtained from remote automatic weather stations and weather forecast maps. The system and associated computation algorithms leverage parallel processing techniques (i.e., High Performance Computing and Cloud Computing) that ensure computational power required for real-time application. All AEGIS functionalities are accessible to authorized end-users through a web-based graphical user interface. An innovative smartphone application, AEGIS App, also provides mobile access to the web-based version of the system.

Comparison of three-dimensional parameters of Halo CMEs using three cone models

NASA Astrophysics Data System (ADS)

Na, H.; Moon, Y.; Jang, S.; Lee, K.

2012-12-01

Halo coronal mass ejections (HCMEs) are a major cause of geomagnetic storms and their three dimensional structures are important for space weather. In this study, we compare three cone models: an elliptical cone model, an ice-cream cone model, and an asymmetric cone model. These models allow us to determine the three dimensional parameters of HCMEs such as radial speed, angular width, and the angle (γ) between sky plane and cone axis. We compare these parameters obtained from three models using 62 well-observed HCMEs observed by SOHO/LASCO from 2001 to 2002. Then we obtain the root mean square error (RMS error) between maximum measured projection speeds and their calculated projection speeds from the cone models. As a result, we find that the radial speeds obtained from the models are well correlated with one another (R > 0.84). The correlation coefficients between angular widths are ranges from 0.04 to 0.53 and those between γ values are from -0.15 to 0.47, which are much smaller than expected. The reason may be due to different assumptions and methods. The RMS errors between the maximum measured projection speeds and the maximum estimated projection speeds of the elliptical cone model, the ice-cream cone model, and the asymmetric cone model are 213 km/s, 254 km/s, and 267 km/s, respectively. And we obtain the correlation coefficients between the location from the models and the flare location (R > 0.75). Finally, we discuss strengths and weaknesses of these models in terms of space weather application.

Extending flood forecasting lead time in a large watershed by coupling WRF QPF with a distributed hydrological model

NASA Astrophysics Data System (ADS)

Li, Ji; Chen, Yangbo; Wang, Huanyu; Qin, Jianming; Li, Jie; Chiao, Sen

2017-03-01

Long lead time flood forecasting is very important for large watershed flood mitigation as it provides more time for flood warning and emergency responses. The latest numerical weather forecast model could provide 1-15-day quantitative precipitation forecasting products in grid format, and by coupling this product with a distributed hydrological model could produce long lead time watershed flood forecasting products. This paper studied the feasibility of coupling the Liuxihe model with the Weather Research and Forecasting quantitative precipitation forecast (WRF QPF) for large watershed flood forecasting in southern China. The QPF of WRF products has three lead times, including 24, 48 and 72 h, with the grid resolution being 20 km  × 20 km. The Liuxihe model is set up with freely downloaded terrain property; the model parameters were previously optimized with rain gauge observed precipitation, and re-optimized with the WRF QPF. Results show that the WRF QPF has bias with the rain gauge precipitation, and a post-processing method is proposed to post-process the WRF QPF products, which improves the flood forecasting capability. With model parameter re-optimization, the model's performance improves also. This suggests that the model parameters be optimized with QPF, not the rain gauge precipitation. With the increasing of lead time, the accuracy of the WRF QPF decreases, as does the flood forecasting capability. Flood forecasting products produced by coupling the Liuxihe model with the WRF QPF provide a good reference for large watershed flood warning due to its long lead time and rational results.

A proposed case-control framework to probabilistically classify individual deaths as expected or excess during extreme hot weather events.

PubMed

Henderson, Sarah B; Gauld, Jillian S; Rauch, Stephen A; McLean, Kathleen E; Krstic, Nikolas; Hondula, David M; Kosatsky, Tom

2016-11-15

Most excess deaths that occur during extreme hot weather events do not have natural heat recorded as an underlying or contributing cause. This study aims to identify the specific individuals who died because of hot weather using only secondary data. A novel approach was developed in which the expected number of deaths was repeatedly sampled from all deaths that occurred during a hot weather event, and compared with deaths during a control period. The deaths were compared with respect to five factors known to be associated with hot weather mortality. Individuals were ranked by their presence in significant models over 100 trials of 10,000 repetitions. Those with the highest rankings were identified as probable excess deaths. Sensitivity analyses were performed on a range of model combinations. These methods were applied to a 2009 hot weather event in greater Vancouver, Canada. The excess deaths identified were sensitive to differences in model combinations, particularly between univariate and multivariate approaches. One multivariate and one univariate combination were chosen as the best models for further analyses. The individuals identified by multiple combinations suggest that marginalized populations in greater Vancouver are at higher risk of death during hot weather. This study proposes novel methods for classifying specific deaths as expected or excess during a hot weather event. Further work is needed to evaluate performance of the methods in simulation studies and against clinically identified cases. If confirmed, these methods could be applied to a wide range of populations and events of interest.

Weather types and strokes in the Augsburg region (Southern Germany)

NASA Astrophysics Data System (ADS)

Beck, Christoph; Ertl, Michael; Giemsa, Esther; Jacobeit, Jucundus; Naumann, Markus; Seubert, Stefanie

2017-04-01

Strokes are one of the leading causes of morbidity and mortality worldwide and the main reason for longterm care dependency in Germany. Concerning the economical impact on patients and healthcare systems it is of particular importance to prevent this disease as well as to improve the outcome of the affected persons. Beside the primary well-known risk factors like hypertension, cigarette smoking, physical inactivity and others, also weather seems to have pronounced influence on the occurrence and frequency of strokes. Previous studies most often focused on effects of singular meteorological variables like ambient air temperature, air pressure or humidity. An advanced approach is to link the entire suite of daily weather elements classified to air mass- or weather types to cerebrovascular morbidity or mortality. In a joint pilot study bringing together climatologists, environmental scientists and physicians from the University of Augsburg and the clinical centre Augsburg, we analysed relationships between singular meteorological parameters as well as combined weather effects (e.g. weather types) and strokes in the urban area of Augsburg and the surrounding rural region. A total of 17.501 stroke admissions to Neurological Clinic and Clinical Neurophysiology at Klinikum Augsburg between 2006 and 2015 are classified to either "ischaemic" (16.354) or "haemorrhagic" (1.147) subtype according to etiology (based on the International Classification of Diseases - 10th Revision). Spearman correlations between daily frequencies of ischaemic and haemorrhagic strokes and singular atmospheric parameters (T, Tmin, Tmax, air pressure, humidity etc.) measured at the DWD (German weather service) meteorological station at Augsburg Muehlhausen are rather low. However, higher correlations are achieved when considering sub-samples of "homogenous weather conditions" derived from synoptic circulation classifications: e.g. within almost all of 10 types arising from a classification of central European mean sea level pressure fields into "Großwettertypes" (Beck 2000) the relationships between meteorological variables and stroke frequencies are increasing. Mainly temperature variables (Tmin, Tmax, Tmean) appear to be important particularly in winter and summer. Moreover distinct correlations of similar magnitude are obtained with other variables like wind speed or precipitation for specific weather types (e.g. westerly type). In how far these initial findings do really point to additional health impacts beyond temperature effects is subject of ongoing work.

Space weather observational activities and data management in Europe

NASA Astrophysics Data System (ADS)

Stanisławska, Iwona; Belehaki, Anna

2009-03-01

One of the primary scientific and technical goals of Space Weather investigations is to produce data in order to study the Sun impact on the Earth and its environment. Studies based on data mining philosophy increase our knowledge of the physical properties of Space Weather, modelling capabilities, and gain applications of various procedures in Space Weather monitoring and forecasting. The paper focuses on an analysis of the availability on the Internet of near-real time and historical collections of the European ground-based and satellite observations, operational indices and parameters. A detailed description of data delivered is included. The following issues are discussed: (1) raw observations, and/or corrected/updated data, (2) resolution and availability of real-time and historical data, (3) products resulting from models and theory including maps, forecasts and alerts, (4) platforms for data delivery.

New datasets for quantifying snow-vegetation-atmosphere interactions in boreal birch and conifer forests

NASA Astrophysics Data System (ADS)

Reid, T. D.; Essery, R.; Rutter, N.; Huntley, B.; Baxter, R.; Holden, R.; King, M.; Hancock, S.; Carle, J.

2012-12-01

Boreal forests exert a strong influence on weather and climate by modifying the surface energy and radiation balance. However, global climate and numerical weather prediction models use forest parameter values from simple look-up tables or maps that are derived from limited satellite data, on large grid scales. In reality, Arctic landscapes are inherently heterogeneous, with highly variable land cover types and structures on a variety of spatial scales. There is value in collecting detailed field data for different areas of vegetation cover, to assess the accuracy of large-scale assumptions. To address these issues, a consortium of researchers funded by the UK's Natural Environment Research Council have collected extensive data on radiation, meteorology, snow cover and canopy structure at two contrasting Arctic forest sites. The chosen study sites were an area of boreal birch forest near Abisko, Sweden in March/April 2011 and mixed conifer forest at Sodankylä, Finland in March/April 2012. At both sites, arrays comprising ten shortwave pyranometers and four longwave pyrgeometers were deployed for periods of up to 50 days, under forest plots of varying canopy structures and densities. In addition, downwelling longwave irradiance and global and diffuse shortwave irradiances were recorded at nearby open sites representing the top-of-canopy conditions. Meteorological data were recorded at all sub-canopy and open sites using automatic weather stations. Over the same periods, tree skin temperatures were measured on selected trees using contact thermocouples, infrared thermocouples and thermal imagery. Canopy structure was accurately quantified through manual surveys, extensive hemispherical photography and terrestrial laser scans of every study plot. Sub-canopy snow depth and snow water equivalent were measured on fine-scale grids at each study plot. Regular site maintenance ensured a high quality dataset covering the important Arctic spring period. The data have several applications, for example in forest ecology, canopy radiative transfer models, snow hydrological modelling, and land surface schemes, for a variety of canopy types from sparse, leafless birch to dense pine and spruce. The work also allows the comparison of modern, highly detailed methods such as laser scanning and thermal imagery with older, well-established data collection methods. By combining these data with airborne and satellite remote sensing data, snow-vegetation-atmosphere interactions could be estimated over a wide area of the heterogeneous boreal landscape. This could improve estimates of crucial parameters such as land surface albedo on the grid scales required for global or regional weather and climate models.

A biometeorological procedure for weather forecast to assess the optimal outdoor clothing insulation.

PubMed

Morabito, Marco; Crisci, Alfonso; Cecchi, Lorenzo; Modesti, Pietro Amedeo; Maracchi, Giampiero; Gensini, Gian Franco; Orlandini, Simone

2008-09-01

Clothing insulation represents an important parameter strongly dependent on climate/weather variability and directly involved in the assessment of the human energy balance. Few studies tried to explore the influence of climate changes on the optimal clothing insulation for outdoor spaces. For this reason, the aim of this work was to investigate mainly the optimal outdoor minimum clothing insulation value required to reach the thermal neutrality (min_clo) related to climate change on a seasonal basis. Subsequently, we developed an example of operational biometeorological procedure to provide 72-hour forecast maps concerning the min_clo. Hourly meteorological data were provided by three Italian weather stations located in Turin, Rome and Palermo, for the period 1951-1995. Environmental variables and subjective characteristics referred to an average adult young male at rest and at a very high metabolic rate were used as input variables to calculate the min_clo by using a thermal index based on the human energy balance. Trends of min_clo were assessed by a non-parametric statistical method. Results showed a lower magnitude of trends in a subject at a very high metabolic rate than at rest. Turin always showed a decrease of min_clo during the study period and prevalently negative trends were also observed in Palermo. On the other hand, an opposite situation was observed in Rome, especially during the morning in all seasons. The development of a daily operational procedure to forecast customized min_clo could provide useful information for the outdoor clothing fitting that might help to reduce the weather-related human health risk.

Highlights in the study of exoplanet atmospheres

NASA Astrophysics Data System (ADS)

Burrows, Adam S.

2014-09-01

Exoplanets are now being discovered in profusion. To understand their character, however, we require spectral models and data. These elements of remote sensing can yield temperatures, compositions and even weather patterns, but only if significant improvements in both the parameter retrieval process and measurements are made. Despite heroic efforts to garner constraining data on exoplanet atmospheres and dynamics, reliable interpretation has frequently lagged behind ambition. I summarize the most productive, and at times novel, methods used to probe exoplanet atmospheres; highlight some of the most interesting results obtained; and suggest various broad theoretical topics in which further work could pay significant dividends.

Revisiting the extended spring indices using gridded weather data and machine learning

NASA Astrophysics Data System (ADS)

Mehdipoor, Hamed; Izquierdo-Verdiguier, Emma; Zurita-Milla, Raul

2016-04-01

The extended spring indices or SI-x [1] have been successfully used to predict the timing of spring onset at continental scales. The SI-x models were created by combining lilac and honeysuckle volunteered phenological observations, temperature data (from weather stations) and latitudinal information. More precisely, these models use a linear regression to predict the day of year of first leaf and first bloom for these two indicator species. In this contribution we revisit both the data and the method used to calibrate the SI-x models to check whether the addition of new input data or the use of non-linear regression methods could lead to improments in the model outputs. In particular, we use a recently published dataset [2] of volunteered observations on cloned and common lilac over longer period of time (1980-2014) and we replace the weather station data by 54 features derived from Daymet [3], which provides 1 by 1 km gridded estimates of daily weather parameters (maximum and minimum temperatures, precipitation, water vapor pressure, solar radiation, day length, snow water equivalent) for North America. These features consist of both daily weather values and their long- and short-term accumulations and elevation. we also replace the original linear regression by a non-linear method. Specifically, we use random forests to both identify the most important features and to predict the day of year of the first leaf of cloned and common lilacs. Preliminary results confirm the importance of the SI-x features (maximum and minimum temperatures and day length). However, our results show that snow water equivalent and water vapor pressure are also necessary to properly model leaf onset. Regarding the predictions, our results indicate that Random Forests yield comparable results to those produced by the SI-x models (in terms of root mean square error -RMSE). For cloned and common lilac, the models predict the day of year of leafing with 16 and 15 days of accuracy respectively. Further research should focus on extensively comparing the features used by both modelling approaches and on analyzing spring onset patterns over continental United States. References 1. Schwartz, M.D., T.R. Ault, and J.L. Betancourt, Spring onset variations and trends in the continental United States: past and regional assessment using temperature-based indices. International Journal of Climatology, 2013. 33(13): p. 2917-2922. 2. Rosemartin, A.H., et al., Lilac and honeysuckle phenology data 1956-2014. Scientific Data, 2015. 2: p. 150038. 3. Thornton, P.E., et al. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2. 2014.

Global distribution of urban parameters derived from high-resolution global datasets for weather modelling

NASA Astrophysics Data System (ADS)

Kawano, N.; Varquez, A. C. G.; Dong, Y.; Kanda, M.

2016-12-01

Numerical model such as Weather Research and Forecasting model coupled with single-layer Urban Canopy Model (WRF-UCM) is one of the powerful tools to investigate urban heat island. Urban parameters such as average building height (Have), plain area index (λp) and frontal area index (λf), are necessary inputs for the model. In general, these parameters are uniformly assumed in WRF-UCM but this leads to unrealistic urban representation. Distributed urban parameters can also be incorporated into WRF-UCM to consider a detail urban effect. The problem is that distributed building information is not readily available for most megacities especially in developing countries. Furthermore, acquiring real building parameters often require huge amount of time and money. In this study, we investigated the potential of using globally available satellite-captured datasets for the estimation of the parameters, Have, λp, and λf. Global datasets comprised of high spatial resolution population dataset (LandScan by Oak Ridge National Laboratory), nighttime lights (NOAA), and vegetation fraction (NASA). True samples of Have, λp, and λf were acquired from actual building footprints from satellite images and 3D building database of Tokyo, New York, Paris, Melbourne, Istanbul, Jakarta and so on. Regression equations were then derived from the block-averaging of spatial pairs of real parameters and global datasets. Results show that two regression curves to estimate Have and λf from the combination of population and nightlight are necessary depending on the city's level of development. An index which can be used to decide which equation to use for a city is the Gross Domestic Product (GDP). On the other hand, λphas less dependence on GDP but indicated a negative relationship to vegetation fraction. Finally, a simplified but precise approximation of urban parameters through readily-available, high-resolution global datasets and our derived regressions can be utilized to estimate a global distribution of urban parameters for later incorporation into a weather model, thus allowing us to acquire a global understanding of urban climate (Global Urban Climatology). Acknowledgment: This research was supported by the Environment Research and Technology Development Fund (S-14) of the Ministry of the Environment, Japan.

Innovative Near Real-Time Data Dissemination Tools Developed by the Space Weather Research Center

NASA Astrophysics Data System (ADS)

Maddox, Marlo M.; Mullinix, Richard; Mays, M. Leila; Kuznetsova, Maria; Zheng, Yihua; Pulkkinen, Antti; Rastaetter, Lutz

2013-03-01

Access to near real-time and real-time space weather data is essential to accurately specifying and forecasting the space environment. The Space Weather Research Center at NASA Goddard Space Flight Center's Space Weather Laboratory provides vital space weather forecasting services primarily to NASA robotic mission operators, as well as external space weather stakeholders including the Air Force Weather Agency. A key component in this activity is the iNtegrated Space Weather Analysis System which is a joint development project at NASA GSFC between the Space Weather Laboratory, Community Coordinated Modeling Center, Applied Engineering & Technology Directorate, and NASA HQ Office Of Chief Engineer. The iSWA system was developed to address technical challenges in acquiring and disseminating space weather environment information. A key design driver for the iSWA system was to generate and present vast amounts of space weather resources in an intuitive, user-configurable, and adaptable format - thus enabling users to respond to current and future space weather impacts as well as enabling post-impact analysis. Having access to near real-time and real-time data is essential to not only ensuring that relevant observational data is available for analysis - but also in ensuring that models can be driven with the requisite input parameters at proper and efficient temporal and spacial resolutions. The iSWA system currently manages over 300 unique near-real and real-time data feeds from various sources consisting of both observational and simulation data. A comprehensive suite of actionable space weather analysis tools and products are generated and provided utilizing a mixture of the ingested data - enabling new capabilities in quickly assessing past, present, and expected space weather effects. This paper will highlight current and future iSWA system capabilities including the utilization of data from the Solar Dynamics Observatory mission. http://iswa.gsfc.nasa.gov/

A simplified rainfall-runoff stochastic simulation method for an application of the SCHADEX method to ungauged catchments.

NASA Astrophysics Data System (ADS)

Penot, David; Paquet, Emmanuel; Lang, Michel

2014-05-01

SCHADEX is a probabilistic method for extreme flood estimation, developed and applied since 2006 at Electricité de France (EDF) for dam spillway design [Paquet et al., 2013]. SCHADEX is based on a semi-continuous rainfall-runoff simulation process. The method has been built around two models: a Multi-Exponential Weather Pattern (MEWP) distribution for rainfall probability estimation [Garavaglia et al., 2010] and the MORDOR hydrological model. To use SCHADEX in ungauged context, rainfall distribution and hydrological model must be regionalized. The regionalization of the MEWP rainfall distribution can be managed with SPAZM, a daily rainfall interpolator [Gottardi et al., 2012] which provides reasonable estimates of point and areal rainfall up to hight quantiles. The main issue remains to regionalize MORDOR which is heavily parametrized. A much more simple model has been considered: the SCS model. It is a well known model for event simulation [USDA SCS, 1985; Beven, 2003] and it relies on only one parameter. Then, the idea is to use the SCS model instead of MORDOR within a simplified stochastic simulation scheme to produce a distribution of flood volume from an exhaustive crossing between rainy events and catchment saturation hazards. The presentation details this process and its capacity to generate a runoff distribution based on catchment areal rainfall distribution. The simulation method depends on a unique parameter Smax, the maximum initial loss of the catchment. Then an initial loss S (between zero and Smax) can be drawn to account for the variability of catchment state (between dry and saturated). The distribution of initial loss (or conversely, of catchment saturation, as modeled by MORDOR) seems closely linked to the catchment's regime, therefore easily to regionalize. The simulation takes into account a snow contribution for snow driven catchments, and an antecedent runoff. The presentation shows the results of this stochastic procedure applied on 80 French catchments and its capacity to represent the asymptotic behaviour of the runoff distribution. References: K. J. Beven. Rainfall-Runoff modelling The Primer, British Library, 2003. F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara. Introducing a rainfall compound distribution model based on weather patterns sub-sampling. Hydrology and Earth System Sciences, 14(6):951-964, 2010. F. Gottardi, C. Obled, J. Gailhard, and E. Paquet. Statistical reanalysis of precipitation fields based on ground network data and weather patterns : Application over french mountains. Journal of Hydrology, 432-433:154-167, 2012. ISSN 0022-1694. E. Paquet, F. Garavaglia, R Garçon, and J. Gailhard. The schadex method : a semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology, 2013. USDA SCS, National Engineering Handbook, Supplement A, Section 4, Chapter 10. Whashington DC, 1985.

Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning

NASA Astrophysics Data System (ADS)

Chaney, Nathaniel W.; Herman, Jonathan D.; Ek, Michael B.; Wood, Eric F.

2016-11-01

With their origins in numerical weather prediction and climate modeling, land surface models aim to accurately partition the surface energy balance. An overlooked challenge in these schemes is the role of model parameter uncertainty, particularly at unmonitored sites. This study provides global parameter estimates for the Noah land surface model using 85 eddy covariance sites in the global FLUXNET network. The at-site parameters are first calibrated using a Latin Hypercube-based ensemble of the most sensitive parameters, determined by the Sobol method, to be the minimum stomatal resistance (rs,min), the Zilitinkevich empirical constant (Czil), and the bare soil evaporation exponent (fxexp). Calibration leads to an increase in the mean Kling-Gupta Efficiency performance metric from 0.54 to 0.71. These calibrated parameter sets are then related to local environmental characteristics using the Extra-Trees machine learning algorithm. The fitted Extra-Trees model is used to map the optimal parameter sets over the globe at a 5 km spatial resolution. The leave-one-out cross validation of the mapped parameters using the Noah land surface model suggests that there is the potential to skillfully relate calibrated model parameter sets to local environmental characteristics. The results demonstrate the potential to use FLUXNET to tune the parameterizations of surface fluxes in land surface models and to provide improved parameter estimates over the globe.

Identifying Patterns in the Weather of Europe for Source Term Estimation

NASA Astrophysics Data System (ADS)

Klampanos, Iraklis; Pappas, Charalambos; Andronopoulos, Spyros; Davvetas, Athanasios; Ikonomopoulos, Andreas; Karkaletsis, Vangelis

2017-04-01

During emergencies that involve the release of hazardous substances into the atmosphere the potential health effects on the human population and the environment are of primary concern. Such events have occurred in the past, most notably involving radioactive and toxic substances. Examples of radioactive release events include the Chernobyl accident in 1986, as well as the more recent Fukushima Daiichi accident in 2011. Often, the release of dangerous substances in the atmosphere is detected at locations different from the release origin. The objective of this work is the rapid estimation of such unknown sources shortly after the detection of dangerous substances in the atmosphere, with an initial focus on nuclear or radiological releases. Typically, after the detection of a radioactive substance in the atmosphere indicating the occurrence of an unknown release, the source location is estimated via inverse modelling. However, depending on factors such as the spatial resolution desired, traditional inverse modelling can be computationally time-consuming. This is especially true for cases where complex topography and weather conditions are involved and can therefore be problematic when timing is critical. Making use of machine learning techniques and the Big Data Europe platform1, our approach moves the bulk of the computation before any such event taking place, therefore allowing for rapid initial, albeit rougher, estimations regarding the source location. Our proposed approach is based on the automatic identification of weather patterns within the European continent. Identifying weather patterns has long been an active research field. Our case is differentiated by the fact that it focuses on plume dispersion patterns and these meteorological variables that affect dispersion the most. For a small set of recurrent weather patterns, we simulate hypothetical radioactive releases from a pre-known set of nuclear reactor locations and for different substance and temporal parameters, using the Java flavour of the Euratom-supported funded RODOS (Real-time On-line DecisiOn Support) system2 for off-site emergency management after nuclear accidents. Once dispersions have been pre-computed, and immediately after a detected release, the currently observed weather can be matched to the derived weather classes. Since each weather class corresponds to a different plume dispersion pattern, the closest classes to an unseen weather sample, say the current weather, are the most likely to lead us to the release origin. In addressing the above problem, we make use of multiple years of weather reanalysis data from NCAR's version3 of ECMWF's ERA-Interim4. To derive useful weather classes, we evaluate several algorithms, ranging from straightforward unsupervised clustering to more complex methods, including relevant neural-network algorithms, on multiple variables. Variables and feature sets, clustering algorithms and evaluation approaches are all dealt with and presented experimentally. The Big Data Europe platform allows for the implementation and execution of the above tasks in the cloud, in a scalable, robust and efficient way.

Shift in fire-ecosystems and weather changes

Treesearch

Bongani Finiza

2013-01-01

During recent decades too much focus fell on fire suppression and fire engineering methods. Little attention has been given to understanding the shift in the changing fire weather resulting from the global change in weather patterns. Weather change have gradually changed the way vegetation cover respond to fire occurrence and brought about changes in fire behavior and...

Forecasting Propagation and Evolution of CMEs in an Operational Setting: What Has Been Learned

NASA Technical Reports Server (NTRS)

Zheng, Yihua; Macneice, Peter; Odstrcil, Dusan; Mays, M. L.; Rastaetter, Lutz; Pulkkinen, Antti; Taktakishvili, Aleksandre; Hesse, Michael; Kuznetsova, M. Masha; Lee, Hyesook;

Forecasting propagation and evolution of CMEs in an operational setting: What has been learned

NASA Astrophysics Data System (ADS)

Zheng, Yihua; Macneice, Peter; Odstrcil, Dusan; Mays, M. L.; Rastaetter, Lutz; Pulkkinen, Antti; Taktakishvili, Aleksandre; Hesse, Michael; Masha Kuznetsova, M.; Lee, Hyesook; Chulaki, Anna

2013-10-01

of the major types of solar eruption, coronal mass ejections (CMEs) not only impact space weather, but also can have significant societal consequences. CMEs cause intense geomagnetic storms and drive fast mode shocks that accelerate charged particles, potentially resulting in enhanced radiation levels both in ions and electrons. Human and technological assets in space can be endangered as a result. CMEs are also the major contributor to generating large amplitude Geomagnetically Induced Currents (GICs), which are a source of concern for power grid safety. Due to their space weather significance, forecasting the evolution and impacts of CMEs has become a much desired capability for space weather operations worldwide. Based on our operational experience at Space Weather Research Center at NASA Goddard Space Flight Center (http://swrc.gsfc.nasa.gov), we present here some of the insights gained about accurately predicting CME impacts, particularly in relation to space weather operations. These include: 1. The need to maximize information to get an accurate handle of three-dimensional (3-D) CME kinetic parameters and therefore improve CME forecast; 2. The potential use of CME simulation results for qualitative prediction of regions of space where solar energetic particles (SEPs) may be found; 3. The need to include all CMEs occurring within a 24 h period for a better representation of the CME interactions; 4. Various other important parameters in forecasting CME evolution in interplanetary space, with special emphasis on the CME propagation direction. It is noted that a future direction for our CME forecasting is to employ the ensemble modeling approach.

Assessment of Existing Data and Reports for System Evaluation

NASA Technical Reports Server (NTRS)

Matolak, David W.; Skidmore, Trent A.

2000-01-01

This report describes work done as part of the Weather Datalink Research project grant. We describe the work done under Task 1 of this project: the assessment of the suitability of available reports and data for use in evaluation of candidate weather datalink systems, and the development of a performance parameter set for comparative system evaluation. It was found that existing data and reports are inadequate for a complete physical layer characterization, but that these reports provide a good foundation for system comparison. In addition, these reports also contain some information useful for evaluation at higher layers. The performance parameter list compiled can be viewed as near complete-additional investigations, both analytical/simulation and experimental, will likely result in additions and improvements to this list.

Monthly means of selected climate variables for 1985 - 1989

NASA Technical Reports Server (NTRS)

Schubert, S.; Wu, C.-Y.; Zero, J.; Schemm, J.-K.; Park, C.-K.; Suarez, M.

1992-01-01

Meteorologists are accustomed to viewing instantaneous weather maps, since these contain the most relevant information for the task of producing short-range weather forecasts. Climatologists, on the other hand, tend to deal with long-term means, which portray the average climate. The recent emphasis on dynamical extended-range forecasting and, in particular measuring and predicting short term climate change makes it important that we become accustomed to looking at variations on monthly and longer time scales. A convenient toll for researchers to familiarize themselves with the variability which occurs in selected parameters on these time scales is provided. The format of the document was chosen to help facilitate the intercomparison of various parameters and highlight the year-to-year variability in monthly means.

Coaxial digital holography measures particular matter in cloud and ambient atmosphere

NASA Astrophysics Data System (ADS)

Li, Baosheng; Yu, Haonan; Jia, Yizhen; Tao, Xiaojie; Zhang, Yang

2018-02-01

In the artificially affected weather, the detection of cloud droplets particles provides an important reference for the effective impact of artificial weather. Digital holography has the unique advantages of full-field, non-contact, no damage, real-time and quantification. In this paper, coaxial digital holography is used to record the polyethylene standard particles and aluminum scrap, and some important parameters, such as three-dimensional coordinate spatial distribution and particle size, will be obtained by the means of analyzing the digital hologram of the particle. The experimental results verify the feasibility of the coaxial digital holographic device applied to the measurement of the cloud parameters, and complete the construction of the coaxial digital holographic system and the measurement of the particles.

Weather elements, chemical air pollutants and airborne pollen influencing asthma emergency room visits in Szeged, Hungary: performance of two objective weather classifications

NASA Astrophysics Data System (ADS)

Makra, László; Puskás, János; Matyasovszky, István; Csépe, Zoltán; Lelovics, Enikő; Bálint, Beatrix; Tusnády, Gábor

2015-09-01

Weather classification approaches may be useful tools in modelling the occurrence of respiratory diseases. The aim of the study is to compare the performance of an objectively defined weather classification and the Spatial Synoptic Classification (SSC) in classifying emergency department (ED) visits for acute asthma depending from weather, air pollutants, and airborne pollen variables for Szeged, Hungary, for the 9-year period 1999-2007. The research is performed for three different pollen-related periods of the year and the annual data set. According to age and gender, nine patient categories, eight meteorological variables, seven chemical air pollutants, and two pollen categories were used. In general, partly dry and cold air and partly warm and humid air aggravate substantially the symptoms of asthmatics. Our major findings are consistent with this establishment. Namely, for the objectively defined weather types favourable conditions for asthma ER visits occur when an anticyclonic ridge weather situation happens with near extreme temperature and humidity parameters. Accordingly, the SSC weather types facilitate aggravating asthmatic conditions if warm or cool weather occur with high humidity in both cases. Favourable conditions for asthma attacks are confirmed in the extreme seasons when atmospheric stability contributes to enrichment of air pollutants. The total efficiency of the two classification approaches is similar in spite of the fact that the methodology for derivation of the individual types within the two classification approaches is completely different.

Weather elements, chemical air pollutants and airborne pollen influencing asthma emergency room visits in Szeged, Hungary: performance of two objective weather classifications.

PubMed

Makra, László; Puskás, János; Matyasovszky, István; Csépe, Zoltán; Lelovics, Enikő; Bálint, Beatrix; Tusnády, Gábor

2015-09-01

Weather classification approaches may be useful tools in modelling the occurrence of respiratory diseases. The aim of the study is to compare the performance of an objectively defined weather classification and the Spatial Synoptic Classification (SSC) in classifying emergency department (ED) visits for acute asthma depending from weather, air pollutants, and airborne pollen variables for Szeged, Hungary, for the 9-year period 1999-2007. The research is performed for three different pollen-related periods of the year and the annual data set. According to age and gender, nine patient categories, eight meteorological variables, seven chemical air pollutants, and two pollen categories were used. In general, partly dry and cold air and partly warm and humid air aggravate substantially the symptoms of asthmatics. Our major findings are consistent with this establishment. Namely, for the objectively defined weather types favourable conditions for asthma ER visits occur when an anticyclonic ridge weather situation happens with near extreme temperature and humidity parameters. Accordingly, the SSC weather types facilitate aggravating asthmatic conditions if warm or cool weather occur with high humidity in both cases. Favourable conditions for asthma attacks are confirmed in the extreme seasons when atmospheric stability contributes to enrichment of air pollutants. The total efficiency of the two classification approaches is similar in spite of the fact that the methodology for derivation of the individual types within the two classification approaches is completely different.

VNIR hyperspectral background characterization methods in adverse weather conditions

NASA Astrophysics Data System (ADS)

Romano, João M.; Rosario, Dalton; Roth, Luz

2009-05-01

Hyperspectral technology is currently being used by the military to detect regions of interest where potential targets may be located. Weather variability, however, may affect the ability for an algorithm to discriminate possible targets from background clutter. Nonetheless, different background characterization approaches may facilitate the ability for an algorithm to discriminate potential targets over a variety of weather conditions. In a previous paper, we introduced a new autonomous target size invariant background characterization process, the Autonomous Background Characterization (ABC) or also known as the Parallel Random Sampling (PRS) method, features a random sampling stage, a parallel process to mitigate the inclusion by chance of target samples into clutter background classes during random sampling; and a fusion of results at the end. In this paper, we will demonstrate how different background characterization approaches are able to improve performance of algorithms over a variety of challenging weather conditions. By using the Mahalanobis distance as the standard algorithm for this study, we compare the performance of different characterization methods such as: the global information, 2 stage global information, and our proposed method, ABC, using data that was collected under a variety of adverse weather conditions. For this study, we used ARDEC's Hyperspectral VNIR Adverse Weather data collection comprised of heavy, light, and transitional fog, light and heavy rain, and low light conditions.

Method and System for Dynamic Automated Corrections to Weather Avoidance Routes for Aircraft in En Route Airspace

NASA Technical Reports Server (NTRS)

McNally, B. David (Inventor); Erzberger, Heinz (Inventor); Sheth, Kapil (Inventor)

2015-01-01

A dynamic weather route system automatically analyzes routes for in-flight aircraft flying in convective weather regions and attempts to find more time and fuel efficient reroutes around current and predicted weather cells. The dynamic weather route system continuously analyzes all flights and provides reroute advisories that are dynamically updated in real time while the aircraft are in flight. The dynamic weather route system includes a graphical user interface that allows users to visualize, evaluate, modify if necessary, and implement proposed reroutes.

The Influence of Weather Conditions on Outdoor Physical Activity Among Older People With and Without Osteoarthritis in 6 European Countries.

PubMed

Timmermans, Erik J; van der Pas, Suzan; Dennison, Elaine M; Maggi, Stefania; Peter, Richard; Castell, Maria Victoria; Pedersen, Nancy L; Denkinger, Michael D; Edwards, Mark H; Limongi, Federica; Herbolsheimer, Florian; Sánchez-Martínez, Mercedes; Siviero, Paola; Queipo, Rocio; Schaap, Laura A; Deeg, Dorly J H

2016-12-01

Older adults with osteoarthritis (OA) often report that their disease symptoms are exacerbated by weather conditions. This study examines the association between outdoor physical activity (PA) and weather conditions in older adults from 6 European countries and assesses whether outdoor PA and weather conditions are more strongly associated in older persons with OA than in those without the condition. The American College of Rheumatology classification criteria were used to diagnose OA. Outdoor PA was assessed using the LASA Physical Activity Questionnaire. Data on weather parameters were obtained from weather stations. Of the 2439 participants (65-85 years), 29.6% had OA in knee, hand and/or hip. Participants with OA spent fewer minutes in PA than participants without OA (Median = 42.9, IQR = 20.0 to 83.1 versus Median = 51.4, IQR = 23.6 to 98.6; P < .01). In the full sample, temperature (B = 1.52; P < .001) and relative humidity (B = -0.77; P < .001) were associated with PA. Temperature was more strongly associated with PA in participants without OA (B = 1.98; P < .001) than in those with the condition (B = 0.48; P = .47). Weather conditions are associated with outdoor PA in older adults in the general population. Outdoor PA and weather conditions were more strongly associated in older adults without OA than in their counterparts with OA.

