Rain cell-based identification of the vertical profile of reflectivity as observed by weather radar and its use for precipitation uncertainty estimation

Science.gov (United States)

Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Uijlenhoet, R.

2012-04-01

The wide scale implementation of weather radar systems over the last couple of decades has increased our understanding concerning spatio-temporal precipitation dynamics. However, the quantitative estimation of precipitation by these devices is affected by many sources of error. A very dominant source of error results from vertical variations in the hydrometeor size distribution known as the vertical profile of reflectivity (VPR). Since the height of the measurement as well as the beam volume increases with distance from the radar, for stratiform precipitation this results in a serious underestimation (overestimation) of the surface reflectivity while sampling within the snow (bright band) region. This research presents a precipitation cell-based implementation to correct volumetric weather radar measurements for VPR effects. Using the properties of a flipping carpenter square, a contour-based identification technique was developed, which is able to identify and track precipitation cells in real time, distinguishing between convective, stratiform and undefined precipitation. For the latter two types of systems, for each individual cell, a physically plausible vertical profile of reflectivity is estimated using a Monte Carlo optimization method. Since it can be expected that the VPR will vary within a given precipitation cell, a method was developed to take the uncertainty of the VPR estimate into account. As a result, we are able to estimate the amount of precipitation uncertainty as observed by weather radar due to VPR for a given precipitation type and storm cell. We demonstrate the possibilities of this technique for a number of winter precipitation systems observed within the Belgian Ardennes. For these systems, in general, the precipitation uncertainty estimate due to vertical reflectivity profile variations varies between 10-40%.

On the dual nature of lichen-induced rock surface weathering in contrasting micro-environments.

Science.gov (United States)

Marques, Joana; Gonçalves, João; Oliveira, Cláudia; Favero-Longo, Sergio E; Paz-Bermúdez, Graciela; Almeida, Rubim; Prieto, Beatriz

2016-10-01

Contradictory evidence from biogeomorphological studies has increased the debate on the extent of lichen contribution to differential rock surface weathering in both natural and cultural settings. This study, undertaken in Côa Valley Archaeological Park, aimed at evaluating the effect of rock surface orientation on the weathering ability of dominant lichens. Hyphal penetration and oxalate formation at the lichen-rock interface were evaluated as proxies of physical and chemical weathering, respectively. A new protocol of pixel-based supervised image classification for the analysis of periodic acid-Schiff stained cross-sections of colonized schist revealed that hyphal spread of individual species was not influenced by surface orientation. However, hyphal spread was significantly higher in species dominant on northwest facing surfaces. An apparently opposite effect was noticed in terms of calcium oxalate accumulation at the lichen-rock interface; it was detected by Raman spectroscopy and complementary X-ray microdiffraction on southeast facing surfaces only. These results suggest that lichen-induced physical weathering may be most severe on northwest facing surfaces by means of an indirect effect of surface orientation on species abundance, and thus dependent on the species, whereas lichen-induced chemical weathering is apparently higher on southeast facing surfaces and dependent on micro-environmental conditions, giving only weak support to the hypothesis that lichens are responsible for the currently observed pattern of rock-art distribution in Côa Valley. Assumptions about the drivers of open-air rock-art distribution patterns elsewhere should also consider the micro-environmental controls of lichen-induced weathering, to avoid biased measures of lichen contribution to rock-art deterioration. © 2016 by the Ecological Society of America.

Identification and uncertainty estimation of vertical reflectivity profiles using a Lagrangian approach to support quantitative precipitation measurements by weather radar

Science.gov (United States)

Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Delrieu, G.; Uijlenhoet, R.

2013-09-01

This paper presents a novel approach to estimate the vertical profile of reflectivity (VPR) from volumetric weather radar data using both a traditional Eulerian as well as a newly proposed Lagrangian implementation. For this latter implementation, the recently developed Rotational Carpenter Square Cluster Algorithm (RoCaSCA) is used to delineate precipitation regions at different reflectivity levels. A piecewise linear VPR is estimated for either stratiform or neither stratiform/convective precipitation. As a second aspect of this paper, a novel approach is presented which is able to account for the impact of VPR uncertainty on the estimated radar rainfall variability. Results show that implementation of the VPR identification and correction procedure has a positive impact on quantitative precipitation estimates from radar. Unfortunately, visibility problems severely limit the impact of the Lagrangian implementation beyond distances of 100 km. However, by combining this procedure with the global Eulerian VPR estimation procedure for a given rainfall type (stratiform and neither stratiform/convective), the quality of the quantitative precipitation estimates increases up to a distance of 150 km. Analyses of the impact of VPR uncertainty shows that this aspect accounts for a large fraction of the differences between weather radar rainfall estimates and rain gauge measurements.

Managing Uncertainty for an Integrated Fishery

Directory of Open Access Journals (Sweden)

MB Hasan

2012-06-01

Full Text Available This paper investigates ways to deal with the uncertainties in fishing trawler scheduling and production planning in a quota-based integrated commercial fishery. A commercial fishery faces uncertainty mainly from variation in catch rate, which may be due to weather, and other environmental factors. The firm tries to manage this uncertainty through planning co-ordination of fishing trawler scheduling, catch quota, processing and labour allocation, and inventory control. Scheduling must necessarily be done over some finite planning horizon, and the trawler schedule itself introduces man-made variability, which in turn induces inventory in the processing plant. This induced inventory must be managed, complicated by the inability to plan easily beyond the current planning horizon. We develop a surprisingly simple innovation in inventory, which we have not seen in other papers on production management, which of requiring beginning inventory to equal ending inventory. This tool gives management a way to calculate a profit-maximizing safety stock that counter-acts the man-made variability due to the trawler scheduling. We found that the variability of catch rate had virtually no effects on the profitability with inventory. We report numerical results for several planning horizon models, based on data for a major New Zealand fishery.

[Health care economics, uncertainty and physician-induced demand].

Science.gov (United States)

Domenighetti, G; Casabianca, A

1995-10-21

The health care market is a very particular one that is mainly characterized by the absence of information and transparency at every level, particularly between the physician-supplier and the patient-consumer. On this market it is up to the physician to evaluate and define the patient's needs and to decide which are the most effective goods for the patient. The determinants of medical prescription are not only related to the health status of the patient, but also to the payment system (fee for services, salary), to physician density, professional uncertainty, the role and status of the physician in his profession, the legal framework which rules the medical profession, and also the information level of the patient. Agency relationship and professional uncertainty are the most relevant determinants of supplier-induced demand. Professional uncertainty inherent in the practice of a stochastic art such as medicine will "always" give an ethical justification for supplier-induced demand or for the pursuit of "maximal" and/or "defensive" care when market competition is perceived by the physician as a threat to his/her income or employment. Time is ripe for consumers and physicians empowerment in the aim to promote better self-management of health and more thoughtful access to care (for consumers) and more evidences based medicine for physicians.

Climate, weather, and hops

Science.gov (United States)

As climate and weather become more variable, hop growers face increased uncertainty in making decisions about their crop. Given the unprecedented nature of these changes, growers may no longer have enough information and intuitive understanding to adequately assess the situation and evaluate their m...

Stochastic simulation experiment to assess radar rainfall retrieval uncertainties associated with attenuation and its correction

Directory of Open Access Journals (Sweden)

R. Uijlenhoet

2008-03-01

Full Text Available As rainfall constitutes the main source of water for the terrestrial hydrological processes, accurate and reliable measurement and prediction of its spatial and temporal distribution over a wide range of scales is an important goal for hydrology. We investigate the potential of ground-based weather radar to provide such measurements through a theoretical analysis of some of the associated observation uncertainties. A stochastic model of range profiles of raindrop size distributions is employed in a Monte Carlo simulation experiment to investigate the rainfall retrieval uncertainties associated with weather radars operating at X-, C-, and S-band. We focus in particular on the errors and uncertainties associated with rain-induced signal attenuation and its correction for incoherent, non-polarimetric, single-frequency, operational weather radars. The performance of two attenuation correction schemes, the (forward Hitschfeld-Bordan algorithm and the (backward Marzoug-Amayenc algorithm, is analyzed for both moderate (assuming a 50 km path length and intense Mediterranean rainfall (for a 30 km path. A comparison shows that the backward correction algorithm is more stable and accurate than the forward algorithm (with a bias in the order of a few percent for the former, compared to tens of percent for the latter, provided reliable estimates of the total path-integrated attenuation are available. Moreover, the bias and root mean square error associated with each algorithm are quantified as a function of path-averaged rain rate and distance from the radar in order to provide a plausible order of magnitude for the uncertainty in radar-retrieved rain rates for hydrological applications.

Uncertainty and sensitivity analysis in nuclear accident consequence assessment

International Nuclear Information System (INIS)

Karlberg, Olof.

1989-01-01

This report contains the results of a four year project in research contracts with the Nordic Cooperation in Nuclear Safety and the National Institute for Radiation Protection. An uncertainty/sensitivity analysis methodology consisting of Latin Hypercube sampling and regression analysis was applied to an accident consequence model. A number of input parameters were selected and the uncertainties related to these parameter were estimated within a Nordic group of experts. Individual doses, collective dose, health effects and their related uncertainties were then calculated for three release scenarios and for a representative sample of meteorological situations. From two of the scenarios the acute phase after an accident were simulated and from one the long time consequences. The most significant parameters were identified. The outer limits of the calculated uncertainty distributions are large and will grow to several order of magnitudes for the low probability consequences. The uncertainty in the expectation values are typical a factor 2-5 (1 Sigma). The variation in the model responses due to the variation of the weather parameters is fairly equal to the parameter uncertainty induced variation. The most important parameters showed out to be different for each pathway of exposure, which could be expected. However, the overall most important parameters are the wet deposition coefficient and the shielding factors. A general discussion of the usefulness of uncertainty analysis in consequence analysis is also given. (au)

Adverse Weather Evokes Nostalgia.

Science.gov (United States)

van Tilburg, Wijnand A P; Sedikides, Constantine; Wildschut, Tim

2018-03-01

Four studies examined the link between adverse weather and the palliative role of nostalgia. We proposed and tested that (a) adverse weather evokes nostalgia (Hypothesis 1); (b) adverse weather causes distress, which predicts elevated nostalgia (Hypothesis 2); (c) preventing nostalgia exacerbates weather-induced distress (Hypothesis 3); and (d) weather-evoked nostalgia confers psychological benefits (Hypothesis 4). In Study 1, participants listened to recordings of wind, thunder, rain, and neutral sounds. Adverse weather evoked nostalgia. In Study 2, participants kept a 10-day diary recording weather conditions, distress, and nostalgia. We also obtained meteorological data. Adverse weather perceptions were positively correlated with distress, which predicted higher nostalgia. Also, adverse natural weather was associated with corresponding weather perceptions, which predicted elevated nostalgia. (Results were mixed for rain.) In Study 3, preventing nostalgia (via cognitive load) increased weather-evoked distress. In Study 4, weather-evoked nostalgia was positively associated with psychological benefits. The findings pioneer the relevance of nostalgia as source of comfort in adverse weather.

Learning-induced uncertainty reduction in perceptual decisions is task-dependent

Directory of Open Access Journals (Sweden)

Feitong eYang

2014-05-01

Full Text Available Perceptual decision making in which decisions are reached primarily from extracting and evaluating sensory information requires close interactions between the sensory system and decision-related networks in the brain. Uncertainty pervades every aspect of this process and can be considered related to either the stimulus signal or decision criterion. Here, we investigated the learning-induced reduction of both the signal and criterion uncertainty in two perceptual decision tasks based on two Glass pattern stimulus sets. This was achieved by manipulating spiral angle and signal level of radial and concentric Glass patterns. The behavioral results showed that the participants trained with a task based on criterion comparison improved their categorization accuracy for both tasks, whereas the participants who were trained on a task based on signal detection improved their categorization accuracy only on their trained task. We fitted the behavioral data with a computational model that can dissociate the contribution of the signal and criterion uncertainties. The modeling results indicated that the participants trained on the criterion comparison task reduced both the criterion and signal uncertainty. By contrast, the participants who were trained on the signal detection task only reduced their signal uncertainty after training. Our results suggest that the signal uncertainty can be resolved by training participants to extract signals from noisy environments and to discriminate between clear signals, which are evidenced by reduced perception variance after both training procedures. Conversely, the criterion uncertainty can only be resolved by the training of fine discrimination. These findings demonstrate that uncertainty in perceptual decision-making can be reduced with training but that the reduction of different types of uncertainty is task-dependent.

Reconstruction of Historical Weather by Assimilating Old Weather Diary Data

Science.gov (United States)

Neluwala, P.; Yoshimura, K.; Toride, K.; Hirano, J.; Ichino, M.; Okazaki, A.

2017-12-01

Climate can control not only human life style but also other living beings. It is important to investigate historical climate to understand the current and future climates. Information about daily weather can give a better understanding of past life on earth. Long-term weather influences crop calendar as well as the development of civilizations. Unfortunately, existing reconstructed daily weather data are limited to 1850s due to the availability of instrumental data. The climate data prior to that are derived from proxy materials (e.g., tree-ring width, ice core isotopes, etc.) which are either in annual or decadal scale. However, there are many historical documents which contain information about weather such as personal diaries. In Japan, around 20 diaries in average during the 16th - 19th centuries have been collected and converted into a digitized form. As such, diary data exist in many other countries. This study aims to reconstruct historical daily weather during the 18th and 19th centuries using personal daily diaries which have analogue weather descriptions such as `cloudy' or `sunny'. A recent study has shown the possibility of assimilating coarse weather data using idealized experiments. We further extend this study by assimilating modern weather descriptions similar to diary data in recent periods. The Global Spectral model (GSM) of National Centers for Environmental Prediction (NCEP) is used to reconstruct weather with the Local Ensemble Kalman filter (LETKF). Descriptive data are first converted to model variables such as total cloud cover (TCC), solar radiation and precipitation using empirical relationships. Those variables are then assimilated on a daily basis after adding random errors to consider the uncertainty of actual diary data. The assimilation of downward short wave solar radiation using weather descriptions improves RMSE from 64.3 w/m2 to 33.0 w/m2 and correlation coefficient (R) from 0.5 to 0.8 compared with the case without any

Addressing forecast uncertainty impact on CSP annual performance

Science.gov (United States)

Ferretti, Fabio; Hogendijk, Christopher; Aga, Vipluv; Ehrsam, Andreas

2017-06-01

This work analyzes the impact of weather forecast uncertainty on the annual performance of a Concentrated Solar Power (CSP) plant. Forecast time series has been produced by a commercial forecast provider using the technique of hindcasting for the full year 2011 in hourly resolution for Ouarzazate, Morocco. Impact of forecast uncertainty has been measured on three case studies, representing typical tariff schemes observed in recent CSP projects plus a spot market price scenario. The analysis has been carried out using an annual performance model and a standard dispatch optimization algorithm based on dynamic programming. The dispatch optimizer has been demonstrated to be a key requisite to maximize the annual revenues depending on the price scenario, harvesting the maximum potential out of the CSP plant. Forecasting uncertainty affects the revenue enhancement outcome of a dispatch optimizer depending on the error level and the price function. Results show that forecasting accuracy of direct solar irradiance (DNI) is important to make best use of an optimized dispatch but also that a higher number of calculation updates can partially compensate this uncertainty. Improvement in revenues can be significant depending on the price profile and the optimal operation strategy. Pathways to achieve better performance are presented by having more updates both by repeatedly generating new optimized trajectories but also more often updating weather forecasts. This study shows the importance of working on DNI weather forecasting for revenue enhancement as well as selecting weather services that can provide multiple updates a day and probabilistic forecast information.

Salt-Induced Physical Weathering of Stone

Science.gov (United States)

Schiro, M.; Ruiz-Agudo, E.; Rodriguez-Navarro, C.

2010-12-01

Salt weathering is recognized as an important mechanism that contributes to the modeling and shaping of the earth’s surface, in a range of environments spanning from the Sahara desert to Antarctica. It also contributes to the degradation and loss of cultural heritage, particularly carved stone and historic buildings. Soluble salts have recently been suggested to contribute to the shaping of rock outcrops on Mars and are being identified in other planetary bodies such as the moons of Jupiter (Europa and IO)1. Soluble salts such as sulfates, nitrates, chlorides and carbonates of alkali and alkali earth metals can crystallize within the porous system of rocks and building stones, exerting sufficient pressure against the pore walls to fracture the substrate. This physical damage results in increased porosity, thus providing a higher surface area for salt-enhanced chemical weathering. To better understand how salt-induced physical weathering occurs, we have studied the crystallization of the particularly damaging salt, sodium sulfate2, in a model system (a sintered porous glass of controlled porosity and pore size). For this elusive task of studying sub-surface crystallization in pores, we combined a variety of instruments to identify which phases crystallized during evaporation and calculated the supersaturation and associated crystallization pressure that caused damage. The heat of crystallization was measured using differential scanning calorimetry (DSC), providing the timing of crystallization events and phase transitions3, while the evaporation rate was recorded using thermal gravimetry (TG). These methods enabled calculation of the sodium sulfate concentration in solution at every point during evaporation. Two-dimensional X-ray diffraction (2D-XRD) performs synchrotron-like experiments in a normal lab by using a Molybdenum X-ray source (more than 5 times more penetrative than conventional Copper source). Using this method, we determined that the first phase to

Sensitivity and uncertainty studies of the CRAC2 computer code

International Nuclear Information System (INIS)

Kocher, D.C.; Ward, R.C.; Killough, G.G.; Dunning, D.E. Jr.; Hicks, B.B.; Hosker, R.P. Jr.; Ku, J.Y.; Rao, K.S.

1987-01-01

The authors have studied the sensitivity of health impacts from nuclear reactor accidents, as predicted by the CRAC2 computer code, to the following sources of uncertainty: (1) the model for plume rise, (2) the model for wet deposition, (3) the meteorological bin-sampling procedure for selecting weather sequences with rain, (4) the dose conversion factors for inhalation as affected by uncertainties in the particle size of the carrier aerosol and the clearance rates of radionuclides from the respiratory tract, (5) the weathering half-time for external ground-surface exposure, and (6) the transfer coefficients for terrestrial foodchain pathways. Predicted health impacts usually showed little sensitivity to use of an alternative plume-rise model or a modified rain-bin structure in bin-sampling. Health impacts often were quite sensitive to use of an alternative wet-deposition model in single-trial runs with rain during plume passage, but were less sensitive to the model in bin-sampling runs. Uncertainties in the inhalation dose conversion factors had important effects on early injuries in single-trial runs. Latent cancer fatalities were moderately sensitive to uncertainties in the weathering half-time for ground-surface exposures, but showed little sensitivity to the transfer coefficients for terrestrial foodchain pathways. Sensitivities of CRAC2 predictions to uncertainties in the models and parameters also depended on the magnitude of the source term, and some of the effects on early health effects were comparable to those that were due only to selection of different sets of weather sequences in bin-sampling

Linking the M&Rfi Weather Generator with Agrometeorological Models

Science.gov (United States)

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

Impact of inherent meteorology uncertainty on air quality ...

Science.gov (United States)

It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is important to understand how uncertainties in these inputs affect the simulated concentrations. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. Most studies explore this uncertainty by running different meteorological models or the same model with different physics options and in some cases combinations of different meteorological and air quality models. While these have been shown to be useful techniques in some cases, we present a technique that leverages the initial condition perturbations of a weather forecast ensemble, namely, the Short-Range Ensemble Forecast system to drive the four-dimensional data assimilation in the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) model with a key focus being the response of ozone chemistry and transport. Results confirm that a sizable spread in WRF solutions, including common weather variables of temperature, wind, boundary layer depth, clouds, and radiation, can cause a relatively large range of ozone-mixing ratios. Pollutant transport can be altered by hundreds of kilometers over several days. Ozone-mixing ratios of the ensemble can vary as much as 10–20 ppb

Dynamic Routing of Aircraft in the Presence of Adverse Weather Using a POMDP Framework

Science.gov (United States)

Balaban, Edward; Roychoudhury, Indranil; Spirkovska, Lilly; Sankararaman, Shankar; Kulkarni, Chetan; Arnon, Tomer

2017-01-01

Each year weather-related airline delays result in hundreds of millions of dollars in additional fuel burn, maintenance, and lost revenue, not to mention passenger inconvenience. The current approaches for aircraft route planning in the presence of adverse weather still mainly rely on deterministic methods. In contrast, this work aims to deal with the problem using a Partially Observable Markov Decision Processes (POMDPs) framework, which allows for reasoning over uncertainty (including uncertainty in weather evolution over time) and results in solutions that are more robust to disruptions. The POMDP-based decision support system is demonstrated on several scenarios involving convective weather cells and is benchmarked against a deterministic planning system with functionality similar to those currently in use or under development.

Energy operations and planning decision support for systems using weather forecast information

International Nuclear Information System (INIS)

Altalo, M.G.

2004-01-01

Hydroelectric utilities deal with uncertainties on a regular basis. These include uncertainties in weather, policy and markets. This presentation outlined regional studies to define uncertainty, sources of uncertainty and their affect on power managers, power marketers, power insurers and end users. Solutions to minimize uncertainties include better forecasting and better business processes to mobilize action. The main causes of uncertainty in energy operations and planning include uncaptured wind, precipitation and wind events. Load model errors also contribute to uncertainty in energy operations. This presentation presented the results of a 2002-2003 study conducted by the National Oceanic and Atmospheric Administration (NOAA) on the impact uncertainties in northeast energy weather forecasts. The study demonstrated the cost of seabreeze error on transmission and distribution. The impact of climate scale events were also presented along with energy demand implications. It was suggested that energy planners should incorporate climate change parameters into planning, and that models should include probability distribution forecasts and ensemble forecasting methods that incorporate microclimate estimates. It was also suggested that seabreeze, lake effect, fog, afternoon thunderstorms and frontal passage should be incorporated into forecasts. tabs., figs

Ionospheric Response to Extremes in the Space Environment: Establishing Benchmarks for the Space Weather Action Plan.

Science.gov (United States)

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.

Presenting Critical Space Weather Information to Customers and Stakeholders (Invited)

Science.gov (United States)

Viereck, R. A.; Singer, H. J.; Murtagh, W. J.; Rutledge, B.

2013-12-01

Space weather involves changes in the near-Earth space environment that impact technological systems such as electric power, radio communication, satellite navigation (GPS), and satellite opeartions. As with terrestrial weather, there are several different kinds of space weather and each presents unique challenges to the impacted technologies and industries. But unlike terrestrial weather, many customers are not fully aware of space weather or how it impacts their systems. This issue is further complicated by the fact that the largest space weather events occur very infrequently with years going by without severe storms. Recent reports have estimated very large potential costs to the economy and to society if a geomagnetic storm were to cause major damage to the electric power transmission system. This issue has come to the attention of emergency managers and federal agencies including the office of the president. However, when considering space weather impacts, it is essential to also consider uncertainties in the frequency of events and the predicted impacts. The unique nature of space weather storms, the specialized technologies that are impacted by them, and the disparate groups and agencies that respond to space weather forecasts and alerts create many challenges to the task of communicating space weather information to the public. Many customers that receive forecasts and alerts are highly technical and knowledgeable about the subtleties of the space environment. Others know very little and require ongoing education and explanation about how a space weather storm will affect their systems. In addition, the current knowledge and understanding of the space environment that goes into forecasting storms is quite immature. It has only been within the last five years that physics-based models of the space environment have played important roles in predictions. Thus, the uncertainties in the forecasts are quite large. There is much that we don't know about space

Assessing measurement uncertainty in meteorology in urban environments

International Nuclear Information System (INIS)

Curci, S; Lavecchia, C; Frustaci, G; Pilati, S; Paganelli, C; Paolini, R

2017-01-01

Measurement uncertainty in meteorology has been addressed in a number of recent projects. In urban environments, uncertainty is also affected by local effects which are more difficult to deal with than for synoptic stations. In Italy, beginning in 2010, an urban meteorological network (Climate Network ® ) was designed, set up and managed at national level according to high metrological standards and homogeneity criteria to support energy applications. The availability of such a high-quality operative automatic weather station network represents an opportunity to investigate the effects of station siting and sensor exposure and to estimate the related measurement uncertainty. An extended metadata set was established for the stations in Milan, including siting and exposure details. Statistical analysis on an almost 3-year-long operational period assessed network homogeneity, quality and reliability. Deviations from reference mean values were then evaluated in selected low-gradient local weather situations in order to investigate siting and exposure effects. In this paper the methodology is depicted and preliminary results of its application to air temperature discussed; this allowed the setting of an upper limit of 1 °C for the added measurement uncertainty at the top of the urban canopy layer. (paper)

Assessing measurement uncertainty in meteorology in urban environments

Science.gov (United States)

Curci, S.; Lavecchia, C.; Frustaci, G.; Paolini, R.; Pilati, S.; Paganelli, C.

2017-10-01

Measurement uncertainty in meteorology has been addressed in a number of recent projects. In urban environments, uncertainty is also affected by local effects which are more difficult to deal with than for synoptic stations. In Italy, beginning in 2010, an urban meteorological network (Climate Network®) was designed, set up and managed at national level according to high metrological standards and homogeneity criteria to support energy applications. The availability of such a high-quality operative automatic weather station network represents an opportunity to investigate the effects of station siting and sensor exposure and to estimate the related measurement uncertainty. An extended metadata set was established for the stations in Milan, including siting and exposure details. Statistical analysis on an almost 3-year-long operational period assessed network homogeneity, quality and reliability. Deviations from reference mean values were then evaluated in selected low-gradient local weather situations in order to investigate siting and exposure effects. In this paper the methodology is depicted and preliminary results of its application to air temperature discussed; this allowed the setting of an upper limit of 1 °C for the added measurement uncertainty at the top of the urban canopy layer.

Combining weather radar nowcasts and numerical weather prediction models to estimate short-term quantitative precipitation and uncertainty

DEFF Research Database (Denmark)

Jensen, David Getreuer

The topic of this Ph.D. thesis is short term forecasting of precipitation for up to 6 hours called nowcasts. The focus is on improving the precision of deterministic nowcasts, assimilation of radar extrapolation model (REM) data into Danish Meteorological Institutes (DMI) HIRLAM numerical weather...

Multimodel Uncertainty Changes in Simulated River Flows Induced by Human Impact Parameterizations

Science.gov (United States)

Liu, Xingcai; Tang, Qiuhong; Cui, Huijuan; Mu, Mengfei; Gerten Dieter; Gosling, Simon; Masaki, Yoshimitsu; Satoh, Yusuke; Wada, Yoshihide

2017-01-01

Human impacts increasingly affect the global hydrological cycle and indeed dominate hydrological changes in some regions. Hydrologists have sought to identify the human-impact-induced hydrological variations via parameterizing anthropogenic water uses in global hydrological models (GHMs). The consequently increased model complexity is likely to introduce additional uncertainty among GHMs. Here, using four GHMs, between-model uncertainties are quantified in terms of the ratio of signal to noise (SNR) for average river flow during 1971-2000 simulated in two experiments, with representation of human impacts (VARSOC) and without (NOSOC). It is the first quantitative investigation of between-model uncertainty resulted from the inclusion of human impact parameterizations. Results show that the between-model uncertainties in terms of SNRs in the VARSOC annual flow are larger (about 2 for global and varied magnitude for different basins) than those in the NOSOC, which are particularly significant in most areas of Asia and northern areas to the Mediterranean Sea. The SNR differences are mostly negative (-20 to 5, indicating higher uncertainty) for basin-averaged annual flow. The VARSOC high flow shows slightly lower uncertainties than NOSOC simulations, with SNR differences mostly ranging from -20 to 20. The uncertainty differences between the two experiments are significantly related to the fraction of irrigation areas of basins. The large additional uncertainties in VARSOC simulations introduced by the inclusion of parameterizations of human impacts raise the urgent need of GHMs development regarding a better understanding of human impacts. Differences in the parameterizations of irrigation, reservoir regulation and water withdrawals are discussed towards potential directions of improvements for future GHM development. We also discuss the advantages of statistical approaches to reduce the between-model uncertainties, and the importance of calibration of GHMs for not only

Climate change impacts on extreme events in the United States: an uncertainty analysis

Science.gov (United States)

Extreme weather and climate events, such as heat waves, droughts and severe precipitation events, have substantial impacts on ecosystems and the economy. However, future climate simulations display large uncertainty in mean changes. As a result, the uncertainty in future changes ...

Uncertainty of a hydrological climate change impact assessment - Is it really all about climate uncertainty?

Science.gov (United States)

Honti, Mark; Reichert, Peter; Scheidegger, Andreas; Stamm, Christian

2013-04-01

Climate change impact assessments have become more and more popular in hydrology since the middle 1980's with another boost after the publication of the IPCC AR4 report. During hundreds of impact studies a quasi-standard methodology emerged, which is mainly shaped by the growing public demand for predicting how water resources management or flood protection should change in the close future. The ``standard'' workflow considers future climate under a specific IPCC emission scenario simulated by global circulation models (GCMs), possibly downscaled by a regional climate model (RCM) and/or a stochastic weather generator. The output from the climate models is typically corrected for bias before feeding it into a calibrated hydrological model, which is run on the past and future meteorological data to analyse the impacts of climate change on the hydrological indicators of interest. The impact predictions are as uncertain as any forecast that tries to describe the behaviour of an extremely complex system decades into the future. Future climate predictions are uncertain due to the scenario uncertainty and the GCM model uncertainty that is obvious on finer resolution than continental scale. Like in any hierarchical model system, uncertainty propagates through the descendant components. Downscaling increases uncertainty with the deficiencies of RCMs and/or weather generators. Bias correction adds a strong deterministic shift to the input data. Finally the predictive uncertainty of the hydrological model ends the cascade that leads to the total uncertainty of the hydrological impact assessment. There is an emerging consensus between many studies on the relative importance of the different uncertainty sources. The prevailing perception is that GCM uncertainty dominates hydrological impact studies. There are only few studies, which found that the predictive uncertainty of hydrological models can be in the same range or even larger than climatic uncertainty. We carried out a

Parameter uncertainty in simulations of extreme precipitation and attribution studies.

Science.gov (United States)

Timmermans, B.; Collins, W. D.; O'Brien, T. A.; Risser, M. D.

2017-12-01

The attribution of extreme weather events, such as heavy rainfall, to anthropogenic influence involves the analysis of their probability in simulations of climate. The climate models used however, such as the Community Atmosphere Model (CAM), employ approximate physics that gives rise to "parameter uncertainty"—uncertainty about the most accurate or optimal values of numerical parameters within the model. In particular, approximate parameterisations for convective processes are well known to be influential in the simulation of precipitation extremes. Towards examining the impact of this source of uncertainty on attribution studies, we investigate the importance of components—through their associated tuning parameters—of parameterisations relating to deep and shallow convection, and cloud and aerosol microphysics in CAM. We hypothesise that as numerical resolution is increased the change in proportion of variance induced by perturbed parameters associated with the respective components is consistent with the decreasing applicability of the underlying hydrostatic assumptions. For example, that the relative influence of deep convection should diminish as resolution approaches that where convection can be resolved numerically ( 10 km). We quantify the relationship between the relative proportion of variance induced and numerical resolution by conducting computer experiments that examine precipitation extremes over the contiguous U.S. In order to mitigate the enormous computational burden of running ensembles of long climate simulations, we use variable-resolution CAM and employ both extreme value theory and surrogate modelling techniques ("emulators"). We discuss the implications of the relationship between parameterised convective processes and resolution both in the context of attribution studies and progression towards models that fully resolve convection.

Considerations in the weathering of wood-plastic composites

Science.gov (United States)

Nicole M. Stark

2007-01-01

During weathering, wood-plastic composites (WPCs) can fade and lose stiffness and strength. Weathering variables that induce these changes include exposure to UV light and water. Each variable degrades WPCs independently, but can also act synergistically. Recent efforts have highlighted the need to understand how WPCs weather, and to develop schemes for protection. The...

Proceedings of a workshop on dealing with uncertainties in the hydroelectric energy business. CD-ROM ed.

International Nuclear Information System (INIS)

2004-01-01

This workshop was attended by experts in Canadian and international hydroelectric utilities to exchange information on current practices and opportunities for improvement or future cooperation. The discussions focused on reducing the uncertainties associated with hydroelectric power production. Although significant improvements have been made in the efficiency, reliability and safety of hydroelectric power production, the sector is still challenged by the uncertainty of water supply which depends greatly on weather conditions. Energy markets pose another challenge to power producers in terms of energy supply, energy demand and energy prices. The workshop focused on 3 themes: (1) weather and hydrologic uncertainty, (2) market uncertainty, and (3) decision making models using uncertainty principles surrounding water resource planning and operation. The workshop featured 22 presentations of which 11 have been indexed separately for inclusion in this database. refs., tabs., figs

Uncertainty enabled Sensor Observation Services

Science.gov (United States)

Cornford, Dan; Williams, Matthew; Bastin, Lucy

2010-05-01

Almost all observations of reality are contaminated with errors, which introduce uncertainties into the actual observation result. Such uncertainty is often held to be a data quality issue, and quantification of this uncertainty is essential for the principled exploitation of the observations. Many existing systems treat data quality in a relatively ad-hoc manner, however if the observation uncertainty is a reliable estimate of the error on the observation with respect to reality then knowledge of this uncertainty enables optimal exploitation of the observations in further processes, or decision making. We would argue that the most natural formalism for expressing uncertainty is Bayesian probability theory. In this work we show how the Open Geospatial Consortium Sensor Observation Service can be implemented to enable the support of explicit uncertainty about observations. We show how the UncertML candidate standard is used to provide a rich and flexible representation of uncertainty in this context. We illustrate this on a data set of user contributed weather data where the INTAMAP interpolation Web Processing Service is used to help estimate the uncertainty on the observations of unknown quality, using observations with known uncertainty properties. We then go on to discuss the implications of uncertainty for a range of existing Open Geospatial Consortium standards including SWE common and Observations and Measurements. We discuss the difficult decisions in the design of the UncertML schema and its relation and usage within existing standards and show various options. We conclude with some indications of the likely future directions for UncertML in the context of Open Geospatial Consortium services.

Impact of Tactical and Strategic Weather Avoidance on Separation Assurance

Science.gov (United States)

Refai, Mohamad S.; Windhorst, Robert

2011-01-01

The ability to keep flights away from weather hazards while maintaining aircraft-to-aircraft separation is critically important. The Advanced Airspace Concept is an automation concept that implements a ground-based strategic conflict resolution algorithm for management of aircraft separation. The impact of dynamic and uncertain weather avoidance on this concept is investigated. A strategic weather rerouting system is integrated with the Advanced Airspace Concept, which also provides a tactical weather avoidance algorithm, in a fast time simulation of the Air Transportation System. Strategic weather rerouting is used to plan routes around weather in the 20 minute to two-hour time horizon. To address forecast uncertainty, flight routes are revised at 15 minute intervals. Tactical weather avoidance is used for short term trajectory adjustments (30 minute planning horizon) that are updated every minute to address any weather conflicts (instances where aircraft are predicted to pass through weather cells) that are left unresolved by strategic weather rerouting. The fast time simulation is used to assess the impact of tactical weather avoidance on the performance of automated conflict resolution as well as the impact of strategic weather rerouting on both conflict resolution and tactical weather avoidance. The results demonstrate that both tactical weather avoidance and strategic weather rerouting increase the algorithm complexity required to find aircraft conflict resolutions. Results also demonstrate that tactical weather avoidance is prone to higher airborne delay than strategic weather rerouting. Adding strategic weather rerouting to tactical weather avoidance reduces total airborne delays for the reported scenario by 18% and reduces the number of remaining weather violations by 13%. Finally, two features are identified that have proven important for strategic weather rerouting to realize these benefits; namely, the ability to revise reroutes and the use of maneuvers

The communicative process of weather forecasts issued in the probabilistic form

Directory of Open Access Journals (Sweden)

Alessio Raimondi

2009-03-01

Full Text Available One of the main purposes of weather forecasting is that of protecting weather-sensitive human activities. Forecasts issued in the probabilistic form have a higher informative content, as opposed to deterministic one, since they bear information that give also a measure of their own uncertainty. However, in order to make an appropriate and effective use of this kind of forecasts in an operational setting, communication becomes significatively relevant.The present paper, after having briefly examined the weather forecasts concerning Hurricane Charley (August 2004, tackles the issue of the communicative process in detail.The bottom line of this study is that for the weather forecast to achieve its best predictive potential, an in-depth analysis of communication issues is necessary.

Regime-dependent forecast uncertainty of convective precipitation

Energy Technology Data Exchange (ETDEWEB)

Keil, Christian; Craig, George C. [Muenchen Univ. (Germany). Meteorologisches Inst.

2011-04-15

Forecast uncertainty of convective precipitation is influenced by all scales, but in different ways in different meteorological situations. Forecasts of the high resolution ensemble prediction system COSMO-DE-EPS of Deutscher Wetterdienst (DWD) are used to examine the dominant sources of uncertainty of convective precipitation. A validation with radar data using traditional as well as spatial verification measures highlights differences in precipitation forecast performance in differing weather regimes. When the forecast uncertainty can primarily be associated with local, small-scale processes individual members run with the same variation of the physical parameterisation driven by different global models outperform all other ensemble members. In contrast when the precipitation is governed by the large-scale flow all ensemble members perform similarly. Application of the convective adjustment time scale confirms this separation and shows a regime-dependent forecast uncertainty of convective precipitation. (orig.)

Kalman filter approach for uncertainty quantification in time-resolved laser-induced incandescence.

Science.gov (United States)

Hadwin, Paul J; Sipkens, Timothy A; Thomson, Kevin A; Liu, Fengshan; Daun, Kyle J

2018-03-01

Time-resolved laser-induced incandescence (TiRe-LII) data can be used to infer spatially and temporally resolved volume fractions and primary particle size distributions of soot-laden aerosols, but these estimates are corrupted by measurement noise as well as uncertainties in the spectroscopic and heat transfer submodels used to interpret the data. Estimates of the temperature, concentration, and size distribution of soot primary particles within a sample aerosol are typically made by nonlinear regression of modeled spectral incandescence decay, or effective temperature decay, to experimental data. In this work, we employ nonstationary Bayesian estimation techniques to infer aerosol properties from simulated and experimental LII signals, specifically the extended Kalman filter and Schmidt-Kalman filter. These techniques exploit the time-varying nature of both the measurements and the models, and they reveal how uncertainty in the estimates computed from TiRe-LII data evolves over time. Both techniques perform better when compared with standard deterministic estimates; however, we demonstrate that the Schmidt-Kalman filter produces more realistic uncertainty estimates.

Meteorological uncertainty of atmospheric dispersion model results (MUD)

International Nuclear Information System (INIS)

Havskov Soerensen, J.; Amstrup, B.; Feddersen, H.