Weather Effects on Mobile Social Interactions: A Case Study of Mobile Phone Users in Lisbon, Portugal

PubMed Central

Phithakkitnukoon, Santi; Leong, Tuck W.; Smoreda, Zbigniew; Olivier, Patrick

2012-01-01

The effect of weather on social interactions has been explored through the analysis of a large mobile phone use dataset. Time spent on phone calls, numbers of connected social ties, and tie strength were used as proxies for social interactions; while weather conditions were characterized in terms of temperature, relative humidity, air pressure, and wind speed. Our results are based on the analysis of a full calendar year of data for 22,696 mobile phone users (53.2 million call logs) in Lisbon, Portugal. The results suggest that different weather parameters have correlations to the level and character of social interactions. We found that although weather did not show much influence upon people's average call duration, the likelihood of longer calls was found to increase during periods of colder weather. During periods of weather that were generally considered to be uncomfortable (i.e., very cold/warm, very low/high air pressure, and windy), people were found to be more likely to communicate with fewer social ties. Despite this tendency, we found that people are more likely to maintain their connections with those they have strong ties with much more than those of weak ties. This study sheds new light on the influence of weather conditions on social relationships and how mobile phone data can be used to investigate the influence of environmental factors on social dynamics. PMID:23071523

Weather effects on mobile social interactions: a case study of mobile phone users in Lisbon, Portugal.

PubMed

Phithakkitnukoon, Santi; Leong, Tuck W; Smoreda, Zbigniew; Olivier, Patrick

2012-01-01

The effect of weather on social interactions has been explored through the analysis of a large mobile phone use dataset. Time spent on phone calls, numbers of connected social ties, and tie strength were used as proxies for social interactions; while weather conditions were characterized in terms of temperature, relative humidity, air pressure, and wind speed. Our results are based on the analysis of a full calendar year of data for 22,696 mobile phone users (53.2 million call logs) in Lisbon, Portugal. The results suggest that different weather parameters have correlations to the level and character of social interactions. We found that although weather did not show much influence upon people's average call duration, the likelihood of longer calls was found to increase during periods of colder weather. During periods of weather that were generally considered to be uncomfortable (i.e., very cold/warm, very low/high air pressure, and windy), people were found to be more likely to communicate with fewer social ties. Despite this tendency, we found that people are more likely to maintain their connections with those they have strong ties with much more than those of weak ties. This study sheds new light on the influence of weather conditions on social relationships and how mobile phone data can be used to investigate the influence of environmental factors on social dynamics.

CME Arrival-time Validation of Real-time WSA-ENLIL+Cone Simulations at the CCMC/SWRC

NASA Astrophysics Data System (ADS)

Wold, A. M.; Mays, M. L.; Taktakishvili, A.; Jian, L.; Odstrcil, D.; MacNeice, P. J.

2016-12-01

The Wang-Sheeley-Arge (WSA)-ENLIL+Cone model is used extensively in space weather operations worldwide to model CME propagation, as such it is important to assess its performance. We present validation results of the WSA-ENLIL+Cone model installed at the Community Coordinated Modeling Center (CCMC) and executed in real-time by the CCMC/Space Weather Research Center (SWRC). The SWRC is a CCMC sub-team that provides space weather services to NASA robotic mission operators and science campaigns, and also prototypes new forecasting models and techniques. CCMC/SWRC uses the WSA-ENLIL+Cone model to predict CME arrivals at NASA missions throughout the inner heliosphere. In this work we compare model predicted CME arrival-times to in-situ ICME shock observations near Earth (ACE, Wind), STEREO-A and B for simulations completed between March 2010 - July 2016 (over 1500 runs). We report hit, miss, false alarm, and correct rejection statistics for all three spacecraft. For hits we compute the bias, RMSE, and average absolute CME arrival time error, and the dependence of these errors on CME input parameters. We compare the predicted geomagnetic storm strength (Kp index) to the CME arrival time error for Earth-directed CMEs. The predicted Kp index is computed using the WSA-ENLIL+Cone plasma parameters at Earth with a modified Newell et al. (2007) coupling function. We also explore the impact of the multi-spacecraft observations on the CME parameters used initialize the model by comparing model validation results before and after the STEREO-B communication loss (since September 2014) and STEREO-A side-lobe operations (August 2014-December 2015). This model validation exercise has significance for future space weather mission planning such as L5 missions.

Predicting key malaria transmission factors, biting and entomological inoculation rates, using modelled soil moisture in Kenya.

PubMed

Patz, J A; Strzepek, K; Lele, S; Hedden, M; Greene, S; Noden, B; Hay, S I; Kalkstein, L; Beier, J C

1998-10-01

While malaria transmission varies seasonally, large inter-annual heterogeneity of malaria incidence occurs. Variability in entomological parameters, biting rates and entomological inoculation rates (EIR) have been strongly associated with attack rates in children. The goal of this study was to assess the weather's impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by the U.S. Army from March 1986 through June 1988 at Kisian, Kenya was analysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface-water availability was used to combine multiple weather parameters with landcover and soil features to improve disease prediction. Modelling soil moisture substantially improved prediction of biting rates compared to rainfall; soil moisture lagged two weeks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 32% variability, peaking after a 4-week lag. The interspecies difference in response to soil moisture was significant (P < 0.00001). A satellite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r = 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of An. gambiae EIR, peaking at a lag of six weeks. The relationship between temperature and An. gambiae biting rates was less robust; maximum temperature r2 = -0.20, and minimum temperature r2 = 0.12 after lagging one week. Benefits of hydrological modelling are compared to raw weather parameters and to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Niño forecasts or global climate change model projections.

The Influence of the Environment and Clothing on Human Exposure to Ultraviolet Light

PubMed Central

Liu, Jin; Zhang, Wei

2015-01-01

Objection The aim of this study is to determine the effect of clothing and the environment on human exposure to ultraviolet light. Methods The ultraviolet (ultraviolet A and ultraviolet B) light intensity was measured, and air quality parameters were recorded in 2014 in Beijing, China. Three types of clothing (white polyester cloth, pure cotton white T-shirt, and pure cotton black T-shirt) were individually placed on a mannequin. The ultraviolet (ultraviolet A and ultraviolet B) light intensities were measured above and beneath each article of clothing, and the percentage of ultraviolet light transmission through the clothing was calculated. Results (1) The ultraviolet light transmission was significantly higher through white cloth than through black cloth; the transmission was significantly higher through polyester cloth than through cotton. (2) The weather significantly influenced ultraviolet light transmission through white polyester cloth; transmission was highest on clear days and lowest on overcast days (ultraviolet A: P=0.000; ultraviolet B: P=0.008). (3) Air quality parameters (air quality index and particulate matter 2.5 and 10) were inversely related to the ultraviolet light intensity that reached the earth’s surface. Ultraviolet B transmission through white polyester cloth was greater under conditions of low air pollution compared with high air pollution. Conclusion Clothing color and material and different types of weather affected ultraviolet light transmission; for one particular cloth, the transmission decreased with increasing air pollution. PMID:25923778

A spectral-spatial-dynamic hierarchical Bayesian (SSD-HB) model for estimating soybean yield

NASA Astrophysics Data System (ADS)

Kazama, Yoriko; Kujirai, Toshihiro

2014-10-01

A method called a "spectral-spatial-dynamic hierarchical-Bayesian (SSD-HB) model," which can deal with many parameters (such as spectral and weather information all together) by reducing the occurrence of multicollinearity, is proposed. Experiments conducted on soybean yields in Brazil fields with a RapidEye satellite image indicate that the proposed SSD-HB model can predict soybean yield with a higher degree of accuracy than other estimation methods commonly used in remote-sensing applications. In the case of the SSD-HB model, the mean absolute error between estimated yield of the target area and actual yield is 0.28 t/ha, compared to 0.34 t/ha when conventional PLS regression was applied, showing the potential effectiveness of the proposed model.

Diagnosis of vertical motions from VAS retrievals during a convective outbreak

NASA Technical Reports Server (NTRS)

Funk, T. W.; Fuelberg, H. E.

1985-01-01

GOES-VAS satellite retrievals are used to investigate an intense convective outbreak over the Mississippi River Valley on 21-22 July 1982. The primary goals are to assess the strengths and weaknesses of three methods for computing vertical motion using satellite retrievals and to determine the effects of short interval observations on the calculations. Then, the vertical motions are incorporated with thermodynamic parameters to assess the usefulness of VAS data in delineating factors leading to storm formation. Results indicate that the quasi-geotrophic omega equation provided patterns and magnitudes most consistent with observed weather events and the 12 h radiosonde-derived motions. The vorticity method generally produced reasonable patterns, especially over the convective outbreak, although magnitudes were large due to its time derivative.

INNOVATIVE URBAN WET-WEATHER FLOW MANAGEMENT SYSTEMS

EPA Science Inventory

This report describes innovative methods to improve wet weather flow (WWF) management systems, that provide drainage services at the same time as decreasing stormwater pollutant discharges, for urban developments of the 21st century. Traditionally, wet-weather collection systems...

Human factors analysis of road weather advisory and control information : final report.

DOT National Transportation Integrated Search

2010-03-31

The amount of available weather information and the methods by which this information can be disseminated to travelers have grown considerably in recent years. This growth includes weather gathering devices (sensors, satellites), models and forecasti...

Use of the SLW index to calculate growth function in the sea cucumber Isostichopus badionotus

PubMed Central

Poot-Salazar, Alicia; Hernández-Flores, Álvaro; Ardisson, Pedro-Luis

2014-01-01

Age and growth analysis is essential to fisheries management. Indirect methods to calculate growth are widely used; however, length frequency data analysis in sea cucumbers is complicated by high data variability caused by body wall elasticity. Here we calculated Isostichopus badionotus parameters of the von Bertalanffy growth function. In order to address bias produced by body wall elasticity, we compared the performance of four measurements and one compound index that combines different biometric parameters: the square root of the length-width product (SLW). Results showed that variability in length data due to body wall elasticity was controlled by using body length (Le) from the SLW compound index. Growth in I. badionotus follows a negative allometric tendency. Slow or zero growth periods were observed during October and November, when weather conditions were adverse. PMID:24909262

The symmetry and mass of halo Coronal Mass Ejections (CMEs) as quantitative predictors for severe space weather at Earth.

NASA Astrophysics Data System (ADS)

Fuselier, S.; Allegrini, F.; Bzowski, M.; Dayeh, M. A.; Desai, M. I.; Funsten, H. O.; Galli, A.; Heirtzler, D.; Janzen, P. H.; Kubiak, M. A.; Kucharek, H.; Lewis, W. S.; Livadiotis, G.; McComas, D. J.; Moebius, E.; Petrinec, S. M.; Quinn, M. S.; Schwadron, N.; Sokol, J. M.; Trattner, K. J.

2014-12-01

The Bureau of Meteorology's Space Weather Service operates an alert service for severe space weather events. The service relies on a statistical model which ingests observations of M and X class solar flares at or shortly after the time of the flare to predict the occurrence and severity of terrestrial impacts with a lead time of 1 to 4 days. This model has been operational since 2012 and caters to the needs of critical infrastructure groups in the Australian region. This paper reports on improvements to the forecast model by including SOHO LASCO coronagraph observations of Coronal Mass Ejections (CMEs). The coronagraphs are analysed to determine the Earthward direction parameter and the integrated intensity as a measure of the CME mass. Both of these parameters can help to predict whether a CME will be geo-effective. This work aims to increase the accuracy of the model predictions and lower the rate of false positives, as well as providing an estimate of the expected level of geomagnetic storm intensity.

The symmetry and mass of halo Coronal Mass Ejections (CMEs) as quantitative predictors for severe space weather at Earth.

NASA Astrophysics Data System (ADS)

Freeland, L. E.; Terkildsen, M. B.

2015-12-01

The Bureau of Meteorology's Space Weather Service operates an alert service for severe space weather events. The service relies on a statistical model which ingests observations of M and X class solar flares at or shortly after the time of the flare to predict the occurrence and severity of terrestrial impacts with a lead time of 1 to 4 days. This model has been operational since 2012 and caters to the needs of critical infrastructure groups in the Australian region. This paper reports on improvements to the forecast model by including SOHO LASCO coronagraph observations of Coronal Mass Ejections (CMEs). The coronagraphs are analysed to determine the Earthward direction parameter and the integrated intensity as a measure of the CME mass. Both of these parameters can help to predict whether a CME will be geo-effective. This work aims to increase the accuracy of the model predictions and lower the rate of false positives, as well as providing an estimate of the expected level of geomagnetic storm intensity.

Potential of turbidity monitoring for real time control of pollutant discharge in sewers during rainfall events.

PubMed

Lacour, C; Joannis, C; Gromaire, M-C; Chebbo, G

2009-01-01

Turbidity sensors can be used to continuously monitor the evolution of pollutant mass discharge. For two sites within the Paris combined sewer system, continuous turbidity, conductivity and flow data were recorded at one-minute time intervals over a one-year period. This paper is intended to highlight the variability in turbidity dynamics during wet weather. For each storm event, turbidity response aspects were analysed through different classifications. The correlation between classification and common parameters, such as the antecedent dry weather period, total event volume per impervious hectare and both the mean and maximum hydraulic flow for each event, was also studied. Moreover, the dynamics of flow and turbidity signals were compared at the event scale. No simple relation between turbidity responses, hydraulic flow dynamics and the chosen parameters was derived from this effort. Knowledge of turbidity dynamics could therefore potentially improve wet weather management, especially when using pollution-based real-time control (P-RTC) since turbidity contains information not included in hydraulic flow dynamics and not readily predictable from such dynamics.

Creating a Realistic Weather Environment for Motion-Based Piloted Flight Simulation

NASA Technical Reports Server (NTRS)

Daniels, Taumi S.; Schaffner, Philip R.; Evans, Emory T.; Neece, Robert T.; Young, Steve D.

2012-01-01

A flight simulation environment is being enhanced to facilitate experiments that evaluate research prototypes of advanced onboard weather radar, hazard/integrity monitoring (HIM), and integrated alerting and notification (IAN) concepts in adverse weather conditions. The simulation environment uses weather data based on real weather events to support operational scenarios in a terminal area. A simulated atmospheric environment was realized by using numerical weather data sets. These were produced from the High-Resolution Rapid Refresh (HRRR) model hosted and run by the National Oceanic and Atmospheric Administration (NOAA). To align with the planned flight simulation experiment requirements, several HRRR data sets were acquired courtesy of NOAA. These data sets coincided with severe weather events at the Memphis International Airport (MEM) in Memphis, TN. In addition, representative flight tracks for approaches and departures at MEM were generated and used to develop and test simulations of (1) what onboard sensors such as the weather radar would observe; (2) what datalinks of weather information would provide; and (3) what atmospheric conditions the aircraft would experience (e.g. turbulence, winds, and icing). The simulation includes a weather radar display that provides weather and turbulence modes, derived from the modeled weather along the flight track. The radar capabilities and the pilots controls simulate current-generation commercial weather radar systems. Appropriate data-linked weather advisories (e.g., SIGMET) were derived from the HRRR weather models and provided to the pilot consistent with NextGen concepts of use for Aeronautical Information Service (AIS) and Meteorological (MET) data link products. The net result of this simulation development was the creation of an environment that supports investigations of new flight deck information systems, methods for incorporation of better weather information, and pilot interface and operational improvements for better aviation safety. This research is part of a larger effort at NASA to study the impact of the growing complexity of operations, information, and systems on crew decision-making and response effectiveness; and then to recommend methods for improving future designs.

Analysis of Convective Weather Impact on Pre-Departure Routing of Flights from Fort Worth Center to New York Center

NASA Technical Reports Server (NTRS)

Arneson, Heather; Bombelli, Alessandro; Segarra-Torne, Adria; Tse, Elmer

2017-01-01

In response to severe weather conditions, Traffic Managers specify flow constraints and reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options and associated airspace capacities would assist Traffic Managers in making more efficient decisions in response to convective weather. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. This paper describes the initial steps and methodology used towards this goal. The focus of this work is flights departing from Fort Worth Center destined for New York Center. Dominant routing structures used in the absence of convective weather are identified. A method to extract relevant features from the large volume of weather data available to quantify the impact of convective weather on this routing structure over a given time range is presented. Finally, a method of estimating flow rate capacity along commonly used routes during convective weather events is described. Results show that the flow rates drop exponentially as a function of the values of the proposed feature and that convective weather on the final third of the route was found to have a greater impact on the flow rate restriction than other portions of the route.

Improving the estimation of zenith dry tropospheric delays using regional surface meteorological data

NASA Astrophysics Data System (ADS)

Luo, X.; Heck, B.; Awange, J. L.

2013-12-01

Global Navigation Satellite Systems (GNSS) are emerging as possible tools for remote sensing high-resolution atmospheric water vapour that improves weather forecasting through numerical weather prediction models. Nowadays, the GNSS-derived tropospheric zenith total delay (ZTD), comprising zenith dry delay (ZDD) and zenith wet delay (ZWD), is achievable with sub-centimetre accuracy. However, if no representative near-site meteorological information is available, the quality of the ZDD derived from tropospheric models is degraded, leading to inaccurate estimation of the water vapour component ZWD as difference between ZTD and ZDD. On the basis of freely accessible regional surface meteorological data, this paper proposes a height-dependent linear correction model for a priori ZDD. By applying the ordinary least-squares estimation (OLSE), bootstrapping (BOOT), and leave-one-out cross-validation (CROS) methods, the model parameters are estimated and analysed with respect to outlier detection. The model validation is carried out using GNSS stations with near-site meteorological measurements. The results verify the efficiency of the proposed ZDD correction model, showing a significant reduction in the mean bias from several centimetres to about 5 mm. The OLSE method enables a fast computation, while the CROS procedure allows for outlier detection. All the three methods produce consistent results after outlier elimination, which improves the regression quality by about 20% and the model accuracy by up to 30%.

Measuring U-series Disequilibrium in Weathering Rinds to Study the Influence of Environmental Factors to Weathering Rates in Tropical Basse-Terre Island (French Guadeloupe)

NASA Astrophysics Data System (ADS)

Guo, J.; Ma, L.; Sak, P. B.; Gaillardet, J.; Chabaux, F. J.; Brantley, S. L.

2015-12-01

Chemical weathering is a critical process to global CO2 consumption, river/ocean chemistry, and nutrient import to biosphere. Weathering rinds experience minimal physical erosion and provide a well-constrained system to study the chemical weathering process. Here, we applied U-series disequilibrium dating method to study weathering advance rates on the wet side of Basse-Terre Island, French Guadeloupe, aiming to understand the role of the precipitation in controlling weathering rates and elucidate the behavior and immobilization mechanisms of U-series isotopes during rind formation. Six weathering clasts from 5 watersheds with mean annual precipitation varying from 2000 to 3000 mm/yr were measured for U-series isotope ratios and major element compositions on linear core-to-rind transects. One sample experienced complete core-to-rind transformation, while the rest clasts contain both rinds and unweathered cores. Our results show that the unweathered cores are under U-series secular equilibrium, while all the rind materials show significant U-series disequilibrium. For most rinds, linear core-to-rind increases of (230Th/232Th) activity ratios suggest a simple continuous U addition history. However, (234U/238U) and (238U/232Th) trends in several clasts show evidences of remobilization of Uranium besides the U addition, complicating the use of U-series dating method. The similarity between U/Th ratios and major elements trends like Fe, Al, P in some transects and the ongoing leaching experiments suggest that redox and organic colloids could control the mobilization of U-series isotopes in the rinds. Rind formation ages and weathering advance rate (0.07-0.29mm/kyr) were calculated for those rinds with a simple U-addition history. Our preliminary results show that local precipitation gradient significantly influenced the weathering advance rate, revealing the potential of estimating weathering advance rates at a large spatial scale using the U-series dating method.

a Weather Monitoring System for Application to Apple and Corn Production

NASA Astrophysics Data System (ADS)

Stirm, Walter Leroy

Many crop management decisions are based on weather -crop development relationships. Daily weather data is currently used in most crop development research and applied models. Present weather and computer technology now makes possible monitoring of crop development on a realtime basis. This research tests a method of computing crop sensitive temperatures for corn and apple using standard hourly meteorological data. The method also makes use of detailed plant physiological stage measurements to determine timing of vital cultural operations tied to the observed weather conditions. The sensitive temperature method incorporates very short term weather variability accounting for changes in the cloud cover, radiation rates, evaporative cooling and other factors involved in the plant's energy balance. The relationship of plant and weather measurements are also used to determine corn emergence, corn grain drydown rate and fruit harvest duration. The monitoring system also incorporates a crop growth unit forecast technique employing short and medium range temperature forecasts of the National Weather Service. The projections of growth units are made for five and ten days into the future. Predicted growth unit accumulations are compared to historical growth unit accumulations to determine the forecast stage. The sensitive temperature crop monitoring system removes some of the error involved in evaluation of growth units by average daily temperature. Carry over maximum and minimums, extended duration of warm or cool periods within the day and disruption of diurnal temperature curve by passage of fronts are eliminated.

Using genetic algorithms to optimize the analogue method for precipitation prediction in the Swiss Alps

NASA Astrophysics Data System (ADS)

Horton, Pascal; Jaboyedoff, Michel; Obled, Charles

2018-01-01

Analogue methods provide a statistical precipitation prediction based on synoptic predictors supplied by general circulation models or numerical weather prediction models. The method samples a selection of days in the archives that are similar to the target day to be predicted, and consider their set of corresponding observed precipitation (the predictand) as the conditional distribution for the target day. The relationship between the predictors and predictands relies on some parameters that characterize how and where the similarity between two atmospheric situations is defined. This relationship is usually established by a semi-automatic sequential procedure that has strong limitations: (i) it cannot automatically choose the pressure levels and temporal windows (hour of the day) for a given meteorological variable, (ii) it cannot handle dependencies between parameters, and (iii) it cannot easily handle new degrees of freedom. In this work, a global optimization approach relying on genetic algorithms could optimize all parameters jointly and automatically. The global optimization was applied to some variants of the analogue method for the Rhône catchment in the Swiss Alps. The performance scores increased compared to reference methods, especially for days with high precipitation totals. The resulting parameters were found to be relevant and coherent between the different subregions of the catchment. Moreover, they were obtained automatically and objectively, which reduces the effort that needs to be invested in exploration attempts when adapting the method to a new region or for a new predictand. For example, it obviates the need to assess a large number of combinations of pressure levels and temporal windows of predictor variables that were manually selected beforehand. The optimization could also take into account parameter inter-dependencies. In addition, the approach allowed for new degrees of freedom, such as a possible weighting between pressure levels, and non-overlapping spatial windows.

Effects of Weathering on TIR Spectra and Rock Classification

NASA Astrophysics Data System (ADS)

McDowell, M. L.; Hamilton, V. E.; Riley, D.

2006-03-01

Changes in mineralogy due to weathering are detectable in the TIR and cause misclassification of rock types. We survey samples over a range of lithologies and attempt to provide a method of correction for rock identification from weathered spectra.

Historical Time Series of Extreme Convective Weather in Finland

NASA Astrophysics Data System (ADS)

Laurila, T. K.; Mäkelä, A.; Rauhala, J.; Olsson, T.; Jylhä, K.

2016-12-01

Thunderstorms, lightning, tornadoes, downbursts, large hail and heavy precipitation are well-known for their impacts to human life. In the high latitudes as in Finland, these hazardous warm season convective weather events are focused in the summer season, roughly from May to September with peak in the midsummer. The position of Finland between the maritime Atlantic and the continental Asian climate zones makes possible large variability in weather in general which reflects also to the occurrence of severe weather; the hot, moist and extremely unstable air masses sometimes reach Finland and makes possible for the occurrence of extreme and devastating weather events. Compared to lower latitudes, the Finnish climate of severe convection is "moderate" and contains a large year-to-year variation; however, behind the modest annual average is hidden the climate of severe weather events that practically every year cause large economical losses and sometimes even losses of life. Because of the increased vulnerability of our modern society, these episodes have gained recently plenty of interest. During the decades, the Finnish Meteorological Institute (FMI) has collected observations and damage descriptions of severe weather episodes in Finland; thunderstorm days (1887-present), annual number of lightning flashes (1960-present), tornados (1796-present), large hail (1930-present), heavy rainfall (1922-present). The research findings show e.g. that a severe weather event may occur practically anywhere in the country, although in general the probability of occurrence is smaller in the Northern Finland. This study, funded by the Finnish Research Programme on Nuclear Power Plant Safety (SAFIR), combines the individual Finnish severe weather time series' and examines their trends, cross-correlation and correlations with other atmospheric parameters. Furthermore, a numerical weather model (HARMONIE) simulation is performed for a historical severe weather case for analyzing how well the present state-of-the-art models grasp these small-scale weather phenomena. Our results give important background for estimating the Finnish severe weather climate in the future.

Mountain ranges, climate and weathering. Do orogens strengthen or weaken the silicate weathering carbon sink?

NASA Astrophysics Data System (ADS)

Maffre, Pierre; Ladant, Jean-Baptiste; Moquet, Jean-Sébastien; Carretier, Sébastien; Labat, David; Goddéris, Yves

2018-07-01

The role of mountains in the geological evolution of the carbon cycle has been intensively debated for the last decades. Mountains are thought to increase the local physical erosion, which in turns promotes silicate weathering, organic carbon transport and burial, and release of sulfuric acid by dissolution of sulfides. In this contribution, we explore the impact of mountain ranges on silicate weathering. Mountains modify the global pattern of atmospheric circulation as well as the local erosion conditions. Using an IPCC-class climate model, we first estimate the climatic impact of mountains by comparing the present day climate with the climate when all the continents are assumed to be flat. We then use these climate output to calculate weathering changes when mountains are present or absent, using standard expression for physical erosion and a 1D vertical model for rock weathering. We found that large-scale climate changes and enhanced rock supply by erosion due to mountain uplift have opposite effect, with similar orders of magnitude. A thorough testing of the weathering model parameters by data-model comparison shows that best-fit parameterizations lead to a decrease of weathering rate in the absence of mountain by about 20%. However, we demonstrate that solutions predicting an increase in weathering in the absence of mountain cannot be excluded. A clear discrimination between the solutions predicting an increase or a decrease in global weathering is pending on the improvement of the existing global databases for silicate weathering. Nevertheless, imposing a constant and homogeneous erosion rate for models without relief, we found that weathering decrease becomes unequivocal for very low erosion rates (below 10 t/km2/yr). We conclude that further monitoring of continental silicate weathering should be performed with a spatial distribution allowing to discriminate between the various continental landscapes (mountains, plains …).

46 CFR 160.176-4 - Incorporation by reference.

Code of Federal Regulations, 2012 CFR

2012-10-01

... and Elongation, Breaking of Woven Cloth; Grab Method—160.176-13 (2) Method 5132, Strength of Cloth, Tearing; Falling-Pendulum Method—160.176-13 (3) Method 5134, Strength of Cloth, Tearing; Tongue Method—160.176-13 (4) Method 5804.1, Weathering Resistance of Cloth; Accelerated Weathering Method—160.176-8 (5...

Weathering and weathering rates of natural stone

NASA Astrophysics Data System (ADS)

Winkler, Erhard M.

1987-06-01

Physical and chemical weathering were studied as separate processes in the past. Recent research, however, shows that most processes are physicochemical in nature. The rates at which calcite and silica weather by dissolution are dependent on the regional and local climatic environment. The weathering of silicate rocks leaves discolored margins and rinds, a function of the rocks' permeability and of the climatic parameters. Salt action, the greatest disruptive factor, is complex and not yet fully understood in all its phases, but some of the causes of disruption are crystallization pressure, hydration pressure, and hygroscopic attraction of excess moisture. The decay of marble is complex, an interaction between disolution, crack-corrosion, and expansion-contraction cycies triggered by the release of residual stresses. Thin spalls of granites commonly found near the street level of buildings are generally caused by a combination of stress relief and salt action. To study and determine weathering rates of a variety of commercial stones, the National Bureau of Standards erected a Stone Exposure Test Wall in 1948. Of the many types of stone represented, only a few fossiliferous limestones permit a valid measurement of surface reduction in a polluted urban environment.

Comparison of pore space textural characteristics of natural stone exposed to real weathering environment and/or subjected to accelerated weathering tests: implications for durability assessment

NASA Astrophysics Data System (ADS)

Prikryl, Richard; Weishauptová, Zuzana

2017-04-01

One of the key questions in the debate on durability of natural stone is related to the relevance of accelerated weathering tests for durability assessments, specifically whether similar material responses can be achieved? In the recent study, specimens of opuka stone (extremely fine-grained clayey-calcareous silicite) was subjected to accelerated weathering tests in a climatic chamber (sulphur dioxide atmosphere, freezing/thawing). After completion of certain number of cycles, pore space textural characteristics by means of mercury porosimetry were studied. These data were compared with porosimetric data obtained from a piece of stone, sampled from a carved stone altar located in the interior of the St. Vitus Cathedral (Prague, Czech Republic) which was affected by 150-years lasting indoor decay processes (cyclic themohygric stresses due to variable indoor atmospheric conditions). Interestingly, the pore space textural characteristics of these two sets of specimens are closely related and show some distinct features different from fresh, non-weathered material. Our observation therefore supports relevance of some accelerated weathering simulations; however, conditions of these simulations must be based on parameters of real environment.

Predicting motorcycle crash injury severity using weather data and alternative Bayesian multivariate crash frequency models.

PubMed

Cheng, Wen; Gill, Gurdiljot Singh; Sakrani, Taha; Dasu, Mohan; Zhou, Jiao

2017-11-01

Motorcycle crashes constitute a very high proportion of the overall motor vehicle fatalities in the United States, and many studies have examined the influential factors under various conditions. However, research on the impact of weather conditions on the motorcycle crash severity is not well documented. In this study, we examined the impact of weather conditions on motorcycle crash injuries at four different severity levels using San Francisco motorcycle crash injury data. Five models were developed using Full Bayesian formulation accounting for different correlations commonly seen in crash data and then compared for fitness and performance. Results indicate that the models with serial and severity variations of parameters had superior fit, and the capability of accurate crash prediction. The inferences from the parameter estimates from the five models were: an increase in the air temperature reduced the possibility of a fatal crash but had a reverse impact on crashes of other severity levels; humidity in air was not observed to have a predictable or strong impact on crashes; the occurrence of rainfall decreased the possibility of crashes for all severity levels. Transportation agencies might benefit from the research results to improve road safety by providing motorcyclists with information regarding the risk of certain crash severity levels for special weather conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

How is the weather? Forecasting inpatient glycemic control

PubMed Central

Saulnier, George E; Castro, Janna C; Cook, Curtiss B; Thompson, Bithika M

2017-01-01

Aim: Apply methods of damped trend analysis to forecast inpatient glycemic control. Method: Observed and calculated point-of-care blood glucose data trends were determined over 62 weeks. Mean absolute percent error was used to calculate differences between observed and forecasted values. Comparisons were drawn between model results and linear regression forecasting. Results: The forecasted mean glucose trends observed during the first 24 and 48 weeks of projections compared favorably to the results provided by linear regression forecasting. However, in some scenarios, the damped trend method changed inferences compared with linear regression. In all scenarios, mean absolute percent error values remained below the 10% accepted by demand industries. Conclusion: Results indicate that forecasting methods historically applied within demand industries can project future inpatient glycemic control. Additional study is needed to determine if forecasting is useful in the analyses of other glucometric parameters and, if so, how to apply the techniques to quality improvement. PMID:29134125

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics ofmore » the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.« less

Approximating high-dimensional dynamics by barycentric coordinates with linear programming.

PubMed

Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Night Sky Weather Monitoring System Using Fish-Eye CCD

NASA Astrophysics Data System (ADS)

Tomida, Takayuki; Saito, Yasunori; Nakamura, Ryo; Yamazaki, Katsuya

Telescope Array (TA) is international joint experiment observing ultra-high energy cosmic rays. TA employs fluorescence detection technique to observe cosmic rays. In this technique, tho existence of cloud significantly affects quality of data. Therefore, cloud monitoring provides important information. We are developing two new methods for evaluating night sky weather with pictures taken by charge-coupled device (CCD) camera. One is evaluating the amount of cloud with pixels brightness. The other is counting the number of stars with contour detection technique. The results of these methods show clear correlation, and we concluded both the analyses are reasonable methods for weather monitoring. We discuss reliability of the star counting method.

Context-Aware Intelligent Assistant Approach to Improving Pilot's Situational Awareness

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Lodha, Suresh K.

2004-01-01

Faulty decision making due to inaccurate or incomplete awareness of the situation tends to be the prevailing cause of fatal general aviation accidents. Of these accidents, loss of weather situational awareness accounts for the largest number of fatalities. We describe a method for improving weather situational awareness through the support of a contextaware,domain and task knowledgeable, personalized and adaptive assistant. The assistant automatically monitors weather reports for the pilot's route of flight and warns her of detected anomalies. When and how warnings are issued is determined by phase of flight, the pilot s definition of acceptable weather conditions, and the pilot's preferences for automatic notification. In addition to automatic warnings, the pilot is able to verbally query for weather and airport information. By noting the requests she makes during the approach phase of flight, our system learns to provide the information without explicit requests on subsequent flights with similar conditions. We show that our weather assistant decreases the effort required to maintain situational awareness by more than 5.5 times when compared to the conventional method of in-flight weather briefings.

3D Structures & dynamic of the solar corona: inputs from stereovision technics and joined Ground Based and Space Observations for the development of Space Weather

NASA Astrophysics Data System (ADS)

Portier-Fozzani, F.; Noens, J.-C.

In this presentation, I will present different techniques for 3D coronal structures reconstructions. Multiscale vision model (MVM, collaboration with A. Bijaoui) based on wavelet decomposition were used to prepare data. With SOHO/EIT, geometrical constraints were added to be able to measure by stereovision loop size parameters. Thus from these parameters, while including information of several observation wavelenghts, it has been possible by using the CHIANTI code to derive temperature and density along and across the loops, and thus to determine loops physical properties. During the emergence of a new active region, a more sophisticated method, was made to measure the twist degree variations. Loops appear twisted and detwist as expand. The magnetic helicity conservation gives thus important criteria to derive the limit of the stability for a non forced phenomena. Sigmoids, twisted ARLs, sheared filament are related with flares and CMEs. In that case 3D measurement can say upon which level of twist the structure will become unstable. With basic geometrical measures, it has been seen that a new active region reconnected a sigmoide leading to a flare. Also, for CMEs, the measure of the filament ejection angle from stereo EUV images, and the following of temporal evolution from coronagraphic measurement such as done by HACO at the Pic Du Midi Observatory, gives possibility to determine if the CME is coming toward the Earth, and when eventually would be the impact with the magnetosphere. The input of new missions such as STEREO/SECCHI would allow us to better understood the coronal dynamic. Such joined observations GBO-space, used simultaneously together with 3D methods, will allow to develop efficiently forecasting for Space Weather.

Linking the M&Rfi Weather Generator with Agrometeorological Models

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Trnka, Miroslav

2015-04-01

Realistic meteorological inputs (representing the present and/or future climates) for the agrometeorological model simulations are often produced by stochastic weather generators (WGs). This contribution presents some methodological issues and results obtained in our recent experiments. We also address selected questions raised in the synopsis of this session. The input meteorological time series for our experiments are produced by the parametric single site weather generator (WG) Marfi, which is calibrated from the available observational data (or interpolated from surrounding stations). To produce meteorological series representing the future climate, the WG parameters are modified by climate change scenarios, which are prepared by the pattern scaling method: the standardised scenarios derived from Global or Regional Climate Models are multiplied by the change in global mean temperature (ΔTG) determined by the simple climate model MAGICC. The presentation will address following questions: (i) The dependence of the quality of the synthetic weather series and impact results on the WG settings. An emphasis will be put on an effect of conditioning the daily WG on monthly WG (presently being one of our hot topics), which aims at improvement of the reproduction of the low-frequency weather variability. Comparison of results obtained with various WG settings is made in terms of climatic and agroclimatic indices (including extreme temperature and precipitation characteristics and drought indices). (ii) Our methodology accounts for the uncertainties coming from various sources. We will show how the climate change impact results are affected by 1. uncertainty in climate modelling, 2. uncertainty in ΔTG, and 3. uncertainty related to the complexity of the climate change scenario (focusing on an effect of inclusion of changes in variability into the climate change scenarios). Acknowledgements: This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248. The weather generator is being developed within the frame of WG4VALUE project (LD12029), which is supported by Ministry of Education, Youth and Sports and linked to the COST action ES1102 VALUE.

Marine traffic model based on cellular automaton: Considering the change of the ship's velocity under the influence of the weather and sea

NASA Astrophysics Data System (ADS)

Qi, Le; Zheng, Zhongyi; Gang, Longhui

2017-10-01

It was found that the ships' velocity change, which is impacted by the weather and sea, e.g., wind, sea wave, sea current, tide, etc., is significant and must be considered in the marine traffic model. Therefore, a new marine traffic model based on cellular automaton (CA) was proposed in this paper. The characteristics of the ship's velocity change are taken into account in the model. First, the acceleration of a ship was divided into two components: regular component and random component. Second, the mathematical functions and statistical distribution parameters of the two components were confirmed by spectral analysis, curve fitting and auto-correlation analysis methods. Third, by combining the two components, the acceleration was regenerated in the update rules for ships' movement. To test the performance of the model, the ship traffic flows in the Dover Strait, the Changshan Channel and the Qiongzhou Strait were studied and simulated. The results show that the characteristics of ships' velocities in the simulations are consistent with the measured data by Automatic Identification System (AIS). Although the characteristics of the traffic flow in different areas are different, the velocities of ships can be simulated correctly. It proves that the velocities of ships under the influence of weather and sea can be simulated successfully using the proposed model.

The influence of weather on migraine – are migraine attacks predictable?

PubMed Central

Hoffmann, Jan; Schirra, Tonio; Lo, Hendra; Neeb, Lars; Reuter, Uwe; Martus, Peter

2015-01-01

Objective The study aimed at elucidating a potential correlation between specific meteorological variables and the prevalence and intensity of migraine attacks as well as exploring a potential individual predictability of a migraine attack based on meteorological variables and their changes. Methods Attack prevalence and intensity of 100 migraineurs were correlated with atmospheric pressure, relative air humidity, and ambient temperature in 4-h intervals over 12 consecutive months. For each correlation, meteorological parameters at the time of the migraine attack as well as their variation within the preceding 24 h were analyzed. For migraineurs showing a positive correlation, logistic regression analysis was used to assess the predictability of a migraine attack based on meteorological information. Results In a subgroup of migraineurs, a significant weather sensitivity could be observed. In contrast, pooled analysis of all patients did not reveal a significant association. An individual prediction of a migraine attack based on meteorological data was not possible, mainly as a result of the small prevalence of attacks. Interpretation The results suggest that only a subgroup of migraineurs is sensitive to specific weather conditions. Our findings may provide an explanation as to why previous studies, which commonly rely on a pooled analysis, show inconclusive results. The lack of individual attack predictability indicates that the use of preventive measures based on meteorological conditions is not feasible. PMID:25642431

Effects of atmospheric variability on energy utilization and conservation. [Space heating energy demand modeling; Program HEATLOAD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reiter, E.R.; Johnson, G.R.; Somervell, W.L. Jr.

Research conducted between 1 July 1975 and 31 October 1976 is reported. A ''physical-adaptive'' model of the space-conditioning demand for energy and its response to changes in weather regimes was developed. This model includes parameters pertaining to engineering factors of building construction, to weather-related factors, and to socio-economic factors. Preliminary testing of several components of the model on the city of Greeley, Colorado, yielded most encouraging results. Other components, especially those pertaining to socio-economic factors, are still under development. Expansion of model applications to different types of structures and larger regions is presently underway. A CRT-display model for energy demandmore » within the conterminous United States also has passed preliminary tests. A major effort was expended to obtain disaggregated data on energy use from utility companies throughout the United States. The study of atmospheric variability revealed that the 22- to 26-day vacillation in the potential and kinetic energy modes of the Northern Hemisphere is related to the behavior of the planetary long-waves, and that the midwinter dip in zonal available potential energy is reflected in the development of blocking highs. Attempts to classify weather patterns over the eastern and central United States have proceeded satisfactorily to the point where testing of our method for longer time periods appears desirable.« less

Colluvial deposits as a possible weathering reservoir in uplifting mountains

NASA Astrophysics Data System (ADS)

Carretier, Sébastien; Goddéris, Yves; Martinez, Javier; Reich, Martin; Martinod, Pierre

2018-03-01

The role of mountain uplift in the evolution of the global climate over geological times is controversial. At the heart of this debate is the capacity of rapid denudation to drive silicate weathering, which consumes CO2. Here we present the results of a 3-D model that couples erosion and weathering during mountain uplift, in which, for the first time, the weathered material is traced during its stochastic transport from the hillslopes to the mountain outlet. To explore the response of weathering fluxes to progressively cooler and drier climatic conditions, we run model simulations accounting for a decrease in temperature with or without modifications in the rainfall pattern based on a simple orographic model. At this stage, the model does not simulate the deep water circulation, the precipitation of secondary minerals, variations in the pH, below-ground pCO2, and the chemical affinity of the water in contact with minerals. Consequently, the predicted silicate weathering fluxes probably represent a maximum, although the predicted silicate weathering rates are within the range of silicate and total weathering rates estimated from field data. In all cases, the erosion rate increases during mountain uplift, which thins the regolith and produces a hump in the weathering rate evolution. This model thus predicts that the weathering outflux reaches a peak and then falls, consistent with predictions of previous 1-D models. By tracking the pathways of particles, the model can also consider how lateral river erosion drives mass wasting and the temporary storage of colluvial deposits on the valley sides. This reservoir is comprised of fresh material that has a residence time ranging from several years up to several thousand years. During this period, the weathering of colluvium appears to sustain the mountain weathering flux. The relative weathering contribution of colluvium depends on the area covered by regolith on the hillslopes. For mountains sparsely covered by regolith during cold periods, colluvium produces most of the simulated weathering flux for a large range of erosion parameters and precipitation rate patterns. In addition to other reservoirs such as deep fractured bedrock, colluvial deposits may help to maintain a substantial and constant weathering flux in rapidly uplifting mountains during cooling periods.

Understanding the roles of ligand promoted dissolution, water column saturation and hydrological properties on intense basalt weathering using reactive transport and watershed-scale hydrologic modeling

NASA Astrophysics Data System (ADS)

Perez Fodich, A.; Walter, M. T.; Derry, L. A.

2016-12-01

The interaction of rocks with rainwater generates physical and chemical changes, which ultimately culminates in soil development. The addition of catalyzers such as plants, atmospheric gases and hydrological properties will result in more intense and/or faster weathering transformations. The intensity of weathering across the Island of Hawaii is strongly correlated with exposure age and time-integrated precipitation. Intense weathering has resulted from interaction between a thermodynamically unstable lithology, high water/rock ratios, atmospheric gases (O2, CO2) and biota as an organic acid and CO2 producer. To further investigate the role of different weathering agents we have developed 1-D reactive transport models (RTM) to understand mineralogical and fluid chemistry changes in the initially basaltic porous media. The initial meso-scale heterogeneity of porosity makes it difficult for RTMs to capture changes in runoff/groundwater partitioning. Therefore, hydraulic properties (hydraulic conductivity and aquifer depth) are modeled as a watershed parameter appropriate for this system where sub-surface hydraulic data is scarce(1). Initial results agree with field data in a broad sense: different rainfall regimes and timescales show depletion of mobile cations, increasingly low pH, congruent dissolution of olivine and pyroxene, incongruent dissolution of plagioclase and basaltic glass, precipitation of non-crystalline allophane and ferrihydrite, and porosity changes due to dissolution and precipitation of minerals; ultimately Al and Fe are also exported from the system. RTM is used to examine the roles of unsaturation in the soil profile, ligand promoted dissolution of Al- and Fe-bearing phases, and Fe-oxide precipitation at the outcrop scale. Also, we aim to test the use of recession flow analysis to model watershed-scale hydrological properties to extrapolate changes in the runoff/groundwater partitioning. The coupling between weathering processes and hydrologic properties is a fundamental driver of the evolution of volcanic landscapes and weathering fluxes. 1. G. F. Mendoza, T. S. Steenhuis, M. T. Walter, J. Y. Parlange, Estimating basin-wide hydraulic parameters of a semi-arid mountainous watershed by recession-flow analysis. Journal of Hydrology 279, 57-69 (2003).

The Potential of Tropospheric Gradients for Regional Precipitation Prediction

NASA Astrophysics Data System (ADS)

Boisits, Janina; Möller, Gregor; Wittmann, Christoph; Weber, Robert

2017-04-01

Changes of temperature and humidity in the neutral atmosphere cause variations in tropospheric path delays and tropospheric gradients. By estimating zenith wet delays (ZWD) and gradients using a GNSS reference station network the obtained time series provide information about spatial and temporal variations of water vapour in the atmosphere. Thus, GNSS-based tropospheric parameters can contribute to the forecast of regional precipitation events. In a recently finalized master thesis at TU Wien the potential of tropospheric gradients for weather prediction was investigated. Therefore, ZWD and gradient time series at selected GNSS reference stations were compared to precipitation data over a period of six months (April to September 2014). The selected GNSS stations form two test areas within Austria. All required meteorological data was provided by the Central Institution for Meteorology and Geodynamics (ZAMG). Two characteristics in ZWD and gradient time series can be anticipated in case of an approaching weather front. First, an induced asymmetry in tropospheric delays results in both, an increased magnitude of the gradient and in gradients pointing towards the weather front. Second, an increase in ZWD reflects the increased water vapour concentration right before a precipitation event. To investigate these characteristics exemplary test events were processed. On the one hand, the sequence of the anticipated increase in ZWD at each GNSS station obtained by cross correlation of the time series indicates the direction of the approaching weather front. On the other hand, the corresponding peak in gradient time series allows the deduction of the direction of movement as well. To verify the results precipitation data from ZAMG was used. It can be deduced, that tropospheric gradients show high potential for predicting precipitation events. While ZWD time series rather indicate the orientation of the air mass boundary, gradients rather indicate the direction of movement of an approaching weather front. Additionally our investigations have shown that gradients are able to capture the characteristics of an approaching weather front twenty to thirty hours before the precipitation event, which allows a first indication well in advance. Thus in conclusion, the utilization of GNSS tropospheric parameters, in particular tropospheric gradients, has the potential to contribute substantially to weather forecasting models.

Sensitivity of turbine-height wind speeds to parameters in planetary boundary-layer and surface-layer schemes in the weather research and forecasting model

DOE PAGES

Yang, Ben; Qian, Yun; Berg, Larry K.; ...

2016-07-21

We evaluate the sensitivity of simulated turbine-height wind speeds to 26 parameters within the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary-layer scheme and MM5 surface-layer scheme of the Weather Research and Forecasting model over an area of complex terrain. An efficient sampling algorithm and generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of simulated turbine-height wind speeds. The results indicate that most of the variability in the ensemble simulations is due to parameters related to the dissipation of turbulent kinetic energy (TKE), Prandtl number, turbulent length scales, surface roughness, and the von Kármán constant. Themore » parameter associated with the TKE dissipation rate is found to be most important, and a larger dissipation rate produces larger hub-height wind speeds. A larger Prandtl number results in smaller nighttime wind speeds. Increasing surface roughness reduces the frequencies of both extremely weak and strong airflows, implying a reduction in the variability of wind speed. All of the above parameters significantly affect the vertical profiles of wind speed and the magnitude of wind shear. Lastly, the relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability.« less

Sensitivity of turbine-height wind speeds to parameters in planetary boundary-layer and surface-layer schemes in the weather research and forecasting model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Ben; Qian, Yun; Berg, Larry K.

We evaluate the sensitivity of simulated turbine-height wind speeds to 26 parameters within the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary-layer scheme and MM5 surface-layer scheme of the Weather Research and Forecasting model over an area of complex terrain. An efficient sampling algorithm and generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of simulated turbine-height wind speeds. The results indicate that most of the variability in the ensemble simulations is due to parameters related to the dissipation of turbulent kinetic energy (TKE), Prandtl number, turbulent length scales, surface roughness, and the von Kármán constant. Themore » parameter associated with the TKE dissipation rate is found to be most important, and a larger dissipation rate produces larger hub-height wind speeds. A larger Prandtl number results in smaller nighttime wind speeds. Increasing surface roughness reduces the frequencies of both extremely weak and strong airflows, implying a reduction in the variability of wind speed. All of the above parameters significantly affect the vertical profiles of wind speed and the magnitude of wind shear. Lastly, the relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability.« less

Parameter Estimation and Sensitivity Analysis of an Urban Surface Energy Balance Parameterization at a Tropical Suburban Site

NASA Astrophysics Data System (ADS)

Harshan, S.; Roth, M.; Velasco, E.

2014-12-01

Forecasting of the urban weather and climate is of great importance as our cities become more populated and considering the combined effects of global warming and local land use changes which make urban inhabitants more vulnerable to e.g. heat waves and flash floods. In meso/global scale models, urban parameterization schemes are used to represent the urban effects. However, these schemes require a large set of input parameters related to urban morphological and thermal properties. Obtaining all these parameters through direct measurements are usually not feasible. A number of studies have reported on parameter estimation and sensitivity analysis to adjust and determine the most influential parameters for land surface schemes in non-urban areas. Similar work for urban areas is scarce, in particular studies on urban parameterization schemes in tropical cities have so far not been reported. In order to address above issues, the town energy balance (TEB) urban parameterization scheme (part of the SURFEX land surface modeling system) was subjected to a sensitivity and optimization/parameter estimation experiment at a suburban site in, tropical Singapore. The sensitivity analysis was carried out as a screening test to identify the most sensitive or influential parameters. Thereafter, an optimization/parameter estimation experiment was performed to calibrate the input parameter. The sensitivity experiment was based on the "improved Sobol's global variance decomposition method" . The analysis showed that parameters related to road, roof and soil moisture have significant influence on the performance of the model. The optimization/parameter estimation experiment was performed using the AMALGM (a multi-algorithm genetically adaptive multi-objective method) evolutionary algorithm. The experiment showed a remarkable improvement compared to the simulations using the default parameter set. The calibrated parameters from this optimization experiment can be used for further model validation studies to identify inherent deficiencies in model physics.

The Weather Forecast Using Data Mining Research Based on Cloud Computing.

NASA Astrophysics Data System (ADS)

Wang, ZhanJie; Mazharul Mujib, A. B. M.

2017-10-01

Weather forecasting has been an important application in meteorology and one of the most scientifically and technologically challenging problem around the world. In my study, we have analyzed the use of data mining techniques in forecasting weather. This paper proposes a modern method to develop a service oriented architecture for the weather information systems which forecast weather using these data mining techniques. This can be carried out by using Artificial Neural Network and Decision tree Algorithms and meteorological data collected in Specific time. Algorithm has presented the best results to generate classification rules for the mean weather variables. The results showed that these data mining techniques can be enough for weather forecasting.

Mode and climatic factors effect on energy losses in transient heat modes of transmission lines

NASA Astrophysics Data System (ADS)

Bigun, A. Ya; Sidorov, O. A.; Osipov, D. S.; Girshin, S. S.; Goryunov, V. N.; Petrova, E. V.

2018-01-01

Electrical energy losses increase in modern grids. The losses are connected with an increase in consumption. Existing models of electric power losses estimation considering climatic factors do not allow estimating the cable temperature in real time. Considering weather and mode factors in real time allows to meet effectively and safely the consumer’s needs to minimize energy losses during transmission, to use electric power equipment effectively. These factors increase an interest in the evaluation of the dynamic thermal mode of overhead transmission lines conductors. The article discusses an approximate analytic solution of the heat balance equation in the transient operation mode of overhead lines based on the least squares method. The accuracy of the results obtained is comparable with the results of solving the heat balance equation of transient thermal mode with the Runge-Kutt method. The analysis of mode and climatic factors effect on the cable temperature in a dynamic thermal mode is presented. The calculation of the maximum permissible current for variation of weather conditions is made. The average electric energy losses during the transient process are calculated with the change of wind, air temperature and solar radiation. The parameters having the greatest effect on the transmission capacity are identified.

On the analytic and numeric optimisation of airplane trajectories under real atmospheric conditions

NASA Astrophysics Data System (ADS)

Gonzalo, J.; Domínguez, D.; López, D.

2014-12-01

From the beginning of aviation era, economic constraints have forced operators to continuously improve the planning of the flights. The revenue is proportional to the cost per flight and the airspace occupancy. Many methods, the first started in the middle of last century, have explore analytical, numerical and artificial intelligence resources to reach the optimal flight planning. In parallel, advances in meteorology and communications allow an almost real-time knowledge of the atmospheric conditions and a reliable, error-bounded forecast for the near future. Thus, apart from weather risks to be avoided, airplanes can dynamically adapt their trajectories to minimise their costs. International regulators are aware about these capabilities, so it is reasonable to envisage some changes to allow this dynamic planning negotiation to soon become operational. Moreover, current unmanned airplanes, very popular and often small, suffer the impact of winds and other weather conditions in form of dramatic changes in their performance. The present paper reviews analytic and numeric solutions for typical trajectory planning problems. Analytic methods are those trying to solve the problem using the Pontryagin principle, where influence parameters are added to state variables to form a split condition differential equation problem. The system can be solved numerically -indirect optimisation- or using parameterised functions -direct optimisation-. On the other hand, numerical methods are based on Bellman's dynamic programming (or Dijkstra algorithms), where the fact that two optimal trajectories can be concatenated to form a new optimal one if the joint point is demonstrated to belong to the final optimal solution. There is no a-priori conditions for the best method. Traditionally, analytic has been more employed for continuous problems whereas numeric for discrete ones. In the current problem, airplane behaviour is defined by continuous equations, while wind fields are given in a discrete grid at certain time intervals. The research demonstrates advantages and disadvantages of each method as well as performance figures of the solutions found for typical flight conditions under static and dynamic atmospheres. This provides significant parameters to be used in the selection of solvers for optimal trajectories.

Realtime Space Weather Forecasts Via Android Phone App

NASA Astrophysics Data System (ADS)

Crowley, G.; Haacke, B.; Reynolds, A.

2010-12-01

For the past several years, ASTRA has run a first-principles global 3-D fully coupled thermosphere-ionosphere model in real-time for space weather applications. The model is the Thermosphere-Ionosphere Mesosphere Electrodynamics General Circulation Model (TIMEGCM). ASTRA also runs the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) in real-time. Using AMIE to drive the high latitude inputs to the TIMEGCM produces high fidelity simulations of the global thermosphere and ionosphere. These simulations can be viewed on the Android Phone App developed by ASTRA. The SpaceWeather app for the Android operating system is free and can be downloaded from the Google Marketplace. We present the current status of realtime thermosphere-ionosphere space-weather forcasting and discuss the way forward. We explore some of the issues in maintaining real-time simulations with assimilative data feeds in a quasi-operational setting. We also discuss some of the challenges of presenting large amounts of data on a smartphone. The ASTRA SpaceWeather app includes the broadest and most unique range of space weather data yet to be found on a single smartphone app. This is a one-stop-shop for space weather and the only app where you can get access to ASTRA’s real-time predictions of the global thermosphere and ionosphere, high latitude convection and geomagnetic activity. Because of the phone's GPS capability, users can obtain location specific vertical profiles of electron density, temperature, and time-histories of various parameters from the models. The SpaceWeather app has over 9000 downloads, 30 reviews, and a following of active users. It is clear that real-time space weather on smartphones is here to stay, and must be included in planning for any transition to operational space-weather use.

Recent Activities on the Embrace Space Weather Regional Warning Center: the New Space Weather Data Center

NASA Astrophysics Data System (ADS)

Denardini, Clezio Marcos; Dal Lago, Alisson; Mendes, Odim; Batista, Inez S.; SantAnna, Nilson; Gatto, Rubens; Takahashi, Hisao; Costa, D. Joaquim; Banik Padua, Marcelo; Campos Velho, Haroldo

2016-07-01

On August 2007 the National Institute for Space Research started a task force to develop and operate a space weather program, which is known by the acronyms Embrace that stands for the Portuguese statement "Estudo e Monitoramento BRAasileiro de Clima Espacial" Program (Brazilian Space Weather Study and Monitoring program). The mission of the Embrace/INPE program is to monitor the Solar-Terrestrial environment, the magnetosphere, the upper atmosphere and the ground induced currents to prevent effects on technological and economic activities. The Embrace/INPE system monitors the physical parameters of the Sun-Earth environment, such as Active Regions (AR) in the Sun and solar radiation by using radio telescope, Coronal Mass Ejection (CME) information by satellite and ground-based cosmic ray monitoring, geomagnetic activity by the magnetometer network, and ionospheric disturbance by ionospheric sounders and using data collected by four GPS receiver network, geomagnetic activity by a magnetometer network, and provides a forecasting for Total Electronic Content (TEC) - 24 hours ahead - using a version of the SUPIM model which assimilates the two latter data using nudging approach. Most of these physical parameters are daily published on the Brazilian space weather program web portal, related to the entire network sensors available. Regarding outreach, it has being published a daily bulletin in Portuguese and English with the status of the space weather environment on the Sun, the Interplanetary Medium and close to the Earth. Since December 2011, all these activities are carried out at the Embrace Headquarter, a building located at the INPE's main campus. Recently, a comprehensive data bank and an interface layer are under commissioning to allow an easy and direct access to all the space weather data collected by Embrace through the Embrace web Portal. The information being released encompasses data from: (a) the Embrace Digisonde Network (Embrace DigiNet) that monitors the ionospheric profiles in two equatorial sites and in two low latitude sites; (b) several solar radio telescopes to monitor solar activity (under development); (c) the matrix of the GNSS TEC map over South America; (d) the Embrace Airglow All-sky Imagers Network (Embrace GlowNet); and (d) the Embrace Magnetometer Network (Embrace Magnet), all of them in South America. Also, the system allows subscription to space weather alerts and reports. Contacting Author: C. M. Denardini (clezio.denardin@inpe.br)

Attic or Roof? An Evaluation of Two Advanced Weatherization Packages

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neuhauser, Ken

2012-06-01

This project examines implementation of advanced retrofit measures in the context of a large-scale weatherization program and the archetypal Chicago brick bungalow. One strategy applies best practice air sealing methods and a standard insulation method to the attic floor. The other strategy creates an unvented roof assembly using materials and methods typically available to weatherization contractors. Through implementations of the retrofit strategies in a total of eight (8) test homes, the research found that the two different strategies achieve similar reductions in air leakage measurement (55%) and predicted energy performance (18%) relative to the pre-retrofit conditions.

Comparison of different models for ground-level atmospheric turbulence strength (C(n)(2)) prediction with a new model according to local weather data for FSO applications.

PubMed

Arockia Bazil Raj, A; Arputha Vijaya Selvi, J; Durairaj, S

2015-02-01

Atmospheric parameters strongly affect the performance of free-space optical communication (FSOC) systems when the optical wave is propagating through the inhomogeneous turbulence transmission medium. Developing a model to get an accurate prediction of the atmospheric turbulence strength (C(n)(2)) according to meteorological parameters (weather data) becomes significant to understand the behavior of the FSOC channel during different seasons. The construction of a dedicated free-space optical link for the range of 0.5 km at an altitude of 15.25 m built at Thanjavur (Tamil Nadu) is described in this paper. The power level and beam centroid information of the received signal are measured continuously with weather data at the same time using an optoelectronic assembly and the developed weather station, respectively, and are recorded in a data-logging computer. Existing models that exhibit relatively fewer prediction errors are briefed and are selected for comparative analysis. Measured weather data (as input factors) and C(n)(2) (as a response factor) of size [177,147×4] are used for linear regression analysis and to design mathematical models more suitable in the test field. Along with the model formulation methodologies, we have presented the contributions of the input factors' individual and combined effects on the response surface and the coefficient of determination (R(2)) estimated using analysis of variance tools. An R(2) value of 98.93% is obtained using the new model, model equation V, from a confirmatory test conducted with a testing data set of size [2000×4]. In addition, the prediction accuracies of the selected and the new models are investigated during different seasons in a one-year period using the statistics of day, week-averaged, month-averaged, and seasonal-averaged diurnal Cn2 profiles, and are verified in terms of the sum of absolute error (SAE). A Cn2 prediction maximum average SAE of 2.3×10(-13)  m(-2/3) is achieved using the new model in a longer range of dynamic meteorological parameters during the different local seasons.

Smsynth: AN Imagery Synthesis System for Soil Moisture Retrieval

NASA Astrophysics Data System (ADS)

Cao, Y.; Xu, L.; Peng, J.

2018-04-01

Soil moisture (SM) is a important variable in various research areas, such as weather and climate forecasting, agriculture, drought and flood monitoring and prediction, and human health. An ongoing challenge in estimating SM via synthetic aperture radar (SAR) is the development of the retrieval SM methods, especially the empirical models needs as training samples a lot of measurements of SM and soil roughness parameters which are very difficult to acquire. As such, it is difficult to develop empirical models using realistic SAR imagery and it is necessary to develop methods to synthesis SAR imagery. To tackle this issue, a SAR imagery synthesis system based on the SM named SMSynth is presented, which can simulate radar signals that are realistic as far as possible to the real SAR imagery. In SMSynth, SAR backscatter coefficients for each soil type are simulated via the Oh model under the Bayesian framework, where the spatial correlation is modeled by the Markov random field (MRF) model. The backscattering coefficients simulated based on the designed soil parameters and sensor parameters are added into the Bayesian framework through the data likelihood where the soil parameters and sensor parameters are set as realistic as possible to the circumstances on the ground and in the validity range of the Oh model. In this way, a complete and coherent Bayesian probabilistic framework is established. Experimental results show that SMSynth is capable of generating realistic SAR images that suit the needs of a large amount of training samples of empirical models.

Developing New Strategies for Coping with Weather: Work in Alaskan and Canadian Coastal Communities

NASA Astrophysics Data System (ADS)

Atkinson, D. E.

2014-12-01

A changing climate is manifested at ground level through the day to day weather. For all Northern residents - community, industrial, operational and response - the need to think about the weather is ever present. Northern residents, and in particular, indigenous community residents, fully understand implications of the weather, however, a comment that has been heard more often is that old ways of knowing are not as reliable as they once were. Weather patterns seem less consistent and subject to more rapid fluctuations. Compromised traditional ways of knowing puts those who need to travel or hunt at greater risk. One response to adapt to this emerging reality is to make greater use of western sources of information, such as weather data and charts provided by NOAA's National Weather Service or Environment Canada. The federal weather agencies have very large and complex forecasting regions to cover, and so one problem is that it can be difficult to provide perfectly tailored forecasts, that cover all possible problems, right down to the very local scale in the communities. Only those affected have a complete feel for their own concerns. Thus, key to a strategy to improve the utility of available weather information is a linking of local-scale manifestations of problematic weather to the larger-scale weather patterns. This is done in two ways: by direct consultation with Northern residents, and by installation of equipment to measure parameters of interest to residents, which are not already being measured. This talk will overview projects in coastal Alaska and Canada targeting this objective. The challenge of designing and conducting interviews, and then of harvesting relevant information, will be visited using examples from the three major contexts: coastal community, industrial, and operational. Examples of how local comments can be married to weather products will be presented.

The UCSD Time-dependent Tomography and IPS use for Exploring Space Weather Events

NASA Astrophysics Data System (ADS)

Yu, H. S.; Jackson, B. V.; Buffington, A.; Hick, P. P.; Tokumaru, M.; Odstrcil, D.; Kim, J.; Yun, J.

2016-12-01

The University of California, San Diego (UCSD) time-dependent, iterative, kinematic reconstruction technique has been used and expanded upon for over two decades. It provides some of the most-accurate predictions and three-dimensional (3D) analyses of heliospheric solar-wind parameters now available using interplanetary scintillation (IPS) data. The parameters provided include reconstructions of velocity, density, and three-component magnetic fields. Precise time-dependent results are now obtained at any solar distance in the inner heliosphere using ISEE (formerly STELab), Japan, IPS data sets, and can be used to drive 3D-MHD models including ENLIL. Using IPS data, these reconstructions provide a real-time prediction of the global solar wind parameters across the whole heliosphere with a time cadence of about one day (see http://ips.ucsd.edu). Here we compare the results (such as density, velocity, and magnetic fields) from the IPS tomography with different in-situ measurements and discuss several specific space weather events that demonstrate the issues resulting from these analyses.

Mapping erosion susceptibility by a multivariate statistical method: A case study from the Ayvalık region, NW Turkey

NASA Astrophysics Data System (ADS)

Akgün, Aykut; Türk, Necdet

2011-09-01

Erosion is one of the most important natural hazard phenomena in the world, and it poses a significant threat to Turkey in terms of land degredation and desertification. To cope with this problem, we must determine which areas are erosion-prone. Many studies have been carried out and different models and methods have been used to this end. In this study, we used a logistic regression to prepare an erosion susceptibility map for the Ayvalık region in Balıkesir (NW Turkey). The following were our assessment parameters: weathering grades of rocks, slope gradient, structural lineament density, drainage density, land cover, stream power index (SPI) and profile curvature. These were processed by Idrisi Kilimanjaro GIS software. We used logistic regression analysis to relate predictor variables to the occurrence or non-occurrence of gully erosion sites within geographic cells, and then we used this relationship to produce a probability map for future erosion sites. The results indicate that lineament density, weathering grades of rocks and drainage density are the most important variables governing erosion susceptibility. Other variables, such as land cover and slope gradient, were revealed as secondary important variables. Highly weathered basalt, andesite, basaltic andesite and lacustrine sediments were the units most susceptible to erosion. In order to calculate the prediction accuracy of the erosion susceptibility map generated, we compared it with the map showing the gully erosion areas. On the basis of this comparison, the area under curvature (AUC) value was found to be 0.81. This result suggests that the erosion susceptibility map we generated is accurate.

Meteorological Conditions for Functioning Automobile Transport in Moscow Region

NASA Astrophysics Data System (ADS)

Shiryaeva, Alexandra

2017-04-01

The purpose of this study is to investigate weather and climate conditions of functioning automobile transport in Moscow region. For this, statistics on the daily number of accidents in the City of Moscow in 2013-2014 were studied and compared with the weather conditions. Various weather phenomena and meteorological parameters that affect the increase and decrease in the number of accidents in warm and cold seasons were identified; the extent of this influence was assessed. Moreover, an analysis of the distribution and change of the frequency of occurrence of these phenomena and meteorological parameters in 1961-2010 in Moscow region was conducted. In the cold season, there are much more weather events influencing the growth in the number of accidents than in the warm season. Fallout of more than 2 cm of snow per date, the reduction in meteorological visibility, drizzle and snow storms lead to an increase of accident rate by 5-15%. In the warm season, when thunderstorms and heavy rainfall there is a decrease in accidents; increase in the number of accidents happens in hot weather (maximum air temperatures over +30 °C). In the period 1991-2010 compared to 1961-1990 in the Moscow oblast the sustained cold period and amount of precipitation under negative air temperature has reduced; a decrease in the number of days with reduced visibility range and the offset of the date of the fallout of the first snow aside winter months is observed, which is favorable for automobile transport. At the same time, there is an increase in the number of days with transitions of air temperature through 0 °C, and the number of hot days, which negatively affects the functioning automobile transport.

Early stage of weathering of medieval-like potash-lime model glass: evaluation of key factors.

PubMed

Gentaz, Lucile; Lombardo, Tiziana; Loisel, Claudine; Chabas, Anne; Vallotto, Marta

2011-02-01

Throughout history, a consequent part of the medieval stained glass windows have been lost, mostly because of deliberate or accidental mechanic destruction during war or revolution, but, in some cases, did not withstand the test of time simply because of their low durability. Indeed, the glasses that remain nowadays are for many in a poor state of conservation and are heavily deteriorated. Under general exposure conditions, stained glass windows undergo different kinds of weathering processes that modify their optical properties, chemistry, and structure: congruent dissolution, leaching, and particle deposition (the combination of those two leading together to the formation of neocrystallisations and eventually crusts). Previous research has studied the weathering forms and the mechanisms from which they are originated, some others identified the main environmental parameters responsible for the deterioration and highlighted that both intrinsic (glass composition) and extrinsic (environmental parameters) factors influence glass degradation. Nevertheless, a clear quantification of the impact of the different deterioration extrinsic factors has not been performed. By analysing the results obtained with model glass (durable and nondurable) exposed in the field, this paper proposes a simple mathematical computation evaluating the contribution of the different weathering factors for the early stages of exposure of the stained glasses. In the case of non durable glass, water runoff was identified as the main factor inducing the leaching (83.4 ± 2.6% contribution), followed by gas (6.4 ± 1.5%) and particle deposition (6.8 ± 2.2%) and adsorbed water (3.4 ± 0.6%). Moreover, it was shown that the extrinsic stimuli superimposes with the impact of glass composition to the weathering. Those results show that the role played by dry deposition, even if less important than that of the wet deposition, cannot be neglected.

HiRadProp: High-Frequency Modeling and Prediction of Tropospheric Radiopropagation Parameters from Ground-Based-Multi-Channel Radiometric Measurements between Ka and W Band

DTIC Science & Technology

2016-05-11

new physically -based prediction models for all-weather path attenuation estimation at Ka, V and W band from multi- channel microwave radiometric data...of new physically -based prediction models for all-weather path attenuation estimation at Ka, V and W band from multi- channel microwave radiometric...the medium behavior at these frequency bands from both a physical and a statistical point of view (e.g., [5]-[7]). However, these campaigns are

Mobility Monitoring System and Vehicle Performance Recorder. Revision.

DTIC Science & Technology

1985-09-01

Activity AREA & WORK UNIT NUMBERS ATTN: STECS-DA-I None Aberdeen Proving Ground, MD 21005-5059 II. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE...included vehicle parameters that indicated the effects of non-vehicle variables (i.e., driver, course, weather). Parameters from the first two categories...category, driver and course were the two considered to have the greatest effect on the conduct of the test. Vehicle parameters were considered which would

Surface atmospheric extremes (Launch and transportation areas)

NASA Technical Reports Server (NTRS)

1972-01-01

The effects of extreme values of surface and low altitude atmospheric parameters on space vehicle design, tests, and operations are discussed. Atmospheric extremes from the surface to 150 meters for geographic locations of interest to NASA are given. Thermal parameters (temperature and solar radiation), humidity, pressure, and atmospheric electricity (lighting and static) are presented. Weather charts and tables are included.

A second generation climate index for tourism (CIT): specification and verification.