2013-08-01

The MUD project addresses assessment of uncertainties of atmospheric dispersion model predictions, as well as possibilities for optimum presentation to decision makers. Previously, it has not been possible to estimate such uncertainties quantitatively, but merely to calculate the 'most likely' dispersion scenario. However, recent developments in numerical weather prediction (NWP) include probabilistic forecasting techniques, which can be utilised also for long-range atmospheric dispersion models. The ensemble statistical methods developed and applied to NWP models aim at describing the inherent uncertainties of the meteorological model results. These uncertainties stem from e.g. limits in meteorological observations used to initialise meteorological forecast series. By perturbing e.g. the initial state of an NWP model run in agreement with the available observational data, an ensemble of meteorological forecasts is produced from which uncertainties in the various meteorological parameters are estimated, e.g. probabilities for rain. Corresponding ensembles of atmospheric dispersion can now be computed from which uncertainties of predicted radionuclide concentration and deposition patterns can be derived. (Author)

Carbon accounting and economic model uncertainty of emissions from biofuels-induced land use change.

Science.gov (United States)

Plevin, Richard J; Beckman, Jayson; Golub, Alla A; Witcover, Julie; O'Hare, Michael

2015-03-03

Few of the numerous published studies of the emissions from biofuels-induced "indirect" land use change (ILUC) attempt to propagate and quantify uncertainty, and those that have done so have restricted their analysis to a portion of the modeling systems used. In this study, we pair a global, computable general equilibrium model with a model of greenhouse gas emissions from land-use change to quantify the parametric uncertainty in the paired modeling system's estimates of greenhouse gas emissions from ILUC induced by expanded production of three biofuels. We find that for the three fuel systems examined--US corn ethanol, Brazilian sugar cane ethanol, and US soybean biodiesel--95% of the results occurred within ±20 g CO2e MJ(-1) of the mean (coefficient of variation of 20-45%), with economic model parameters related to crop yield and the productivity of newly converted cropland (from forestry and pasture) contributing most of the variance in estimated ILUC emissions intensity. Although the experiments performed here allow us to characterize parametric uncertainty, changes to the model structure have the potential to shift the mean by tens of grams of CO2e per megajoule and further broaden distributions for ILUC emission intensities.

Space weather effects on ground based technology

Science.gov (United States)

Clark, T.

Space weather can affect a variety of forms of ground-based technology, usually as a result of either the direct effects of the varying geomagnetic field, or as a result of the induced electric field that accompanies such variations. Technologies affected directly by geomagnetic variations include magnetic measurements made d ringu geophysical surveys, and navigation relying on the geomagnetic field as a direction reference, a method that is particularly common in the surveying of well-bores in the oil industry. The most obvious technology affected by induced electric fields during magnetic storms is electric power transmission, where the example of the blackout in Quebec during the March 1989 magnetic storm is widely known. Additionally, space weather effects must be taken into account in the design of active cathodic protection systems on pipelines to protect them against corrosion. Long-distance telecommunication cables may also have to be designed to cope with space weather related effects. This paper reviews the effects of space weather in these different areas of ground-based technology, and provides examples of how mitigation against hazards may be achieved. (The paper does not include the effects of space weather on radio communication or satellite navigation systems).

Sensitivity and uncertainty studies of the CRAC2 computer code

International Nuclear Information System (INIS)

Kocher, D.C.; Ward, R.C.; Killough, G.G.; Dunning, D.E. Jr.; Hicks, B.B.; Hosker, R.P. Jr.; Ku, J.Y.; Rao, K.S.

1985-05-01

This report presents a study of the sensitivity of early fatalities, early injuries, latent cancer fatalities, and economic costs for hypothetical nuclear reactor accidents as predicted by the CRAC2 computer code (CRAC = Calculation of Reactor Accident Consequences) to uncertainties in selected models and parameters used in the code. The sources of uncertainty that were investigated in the CRAC2 sensitivity studies include (1) the model for plume rise, (2) the model for wet deposition, (3) the procedure for meteorological bin-sampling involving the selection of weather sequences that contain rain, (4) the dose conversion factors for inhalation as they are affected by uncertainties in the physical and chemical form of the released radionuclides, (5) the weathering half-time for external ground-surface exposure, and (6) the transfer coefficients for estimating exposures via terrestrial foodchain pathways. The sensitivity studies were performed for selected radionuclide releases, hourly meteorological data, land-use data, a fixed non-uniform population distribution, a single evacuation model, and various release heights and sensible heat rates. Two important general conclusions from the sensitivity and uncertainty studies are as follows: (1) The large effects on predicted early fatalities and early injuries that were observed in some of the sensitivity studies apparently are due in part to the presence of thresholds in the dose-response models. Thus, the observed sensitivities depend in part on the magnitude of the radionuclide releases. (2) Some of the effects on predicted early fatalities and early injuries that were observed in the sensitivity studies were comparable to effects that were due only to the selection of different sets of weather sequences in bin-sampling runs. 47 figs., 50 tabs

Perseveration induces dissociative uncertainty in obsessive-compulsive disorder.

Science.gov (United States)

Giele, Catharina L; van den Hout, Marcel A; Engelhard, Iris M; Dek, Eliane C P; Toffolo, Marieke B J; Cath, Danielle C

2016-09-01

Obsessive compulsive (OC)-like perseveration paradoxically increases feelings of uncertainty. We studied whether the underlying mechanism between perseveration and uncertainty is a reduced accessibility of meaning ('semantic satiation'). OCD patients (n = 24) and matched non-clinical controls (n = 24) repeated words 2 (non-perseveration) or 20 times (perseveration). They decided whether this word was related to another target word. Speed of relatedness judgments and feelings of dissociative uncertainty were measured. The effects of real-life perseveration on dissociative uncertainty were tested in a smaller subsample of the OCD group (n = 9). Speed of relatedness judgments was not affected by perseveration. However, both groups reported more dissociative uncertainty after perseveration compared to non-perseveration, which was higher in OCD patients. Patients reported more dissociative uncertainty after 'clinical' perseveration compared to non-perseveration.. Both parts of this study are limited by some methodological issues and a small sample size. Although the mechanism behind 'perseveration → uncertainty' is still unclear, results suggest that the effects of perseveration are counterproductive. Copyright © 2016 Elsevier Ltd. All rights reserved.

Diagnosing Geospatial Uncertainty Visualization Challenges in Seasonal Temperature and Precipitation Forecasts

Science.gov (United States)

Speciale, A.; Kenney, M. A.; Gerst, M.; Baer, A. E.; DeWitt, D.; Gottschalk, J.; Handel, S.

2017-12-01

The uncertainty of future weather and climate conditions is important for many decisions made in communities and economic sectors. One tool that decision-makers use in gauging this uncertainty is forecasts, especially maps (or visualizations) of probabilistic forecast results. However, visualizing geospatial uncertainty is challenging because including probability introduces an extra variable to represent and probability is often poorly understood by users. Using focus group and survey methods, this study seeks to understand the barriers to using probabilistic temperature and precipitation visualizations for specific decisions in the agriculture, energy, emergency management, and water resource sectors. Preliminary results shown here focus on findings of emergency manager needs. Our experimental design uses National Oceanic and Atmospheric Administration (NOAA's) Climate Prediction Center (CPC) climate outlooks, which produce probabilistic temperature and precipitation forecast visualizations at the 6-10 day, 8-14 day, 3-4 week, and 1 and 3 month timeframes. Users were asked to complete questions related to how they use weather information, how uncertainty is represented, and design elements (e.g., color, contour lines) of the visualizations. Preliminary results from the emergency management sector indicate there is significant confusion on how "normal" weather is defined, boundaries between probability ranges, and meaning of the contour lines. After a complete understandability diagnosis is made using results from all sectors, we will collaborate with CPC to suggest modifications to the climate outlook visualizations. These modifications will then be retested in similar focus groups and web-based surveys to confirm they better meet the needs of users.

Energy, variability and weather finance engineering

Science.gov (United States)

Roussis, Dimitrios; Parara, Iliana; Gournari, Panagiota; Moustakis, Yiannis; Dimitriadis, Panayiotis; Iliopoulou, Theano; Koutsoyiannis, Demetris; Karakatsanis, Georgios

2017-04-01

Most types of renewable energies are characterized by intense intermittency, causing significant instabilities to the grid; further requiring additional infrastructure (e.g. pumped-storage) for buffering hydrometeorological uncertainties, as well as complex operational rules for load balancing. In addition, most intermittent renewable units are subsidized, creating significant market inefficiencies. Weather derivatives comprise mature financial tools for integrating successfully the intermittent-load and base-load components into a unified hybrid energy system and establish their operation within a generalized uncertainty management market. With a growing global market share and 46% utilization of this financial tool by the energy industry and 12% by agriculture (that partially concerns biofuel resources), weather derivatives are projected to constitute a critical subsystem of many grids for buffering frequent hydrometeorological risks of low and medium impacts -which are not covered by standard insurance contracts that aim exclusively at extreme events and high financial damages. In this context, we study the attributes of hydrometeorological time series in a remote and small island in Greece, powered by an autonomous hybrid energy system. Upon the results we choose the optimal underlying index and we further compose and engineer a weather derivative with features of a typical option contract -which we consider most flexible and appropriate for the case- to test our assumptions on its beneficiary effects for both the budget of private energy producers and the island's public administration. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

Exploring the future change space for fire weather in southeast Australia

Science.gov (United States)

Clarke, Hamish; Evans, Jason P.

2018-05-01

High-resolution projections of climate change impacts on fire weather conditions in southeast Australia out to 2080 are presented. Fire weather is represented by the McArthur Forest Fire Danger Index (FFDI), calculated from an objectively designed regional climate model ensemble. Changes in annual cumulative FFDI vary widely, from - 337 (- 21%) to + 657 (+ 24%) in coastal areas and - 237 (- 12%) to + 1143 (+ 26%) in inland areas. A similar spread is projected in extreme FFDI values. In coastal regions, the number of prescribed burning days is projected to change from - 11 to + 10 in autumn and - 10 to + 3 in spring. Across the ensemble, the most significant increases in fire weather and decreases in prescribed burn windows are projected to take place in spring. Partial bias correction of FFDI leads to similar projections but with a greater spread, particularly in extreme values. The partially bias-corrected FFDI performs similarly to uncorrected FFDI compared to the observed annual cumulative FFDI (ensemble root mean square error spans 540 to 1583 for uncorrected output and 695 to 1398 for corrected) but is generally worse for FFDI values above 50. This emphasizes the need to consider inter-variable relationships when bias-correcting for complex phenomena such as fire weather. There is considerable uncertainty in the future trajectory of fire weather in southeast Australia, including the potential for less prescribed burning days and substantially greater fire danger in spring. Selecting climate models on the basis of multiple criteria can lead to more informative projections and allow an explicit exploration of uncertainty.

Amphetamine-induced sensitization and reward uncertainty similarly enhance incentive salience for conditioned cues

Science.gov (United States)

Robinson, Mike J.F.; Anselme, Patrick; Suchomel, Kristen; Berridge, Kent C.

2015-01-01

Amphetamine and stress can sensitize mesolimbic dopamine-related systems. In Pavlovian autoshaping, repeated exposure to uncertainty of reward prediction can enhance motivated sign-tracking or attraction to a discrete reward-predicting cue (lever CS+), as well as produce cross-sensitization to amphetamine. However, it remains unknown how amphetamine-sensitization or repeated restraint stress interact with uncertainty in controlling CS+ incentive salience attribution reflected in sign-tracking. Here rats were tested in three successive phases. First, different groups underwent either induction of amphetamine sensitization or repeated restraint stress, or else were not sensitized or stressed as control groups (either saline injections only, or no stress or injection at all). All next received Pavlovian autoshaping training under either certainty conditions (100% CS-UCS association) or uncertainty conditions (50% CS-UCS association and uncertain reward magnitude). During training, rats were assessed for sign-tracking to the lever CS+ versus goal-tracking to the sucrose dish. Finally, all groups were tested for psychomotor sensitization of locomotion revealed by an amphetamine challenge. Our results confirm that reward uncertainty enhanced sign-tracking attraction toward the predictive CS+ lever, at the expense of goal-tracking. We also report that amphetamine sensitization promoted sign-tracking even in rats trained under CS-UCS certainty conditions, raising them to sign-tracking levels equivalent to the uncertainty group. Combining amphetamine sensitization and uncertainty conditions together did not add together to elevate sign-tracking further above the relatively high levels induced by either manipulation alone. In contrast, repeated restraint stress enhanced subsequent amphetamine-elicited locomotion, but did not enhance CS+ attraction. PMID:26076340

Improving Air Quality (and Weather) Predictions using Advanced Data Assimilation Techniques Applied to Coupled Models during KORUS-AQ

Science.gov (United States)

Carmichael, G. R.; Saide, P. E.; Gao, M.; Streets, D. G.; Kim, J.; Woo, J. H.

2017-12-01

Ambient aerosols are important air pollutants with direct impacts on human health and on the Earth's weather and climate systems through their interactions with radiation and clouds. Their role is dependent on their distributions of size, number, phase and composition, which vary significantly in space and time. There remain large uncertainties in simulated aerosol distributions due to uncertainties in emission estimates and in chemical and physical processes associated with their formation and removal. These uncertainties lead to large uncertainties in weather and air quality predictions and in estimates of health and climate change impacts. Despite these uncertainties and challenges, regional-scale coupled chemistry-meteorological models such as WRF-Chem have significant capabilities in predicting aerosol distributions and explaining aerosol-weather interactions. We explore the hypothesis that new advances in on-line, coupled atmospheric chemistry/meteorological models, and new emission inversion and data assimilation techniques applicable to such coupled models, can be applied in innovative ways using current and evolving observation systems to improve predictions of aerosol distributions at regional scales. We investigate the impacts of assimilating AOD from geostationary satellite (GOCI) and surface PM2.5 measurements on predictions of AOD and PM in Korea during KORUS-AQ through a series of experiments. The results suggest assimilating datasets from multiple platforms can improve the predictions of aerosol temporal and spatial distributions.

An equilibrium pricing model for weather derivatives in a multi-commodity setting

International Nuclear Information System (INIS)

Lee, Yongheon; Oren, Shmuel S.

2009-01-01

Many industries are exposed to weather risk. Weather derivatives can play a key role in hedging and diversifying such risk because the uncertainty in a company's profit function can be correlated to weather condition which affects diverse industry sectors differently. Unfortunately the weather derivatives market is a classical example of an incomplete market that is not amenable to standard methodologies used for derivative pricing in complete markets. In this paper, we develop an equilibrium pricing model for weather derivatives in a multi-commodity setting. The model is constructed in the context of a stylized economy where agents optimize their hedging portfolios which include weather derivatives that are issued in a fixed quantity by a financial underwriter. The supply and demand resulting from hedging activities and the supply by the underwriter are combined in an equilibrium pricing model under the assumption that all agents maximize some risk averse utility function. We analyze the gains due to the inclusion of weather derivatives in hedging portfolios and examine the components of that gain attributable to hedging and to risk sharing. (author)

Amphetamine-induced sensitization and reward uncertainty similarly enhance incentive salience for conditioned cues.

Science.gov (United States)

Robinson, Mike J F; Anselme, Patrick; Suchomel, Kristen; Berridge, Kent C

2015-08-01

Amphetamine and stress can sensitize mesolimbic dopamine-related systems. In Pavlovian autoshaping, repeated exposure to uncertainty of reward prediction can enhance motivated sign-tracking or attraction to a discrete reward-predicting cue (lever-conditioned stimulus; CS+), as well as produce cross-sensitization to amphetamine. However, it remains unknown how amphetamine sensitization or repeated restraint stress interact with uncertainty in controlling CS+ incentive salience attribution reflected in sign-tracking. Here rats were tested in 3 successive phases. First, different groups underwent either induction of amphetamine sensitization or repeated restraint stress, or else were not sensitized or stressed as control groups (either saline injections only, or no stress or injection at all). All next received Pavlovian autoshaping training under either certainty conditions (100% CS-UCS association) or uncertainty conditions (50% CS-UCS association and uncertain reward magnitude). During training, rats were assessed for sign-tracking to the CS+ lever versus goal-tracking to the sucrose dish. Finally, all groups were tested for psychomotor sensitization of locomotion revealed by an amphetamine challenge. Our results confirm that reward uncertainty enhanced sign-tracking attraction toward the predictive CS+ lever, at the expense of goal-tracking. We also reported that amphetamine sensitization promoted sign-tracking even in rats trained under CS-UCS certainty conditions, raising them to sign-tracking levels equivalent to the uncertainty group. Combining amphetamine sensitization and uncertainty conditions did not add together to elevate sign-tracking further above the relatively high levels induced by either manipulation alone. In contrast, repeated restraint stress enhanced subsequent amphetamine-elicited locomotion, but did not enhance CS+ attraction. (c) 2015 APA, all rights reserved).

A Study on the Uncertainty of Flow-Induced Vibration in a Cross Flow over Staggered Tubes

Energy Technology Data Exchange (ETDEWEB)

Kim, Ji-Su; Park, Jong-Woon [Dongguk univ, Gyeong Ju (Korea, Republic of); Choi, Hyeon-Kyeong [HanNam University, Daejeon (Korea, Republic of)

2015-05-15

Cross-flow in many support columns of very high temperature reactor (VHTR) lower plenum would have FIV issues under high speed flow jetting from the core. For a group of multiple circular cylinders subjected to a cross-flow, three types of potential vibration mechanisms may exist: (1) Vortex-induced vibration (VIV), (2) Fluid-elastic vibration (FEV) and (3) Turbulence-induced vibration (TIV). Kevalahan studied the free vibration of circular cylinders in a tightly packed periodic square inline array of cylinders. Pandey et al. studied the flue gas flow distribution in the Low Temperature Super Heater (LTSH) tube bundles situated in second pass of a utility boiler and the phenomenon of flow induced vibration. Nakamura et al. studied flow instability of cylinder arrays resembling U-bend tubes in steam generators. The FIV evaluation is usually performed with computational fluid dynamic (CFD) analysis to obtain unknown frequency of oscillation of the multiple objects under turbulent flow and thus the uncertainty residing in the turbulence model used should be quantified. In this paper, potential FIV uncertainty arising from the turbulence phenomena are evaluated for a typical cross flow through staggered tube bundles resembling the VHTR lower plenum support columns. Flow induced vibration (FIV) is one of the important mechanical and fatigue issues in nuclear systems. Especially, cross-flow in many support structures of VHTR lower plenum would have FIV issues under highly turbulent jet flows from the core. The results show that the effect of turbulence parameters on FIV is not negligible and the uncertainty is 5 to 10%. Present method can be applied to future FIV evaluations of nuclear systems. More extensive studies on flow induced vibration in a plant scale by using more rigorous computational methods are under way.

Next generation of weather generators on web service framework

Science.gov (United States)

Chinnachodteeranun, R.; Hung, N. D.; Honda, K.; Ines, A. V. M.

2016-12-01

Weather generator is a statistical model that synthesizes possible realization of long-term historical weather in future. It generates several tens to hundreds of realizations stochastically based on statistical analysis. Realization is essential information as a crop modeling's input for simulating crop growth and yield. Moreover, they can be contributed to analyzing uncertainty of weather to crop development stage and to decision support system on e.g. water management and fertilizer management. Performing crop modeling requires multidisciplinary skills which limit the usage of weather generator only in a research group who developed it as well as a barrier for newcomers. To improve the procedures of performing weather generators as well as the methodology to acquire the realization in a standard way, we implemented a framework for providing weather generators as web services, which support service interoperability. Legacy weather generator programs were wrapped in the web service framework. The service interfaces were implemented based on an international standard that was Sensor Observation Service (SOS) defined by Open Geospatial Consortium (OGC). Clients can request realizations generated by the model through SOS Web service. Hierarchical data preparation processes required for weather generator are also implemented as web services and seamlessly wired. Analysts and applications can invoke services over a network easily. The services facilitate the development of agricultural applications and also reduce the workload of analysts on iterative data preparation and handle legacy weather generator program. This architectural design and implementation can be a prototype for constructing further services on top of interoperable sensor network system. This framework opens an opportunity for other sectors such as application developers and scientists in other fields to utilize weather generators.