PubMed

de Freitas, C R; Scott, Daniel; McBoyle, Geoff

2008-05-01

Climate is a key resource for many types of tourism and as such can be measured and evaluated. An index approach is required for this task because of the multifaceted nature of weather and the complex ways that weather variables come together to give meaning to climate for tourism. Here we address the deficiencies of past indices by devising a theoretically sound and empirically tested method that integrates the various facets of climate and weather into a single index called the Climate Index for Tourism (CIT). CIT rates the climate resource for activities that are highly climate/weather sensitive, specifically, beach "sun, sea and sand" (3S) holidays. CIT integrates thermal (T), aesthetic (A) and physical (P) facets of weather, which are combined in a weather typology matrix to determine a climate satisfaction rating that ranges from very poor (1=unacceptable) to very good (7=optimal). Parameter A refers to sky condition and P to rain or high wind. T is the body-atmosphere energy balance that integrates the environmental and physiological thermal variables, such as solar heat load, heat loss by convection (wind) and by evaporation (sweating), longwave radiation exchange and metabolic heat (activity level). Rather than use T as a net energy (calorific) value, CIT requires that it be expressed as thermal sensation using the standard nine-point ASHRAE scale ("very hot" to "very cold"). In this way, any of the several body-atmosphere energy balance schemes available may be used, maximizing the flexibility of the index. A survey (N=331) was used to validate the initial CIT. Respondents were asked to rate nine thermal states (T) with different sky conditions (A). They were also asked to assess the impact of high winds or prolonged rain on the perceived quality of the overall weather condition. The data was analysed statistically to complete the weather typology matrix, which covered every possible combination of T, A and P. Conditions considered to be optimal (CIT class 6-7) for 3S tourism were those that were "slightly warm" with clear skies or scattered cloud (

A second generation climate index for tourism (CIT): specification and verification

NASA Astrophysics Data System (ADS)

de Freitas, C. R.; Scott, Daniel; McBoyle, Geoff

2008-05-01

Climate is a key resource for many types of tourism and as such can be measured and evaluated. An index approach is required for this task because of the multifaceted nature of weather and the complex ways that weather variables come together to give meaning to climate for tourism. Here we address the deficiencies of past indices by devising a theoretically sound and empirically tested method that integrates the various facets of climate and weather into a single index called the Climate Index for Tourism (CIT). CIT rates the climate resource for activities that are highly climate/weather sensitive, specifically, beach “sun, sea and sand” (3S) holidays. CIT integrates thermal (T), aesthetic (A) and physical (P) facets of weather, which are combined in a weather typology matrix to determine a climate satisfaction rating that ranges from very poor (1 = unacceptable) to very good (7 = optimal). Parameter A refers to sky condition and P to rain or high wind. T is the body-atmosphere energy balance that integrates the environmental and physiological thermal variables, such as solar heat load, heat loss by convection (wind) and by evaporation (sweating), longwave radiation exchange and metabolic heat (activity level). Rather than use T as a net energy (calorific) value, CIT requires that it be expressed as thermal sensation using the standard nine-point ASHRAE scale (“very hot” to “very cold”). In this way, any of the several body-atmosphere energy balance schemes available may be used, maximizing the flexibility of the index. A survey ( N = 331) was used to validate the initial CIT. Respondents were asked to rate nine thermal states (T) with different sky conditions (A). They were also asked to assess the impact of high winds or prolonged rain on the perceived quality of the overall weather condition. The data was analysed statistically to complete the weather typology matrix, which covered every possible combination of T, A and P. Conditions considered to be optimal (CIT class 6-7) for 3S tourism were those that were “slightly warm” with clear skies or scattered cloud (≤25% cloud). Acceptable conditions (CIT = 4-5) fell within the thermal range “indifferent” to “hot” even when the sky was overcast. Wind equal to or in excess of 6 m/s (22 km/h) or rain resulted in the CIT rating dropping to 1 or 2 (unacceptable) and was thus an override of pleasant thermal conditions. Further cross-cultural research is underway to examine whether climate preferences vary with different social and cultural tourist segments internationally.

Application of Metaheuristic and Deterministic Algorithms for Aircraft Reference Trajectory Optimization =

NASA Astrophysics Data System (ADS)

Murrieta Mendoza, Alejandro

Aircraft reference trajectory is an alternative method to reduce fuel consumption, thus the pollution released to the atmosphere. Fuel consumption reduction is of special importance for two reasons: first, because the aeronautical industry is responsible of 2% of the CO2 released to the atmosphere, and second, because it will reduce the flight cost. The aircraft fuel model was obtained from a numerical performance database which was created and validated by our industrial partner from flight experimental test data. A new methodology using the numerical database was proposed in this thesis to compute the fuel burn for a given trajectory. Weather parameters such as wind and temperature were taken into account as they have an important effect in fuel burn. The open source model used to obtain the weather forecast was provided by Weather Canada. A combination of linear and bi-linear interpolations allowed finding the required weather data. The search space was modelled using different graphs: one graph was used for mapping the different flight phases such as climb, cruise and descent, and another graph was used for mapping the physical space in which the aircraft would perform its flight. The trajectory was optimized in its vertical reference trajectory using the Beam Search algorithm, and a combination of the Beam Search algorithm with a search space reduction technique. The trajectory was optimized simultaneously for the vertical and lateral reference navigation plans while fulfilling a Required Time of Arrival constraint using three different metaheuristic algorithms: the artificial bee's colony, and the ant colony optimization. Results were validated using the software FlightSIMRTM, a commercial Flight Management System, an exhaustive search algorithm, and as flown flights obtained from flightawareRTM. All algorithms were able to reduce the fuel burn, and the flight costs. None None None None None None None

Spatio-temporal patterns and source apportionment of pollution in Qiantang River (China) using neural-based modeling and multivariate statistical techniques

NASA Astrophysics Data System (ADS)

Su, Shiliang; Zhi, Junjun; Lou, Liping; Huang, Fang; Chen, Xia; Wu, Jiaping

Characterizing the spatio-temporal patterns and apportioning the pollution sources of water bodies are important for the management and protection of water resources. The main objective of this study is to describe the dynamics of water quality and provide references for improving river pollution control practices. Comprehensive application of neural-based modeling and different multivariate methods was used to evaluate the spatio-temporal patterns and source apportionment of pollution in Qiantang River, China. Measurement data were obtained and pretreated for 13 variables from 41 monitoring sites for the period of 2001-2004. A self-organizing map classified the 41 monitoring sites into three groups (Group A, B and C), representing different pollution characteristics. Four significant parameters (dissolved oxygen, biochemical oxygen demand, total phosphorus and total lead) were identified by discriminant analysis for distinguishing variations of different years, with about 80% correct assignment for temporal variation. Rotated principal component analysis (PCA) identified four potential pollution sources for Group A (domestic sewage and agricultural pollution, industrial wastewater pollution, mineral weathering, vehicle exhaust and sand mining), five for Group B (heavy metal pollution, agricultural runoff, vehicle exhaust and sand mining, mineral weathering, chemical plants discharge) and another five for Group C (vehicle exhaust and sand mining, chemical plants discharge, soil weathering, biochemical pollution, mineral weathering). The identified potential pollution sources explained 75.6% of the total variances for Group A, 75.0% for Group B and 80.0% for Group C, respectively. Receptor-based source apportionment was applied to further estimate source contributions for each pollution variable in the three groups, which facilitated and supported the PCA results. These results could assist managers to develop optimal strategies and determine priorities for river pollution control and effective water resources management.

A Method for Correlation of Gravestone Weathering and Air Quality (SO2), West Amidlands, UK

NASA Astrophysics Data System (ADS)

Carlson, Michael John

From the beginning of the Industrial Revolution through the environmental revolution of the 1970s Britain suffered the effects of poor air quality primarily from particulate matter and acid in the form of NOx and SO x compounds. Air quality stations across the region recorded SO 2 beginning in the 1960s however the direct measurement of air quality prior to 1960 is lacking and only anecdotal notations exist. Proxy records including lung tissue samples, particulates in sediments cores, lake acidification studies and gravestone weathering have all been used to reconstruct the history of air quality. A 120-year record of acid deposition reconstructed from lead-lettered marble gravestone weathering combined with SO2 measurements from the air monitoring network across the West Midlands, UK region beginning in the 1960s form the framework for this study. The study seeks to create a spatial and temporal correlation between the gravestone weathering and measured SO 2. Successful correlation of the dataset from 1960s to the 2000s would allow a paleo-air quality record to be generated from the 120-year record of gravestone weathering. Decadal gravestone weathering rates can be estimated by non-linear regression analysis of stone loss at individual cemeteries. Gravestone weathering rates are interpolated across the region through Empirical Bayesian Kriging (EBK) methods performed through ArcGISRTM and through a land use based approach based on digitized maps of land use. Both methods of interpolation allow for the direct correlation of gravestone weathering and measured SO2 to be made. Decadal scale correlations of gravestone weathering rates and measured SO2 are very weak and non-existent for both EBK and the land use based approach. Decadal results combined together on a larger scale for each respective method display a better visual correlation. However, the relative clustering of data at lower SO2 concentrations and the lack of data at higher SO2 concentrations make the confidence in the correlations made too weak to rely on. The relation between surrounding land use and gravestone weathering rates was very strong for the 1960s-1980s with diminishing correlations approaching the 2000s. Gravestone weathering of cemeteries is highly influenced by the amount of industrial sources of pollution within a 7km radius. Reduced correlation of land use and weathering beyond the 1980s is solid grounds for the success of environmental regulation and control put in place across the UK during later parts of the 20th century.

Research for Environmental Stewardship and Conservation at the APTRU

USDA-ARS?s Scientific Manuscript database

Research methods for mitigation of off-target spray drift, remote sensing for precision crop management, and irrigation and tillage methods are presented. Research for mitigation of off target spray drift includes development of sophisticated weather apparatus to determine weather conditions unfavor...

Effect of weathering cycle and manufacturing method on performance of wood flour and high-density polyethylene composites

Treesearch

Nicole M. Stark

2006-01-01

Wood–plastic lumber is promoted as a low-maintenance high-durability product. When exposed to accelerated weathering, however, wood–plastic composites may experience a color change and loss in mechanical properties. Differences in weathering cycle and composite surface characteristics can affect the rate and amount of change caused by weathering. In this study, 50%...

Predictable weathering of puparial hydrocarbons of necrophagous flies for determining the postmortem interval: a field experiment using Chrysomya rufifacies.

PubMed

Zhu, Guang-Hui; Jia, Zheng-Jun; Yu, Xiao-Jun; Wu, Ku-Sheng; Chen, Lu-Shi; Lv, Jun-Yao; Eric Benbow, M

2017-05-01

Preadult development of necrophagous flies is commonly recognized as an accurate method for estimating the minimum postmortem interval (PMImin). However, once the PMImin exceeds the duration of preadult development, the method is less accurate. Recently, fly puparial hydrocarbons were found to significantly change with weathering time in the field, indicating their potential use for PMImin estimates. However, additional studies are required to demonstrate how the weathering varies among species. In this study, the puparia of Chrysomya rufifacies were placed in the field to experience natural weathering to characterize hydrocarbon composition change over time. We found that weathering of the puparial hydrocarbons was regular and highly predictable in the field. For most of the hydrocarbons, the abundance decreased significantly and could be modeled using a modified exponent function. In addition, the weathering rate was significantly correlated with the hydrocarbon classes. The weathering rate of 2-methyl alkanes was significantly lower than that of alkenes and internal methyl alkanes, and alkenes were higher than the other two classes. For mono-methyl alkanes, the rate was significantly and positively associated with carbon chain length and branch position. These results indicate that puparial hydrocarbon weathering is highly predictable and can be used for estimating long-term PMImin.

What weather variables are important in predicting heat-related mortality? A new application of statistical learning methods

PubMed Central

Zhang, Kai; Li, Yun; Schwartz, Joel D.; O'Neill, Marie S.

2014-01-01

Hot weather increases risk of mortality. Previous studies used different sets of weather variables to characterize heat stress, resulting in variation in heat-mortality- associations depending on the metric used. We employed a statistical learning method – random forests – to examine which of various weather variables had the greatest impact on heat-related mortality. We compiled a summertime daily weather and mortality counts dataset from four U.S. cities (Chicago, IL; Detroit, MI; Philadelphia, PA; and Phoenix, AZ) from 1998 to 2006. A variety of weather variables were ranked in predicting deviation from typical daily all-cause and cause-specific death counts. Ranks of weather variables varied with city and health outcome. Apparent temperature appeared to be the most important predictor of heat-related mortality for all-cause mortality. Absolute humidity was, on average, most frequently selected one of the top variables for all-cause mortality and seven cause-specific mortality categories. Our analysis affirms that apparent temperature is a reasonable variable for activating heat alerts and warnings, which are commonly based on predictions of total mortality in next few days. Additionally, absolute humidity should be included in future heat-health studies. Finally, random forests can be used to guide choice of weather variables in heat epidemiology studies. PMID:24834832

The susceptibility of weathered versus unweathered schist to biological colonization in the Côa Valley Archaeological Park (north-east Portugal).

PubMed

Marques, Joana; Vázquez-Nion, Daniel; Paz-Bermúdez, Graciela; Prieto, Beatriz

2015-05-01

This study addresses the primary and secondary bioreceptivity of schist used as a support for prehistoric rock art in the Côa Valley Archaeological Park (north-east Portugal) and provides some parameters that can be related to the risk of biologically induced schist weathering. Samples of freshly quarried and naturally weathered schist were characterized in terms of their intrinsic properties and maintained in controlled environmental conditions after inoculation with biofilm-forming cyanobacteria. The physical properties of the studied schist, as well as its abrasion pH, all varied according to the weathering degree of the samples and so did its susceptibility to colonization by biofilm-forming cyanobacteria. Complete separation between weathered and unweathered schist samples in terms of laboratory-induced photosynthetic biomass was obtained by measuring total colour change in the CIE (International Commission on Illumination) L*a*b* colour space. Weathered schist was more bioreceptive than unweathered schist, associated with increased open porosity, water saturation, capillary water and capillarity coefficient and decreased abrasion pH. In the future, it might be possible to determine the susceptibility of schist surfaces to biological colonization through evaluation of colour differences associated with the different weathering degrees presented by those surfaces prior to colonization. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Probabilistic Solar Wind and Geomagnetic Forecasting Using an Analogue Ensemble or "Similar Day" Approach

NASA Astrophysics Data System (ADS)

Owens, M. J.; Riley, P.; Horbury, T. S.

2017-05-01

Effective space-weather prediction and mitigation requires accurate forecasting of near-Earth solar-wind conditions. Numerical magnetohydrodynamic models of the solar wind, driven by remote solar observations, are gaining skill at forecasting the large-scale solar-wind features that give rise to near-Earth variations over days and weeks. There remains a need for accurate short-term (hours to days) solar-wind forecasts, however. In this study we investigate the analogue ensemble (AnEn), or "similar day", approach that was developed for atmospheric weather forecasting. The central premise of the AnEn is that past variations that are analogous or similar to current conditions can be used to provide a good estimate of future variations. By considering an ensemble of past analogues, the AnEn forecast is inherently probabilistic and provides a measure of the forecast uncertainty. We show that forecasts of solar-wind speed can be improved by considering both speed and density when determining past analogues, whereas forecasts of the out-of-ecliptic magnetic field [BN] are improved by also considering the in-ecliptic magnetic-field components. In general, the best forecasts are found by considering only the previous 6 - 12 hours of observations. Using these parameters, the AnEn provides a valuable probabilistic forecast for solar-wind speed, density, and in-ecliptic magnetic field over lead times from a few hours to around four days. For BN, which is central to space-weather disturbance, the AnEn only provides a valuable forecast out to around six to seven hours. As the inherent predictability of this parameter is low, this is still likely a marked improvement over other forecast methods. We also investigate the use of the AnEn in forecasting geomagnetic indices Dst and Kp. The AnEn provides a valuable probabilistic forecast of both indices out to around four days. We outline a number of future improvements to AnEn forecasts of near-Earth solar-wind and geomagnetic conditions.

The Polygon-Ellipse Method of Data Compression of Weather Maps

DTIC Science & Technology

1994-03-28

Report No. DOT’•FAAJRD-9416 Pr•oject Report AD-A278 958 ATC-213 The Polygon-Ellipse Method of Data Compression of Weather Maps ELDCT E J.L. GerIz 28...a o means must he- found to Compress this image. The l’olygion.Ellip.e (PE.) encoding algorithm develop.ed in this report rt-premrnt. weather regions...severely compress the image. For example, Mode S would require approximately a 10-fold compression . In addition, the algorithms used to perform the

Analysis of Shield Construction in Spherical Weathered Granite Development Area

NASA Astrophysics Data System (ADS)

Cao, Quan; Li, Peigang; Gong, Shuhua

2018-01-01

The distribution of spherical weathered bodies (commonly known as "boulder") in the granite development area directly affects the shield construction of urban rail transit engineering. This paper is based on the case of shield construction of granite globular development area in Southern China area, the parameter control in shield machine selection and shield advancing during the shield tunneling in this special geological environment is analyzed. And it is suggested that shield machine should be selected for shield construction of granite spherical weathered zone. Driving speed, cutter torque, shield machine thrust, the amount of penetration and the speed of the cutter head of shield machine should be controlled when driving the boulder formation, in order to achieve smooth excavation and reduce the disturbance to the formation.

Histogram-based ionogram displays and their application to autoscaling

NASA Astrophysics Data System (ADS)

Lynn, Kenneth J. W.

2018-03-01

A simple method is described for displaying and auto scaling the basic ionogram parameters foF2 and h'F2 as well as some additional layer parameters from digital ionograms. The technique employed is based on forming frequency and height histograms in each ionogram. This technique has now been applied specifically to ionograms produced by the IPS5D ionosonde developed and operated by the Australian Space Weather Service (SWS). The SWS ionograms are archived in a cleaned format and readily available from the SWS internet site. However, the method is applicable to any ionosonde which produces ionograms in a digital format at a useful signal-to-noise level. The most novel feature of the technique for autoscaling is its simplicity and the avoidance of the mathematical imaging and line fitting techniques often used. The program arose from the necessity to display many days of ionogram output to allow the location of specific types of ionospheric event such as ionospheric storms, travelling ionospheric disturbances and repetitive ionospheric height changes for further investigation and measurement. Examples and applications of the method are given including the removal of sporadic E and spread F.

Audio-Visual Situational Awareness for General Aviation Pilots

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Lodha, Suresh K.; Clancy, Daniel (Technical Monitor)

2001-01-01

Weather is one of the major causes of general aviation accidents. Researchers are addressing this problem from various perspectives including improving meteorological forecasting techniques, collecting additional weather data automatically via on-board sensors and "flight" modems, and improving weather data dissemination and presentation. We approach the problem from the improved presentation perspective and propose weather visualization and interaction methods tailored for general aviation pilots. Our system, Aviation Weather Data Visualization Environment (AWE), utilizes information visualization techniques, a direct manipulation graphical interface, and a speech-based interface to improve a pilot's situational awareness of relevant weather data. The system design is based on a user study and feedback from pilots.

Multi-site precipitation downscaling using a stochastic weather generator

NASA Astrophysics Data System (ADS)

Chen, Jie; Chen, Hua; Guo, Shenglian

2018-03-01

Statistical downscaling is an efficient way to solve the spatiotemporal mismatch between climate model outputs and the data requirements of hydrological models. However, the most commonly-used downscaling method only produces climate change scenarios for a specific site or watershed average, which is unable to drive distributed hydrological models to study the spatial variability of climate change impacts. By coupling a single-site downscaling method and a multi-site weather generator, this study proposes a multi-site downscaling approach for hydrological climate change impact studies. Multi-site downscaling is done in two stages. The first stage involves spatially downscaling climate model-simulated monthly precipitation from grid scale to a specific site using a quantile mapping method, and the second stage involves the temporal disaggregating of monthly precipitation to daily values by adjusting the parameters of a multi-site weather generator. The inter-station correlation is specifically considered using a distribution-free approach along with an iterative algorithm. The performance of the downscaling approach is illustrated using a 10-station watershed as an example. The precipitation time series derived from the National Centers for Environment Prediction (NCEP) reanalysis dataset is used as the climate model simulation. The precipitation time series of each station is divided into 30 odd years for calibration and 29 even years for validation. Several metrics, including the frequencies of wet and dry spells and statistics of the daily, monthly and annual precipitation are used as criteria to evaluate the multi-site downscaling approach. The results show that the frequencies of wet and dry spells are well reproduced for all stations. In addition, the multi-site downscaling approach performs well with respect to reproducing precipitation statistics, especially at monthly and annual timescales. The remaining biases mainly result from the non-stationarity of NCEP precipitation. Overall, the proposed approach is efficient for generating multi-site climate change scenarios that can be used to investigate the spatial variability of climate change impacts on hydrology.

Development and Testing of Operational Dual-Polarimetric Radar Based Lightning Initiation Forecast Techniques

NASA Technical Reports Server (NTRS)

Woodard, Crystal; Carey, Lawrence D.; Petersen, Walter A.; Felix, Mariana; Roeder, William P.

2011-01-01

Lightning is one of Earth s natural dangers, destructive not only to life but also physical property. According to the National Weather Service, there are on average 58 lightning fatalities each year, with over 300 related injuries (NWS 2010). The ability to forecast lightning is critical to a host of activities ranging from space vehicle launch operations to recreational sporting events. For example a single lightning strike to a Space Shuttle could cause billions of dollars of damage and possible loss of life. While forecasting that provides longer lead times could provide sporting officials with more time to respond to possible threatening weather events, thus saving the lives of player and bystanders. Many researchers have developed and tested different methods and tools of first flash forecasting, however few have done so using dual-polarimetric radar variables and products on an operational basis. The purpose of this study is to improve algorithms for the short-term prediction of lightning initiation through development and testing of operational techniques that rely on parameters observed and diagnosed using C-band dual-polarimetric radar.

Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar. Thesis Technical Report No. 20

NASA Technical Reports Server (NTRS)

Lai, Jonathan Y.

1994-01-01

This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.

Image processing for hazard recognition in on-board weather radar

NASA Technical Reports Server (NTRS)

Kelly, Wallace E. (Inventor); Rand, Timothy W. (Inventor); Uckun, Serdar (Inventor); Ruokangas, Corinne C. (Inventor)

2003-01-01

A method of providing weather radar images to a user includes obtaining radar image data corresponding to a weather radar image to be displayed. The radar image data is image processed to identify a feature of the weather radar image which is potentially indicative of a hazardous weather condition. The weather radar image is displayed to the user along with a notification of the existence of the feature which is potentially indicative of the hazardous weather condition. Notification can take the form of textual information regarding the feature, including feature type and proximity information. Notification can also take the form of visually highlighting the feature, for example by forming a visual border around the feature. Other forms of notification can also be used.

A Backscatter-Lidar Forward-Operator

NASA Astrophysics Data System (ADS)

Geisinger, Armin; Behrendt, Andreas; Wulfmeyer, Volker; Vogel, Bernhard; Mattis, Ina; Flentje, Harald; Förstner, Jochen; Potthast, Roland

2015-04-01

We have developed a forward-operator which is capable of calculating virtual lidar profiles from atmospheric state simulations. The operator allows us to compare lidar measurements and model simulations based on the same measurement parameter: the lidar backscatter profile. This method simplifies qualitative comparisons and also makes quantitative comparisons possible, including statistical error quantification. Implemented into an aerosol-capable model system, the operator will act as a component to assimilate backscatter-lidar measurements. As many weather services maintain already networks of backscatter-lidars, such data are acquired already in an operational manner. To estimate and quantify errors due to missing or uncertain aerosol information, we started sensitivity studies about several scattering parameters such as the aerosol size and both the real and imaginary part of the complex index of refraction. Furthermore, quantitative and statistical comparisons between measurements and virtual measurements are shown in this study, i.e. applying the backscatter-lidar forward-operator on model output.

Thermal Performance Analysis of Solar Collectors Installed for Combisystem in the Apartment Building

NASA Astrophysics Data System (ADS)

Žandeckis, A.; Timma, L.; Blumberga, D.; Rochas, C.; Rošā, M.

2012-01-01

The paper focuses on the application of wood pellet and solar combisystem for space heating and hot water preparation at apartment buildings under the climate of Northern Europe. A pilot project has been implemented in the city of Sigulda (N 57° 09.410 E 024° 52.194), Latvia. The system was designed and optimised using TRNSYS - a dynamic simulation tool. The pilot project was continuously monitored. To the analysis the heat transfer fluid flow rate and the influence of the inlet temperature on the performance of solar collectors were subjected. The thermal performance of a solar collector loop was studied using a direct method. A multiple regression analysis was carried out using STATGRAPHICS Centurion 16.1.15 with the aim to identify the operational and weather parameters of the system which cause the strongest influence on the collector's performance. The parameters to be used for the system's optimisation have been evaluated.

Introduction and analysis of several FY3C-MWHTS cloud/rain screening methods

NASA Astrophysics Data System (ADS)

Li, Xiaoqing

2017-04-01

Data assimilation of satellite microwave sounders are very important for numerical weather prediction. Fengyun-3C (FY-3C),launched in September, 2013, has two such sounders: MWTS (MicroWave Temperature Sounder) and MWHTS (MicroWave Humidity and Temperature Sounder). These data should be quality-controlled before assimilation and cloud/rain detection is one of the crucial steps. This paper introduced different cloud/rain detection methods based on MWHTS, VIRR (Visible and InfraRed Radiometer) and MWRI (Microwave Radiation Imager) observations. We designed 6 cloud/rain detection combinations and then analyzed the application effect of these schemes. The difference between observations and model simulations for FY-3C MWHTS channels were calculated as a parameter for analysis. Both RTTOV and CRTM were used to fast simulate radiances of MWHTS channels.

Weather or Not To Teach Junior High Meteorology.

ERIC Educational Resources Information Center

Knorr, Thomas P.

1984-01-01

Presents a technique for teaching meteorology allowing students to observe and analyze consecutive weather maps and relate local conditions; a model illustrating the three-dimensional nature of the atmosphere is employed. Instructional methods based on studies of daily weather maps to trace systems sweeping across the United States are discussed.…

Corn response to nitrogen is influenced by soil texture and weather

USDA-ARS?s Scientific Manuscript database

Soil properties and weather conditions are known to affect soil nitrogen (N) availability and plant N uptake. However, studies examining N response as affected by soil and weather sometimes give conflicting results. Meta-analysis is a statistical method for estimating treatment effects in a se...

Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions

PubMed Central

Che, H. C.; Zhang, X. Y.; Wang, Y. Q.; Zhang, L.; Shen, X. J.; Zhang, Y. M.; Ma, Q. L.; Sun, J. Y.; Zhang, Y. W.; Wang, T. T.

2016-01-01

To better understand the cloud condensation nuclei (CCN) activation capacity of aerosol particles in different pollution conditions, a long-term field experiment was carried out at a regional GAW (Global Atmosphere Watch) station in the Yangtze River Delta area of China. The homogeneity of aerosol particles was the highest in clean weather, with the highest active fraction of all the weather types. For pollution with the same visibility, the residual aerosol particles in higher relative humidity weather conditions were more externally mixed and heterogeneous, with a lower hygroscopic capacity. The hygroscopic capacity (κ) of organic aerosols can be classified into 0.1 and 0.2 in different weather types. The particles at ~150 nm were easily activated in haze weather conditions. For CCN predictions, the bulk chemical composition method was closer to observations at low supersaturations (≤0.1%), whereas when the supersaturation was ≥0.2%, the size-resolved chemical composition method was more accurate. As for the mixing state of the aerosol particles, in haze, heavy haze, and severe haze weather conditions CCN predictions based on the internal mixing assumption were robust, whereas for other weather conditions, predictions based on the external mixing assumption were more accurate. PMID:27075947

4-D Cloud Water Content Fields Derived from Operational Satellite Data

NASA Technical Reports Server (NTRS)

Smith, William L., Jr.; Minnis, Patrick

2010-01-01

In order to improve operational safety and efficiency, the transportation industry, including aviation, has an urgent need for accurate diagnoses and predictions of clouds and associated weather conditions. Adverse weather accounts for 70% of all air traffic delays within the U.S. National Airspace System. The Federal Aviation Administration has determined that as much as two thirds of weather-related delays are potentially avoidable with better weather information and roughly 20% of all aviation accidents are weather related. Thus, it is recognized that an important factor in meeting the goals of the Next Generation Transportation System (NexGen) vision is the improved integration of weather information. The concept of a 4-D weather cube is being developed to address that need by integrating observed and forecasted weather information into a shared 4-D database, providing an integrated and nationally consistent weather picture for a variety of users and to support operational decision support systems. Weather analyses and forecasts derived using Numerical Weather Prediction (NWP) models are a critical tool that forecasters rely on for guidance and also an important element in current and future decision support systems. For example, the Rapid Update Cycle (RUC) and the recently implemented Rapid Refresh (RR) Weather Research and Forecast (WRF) models provide high frequency forecasts and are key elements of the FAA Aviation Weather Research Program. Because clouds play a crucial role in the dynamics and thermodynamics of the atmosphere, they must be adequately accounted for in NWP models. The RUC, for example, cycles at full resolution five cloud microphysical species (cloud water, cloud ice, rain, snow, and graupel) and has the capability of updating these fields from observations. In order to improve the models initial state and subsequent forecasts, cloud top altitude (or temperature, T(sub c)) derived from operational satellite data, surface observations of cloud base altitude, radar reflectivity, and lightning data are used to help build and remove clouds in the models assimilation system. Despite this advance and the many recent advances made in our understanding of cloud physical processes and radiative effects, many problems remain in adequately representing clouds in models. While the assimilation of cloud top information derived from operational satellite data has merit, other information is available that has not yet been exploited. For example, the vertically integrated cloud water content (CWC) or cloud water path (CWP) and cloud geometric thickness (delta Z) are standard products being derived routinely from operational satellite data. These and other cloud products have been validated under a variety of conditions. Since the uncertainties have generally been found to be less than those found in model analyses and forecasts, the satellite products should be suitable for data assimilation, provided an appropriate strategy can be developed that links the satellite-derived cloud parameters with cloud parameters specified in the model. In this paper, we briefly outline such a strategy and describe a methodology to retrieve cloud water content profiles from operational satellite data. Initial results and future plans are presented. It is expected that the direct assimilation of this new product will provide the most accurate depiction of the vertical distribution of cloud water ever produced at the high spatial and temporal resolution needed for short term weather analyses and forecasts.

Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review

PubMed Central

Armstrong, Ben; Fleming, Lora E.; Elson, Richard; Kovats, Sari; Vardoulakis, Sotiris; Nichols, Gordon L.

2017-01-01

Infectious diseases attributable to unsafe water supply, sanitation and hygiene (e.g. Cholera, Leptospirosis, Giardiasis) remain an important cause of morbidity and mortality, especially in low-income countries. Climate and weather factors are known to affect the transmission and distribution of infectious diseases and statistical and mathematical modelling are continuously developing to investigate the impact of weather and climate on water-associated diseases. There have been little critical analyses of the methodological approaches. Our objective is to review and summarize statistical and modelling methods used to investigate the effects of weather and climate on infectious diseases associated with water, in order to identify limitations and knowledge gaps in developing of new methods. We conducted a systematic review of English-language papers published from 2000 to 2015. Search terms included concepts related to water-associated diseases, weather and climate, statistical, epidemiological and modelling methods. We found 102 full text papers that met our criteria and were included in the analysis. The most commonly used methods were grouped in two clusters: process-based models (PBM) and time series and spatial epidemiology (TS-SE). In general, PBM methods were employed when the bio-physical mechanism of the pathogen under study was relatively well known (e.g. Vibrio cholerae); TS-SE tended to be used when the specific environmental mechanisms were unclear (e.g. Campylobacter). Important data and methodological challenges emerged, with implications for surveillance and control of water-associated infections. The most common limitations comprised: non-inclusion of key factors (e.g. biological mechanism, demographic heterogeneity, human behavior), reporting bias, poor data quality, and collinearity in exposures. Furthermore, the methods often did not distinguish among the multiple sources of time-lags (e.g. patient physiology, reporting bias, healthcare access) between environmental drivers/exposures and disease detection. Key areas of future research include: disentangling the complex effects of weather/climate on each exposure-health outcome pathway (e.g. person-to-person vs environment-to-person), and linking weather data to individual cases longitudinally. PMID:28604791

Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review.

PubMed

Lo Iacono, Giovanni; Armstrong, Ben; Fleming, Lora E; Elson, Richard; Kovats, Sari; Vardoulakis, Sotiris; Nichols, Gordon L

2017-06-01

Infectious diseases attributable to unsafe water supply, sanitation and hygiene (e.g. Cholera, Leptospirosis, Giardiasis) remain an important cause of morbidity and mortality, especially in low-income countries. Climate and weather factors are known to affect the transmission and distribution of infectious diseases and statistical and mathematical modelling are continuously developing to investigate the impact of weather and climate on water-associated diseases. There have been little critical analyses of the methodological approaches. Our objective is to review and summarize statistical and modelling methods used to investigate the effects of weather and climate on infectious diseases associated with water, in order to identify limitations and knowledge gaps in developing of new methods. We conducted a systematic review of English-language papers published from 2000 to 2015. Search terms included concepts related to water-associated diseases, weather and climate, statistical, epidemiological and modelling methods. We found 102 full text papers that met our criteria and were included in the analysis. The most commonly used methods were grouped in two clusters: process-based models (PBM) and time series and spatial epidemiology (TS-SE). In general, PBM methods were employed when the bio-physical mechanism of the pathogen under study was relatively well known (e.g. Vibrio cholerae); TS-SE tended to be used when the specific environmental mechanisms were unclear (e.g. Campylobacter). Important data and methodological challenges emerged, with implications for surveillance and control of water-associated infections. The most common limitations comprised: non-inclusion of key factors (e.g. biological mechanism, demographic heterogeneity, human behavior), reporting bias, poor data quality, and collinearity in exposures. Furthermore, the methods often did not distinguish among the multiple sources of time-lags (e.g. patient physiology, reporting bias, healthcare access) between environmental drivers/exposures and disease detection. Key areas of future research include: disentangling the complex effects of weather/climate on each exposure-health outcome pathway (e.g. person-to-person vs environment-to-person), and linking weather data to individual cases longitudinally.

A global method for identifying dependences between helio-geophysical and biological series by filtering the precedents (outliers)

NASA Astrophysics Data System (ADS)

Ozheredov, V. A.; Breus, T. K.; Gurfinkel, Yu. I.; Matveeva, T. A.

2014-12-01

A new approach to finding the dependence between heliophysical and meteorological factors and physiological parameters is considered that is based on the preliminary filtering of precedents (outliers). The sought-after dependence is masked by extraneous influences which cannot be taken into account. Therefore, the typically calculated correlation between the external-influence ( x) and physiology ( y) parameters is extremely low and does not allow their interdependence to be conclusively proved. A robust method for removing the precedents (outliers) from the database is proposed that is based on the intelligent sorting of the polynomial curves of possible dependences y( x), followed by filtering out the precedents which are far away from y( x) and optimizing the coefficient of nonlinear correlation between the regular, i.e., remaining, precedents. This optimization problem is shown to be a search for a maximum in the absence of the concept of gradient and requires the use of a genetic algorithm based on the Gray code. The relationships between the various medical and biological parameters and characteristics of the space and terrestrial weather are obtained and verified using the cross-validation method. It is proven that, by filtering out no more than 20% of precedents, it is possible to obtain a nonlinear correlation coefficient of no less than 0.5. A juxtaposition of the proposed method for filtering precedents (outliers) and the least-square method (LSM) for determining the optimal polynomial using multiple independent tests (Monte Carlo method) of models, which are as close as possible to real dependences, has shown that the LSM determination loses much in comparison to the proposed method.