Meteorological uncertainty of atmospheric dispersion model results (MUD)

Energy Technology Data Exchange (ETDEWEB)

Havskov Soerensen, J.; Amstrup, B.; Feddersen, H. [Danish Meteorological Institute, Copenhagen (Denmark)] [and others

2013-08-15

The MUD project addresses assessment of uncertainties of atmospheric dispersion model predictions, as well as possibilities for optimum presentation to decision makers. Previously, it has not been possible to estimate such uncertainties quantitatively, but merely to calculate the 'most likely' dispersion scenario. However, recent developments in numerical weather prediction (NWP) include probabilistic forecasting techniques, which can be utilised also for long-range atmospheric dispersion models. The ensemble statistical methods developed and applied to NWP models aim at describing the inherent uncertainties of the meteorological model results. These uncertainties stem from e.g. limits in meteorological observations used to initialise meteorological forecast series. By perturbing e.g. the initial state of an NWP model run in agreement with the available observational data, an ensemble of meteorological forecasts is produced from which uncertainties in the various meteorological parameters are estimated, e.g. probabilities for rain. Corresponding ensembles of atmospheric dispersion can now be computed from which uncertainties of predicted radionuclide concentration and deposition patterns can be derived. (Author)

Identifying and Analyzing Uncertainty Structures in the TRMM Microwave Imager Precipitation Product over Tropical Ocean Basins

Science.gov (United States)

Liu, Jianbo; Kummerow, Christian D.; Elsaesser, Gregory S.

2016-01-01

Despite continuous improvements in microwave sensors and retrieval algorithms, our understanding of precipitation uncertainty is quite limited, due primarily to inconsistent findings in studies that compare satellite estimates to in situ observations over different parts of the world. This study seeks to characterize the temporal and spatial properties of uncertainty in the Tropical Rainfall Measuring Mission Microwave Imager surface rainfall product over tropical ocean basins. Two uncertainty analysis frameworks are introduced to qualitatively evaluate the properties of uncertainty under a hierarchy of spatiotemporal data resolutions. The first framework (i.e. 'climate method') demonstrates that, apart from random errors and regionally dependent biases, a large component of the overall precipitation uncertainty is manifested in cyclical patterns that are closely related to large-scale atmospheric modes of variability. By estimating the magnitudes of major uncertainty sources independently, the climate method is able to explain 45-88% of the monthly uncertainty variability. The percentage is largely resolution dependent (with the lowest percentage explained associated with a 1 deg x 1 deg spatial/1 month temporal resolution, and highest associated with a 3 deg x 3 deg spatial/3 month temporal resolution). The second framework (i.e. 'weather method') explains regional mean precipitation uncertainty as a summation of uncertainties associated with individual precipitation systems. By further assuming that self-similar recurring precipitation systems yield qualitatively comparable precipitation uncertainties, the weather method can consistently resolve about 50 % of the daily uncertainty variability, with only limited dependence on the regions of interest.

Automatic processing, quality assurance and serving of real-time weather data

Science.gov (United States)

Williams, Matthew; Cornford, Dan; Bastin, Lucy; Jones, Richard; Parker, Stephen

2011-03-01

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts, a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the world. Despite the abundance of available data, the production of usable information about the weather in individual local neighbourhoods requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this instance, this allows a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods provided by the INTAMAP project. A simplified example illustrates how the INTAMAP web processing service can be employed as part of a quality control procedure to estimate the bias and residual variance of user contributed temperature observations, using a reference standard based on temperature observations with carefully controlled quality. We also consider how the uncertainty introduced by the interpolation can be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

Weather in the Cockpit: Priorities, Sources, Delivery, and Needs in the Next Generation Air Transportation System

Science.gov (United States)

2012-07-01

System GSD ----------- NOAA/ESRL/ Global Systems Division IAF ------------- Initial Approach Fix IFR ------------- Instrument Flight Rules IMC... uncertainties . A distillation of our review of the literature and a new detailed analysis of our own leads to the weather factors shown in Figure 1...ratings of weather factors differed between operating in visual flight rules (VFR) and operating in instrument flight rules ( IFR ). In characterizing

Flood modelling : Parameterisation and inflow uncertainty

NARCIS (Netherlands)

Mukolwe, M.M.; Di Baldassarre, G.; Werner, M.; Solomatine, D.P.

2014-01-01

This paper presents an analysis of uncertainty in hydraulic modelling of floods, focusing on the inaccuracy caused by inflow errors and parameter uncertainty. In particular, the study develops a method to propagate the uncertainty induced by, firstly, application of a stage–discharge rating curve

Effectiveness of Weather Derivatives as a Risk Management Tool in Food Retail: The Case of Croatia

Directory of Open Access Journals (Sweden)

Ivana Štulec

2017-01-01

Full Text Available Non-catastrophic weather risk is gaining importance as climate change becomes more pronounced and economic crisis forces companies to strengthen their cost control. Recent literature proposes weather derivatives as flexible weather risk mitigating tools. Only a handful of studies analysed the feasibility of weather derivatives in industries other than agriculture and energy. The purpose of this paper is to review available weather risk management solutions in retail, present weather derivatives as non-catastrophic weather risk management tools, empirically demonstrate the process of designing weather derivatives and assess their effectiveness as risk mitigating tools in retail. Empirical analysis is performed on beverage sales in 60 large food stores in Croatia, and performance of monthly temperature put options during the summer season is examined. For weather sensitivity analysis of sales, the method of panel regression was used. Results show that weather has a statistically significant effect on beverage sales and that weather derivatives prove to be effective in beverage sales uncertainty reduction. Their effectiveness differs between covered periods and cities.

The communicative process of weather forecasts issued in the probabilistic form (Italian original version

Directory of Open Access Journals (Sweden)

Alessio Raimondi

2009-03-01

Full Text Available One of the main purposes of weather forecasting is that of protecting weather-sensitive human activities. Forecasts issued in the probabilistic form have a higher informative content, as opposed to deterministic one, since they bear information that give also a measure of their own uncertainty. However, in order to make an appropriate and effective use of this kind of forecasts in an operational setting, communication becomes significatively relevant.The present paper, after having briefly examined the weather forecasts concerning Hurricane Charley (August 2004, tackles the issue of the communicative process in detail.The bottom line of this study is that for the weather forecast to achieve its best predictive potential, an in-depth analysis of communication issues is necessary.

Flood forecasting and uncertainty of precipitation forecasts

International Nuclear Information System (INIS)

Kobold, Mira; Suselj, Kay

2004-01-01

The timely and accurate flood forecasting is essential for the reliable flood warning. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual rainfall - runoff models enable the estimation of these parameters and lead to useful operational forecasts. The accurate rainfall is the most important input into hydrological models. The input for the rainfall can be real time rain-gauges data, or weather radar data, or meteorological forecasted precipitation. The torrential nature of streams and fast runoff are characteristic for the most of the Slovenian rivers. Extensive damage is caused almost every year- by rainstorms affecting different regions of Slovenia' The lag time between rainfall and runoff is very short for Slovenian territory and on-line data are used only for now casting. Forecasted precipitations are necessary for hydrological forecast for some days ahead. ECMWF (European Centre for Medium-Range Weather Forecasts) gives general forecast for several days ahead while more detailed precipitation data with limited area ALADIN/Sl model are available for two days ahead. There is a certain degree of uncertainty using such precipitation forecasts based on meteorological models. The variability of precipitation is very high in Slovenia and the uncertainty of ECMWF predicted precipitation is very large for Slovenian territory. ECMWF model can predict precipitation events correctly, but underestimates amount of precipitation in general The average underestimation is about 60% for Slovenian region. The predictions of limited area ALADIN/Si model up to; 48 hours ahead show greater applicability in hydrological forecasting. The hydrological models are sensitive to precipitation input. The deviation of runoff is much bigger than the rainfall deviation. Runoff to rainfall error fraction is about 1.6. If spatial and time distribution

Progress in space weather predictions and applications

Science.gov (United States)

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.

Model Uncertainty Quantification Methods In Data Assimilation

Science.gov (United States)

Pathiraja, S. D.; Marshall, L. A.; Sharma, A.; Moradkhani, H.

2017-12-01

Data Assimilation involves utilising observations to improve model predictions in a seamless and statistically optimal fashion. Its applications are wide-ranging; from improving weather forecasts to tracking targets such as in the Apollo 11 mission. The use of Data Assimilation methods in high dimensional complex geophysical systems is an active area of research, where there exists many opportunities to enhance existing methodologies. One of the central challenges is in model uncertainty quantification; the outcome of any Data Assimilation study is strongly dependent on the uncertainties assigned to both observations and models. I focus on developing improved model uncertainty quantification methods that are applicable to challenging real world scenarios. These include developing methods for cases where the system states are only partially observed, where there is little prior knowledge of the model errors, and where the model error statistics are likely to be highly non-Gaussian.

Assessing uncertainty in high-resolution spatial climate data across the US Northeast.

Science.gov (United States)

Bishop, Daniel A; Beier, Colin M

2013-01-01

Local and regional-scale knowledge of climate change is needed to model ecosystem responses, assess vulnerabilities and devise effective adaptation strategies. High-resolution gridded historical climate (GHC) products address this need, but come with multiple sources of uncertainty that are typically not well understood by data users. To better understand this uncertainty in a region with a complex climatology, we conducted a ground-truthing analysis of two 4 km GHC temperature products (PRISM and NRCC) for the US Northeast using 51 Cooperative Network (COOP) weather stations utilized by both GHC products. We estimated GHC prediction error for monthly temperature means and trends (1980-2009) across the US Northeast and evaluated any landscape effects (e.g., elevation, distance from coast) on those prediction errors. Results indicated that station-based prediction errors for the two GHC products were similar in magnitude, but on average, the NRCC product predicted cooler than observed temperature means and trends, while PRISM was cooler for means and warmer for trends. We found no evidence for systematic sources of uncertainty across the US Northeast, although errors were largest at high elevations. Errors in the coarse-scale (4 km) digital elevation models used by each product were correlated with temperature prediction errors, more so for NRCC than PRISM. In summary, uncertainty in spatial climate data has many sources and we recommend that data users develop an understanding of uncertainty at the appropriate scales for their purposes. To this end, we demonstrate a simple method for utilizing weather stations to assess local GHC uncertainty and inform decisions among alternative GHC products.

Uncertainty and Climate Change

OpenAIRE

Berliner, L. Mark

2003-01-01

Anthropogenic, or human-induced, climate change is a critical issue in science and in the affairs of humankind. Though the target of substantial research, the conclusions of climate change studies remain subject to numerous uncertainties. This article presents a very brief review of the basic arguments regarding anthropogenic climate change with particular emphasis on uncertainty.

Quantifying statistical uncertainty in the attribution of human influence on severe weather

OpenAIRE

Paciorek, CJ; Stone, DA; Wehner, MF

2018-01-01

© 2018 The Authors Event attribution in the context of climate change seeks to understand the role of anthropogenic greenhouse gas emissions on extreme weather events, either specific events or classes of events. A common approach to event attribution uses climate model output under factual (real-world) and counterfactual (world that might have been without anthropogenic greenhouse gas emissions) scenarios to estimate the probabilities of the event of interest under the two scenarios. Event a...

A study on the weather sampling method for probabilistic consequence analysis

International Nuclear Information System (INIS)

Oh, Hae Cheol

1996-02-01

The main task of probabilistic accident consequence analysis model is to predict the radiological situation and to provide a reliable quantitative data base for making decisions on countermeasures. The magnitude of accident consequence is depended on the characteristic of the accident and the weather coincident. In probabilistic accident consequence analysis, it is necessary to repeat the atmospheric dispersion calculation with several hundreds of weather sequences to predict the full distribution of consequences which may occur following a postulated accident release. It is desirable to select a representative sample of weather sequences from a meteorological record which is typical of the area over which the released radionuclides will disperse and which spans a sufficiently long period. The selection process is done by means of sampling techniques from a full year of hourly weather data characteristic of the plant site. In this study, the proposed Weighted importance sampling method selects proportional to the each bin size to closely approximate the true frequency distribution of weather condition at the site. The Weighted importance sampling method results in substantially less sampling uncertainty than the previous technique. The proposed technique can result in improve confidence in risk estimates

Aerosols and their Impact on Radiation, Clouds, Precipitation & Severe Weather Events

Energy Technology Data Exchange (ETDEWEB)

Li, Zhanqing; Rosenfeld, Daniel; Fan, Jiwen

2017-09-22

Aerosols, the tiny particles suspended in the atmosphere, have been in the forefront of environmental and climate change sciences as the primary atmospheric pollutant and external force affecting Earth’s weather and climate. There are two dominant mechanisms by which aerosols affect weather and climate: aerosol-radiation interactions (ARI) and aerosol-cloud interactions (ACI). ARI arises from aerosol scattering and absorption, which alters the radiation budgets of the atmosphere and surface, while ACI is rooted to the fact that aerosols serve as cloud condensation nuclei and ice nuclei. Both ARI and ACI are coupled with atmospheric dynamics to produce a chain of complex interactions with a large range of meteorological variables that influence both weather and climate. Elaborated here are the impacts of aerosols on the radiation budget, clouds (microphysics, structure, and lifetime), precipitation, and severe weather events (lightning, thunderstorms, hail, and tornados). Depending on environmental variables and aerosol properties, the effects can be both positive and negative, posing the largest uncertainties in the external forcing of the climate system. This has considerably hindered our ability in projecting future climate changes and in doing accurate numerical weather predictions.

Weather derivatives: Business hedge instrument from weather risks

Directory of Open Access Journals (Sweden)

Đorđević Bojan S.

2014-01-01

Full Text Available In the late 1990s, a new financial market was developed - a market for weather derivatives, so that the risk managers could hedge their exposure to weather risk. After a rather slow start, the weather derivatives market had started to grow rapidly. Risk managers could no longer blame poor financial results on the weather. Weather risk could now be removed by hedging procedure. This paper will explain briefly what the weather derivatives are and will point out at some of the motives for use of derivatives. Thereafter we will look at the history of the weather risk market, how the weather derivatives market has developed in recent years and also who are the current and potential players in the weather derivatives market.

Impacts of uncertainties in weather and streamflow observations in calibration and evaluation of an elevation distributed HBV-model

Science.gov (United States)

Engeland, K.; Steinsland, I.; Petersen-Øverleir, A.; Johansen, S.

2012-04-01

The aim of this study is to assess the uncertainties in streamflow simulations when uncertainties in both observed inputs (precipitation and temperature) and streamflow observations used in the calibration of the hydrological model are explicitly accounted for. To achieve this goal we applied the elevation distributed HBV model operating on daily time steps to a small catchment in high elevation in Southern Norway where the seasonal snow cover is important. The uncertainties in precipitation inputs were quantified using conditional simulation. This procedure accounts for the uncertainty related to the density of the precipitation network, but neglects uncertainties related to measurement bias/errors and eventual elevation gradients in precipitation. The uncertainties in temperature inputs were quantified using a Bayesian temperature interpolation procedure where the temperature lapse rate is re-estimated every day. The uncertainty in the lapse rate was accounted for whereas the sampling uncertainty related to network density was neglected. For every day a random sample of precipitation and temperature inputs were drawn to be applied as inputs to the hydrologic model. The uncertainties in observed streamflow were assessed based on the uncertainties in the rating curve model. A Bayesian procedure was applied to estimate the probability for rating curve models with 1 to 3 segments and the uncertainties in their parameters. This method neglects uncertainties related to errors in observed water levels. Note that one rating curve was drawn to make one realisation of a whole time series of streamflow, thus the rating curve errors lead to a systematic bias in the streamflow observations. All these uncertainty sources were linked together in both calibration and evaluation of the hydrologic model using a DREAM based MCMC routine. Effects of having less information (e.g. missing one streamflow measurement for defining the rating curve or missing one precipitation station

Post-Palaeozoic evolution of weathered landsurfaces in Uganda by tectonically controlled deep weathering and stripping

Science.gov (United States)

Taylor, R. G.; Howard, K. W. F.

1998-11-01

A model for the evolution of weathered landsurfaces in Uganda is developed using available geotectonic, climatic, sedimentological and chronological data. The model demonstrates the pivotal role of tectonic uplift in inducing cycles of stripping, and tectonic quiescence for cycles of deep weathering. It is able to account for the development of key landforms, such as inselbergs and duricrust-capped plateaux, which previous hypotheses of landscape evolution that are based on climatic or eustatic controls are unable to explain. Development of the Ugandan landscape is traced back to the Permian. Following late Palaeozoic glaciation, a trend towards warmer and more humid climates through the Mesozoic enabled deep weathering of the Jurassic/mid-Cretaceous surface in Uganda during a period of prolonged tectonic quiescence. Uplift associated with the opening South Atlantic Ocean terminated this cycle and instigated a cycle of stripping between the mid-Cretaceous and early Miocene. Deep weathering on the succeeding Miocene to recent (African) surface has occurred from Miocene to present but has been interrupted in the areas adjacent to the western rift where development of a new drainage base level has prompted cycles of stripping in the Miocene and Pleistocene.

Planning Under Uncertainty for Aggregated Electric Vehicle Charging with Renewable Energy Supply

NARCIS (Netherlands)

Walraven, E.M.P.; Spaan, M.T.J.; Kaminka, Gal A.; Fox, Maria; Bouquet, Paolo; Hüllermeier, Eyke; Dignum, Virginia; Dignum, Frank; van Harmelen, Frank

2016-01-01

Renewable energy sources introduce uncertainty regarding generated power in smart grids. For instance, power that is generated by wind turbines is time-varying and dependent on the weather. Electric vehicles will become increasingly important in the development of smart grids with a high penetration

Extremely Severe Space Weather and Geomagnetically Induced Currents in Regions with Locally Heterogeneous Ground Resistivity

Science.gov (United States)

Fujita, Shigeru; Kataoka, Ryuho; Pulkkinen, Antti; Watari, Shinichi

2016-01-01

Large geomagnetically induced currents (GICs) triggered by extreme space weather events are now regarded as one of the serious natural threats to the modern electrified society. The risk is described in detail in High-Impact, Low-Frequency Event Risk, A Jointly-Commissioned Summary Report of the North American Electric Reliability Corporation and the US Department of Energy's November 2009 Workshop, June 2010. For example, the March 13-14,1989 storm caused a large-scale blackout affecting about 6 million people in Quebec, Canada, and resulting in substantial economic losses in Canada and the USA (Bolduc 2002). Therefore, European and North American nations have invested in GIC research such as the Solar Shield project in the USA (Pulkkinen et al. 2009, 2015a). In 2015, the Japanese government (Ministry of Economy, Trade and Industry, METI) acknowledged the importance of GIC research in Japan. After reviewing the serious damages caused by the 2011 Tohoku-Oki earthquake, METI recognized the potential risk to the electric power grid posed by extreme space weather. During extreme events, GICs can be concerning even in mid- and low-latitude countries and have become a global issue.