Key Parameters for Urban Heat Island Assessment in A Mediterranean Context: A Sensitivity Analysis Using the Urban Weather Generator Model

NASA Astrophysics Data System (ADS)

Salvati, Agnese; Palme, Massimo; Inostroza, Luis

2017-10-01

Although Urban Heat Island (UHI) is a fundamental effect modifying the urban climate, being widely studied, the relative weight of the parameters involved in its generation is still not clear. This paper investigates the hierarchy of importance of eight parameters responsible for UHI intensity in the Mediterranean context. Sensitivity analyses have been carried out using the Urban Weather Generator model, considering the range of variability of: 1) city radius, 2) urban morphology, 3) tree coverage, 4) anthropogenic heat from vehicles, 5) building’s cooling set point, 6) heat released to canyon from HVAC systems, 7) wall construction properties and 8) albedo of vertical and horizontal surfaces. Results show a clear hierarchy of significance among the considered parameters; the urban morphology is the most important variable, causing a relative change up to 120% of the annual average UHI intensity in the Mediterranean context. The impact of anthropogenic sources of heat such as cooling systems and vehicles is also significant. These results suggest that urban morphology parameters can be used as descriptors of the climatic performance of different urban areas, easing the work of urban planners and designers in understanding a complex physical phenomenon, such as the UHI.

Operational early warning platform for extreme meteorological events

NASA Astrophysics Data System (ADS)

Mühr, Bernhard; Kunz, Michael

2015-04-01

Operational early warning platform for extreme meteorological events Most natural disasters are related to extreme weather events (e.g. typhoons); weather conditions, however, are also highly relevant for humanitarian and disaster relief operations during and after other natural disaster like earthquakes. The internet service "Wettergefahren-Frühwarnung" (WF) provides various information on extreme weather events, especially when these events are associated with a high potential for large damage. The main focus of the platform is on Central Europe, but major events are also monitored worldwide on a daily routine. WF provides high-resolution forecast maps for many weather parameters which allow detailed and reliable predictions about weather conditions during the next days in the affected areas. The WF service became operational in February 2004 and is part of the Center for Disaster Management and Risk Reduction Technology (CEDIM) since 2007. At the end of 2011, CEDIM embarked a new type of interdisciplinary disaster research termed as forensic disaster analysis (FDA) in near real time. In case of an imminent extreme weather event WF plays an important role in CEDIM's FDA group. It provides early and precise information which are always available and updated several times during a day and gives advice and assists with articles and reports on extreme events.

Fire Weather Products for Public and Emergency Use: Extending Professional Resources to the Public

NASA Astrophysics Data System (ADS)

Rogers, M. A.; Schranz, S.; Kriederman, L.

2012-12-01

Large wildfires require significant resources to combat, including dedicated meteorological support to provide accurate and timely forecasts to assist incident commanders in making decisions for logistical and tactical firefighting operations. Smaller fires often require the same capabilities for understanding fire and the fire weather environment, but access to needed resources and tools is often limited due to technical, training, or education limitations. Providing fire weather information and training to incident commanders for smaller wildfires should prove to enhance firefighting capabilities and improve safety for both firefighters and for the public as well. One of the premier tools used to support fire weather forecasting for the largest wildfires is the FX-Net product, a thin-client version of the Advanced Weather Interactive Processing System used by NWS incident meteorologists (IMETs) deployed to large wildfires. We present results from an ongoing project to extend the sophisticated products available from FX-Net to more accessible and mobile software platforms, such as Google Earth. The project involves input from IMETs and fire commanders to identify the key parameters used in fighting wildfires, and involves a large training component for fire responders to utilize simplified products to improve understanding of fire weather in the context of firefighting operations.

Outcome of the Third Cloud Retrieval Evaluation Workshop

NASA Astrophysics Data System (ADS)

Roebeling, R.; Baum, B.; Bennartz, R.; Hamann, U.; Heidinger, A.; Thoss, A.; Walther, A.

2012-04-01

Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and inter-annual variations are needed to improve the understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics need to be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), which was held from 15-18 November 2011 in Madison, Wisconsin, USA, is to enhance our knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimising these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods that are used to prepare daily and monthly cloud parameter climatologies. An important component of the workshop is the discussion on the results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we will summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on the reasons for the observed differences. More in depth discussions were held on retrieval principles and validation, and the utilization of cloud parameters for climate research. This was done in parallel breakout sessions on cloud vertical placement; cloud physical properties, and cloud climatologies. We will present the recommendations of these sessions, propose a way forward to establish international partnerships on cloud research, and summarize the actions defined to tailor the CREW activities to missions of international programs, such as the Global Energy and Water Cycle Experiment (GEWEX) and Sustained, Co-Ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM). Finally, attention will be given to increase the traceability and uniformity of different long-term and homogeneous records of cloud parameters.

Computation of rainfall erosivity from daily precipitation amounts.

PubMed

Beguería, Santiago; Serrano-Notivoli, Roberto; Tomas-Burguera, Miquel

2018-10-01

Rainfall erosivity is an important parameter in many erosion models, and the EI30 defined by the Universal Soil Loss Equation is one of the best known erosivity indices. One issue with this and other erosivity indices is that they require continuous breakpoint, or high frequency time interval, precipitation data. These data are rare, in comparison to more common medium-frequency data, such as daily precipitation data commonly recorded by many national and regional weather services. Devising methods for computing estimates of rainfall erosivity from daily precipitation data that are comparable to those obtained by using high-frequency data is, therefore, highly desired. Here we present a method for producing such estimates, based on optimal regression tools such as the Gamma Generalised Linear Model and universal kriging. Unlike other methods, this approach produces unbiased and very close to observed EI30, especially when these are aggregated at the annual level. We illustrate the method with a case study comprising more than 1500 high-frequency precipitation records across Spain. Although the original records have a short span (the mean length is around 10 years), computation of spatially-distributed upscaling parameters offers the possibility to compute high-resolution climatologies of the EI30 index based on currently available, long-span, daily precipitation databases. Copyright © 2018 Elsevier B.V. All rights reserved.

Design of all-weather celestial navigation system

NASA Astrophysics Data System (ADS)

Sun, Hongchi; Mu, Rongjun; Du, Huajun; Wu, Peng

2018-03-01

In order to realize autonomous navigation in the atmosphere, an all-weather celestial navigation system is designed. The research of celestial navigation system include discrimination method of comentropy and the adaptive navigation algorithm based on the P value. The discrimination method of comentropy is studied to realize the independent switching of two celestial navigation modes, starlight and radio. Finally, an adaptive filtering algorithm based on P value is proposed, which can greatly improve the disturbance rejection capability of the system. The experimental results show that the accuracy of the three axis attitude is better than 10″, and it can work all weather. In perturbation environment, the position accuracy of the integrated navigation system can be increased 20% comparing with the traditional method. It basically meets the requirements of the all-weather celestial navigation system, and it has the ability of stability, reliability, high accuracy and strong anti-interference.

The Atmospheric Infrared Sounder- An Overview

NASA Technical Reports Server (NTRS)

Larnbrigtsen, Bjorn; Fetzer, Eric; Lee, Sung-Yung; Irion, Fredrick; Hearty, Thomas; Gaiser, Steve; Pagano, Thomas; Aumann, Hartmut; Chahine, Moustafa

2004-01-01

The Atmospheric Infrared Sounder (AIRS) was launched in May 2002. Along with two companion microwave sensors, it forms the AIRS Sounding Suite. This system is the most advanced atmospheric sounding system to date, with measurement accuracies far surpassing those available on current weather satellites. The data products are calibrated radiances from all three sensors and a number of derived geophysical parameters, including vertical temperature and humidity profiles, surface temperature, cloud fraction, cIoud top pressure, and profiles of ozone. These products are generated under cloudy as well as clear conditions. An ongoing calibration validation effort has confirmed that the system is very accurate and stable, and many of the geophysical parameters have been validated. AIRS is in some cases more accurate than any other source and can therefore be difficult to validate, but this offers interesting new research opportunities. The applications for the AIRS products range from numerical weather prediction to atmospheric research - where the AIRS water vapor products near the surface and in the mid to upper troposphere will make it possible to characterize and model phenomena that are key for short-term atmospheric processes, such as weather patterns, to long-term processes, such as interannual cycles (e.g., El Nino) and climate change.

Evaluation of dynamically downscaled extreme temperature using a spatially-aggregated generalized extreme value (GEV) model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jiali; Han, Yuefeng; Stein, Michael L.

2016-02-10

The Weather Research and Forecast (WRF) model downscaling skill in extreme maximum daily temperature is evaluated by using the generalized extreme value (GEV) distribution. While the GEV distribution has been used extensively in climatology and meteorology for estimating probabilities of extreme events, accurately estimating GEV parameters based on data from a single pixel can be difficult, even with fairly long data records. This work proposes a simple method assuming that the shape parameter, the most difficult of the three parameters to estimate, does not vary over a relatively large region. This approach is applied to evaluate 31-year WRF-downscaled extreme maximummore » temperature through comparison with North American Regional Reanalysis (NARR) data. Uncertainty in GEV parameter estimates and the statistical significance in the differences of estimates between WRF and NARR are accounted for by conducting bootstrap resampling. Despite certain biases over parts of the United States, overall, WRF shows good agreement with NARR in the spatial pattern and magnitudes of GEV parameter estimates. Both WRF and NARR show a significant increase in extreme maximum temperature over the southern Great Plains and southeastern United States in January and over the western United States in July. The GEV model shows clear benefits from the regionally constant shape parameter assumption, for example, leading to estimates of the location and scale parameters of the model that show coherent spatial patterns.« less

Model Parameter Estimation Using Ensemble Data Assimilation: A Case with the Nonhydrostatic Icosahedral Atmospheric Model NICAM and the Global Satellite Mapping of Precipitation Data

NASA Astrophysics Data System (ADS)

Kotsuki, Shunji; Terasaki, Koji; Yashiro, Hasashi; Tomita, Hirofumi; Satoh, Masaki; Miyoshi, Takemasa

2017-04-01

This study aims to improve precipitation forecasts from numerical weather prediction (NWP) models through effective use of satellite-derived precipitation data. Kotsuki et al. (2016, JGR-A) successfully improved the precipitation forecasts by assimilating the Japan Aerospace eXploration Agency (JAXA)'s Global Satellite Mapping of Precipitation (GSMaP) data into the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) at 112-km horizontal resolution. Kotsuki et al. mitigated the non-Gaussianity of the precipitation variables by the Gaussian transform method for observed and forecasted precipitation using the previous 30-day precipitation data. This study extends the previous study by Kotsuki et al. and explores an online estimation of model parameters using ensemble data assimilation. We choose two globally-uniform parameters, one is the cloud-to-rain auto-conversion parameter of the Berry's scheme for large scale condensation and the other is the relative humidity threshold of the Arakawa-Schubert cumulus parameterization scheme. We perform the online-estimation of the two model parameters with an ensemble transform Kalman filter by assimilating the GSMaP precipitation data. The estimated parameters improve the analyzed and forecasted mixing ratio in the lower troposphere. Therefore, the parameter estimation would be a useful technique to improve the NWP models and their forecasts. This presentation will include the most recent progress up to the time of the symposium.

The Predicted Influence of Climate Change on Lesser Prairie-Chicken Reproductive Parameters

PubMed Central

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, Dawn M.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001–2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter’s linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival. PMID:23874549

Modelling chemical depletion profiles in regolith

USGS Publications Warehouse

Brantley, S.L.; Bandstra, J.; Moore, J.; White, A.F.

2008-01-01

Chemical or mineralogical profiles in regolith display reaction fronts that document depletion of leachable elements or minerals. A generalized equation employing lumped parameters was derived to model such ubiquitously observed patterns:C = frac(C0, frac(C0 - Cx = 0, Cx = 0) exp (??ini ?? over(k, ??) ?? x) + 1)Here C, Cx = 0, and Co are the concentrations of an element at a given depth x, at the top of the reaction front, or in parent respectively. ??ini is the roughness of the dissolving mineral in the parent and k???? is a lumped kinetic parameter. This kinetic parameter is an inverse function of the porefluid advective velocity and a direct function of the dissolution rate constant times mineral surface area per unit volume regolith. This model equation fits profiles of concentration versus depth for albite in seven weathering systems and is consistent with the interpretation that the surface area (m2 mineral m- 3 bulk regolith) varies linearly with the concentration of the dissolving mineral across the front. Dissolution rate constants can be calculated from the lumped fit parameters for these profiles using observed values of weathering advance rate, the proton driving force, the geometric surface area per unit volume regolith and parent concentration of albite. These calculated values of the dissolution rate constant compare favorably to literature values. The model equation, useful for reaction fronts in both steady-state erosional and quasi-stationary non-erosional systems, incorporates the variation of reaction affinity using pH as a master variable. Use of this model equation to fit depletion fronts for soils highlights the importance of buffering of pH in the soil system. Furthermore, the equation should allow better understanding of the effects of important environmental variables on weathering rates. ?? 2008.

Determining the vertical evolution of hydrodynamic parameters in weathered and fractured south Indian crystalline-rock aquifers: insights from a study on an instrumented site

NASA Astrophysics Data System (ADS)

Boisson, A.; Guihéneuf, N.; Perrin, J.; Bour, O.; Dewandel, B.; Dausse, A.; Viossanges, M.; Ahmed, S.; Maréchal, J. C.

2015-02-01

Due to extensive irrigation, most crystalline aquifers of south India are overexploited. Aquifer structure consists of an upper weathered saprolite followed by a fractured zone whose fracture density decreases with depth. To achieve sustainable management, the evolution of hydrodynamic parameters (transmissivity and storage coefficient) by depth in the south Indian context should be quantified. Falling-head borehole permeameter tests, injection tests, flowmeter profiles, single-packer tests and pumping tests were carried out in the unsaturated saprolite and saturated fractured granite. Results show that the saprolite is poorly transmissive (T fs = 3 × 10-7 to 8.5 × 10-8 m2 s-1) and that the most conductive part of the aquifer corresponds to the bottom of the saprolite and the upper part of the fractured rock (T = 1.0 × 10-3 to 7.0 × 10-4 m2 s-1). The transmissivity along the profile is mostly controlled by two distinct conductive zones without apparent vertical hydraulic connection. The transmissivity and storage coefficient both decrease with depth depending on the saturation of the main fracture zones, and boreholes are not exploitable after a certain depth (27.5 m on the investigated section). The numerous investigations performed allow a complete quantification with depth of the hydrodynamic parameters along the weathering profile, and a conceptual model is presented. Hydrograph observations (4 years) are shown to be relevant as a first-order characterization of the media and diffusivity evolution with depth. The evolution of these hydrodynamic parameters along the profile has a great impact on groundwater prospecting, exploitation and transport properties in such crystalline rock aquifers.

Selected instability indices in Europe

NASA Astrophysics Data System (ADS)

Siedlecki, Mariusz

2009-04-01

A climatology of various parameters associated with severe weather and convective storms has been created for Europe that involves using radiosounding data collected at the University of Wyoming for the period from 1991 to 2005. The analysis is based on monthly means, frequency distributions of such parameters as convective available potential energy (CAPE), convective inhibition energy (CIN), KI - index, total totals index (TTI), and the severe weather threat index (SWEAT). Monthly average CAPE values exceeding 300 Jkg-1 are observed over the west Mediterranean Sea and the neighboring coastal countries. The similar seasonal cycle and spatial distributions exhibit CIN fields with summer monthly means above 100 Jkg-1 observed on the south part of the researched domain. The KI, TTI, and SWEAT indices, which assess both the lapse ratio between 850 and 500 hPa and low level humidity, show the privileged region (the Alpine area and the Carpathian Basin) with the highest instability conditions. Orography clearly plays an important role in this structure. Farther from this area, the monthly average decreases to the east, west, north, and south of the research domain. Ward’s procedure was applied to create objective regionalization according to instability conditions. This method tends to produce two regions with relatively different instability conditions and few subregions with similar conditions. The first region, covering the Alpine area, the west Mediterranean Sea, west Turkey and the southern Ukraine, is characterized by the highest instability. The rest of the investigated area is the second region with a more stable atmosphere.

A Meta-Analysis quantifying the relationships between response to nitrogen fertilization vs soil texture and weather

USDA-ARS?s Scientific Manuscript database

Weather and soil properties are known to affect soil nitrogen (N) availability and plant N uptake. Studies examining N response as affected by soil and weather sometimes give conflicting results. Meta-analysis is a statistical method for estimating treatment effects in a series of experiments...

Interactive Exercises for an Introductory Weather and Climate Course

ERIC Educational Resources Information Center

Carbone, Gregory J.; Power, Helen C.

2005-01-01

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…

Evolution of porosity and diffusivity associated with chemical weathering of a basalt clast

DOE Office of Scientific and Technical Information (OSTI.GOV)

Navarre-Sitchler, A.; Steefel, C.I.; Yang, L.

Weathering of rocks as a result of exposure to water and the atmosphere can cause significant changes in their chemistry and porosity. In low-porosity rocks, such as basalts, changes in porosity, resulting from chemical weathering, are likely to modify the rock's effective diffusivity and permeability, affecting the rate of solute transport and thus potentially the rate of overall weathering to the extent that transport is the rate limiting step. Changes in total porosity as a result of mineral dissolution and precipitation have typically been used to calculate effective diffusion coefficients through Archie's law for reactive transport simulations of chemical weathering,more » but this approach fails to account for unconnected porosity that does not contribute to transport. In this study, we combine synchrotron X-ray microcomputed tomography ({mu}CT) and laboratory and numerical diffusion experiments to examine changes in both total and effective porosity and effective diffusion coefficients across a weathering interface in a weathered basalt clast from Costa Rica. The {mu}CT data indicate that below a critical value of {approx}9%, the porosity is largely unconnected in the basalt clast. The {mu}CT data were further used to construct a numerical pore network model to determine upscaled, effective diffusivities as a function of total porosity (ranging from 3 to 30%) for comparison with diffusivities determined in laboratory tracer experiments. By using effective porosity as the scaling parameter and accounting for critical porosity, a model is developed that accurately predicts continuum-scale effective diffusivities across the weathering interface of the basalt clast.« less

Sobol' sensitivity analysis for stressor impacts on honeybee ...

EPA Pesticide Factsheets

We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather, colony resources, population structure, and other important variables. This allows us to test the effects of defined pesticide exposure scenarios versus controlled simulations that lack pesticide exposure. The daily resolution of the model also allows us to conditionally identify sensitivity metrics. We use the variancebased global decomposition sensitivity analysis method, Sobol’, to assess firstand secondorder parameter sensitivities within VarroaPop, allowing us to determine how variance in the output is attributed to each of the input variables across different exposure scenarios. Simulations with VarroaPop indicate queen strength, forager life span and pesticide toxicity parameters are consistent, critical inputs for colony dynamics. Further analysis also reveals that the relative importance of these parameters fluctuates throughout the simulation period according to the status of other inputs. Our preliminary results show that model variability is conditional and can be attributed to different parameters depending on different timescales. By using sensitivity analysis to assess model output and variability, calibrations of simulation models can be better informed to yield more

On the effect of model parameters on forecast objects

NASA Astrophysics Data System (ADS)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

A comparative analysis of extended water cloud model and backscatter modelling for above-ground biomass assessment in Corbett Tiger Reserve

NASA Astrophysics Data System (ADS)

Kumar, Yogesh; Singh, Sarnam; Chatterjee, R. S.; Trivedi, Mukul

2016-04-01

Forest biomass acts as a backbone in regulating the climate by storing carbon within itself. Thus the assessment of forest biomass is crucial in understanding the dynamics of the environment. Traditionally the destructive methods were adopted for the assessment of biomass which were further advanced to the non-destructive methods. The allometric equations developed by destructive methods were further used in non-destructive methods for the assessment, but they were mostly applied for woody/commercial timber species. However now days Remote Sensing data are primarily used for the biomass geospatial pattern assessment. The Optical Remote Sensing data (Landsat8, LISS III, etc.) are being used very successfully for the estimation of above ground biomass (AGB). However optical data is not suitable for all atmospheric/environmental conditions, because it can't penetrate through clouds and haze. Thus Radar data is one of the alternate possible ways to acquire data in all-weather conditions irrespective of weather and light. The paper examines the potential of ALOS PALSAR L-band dual polarisation data for the estimation of AGB in the Corbett Tiger Reserve (CTR) covering an area of 889 km2. The main focus of this study is to explore the accuracy of Polarimetric Scattering Model (Extended Water Cloud Model (EWCM) with respect to Backscatter model in the assessment of AGB. The parameters of the EWCM were estimated using the decomposition components (Raney Decomposition) and the plot level information. The above ground biomass in the CTR ranges from 9.6 t/ha to 322.6 t/ha.

Bird migration flight altitudes studied by a network of operational weather radars.

PubMed

Dokter, Adriaan M; Liechti, Felix; Stark, Herbert; Delobbe, Laurent; Tabary, Pierre; Holleman, Iwan

2011-01-06

A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which--when extended to multiple radars--enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe.

[The influence of the climatic and weather conditions on the mechanisms underlying the formation of enhanced meteosensitivity (a literature review)].

PubMed

Uyanaeva, A I; Tupitsyna, Yu Yu; Rassulova, M A; Turova, E A; Lvova, N V; Ajrapetova, N S

The present review concerns the problem of the influence of the climatic conditions on the human body, the creation of the medical weather forecast service, the development of non-pharmacological methods for the correction of meteopathic disorders, and the reduction of the risk of the complications provoked by the unfavourable weather conditions. The literature data are used to analyse the influence of climatic and weather factors on the formation of enhanced meteosensitivity and the development of exacerbations of chronic non-communicable diseases under the influence of weather conditions. It is concluded that marked changes of the weather may lead to an increased frequency of exacerbations of the chronic non-communicable diseases. The influence of weather and climate on human health is becoming an increasingly important factor under the current conditions bearing in mind the modern tendency toward variations of the global climatic conditions and their specific regional manifestations. The authors emphasize the necessity of the identification and evaluation of the predictors of the development of high meteosensitivity for the prognostication of the risks of the meteopathic reactions and the complications associated with the changes in weather conditions as well as the importance of the improvement of the existing and the development of new methods for the non-pharmacological prevention and correction of enhanced meteosensitivity with the application of the natural and preformed physical factors.

Identifying when weather influences life-history traits of grazing herbivores.

PubMed

Sims, Michelle; Elston, David A; Larkham, Ann; Nussey, Daniel H; Albon, Steve D

2007-07-01

1. There is increasing evidence that density-independent weather effects influence life-history traits and hence the dynamics of populations of animals. Here, we present a novel statistical approach to estimate when such influences are strongest. The method is demonstrated by analyses investigating the timing of the influence of weather on the birth weight of sheep and deer. 2. The statistical technique allowed for the pattern of temporal correlation in the weather data enabling the effects of weather in many fine-scale time intervals to be investigated simultaneously. Thus, while previous studies have typically considered weather averaged across a single broad time interval during pregnancy, our approach enabled examination simultaneously of the relationships with weekly and fortnightly averages throughout the whole of pregnancy. 3. We detected a positive effect of temperature on the birth weight of deer, which is strongest in late pregnancy (mid-March to mid-April), and a negative effect of rainfall on the birthweight of sheep, which is strongest during mid-pregnancy (late January to early February). The possible mechanisms underlying these weather-birth weight relationships are discussed. 4. This study enhances our insight into the pattern of the timing of influence of weather on early development. The method is of much more general application and could provide valuable insights in other areas of ecology in which sequences of intercorrelated explanatory variables have been collected in space or in time.

Bird migration flight altitudes studied by a network of operational weather radars

PubMed Central

Dokter, Adriaan M.; Liechti, Felix; Stark, Herbert; Delobbe, Laurent; Tabary, Pierre; Holleman, Iwan

2011-01-01

A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which—when extended to multiple radars—enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe. PMID:20519212

Reconstruction of missed critical frequency of F2-layer over Mexico using TEC

NASA Astrophysics Data System (ADS)

Sergeeva, M. A.; Maltseva, O. A.; Gonzalez-Esparza, A.; Romero Hernandez, E.; De la Luz, V.; Rodriguez-Martinez, M. R.

2016-12-01

The study of the Earth's ionosphere's state is one of the key issues within the Space Weather monitoring task. It is hard to overestimate the importance of diagnostics of its current state and forecasts of Space Weather conditions. There are different methods of short-time predictions for the ionosphere state change. The real-time monitoring of the ionospheric Total Electron Content (TEC) provides the opportunity to choose an appropriate technique for the particular observation point on the Earth. From September 2015 the continuous monitoring of TEC variations over the territory of Mexico is performed by the Mexican Space Weather Service (SCiESMEX). Regular patterns of the diurnal and seasonal TEC variations were revealed in base of past statistics and real-time observations which can be used to test the prediction method. Some specific features of the ionosphere behaviour are discussed. However, with all the merits of TEC as an ionospheric parameter, for the full picture of the processes in the ionosphere and for practical applications it is needed to identify the behaviour of other principal ionospheric parameters provided by ionosondes. Currently, SCiESMEX works on the project of the ionosonde installation in Mexico. This study was focused on the reconstruction of the critical frequency of F2-layer of the ionosphere (foF2) when this data is missing. For this purpose measurements of TEC and the median value of the equivalent slab thickness of the ionosphere were used. First, the foF2 values reconstruction was made for the case of the ionosonde data being absent during some hours or days. Second, the possibility of foF2 reconstruction was estimated for the Mexican region having no ionosonde using local TEC data and foF2 data obtained in the regions close to Mexico. Calculations were performed for quiet and disturbed periods. The results of reconstruction were compared to the foF2 obtained from the International Reference Model and to median foF2 values. Comparison with other low-and mid-latitude regions was made. It was shown that foF2 reconstructed using TEC have better agreement with the experimental data. Considering the said above, the use of the reconstructed foF2 values is a great aid for the ionosphere state estimation over Mexico when foF2 information is missed.

Optimizing biomass feedstock blends with respect to cost, supply, and quality for catalyzed and uncatalyzed fast pyrolysis applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, Vicki S.; Aston, John E.; Lacey, Jeffrey A.

Here, biomass cost, quality and quantity are important parameters to consider when choosing feedstocks and locations for biorefineries. Biomass cost is dependent upon type, location, quantities available in a given area and logistics costs as well the quality needed for the biorefinery. Biomass quality depends upon type, growth conditions, weather, harvesting methods, storage conditions as well as any preprocessing methods used to improve quality. Biomass quantity depends heavily on location as well as growth conditions, weather, harvesting methods and storage conditions. This study examines how all three of these parameters affect the biomass mixture that is needed in a biomassmore » depot or biorefinery to achieve the lowest cost with the highest quality and at the quantities needed for biorefinery operation. Four biomass depots were proposed in South Carolina that would each process the predominant type of biomass available in that area and each produce 200,000 tons of feedstock per year. These depots would then feed a centrally located 800,000 ton biorefinery that would convert the feedstocks to pyrolysis oil using either catalyzed or uncatalyzed fast pyrolysis. The four depots each needed to produce different blends of biomass based upon the quantities available to them but still meet the minimum quality requirements for the biorefinery. Costs were minimized by using waste biomass resources such as construction and demolition waste, logging residues and forest residuals. Depending upon the quality specification required by the biorefinery, it was necessary to utilize preprocessing methods such as air classification and acid leaching to upgrade biomass quality. In the case of uncatalyzed fast pyrolysis, all four depots could produce biomass blends that were lower cost than the the preferred pyrolysis feedstock, clean pine, and meet quality and quantity specifications. For catalyzed fast pyrolysis, three of the four depots were able to produce blends that met both quality and quantity specifications at minimum cost. The fourth depot would not be able to produce a blend meeting specifications without increasing the supply radius for the depot.« less

Optimizing biomass feedstock blends with respect to cost, supply, and quality for catalyzed and uncatalyzed fast pyrolysis applications

DOE PAGES

Thompson, Vicki S.; Aston, John E.; Lacey, Jeffrey A.; ...

2017-05-24

Here, biomass cost, quality and quantity are important parameters to consider when choosing feedstocks and locations for biorefineries. Biomass cost is dependent upon type, location, quantities available in a given area and logistics costs as well the quality needed for the biorefinery. Biomass quality depends upon type, growth conditions, weather, harvesting methods, storage conditions as well as any preprocessing methods used to improve quality. Biomass quantity depends heavily on location as well as growth conditions, weather, harvesting methods and storage conditions. This study examines how all three of these parameters affect the biomass mixture that is needed in a biomassmore » depot or biorefinery to achieve the lowest cost with the highest quality and at the quantities needed for biorefinery operation. Four biomass depots were proposed in South Carolina that would each process the predominant type of biomass available in that area and each produce 200,000 tons of feedstock per year. These depots would then feed a centrally located 800,000 ton biorefinery that would convert the feedstocks to pyrolysis oil using either catalyzed or uncatalyzed fast pyrolysis. The four depots each needed to produce different blends of biomass based upon the quantities available to them but still meet the minimum quality requirements for the biorefinery. Costs were minimized by using waste biomass resources such as construction and demolition waste, logging residues and forest residuals. Depending upon the quality specification required by the biorefinery, it was necessary to utilize preprocessing methods such as air classification and acid leaching to upgrade biomass quality. In the case of uncatalyzed fast pyrolysis, all four depots could produce biomass blends that were lower cost than the the preferred pyrolysis feedstock, clean pine, and meet quality and quantity specifications. For catalyzed fast pyrolysis, three of the four depots were able to produce blends that met both quality and quantity specifications at minimum cost. The fourth depot would not be able to produce a blend meeting specifications without increasing the supply radius for the depot.« less

Estimation of future flow regime for a spatially varied Himalayan watershed using improved multi-site calibration method of SWAT model.

NASA Astrophysics Data System (ADS)

Pradhanang, S. M.; Hasan, M. A.; Booth, P.; Fallatah, O.

2016-12-01

The monsoon and snow driven regime in the Himalayan region has received increasing attention in the recent decade regarding the effects of climate change on hydrologic regimes. Modeling streamflow in such spatially varied catchment requires proper calibration and validation in hydrologic modeling. While calibration and validation are time consuming and computationally intensive, an effective regionalized approach with multi-site information is crucial for flow estimation, especially in daily scale. In this study, we adopted a multi-site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for the Karnali river catchment, which is characterized as being the most vulnerable catchment to climate change in the Himalayan region. APHRODITE's (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) daily gridded precipitation data, one of the accurate and reliable weather date over this region were utilized in this study. The model evaluation of the entire catchment divided into four sub-catchments, utilizing discharge records from 1963 to 2010. In previous studies, multi-site calibration used only a single set of calibration parameters for all sub-catchment of a large watershed. In this study, we introduced a technique that can incorporate different sets of calibration parameters for each sub-basin, which eventually ameliorate the flow of the whole watershed. Results show that the calibrated model with new method can capture almost identical pattern of flow over the region. The predicted daily streamflow matched the observed values, with a Nash-Sutcliffe coefficient of 0.73 during calibration and 0.71 during validation period. The method perfumed better than existing multi-site calibration methods. To assess the influence of continued climate change on hydrologic processes, we modified the weather inputs for the model using precipitation and temperature changes for two Representative Concentration Pathways (RCPs) scenarios, RCP 4.5 and 8.5. Climate simulation for RCP scenarios were conducted from 1981-2100, where 1981-2005 was considered as baseline and 2006-2100 was considered as the future projection. The result shows that probability of flooding will eventually increase in future years due to increased flow in both scenarios.

Improving vehicle tracking rate and speed estimation in dusty and snowy weather conditions with a vibrating camera

PubMed Central

Yaghoobi Ershadi, Nastaran

2017-01-01

Traffic surveillance systems are interesting to many researchers to improve the traffic control and reduce the risk caused by accidents. In this area, many published works are only concerned about vehicle detection in normal conditions. The camera may vibrate due to wind or bridge movement. Detection and tracking of vehicles is a very difficult task when we have bad weather conditions in winter (snowy, rainy, windy, etc.), dusty weather in arid and semi-arid regions, at night, etc. Also, it is very important to consider speed of vehicles in the complicated weather condition. In this paper, we improved our method to track and count vehicles in dusty weather with vibrating camera. For this purpose, we used a background subtraction based strategy mixed with an extra processing to segment vehicles. In this paper, the extra processing included the analysis of the headlight size, location, and area. In our work, tracking was done between consecutive frames via a generalized particle filter to detect the vehicle and pair the headlights using the connected component analysis. So, vehicle counting was performed based on the pairing result, with Centroid of each blob we calculated distance between two frames by simple formula and hence dividing it by the time between two frames obtained from the video. Our proposed method was tested on several video surveillance records in different conditions such as dusty or foggy weather, vibrating camera, and in roads with medium-level traffic volumes. The results showed that the new proposed method performed better than our previously published method and other methods, including the Kalman filter or Gaussian model, in different traffic conditions. PMID:29261719

Improving vehicle tracking rate and speed estimation in dusty and snowy weather conditions with a vibrating camera.

PubMed

Yaghoobi Ershadi, Nastaran

2017-01-01

Traffic surveillance systems are interesting to many researchers to improve the traffic control and reduce the risk caused by accidents. In this area, many published works are only concerned about vehicle detection in normal conditions. The camera may vibrate due to wind or bridge movement. Detection and tracking of vehicles is a very difficult task when we have bad weather conditions in winter (snowy, rainy, windy, etc.), dusty weather in arid and semi-arid regions, at night, etc. Also, it is very important to consider speed of vehicles in the complicated weather condition. In this paper, we improved our method to track and count vehicles in dusty weather with vibrating camera. For this purpose, we used a background subtraction based strategy mixed with an extra processing to segment vehicles. In this paper, the extra processing included the analysis of the headlight size, location, and area. In our work, tracking was done between consecutive frames via a generalized particle filter to detect the vehicle and pair the headlights using the connected component analysis. So, vehicle counting was performed based on the pairing result, with Centroid of each blob we calculated distance between two frames by simple formula and hence dividing it by the time between two frames obtained from the video. Our proposed method was tested on several video surveillance records in different conditions such as dusty or foggy weather, vibrating camera, and in roads with medium-level traffic volumes. The results showed that the new proposed method performed better than our previously published method and other methods, including the Kalman filter or Gaussian model, in different traffic conditions.

Predictability Analysis of PM10 Concentrations in Budapest

NASA Astrophysics Data System (ADS)

Ferenczi, Zita

2013-04-01

Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.

A conceptual weather-type classification procedure for the Philadelphia, Pennsylvania, area

USGS Publications Warehouse

McCabe, Gregory J.

1990-01-01

A simple method of weather-type classification, based on a conceptual model of pressure systems that pass through the Philadelphia, Pennsylvania, area, has been developed. The only inputs required for the procedure are daily mean wind direction and cloud cover, which are used to index the relative position of pressure systems and fronts to Philadelphia.Daily mean wind-direction and cloud-cover data recorded at Philadelphia, Pennsylvania, from January 1954 through August 1988 were used to categorize daily weather conditions. The conceptual weather types reflect changes in daily air and dew-point temperatures, and changes in monthly mean temperature and monthly and annual precipitation. The weather-type classification produced by using the conceptual model was similar to a classification produced by using a multivariate statistical classification procedure. Even though the conceptual weather types are derived from a small amount of data, they appear to account for the variability of daily weather patterns sufficiently to describe distinct weather conditions for use in environmental analyses of weather-sensitive processes.

Subsurface Salts in Antarctic Dry Valley Soils

NASA Technical Reports Server (NTRS)

Englert, P.; Bishop, J. L.; Gibson, E. K.; Koeberl, C.

2013-01-01

The distribution of water-soluble ions, major and minor elements, and other parameters were examined to determine the extent and effects of chemical weathering on cold desert soils. Patterns at the study sites support theories of multiple salt forming processes, including marine aerosols and chemical weathering of mafic minerals. Periodic solar-mediated ionization of atmospheric nitrogen might also produce high nitrate concentrations found in older sediments. Chemical weathering, however, was the major contributor of salts in Antarctic Dry Valleys. The Antarctic Dry Valleys represent a unique analog for Mars, as they are extremely cold and dry desert environments. Similarities in the climate, surface geology, and chemical properties of the Dry Valleys to that of Mars imply the possible presence of these soil formation mechanisms on Mars, other planets and icy satellites.