Uncertainty analysis of accident notification time and emergency medical service response time in work zone traffic accidents.

Science.gov (United States)

Meng, Qiang; Weng, Jinxian

2013-01-01

Taking into account the uncertainty caused by exogenous factors, the accident notification time (ANT) and emergency medical service (EMS) response time were modeled as 2 random variables following the lognormal distribution. Their mean values and standard deviations were respectively formulated as the functions of environmental variables including crash time, road type, weekend, holiday, light condition, weather, and work zone type. Work zone traffic accident data from the Fatality Analysis Report System between 2002 and 2009 were utilized to determine the distributions of the ANT and the EMS arrival time in the United States. A mixed logistic regression model, taking into account the uncertainty associated with the ANT and the EMS response time, was developed to estimate the risk of death. The results showed that the uncertainty of the ANT was primarily influenced by crash time and road type, whereas the uncertainty of EMS response time is greatly affected by road type, weather, and light conditions. In addition, work zone accidents occurring during a holiday and in poor light conditions were found to be statistically associated with a longer mean ANT and longer EMS response time. The results also show that shortening the ANT was a more effective approach in reducing the risk of death than the EMS response time in work zones. To shorten the ANT and the EMS response time, work zone activities are suggested to be undertaken during non-holidays, during the daytime, and in good weather and light conditions.

Oil price uncertainty in Canada

Energy Technology Data Exchange (ETDEWEB)

Elder, John [Department of Finance and Real Estate, 1272 Campus Delivery, Colorado State University, Fort Collins, CO 80523 (United States); Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alberta (Canada)

2009-11-15

Bernanke [Bernanke, Ben S. Irreversibility, uncertainty, and cyclical investment. Quarterly Journal of Economics 98 (1983), 85-106.] shows how uncertainty about energy prices may induce optimizing firms to postpone investment decisions, thereby leading to a decline in aggregate output. Elder and Serletis [Elder, John and Serletis, Apostolos. Oil price uncertainty.] find empirical evidence that uncertainty about oil prices has tended to depress investment in the United States. In this paper we assess the robustness of these results by investigating the effects of oil price uncertainty in Canada. Our results are remarkably similar to existing results for the United States, providing additional evidence that uncertainty about oil prices may provide another explanation for why the sharp oil price declines of 1985 failed to produce rapid output growth. Impulse-response analysis suggests that uncertainty about oil prices may tend to reinforce the negative response of output to positive oil shocks. (author)

Understanding the weather signal in national crop-yield variability

Science.gov (United States)

Frieler, Katja; Schauberger, Bernhard; Arneth, Almut; Balkovič, Juraj; Chryssanthacopoulos, James; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Khabarov, Nikolay; Müller, Christoph; Olin, Stefan; Pugh, Thomas A. M.; Schaphoff, Sibyll; Schewe, Jacob; Schmid, Erwin; Warszawski, Lila; Levermann, Anders

2017-06-01

Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

Assessing the impact of a solar eclipse on weather and photovoltaic production

Directory of Open Access Journals (Sweden)

Carmen Köhler

2016-02-01

Full Text Available With the strong expansion of the installed renewable energy over the last years, the relevance of weather forecasts for operating the German power system has considerably increased. In that context, rare but important events like the solar eclipse on the morning of 20 March 2015 pose an additional challenge when operating the power system, as it affects the photovoltaic (PV power production by inducing strong gradients in the feed-in. In order to maintain grid stability, the uncertainties associated with the eclipse have been estimated in advance for planning necessary precautions. Especially the maximum gradients in PV-power were of importance for the provision of balancing energy. Numerical weather prediction (NWP is very suited for this assessment, as it allows to consider the complex mechanisms occurring in the atmosphere. Thus the impact of the eclipse on meteorological parameters which affect the PV-power generation were evaluated. Sensitivity studies with NWP models have been conducted in order to assess the reduction in short wave radiation and temperature during the total solar eclipse months before the actual event. For this purpose, model simulations with the non-hydrostatic COSMO models from the German Weather Service (DWD have been performed over Germany and Europe. As the weather situation and especially the cloud cover during the eclipse could not be known in advance, a realistic worst case (clear sky conditions and a best case (overcast conditions scenario were simulated over Germany. Thereof the PV-power production has been estimated and analyzed for the different scenarios. The NWP model data from the sensitivity studies are openly distributed (doi:10.1594/PANGAEA.839163. As near real-time NWP simulations considering the solar eclipse were conducted a few days prior to the event, they are herein validated with measurements. Furthermore, the actual PV-power production and actions taken by the TSOs during the solar eclipse are

WEATHER INDEX- THE BASIS OF WEATHER DERIVATIVES

Directory of Open Access Journals (Sweden)

Botos Horia Mircea

2011-07-01

Full Text Available This paper approaches the subject of Weather Derivatives, more exactly their basic element the weather index. The weather index has two forms, the Heating Degree Day (HDD and the Cooling Degree Day (CDD. We will try to explain their origin, use and the relationship between the two forms of the index. In our research we started from the analysis of the weather derivatives and what they are based on. After finding out about weather index, we were interested in understanding exactly how they work and how they influence the value of the contract. On the national level the research in the field is scares, but foreign materials available. The study for this paper was based firstly on reading about Weather Derivative, and then going in the meteorogical field and determining the way by which the indices were determined. After this, we went to the field with interest in the indices, such as the energy and gas industries, and figured out how they determined the weather index. For the examples we obtained data from the weather index database, and calculated the value for the period. The study is made on a period of five years, in 8 cities of the European Union. The result of this research is that we can now understand better the importance of the way the indices work and how they influence the value of the Weather Derivatives. This research has an implication on the field of insurance, because of the fact that weather derivative are at the convergence point of the stock markets and the insurance market. The originality of the paper comes from the personal touch given to the theoretical aspect and through the analysis of the HDD and CDD index in order to show their general behaviour and relationship.

Uncertainties in the estimation of specific absorption rate during radiofrequency alternating magnetic field induced non-adiabatic heating of ferrofluids

Science.gov (United States)

Lahiri, B. B.; Ranoo, Surojit; Philip, John

2017-11-01

Magnetic fluid hyperthermia (MFH) is becoming a viable cancer treatment methodology where the alternating magnetic field induced heating of magnetic fluid is utilized for ablating the cancerous cells or making them more susceptible to the conventional treatments. The heating efficiency in MFH is quantified in terms of specific absorption rate (SAR), which is defined as the heating power generated per unit mass. In majority of the experimental studies, SAR is evaluated from the temperature rise curves, obtained under non-adiabatic experimental conditions, which is prone to various thermodynamic uncertainties. A proper understanding of the experimental uncertainties and its remedies is a prerequisite for obtaining accurate and reproducible SAR. Here, we study the thermodynamic uncertainties associated with peripheral heating, delayed heating, heat loss from the sample and spatial variation in the temperature profile within the sample. Using first order approximations, an adiabatic reconstruction protocol for the measured temperature rise curves is developed for SAR estimation, which is found to be in good agreement with those obtained from the computationally intense slope corrected method. Our experimental findings clearly show that the peripheral and delayed heating are due to radiation heat transfer from the heating coils and slower response time of the sensor, respectively. Our results suggest that the peripheral heating is linearly proportional to the sample area to volume ratio and coil temperature. It is also observed that peripheral heating decreases in presence of a non-magnetic insulating shielding. The delayed heating is found to contribute up to ~25% uncertainties in SAR values. As the SAR values are very sensitive to the initial slope determination method, explicit mention of the range of linear regression analysis is appropriate to reproduce the results. The effect of sample volume to area ratio on linear heat loss rate is systematically studied and the

Uncertainties in the estimation of specific absorption rate during radiofrequency alternating magnetic field induced non-adiabatic heating of ferrofluids

International Nuclear Information System (INIS)

Lahiri, B B; Ranoo, Surojit; Philip, John

2017-01-01

Magnetic fluid hyperthermia (MFH) is becoming a viable cancer treatment methodology where the alternating magnetic field induced heating of magnetic fluid is utilized for ablating the cancerous cells or making them more susceptible to the conventional treatments. The heating efficiency in MFH is quantified in terms of specific absorption rate (SAR), which is defined as the heating power generated per unit mass. In majority of the experimental studies, SAR is evaluated from the temperature rise curves, obtained under non-adiabatic experimental conditions, which is prone to various thermodynamic uncertainties. A proper understanding of the experimental uncertainties and its remedies is a prerequisite for obtaining accurate and reproducible SAR. Here, we study the thermodynamic uncertainties associated with peripheral heating, delayed heating, heat loss from the sample and spatial variation in the temperature profile within the sample. Using first order approximations, an adiabatic reconstruction protocol for the measured temperature rise curves is developed for SAR estimation, which is found to be in good agreement with those obtained from the computationally intense slope corrected method. Our experimental findings clearly show that the peripheral and delayed heating are due to radiation heat transfer from the heating coils and slower response time of the sensor, respectively. Our results suggest that the peripheral heating is linearly proportional to the sample area to volume ratio and coil temperature. It is also observed that peripheral heating decreases in presence of a non-magnetic insulating shielding. The delayed heating is found to contribute up to ∼25% uncertainties in SAR values. As the SAR values are very sensitive to the initial slope determination method, explicit mention of the range of linear regression analysis is appropriate to reproduce the results. The effect of sample volume to area ratio on linear heat loss rate is systematically studied and

Probabilistic Harmonic Analysis on Distributed Photovoltaic Integration Considering Typical Weather Scenarios

Science.gov (United States)

Bin, Che; Ruoying, Yu; Dongsheng, Dang; Xiangyan, Wang

2017-05-01

Distributed Generation (DG) integrating to the network would cause the harmonic pollution which would cause damages on electrical devices and affect the normal operation of power system. On the other hand, due to the randomness of the wind and solar irradiation, the output of DG is random, too, which leads to an uncertainty of the harmonic generated by the DG. Thus, probabilistic methods are needed to analyse the impacts of the DG integration. In this work we studied the harmonic voltage probabilistic distribution and the harmonic distortion in distributed network after the distributed photovoltaic (DPV) system integrating in different weather conditions, mainly the sunny day, cloudy day, rainy day and the snowy day. The probabilistic distribution function of the DPV output power in different typical weather conditions could be acquired via the parameter identification method of maximum likelihood estimation. The Monte-Carlo simulation method was adopted to calculate the probabilistic distribution of harmonic voltage content at different frequency orders as well as the harmonic distortion (THD) in typical weather conditions. The case study was based on the IEEE33 system and the results of harmonic voltage content probabilistic distribution as well as THD in typical weather conditions were compared.

Water geochemistry of the Xijiang basin rivers, South China: Chemical weathering and CO2 consumption

International Nuclear Information System (INIS)

Xu Zhifang; Liu Congqiang

2010-01-01

Research highlights: → The Xijiang River is the second largest river in China and flows through a large carbonate rock region in South China. → Sulfuric acid, which emanate from acid precipitation and the oxidation of sulfide minerals, is involved as a proton donor in weathering reactions in the Xijiang basin. → Calculated results show that the contribution of cations from rock weathering induced by sulfuric acid accounts for approximately 11.2%. → The flux of CO 2 released into the atmosphere is approximately 0.41 x 10 12 gC yr -1 produced by sulfuric acid-induced carbonate weathering in the Xijiang basin. → Sulfuric acid-induced carbonate weathering could counterbalance a significant part of the CO 2 consumed by silicate weathering. - Abstract: The Xijiang River, the mainstream of the Zhujiang (Pearl) River, which is the second largest river in China in terms of discharge, flows through a large carbonate rock region in South China. The chemical and Sr isotopic compositions of the Xijiang waters were determined during the high-flow season in order to understand the chemical weathering processes, associated CO 2 consumption and anthropogenic influences within the carbonate-dominated basin. The major ion compositions of the river waters are characterized by the dominance of Ca 2+ , Mg 2+ , HCO 3 - and are significantly rich in SO 4 2- . The SO 4 2- is mainly derived from the oxidation of sulfide minerals and acid precipitation caused by coal combustion. Chemical and Sr isotopic compositions of the river waters indicate that four reservoirs (carbonates, silicates, evaporites and anthropogenic inputs) contribute to the total dissolved loads. The chemical weathering rates of carbonates and silicates for the Xijiang basin are estimated to be approximately 78.5 and 7.45 ton km -2 a -1 , respectively. The total chemical weathering rate of rocks for the Xijiang basin is approximately 86.1 ton km -2 a -1 or 42 mm ka -1 , which is much higher than global mean

Regional climate change trends and uncertainty analysis using extreme indices: A case study of Hamilton, Canada

OpenAIRE

Razavi, Tara; Switzman, Harris; Arain, Altaf; Coulibaly, Paulin

2016-01-01

This study aims to provide a deeper understanding of the level of uncertainty associated with the development of extreme weather frequency and intensity indices at the local scale. Several different global climate models, downscaling methods, and emission scenarios were used to develop extreme temperature and precipitation indices at the local scale in the Hamilton region, Ontario, Canada. Uncertainty associated with historical and future trends in extreme indices and future climate projectio...

Modeling extreme "Carrington-type" space weather events using three-dimensional global MHD simulations

Science.gov (United States)

Ngwira, Chigomezyo M.; Pulkkinen, Antti; Kuznetsova, Maria M.; Glocer, Alex

2014-06-01

There is a growing concern over possible severe societal consequences related to adverse space weather impacts on man-made technological infrastructure. In the last two decades, significant progress has been made toward the first-principles modeling of space weather events, and three-dimensional (3-D) global magnetohydrodynamics (MHD) models have been at the forefront of this transition, thereby playing a critical role in advancing our understanding of space weather. However, the modeling of extreme space weather events is still a major challenge even for the modern global MHD models. In this study, we introduce a specially adapted University of Michigan 3-D global MHD model for simulating extreme space weather events with a Dst footprint comparable to the Carrington superstorm of September 1859 based on the estimate by Tsurutani et. al. (2003). Results are presented for a simulation run with "very extreme" constructed/idealized solar wind boundary conditions driving the magnetosphere. In particular, we describe the reaction of the magnetosphere-ionosphere system and the associated induced geoelectric field on the ground to such extreme driving conditions. The model setup is further tested using input data for an observed space weather event of Halloween storm October 2003 to verify the MHD model consistence and to draw additional guidance for future work. This extreme space weather MHD model setup is designed specifically for practical application to the modeling of extreme geomagnetically induced electric fields, which can drive large currents in ground-based conductor systems such as power transmission grids. Therefore, our ultimate goal is to explore the level of geoelectric fields that can be induced from an assumed storm of the reported magnitude, i.e., Dst˜=-1600 nT.

Uncertainty, joint uncertainty, and the quantum uncertainty principle

International Nuclear Information System (INIS)

Narasimhachar, Varun; Poostindouz, Alireza; Gour, Gilad

2016-01-01

Historically, the element of uncertainty in quantum mechanics has been expressed through mathematical identities called uncertainty relations, a great many of which continue to be discovered. These relations use diverse measures to quantify uncertainty (and joint uncertainty). In this paper we use operational information-theoretic principles to identify the common essence of all such measures, thereby defining measure-independent notions of uncertainty and joint uncertainty. We find that most existing entropic uncertainty relations use measures of joint uncertainty that yield themselves to a small class of operational interpretations. Our notion relaxes this restriction, revealing previously unexplored joint uncertainty measures. To illustrate the utility of our formalism, we derive an uncertainty relation based on one such new measure. We also use our formalism to gain insight into the conditions under which measure-independent uncertainty relations can be found. (paper)

Probabilistic Space Weather Forecasting: a Bayesian Perspective

Science.gov (United States)

Camporeale, E.; Chandorkar, M.; Borovsky, J.; Care', A.

2017-12-01

Most of the Space Weather forecasts, both at operational and research level, are not probabilistic in nature. Unfortunately, a prediction that does not provide a confidence level is not very useful in a decision-making scenario. Nowadays, forecast models range from purely data-driven, machine learning algorithms, to physics-based approximation of first-principle equations (and everything that sits in between). Uncertainties pervade all such models, at every level: from the raw data to finite-precision implementation of numerical methods. The most rigorous way of quantifying the propagation of uncertainties is by embracing a Bayesian probabilistic approach. One of the simplest and most robust machine learning technique in the Bayesian framework is Gaussian Process regression and classification. Here, we present the application of Gaussian Processes to the problems of the DST geomagnetic index forecast, the solar wind type classification, and the estimation of diffusion parameters in radiation belt modeling. In each of these very diverse problems, the GP approach rigorously provide forecasts in the form of predictive distributions. In turn, these distributions can be used as input for ensemble simulations in order to quantify the amplification of uncertainties. We show that we have achieved excellent results in all of the standard metrics to evaluate our models, with very modest computational cost.

Expanded and combined uncertainty in measurements by GM counters

International Nuclear Information System (INIS)

Stankovic, K.; Arandjic, D.; Lazarevic, Dj.; Osmokrovic, P.

2007-01-01

This paper deals with possible ways of obtaining expanded and combined uncertainty in measurements for four types of GM counters with a same counter's tube, in cases when the contributors of these uncertainties are cosmic background radiation and induced overvoltage phenomena. Nowadays, as a consequence of electromagnetic radiation, the latter phenomenon is especially marked in urban environments. Based on experimental results obtained, it has been established that the uncertainties of an influenced random variable 'number of pulses from background radiation' and 'number of pulses induced by overvoltage' depend on the technological solution of the counter's reading system and contribute in different ways to the expanded and combined uncertainty in measurements of the applied types of GM counters. (author)

Wave-optics uncertainty propagation and regression-based bias model in GNSS radio occultation bending angle retrievals

Directory of Open Access Journals (Sweden)

M. E. Gorbunov

2018-01-01

Full Text Available A new reference occultation processing system (rOPS will include a Global Navigation Satellite System (GNSS radio occultation (RO retrieval chain with integrated uncertainty propagation. In this paper, we focus on wave-optics bending angle (BA retrieval in the lower troposphere and introduce (1 an empirically estimated boundary layer bias (BLB model then employed to reduce the systematic uncertainty of excess phases and bending angles in about the lowest 2 km of the troposphere and (2 the estimation of (residual systematic uncertainties and their propagation together with random uncertainties from excess phase to bending angle profiles. Our BLB model describes the estimated bias of the excess phase transferred from the estimated bias of the bending angle, for which the model is built, informed by analyzing refractivity fluctuation statistics shown to induce such biases. The model is derived from regression analysis using a large ensemble of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC RO observations and concurrent European Centre for Medium-Range Weather Forecasts (ECMWF analysis fields. It is formulated in terms of predictors and adaptive functions (powers and cross products of predictors, where we use six main predictors derived from observations: impact altitude, latitude, bending angle and its standard deviation, canonical transform (CT amplitude, and its fluctuation index. Based on an ensemble of test days, independent of the days of data used for the regression analysis to establish the BLB model, we find the model very effective for bias reduction and capable of reducing bending angle and corresponding refractivity biases by about a factor of 5. The estimated residual systematic uncertainty, after the BLB profile subtraction, is lower bounded by the uncertainty from the (indirect use of ECMWF analysis fields but is significantly lower than the systematic uncertainty without BLB correction. The

Wave-optics uncertainty propagation and regression-based bias model in GNSS radio occultation bending angle retrievals

Science.gov (United States)

Gorbunov, Michael E.; Kirchengast, Gottfried

2018-01-01

A new reference occultation processing system (rOPS) will include a Global Navigation Satellite System (GNSS) radio occultation (RO) retrieval chain with integrated uncertainty propagation. In this paper, we focus on wave-optics bending angle (BA) retrieval in the lower troposphere and introduce (1) an empirically estimated boundary layer bias (BLB) model then employed to reduce the systematic uncertainty of excess phases and bending angles in about the lowest 2 km of the troposphere and (2) the estimation of (residual) systematic uncertainties and their propagation together with random uncertainties from excess phase to bending angle profiles. Our BLB model describes the estimated bias of the excess phase transferred from the estimated bias of the bending angle, for which the model is built, informed by analyzing refractivity fluctuation statistics shown to induce such biases. The model is derived from regression analysis using a large ensemble of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) RO observations and concurrent European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields. It is formulated in terms of predictors and adaptive functions (powers and cross products of predictors), where we use six main predictors derived from observations: impact altitude, latitude, bending angle and its standard deviation, canonical transform (CT) amplitude, and its fluctuation index. Based on an ensemble of test days, independent of the days of data used for the regression analysis to establish the BLB model, we find the model very effective for bias reduction and capable of reducing bending angle and corresponding refractivity biases by about a factor of 5. The estimated residual systematic uncertainty, after the BLB profile subtraction, is lower bounded by the uncertainty from the (indirect) use of ECMWF analysis fields but is significantly lower than the systematic uncertainty without BLB correction. The systematic and

Structure of, access to and uncertainty in reasoning and their dependence on content

NARCIS (Netherlands)

Vos, Henk; et al Mason, L.