Estimation of daily reference evapotranspiration (ETo) using artificial intelligence methods: Offering a new approach for lagged ETo data-based modeling

NASA Astrophysics Data System (ADS)

Mehdizadeh, Saeid

2018-04-01

Evapotranspiration (ET) is considered as a key factor in hydrological and climatological studies, agricultural water management, irrigation scheduling, etc. It can be directly measured using lysimeters. Moreover, other methods such as empirical equations and artificial intelligence methods can be used to model ET. In the recent years, artificial intelligence methods have been widely utilized to estimate reference evapotranspiration (ETo). In the present study, local and external performances of multivariate adaptive regression splines (MARS) and gene expression programming (GEP) were assessed for estimating daily ETo. For this aim, daily weather data of six stations with different climates in Iran, namely Urmia and Tabriz (semi-arid), Isfahan and Shiraz (arid), Yazd and Zahedan (hyper-arid) were employed during 2000-2014. Two types of input patterns consisting of weather data-based and lagged ETo data-based scenarios were considered to develop the models. Four statistical indicators including root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE) were used to check the accuracy of models. The local performance of models revealed that the MARS and GEP approaches have the capability to estimate daily ETo using the meteorological parameters and the lagged ETo data as inputs. Nevertheless, the MARS had the best performance in the weather data-based scenarios. On the other hand, considerable differences were not observed in the models' accuracy for the lagged ETo data-based scenarios. In the innovation of this study, novel hybrid models were proposed in the lagged ETo data-based scenarios through combination of MARS and GEP models with autoregressive conditional heteroscedasticity (ARCH) time series model. It was concluded that the proposed novel models named MARS-ARCH and GEP-ARCH improved the performance of ETo modeling compared to the single MARS and GEP. In addition, the external analysis of the performance of models at stations with similar climatic conditions denoted the applicability of nearby station' data for estimation of the daily ETo at target station.

Parametric vs. non-parametric daily weather generator: validation and comparison

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin

2016-04-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30 years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database.

Ionospheric Response to Extremes in the Space Environment: Establishing Benchmarks for the Space Weather Action Plan.

NASA Astrophysics Data System (ADS)

Viereck, R. A.; Azeem, S. I.

2017-12-01

One of the goals of the National Space Weather Action Plan is to establish extreme event benchmarks. These benchmarks are estimates of environmental parameters that impact technologies and systems during extreme space weather events. Quantitative assessment of anticipated conditions during these extreme space weather event will enable operators and users of affected technologies to develop plans for mitigating space weather risks and improve preparedness. The ionosphere is one of the most important regions of space because so many applications either depend on ionospheric space weather for their operation (HF communication, over-the-horizon radars), or can be deleteriously affected by ionospheric conditions (e.g. GNSS navigation and timing, UHF satellite communications, synthetic aperture radar, HF communications). Since the processes that influence the ionosphere vary over time scales from seconds to years, it continues to be a challenge to adequately predict its behavior in many circumstances. Estimates with large uncertainties, in excess of 100%, may result in operators of impacted technologies over or under preparing for such events. The goal of the next phase of the benchmarking activity is to reduce these uncertainties. In this presentation, we will focus on the sources of uncertainty in the ionospheric response to extreme geomagnetic storms. We will then discuss various research efforts required to better understand the underlying processes of ionospheric variability and how the uncertainties in ionospheric response to extreme space weather could be reduced and the estimates improved.

Exploring adaptations to climate change with stakeholders: A participatory method to design grassland-based farming systems.

PubMed

Sautier, Marion; Piquet, Mathilde; Duru, Michel; Martin-Clouaire, Roger

2017-05-15

Research is expected to produce knowledge, methods and tools to enhance stakeholders' adaptive capacity by helping them to anticipate and cope with the effects of climate change at their own level. Farmers face substantial challenges from climate change, from changes in the average temperatures and the precipitation regime to an increased variability of weather conditions and the frequency of extreme events. Such changes can have dramatic consequences for many types of agricultural production systems such as grassland-based livestock systems for which climate change influences the seasonality and productivity of fodder production. We present a participatory design method called FARMORE (FARM-Oriented REdesign) that allows farmers to design and evaluate adaptations of livestock systems to future climatic conditions. It explicitly considers three climate features in the design and evaluation processes: climate change, climate variability and the limited predictability of weather. FARMORE consists of a sequence of three workshops for which a pre-existing game-like platform was adapted. Various year-round forage production and animal feeding requirements must be assembled by participants with a computerized support system. In workshop 1, farmers aim to produce a configuration that satisfies an average future weather scenario. They refine or revise the previous configuration by considering a sample of the between-year variability of weather in workshop 2. In workshop 3, they explicitly take the limited predictability of weather into account. We present the practical aspects of the method based on four case studies involving twelve farmers from Aveyron (France), and illustrate it through an in-depth description of one of these case studies with three dairy farmers. The case studies shows and discusses how workshop sequencing (1) supports a design process that progressively accommodates complexity of real management contexts by enlarging considerations of climate change to climate variability and low weather predictability, and (2) increases the credibility and salience of the design method. Further enhancements of the method are outlined, especially the selection of pertinent weather scenarios. Copyright © 2017 Elsevier Ltd. All rights reserved.

New Generation of Satellite-Derived Ocean Thermal Structure for the Western North Pacific Typhoon Intensity Forecasting

DTIC Science & Technology

2013-10-26

took 35% of error as a threshold to deter- mine whether the parameters derived by the REGWNP are of acceptable accuracy. Fig. 13 shows the applicable...2000. The interaction between Hurricane Opal (1995) and a warm core ring in the Gulf of Mexico. Monthly Weather Review 128, 1347–1365. Jacob, S.D...Hurricane Opal . Monthly Weather Review 128, 1366–1383. Stephens, C., Antonov, J.I., Boyer, T.P., Conkright, M.E., Locarnini, R.A., O’Brien, T.D., Carcia

P.88 Regional Precipitation Forecast with Atmospheric Infrared Sounder (AIRS) Profiles

NASA Technical Reports Server (NTRS)

Chou, Shih-Hung; Zavodsky, Bradley; Jedlovec, Gary

2010-01-01

Prudent assimulation of AIRS thermodynamic profiles and quality indicators can improve initial conditions for regional weather models. In general, AIRS-enhanced analysis more closely resembles radiosondes than the CNTL; forecasts with AIRS profiles are generally closer to NAM analyses than CNTL for sensible weather parameters (not shown here). Assimilation of AIRS leads to an overall QPF improvement in 6-h accumulated precipitation forecases. Including AIRS profiles in assimilation process enhances the low-level instability and produces stronger updrafts and a better precipitation forecast than the CNTL run.

An Initial Study of the Sensitivity of Aircraft Vortex Spacing System (AVOSS) Spacing Sensitivity to Weather and Configuration Input Parameters

NASA Technical Reports Server (NTRS)

Riddick, Stephen E.; Hinton, David A.

2000-01-01

A study has been performed on a computer code modeling an aircraft wake vortex spacing system during final approach. This code represents an initial engineering model of a system to calculate reduced approach separation criteria needed to increase airport productivity. This report evaluates model sensitivity toward various weather conditions (crosswind, crosswind variance, turbulent kinetic energy, and thermal gradient), code configurations (approach corridor option, and wake demise definition), and post-processing techniques (rounding of provided spacing values, and controller time variance).

The Australian Bureau of Meteorology Activities for the Regional Ionosphere Specification and Forcating

NASA Astrophysics Data System (ADS)

Bouya, Z.; Terkildsen, M.; Maher, P.

2016-12-01

Space Weather Services, Australian Bureau of Meteorology, Sydney, Australia Abstract:The Australian Bureau of Meteorology through its Space Weather Service (SWS) provides ionospheric products and services to a diverse group of customers. In this work, we present a regional approach to characterizing the Australian regional Total Electron Content (TEC) and an assimilative model to map the Ionospheric layer parameter foF2. Finally we outline the design of an Australian regional Ionospheric forecast model at SWS. Keywords: TEC, foF2, regional, data assimilation, forecast

Modeling AWSoM CMEs with EEGGL: A New Approach for Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Jin, M.; Manchester, W.; van der Holst, B.; Sokolov, I.; Toth, G.; Vourlidas, A.; de Koning, C. A.; Gombosi, T. I.

2015-12-01

The major source of destructive space weather is coronal mass ejections (CMEs). However, our understanding of CMEs and their propagation in the heliosphere is limited by the insufficient observations. Therefore, the development of first-principals numerical models plays a vital role in both theoretical investigation and providing space weather forecasts. Here, we present results of the simulation of CME propagation from the Sun to 1AU by combining the analytical Gibson & Low (GL) flux rope model with the state-of-art solar wind model AWSoM. We also provide an approach for transferring this research model to a space weather forecasting tool by demonstrating how the free parameters of the GL flux rope can be prescribed based on remote observations via the new Eruptive Event Generator by Gibson-Low (EEGGL) toolkit. This capability allows us to predict the long-term evolution of the CME in interplanetary space. We perform proof-of-concept case studies to show the capability of the model to capture physical processes that determine CME evolution while also reproducing many observed features both in the corona and at 1 AU. We discuss the potential and limitations of this model as a future space weather forecasting tool.

Surface Landing Site Weather Analysis for NASA's Constellation Program

NASA Technical Reports Server (NTRS)

Altino, Karen M.; Burns, K. L.

2008-01-01

Weather information is an important asset for NASA's Constellation Program in developing the next generation space transportation system to fly to the International Space Station, the Moon and, eventually, to Mars. Weather conditions can affect vehicle safety and performance during multiple mission phases ranging from pre-launch ground processing of the Ares vehicles to landing and recovery operations, including all potential abort scenarios. Meteorological analysis is art important contributor, not only to the development and verification of system design requirements but also to mission planning and active ground operations. Of particular interest are the surface weather conditions at both nominal and abort landing sites for the manned Orion capsule. Weather parameters such as wind, rain, and fog all play critical roles in the safe landing of the vehicle and subsequent crew and vehicle recovery. The Marshall Space Flight Center (MSFC) Natural Environments Branch has been tasked by the Constellation Program with defining the natural environments at potential landing zones. This paper wiI1 describe the methodology used for data collection and quality control, detail the types of analyses performed, and provide a sample of the results that cab be obtained.

A new look at the decomposition of agricultural productivity growth incorporating weather effects.

PubMed

Njuki, Eric; Bravo-Ureta, Boris E; O'Donnell, Christopher J

2018-01-01

Random fluctuations in temperature and precipitation have substantial impacts on agricultural output. However, the contribution of these changing configurations in weather to total factor productivity (TFP) growth has not been addressed explicitly in econometric analyses. Thus, the key objective of this study is to quantify and to investigate the role of changing weather patterns in explaining yearly fluctuations in TFP. For this purpose, we define TFP to be a measure of total output divided by a measure of total input. We estimate a stochastic production frontier model using U.S. state-level agricultural data incorporating growing season temperature and precipitation, and intra-annual standard deviations of temperature and precipitation for the period 1960-2004. We use the estimated parameters of the model to compute a TFP index that has good axiomatic properties. We then decompose TFP growth in each state into weather effects, technological progress, technical efficiency, and scale-mix efficiency changes. This approach improves our understanding of the role of different components of TFP in agricultural productivity growth. We find that annual TFP growth averaged 1.56% between 1960 and 2004. Moreover, we observe substantial heterogeneity in weather effects across states and over time.

A new look at the decomposition of agricultural productivity growth incorporating weather effects

PubMed Central

Bravo-Ureta, Boris E.; O’Donnell, Christopher J.

2018-01-01

Random fluctuations in temperature and precipitation have substantial impacts on agricultural output. However, the contribution of these changing configurations in weather to total factor productivity (TFP) growth has not been addressed explicitly in econometric analyses. Thus, the key objective of this study is to quantify and to investigate the role of changing weather patterns in explaining yearly fluctuations in TFP. For this purpose, we define TFP to be a measure of total output divided by a measure of total input. We estimate a stochastic production frontier model using U.S. state-level agricultural data incorporating growing season temperature and precipitation, and intra-annual standard deviations of temperature and precipitation for the period 1960–2004. We use the estimated parameters of the model to compute a TFP index that has good axiomatic properties. We then decompose TFP growth in each state into weather effects, technological progress, technical efficiency, and scale-mix efficiency changes. This approach improves our understanding of the role of different components of TFP in agricultural productivity growth. We find that annual TFP growth averaged 1.56% between 1960 and 2004. Moreover, we observe substantial heterogeneity in weather effects across states and over time. PMID:29466461

Sensitivity of Turbine-Height Wind Speeds to Parameters in Planetary Boundary-Layer and Surface-Layer Schemes in the Weather Research and Forecasting Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Ben; Qian, Yun; Berg, Larry K.

We evaluate the sensitivity of simulated turbine-height winds to 26 parameters applied in a planetary boundary layer (PBL) scheme and a surface layer scheme of the Weather Research and Forecasting (WRF) model over an area of complex terrain during the Columbia Basin Wind Energy Study. An efficient sampling algorithm and a generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of modeled turbine-height winds. The results indicate that most of the variability in the ensemble simulations is contributed by parameters related to the dissipation of the turbulence kinetic energy (TKE), Prandtl number, turbulencemore » length scales, surface roughness, and the von Kármán constant. The relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability. The parameter associated with the TKE dissipation rate is found to be the most important one, and a larger dissipation rate can produce larger hub-height winds. A larger Prandtl number results in weaker nighttime winds. Increasing surface roughness reduces the frequencies of both extremely weak and strong winds, implying a reduction in the variability of the wind speed. All of the above parameters can significantly affect the vertical profiles of wind speed, the altitude of the low-level jet and the magnitude of the wind shear strength. The wind direction is found to be modulated by the same subset of influential parameters. Remainder of abstract is in attachment.« less

Long-term weather predictability: Ural case study

NASA Astrophysics Data System (ADS)

Kubyshen, Alexander; Shopin, Sergey

2016-04-01

The accuracy of the state-of-the-art long-term meteorological forecast (at the seasonal level) is still low. Here it is presented approach (RAMES method) realizing different forecasting methodology. It provides prediction horizon of up to 19-22 years under equal probabilities of determination of parameters in every analyzed period [1]. Basic statements of the method are the following. 1. Long-term forecast on the basis of numerical modeling of the global meteorological process is principally impossible. Extension of long-term prediction horizon could be obtained only by the revealing and using a periodicity of meteorological situations at one point of observation. 2. Conventional calendar is unsuitable for generalization of meteorological data and revealing of cyclicity of meteorological processes. RAMES method uses natural time intervals: one day, synodic month and one year. It was developed a set of special calendars using these natural periods and the Metonic cycle. 3. Long-term time series of meteorological data is not a uniform universal set, it is a sequence of 28 universal sets appropriately superseding each other in time. The specifics of the method are: 1. Usage of the original research toolkit consisting of - a set of calendars based on the Metonic cycle; - a set of charts (coordinate systems) for the construction of sequence diagrams (of daily variability of a meteorological parameter during the analyzed year; of daily variability of a meteorological parameter using long-term dynamical time series of periods-analogues; of monthly and yearly variability of accumulated value of meteorological parameter). 2. Identification and usage of new virtual meteorological objects having several degrees of generalization appropriately located in the used coordinate systems. 3. All calculations are integrated into the single technological scheme providing comparison and mutual verification of calculation results. During the prolonged testing in the Ural region, it was proved the efficiency of the method for forecasting the following meteorological parameters: ­- air temperature (minimum, maximum, daily mean, diurnal variation, last spring and first autumn freeze); - periods of winds with speeds of >5m/s and the maximal expected wind speed; - precipitation periods and amount of precipitations; -­ relative humidity; - atmospheric pressure. Atmospheric events (thunderstorms, fog) and hydrometeors also occupy the appropriate positions at the sequence diagrams that provides a possibility of long-term forecasting also for these events. Accuracy of forecasts was tested in 2006-2009 years. The difference between the forecasted monthly mean temperature and actual values was <0.5°C in 40.9% of cases, between 0.5°C and 1°C in 18.2% of cases, between 1°C and 1.5°C in 18.2% of cases, <2°C in 86% of cases. The RAMES method provides the toolkit to successfully forecast the weather conditions in advance of several years. 1. A.F. Kubyshen, "RAMES method: revealing the periodicity of meteorological processes and it usage for long-term forecast [Metodika «RAMES»: vyjavlenie periodichnosti meteorologicheskih processov i ee ispol'zovanie dlja dolgosrochnogo prognozirovanija]", in A.E. Fedorov (ed.), Sistema «Planeta Zemlja»: 200 let so dnja rozhdenija Izmaila Ivanovicha Sreznevskogo. 100 let so dnja izdanija ego slovarja drevnerusskogo jazyka. LENAND. Moscow. pp. 305-311. (In Russian)

Modelling Solar Energetic Particle Events Using the iPATH Model

NASA Astrophysics Data System (ADS)

Li, G.; Hu, J.; Ao, X.; Zank, G. P.; Verkhoglyadova, O. P.

2016-12-01

Solar Energetic Particles (SEPs) is the No. 1 space weather hazard. Understanding how particles are energized and propagated in these events is of practical concerns to the manned space missions. In particular, both the radial evolution and the longitudinal extent of a gradual solarenergetic particle (SEP) event are central topics for space weather forecasting. In this talk, I discuss the improved Particle Acceleration and Transport in the Heliosphere (iPATH) model. The iPATH model consists of three parts: (1) an updated ZEUS3D V3.5 MHD module that models thebackground solar wind and the initiation of a CME in a 2D domain; (2) an updated shock acceleration module where we investigate particle acceleration at different longitudinal locations along the surface of a CME-driven shock. Accelerated particle spectrum are obtained at the shock under the diffusive shock acceleration mechanism. Shock parameters and particle distributions are recorded and used as inputs for the later part. (3) an updated transport module where we follow the transport of accelerated particles from the shock to any destinations (Earth and/or Mars, e.g.) using a Monte-Carlo method. Both pitch angle scattering due to MHD turbulence and perpendicular diffusion across magnetic field are included. Our iPATH model is therefore intrinsically 2D in nature. The model is capable of generating time intensity profiles and instantaneous particle spectra atvarious locations and can greatly improve our current space weather forecasting capability.

Effects of rainfall events on the occurrence and detection efficiency of viruses in river water impacted by combined sewer overflows.

PubMed

Hata, Akihiko; Katayama, Hiroyuki; Kojima, Keisuke; Sano, Shoichi; Kasuga, Ikuro; Kitajima, Masaaki; Furumai, Hiroaki

2014-01-15

Rainfall events can introduce large amount of microbial contaminants including human enteric viruses into surface water by intermittent discharges from combined sewer overflows (CSOs). The present study aimed to investigate the effect of rainfall events on viral loads in surface waters impacted by CSO and the reliability of molecular methods for detection of enteric viruses. The reliability of virus detection in the samples was assessed by using process controls for virus concentration, nucleic acid extraction and reverse transcription (RT)-quantitative PCR (qPCR) steps, which allowed accurate estimation of virus detection efficiencies. Recovery efficiencies of poliovirus in river water samples collected during rainfall events (<10%) were lower than those during dry weather conditions (>10%). The log10-transformed virus concentration efficiency was negatively correlated with suspended solid concentration (r(2)=0.86) that increased significantly during rainfall events. Efficiencies of DNA extraction and qPCR steps determined with adenovirus type 5 and a primer sharing control, respectively, were lower in dry weather. However, no clear relationship was observed between organic water quality parameters and efficiencies of these two steps. Observed concentrations of indigenous enteric adenoviruses, GII-noroviruses, enteroviruses, and Aichi viruses increased during rainfall events even though the virus concentration efficiency was presumed to be lower than in dry weather. The present study highlights the importance of using appropriate process controls to evaluate accurately the concentration of water borne enteric viruses in natural waters impacted by wastewater discharge, stormwater, and CSOs. © 2013.

Exploring gravity wave characteristics in 3-D using a novel S-transform technique: AIRS/Aqua measurements over the Southern Andes and Drake Passage

NASA Astrophysics Data System (ADS)

Wright, Corwin J.; Hindley, Neil P.; Hoffmann, Lars; Alexander, M. Joan; Mitchell, Nicholas J.

2017-07-01

Gravity waves (GWs) transport momentum and energy in the atmosphere, exerting a profound influence on the global circulation. Accurately measuring them is thus vital both for understanding the atmosphere and for developing the next generation of weather forecasting and climate prediction models. However, it has proven very difficult to measure the full set of GW parameters from satellite measurements, which are the only suitable observations with global coverage. This is particularly critical at latitudes close to 60° S, where climate models significantly under-represent wave momentum fluxes. Here, we present a novel fully 3-D method for detecting and characterising GWs in the stratosphere. This method is based around a 3-D Stockwell transform, and can be applied retrospectively to existing observed data. This is the first scientific use of this spectral analysis technique. We apply our method to high-resolution 3-D atmospheric temperature data from AIRS/Aqua over the altitude range 20-60 km. Our method allows us to determine a wide range of parameters for each wave detected. These include amplitude, propagation direction, horizontal/vertical wavelength, height/direction-resolved momentum fluxes (MFs), and phase and group velocity vectors. The latter three have not previously been measured from an individual satellite instrument. We demonstrate this method over the region around the Southern Andes and Antarctic Peninsula, the largest known sources of GW MFs near the 60° S belt. Our analyses reveal the presence of strongly intermittent highly directionally focused GWs with very high momentum fluxes (˜ 80-100 mPa or more at 30 km altitude). These waves are closely associated with the mountains rather than the open ocean of the Drake Passage. Measured fluxes are directed orthogonal to both mountain ranges, consistent with an orographic source mechanism, and are largest in winter. Further, our measurements of wave group velocity vectors show clear observational evidence that these waves are strongly focused into the polar night wind jet, and thus may contribute significantly to the missing momentum at these latitudes. These results demonstrate the capabilities of our new method, which provides a powerful tool for delivering the observations required for the next generation of weather and climate models.

Adjustment of corn nitrogen in-season fertilization based on soil texture and weather conditions: a Meta-analysis of North American trials

USDA-ARS?s Scientific Manuscript database

Soil properties and weather conditions are known to affect soil nitrogen (N) availability and plant N uptake. However, studies examining N response as affected by soil and weather sometimes give conflicting results. Meta-analysis is a statistical method for estimating treatment effects in a series o...

Simulating spatial and temporally related fire weather

Treesearch

Isaac C. Grenfell; Mark Finney; Matt Jolly

2010-01-01

Use of fire behavior models has assumed an increasingly important role for managers of wildfire incidents to make strategic decisions. For fire risk assessments and danger rating at very large spatial scales, these models depend on fire weather variables or fire danger indices. Here, we describe a method to simulate fire weather at a national scale that captures the...

Models of Weather Impact on Air Traffic

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Wang, Yao

2017-01-01

Flight delays have been a serious problem in the national airspace system costing about $30B per year. About 70 of the delays are attributed to weather and upto two thirds of these are avoidable. Better decision support tools would reduce these delays and improve air traffic management tools. Such tools would benefit from models of weather impacts on the airspace operations. This presentation discusses use of machine learning methods to mine various types of weather and traffic data to develop such models.

Quantifying Heterogeneities in Soil Cover and Weathering in the Bitterroot and Sapphire Mountains, Montana: Implications for Glacial Legacies and their Morphologic Control on Soil Formation

NASA Astrophysics Data System (ADS)

Benjaram, S. S.; Dixon, J. L.

2017-12-01

To what extent is chemical weathering governed by a landscape's topography? Quantifying chemical weathering in both steep rocky landscapes and soil-mantled landscapes requires describing heterogeneity in soil and rock cover at local and landscape scales. Two neighboring mountain ranges in the northern Rockies of western Montana, USA, provide an ideal natural laboratory in which to investigate the relationship between soil chemical weathering, persistence of soil cover, and topography. We focus our work in the previously glaciated Bitterroot Mountains, which consist of steep, rock-dominated hillslopes, and the neighboring unglaciated Sapphire Mountains, which display convex, soil-mantled hillslopes. Soil thickness measurements, soil and rock geochemistry, and digital terrain analysis reveal that soils in the rock-dominated Bitterroot Mountains are only slightly less weathered than those in the Sapphire Mountains. However, these differences are magnified when adjusted for rock fragments at a local scale and bedrock cover at a landscape scale, using our newly developed metric, the rock-adjusted chemical depletion fraction (RACDF) and rock-adjusted mass transfer coefficient (RA τ). The Bitterroots overall are 30% less weathered than the Sapphires despite higher mean annual precipitation in the former, with an average rock-adjusted CDF of 0.38 in the postglacial Bitterroots catchment and 0.61 in the nonglacial Sapphire catchment, suggesting that 38% of rock mass is lost in the conversion to soil in the Bitterroots, whereas 61% of rock mass is lost in the nonglaciated Sapphires. Because the previously glaciated Bitterroots are less weathered despite being wetter, we conclude that the glacial history of this landscape exerts more influence on soil chemical weathering than does modern climate. However, while previous studies have correlated weathering intensity with topographic parameters such as slope gradient, we find little topographic indication of specific controls on weathering in these complex systems.

Geochemistry of the dissolved loads of the Liao River basin in northeast China under anthropogenic pressure: Chemical weathering and controlling factors

NASA Astrophysics Data System (ADS)

Ding, Hu; Liu, Cong-Qiang; Zhao, Zhi-Qi; Li, Si-Liang; Lang, Yun-Chao; Li, Xiao-Dong; Hu, Jian; Liu, Bao-Jian

2017-05-01

This study focuses on the chemical and Sr isotopic compositions of the dissolved load of the rivers in the Liao River basin, which is one of the principal river systems in northeast China. Water samples were collected from both the tributaries and the main channel of the Liao River, Daling River and Hun-Tai River. Chemical and isotopic analyses indicated that four major reservoirs (carbonates (+gypsum), silicates, evaporites and anthropogenic inputs) contribute to the total dissolved solutes. Other than carbonate (+gypsum) weathering, anthropogenic inputs provide the majority of the solutes in the river water. The estimated chemical weathering rates (as TDS) of silicate, carbonate (+gypsum) and evaporites are 0.28, 3.12 and 0.75 t/km2/yr for the main stream of the Liao River and 7.01, 25.0 and 2.80 t/km2/yr for the Daliao River, respectively. The associated CO2 consumption rates by silicate weathering and carbonate (+gypsum) weathering are 10.1 and 9.94 × 103 mol/km2/yr in the main stream of the Liao River and 69.0 and 80.4 × 103 mol/km2/yr in the Hun-Tai River, respectively. The Daling River basin has the highest silicate weathering rate (TDSsil, 3.84 t/km2/yr), and the Hun-Tai River has the highest carbonate weathering rate (TDScarb, 25.0 t/km2/yr). The Raoyang River, with an anthropogenic cation input fraction of up to 49%, has the lowest chemical weathering rates, which indicates that human impact is not a negligible parameter when studying the chemical weathering of these rivers. Both short-term and long-term study of riverine dissolved loads are needed to a better understanding of the chemical weathering and controlling factors.

The use of National Weather Service Data to Compute the Dose to the MEOI.

PubMed

Vickers, Linda

2018-05-01

The Turner method is the "benchmark method" for computing the stability class that is used to compute the X/Q (s m). The Turner method should be used to ascertain the validity of X/Q results determined by other methods. This paper used site-specific meteorological data obtained from the National Weather Service. The Turner method described herein is simple, quick, accurate, and transparent because all of the data, calculations, and results are visible for verification and validation with published literature.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Newsom, R. K.; Sivaraman, C.; Shippert, T. R.

Wind speed and direction, together with pressure, temperature, and relative humidity, are the most fundamental atmospheric state parameters. Accurate measurement of these parameters is crucial for numerical weather prediction. Vertically resolved wind measurements in the atmospheric boundary layer are particularly important for modeling pollutant and aerosol transport. Raw data from a scanning coherent Doppler lidar system can be processed to generate accurate height-resolved measurements of wind speed and direction in the atmospheric boundary layer.

Near-real-time Estimation and Forecast of Total Precipitable Water in Europe

NASA Astrophysics Data System (ADS)

Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.

2013-12-01

Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so-called mod06 results (Cloud Product) are assimilated twice a day (at 00 and 12 UTC) by DBCRAS. DBCRAS creates 72 hours long weather forecasts with 48 km horizontal resolution. DBCRAS is operational at the University since 2009 which means that by now sufficient data is available for the verification of the model. In the present study verification results for the DBCRAS total precipitable water forecasts are presented based on analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Numerical indices are calculated to quantify the performance of DBCRAS. During a limited time period DBCRAS was also ran without assimilating MODIS products which means that there is possibility to quantify the effect of assimilating MODIS physical products on the quality of the forecasts. For this limited time period verification indices are compared to decide whether MODIS data improves forecast quality or not.

Evaluating an education/training module to foster knowledge of cockpit weather technology.

PubMed

Cobbett, Erin A; Blickensderfer, Elizabeth L; Lanicci, John

2014-10-01

Previous research has indicated that general aviation (GA) pilots may use the sophisticated meteorological information available to them via a variety of Next-Generation Weather Radar (NEXRAD) based weather products in a manner that actually decreases flight safety. The current study examined an education/training method designed to enable GA pilots to use NEXRAD-based products effectively in convective weather situations. The training method was lecture combined with paper-based scenario exercises. A multivariate analysis of variance revealed that subjects in the training condition performed significantly better than did subjects in the control condition on several knowledge and attitude measures. Subjects in the training condition improved from a mean score of 66% to 80% on the radar-knowledge test and from 62% to 75% on the scenario-knowledge test. Although additional research is needed, these results demonstrated that pilots can benefit from a well-designed education/training program involving specific areas of aviation weather-related knowledge.

Validation of two (parametric vs non-parametric) daily weather generators

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Skalak, P.

2015-12-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed-like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30-years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).

Design and Evaluation of a Dynamic Programming Flight Routing Algorithm Using the Convective Weather Avoidance Model

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Grabbe, Shon; Mukherjee, Avijit

2010-01-01

The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.

Department of Defense meteorological and environmental inputs to aviation systems

NASA Technical Reports Server (NTRS)

Try, P. D.

1983-01-01

Recommendations based on need, cost, and achievement of flight safety are offered, and the re-evaluation of weather parameters needed for safe landing operations that lead to reliable and consistent automated observation capabilities are considered.

Identification of atmospheric boundary layer thickness using doppler radar datas and WRF - ARW model in Merauke

NASA Astrophysics Data System (ADS)

Putri, R. J. A.; Setyawan, T.

2017-01-01

In the synoptic scale, one of the important meteorological parameter is the atmospheric boundary layer. Aside from being a supporter of the parameters in weather and climate models, knowing the thickness of the layer of the atmosphere can help identify aerosols and the strength of the vertical mixing of pollutants in it. The vertical wind profile data from C-band Doppler radar Mopah-Merauke which is operated by BMKG through Mopah-Merauke Meteorological Station can be used to identify the peak of Atmospheric Boundaryu Layer (ABL). ABL peak marked by increasing wind shear over the layer blending. Samples in January 2015 as a representative in the wet and in July 2015 as the representation of a dry month, shows that ABL heights using WRF models show that in July (sunny weather) ABL height values higher than in January (cloudy)

Six-hourly time series of horizontal troposphere gradients in VLBI analyis

NASA Astrophysics Data System (ADS)

Landskron, Daniel; Hofmeister, Armin; Mayer, David; Böhm, Johannes

2016-04-01

Consideration of horizontal gradients is indispensable for high-precision VLBI and GNSS analysis. As a rule of thumb, all observations below 15 degrees elevation need to be corrected for the influence of azimuthal asymmetry on the delay times, which is mainly a product of the non-spherical shape of the atmosphere and ever-changing weather conditions. Based on the well-known gradient estimation model by Chen and Herring (1997), we developed an augmented gradient model with additional parameters which are determined from ray-traced delays for the complete history of VLBI observations. As input to the ray-tracer, we used operational and re-analysis data from the European Centre for Medium-Range Weather Forecasts. Finally, we applied those a priori gradient parameters to VLBI analysis along with other empirical gradient models and assessed their impact on baseline length repeatabilities as well as on celestial and terrestrial reference frames.

Fatal accidents in nighttime vs. daytime highway construction work zones.

PubMed

Arditi, David; Lee, Dong-Eun; Polat, Gul

2007-01-01

Awareness about worker safety in nighttime construction has been a major concern because it is believed that nighttime construction creates hazardous work conditions. However, only a few studies provide valuable comparative information about accident characteristics of nighttime and daytime highway construction activities. This study investigates fatal accidents that occurred in Illinois highway work zones in the period 1996-2001 in order to determine the safety differences between nighttime and daytime highway construction. The lighting and weather conditions were included into the study as control parameters to see their effects on the frequency of fatal accidents occurring in work zones. According to this study, there is evidence that nighttime construction is more hazardous than daytime construction. The inclusion of a weather parameter into the analysis has limited effect on this finding. The study justifies establishing an efficient work zone accident reporting system and taking all necessary measures to enhance safety in nighttime work zones.

Research on Construction Technology of First Pile in an Urban Expressway under Complicated Conditions

NASA Astrophysics Data System (ADS)

Zhu, Zhi gang

2017-12-01

This paper develops a research method on the construction of the first pile in the process of the construction on an urban expressway under complicated conditions, such as the difference between the underground conditions and the exploration results,the sand formation,the whole weathered and the rich groundwater. We study the relevant technical parameters and construction organization through construction of the first pile. The results show that construction on the first pile is very important under complicated conditions and can provide a basis to continuously improve the level of the whole pile foundation construction technology, and ultimately determine the entire project feasible construction program and the successful completion of the construction project.

Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation. [Great Plains Corridor

NASA Technical Reports Server (NTRS)

Rouse, J. W., Jr. (Principal Investigator); Haas, R. H.; Deering, D. W.; Schell, J. A.; Harlan, J. C.

1974-01-01

The author has identified the following significant results. The Great Plains Corridor rangeland project successfully utilized natural vegetation systems as phenological indicators of seasonal development and climatic effects upon regional growth conditions. An effective method was developed for quantitative measurement of vegetation conditions, including green biomass estimates, recorded in bands 5 and 6, corrected for sun angle, were used to compute a ratio parameter (TV16) which is shown to be highly correlated with green biomass and vegatation moisture content. Analyses results of ERTS-1 digital data and correlated ground data are summarized. Attention was given to analyzing weather influences and test site variables on vegetation condition measurements with ERTS-1 data.

Accuracy evaluation of ClimGen weather generator and daily to hourly disaggregation methods in tropical conditions

NASA Astrophysics Data System (ADS)

Safeeq, Mohammad; Fares, Ali

2011-12-01

Daily and sub-daily weather data are often required for hydrological and environmental modeling. Various weather generator programs have been used to generate synthetic climate data where observed climate data are limited. In this study, a weather data generator, ClimGen, was evaluated for generating information on daily precipitation, temperature, and wind speed at four tropical watersheds located in Hawai`i, USA. We also evaluated different daily to sub-daily weather data disaggregation methods for precipitation, air temperature, dew point temperature, and wind speed at Mākaha watershed. The hydrologic significance values of the different disaggregation methods were evaluated using Distributed Hydrology Soil Vegetation Model. MuDRain and diurnal method performed well over uniform distribution in disaggregating daily precipitation. However, the diurnal method is more consistent if accurate estimates of hourly precipitation intensities are desired. All of the air temperature disaggregation methods performed reasonably well, but goodness-of-fit statistics were slightly better for sine curve model with 2 h lag. Cosine model performed better than random model in disaggregating daily wind speed. The largest differences in annual water balance were related to wind speed followed by precipitation and dew point temperature. Simulated hourly streamflow, evapotranspiration, and groundwater recharge were less sensitive to the method of disaggregating daily air temperature. ClimGen performed well in generating the minimum and maximum temperature and wind speed. However, for precipitation, it clearly underestimated the number of extreme rainfall events with an intensity of >100 mm/day in all four locations. ClimGen was unable to replicate the distribution of observed precipitation at three locations (Honolulu, Kahului, and Hilo). ClimGen was able to reproduce the distributions of observed minimum temperature at Kahului and wind speed at Kahului and Hilo. Although the weather data generation and disaggregation methods were concentrated in a few Hawaiian watersheds, the results presented can be used to similar mountainous location settings, as well as any specific locations aimed at furthering the site-specific performance evaluation of these tested models.