2003-01-01

It is known that content has an effect on reasoning. In this paper the influence of the content on the structure of reasoning, the access to it, and the ability to handle uncertainty was studied. The participants were presented with reasoning tasks about the weather and about the oscilloscope in

Decision making under uncertainty: Recommendations for the Wildland Fire Decision Support System (WFDSS)

Science.gov (United States)

Matthew P. Thompson

2015-01-01

The management of wildfire is a dynamic, complex, and fundamentally uncertain enterprise. Fire managers face uncertainties regarding fire weather and subsequent influence on fire behavior, the effects of fire on socioeconomic and ecological resources, and the efficacy of alternative suppression actions on fire outcomes. In these types of difficult decision environments...

Municipalities' Preparedness for Weather Hazards and Response to Weather Warnings.

Science.gov (United States)

Mehiriz, Kaddour; Gosselin, Pierre

2016-01-01

The study of the management of weather-related disaster risks by municipalities has attracted little attention even though these organizations play a key role in protecting the population from extreme meteorological conditions. This article contributes to filling this gap with new evidence on the level and determinants of Quebec municipalities' preparedness for weather hazards and response to related weather warnings. Using survey data from municipal emergency management coordinators and secondary data on the financial and demographic characteristics of municipalities, the study shows that most Quebec municipalities are sufficiently prepared for weather hazards and undertake measures to protect the population when informed of imminent extreme weather events. Significant differences between municipalities were noted though. Specifically, the level of preparedness was positively correlated with the municipalities' capacity and population support for weather-related disaster management policies. In addition, the risk of weather-related disasters increases the preparedness level through its effect on population support. We also found that the response to weather warnings depended on the risk of weather-related disasters, the preparedness level and the quality of weather warnings. These results highlight areas for improvement in the context of increasing frequency and/or severity of such events with current climate change.

National Weather Service

Science.gov (United States)

... GIS International Weather Cooperative Observers Storm Spotters Tsunami Facts and Figures National Water Center WEATHER SAFETY NOAA Weather Radio StormReady Heat Lightning Hurricanes Thunderstorms Tornadoes Rip Currents Floods Winter Weather ...

Uncertainty and sensitivity analysis of environmental transport models

International Nuclear Information System (INIS)

Margulies, T.S.; Lancaster, L.E.

1985-01-01

An uncertainty and sensitivity analysis has been made of the CRAC-2 (Calculations of Reactor Accident Consequences) atmospheric transport and deposition models. Robustness and uncertainty aspects of air and ground deposited material and the relative contribution of input and model parameters were systematically studied. The underlying data structures were investigated using a multiway layout of factors over specified ranges generated via a Latin hypercube sampling scheme. The variables selected in our analysis include: weather bin, dry deposition velocity, rain washout coefficient/rain intensity, duration of release, heat content, sigma-z (vertical) plume dispersion parameter, sigma-y (crosswind) plume dispersion parameter, and mixing height. To determine the contributors to the output variability (versus distance from the site) step-wise regression analyses were performed on transformations of the spatial concentration patterns simulated. 27 references, 2 figures, 3 tables

Estimation of uncertainty of wind energy predictions with application to weather routing and wind power generation

CERN Document Server

Zastrau, David

2017-01-01

Wind drives in combination with weather routing can lower the fuel consumption of cargo ships significantly. For this reason, the author describes a mathematical method based on quantile regression for a probabilistic estimate of the wind propulsion force on a ship route.

Uncertainty in projected point precipitation extremes for hydrological impact analysis of climate change

Science.gov (United States)

Van Uytven, Els; Willems, Patrick

2017-04-01

Current trends in the hydro-meteorological variables indicate the potential impact of climate change on hydrological extremes. Therefore, they trigger an increased importance climate adaptation strategies in water management. The impact of climate change on hydro-meteorological and hydrological extremes is, however, highly uncertain. This is due to uncertainties introduced by the climate models, the internal variability inherent to the climate system, the greenhouse gas scenarios and the statistical downscaling methods. In view of the need to define sustainable climate adaptation strategies, there is a need to assess these uncertainties. This is commonly done by means of ensemble approaches. Because more and more climate models and statistical downscaling methods become available, there is a need to facilitate the climate impact and uncertainty analysis. A Climate Perturbation Tool has been developed for that purpose, which combines a set of statistical downscaling methods including weather typing, weather generator, transfer function and advanced perturbation based approaches. By use of an interactive interface, climate impact modelers can apply these statistical downscaling methods in a semi-automatic way to an ensemble of climate model runs. The tool is applicable to any region, but has been demonstrated so far to cases in Belgium, Suriname, Vietnam and Bangladesh. Time series representing future local-scale precipitation, temperature and potential evapotranspiration (PET) conditions were obtained, starting from time series of historical observations. Uncertainties on the future meteorological conditions are represented in two different ways: through an ensemble of time series, and a reduced set of synthetic scenarios. The both aim to span the full uncertainty range as assessed from the ensemble of climate model runs and downscaling methods. For Belgium, for instance, use was made of 100-year time series of 10-minutes precipitation observations and daily

Space Weather Studies at Istanbul Technical University

Science.gov (United States)

Kaymaz, Zerefsan

2016-07-01

This presentation will introduce the Upper Atmosphere and Space Weather Laboratory of Istanbul Technical University (ITU). It has been established to support the educational needs of the Faculty of Aeronautics and Astronautics in 2011 to conduct scientific research in Space Weather, Space Environment, Space Environment-Spacecraft Interactions, Space instrumentation and Upper Atmospheric studies. Currently the laboratory has some essential infrastructure and the most instrumentation for ionospheric observations and ground induced currents from the magnetosphere. The laboratory has two subunits: SWIFT dealing with Space Weather Instrumentation and Forecasting unit and SWDPA dealing with Space Weather Data Processing and Analysis. The research area covers wide range of upper atmospheric and space science studies from ionosphere, ionosphere-magnetosphere coupling, magnetic storms and magnetospheric substorms, distant magnetotail, magnetopause and bow shock studies, as well as solar and solar wind disturbances and their interaction with the Earth's space environment. We also study the spacecraft environment interaction and novel plasma instrument design. Several scientific projects have been carried out in the laboratory. Operational objectives of our laboratory will be carried out with the collaboration of NASA's Space Weather Laboratory and the facilities are in the process of integration to their prediction services. Educational and research objectives, as well as the examples from the research carried out in our laboratory will be demonstrated in this presentation.

Case report of cold-weather-induced radiation recall dermatitis after chemoradiotherapy with cisplatin

International Nuclear Information System (INIS)

Kindts, Isabelle; Stellamans, Karin; Planckaert, Nikie; Goethals, Laurence; Bonny, Michiel

2014-01-01

The radiation recall reaction (RRR) is an inflammatory reaction that occurs in previously irradiated areas. The phenomenon is probably due to an idiosyncratic hypersensitivity reaction, in which a second agent can recall the inflammatory reaction. This case report documents a cold-weather-induced radiation recall dermatitis (RRD). We observed a severe RRD in a patient after chemoradiotherapy treatment with cisplatin for a nasopharyngeal carcinoma, precipitated by cold temperatures, which developed 9 days after completion of therapy. In the medical literature, RRD following extreme cold temperatures seems to be a peculiar event. Until further information on the interaction is available, future studies on combined chemotherapy with cisplatin should be carefully monitored and any side effects clearly documented. This case suggests that environmental conditions may play a contributing role in the development of RRD. This case also implies that neither fraction size nor total radiation dose is a determining factor in the development of the dermatologic reaction. (orig.) [de

Modeling extreme (Carrington-type) space weather events using three-dimensional MHD code simulations

Science.gov (United States)

Ngwira, C. M.; Pulkkinen, A. A.; Kuznetsova, M. M.; Glocer, A.

2013-12-01

There is growing concern over possible severe societal consequences related to adverse space weather impacts on man-made technological infrastructure and systems. In the last two decades, significant progress has been made towards the modeling of space weather events. Three-dimensional (3-D) global magnetohydrodynamics (MHD) models have been at the forefront of this transition, and have played a critical role in advancing our understanding of space weather. However, the modeling of extreme space weather events is still a major challenge even for existing global MHD models. In this study, we introduce a specially adapted University of Michigan 3-D global MHD model for simulating extreme space weather events that have a ground footprint comparable (or larger) to the Carrington superstorm. Results are presented for an initial simulation run with ``very extreme'' constructed/idealized solar wind boundary conditions driving the magnetosphere. In particular, we describe the reaction of the magnetosphere-ionosphere system and the associated ground induced geoelectric field to such extreme driving conditions. We also discuss the results and what they might mean for the accuracy of the simulations. The model is further tested using input data for an observed space weather event to verify the MHD model consistence and to draw guidance for future work. This extreme space weather MHD model is designed specifically for practical application to the modeling of extreme geomagnetically induced electric fields, which can drive large currents in earth conductors such as power transmission grids.

Weathering of the New Albany Shale, Kentucky, USA: I. Weathering zones defined by mineralogy and major-element composition

Science.gov (United States)

Tuttle, M.L.W.; Breit, G.N.

2009-01-01

Comprehensive understanding of chemical and mineralogical changes induced by weathering is valuable information when considering the supply of nutrients and toxic elements from rocks. Here minerals that release and fix major elements during progressive weathering of a bed of Devonian New Albany Shale in eastern Kentucky are documented. Samples were collected from unweathered core (parent shale) and across an outcrop excavated into a hillside 40 year prior to sampling. Quantitative X-ray diffraction mineralogical data record progressive shale alteration across the outcrop. Mineral compositional changes reflect subtle alteration processes such as incongruent dissolution and cation exchange. Altered primary minerals include K-feldspars, plagioclase, calcite, pyrite, and chlorite. Secondary minerals include jarosite, gypsum, goethite, amorphous Fe(III) oxides and Fe(II)-Al sulfate salt (efflorescence). The mineralogy in weathered shale defines four weathered intervals on the outcrop-Zones A-C and soil. Alteration of the weakly weathered shale (Zone A) is attributed to the 40-a exposure of the shale. In this zone, pyrite oxidization produces acid that dissolves calcite and attacks chlorite, forming gypsum, jarosite, and minor efflorescent salt. The pre-excavation, active weathering front (Zone B) is where complete pyrite oxidation and alteration of feldspar and organic matter result in increased permeability. Acidic weathering solutions seep through the permeable shale and evaporate on the surface forming abundant efflorescent salt, jarosite and minor goethite. Intensely weathered shale (Zone C) is depleted in feldspars, chlorite, gypsum, jarosite and efflorescent salts, but has retained much of its primary quartz, illite and illite-smectite. Goethite and amorphous FE(III) oxides increase due to hydrolysis of jarosite. Enhanced permeability in this zone is due to a 14% loss of the original mass in parent shale. Denudation rates suggest that characteristics of Zone C

Decision aids for multiple-decision disease management as affected by weather input errors.

Science.gov (United States)

Pfender, W F; Gent, D H; Mahaffee, W F; Coop, L B; Fox, A D

2011-06-01

Many disease management decision support systems (DSSs) rely, exclusively or in part, on weather inputs to calculate an indicator for disease hazard. Error in the weather inputs, typically due to forecasting, interpolation, or estimation from off-site sources, may affect model calculations and management decision recommendations. The extent to which errors in weather inputs affect the quality of the final management outcome depends on a number of aspects of the disease management context, including whether management consists of a single dichotomous decision, or of a multi-decision process extending over the cropping season(s). Decision aids for multi-decision disease management typically are based on simple or complex algorithms of weather data which may be accumulated over several days or weeks. It is difficult to quantify accuracy of multi-decision DSSs due to temporally overlapping disease events, existence of more than one solution to optimizing the outcome, opportunities to take later recourse to modify earlier decisions, and the ongoing, complex decision process in which the DSS is only one component. One approach to assessing importance of weather input errors is to conduct an error analysis in which the DSS outcome from high-quality weather data is compared with that from weather data with various levels of bias and/or variance from the original data. We illustrate this analytical approach for two types of DSS, an infection risk index for hop powdery mildew and a simulation model for grass stem rust. Further exploration of analysis methods is needed to address problems associated with assessing uncertainty in multi-decision DSSs.

Using Weather Types to Understand and Communicate Weather and Climate Impacts

Science.gov (United States)

Prein, A. F.; Hale, B.; Holland, G. J.; Bruyere, C. L.; Done, J.; Mearns, L.

2017-12-01

A common challenge in atmospheric research is the translation of scientific advancements and breakthroughs to decision relevant and actionable information. This challenge is central to the mission of NCAR's Capacity Center for Climate and Weather Extremes (C3WE, www.c3we.ucar.edu). C3WE advances our understanding of weather and climate impacts and integrates these advances with distributed information technology to create tools that promote a global culture of resilience to weather and climate extremes. Here we will present an interactive web-based tool that connects historic U.S. losses and fatalities from extreme weather and climate events to 12 large-scale weather types. Weather types are dominant weather situations such as winter high-pressure systems over the U.S. leading to very cold temperatures or summertime moist humid air masses over the central U.S. leading to severe thunderstorms. Each weather type has a specific fingerprint of economic losses and fatalities in a region that is quantified. Therefore, weather types enable a direct connection of observed or forecasted weather situation to loss of life and property. The presented tool allows the user to explore these connections, raise awareness of existing vulnerabilities, and build resilience to weather and climate extremes.

Uncertainty of climate change impact on groundwater reserves - Application to a chalk aquifer

Science.gov (United States)

Goderniaux, Pascal; Brouyère, Serge; Wildemeersch, Samuel; Therrien, René; Dassargues, Alain

2015-09-01

Recent studies have evaluated the impact of climate change on groundwater resources for different geographical and climatic contexts. However, most studies have either not estimated the uncertainty around projected impacts or have limited the analysis to the uncertainty related to climate models. In this study, the uncertainties around impact projections from several sources (climate models, natural variability of the weather, hydrological model calibration) are calculated and compared for the Geer catchment (465 km2) in Belgium. We use a surface-subsurface integrated model implemented using the finite element code HydroGeoSphere, coupled with climate change scenarios (2010-2085) and the UCODE_2005 inverse model, to assess the uncertainty related to the calibration of the hydrological model. This integrated model provides a more realistic representation of the water exchanges between surface and subsurface domains and constrains more the calibration with the use of both surface and subsurface observed data. Sensitivity and uncertainty analyses were performed on predictions. The linear uncertainty analysis is approximate for this nonlinear system, but it provides some measure of uncertainty for computationally demanding models. Results show that, for the Geer catchment, the most important uncertainty is related to calibration of the hydrological model. The total uncertainty associated with the prediction of groundwater levels remains large. By the end of the century, however, the uncertainty becomes smaller than the predicted decline in groundwater levels.

Surface Weather, Signal Service and Weather Bureau

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Surface Weather, Signal Service and Weather Bureau (SWSSWB) Records primarily created by the United States Army Signal Service from 1819 until the paid and voluntary...

Climate change and global crop yield: impacts, uncertainties and adaptation

OpenAIRE

Deryng, Delphine

2014-01-01

As global mean temperature continues to rise steadily, agricultural systems are projected to face unprecedented challenges to cope with climate change. However, understanding of climate change impacts on global crop yield, and of farmers’ adaptive capacity, remains incomplete as previous global assessments: (1) inadequately evaluated the role of extreme weather events; (2) focused on a small subset of the full range of climate change predictions; (3) overlooked uncertainties related to the ch...

Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

Science.gov (United States)

Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

2015-04-01

Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations

Elemental and mineralogical imaging of a weathered limestone rock by double-pulse micro-Laser-Induced Breakdown Spectroscopy

Science.gov (United States)

Senesi, Giorgio S.; Campanella, Beatrice; Grifoni, Emanuela; Legnaioli, Stefano; Lorenzetti, Giulia; Pagnotta, Stefano; Poggialini, Francesco; Palleschi, Vincenzo; De Pascale, Olga

2018-05-01

The present work aims to evaluate the alteration conditions of historical limestone rocks exposed to urban environment using the Laser-Induced Breakdown Spectroscopy (LIBS) technique. The approach proposed is based on the microscale three dimensional (3D) compositional imaging of the sample through double-pulse micro-Laser-Induced Breakdown Spectroscopy (DP-μLIBS) in conjunction with optical microscopy. DP-μLIBS allows to perform a quick and detailed in-depth analysis of the composition of the weathered artifact by creating a 'virtual thin section' (VTS) of the sample which can estimate the extent of the alteration processes occurred at the limestone surface. The DP-μLIBS analysis of these thin sections showed a reduction with depth of the elements (mainly Fe, Si and Na) originating from atmospheric dust, particulate deposition and the surrounding environment (due to the proximity of the sea), whereas, the LIBS signal of Ca increased in intensity from the black crust to the limestone underneath.

Probabilistic forecasting of shallow, rainfall-triggered landslides using real-time numerical weather predictions

Directory of Open Access Journals (Sweden)

J. Schmidt

2008-04-01

Full Text Available A project established at the National Institute of Water and Atmospheric Research (NIWA in New Zealand is aimed at developing a prototype of a real-time landslide forecasting system. The objective is to predict temporal changes in landslide probability for shallow, rainfall-triggered landslides, based on quantitative weather forecasts from numerical weather prediction models. Global weather forecasts from the United Kingdom Met Office (MO Numerical Weather Prediction model (NWP are coupled with a regional data assimilating NWP model (New Zealand Limited Area Model, NZLAM to forecast atmospheric variables such as precipitation and temperature up to 48 h ahead for all of New Zealand. The weather forecasts are fed into a hydrologic model to predict development of soil moisture and groundwater levels. The forecasted catchment-scale patterns in soil moisture and soil saturation are then downscaled using topographic indices to predict soil moisture status at the local scale, and an infinite slope stability model is applied to determine the triggering soil water threshold at a local scale. The model uses uncertainty of soil parameters to produce probabilistic forecasts of spatio-temporal landslide occurrence 48~h ahead. The system was evaluated for a damaging landslide event in New Zealand. Comparison with landslide densities estimated from satellite imagery resulted in hit rates of 70–90%.