Verification of Weather Running Estimate-Nowcast (WRE-N) Forecasts Using a Spatial-Categorical Method

DTIC Science & Technology

2017-07-01

forecasts and observations on a common grid, which enables the application a number of different spatial verification methods that reveal various...forecasts of continuous meteorological variables using categorical and object-based methods . White Sands Missile Range (NM): Army Research Laboratory (US... Research version of the Weather Research and Forecasting Model adapted for generating short-range nowcasts and gridded observations produced by the

Weather effects on the patterns of people's everyday activities: a study using GPS traces of mobile phone users.

PubMed

Horanont, Teerayut; Phithakkitnukoon, Santi; Leong, Tuck W; Sekimoto, Yoshihide; Shibasaki, Ryosuke

2013-01-01

This study explores the effects that the weather has on people's everyday activity patterns. Temperature, rainfall, and wind speed were used as weather parameters. People's daily activity patterns were inferred, such as place visited, the time this took place, the duration of the visit, based on the GPS location traces of their mobile phones overlaid upon Yellow Pages information. Our analysis of 31,855 mobile phone users allowed us to infer that people were more likely to stay longer at eateries or food outlets, and (to a lesser degree) at retail or shopping areas when the weather is very cold or when conditions are calm (non-windy). When compared to people's regular activity patterns, certain weather conditions affected people's movements and activities noticeably at different times of the day. On cold days, people's activities were found to be more diverse especially after 10AM, showing greatest variations between 2PM and 6PM. A similar trend is observed between 10AM and midnight on rainy days, with people's activities found to be most diverse on days with heaviest rainfalls or on days when the wind speed was stronger than 4 km/h, especially between 10AM-1AM. Finally, we observed that different geographical areas of a large metropolis were impacted differently by the weather. Using data of urban infrastructure to characterize areas, we found strong correlations between weather conditions upon people's accessibility to trains. This study sheds new light on the influence of weather conditions on human behavior, in particular the choice of daily activities and how mobile phone data can be used to investigate the influence of environmental factors on urban dynamics.

Weather Effects on the Patterns of People's Everyday Activities: A Study Using GPS Traces of Mobile Phone Users

PubMed Central

Leong, Tuck W.; Sekimoto, Yoshihide; Shibasaki, Ryosuke

2013-01-01

This study explores the effects that the weather has on people's everyday activity patterns. Temperature, rainfall, and wind speed were used as weather parameters. People's daily activity patterns were inferred, such as place visited, the time this took place, the duration of the visit, based on the GPS location traces of their mobile phones overlaid upon Yellow Pages information. Our analysis of 31,855 mobile phone users allowed us to infer that people were more likely to stay longer at eateries or food outlets, and (to a lesser degree) at retail or shopping areas when the weather is very cold or when conditions are calm (non-windy). When compared to people's regular activity patterns, certain weather conditions affected people's movements and activities noticeably at different times of the day. On cold days, people's activities were found to be more diverse especially after 10AM, showing greatest variations between 2PM and 6PM. A similar trend is observed between 10AM and midnight on rainy days, with people's activities found to be most diverse on days with heaviest rainfalls or on days when the wind speed was stronger than 4 km/h, especially between 10AM–1AM. Finally, we observed that different geographical areas of a large metropolis were impacted differently by the weather. Using data of urban infrastructure to characterize areas, we found strong correlations between weather conditions upon people's accessibility to trains. This study sheds new light on the influence of weather conditions on human behavior, in particular the choice of daily activities and how mobile phone data can be used to investigate the influence of environmental factors on urban dynamics. PMID:24367481

Hydraulic properties of groundwater systems in the saprolite and sediments of the wheatbelt, Western Australia

NASA Astrophysics Data System (ADS)

George, Richard J.

1992-01-01

Hydraulic properties of deeply weathered basement rocks and variably weathered sedimentary materials were measured by pumping and slug-test methods. Results from over 200 bores in 13 catchments, and eight pumping-test sites across the eastern and central wheatbelt of Western Australia were analysed. Measurements were made in each of the major lithological units, and emphasis placed on a ubiquitous basal saprolite aquifer. Comparisons were made between alternative drilling and analytical procedures to determine the most appropriate methods of investigation. Aquifers with an average hydraulic conductivity of 0.55 m day -1 occur in variably weathered Cainozoic sediments and poorly weathered saprolite grits (0.57 m day -1). These aquifers are separated by an aquitard (0.065 m day -1) comprising the mottled and pallid zones of the deeply weathered profile. Locally higher values of hydraulic conductivity occur in the saprolite aquifer, although after prolonged periods of pumping the values decrease until they are similar to those obtained from the slug-test methods. Hydraulic conductivities measured in bores drilled with rotary auger rigs were approximately an order of magnitude lower than those measured in the same material with bores drilled by the rotary air-blast method. Wheatbelt aquifers range from predominantly unconfined (Cainozoic sediments), to confined (saprolite grit aquifer). The poorly weathered saprolite grit aquifer has moderate to high transmissivities (4-50 m 2 day -1) and is capable of producing from less than 5 to over 230 kl day -1 of ground water, which is often of a quality suitable for livestock. Yields are influenced by the variability in the permeability of isovolumetrically weathered materials from which the aquifer is derived. The overlying aquitard has a low transmissivity (< 1 m 2 day -1), especially when deeply weathered, indurated and silicified. The transmissivity of the variably weathered sedimentary materials ranges from less than 0.5 m 2 day -1 to over 10 m 2 day -1, depending on the texture of the materials and their position within the landscape. Higher transmissivity zones may occur as discrete layers of coarser textured materials. The salinity of the saprolite and sedimentary aquifers ranges from less than 2000 mgl -1 to greater than 250000 mgl -1 (total dissolved solids; TDS), depending on position within the landscape. Secondary soil salinization develops when groundwater discharge occurs from either saprolite or sedimentary aquifers.

Effect of surface preparation on service life of top-coats applied to weathered primer paint

Treesearch

R. Sam Williams; Mark Knaebe; Peter Sotos

2008-01-01

Paint companies usually recommend that topcoats be applied to primer paint within two weeks. Unfortunately, this is not always possible. For example, onset of winter weather shortly after applying primer may delay topcoat application until spring. Scuff sanding or repriming are often recommended remedial methods for preparing a weathered primer for topcoats, but there...

[Vulnerability to atmospheric and geomagnetic factors of the body functions in healthy male dwellers of the Russian North].

PubMed

Markov, A L; Zenchenko, T A; Solonin, Iu G; Boĭko, E R

2013-01-01

In April 2009 through to November 2011, a Mars-500 satellite study of Russian Northerners (Syktyvkar citizens) was performed using the standard ECOSAN-2007 procedure evaluating the atmospheric and geomagnetic susceptibility of the main body functional parameters. Seventeen essentially healthy men at the age of 25 to 46 years were investigated. Statistical data treatment included correlation and single-factor analysis of variance. Comparison of the number of statistical correlations of the sum of all functional parameters for participants showed that most often they were sensitive to atmospheric pressure, temperature, relative humidity and oxygen partial pressure (29-35 %), and geomagnetic activity (28 %). Dependence of the functional parameters on the rate of temperature and pressure change was weak and comparable with random coincidence (11 %). Among the hemodynamic parameters, systolic pressure was particularly sensitive to space and terrestrial weather variations (29 %); sensitivity of heart rate and diastolic pressure were determined in 25 % and 21 % of participants, respectively. Among the heart rate variability parameters (HRV) the largest number of statistically reliable correlations was determined for the centralization index (32 %) and high-frequency HRV spectrum (31 %); index of the regulatory systems activity was least dependable (19 %). Life index, maximal breath-holding and Ckibinskaya's cardiorespiratory index are also susceptible. Individual responses of the functional parameters to terrestrial and space weather changes varied with partidpants which points to the necessity of individual approach to evaluation of person's reactions to environmental changes.

Weather Forecasting Systems and Methods

NASA Technical Reports Server (NTRS)

Mecikalski, John (Inventor); MacKenzie, Wayne M., Jr. (Inventor); Walker, John Robert (Inventor)

2014-01-01

A weather forecasting system has weather forecasting logic that receives raw image data from a satellite. The raw image data has values indicative of light and radiance data from the Earth as measured by the satellite, and the weather forecasting logic processes such data to identify cumulus clouds within the satellite images. For each identified cumulus cloud, the weather forecasting logic applies interest field tests to determine a score indicating the likelihood of the cumulus cloud forming precipitation and/or lightning in the future within a certain time period. Based on such scores, the weather forecasting logic predicts in which geographic regions the identified cumulus clouds will produce precipitation and/or lighting within during the time period. Such predictions may then be used to provide a weather map thereby providing users with a graphical illustration of the areas predicted to be affected by precipitation within the time period.

Characterization of energy exchange parameters in the Himalayan foothills Pakistan

NASA Astrophysics Data System (ADS)

Khalid, Bushra; Kumar, Mukul; Cholaw, Bueh; Aziz Khan, Junaid; Hayat Khan, Azmat

2017-04-01

The characterization of energy exchange parameters for spring season (April-May) has been done for Margalla hills national park (MHNP) Islamabad, Pakistan. It is important because Islamabad city lies in the foothills of Himalayas and micro meteorological activity makes the climate of surrounding areas. The activity on Himalaya's foothills (i.e., Margalla hills) regulate weather and also provide fresh water to the lakes and ponds by late afternoon thunder showers. This research is also important from the perspective of rain water harvesting in Islamabad, Pakistan. The objective of this study is to characterize the energy exchange parameters in the foothills of great Himalayas particularly on MHNP. Landsat ETM+ imageries have been used for calculating the land surface temperature (LST), normalized difference vegetation index (NDVI), and normalized difference moisture index (NDMI). SPOT 5 image has been used for land use/land cover classification over MHNP. The turbulent fluxes have been calculated by computing the values acquired from the processing of satellite imageries and real time observation data sets. The comparisons have been made between the land and atmospheric temperature and moisture to see the difference and its impacts on weather of twin cities i.e., Islamabad and Rawalpindi. The energy exchange parameters have been characterized by analyzing the impacts of weather parameters and turbulent fluxes on MHNP and surrounding cities. The potential rain water harvesting sites have been marked in the foothills. Weather and surface conditions become more favorable for the growth of vegetation by the end of April as the spring season reaches at its peak. There is the start of growing season in the month of April whereas the vegetation becomes thick over time during the month of May over Margalla hills however, the energy exchange parameters follow the same pattern in May as in April. The relative humidity remains between 18 - 55 % and the atmospheric temperature variations are between 19 to 35 0C during the studied period. As the atmospheric temperature and RH fluctuate, it effects the soil moisture and land surface temperature. Even if the atmospheric temperature rise or fall, the evergreen vegetation is found throughout the year on Margalla hills maintains/regulates the land surface temperature and soil moisture. The latent heat flux cause an increase in the noon temperature and RH levels. It further increases the moisture level in the atmosphere that is greatly supported by sensible heat flux to drive the moisture to the higher vertical levels and cause late afternoon thunder showers on the foothills and surrounding areas. The thundershowers are usually intense that cause light or heavy hail and changes the atmospheric temperature around 20 degrees Celsius in the evening time.

Towards assimilation of InSAR data in operational weather models

NASA Astrophysics Data System (ADS)

Mulder, Gert; van Leijen, Freek; Barkmeijer, Jan; de Haan, Siebren; Hanssen, Ramon

2017-04-01

InSAR signal delays due to the varying atmospheric refractivity are a potential data source to improve weather models [1]. Especially with the launch of the new Sentinel-1 satellites, which increases data coverage, latency and accessibility, it may become possible to operationalize the assimilation of differential integrated refractivity (DIR) values in numerical weather models. Although studies exist on comparison between InSAR data and weather models [2], the impact of assimilation of DIR values in an operational weather model has never been assessed. In this study we present different ways to assimilate DIR values in an operational weather model and show the first forecast results. There are different possibilities to assimilate InSAR-data in a weather model. For example, (i) absolute DIR values can be derived using additional GNSS zenith or slant delay values, (ii) DIR values can be converted to water vapor pressures, or (iii) water vapor pressures can be derived for different heights by combining GNSS and InSAR data. However, an increasing number of assumptions in these processing steps will increase the uncertainty in the final results. Therefore, we chose to insert the InSAR derived DIR values after minimal additional processing. In this study we use the HARMONIE model [3], which is a spectral, non-hydrostatic model with a resolution of about 2.5 km. Currently, this is the operational model in 11 European countries and based on the AROME model [4]. To assimilate the DIR values in the weather model we use a simple adjustment of the weather parameters over the full slant column to match the DIR values. This is a first step towards a more sophisticated approach based on the 3D-VAR or 4D-VAR schemes [5]. Where both assimilation schemes can correct for different weather parameters simultaneously, and 4D-VAR allow us to assimilate DIR values at the exact moment of satellite overpass instead of the start of the forecast window. The approach will be demonstrated based on several case studies. This research can be seen as a first step towards the operational use of InSAR data in state-of-the-art weather models and can be a driver for the design and development for new SAR missions, such as NISAR. References: [1] Hanssen, R. F., Weckwerth, T. M., Zebker, H. A., & Klees, R. (1999). High-resolution water vapor mapping from interferometric radar measurements.Science, 283(5406), 1297-1299. [2] P. Mateus, R. Tomé, G. Nico and J. Catalão, "Three-Dimensional Variational Assimilation of InSAR PWV Using the WRFDA Model," in IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 12, pp. 7323-7330, Dec. 2016. [3] Navascués, B., Calvo, J., Morales, G., Santos, C., Callado, A., Cansado, A., ... & García-Colombo, O. (2013). Long-term verification of HIRLAM and ECMWF forecasts over southern europe: History and perspectives of numerical weather prediction at AEMET. Atmospheric Research, 125, 20-33. [4] Seity, Y., P. Brousseau, S. Malardel, G. Hello, P. Bénard, F. Bouttier, C. Lac, and V. Masson, 2011: The AROME-France Convective-Scale Operational Model. Mon. Wea. Rev., 139, 976-991. [5] Lorenc, A. C. and Rawlins, F. (2005), Why does 4D-Var beat 3D-Var?. Q.J.R. Meteorol. Soc., 131: 3247-3257.

Efficient transfer of weather information to the pilot in flight

NASA Technical Reports Server (NTRS)

Mcfarland, R. H.

1982-01-01

Efficient methods for providing weather information to the pilot in flight are summarized. Use of discrete communications channels in the aeronautical, VHF band or subcarriers in the VOR navigation band are considered the best possibilities. Data rates can be provided such that inputs to the ground based transmitters from 2400 band telephone lines are easily accommodated together with additional data. The crucial weather data considered for uplinking are identified as radar reflectivity patterns relating to precipitation, spherics data, hourly sequences, nowcasts, forecasts, cloud top heights with freezing and icing conditions, the critical weather map and satellite maps. NEXRAD, the ground based, Doppler weather radar which will produce an improved weather product also encourages use of an uplink to fully utilize its capability to improve air safety.

Feasibility of using a seismic surface wave method to study seasonal and weather effects on shallow surface soils

USDA-ARS?s Scientific Manuscript database

The objective of the paper is to study the temporal variations of the subsurface soil properties due to seasonal and weather effects using a combination of a new seismic surface method and an existing acoustic probe system. A laser Doppler vibrometer (LDV) based multi-channel analysis of surface wav...

Measuring fire weather and forest inflammability

Treesearch

H. T. Gisborne

1936-01-01

In the measurement of fire weather and forest inflammability, now practiced regularly at more than 90 forest stations in northern Idaho and western Montana, it is necessary to use many methods that are peculiar to this work. Some of these methods are familiar to meteorologists, but few foresters have had any appreciable training in meteorology. Others are of such,...

2010 weather and aeolian sand-transport data from the Colorado River corridor, Grand Canyon, Arizona

USGS Publications Warehouse

Dealy, Timothy P.; East, Amy E.; Fairley, Helen C.

2014-01-01

Measurements of weather parameters and aeolian sand transport were made in 2010 near selected archeological sites in the Colorado River corridor through Grand Canyon, Arizona. Data collected in 2010 indicate event- and seasonal-scale variations in rainfall, wind, temperature, humidity, and barometric pressure. Differences in weather patterns between 2009 and 2010 included a slightly later spring windy season, greater spring precipitation and annual rainfall totals, and a later onset and length of the reduced diurnal barometric-pressure fluctuations commonly associated with summer monsoon conditions. The increase in spring precipitation was consistent with the 2010 spring El Niño conditions compared to the 2009 spring La Niña conditions, whereas the subsequent transition to an El Niño-Southern Oscillation neutral phase appeared to delay the reduction in diurnal barometric fluctuations.

A Geosynchronous Lidar System for Atmospheric Winds and Moisture Measurements

NASA Technical Reports Server (NTRS)

Emmitt, G. D.

2001-01-01

An observing system comprised of two lidars in geosychronous orbit would enable the synoptic and meso-scale measurement of atmospheric winds and moisture both of which are key first-order variables of the Earth's weather equation. Simultaneous measurement of these parameters at fast revisit rates promises large advancements in our weather prediction skills. Such capabilities would be unprecedented and a) yield greatly improved and finer resolution initial conditions for models, b) make existing costly and cumbersome measurement approaches obsolete, and c) obviate the use of numerical techniques needed to correct data obtained using present observing systems. Additionally, simultaneous synoptic wind and moisture observations would lead to improvements in model parameterizations, and in our knowledge of small-scale weather processes. Technology and science data product assessments are ongoing. Results will be presented during the conference.

2009 weather and aeolian sand-transport data from the Colorado River corridor, Grand Canyon, Arizona

USGS Publications Warehouse

Draut, Amy E.; Sondossi, Hoda A.; Dealy, Timothy P.; Hazel, Joseph E.; Fairley, Helen C.; Brown, Christopher R.

2010-01-01

This report presents measurements of weather parameters and aeolian sand transport made in 2009 near selected archeological sites in the Colorado River corridor through Grand Canyon, Ariz. The quantitative methods and data discussed here form a basis for monitoring ecosystem processes that affect archeological-site stability. Combined with forthcoming work to evaluate landscape evolution at nearby archeological sites, these data can be used to document the relation between physical processes, including weather and aeolian sand transport, and their effects on the physical integrity of archeological sites. Data collected in 2009 reveal event- and seasonal-scale variations in rainfall, wind, temperature, humidity, and barometric pressure. Broad seasonal changes in aeolian sediment flux are also apparent at most study sites. Differences in weather patterns between 2008 and 2009 included an earlier spring windy season, greater spring precipitation even though 2009 annual rainfall totals were in general substantially lower than in 2008, and earlier onset of the reduced diurnal barometric-pressure fluctuations commonly associated with summer monsoon conditions. Weather patterns in middle to late 2009 were apparently affected by a transition of the ENSO cycle from a neutral phase to the El Ni?o phase. The continuation of monitoring that began in 2007, and installation of additional equipment at several new sites in early 2008, allowed evaluation of the effects of the March 2008 high-flow experiment (HFE) on aeolian sand transport. As reported earlier, at 2 of the 9 sites studied, spring and summer winds in 2008 reworked the HFE sandbars to form new aeolian dunes, where sand moved inland toward larger, well-established dune fields. Observations in 2009 showed that farther inland migration of the dune at one of those two sites is likely inhibited by vegetation. At the other location, the new aeolian dune form was found to have moved 10 m inland toward older, well-established dunes during 2009, resulting in landward transport of several hundred cubic meters of new sand upslope and above the elevation reached by the peak HFE water level.

Environmental drivers of soil microbial community structure and function at the Avon River Critical Zone Observatory.

PubMed

Gleeson, Deirdre; Mathes, Falko; Farrell, Mark; Leopold, Matthias

2016-11-15

The Critical Zone is defined as the thin, permeable layer from the tops of the trees to the bottom of the bedrock that sustains terrestrial life on Earth. The geometry and shape of the various weathering zones are known as the critical zone architecture. At the centre of the Critical Zone are soils and the microorganisms that inhabit them. In Western Australia, the million-year-old stable weathering history and more recent lateral erosion during the past hundreds of thousands of years have created a geomorphic setting where deep weathering zones are now exposed on the surface along the flanks of many lateritic hills. These old weathering zones provide diverse physical and chemical properties that influence near surface pedologic conditions and thus likely shape current surface microbiology. Here, we present data derived from a small lateritic hill on the UWA Farm Ridgefield. Spatial soil sampling revealed the contrasting distribution patterns of simple soil parameters such as pH (CaCl2) and electric conductivity. These are clearly linked with underlying changes of the critical zone architecture and show a strong contrast with low values of pH3.3 at the top of the hill to pH5.3 at the bottom. These parameters were identified as major drivers of microbial spatial variability in terms of bacterial and archaeal community composition but not abundance. In addition, we used sensitive (14)C labelling to assess turnover of three model organic nitrogen compounds - an important biogeochemical functional trait relating to nutrient availability. Though generally rapid and in the order of rates reported elsewhere (t½<5h), some points in the sampling area showed greatly reduced turnover rates (t½>10h). In conclusion, we have shown that the weathering and erosion history of ancient Western Australia affects the surface pedology and has consequences for microbial community structure and function. Copyright © 2016 Elsevier B.V. All rights reserved.

WOD - Weather On Demand forecasting system

NASA Astrophysics Data System (ADS)

Rognvaldsson, Olafur; Ragnarsson, Logi; Stanislawska, Karolina

2017-04-01

The backbone of the Belgingur forecasting system (called WOD - Weather On Demand) is the WRF-Chem atmospheric model, with a number of in-house customisations. Initial and boundary data are taken from the Global Forecasting System, operated by the National Oceanic and Atmospheric Administration (NOAA). Operational forecasts use cycling of a number of parameters, mainly deep soil and surface fields. This is done to minimise spin-up effects and to ensure proper book-keeping of hydrological fields such as snow accumulation and runoff, as well as the constituents of various chemical parameters. The WOD system can be used to create conventional short- to medium-range weather forecasts for any location on the globe. The WOD system can also be used for air quality purposes (e.g. dispersion forecasts from volcanic eruptions) and as a tool to provide input to other modelling systems, such as hydrological models. A wide variety of post-processing options are also available, making WOD an ideal tool for creating highly customised output that can be tailored to the specific needs of individual end-users. The most recent addition to the WOD system is an integrated verification system where forecasts can be compared to surface observations from chosen locations. Forecast visualisation, such as weather charts, meteograms, weather icons and tables, is done via number of web components that can be configured to serve the varying needs of different end-users. The WOD system itself can be installed in an automatic way on hardware running a range of Linux based OS. System upgrades can also be done in semi-automatic fashion, i.e. upgrades and/or bug-fixes can be pushed to the end-user hardware without system downtime. Importantly, the WOD system requires only rudimentary knowledge of the WRF modelling, and the Linux operating systems on behalf of the end-user, making it an ideal NWP tool in locations with limited IT infrastructure.

Weather-induced ischemia and arrhythmia in patients undergoing cardiac rehabilitation: another difference between men and women

NASA Astrophysics Data System (ADS)

Schneider, Alexandra; Schuh, Angela; Maetzel, Friedrich-Karl; Rückerl, Regina; Breitner, Susanne; Peters, Annette

2008-07-01

Given the accumulating evidence that people with underlying heart disease are a particularly vulnerable group for triggers like changing meteorological parameters, the objective of this longitudinal study was to analyze the influence of weather parameters on blood pressure, arrhythmia and ischemia in cardiovascular patients. A panel study with repeated measurements was conducted in a rehabilitation clinic in Timmendorfer Strand (Baltic Sea, Germany) with 872 cardiovascular patients. Heart rate, blood pressure and electrocardiography changes were measured during repeated bicycle ergometries. Generalized Estimating Equations were used for regression analyses of immediate, delayed and cumulative influences of the daily measured meteorological data. For men, a decrease in air temperature and in water vapor pressure doubled the risk of ST-segment depression during ergometry [odds ratio (OR) for 1 day delay: 1.88 (1.24; 2.83) for air temperature] with a delay of 1-2 days. For women, an increase of their heart rate before the start of the ergometry [same day: 4.36 beats/min (0.99; 7.74) for air temperature] and a 2- to 3-fold higher risk for ventricular ectopic beats [1 day delay: OR 2.43 (1.17; 5.05) for air temperature] was observed with an increase in temperature and water vapor pressure in almost all analyzed time-windows. The study indicates that meteorological parameters can induce changes in heart function which may lead to adverse cardiovascular events especially in susceptible, diseased individuals. The observed effect on ST-segment depression could be a link between the association of weather changes and cardiovascular morbidity and mortality.

Validation of Real-time Modeling of Coronal Mass Ejections Using the WSA-ENLIL+Cone Heliospheric Model

NASA Astrophysics Data System (ADS)

Romano, M.; Mays, M. L.; Taktakishvili, A.; MacNeice, P. J.; Zheng, Y.; Pulkkinen, A. A.; Kuznetsova, M. M.; Odstrcil, D.

2013-12-01

Modeling coronal mass ejections (CMEs) is of great interest to the space weather research and forecasting communities. We present recent validation work of real-time CME arrival time predictions at different satellites using the WSA-ENLIL+Cone three-dimensional MHD heliospheric model available at the Community Coordinated Modeling Center (CCMC) and performed by the Space Weather Research Center (SWRC). SWRC is an in-house research-based operations team at the CCMC which provides interplanetary space weather forecasting for NASA's robotic missions and performs real-time model validation. The quality of model operation is evaluated by comparing its output to a measurable parameter of interest such as the CME arrival time and geomagnetic storm strength. The Kp index is calculated from the relation given in Newell et al. (2007), using solar wind parameters predicted by the WSA-ENLIL+Cone model at Earth. The CME arrival time error is defined as the difference between the predicted arrival time and the observed in-situ CME shock arrival time at the ACE, STEREO A, or STEREO B spacecraft. This study includes all real-time WSA-ENLIL+Cone model simulations performed between June 2011-2013 (over 400 runs) at the CCMC/SWRC. We report hit, miss, false alarm, and correct rejection statistics for all three spacecraft. For hits we show the average absolute CME arrival time error, and the dependence of this error on CME input parameters such as speed, width, and direction. We also present the predicted geomagnetic storm strength (using the Kp index) error for Earth-directed CMEs.

GUMICS-4 Year Run: Ground Magnetic Field Predictions

NASA Astrophysics Data System (ADS)

Honkonen, I. J.; Viljanen, A.; Juusola, L.; Facsko, G.; Vanhamäki, H.

2013-12-01

Space weather can have severe effects even at ground level when Geomagnetically Induced Currents (GIC) disrupt power transmission networks, the worst case being a complete blackout affecting millions of people. The importance of space weather forecasting as well as the need for model improvement and validation has been recognized internationally. The recently concluded GUMICS-4 one year run, in which solar wind observations obtained from OMNIWeb for the period 2002-01-29 to 2003-02-02 were given as input to the model, will allow GUMICS to be validated against observations on an unprecedented scale. The performance of GUMICS can be quantified statistically, as a function of, for example, the solar wind driver, various geomagnetic indices, magnetic local time and other parameters. Here we concentrate on the ability of GUMICS to predict ground magnetic field observations for one year of simulated results. The ground magnetic field predictions are compared to observations of the mainland IMAGE magnetometer stations located at CGM latitudes 54-68 N. Furthermore the GIC derived from ground magnetic field predictions are compared to observations along the natural gas pipeline at Mäntsälä, South Finland. Various metrics are used to objectively evaluate the performance of GUMICS as a function of different parameters, thereby providing significant insight into the space weather forecasting ability of models based on first principles.

Quantifying the past and future impact of climate on outbreak patterns of bank voles (Myodes glareolus).

PubMed

Imholt, Christian; Reil, Daniela; Eccard, Jana A; Jacob, Daniela; Hempelmann, Nils; Jacob, Jens

2015-02-01

Central European outbreak populations of the bank vole (Myodes glareolus Schreber) are known to cause damage in forestry and to transmit the most common type of Hantavirus (Puumala virus, PUUV) to humans. A sound estimation of potential effects of future climate scenarios on population dynamics is a prerequisite for long-term management strategies. Historic abundance time series were used to identify the key weather conditions associated with bank vole abundance, and were extrapolated to future climate scenarios to derive potential long-term changes in bank vole abundance dynamics. Classification and regression tree analysis revealed the most relevant weather parameters associated with high and low bank vole abundances. Summer temperatures 2 years prior to trapping had the highest impact on abundance fluctuation. Extrapolation of the identified parameters to future climate conditions revealed an increase in years with high vole abundance. Key weather patterns associated with vole abundance reflect the importance of superabundant food supply through masting to the occurrence of bank vole outbreaks. Owing to changing climate, these outbreaks are predicted potentially to increase in frequency 3-4-fold by the end of this century. This may negatively affect damage patterns in forestry and the risk of human PUUV infection in the long term. © 2014 Society of Chemical Industry.

Tests of the Grobner Basis Solution for Lightning Ground Flash Fraction Retrieval

NASA Technical Reports Server (NTRS)

Koshak, William; Solakiewicz, Richard; Attele, Rohan

2011-01-01

Satellite lightning imagers such as the NASA Tropical Rainfall Measuring Mission Lightning Imaging Sensor (TRMM/LIS) and the future GOES-R Geostationary Lightning Mapper (GLM) are designed to detect total lightning (ground flashes + cloud flashes). However, there is a desire to discriminate ground flashes from cloud flashes from the vantage point of space since this would enhance the overall information content of the satellite lightning data and likely improve its operational and scientific applications (e.g., in severe weather warning, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method was previously introduced for retrieving the fraction of ground flashes in a set of flashes observed from a satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters (one of which is the ground flash fraction), a scalar function was minimized by a numerical method. In order to improve this optimization, a Grobner basis solution was introduced to obtain analytic representations of the model parameters that serve as a refined initialization scheme to the numerical optimization. In this study, we test the efficacy of the Grobner basis initialization using actual lightning imager measurements and ground flash truth derived from the national lightning network.

Determination of CME 3D parameters based on a new full ice-cream cone model

NASA Astrophysics Data System (ADS)

Na, Hyeonock; Moon, Yong-Jae

2017-08-01

In space weather forecast, it is important to determine three-dimensional properties of CMEs. Using 29 limb CMEs, we examine which cone type is close to a CME three-dimensional structure. We find that most CMEs have near full ice-cream cone structure which is a symmetrical circular cone combined with a hemisphere. We develop a full ice-cream cone model based on a new methodology that the full ice-cream cone consists of many flat cones with different heights and angular widths. By applying this model to 12 SOHO/LASCO halo CMEs, we find that 3D parameters from our method are similar to those from other stereoscopic methods (i.e., a triangulation method and a Graduated Cylindrical Shell model). In addition, we derive CME mean density (ρmean=Mtotal/Vcone) based on the full ice-cream cone structure. For several limb events, we determine CME mass by applying the Solarsoft procedure (e.g., cme_mass.pro) to SOHO/LASCO C3 images. CME volumes are estimated from the full ice-cream cone structure. From the power-law relationship between CME mean density and its height, we estimate CME mean densities at 20 solar radii (Rs). We will compare the CME densities at 20 Rs with their corresponding ICME densities.

Statistical Correction of Air Temperature Forecasts for City and Road Weather Applications

NASA Astrophysics Data System (ADS)

Mahura, Alexander; Petersen, Claus; Sass, Bent; Gilet, Nicolas

2014-05-01

The method for statistical correction of air /road surface temperatures forecasts was developed based on analysis of long-term time-series of meteorological observations and forecasts (from HIgh Resolution Limited Area Model & Road Conditions Model; 3 km horizontal resolution). It has been tested for May-Aug 2012 & Oct 2012 - Mar 2013, respectively. The developed method is based mostly on forecasted meteorological parameters with a minimal inclusion of observations (covering only a pre-history period). Although the st iteration correction is based taking into account relevant temperature observations, but the further adjustment of air and road temperature forecasts is based purely on forecasted meteorological parameters. The method is model independent, e.g. it can be applied for temperature correction with other types of models having different horizontal resolutions. It is relatively fast due to application of the singular value decomposition method for matrix solution to find coefficients. Moreover, there is always a possibility for additional improvement due to extra tuning of the temperature forecasts for some locations (stations), and in particular, where for example, the MAEs are generally higher compared with others (see Gilet et al., 2014). For the city weather applications, new operationalized procedure for statistical correction of the air temperature forecasts has been elaborated and implemented for the HIRLAM-SKA model runs at 00, 06, 12, and 18 UTCs covering forecast lengths up to 48 hours. The procedure includes segments for extraction of observations and forecast data, assigning these to forecast lengths, statistical correction of temperature, one-&multi-days statistical evaluation of model performance, decision-making on using corrections by stations, interpolation, visualisation and storage/backup. Pre-operational air temperature correction runs were performed for the mainland Denmark since mid-April 2013 and shown good results. Tests also showed that the CPU time required for the operational procedure is relatively short (less than 15 minutes including a large time spent for interpolation). These also showed that in order to start correction of forecasts there is no need to have a long-term pre-historical data (containing forecasts and observations) and, at least, a couple of weeks will be sufficient when a new observational station is included and added to the forecast point. Note for the road weather application, the operationalization of the statistical correction of the road surface temperature forecasts (for the RWM system daily hourly runs covering forecast length up to 5 hours ahead) for the Danish road network (for about 400 road stations) was also implemented, and it is running in a test mode since Sep 2013. The method can also be applied for correction of the dew point temperature and wind speed (as a part of observations/ forecasts at synoptical stations), where these both meteorological parameters are parts of the proposed system of equations. The evaluation of the method performance for improvement of the wind speed forecasts is planned as well, with considering possibilities for the wind direction improvements (which is more complex due to multi-modal types of such data distribution). The method worked for the entire domain of mainland Denmark (tested for 60 synoptical and 395 road stations), and hence, it can be also applied for any geographical point within this domain, as through interpolation to about 100 cities' locations (for Danish national byvejr forecasts). Moreover, we can assume that the same method can be used in other geographical areas. The evaluation for other domains (with a focus on Greenland and Nordic countries) is planned. In addition, a similar approach might be also tested for statistical correction of concentrations of chemical species, but such approach will require additional elaboration and evaluation.

Air Weather Service Support to the United States Army Tet and the Decade After

DTIC Science & Technology

1979-08-01

than traditional air interdiction methods, and, more important, it was more humane because it saved lives. 6 1 The very nature of the project led it to...every four hours, 24 hours a day.04 Taylor stressed that he functioned primarily as a weather briefer, that the weather forecasts the 1st Cavalry... stressed to them in peacetime. "I think the Army began there," Carmell opined, "to appreciate the worth of weather in its planning," "We got our foot in

Insights into Regolith Dynamics from the Irradiation Record Preserved in Hayabusa Samples

NASA Technical Reports Server (NTRS)

Keller, Lindsay P.; Berger, E. L.

2014-01-01

The rates of space weathering processes are poorly constrained for asteroid surfaces, with recent estimates ranging over 5 orders of magnitude. The return of the first surface samples from a space-weathered asteroid by the Hayabusa mission and their laboratory analysis provides "ground truth" to anchor the timescales for space weathering. We determine the rates of space weathering on Itokawa by measuring solar flare track densities and the widths of solar wind damaged rims on grains. These measurements are made possible through novel focused ion beam (FIB) sample preparation methods.

Operational Space Weather Needs - Perspectives from SEASONS 2014

NASA Astrophysics Data System (ADS)

Comberiate, J.; Kelly, M. A.; Paxton, L. J.; Schaefer, R. K.; Bust, G. S.; Sotirelis, T.; Fox, N. J.

2014-12-01

A key challenge for the operational space weather community is the gap between the latest scientific data, models, methods, and indices and those that are currently used in operational systems. The November 2014 SEASONS (Space Environment Applications, Systems, and Operations for National Security) Workshop at JHU/APL in Laurel, Maryland, brings together representatives from the operational and scientific communities. The theme of SEASONS 2014 is "Beyond Climatology," with a focus on how space weather events threaten operational assets and disrupt missions. Here we present perspectives from SEASONS 2014 on new observations, models in development, and forecasting methods that are of interest to the operational space weather community. Highlighted topics include ionospheric data assimilation and forecasting models, HF propagation models, radiation belt observations, and energetic particle modeling. The SEASONS 2014 web site can be found at https://secwww.jhuapl.edu/SEASONS/

Development of a Full Ice-cream Cone Model for Halo Coronal Mass Ejections

NASA Astrophysics Data System (ADS)

Na, Hyeonock; Moon, Y.-J.; Lee, Harim

2017-04-01

It is essential to determine three-dimensional parameters (e.g., radial speed, angular width, and source location) of coronal mass ejections (CMEs) for the space weather forecast. In this study, we investigate which cone type represents a halo CME morphology using 29 CMEs (12 Solar and Heliospheric Observatory (SOHO)/Large Angle and Spectrometric Coronagraph (LASCO) halo CMEs and 17 Solar Terrestrial Relations Observatory (STEREO)/Sun-Earth Connection Coronal and Heliospheric Investigation COR2 halo CMEs) from 2010 December to 2011 June. These CMEs are identified as halo CMEs by one spacecraft (SOHO or one of STEREO A and B) and limb ones by the other spacecraft (One of STEREO A and B or SOHO). From cone shape parameters of these CMEs, such as their front curvature, we find that the CME observational structures are much closer to a full ice-cream cone type than a shallow ice-cream cone type. Thus, we develop a full ice-cream cone model based on a new methodology that the full ice-cream cone consists of many flat cones with different heights and angular widths to estimate the three-dimensional parameters of the halo CMEs. This model is constructed by carrying out the following steps: (1) construct a cone for a given height and angular width, (2) project the cone onto the sky plane, (3) select points comprising the outer boundary, and (4) minimize the difference between the estimated projection speeds with the observed ones. By applying this model to 12 SOHO/LASCO halo CMEs, we find that 3D parameters from our method are similar to those from other stereoscopic methods (I.e., a triangulation method and a Graduated Cylindrical Shell model).

Development of a Full Ice-cream Cone Model for Halo Coronal Mass Ejections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Na, Hyeonock; Moon, Y.-J.; Lee, Harim, E-mail: nho0512@khu.ac.kr, E-mail: moonyj@khu.ac.kr

It is essential to determine three-dimensional parameters (e.g., radial speed, angular width, and source location) of coronal mass ejections (CMEs) for the space weather forecast. In this study, we investigate which cone type represents a halo CME morphology using 29 CMEs (12 Solar and Heliospheric Observatory (SOHO) /Large Angle and Spectrometric Coronagraph (LASCO) halo CMEs and 17 Solar Terrestrial Relations Observatory ( STEREO )/Sun–Earth Connection Coronal and Heliospheric Investigation COR2 halo CMEs) from 2010 December to 2011 June. These CMEs are identified as halo CMEs by one spacecraft ( SOHO or one of STEREO A and B ) and limbmore » ones by the other spacecraft (One of STEREO A and B or SOHO ). From cone shape parameters of these CMEs, such as their front curvature, we find that the CME observational structures are much closer to a full ice-cream cone type than a shallow ice-cream cone type. Thus, we develop a full ice-cream cone model based on a new methodology that the full ice-cream cone consists of many flat cones with different heights and angular widths to estimate the three-dimensional parameters of the halo CMEs. This model is constructed by carrying out the following steps: (1) construct a cone for a given height and angular width, (2) project the cone onto the sky plane, (3) select points comprising the outer boundary, and (4) minimize the difference between the estimated projection speeds with the observed ones. By applying this model to 12 SOHO /LASCO halo CMEs, we find that 3D parameters from our method are similar to those from other stereoscopic methods (i.e., a triangulation method and a Graduated Cylindrical Shell model).« less

Petroleum Release Assessment and Impacts of Weather Extremes

EPA Science Inventory

Contaminated ground water and vapor intrusion are two major exposure pathways of concern at petroleum release sites. EPA has recently developed a model for petroleum vapor intrusion, called PVIScreen, which incorporates variability and uncertainty in input parameters. This ap...

Impacts of signal system timings on rain related congestion.

DOT National Transportation Integrated Search

2010-06-01

It is known that inclement weather can affect traffic volumes, vehicle speeds, speed variance, saturation flow rates, and sometimes : discharge rates from traffic signals. These parameters in turn can have a significant impact on the efficiency of tr...

Undergraduate Earth System Science Education: Project-Based Learning, Land-Atmosphere Interaction, and a Newly Established Student Weather Station

NASA Astrophysics Data System (ADS)

Baker, D.

2004-12-01

Undergraduate students conducted a semester-long research project as part of a special topics course that launched the Austin College Weather Station in spring 2001. The weather station is located on restored prairie roughly 100 km north of Dallas, Texas. In addition to standard meteorological observations, the Austin College Weather Station measures surface quantities such as soil moisture, soil temperature, solar radiation, infrared radiation, and soil heat flux. These additional quantities are used to calculate the surface energy balance using the Bowen ratio method. Thus, the Austin College Weather Station provides valuable information on land-atmosphere interaction in a prairie environment. This project provided a remarkable learning experience for the students. Each student supervised two instruments on the weather station. Students skillfully learned instrumentation details and the physical phenomena measured by the instruments. Team meetings were held each week to discuss issues such as station location, power requirements, telecommunication options, and data acquisition. Students made important decisions during the meetings. They would then work collaboratively on specific tasks that needed to be accomplished before the next meeting. Students also assessed the validity of their measurements after the weather station came on-line. With this approach, students became the experts. They utilized the scientific method to think critically and to solve problems. For at least a semester, students became Earth system scientists.

[Parameters modification and evaluation of two evapotranspiration models based on Penman-Monteith model for summer maize].

PubMed

Wang, Juan; Wang, Jian Lin; Liu, Jia Bin; Jiang, Wen; Zhao, Chang Xing

2017-06-18

The dynamic variations of evapotranspiration (ET) and weather data during summer maize growing season in 2013-2015 were monitored with eddy covariance system, and the applicability of two operational models (FAO-PM model and KP-PM model) based on the Penman-Monteith model were analyzed. Firstly, the key parameters in the two models were calibrated with the measured data in 2013 and 2014; secondly, the daily ET in 2015 calculated by the FAO-PM model and KP-PM model was compared to the observed ET, respectively. Finally, the coefficients in the KP-PM model were further revised with the coefficients calculated according to the different growth stages, and the performance of the revised KP-PM model was also evaluated. These statistical parameters indicated that the calculated daily ET for 2015 by the FAO-PM model was closer to the observed ET than that by the KP-PM model. The daily ET calculated from the revised KP-PM model for daily ET was more accurate than that from the FAO-PM model. It was also found that the key parameters in the two models were correlated with weather conditions, so the calibration was necessary before using the models to predict the ET. The above results could provide some guidelines on predicting ET with the two models.

Improving Land-Surface Model Hydrology: Is an Explicit Aquifer Model Better than a Deeper Soil Profile?

NASA Technical Reports Server (NTRS)

Gulden, L. E.; Rosero, E.; Yang, Z.-L.; Rodell, Matthew; Jackson, C. S.; Niu, G.-Y.; Yeh, P. J.-F.; Famiglietti, J. S.

2007-01-01

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the storage and movement of water (including soil moisture, snow, evaporation, and runoff) after it falls to the ground as precipitation. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy. Hence LSMs have been developed to integrate the available information, including satellite observations, using powerful computers, in order to track water storage and redistribution. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. Recently, the models have begun to simulate groundwater storage. In this paper, we compare several possible approaches, and examine the pitfalls associated with trying to estimate aquifer parameters (such as porosity) that are required by the models. We find that explicit representation of groundwater, as opposed to the addition of deeper soil layers, considerably decreases the sensitivity of modeled terrestrial water storage to aquifer parameter choices. We also show that approximate knowledge of parameter values is not sufficient to guarantee realistic model performance: because interaction among parameters is significant, they must be prescribed as a harmonious set.

HF-START: A Regional Radio Propagation Simulator

NASA Astrophysics Data System (ADS)

Hozumi, K.; Maruyama, T.; Saito, S.; Nakata, H.; Rougerie, S.; Yokoyama, T.; Jin, H.; Tsugawa, T.; Ishii, M.

2017-12-01

HF-START (HF Simulator Targeting for All-users' Regional Telecommunications) is a user-friendly simulator developed to meet the needs of space weather users. Prediction of communications failure due to space weather disturbances is of high priority. Space weather users from various backgrounds with high economic impact, i.e. airlines, telecommunication companies, GPS-related companies, insurance companies, international amateur radio union, etc., recently increase. Space weather information provided by Space Weather Information Center of NICT is, however, too professional to be understood and effectively used by the users. To overcome this issue, I try to translate the research level data to the user level data based on users' needs and provide an immediate usable data. HF-START is positioned to be a space weather product out of laboratory based truly on users' needs. It is originally for radio waves in HF band (3-30 MHz) but higher frequencies up to L band are planned to be covered. Regional ionospheric data in Japan and southeast Asia are employed as a reflector of skywave mode propagation. GAIA (Ground-to-topside model of Atmosphere and Ionosphere for Aeronomy) model will be used as ionospheric input for global simulation. To evaluate HF-START, an evaluation campaign for Japan region will be launched in coming months. If the campaign successes, it will be expanded to southeast Asia region as well. The final goal of HF-START is to provide the near-realtime necessary radio parameters as well as the warning message of radio communications failure to the radio and space weather users.

Will climate change affect weather types associated with flooding in the Elbe river basin?

NASA Astrophysics Data System (ADS)

Nissen, Katrin M.; Pardowitz, Tobias; Ulbrich, Uwe; Nied, Manuela

2013-04-01

This study investigates the effects of anthropogenic climate change on weather types associated with flooding in the Elbe river basin. The study is based on an ensemble of 3 simulations with the ECHAM5 MPIOM coupled model forced with historical and SRES A1B greenhouse gas concentrations. Relevant weather types, occuring in association with recent flood events, are identified in the ERA40 reanalysis data set. The weather types are classified with the SANDRA cluster algorithm. Distributions of tropospheric humidity content, 500 hPa geopotential height and 500 hPa temperature over Europe are taken as input parameters. 8 (out of 40) weather types are found to be associated with flooding events in the Elbe river basin. The majority of these (6) typically occur during winter, while 2 are warm season patterns. Downscaling reveals characteristic precipitation anomalies associated with the individual patterns. The 8 flood relevant weather types are then identified in the ECHAM5 simulations. The effect of climate change on these patterns is investigated by comparing the last 30 years of the previous century to the last 30 years of the 21st century. According to the model the frequency of most patterns will not change. 5 patterns may experience a statistically significant increase in the mean precipitation over the catchment area and 4 patterns an increase in extreme precipitation. Persistence may slightly decrease for 2 patterns and remain unchanged for the others. Overall, this indicates a moderate increase in the risk for Elbe river flooding, related to changes in the weather patterns, in the coming decades.

Motivating and Facilitating Advancements in Space Weather Real-Time Data Availability: Factors, Data, and Access Methods

NASA Astrophysics Data System (ADS)

Pankratz, C. K.; Baker, D. N.; Jaynes, A. N.; Elkington, S. R.; Baltzer, T.; Sanchez, F.

2017-12-01

Society's growing reliance on complex and highly interconnected technological systems makes us increasingly vulnerable to the effects of space weather events - maybe more than for any other natural hazard. An extreme solar storm today could conceivably impact hundreds of the more than 1400 operating Earth satellites. Such an extreme storm could cause collapse of the electrical grid on continental scales. The effects on navigation, communication, and remote sensing of our home planet could be devastating to our social functioning. Thus, it is imperative that the scientific community address the question of just how severe events might become. At least as importantly, it is crucial that policy makers and public safety officials be informed by the facts on what might happen during extreme conditions. This requires essentially real-time alerts, warnings, and also forecasts of severe space weather events, which in turn demands measurements, models, and associated data products to be available via the most effective data discovery and access methods possible. Similarly, advancement in the fundamental scientific understanding of space weather processes is also vital, requiring that researchers have convenient and effective access to a wide variety of data sets and models from multiple sources. The space weather research community, as with many scientific communities, must access data from dispersed and often uncoordinated data repositories to acquire the data necessary for the analysis and modeling efforts that advance our understanding of solar influences and space physics on the Earth's environment. The Laboratory for Atmospheric and Space Physics (LASP), as a leading institution in both producing data products and advancing the state of scientific understanding of space weather processes, is well positioned to address many of these issues. In this presentation, we will outline the motivating factors for effective space weather data access, summarize the various data and models that are available, and present methods for meeting the data management and access needs of the disparate communities who require low-latency space weather data and information.

Atmospheric gradients from GNSS, VLBI, and DORIS analyses and from Numerical Weather Models during CONT14

NASA Astrophysics Data System (ADS)

Heinkelmann, Robert; Dick, Galina; Nilsson, Tobias; Soja, Benedikt; Wickert, Jens; Zus, Florian; Schuh, Harald

2015-04-01

Observations from space-geodetic techniques are nowadays increasingly used to derive atmospheric information for various commercial and scientific applications. A prominent example is the operational use of GNSS data to improve global and regional weather forecasts, which was started in 2006. Atmosphere gradients describe the azimuthal asymmetry of zenith delays. Estimates of geodetic and other parameters significantly improve when atmosphere gradients are determined in addition. Here we assess the capability of several space geodetic techniques (GNSS, VLBI, DORIS) to determine atmosphere gradients of refractivity. For this purpose we implement and compare various strategies for gradient estimation, such as different values for the temporal resolution and the corresponding parameter constraints. Applying least squares estimation the gradients are usually deterministically modelled as constants or piece-wise linear functions. In our study we compare this approach with a stochastic approach modelling atmosphere gradients as random walk processes and applying a Kalman Filter for parameter estimation. The gradients, derived from space geodetic techniques are verified by comparison with those derived from Numerical Weather Models (NWM). These model data were generated using raytracing calculations based on European Centre for Medium-Range Weather Forecast (ECMWF) and National Centers for Environmental Prediction (NCEP) analyses with different spatial resolutions. The investigation of the differences between the ECMWF and NCEP gradients hereby in addition allow for an empirical assessment of the quality of model gradients and how suitable the NWM data are for verification. CONT14 (2014-05-06 until 2014-05-20) is the youngest two week long continuous VLBI campaign carried out by IVS (International VLBI Service for Geodesy and Astrometry). It presents the state-of-the-art VLBI performance in terms of number of stations and number of observations and presents thus an excellent test period for comparisons with other space geodetic techniques. During the VLBI campaign CONT14 the HOBART12 and HOBART26 (Hobart, Tasmania, Australia) VLBI antennas were involved that co-locate with each other. The investigation of the gradient estimate differences from these co-located antennas allows for a valuable empirical quality assessment. Another quality criterion for gradient estimates are the differences of parameters at the borders of adjacent 24h-sessions. Both are investigated in our study.

Adaptation of an urban land surface model to a tropical suburban area: Offline evaluation, sensitivity analysis, and optimization of TEB/ISBA (SURFEX)

NASA Astrophysics Data System (ADS)

Harshan, Suraj

The main objective of the present thesis is the improvement of the TEB/ISBA (SURFEX) urban land surface model (ULSM) through comprehensive evaluation, sensitivity analysis, and optimization experiments using energy balance and radiative and air temperature data observed during 11 months at a tropical sub-urban site in Singapore. Overall the performance of the model is satisfactory, with a small underestimation of net radiation and an overestimation of sensible heat flux. Weaknesses in predicting the latent heat flux are apparent with smaller model values during daytime and the model also significantly underpredicts both the daytime peak and nighttime storage heat. Surface temperatures of all facets are generally overpredicted. Significant variation exists in the model behaviour between dry and wet seasons. The vegetation parametrization used in the model is inadequate to represent the moisture dynamics, producing unrealistically low latent heat fluxes during a particularly dry period. The comprehensive evaluation of the USLM shows the need for accurate estimation of input parameter values for present site. Since obtaining many of these parameters through empirical methods is not feasible, the present study employed a two step approach aimed at providing information about the most sensitive parameters and an optimized parameter set from model calibration. Two well established sensitivity analysis methods (global: Sobol and local: Morris) and a state-of-the-art multiobjective evolutionary algorithm (Borg) were employed for sensitivity analysis and parameter estimation. Experiments were carried out for three different weather periods. The analysis indicates that roof related parameters are the most important ones in controlling the behaviour of the sensible heat flux and net radiation flux, with roof and road albedo as the most influential parameters. Soil moisture initialization parameters are important in controlling the latent heat flux. The built (town) fraction has a significant influence on all fluxes considered. Comparison between the Sobol and Morris methods shows similar sensitivities, indicating the robustness of the present analysis and that the Morris method can be employed as a computationally cheaper alternative of Sobol's method. Optimization as well as the sensitivity experiments for the three periods (dry, wet and mixed), show a noticeable difference in parameter sensitivity and parameter convergence, indicating inadequacies in model formulation. Existence of a significant proportion of less sensitive parameters might be indicating an over-parametrized model. Borg MOEA showed great promise in optimizing the input parameters set. The optimized model modified using the site specific values for thermal roughness length parametrization shows an improvement in the performances of outgoing longwave radiation flux, overall surface temperature, heat storage flux and sensible heat flux.

The ESA Nanosatellite Beacons for Space Weather Monitoring Study

NASA Astrophysics Data System (ADS)

Hapgood, M.; Eckersley, S.; Lundin, R.; Kluge, M.

2008-09-01

This paper will present final results from this ESA-funded study that has investigated how current and emerging concepts for nanosats may be used to monitor space weather conditions and provide improved access to data needed for space weather services. The study has reviewed requirements developed in previous ESA space weather studies to establish a set of service and measurements requirements appropriate to nanosat solutions. The output is conveniently represented as a set of five distinct classes of nanosat constellations, each in different orbit locations and which can address a specific group of measurement requirements. One example driving requirement for several of the constellations was the need for real-time data reception. Given this background, the study then iterated a set of instrument and spacecraft solutions to address each of the nanosat constellations from the requirements. Indeed, iteration has proved to be a critical aspect of the study. The instrument solutions have driven a refinement of requirements through assessment of whether or not the physical parameters to be measured dictate instrument components too large for a nanosat. In addition, the study has also reviewed miniaturization trends for instruments relevant to space weather monitoring by nanosats, looking at the near, mid and far-term timescales. Within the spacecraft solutions the study reviewed key technology trends relevant to space weather monitoring by nanosats: (a) micro and nano-technology devices for spacecraft communications, navigation, propulsion and power, and (b) development and flight experience with nanosats for science and for engineering demonstration. These requirements and solutions were then subject to an iterative system and mission analysis including key mission design issues (e.g. launch/transfer, mission geometry, instrument accommodation, numbers of spacecraft, communications architectures, de-orbit, nanosat reliability and constellation robustness) and the impact of nanosat fundamental limitations (e.g. mass, volume/size, power, communications). As a result, top-level Strawman mission concepts were developed for each constellation, and ROM costs were derived for programme development, operation and maintenance over a ten-year period. Nanosat reliability and constellation robustness were shown to be a key driver in deriving mission costs. In parallel with the mission analysis the study results have been reviewed to identify key issues that determine the prospects for a space weather nanosat programme and to make recommendations on measures to enable implementation of such a programme. As a follow-on to this study, a student MSc project was initiated by Astrium at Cranfield University to analyse a potential space weather precursor demonstration mission in GTO (one of the recommendations from this ESA study), composing of a reduced constellation of nanosats, launched on ASAP or some other low cost method. The demonstration would include: 1/ Low cost multiple manufacture techniques for a fully industrial nanosat constellation programme 2/ Real time datalinks and fully operational mission for space weather 3/ Miniaturised payloads to fit in a nanosat for space weather monitoring: 4/ Other possible demonstrations of advanced technology The aim was to comply with ESA demonstration mission (i.e. PROBA-type) requirements, to be representative on issues such as cost and risk

Studying Weather and Climate Extremes in a Non-stationary Framework

NASA Astrophysics Data System (ADS)

Wu, Z.

2010-12-01

The study of weather and climate extremes often uses the theory of extreme values. Such a detection method has a major problem: to obtain the probability distribution of extremes, one has to implicitly assume the Earth’s climate is stationary over a long period within which the climatology is defined. While such detection makes some sense in a purely statistical view of stationary processes, it can lead to misleading statistical properties of weather and climate extremes caused by long term climate variability and change, and may also cause enormous difficulty in attributing and predicting these extremes. To alleviate this problem, here we report a novel non-stationary framework for studying weather and climate extremes in a non-stationary framework. In this new framework, the weather and climate extremes will be defined as timescale-dependent quantities derived from the anomalies with respect to non-stationary climatologies of different timescales. With this non-stationary framework, the non-stationary and nonlinear nature of climate system will be taken into account; and the attribution and the prediction of weather and climate extremes can then be separated into 1) the change of the statistical properties of the weather and climate extremes themselves and 2) the background climate variability and change. The new non-stationary framework will use the ensemble empirical mode decomposition (EEMD) method, which is a recent major improvement of the Hilbert-Huang Transform for time-frequency analysis. Using this tool, we will adaptively decompose various weather and climate data from observation and climate models in terms of the components of the various natural timescales contained in the data. With such decompositions, the non-stationary statistical properties (both spatial and temporal) of weather and climate anomalies and of their corresponding climatologies will be analyzed and documented.

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2012-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours. AFWA recognizes the importance of operational benchmarking and uncertainty characterization for land surface modeling and is developing standard methods, software, and metrics to verify and/or validate LIS output products. To facilitate this and other needs for land analysis activities at AFWA, the Model Evaluation Toolkit (MET) -- a joint product of the National Center for Atmospheric Research Developmental Testbed Center (NCAR DTC), AFWA, and the user community -- and the Land surface Verification Toolkit (LVT), developed at the Goddard Space Flight Center (GSFC), have been adapted to operational benchmarking needs of AFWA's land characterization activities.

Mistletoe Berry Outline Mapping with a Path Curve Function and Recording the Circadian Rhythm of Their Phenotypic Shape Change

PubMed Central

Derbidge, Renatus; Baumgartner, Stephan; Heusser, Peter

2016-01-01

This paper presents a discovery: the change of the outline shape of mistletoe (Viscum album ssp. album) berries in vivo and in situ during ripening. It was found that a plant organ that is usually considered to merely increase in size actually changes shape in a specific rhythmic fashion. We introduce a new approach to chronobiological research on a macro-phenotypic scale to trace changes over long periods of time (with a resolution from hours to months) by using a dynamic form-determining parameter called Lambda (λ). λ is known in projective geometry as a measure for pertinent features of the outline shapes of egg-like forms, so called path curves. Ascertained circadian changes of form were analyzed for their correlation with environmental factors such as light, temperature, and other weather influences. Certain weather conditions such as sky cover, i.e., sunshine minutes per hour, have an impact on the amplitude of the daily change in form. The present paper suggests a possible supplement to established methods in chronobiology, as in this case the dynamic of form-change becomes a measurable feature, displaying a convincing accordance between mathematical rule and plant shape. PMID:27933073

Evaluating weather factors and material response during outdoor exposure to determine accelerated test protocols for predicting service life

Treesearch

R. Sam Williams; Steven Lacher; Corey Halpin; Christopher White

2005-01-01

To develop service life prediction methods for the study of sealants, a fully instrumented weather station was installed at an outdoor test site near Madison, WI. Temperature, relative humidiy, rainfall, ultraviolet (UV) radiation at 18 wavelengths, and wind speed and direction are being continuously measured and stored. The weather data can be integrated over time to...

Simulating the Refractive Index Structure Constant ({C}_{n}^{2}) in the Surface Layer at Antarctica with a Mesoscale Model

NASA Astrophysics Data System (ADS)

Qing, Chun; Wu, Xiaoqing; Li, Xuebin; Tian, Qiguo; Liu, Dong; Rao, Ruizhong; Zhu, Wenyue

2018-01-01

In this paper, we introduce an approach wherein the Weather Research and Forecasting (WRF) model is coupled with the bulk aerodynamic method to estimate the surface layer refractive index structure constant (C n 2) above Taishan Station in Antarctica. First, we use the measured meteorological parameters to estimate C n 2 using the bulk aerodynamic method, and second, we use the WRF model output parameters to estimate C n 2 using the bulk aerodynamic method. Finally, the corresponding C n 2 values from the micro-thermometer are compared with the C n 2 values estimated using the WRF model coupled with the bulk aerodynamic method. We analyzed the statistical operators—the bias, root mean square error (RMSE), bias-corrected RMSE (σ), and correlation coefficient (R xy )—in a 20 day data set to assess how this approach performs. In addition, we employ contingency tables to investigate the estimation quality of this approach, which provides complementary key information with respect to the bias, RMSE, σ, and R xy . The quantitative results are encouraging and permit us to confirm the fine performance of this approach. The main conclusions of this study tell us that this approach provides a positive impact on optimizing the observing time in astronomical applications and provides complementary key information for potential astronomical sites.

Retrieving Storm Electric Fields From Aircraft Field Mill Data. Part 2; Applications

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Mach, D. M.; Christian, H. J.; Stewart, M. F.; Bateman, M. G.

2005-01-01

The Lagrange multiplier theory and "pitch down method" developed in Part I of this study are applied to complete the calibration of a Citation aircraft that is instrumented with six field mill sensors. When side constraints related to average fields are used, the method performs well in computer simulations. For mill measurement errors of 1 V/m and a 5 V/m error in the mean fair weather field function, the 3-D storm electric field is retrieved to within an error of about 12%. A side constraint that involves estimating the detailed structure of the fair weather field was also tested using computer simulations. For mill measurement errors of 1 V/m, the method retrieves the 3-D storm field to within an error of about 8% if the fair weather field estimate is typically within 1 V/m of the true fair weather field. Using this side constraint and data from fair weather field maneuvers taken on 29 June 2001, the Citation aircraft was calibrated. The resulting calibration matrix was then used to retrieve storm electric fields during a Citation flight on 2 June 2001. The storm field results are encouraging and agree favorably with the results obtained from earlier calibration analyses that were based on iterative techniques.

Waterspout Forecasting Method Over the Eastern Adriatic Using a High-Resolution Numerical Weather Model

NASA Astrophysics Data System (ADS)

Renko, Tanja; Ivušić, Sarah; Telišman Prtenjak, Maja; Šoljan, Vinko; Horvat, Igor

2018-03-01

In this study, a synoptic and mesoscale analysis was performed and Szilagyi's waterspout forecasting method was tested on ten waterspout events in the period of 2013-2016. Data regarding waterspout occurrences were collected from weather stations, an online survey at the official website of the National Meteorological and Hydrological Service of Croatia and eyewitness reports from newspapers and the internet. Synoptic weather conditions were analyzed using surface pressure fields, 500 hPa level synoptic charts, SYNOP reports and atmospheric soundings. For all observed waterspout events, a synoptic type was determined using the 500 hPa geopotential height chart. The occurrence of lightning activity was determined from the LINET lightning database, and waterspouts were divided into thunderstorm-related and "fair weather" ones. Mesoscale characteristics (with a focus on thermodynamic instability indices) were determined using the high-resolution (500 m grid length) mesoscale numerical weather model and model results were compared with the available observations. Because thermodynamic instability indices are usually insufficient for forecasting waterspout activity, the performance of the Szilagyi Waterspout Index (SWI) was tested using vertical atmospheric profiles provided by the mesoscale numerical model. The SWI successfully forecasted all waterspout events, even the winter events. This indicates that the Szilagyi's waterspout prognostic method could be used as a valid prognostic tool for the eastern Adriatic.

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2011-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours

Toward Robust Climate Baselining: Objective Assessment of Climate Change Using Widely Distributed Miniaturized Sensors for Accurate World-Wide Geophysical Measurements

DOE R&D Accomplishments Database

Teller, E.; Leith, C.; Canavan, G.; Marion, J.; Wood, L.

2001-11-13

A gap-free, world-wide, ocean-, atmosphere-, and land surface-spanning geophysical data-set of three decades time-duration containing the full set of geophysical parameters characterizing global weather is the scientific perquisite for defining the climate; the generally-accepted definition in the meteorological community is that climate is the 30-year running-average of weather. Until such a tridecadal climate baseline exists, climate change discussions inevitably will have a semi-speculative, vs. a purely scientific, character, as the baseline against which changes are referenced will at least somewhat uncertain.

A Review on Climate Change in Weather Stations of Guilan Province Using Mann-Kendal Methodand GIS

NASA Astrophysics Data System (ADS)

Behzadi, Jalal

2016-07-01

Climate has always been changing during the life time of the earth, and has appeared in the form of ice age, hurricanes, severe and sudden temperature changes, precipitation and other climatic elements, and has dramatically influenced the environment, and in some cases has caused severe changes and even destructions. Some of the most important aspects of climate changes can be found in precipitation types of different regions in the world and especially Guilan, which is influenced by drastic land conversions and greenhouse gases. Also, agriculture division, industrial activities and unnecessary land conversions are thought to have a huge influence on climate change. Climate change is a result of abnormalcies of metorologyl parameters. Generally, the element of precipitation is somehow included in most theories about climate change. The present study aims to reveal precipitation abnormalcies in Guilan which lead to climate change, and possible deviations of precipitation parameter based on annual, seasonal and monthly series have been evaluated. The Mann-Kendal test has been used to reveal likely deviations leading to climate change. The trend of precipitation changes in long-term has been identifiedusing this method. Also, the beginning and end of these changes have been studied in five stations as representatives of all the thirteen weather stations. Then,the areas which have experienced climate change have been identified using the GIS software along with the severity of the changes with an emphasis on drought. These results can be used in planning and identifying the effects of these changes on the environment. Keywords: Climate Change, Guilan, Mann-Kendal, GIS

Spectral induced polarization (SIP) response of mine tailings

NASA Astrophysics Data System (ADS)

Placencia-Gómez, Edmundo; Parviainen, Annika; Slater, Lee; Leveinen, Jussi

2015-02-01

Mine tailings impoundments are a source of leachates known as acid mine drainage (AMD) which can pose a contamination risk for surrounding surface and groundwater. Methodologies which can help management of this environmental issue are needed. We carried out a laboratory study of the spectral induced polarization (SIP) response of tailings from the Haveri Au-Cu mine, SW Finland. The primary objectives were, (1) to determine possible correlations between SIP parameters and textural properties associated with oxidative-weathering mechanisms, mineralogical composition and metallic content, and (2) to evaluate the effects of the pore water chemistry on SIP parameters associated with redox-inactive and redox-active electrolytes varying in molar concentration, conductivity and pH. The Haveri tailings exhibit well defined relaxation spectra between 100 and 10,000 Hz. The relaxation magnitudes are governed by the in-situ oxidative-weathering conditions on sulphide mineral surfaces contained in the tailings, and decrease with the oxidation degree. The oxidation-driven textural variation in the tailings results in changes to the frequency peak of the phase angle, the imaginary conductivity and chargeability, when plotted versus the pore water conductivity. In contrast, the real and the formation electrical conductivity components show a single linear dependence on the pore water conductivity. The increase of the pore water conductivity (dominated by the increase of ions concentration in solution) along with a transition to acidic conditions shifts the polarization peak towards higher frequencies. These findings show the unique sensitivity of the SIP method to potentially discriminate AMD discharges from reactive oxidation zones in tailings, suggesting a significant advantage for monitoring threatened aquifers.

A Bispectral Composite Threshold Approach for Automatic Cloud Detection in VIIRS Imagery

NASA Technical Reports Server (NTRS)

LaFontaine Frank J.; Jedlovec, Gary J.

2015-01-01

The detection of clouds in satellite imagery has a number of important applications in weather and climate studies. The presence of clouds can alter the energy budget of the Earth-atmosphere system through scattering and absorption of shortwave radiation and the absorption and re-emission of infrared radiation at longer wavelengths. The scattering and absorption characteristics of clouds vary with the microphysical properties of clouds, hence the cloud type. Thus, detecting the presence of clouds over a region in satellite imagery is important in order to derive atmospheric or surface parameters that give insight into weather and climate processes. For many applications however, clouds are a contaminant whose presence interferes with retrieving atmosphere or surface information. In these cases, is important to isolate cloud-free pixels, used to retrieve atmospheric thermodynamic information or surface geophysical parameters, from cloudy ones. This abstract describes an application of a two-channel bispectral composite threshold (BCT) approach applied to VIIRS imagery. The simplified BCT approach uses only the 10.76 and 3.75 micrometer spectral channels from VIIRS in two spectral tests; a straight-forward infrared threshold test with the longwave channel and a shortwave - longwave channel difference test. The key to the success of this approach as demonstrated in past applications to GOES and MODIS data is the generation of temporally and spatially dependent thresholds used in the tests from a previous number of days at similar observations to the current data. The paper and subsequent presentation will present an overview of the approach and intercomparison results with other satellites, methods, and against verification data.

A Meteorological Supersite for Aviation and Cold Weather Applications

NASA Astrophysics Data System (ADS)

Gultepe, Ismail; Agelin-Chaab, M.; Komar, J.; Elfstrom, G.; Boudala, F.; Zhou, B.

2018-05-01

The goal of this study is to better understand atmospheric boundary layer processes and parameters, and to evaluate physical processes for aviation applications using data from a supersite observing site. Various meteorological sensors, including a weather and environmental unmanned aerial vehicle (WE-UAV), and a fog and snow tower (FSOS) observations are part of the project. The PanAm University of Ontario Institute of Technology (UOIT) Meteorological Supersite (PUMS) observations are being collected from April 2015 to date. The FSOS tower gathers observations related to rain, snow, fog, and visibility, aerosols, solar radiation, and wind and turbulence, as well as surface and sky temperature. The FSOSs are located at three locations at about 450-800 m away from the PUMS supersite. The WE-UAV measurements representing aerosol, wind speed and direction, as well as temperature (T) and relative humidity (RH) are provided during clear weather conditions. Other measurements at the PUMS site include cloud backscattering profiles from CL51 ceilometer, MWR observations of liquid water content (LWC), T, and RH, and Microwave Rain Radar (MRR) reflectivity profile, as well as the present weather type, snow water depth, icing rate, 3D-ultrasonic wind and turbulence, and conventional meteorological observations from compact weather stations, e.g., WXTs. The results based on important weather event studies, representing fog, snow, rain, blowing snow, wind gust, planetary boundary layer (PBL) wind research for UAV, and icing conditions are given. The microphysical parameterizations and analysis processes for each event are provided, but the results should not be generalized for all weather events and be used cautiously. Results suggested that integrated observing systems based on data from a supersite as well as satellite sites can provide better information applicable to aviation meteorology, including PBL weather research, validation of numerical weather model predictions, and remote-sensing retrievals. Overall, the results from the five cases are provided and challenges related to observations applicable to aviation meteorology are discussed.