Weather swap as an instrument for weather risk management in wheat production

Directory of Open Access Journals (Sweden)

Marković Todor

2012-01-01

Full Text Available A special type of weather derivatives are weather forwards and they exists mostly in the form of weather swaps. Hedging effectiveness in wheat production with and without weather swap was analyzed in this paper using stochastic dominance. The results show that the effect of risk reduction is significant using weather swap, but geographical- basis risk and production-related basis risk are important factor that reduce the utility of weather derivatives.

Improved Wave-vessel Transfer Functions by Uncertainty Modelling

DEFF Research Database (Denmark)

Nielsen, Ulrik Dam; Fønss Bach, Kasper; Iseki, Toshio

2016-01-01

This paper deals with uncertainty modelling of wave-vessel transfer functions used to calculate or predict wave-induced responses of a ship in a seaway. Although transfer functions, in theory, can be calculated to exactly reflect the behaviour of the ship when exposed to waves, uncertainty in inp...

Weathering and landscape evolution

Science.gov (United States)

Turkington, Alice V.; Phillips, Jonathan D.; Campbell, Sean W.

2005-04-01

In recognition of the fundamental control exerted by weathering on landscape evolution and topographic development, the 35th Binghamton Geomorphology Symposium was convened under the theme of Weathering and Landscape Evolution. The papers and posters presented at the conference imparted the state-of-the-art in weathering geomorphology, tackled the issue of scale linkage in geomorphic studies and offered a vehicle for interdisciplinary communication on research into weathering and landscape evolution. The papers included in this special issue are encapsulated here under the general themes of weathering mantles, weathering and relative dating, weathering and denudation, weathering processes and controls and the 'big picture'.

Vulnerability and adaptation to severe weather events in the American southwest

OpenAIRE

Boero, Riccardo; Bianchini, Laura; Pasqualini, Donatella

2015-01-01

Climate change can induce changes in the frequency of severe weather events representing a threat to socio-economic development. It is thus of uttermost importance to understand how the vulnerability to the weather of local communities is determined and how adaptation public policies can be effectively put in place. We focused our empirical analysis on the American Southwest. Results show that, consistently with the predictions of an investment model, economic characteristics signaling loc...

Uncertainty analysis of an integrated energy system based on information theory

International Nuclear Information System (INIS)

Fu, Xueqian; Sun, Hongbin; Guo, Qinglai; Pan, Zhaoguang; Xiong, Wen; Wang, Li

2017-01-01

Currently, a custom-designed configuration of different renewable technologies named the integrated energy system (IES) has become popular due to its high efficiency, benefiting from complementary multi-energy technologies. This paper proposes an information entropy approach to quantify uncertainty in an integrated energy system based on a stochastic model that drives a power system model derived from an actual network on Barry Island. Due to the complexity of co-behaviours between generators, a copula-based approach is utilized to articulate the dependency structure of the generator outputs with regard to such factors as weather conditions. Correlation coefficients and mutual information, which are effective for assessing the dependence relationships, are applied to judge whether the stochastic IES model is correct. The calculated information values can be used to analyse the impacts of the coupling of power and heat on power flows and heat flows, and this approach will be helpful for improving the operation of IES. - Highlights: • The paper explores uncertainty of an integrated energy system. • The dependent weather model is verified from the perspective of correlativity. • The IES model considers the dependence between power and heat. • The information theory helps analyse the complexity of IES operation. • The application of the model is studied using an operational system on Barry Island.

Monthly Weather Review

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Supplements to the Monthly Weather Review publication. The Weather Bureau published the Monthly weather review Supplement irregularly from 1914 to 1949. The...

Root-driven Weathering Impacts on Mineral-Organic Associations in Deep Soil

Science.gov (United States)

Keiluweit, M.; Garcia Arredondo, M.; Tfaily, M. M.; Kukkadapu, R. K.; Schulz, M. S.; Lawrence, C. R.

2017-12-01

Plant roots dramatically reshape the soil environments through the release of organic compounds. While root-derived organic compounds are recognized as an important source of soil C, their role in promoting weathering reactions has largely been overlooked. On the one hand, root-driven weathering may generate mineral-organic associations, which can protect soil C for centuries to millennia. On the other hand, root-driven weathering also transforms minerals, potentially disrupting protective mineral-organic associations in the process. Hence root-derived C may not only initiate C accumulation, but also diminish C stocks through disruption of mineral-organic associations. Here we determined the impact of rhizogenic weathering on mineral-organic associations, and associated changes in C storage, across the Santa Cruz Marine Terrace chronosequence (65ka-226ka). Using a combination of high-resolution mass spectrometry, Mössbauer, and X-ray (micro)spectroscopy, we examined mineral-organic associations of deep soil horizons characterized by intense rhizogenic weathering gradients. Initial rhizogenic weathering dramatically increased C stocks, which is directly linked to an increase of microbially-derived C bound to monomeric Fe and Al and nano-goethite. As weathering proceeded, the soil C stocks declined concurrent with an increasingly plant-derived C signature and decreasing crystallinity. X-ray spectromicroscopic analyses revealed strong spatial associations between C and Fe during initial weathering stages, indicative of protective mineral-organic associations. In contrast, later weathering stages showed weaker spatial relationships between C and Fe. We conclude that rhizogenic weathering enhance C storage by creating protective mineral-organic associations in the initial weathering stages. As root-driven weathering proceeds, minerals are transformed into more crystalline phases that retain lower amounts of C. Our results demonstrate that root-induced weathering

Operational space weather service for GNSS precise positioning

Directory of Open Access Journals (Sweden)

N. Jakowski

2005-11-01

Full Text Available The ionospheric plasma can significantly influence the propagation of radio waves and the ionospheric disturbances are capable of causing range errors, rapid phase and amplitude fluctuations (radio scintillations of satellite signals that may lead to degradation of the system performance, its accuracy and reliability. The cause of such disturbances should be sought in the processes originating in the Sun. Numerous studies on these phenomena have been already carried out at a broad international level, in order to measure/estimate these space weather induced effects, to forecast them, and to understand and mitigate their impact on present-day technological systems. SWIPPA (Space Weather Impact on Precise Positioning Applications is a pilot project jointly supported by the German Aerospace Centre (DLR and the European Space Agency (ESA. The project aims at establishing, operating, and evaluating a specific space-weather monitoring service that can possibly lead to improving current positioning applications based on Global Navigation Satellite Systems (GNSS. This space weather service provides GNSS users with essential expert information delivered in the form of several products - maps of TEC values, TEC spatial and temporal gradients, alerts for ongoing/oncoming ionosphere disturbances, etc.

Operational space weather service for GNSS precise positioning

Directory of Open Access Journals (Sweden)

N. Jakowski

2005-11-01

Full Text Available The ionospheric plasma can significantly influence the propagation of radio waves and the ionospheric disturbances are capable of causing range errors, rapid phase and amplitude fluctuations (radio scintillations of satellite signals that may lead to degradation of the system performance, its accuracy and reliability. The cause of such disturbances should be sought in the processes originating in the Sun. Numerous studies on these phenomena have been already carried out at a broad international level, in order to measure/estimate these space weather induced effects, to forecast them, and to understand and mitigate their impact on present-day technological systems.

SWIPPA (Space Weather Impact on Precise Positioning Applications is a pilot project jointly supported by the German Aerospace Centre (DLR and the European Space Agency (ESA. The project aims at establishing, operating, and evaluating a specific space-weather monitoring service that can possibly lead to improving current positioning applications based on Global Navigation Satellite Systems (GNSS. This space weather service provides GNSS users with essential expert information delivered in the form of several products - maps of TEC values, TEC spatial and temporal gradients, alerts for ongoing/oncoming ionosphere disturbances, etc.

Decision Making and Risk Evaluation Frameworks for Extreme Space Weather Events

Science.gov (United States)

Uritskaya, O.; Robinson, R. M.; Pulkkinen, A. A.

2017-12-01

Extreme Space Weather events (ESWE) are in the spotlight nowadays because they can produce a significant impact not only due to their intensity and broad geographical scope, but also because of the widespread levels and the multiple sectors of the economy that could be involved. In the task of evaluation of the ESWE consequences, the most problematic and vulnerable aspect is the determination and calculation of the probability of statistically infrequent events and the subsequent assessment of the economic risks. In this work, we conduct a detailed analysis of the available frameworks of the general Decision-Making Theory in the presence of uncertainty, in the context of their applicability for the numerical estimation of the risks and losses associated with ESWE. The results of our study demonstrate that, unlike the Multiple-criteria decision analysis or Minimax approach to modeling of the possible scenarios for the ESWE effects, which prevail in the literature, the most suitable concept is the Games Against Nature (GAN). It enables an evaluation of every economically relevant aspect of space weather conditions and obtain more detailed results. Choosing the appropriate methods for solving GAN models, i.e. determining the most optimal strategy with a given level of uncertainty, requires estimating the conditional probabilities of Space Weather events for each outcome of possible scenarios of this natural disaster. Due to the specifics of complex natural and economic systems, with which we are dealing in this case, this problem remains unsolved, mainly because of inevitable loss of information at every stage of the decision-making process. The analysis is illustrated by deregulated electricity markets of the USA and Canada, whose power grid systems are known to be perceptive to ESWE. The GAN model is more appropriate in identifying potential risks in economic systems. The proposed approach, when applied to the existing database of Space Weather observations and

Uncertainty Assessment: Reservoir Inflow Forecasting with Ensemble Precipitation Forecasts and HEC-HMS

Directory of Open Access Journals (Sweden)

Sheng-Chi Yang

2014-01-01

Full Text Available During an extreme event, having accurate inflow forecasting with enough lead time helps reservoir operators decrease the impact of floods downstream. Furthermore, being able to efficiently operate reservoirs could help maximize flood protection while saving water for drier times of the year. This study combines ensemble quantitative precipitation forecasts and a hydrological model to provide a 3-day reservoir inflow in the Shihmen Reservoir, Taiwan. A total of six historical typhoons were used for model calibration, validation, and application. An understanding of cascaded uncertainties from the numerical weather model through the hydrological model is necessary for a better use for forecasting. This study thus conducted an assessment of forecast uncertainty on magnitude and timing of peak and cumulative inflows. It found that using the ensemble-mean had less uncertainty than randomly selecting individual member. The inflow forecasts with shorter length of cumulative time had a higher uncertainty. The results showed that using the ensemble precipitation forecasts with the hydrological model would have the advantage of extra lead time and serve as a valuable reference for operating reservoirs.

Do location specific forecasts pose a new challenge for communicating uncertainty?

Science.gov (United States)

Abraham, Shyamali; Bartlett, Rachel; Standage, Matthew; Black, Alison; Charlton-Perez, Andrew; McCloy, Rachel

2015-04-01

In the last decade, the growth of local, site-specific weather forecasts delivered by mobile phone or website represents arguably the fastest change in forecast consumption since the beginning of Television weather forecasts 60 years ago. In this study, a street-interception survey of 274 members of the public a clear first preference for narrow weather forecasts above traditional broad weather forecasts is shown for the first time, with a clear bias towards this preference for users under 40. The impact of this change on the understanding of forecast probability and intensity information is explored. While the correct interpretation of the statement 'There is a 30% chance of rain tomorrow' is still low in the cohort, in common with previous studies, a clear impact of age and educational attainment on understanding is shown, with those under 40 and educated to degree level or above more likely to correctly interpret it. The interpretation of rainfall intensity descriptors ('Light', 'Moderate', 'Heavy') by the cohort is shown to be significantly different to official and expert assessment of the same descriptors and to have large variance amongst the cohort. However, despite these key uncertainties, members of the cohort generally seem to make appropriate decisions about rainfall forecasts. There is some evidence that the decisions made are different depending on the communication format used, and the cohort expressed a clear preference for tabular over graphical weather forecast presentation.

Skill prediction of local weather forecasts based on the ECMWF ensemble

Directory of Open Access Journals (Sweden)

C. Ziehmann

2001-01-01

Full Text Available Ensemble Prediction has become an essential part of numerical weather forecasting. In this paper we investigate the ability of ensemble forecasts to provide an a priori estimate of the expected forecast skill. Several quantities derived from the local ensemble distribution are investigated for a two year data set of European Centre for Medium-Range Weather Forecasts (ECMWF temperature and wind speed ensemble forecasts at 30 German stations. The results indicate that the population of the ensemble mode provides useful information for the uncertainty in temperature forecasts. The ensemble entropy is a similar good measure. This is not true for the spread if it is simply calculated as the variance of the ensemble members with respect to the ensemble mean. The number of clusters in the C regions is almost unrelated to the local skill. For wind forecasts, the results are less promising.

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

Science.gov (United States)

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

Uncertainty information in climate data records from Earth observation

Science.gov (United States)

Merchant, Christopher J.; Paul, Frank; Popp, Thomas; Ablain, Michael; Bontemps, Sophie; Defourny, Pierre; Hollmann, Rainer; Lavergne, Thomas; Laeng, Alexandra; de Leeuw, Gerrit; Mittaz, Jonathan; Poulsen, Caroline; Povey, Adam C.; Reuter, Max; Sathyendranath, Shubha; Sandven, Stein; Sofieva, Viktoria F.; Wagner, Wolfgang

2017-07-01

The question of how to derive and present uncertainty information in climate data records (CDRs) has received sustained attention within the European Space Agency Climate Change Initiative (CCI), a programme to generate CDRs addressing a range of essential climate variables (ECVs) from satellite data. Here, we review the nature, mathematics, practicalities, and communication of uncertainty information in CDRs from Earth observations. This review paper argues that CDRs derived from satellite-based Earth observation (EO) should include rigorous uncertainty information to support the application of the data in contexts such as policy, climate modelling, and numerical weather prediction reanalysis. Uncertainty, error, and quality are distinct concepts, and the case is made that CDR products should follow international metrological norms for presenting quantified uncertainty. As a baseline for good practice, total standard uncertainty should be quantified per datum in a CDR, meaning that uncertainty estimates should clearly discriminate more and less certain data. In this case, flags for data quality should not duplicate uncertainty information, but instead describe complementary information (such as the confidence in the uncertainty estimate provided or indicators of conditions violating the retrieval assumptions). The paper discusses the many sources of error in CDRs, noting that different errors may be correlated across a wide range of timescales and space scales. Error effects that contribute negligibly to the total uncertainty in a single-satellite measurement can be the dominant sources of uncertainty in a CDR on the large space scales and long timescales that are highly relevant for some climate applications. For this reason, identifying and characterizing the relevant sources of uncertainty for CDRs is particularly challenging. The characterization of uncertainty caused by a given error effect involves assessing the magnitude of the effect, the shape of the

Dynamic Weather Routes: A Weather Avoidance Concept for Trajectory-Based Operations

Science.gov (United States)

McNally, B. David; Love, John

2011-01-01

The integration of convective weather modeling with trajectory automation for conflict detection, trial planning, direct routing, and auto resolution has uncovered a concept that could help controllers, dispatchers, and pilots identify improved weather routes that result in significant savings in flying time and fuel burn. Trajectory automation continuously and automatically monitors aircraft in flight to find those that could potentially benefit from improved weather reroutes. Controllers, dispatchers, and pilots then evaluate reroute options to assess their suitability given current weather and traffic. In today's operations aircraft fly convective weather avoidance routes that were implemented often hours before aircraft approach the weather and automation does not exist to automatically monitor traffic to find improved weather routes that open up due to changing weather conditions. The automation concept runs in real-time and employs two keysteps. First, a direct routing algorithm automatically identifies flights with large dog legs in their routes and therefore potentially large savings in flying time. These are common - and usually necessary - during convective weather operations and analysis of Fort Worth Center traffic shows many aircraft with short cuts that indicate savings on the order of 10 flying minutes. The second and most critical step is to apply trajectory automation with weather modeling to determine what savings could be achieved by modifying the direct route such that it avoids weather and traffic and is acceptable to controllers and flight crews. Initial analysis of Fort Worth Center traffic suggests a savings of roughly 50% of the direct route savings could be achievable.The core concept is to apply trajectory automation with convective weather modeling in real time to identify a reroute that is free of weather and traffic conflicts and indicates enough time and fuel savings to be considered. The concept is interoperable with today

Analysis of uncertainties in CRAC2 calculations: the inhalation pathway

International Nuclear Information System (INIS)

Killough, G.G.; Dunning, D.E. Jr.

1984-01-01

CRAC2 is a computer code for estimating the health effects and economic costs that might result from a release of radioactivity from a nuclear reactor to the environment. This paper describes tests of sensitivity of the predicted health effects to uncertainties in parameters associated with inhalation of the released radionuclides. These parameters are the particle size of the carrier aerosol and, for each element in the release, the clearance parameters for the lung model on which the code's dose conversion factors for inhalation are based. CRAC2 uses hourly meteorological data and a straight-line Gaussian plume model to predict the transport of airborne radioactivity; it includes models for plume depletion and population evacuation, and data for the distributions of population and land use. The code can compute results for single weather sequences, or it can perform random sampling of weather sequences from the meteorological data file and compute results for each weather sequence in the sample. For the work described in this paper, we concentrated on three fixed weather sequences that represent a range of conditions. For each fixed weather sequence, we applied random sampling to joint distributions of the inhalation parameters in order to estimate the sensitivity of the predicted health effects. All sampling runs produced coefficients of variation that were less than 50%, but some differences of means between weather sequences were substantial, as were some differences between means and the corresponding CRAC2 results without random sampling. Early injuries showed differences of as much as 1 to 2 orders of magnitude, while the differences in early fatalities were less than a factor of 2. Latent cancer fatalities varied by less than 10%. 19 references, 6 figures, 3 tables

Constraints on continental crustal mass loss via chemical weathering using lithium and its isotopes

Science.gov (United States)

Rudnick, R. L.; Liu, X. M.

2012-04-01

The continental crust has an "intermediate" bulk composition that is distinct from primary melts of peridotitic mantle (basalt or picrite). This mismatch between the "building blocks" and the "edifice" that is the continental crust points to the operation of processes that preferentially remove mafic to ultramafic material from the continents. Such processes include lower crustal recycling (via density foundering or lower crustal subduction - e.g., relamination, Hacker et al., 2011, EPSL), generation of evolved melts via slab melting, and/or chemical weathering. Stable isotope systems point to the influence of chemical weathering on the bulk crust composition: the oxygen isotope composition of the bulk crust is distinctly heavier than that of primary, mantle-derived melts (Simon and Lecuyer, 2005, G-cubed) and the Li isotopic composition of the bulk crust is distinctly lighter than that of mantle-derive melts (Teng et al., 2004, GCA; 2008, Chem. Geol.). Both signatures mark the imprint of chemical weathering on the bulk crust composition. Here, we use a simple mass balance model for lithium inputs and outputs from the continental crust to quantify the mass lost due to chemical weathering. We find that a minimum of 15%, a maximum of 60%, and a best estimate of ~40% of the original juvenile rock mass may have been lost via chemical weathering. The accumulated percentage of mass loss due to chemical weathering leads to an average global chemical weathering rate (CWR) of ~ 1×10^10 to 2×10^10 t/yr since 3.5 Ga, which is about an order of magnitude higher than the minimum estimates based on modern rivers (Gaillardet et al., 1999, Chem. Geol.). While we cannot constrain the exact portion of crustal mass loss via chemical weathering, given the uncertainties of the calculation, we can demonstrate that the weathering flux is non-zero. Therefore, chemical weathering must play a role in the evolution of the composition and mass of the continental crust.

Cold-Weather Sports

Science.gov (United States)

... Videos for Educators Search English Español Cold-Weather Sports KidsHealth / For Teens / Cold-Weather Sports What's in this article? What to Do? Classes ... weather. What better time to be outdoors? Winter sports can help you burn calories, increase your cardiovascular ...

Briefing highlights space weather risks to GPS

Science.gov (United States)

Tretkoff, Ernie

2011-07-01

Solar storms, which are expected to increase as the Sun nears the most active phase of the solar cycle, can disrupt a variety of technologies on which society relies. Speakers at a 22 June briefing on Capitol Hill in Washington, D. C., focused on how space weather can affect the Global Positioning System (GPS), which is used in a wide range of industries, including commercial air travel, agriculture, national security, and emergency response. Rocky Stone, chief technical pilot for United Airlines, noted that GPS allows more aircraft to be in airspace, saves fuel, and helps aircraft move safely on runways. “Improvements in space weather forecasting need to be pursued,” he said. Precision GPS has also “changed the whole nature of farming,” said Ron Hatch, Director of Navigation Systems, NavCom Technology/John Deere. GPS makes it possible for tractors to be driven in the most efficient paths and for fertilizer and water to be applied precisely to the areas that most need them. Space weather-induced degradation of GPS signals can cause significant loss to farms that rely on GPS. Elizabeth Zimmerman, Deputy Associate Administrator for the Office of Response and Recovery at the Federal Emergency Management Agency (FEMA), described how FEMA relies on GPS for disaster recovery. The agency is developing an operations plan for dealing with space weather, she said.

Foreign oil companies weathering Peru's political crisis

International Nuclear Information System (INIS)

Anon.

1992-01-01

This paper reports that foreign oil companies are weathering Peru's political crisis, and the outlook for increased foreign participation in Peru's petroleum sector remains promising. There has been improvement in the political turmoil and soured international relations that followed President Alberto Fujimori's Apr. 5 suspension of Peru's Congress, charging political corruption and attempts to block his fiscal reforms. But there are fresh concerns over an increase in terrorism aimed at oil industry facilities by antigovernment guerrilla groups in Peru. Meanwhile, state-owned oil company Petroleos del Peru (Petroperu) continues efforts to sell assets as part of Fujimori's mandated privatization program. And foreign companies continue to grapple with uncertainty and bureaucratic red tape in chasing investment opportunities in Peru's beleaguered but opening petroleum sector

Communicating Low-Probability High-Consequence Risk, Uncertainty and Expert Confidence: Induced Seismicity of Deep Geothermal Energy and Shale Gas.

Science.gov (United States)

Knoblauch, Theresa A K; Stauffacher, Michael; Trutnevyte, Evelina

2018-04-01

Subsurface energy activities entail the risk of induced seismicity including low-probability high-consequence (LPHC) events. For designing respective risk communication, the scientific literature lacks empirical evidence of how the public reacts to different written risk communication formats about such LPHC events and to related uncertainty or expert confidence. This study presents findings from an online experiment (N = 590) that empirically tested the public's responses to risk communication about induced seismicity and to different technology frames, namely deep geothermal energy (DGE) and shale gas (between-subject design). Three incrementally different formats of written risk communication were tested: (i) qualitative, (ii) qualitative and quantitative, and (iii) qualitative and quantitative with risk comparison. Respondents found the latter two the easiest to understand, the most exact, and liked them the most. Adding uncertainty and expert confidence statements made the risk communication less clear, less easy to understand and increased concern. Above all, the technology for which risks are communicated and its acceptance mattered strongly: respondents in the shale gas condition found the identical risk communication less trustworthy and more concerning than in the DGE conditions. They also liked the risk communication overall less. For practitioners in DGE or shale gas projects, the study shows that the public would appreciate efforts in describing LPHC risks with numbers and optionally risk comparisons. However, there seems to be a trade-off between aiming for transparency by disclosing uncertainty and limited expert confidence, and thereby decreasing clarity and increasing concern in the view of the public. © 2017 Society for Risk Analysis.

Protein flexibility: coordinate uncertainties and interpretation of structural differences

Energy Technology Data Exchange (ETDEWEB)

Rashin, Alexander A., E-mail: alexander-rashin@hotmail.com [BioChemComp Inc., 543 Sagamore Avenue, Teaneck, NJ 07666 (United States); LH Baker Center for Bioinformatics and Department of Biochemistry, Biophysics and Molecular Biology, 112 Office and Lab Building, Iowa State University, Ames, IA 50011-3020 (United States); Rashin, Abraham H. L. [BioChemComp Inc., 543 Sagamore Avenue, Teaneck, NJ 07666 (United States); Rutgers, The State University of New Jersey, 22371 BPO WAY, Piscataway, NJ 08854-8123 (United States); Jernigan, Robert L. [LH Baker Center for Bioinformatics and Department of Biochemistry, Biophysics and Molecular Biology, 112 Office and Lab Building, Iowa State University, Ames, IA 50011-3020 (United States); BioChemComp Inc., 543 Sagamore Avenue, Teaneck, NJ 07666 (United States)

2009-11-01

Criteria for the interpretability of coordinate differences and a new method for identifying rigid-body motions and nonrigid deformations in protein conformational changes are developed and applied to functionally induced and crystallization-induced conformational changes. Valid interpretations of conformational movements in protein structures determined by X-ray crystallography require that the movement magnitudes exceed their uncertainty threshold. Here, it is shown that such thresholds can be obtained from the distance difference matrices (DDMs) of 1014 pairs of independently determined structures of bovine ribonuclease A and sperm whale myoglobin, with no explanations provided for reportedly minor coordinate differences. The smallest magnitudes of reportedly functional motions are just above these thresholds. Uncertainty thresholds can provide objective criteria that distinguish between true conformational changes and apparent ‘noise’, showing that some previous interpretations of protein coordinate changes attributed to external conditions or mutations may be doubtful or erroneous. The use of uncertainty thresholds, DDMs, the newly introduced CDDMs (contact distance difference matrices) and a novel simple rotation algorithm allows a more meaningful classification and description of protein motions, distinguishing between various rigid-fragment motions and nonrigid conformational deformations. It is also shown that half of 75 pairs of identical molecules, each from the same asymmetric crystallographic cell, exhibit coordinate differences that range from just outside the coordinate uncertainty threshold to the full magnitude of large functional movements. Thus, crystallization might often induce protein conformational changes that are comparable to those related to or induced by the protein function.

Cockpit weather information needs

Science.gov (United States)

Scanlon, Charles H.

1992-01-01

The primary objective is to develop an advanced pilot weather interface for the flight deck and to measure its utilization and effectiveness in pilot reroute decision processes, weather situation awareness, and weather monitoring. Identical graphical weather displays for the dispatcher, air traffic control (ATC), and pilot crew should also enhance the dialogue capabilities for reroute decisions. By utilizing a broadcast data link for surface observations, forecasts, radar summaries, lightning strikes, and weather alerts, onboard weather computing facilities construct graphical displays, historical weather displays, color textual displays, and other tools to assist the pilot crew. Since the weather data is continually being received and stored by the airborne system, the pilot crew has instantaneous access to the latest information. This information is color coded to distinguish degrees of category for surface observations, ceiling and visibilities, and ground radar summaries. Automatic weather monitoring and pilot crew alerting is accomplished by the airborne computing facilities. When a new weather information is received, the displays are instantaneously changed to reflect the new information. Also, when a new surface or special observation for the intended destination is received, the pilot crew is informed so that information can be studied at the pilot's discretion. The pilot crew is also immediately alerted when a severe weather notice, AIRMET or SIGMET, is received. The cockpit weather display shares a multicolor eight inch cathode ray tube and overlaid touch panel with a pilot crew data link interface. Touch sensitive buttons and areas are used for pilot selection of graphical and data link displays. Time critical ATC messages are presented in a small window that overlays other displays so that immediate pilot alerting and action can be taken. Predeparture and reroute clearances are displayed on the graphical weather system so pilot review of weather along

Space weather in the EU’s FP7 Space Theme

Directory of Open Access Journals (Sweden)

Chiarini Paola

2013-11-01

Full Text Available Technological infrastructures in space and on ground provide services on which modern society and economies rely. Space weather related research is funded under the 7th Framework Programme for Research and Innovation (FP7 of the European Union in response to the need of protecting such critical infrastructures from the damage which could be caused by extreme space weather events. The calls for proposals published under the topic “Security of space assets from space weather events” of the FP7 Space Theme aimed to improve forecasts and predictions of disruptive space weather events as well as identify best practices to limit the impacts on space- and ground-based infrastructures and their data provision. Space weather related work was also funded under the topic “Exploitation of space science and exploration data”, which aims to add value to space missions and Earth-based observations by contributing to the effective scientific exploitation of collected data. Since 2007 a total of 20 collaborative projects have been funded, covering a variety of physical phenomena associated with space weather, from ionospheric disturbances and scintillation, to geomagnetically induced currents at Earth’s surface, to coronal mass ejections and solar energetic particles. This article provides an overview of the funded projects, touching upon some results and referring to specific websites for a more exhaustive description of the projects’ outcomes.

Uncertainty in the area-related QPF for heavy convective precipitation

Czech Academy of Sciences Publication Activity Database

Řezáčová, Daniela; Zacharov, Petr, jr.; Sokol, Zbyněk

2009-01-01

Roč. 93, 1-3 (2009), s. 238-246 ISSN 0169-8095. [European Conference on Severe Storms /4./. Miramare -Trieste, 10.09.2007-14.09.2007] R&D Projects: GA ČR GA205/07/0905; GA MŠk OC 112 Institutional research plan: CEZ:AV0Z30420517 Keywords : Convective storm * Quantitative precipitation forecast * Uncertainty in precipitation forecasting * Ensemble forecasting * Numerical weather prediction model Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.811, year: 2009 http://www.sciencedirect.com/science/journal/01698095

The USGS Geomagnetism Program and its role in Space-Weather Monitoring

Science.gov (United States)

Love, Jeffrey J.; Finn, Carol A.

2011-01-01

Magnetic storms result from the dynamic interaction of the solar wind with the coupled magnetospheric-ionospheric system. Large storms represent a potential hazard for the activities and infrastructure of a modern, technologically based society [Baker et al., 2008]; they can cause the loss of radio communications, reduce the accuracy of global positioning systems, damage satellite electronics and affect satellite operations, increase pipeline corrosion, and induce voltage surges in electric power grids, causing blackouts. So while space weather starts with the Sun and is driven by the solar wind, it is on, or just above, the surface of the Earth that the practical effects of space weather are realized. Therefore, ground-based sensor networks, including magnetic observatories [Love, 2008], play an important role in space weather monitoring.

Space weather and power grids: findings and outlook

Science.gov (United States)

Krausmann, Elisabeth; Andersson, Emmelie; Murtagh, William; Mitchison, Neil

2014-05-01

The impact of space weather on the power grid is a tangible and recurring threat with potentially serious consequences on society. Of particular concern is the long-distance high-voltage power grid, which is vulnerable to the effects of geomagnetic storms that can damage or destroy equipment or lead to grid collapse. In order to launch a dialogue on the topic and encourage authorities, regulators and operators in European countries and North America to learn from each other, the European Commission's Joint Research Centre, the Swedish Civil Contingencies Agency, and NOAA's Space Weather Prediction Centre, with the contribution of the UK Civil Contingencies Secretariat, jointly organised a workshop on the impact of extreme space weather on the power grid on 29-30 October 2013. Being structured into 6 sessions, the topics addressed were space-weather phenomena and the dynamics of their impact on the grid, experiences with prediction and now-casting in the USA and in Europe, risk assessment and preparedness, as well as policy implications arising from increased awareness of the space-weather hazard. The main workshop conclusions are: • There is increasing awareness of the risk of space-weather impact among power-grid operators and regulators and some countries consider it a priority risk to be addressed. • The predictability of space-weather phenomena is still limited and relies, in part, on data from ageing satellites. NOAA is working with NASA to launch the DSCOVR solar wind spacecraft, the replacement for the ACE satellite, in early 2015. • In some countries, models and tools for GIC prediction and grid impact assessment have been developed in collaboration with national power grids but equipment vulnerability models are scarce. • Some countries have successfully hardened their transmission grids to space-weather impact and sustained relatively little or no damage due to currents induced by past moderate space-weather events. • While there is preparedness

An Experimental Study on the Water-Induced Strength Reduction in Zigong Argillaceous Siltstone with Different Degree of Weathering

Directory of Open Access Journals (Sweden)

Yu-chuan Yang

2016-01-01

Full Text Available The water-softening property of soft rocks is a key problem in geotechnical engineering. A typical red-bed soft rock (the Zigong argillaceous siltstones with different weathering degree is selected as an example to study the water-softening property and the influence of degree of weathering. A series of mechanical and microstructure tests are carried out to analyze the weathering characteristics and mechanism of the Zigong argillaceous siltstones. The results of mechanical experiments reveal that the water content and the weathering degree of rock specimens both have a weakening effect on the compressive and shear strengths. According to the results of present microstructure tests, the mechanical properties of the Zigong argillaceous siltstones are closely correlated with their physical properties, including internal microstructure and material composition for highly weathered rocks or moderately weathered rocks (in both natural and saturation conditions. Finally, experimental results indicate that the changes of microstructure and internal materials are two main factors that influence rock strength parameters after contacting with water and that these properties reflect the rock weathering degree. In a word, when red-bed soft rocks are encountered in geotechnical engineering, special attention should be paid to presence of water.

NASA Space Weather Center Services: Potential for Space Weather Research

Science.gov (United States)

Zheng, Yihua; Kuznetsova, Masha; Pulkkinen, Antti; Taktakishvili, A.; Mays, M. L.; Chulaki, A.; Lee, H.; Hesse, M.

2012-01-01

The NASA Space Weather Center's primary objective is to provide the latest space weather information and forecasting for NASA's robotic missions and its partners and to bring space weather knowledge to the public. At the same time, the tools and services it possesses can be invaluable for research purposes. Here we show how our archive and real-time modeling of space weather events can aid research in a variety of ways, with different classification criteria. We will list and discuss major CME events, major geomagnetic storms, and major SEP events that occurred during the years 2010 - 2012. Highlights of major tools/resources will be provided.

Weathering and weathering rates of natural stone

Science.gov (United States)

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.

Weatherization Works: Weatherization Assistance Program Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

The United States demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

GRAPH THEORY APPROACH TO QUANTIFY UNCERTAINTY OF PERFORMANCE MEASURES

Directory of Open Access Journals (Sweden)

Sérgio D. Sousa

2015-03-01

Full Text Available In this work, the performance measurement process is studied to quantify the uncertainty induced in the resulting performance measure (PM. To that end, the causes of uncertainty are identified, analysing the activities undertaken in the three following stages of the performance measurement process: design and implementation, data collection and record, and determination and analysis. A quantitative methodology based on graph theory and on the sources of uncertainty of the performance measurement process is used to calculate an uncertainty index to evaluate the level of uncertainty of a given PM or (key performance indicator. An application example is presented. The quantification of PM uncertainty could contribute to better represent the risk associated with a given decision and also to improve the PM to increase its precision and reliability.

A new system to quantify uncertainties in LEO satellite position determination due to space weather events

Data.gov (United States)

National Aeronautics and Space Administration — We propose to develop a new system for quantitative assessment of uncertainties in LEO satellite position caused by storm time changes in space environmental...

Understanding Climate Uncertainty with an Ocean Focus

Science.gov (United States)

Tokmakian, R. T.

2009-12-01

Uncertainty in climate simulations arises from various aspects of the end-to-end process of modeling the Earth’s climate. First, there is uncertainty from the structure of the climate model components (e.g. ocean/ice/atmosphere). Even the most complex models are deficient, not only in the complexity of the processes they represent, but in which processes are included in a particular model. Next, uncertainties arise from the inherent error in the initial and boundary conditions of a simulation. Initial conditions are the state of the weather or climate at the beginning of the simulation and other such things, and typically come from observations. Finally, there is the uncertainty associated with the values of parameters in the model. These parameters may represent physical constants or effects, such as ocean mixing, or non-physical aspects of modeling and computation. The uncertainty in these input parameters propagates through the non-linear model to give uncertainty in the outputs. The models in 2020 will no doubt be better than today’s models, but they will still be imperfect, and development of uncertainty analysis technology is a critical aspect of understanding model realism and prediction capability. Smith [2002] and Cox and Stephenson [2007] discuss the need for methods to quantify the uncertainties within complicated systems so that limitations or weaknesses of the climate model can be understood. In making climate predictions, we need to have available both the most reliable model or simulation and a methods to quantify the reliability of a simulation. If quantitative uncertainty questions of the internal model dynamics are to be answered with complex simulations such as AOGCMs, then the only known path forward is based on model ensembles that characterize behavior with alternative parameter settings [e.g. Rougier, 2007]. The relevance and feasibility of using "Statistical Analysis of Computer Code Output" (SACCO) methods for examining uncertainty in

The Weather and Ménière's Disease: A Longitudinal Analysis in the UK.

Science.gov (United States)

Schmidt, Wiebke; Sarran, Christophe; Ronan, Natalie; Barrett, George; Whinney, David J; Fleming, Lora E; Osborne, Nicholas J; Tyrrell, Jessica

2017-02-01

Changes in the weather influence symptom severity in Ménière's disease (MD). MD is an unpredictable condition that significantly impacts on quality of life. It is suggested that fluctuations in the weather, especially atmospheric pressure may influence the symptoms of MD. However, to date, limited research has investigated the impact of the weather on MD. In a longitudinal study, a mobile phone application collected data from 397 individuals (277 females and 120 males with an average age of 50 yr) from the UK reporting consultant-diagnosed MD. Daily symptoms (vertigo, aural fullness, tinnitus, hearing loss, and attack prevalence) and GPS locations were collected; these data were linked with Met Office weather data (including atmospheric pressure, humidity, temperature, visibility, and wind speed). Symptom severity and attack prevalence were reduced on days when atmospheric pressure was higher. When atmospheric pressure was below 1,013 hectopascals, the risk of an attack was 1.30 (95% confidence interval: 1.10, 1.54); when the humidity was above 90%, the risk of an attack was 1.26 (95% confidence interval 1.06, 1.49). This study provides the strongest evidence to date that changes in atmospheric pressure and humidity are associated with symptom exacerbation in MD. Improving our understanding of the role of weather and other environmental triggers in Ménière's may reduce the uncertainty associated with living with this condition, significantly contributing to improved quality of life.

Powernext weather, benchmark indices for effective weather risk management

International Nuclear Information System (INIS)

2006-01-01

According to the U.S. Department of Energy, an estimated 25% of the GNP is affected by weather-related events. The variations in temperature - even small ones - can also have long-lasting effects on the operational results of a company. Among other, the Energy supply sector is sensitive to weather risks: a milder or harsher than usual winter leads to a decrease or increase of energy consumption. The price of electricity on power trading facilities like Powernext is especially sensitive to odd changes in temperatures. Powernext and Meteo-France (the French meteorological agency) have joined expertise in order to promote the use of weather indices in term of decision making or underlying of hedging tools to energy actors, end users from any other sector of activity and specialists of the weather risk hedging. The Powernext Weather indices are made from information collected by Meteo-France's main observation network according to the norms of international meteorology, in areas carefully selected. The gross data are submitted to a thorough review allowing the correction of abnormalities and the reconstitution of missing data. Each index is fashioned to take into account the economic activity in the various regions of the country as represented by each region's population. This demographic information represents a fair approximation of the weight of the regional economic activity. This document presents the Powernext/Meteo France partnership for the elaboration of efficient weather-related risk management indices. (J.S.)

Socio-Economic Impacts of Space Weather and User Needs for Space Weather Information

Science.gov (United States)

Worman, S. L.; Taylor, S. M.; Onsager, T. G.; Adkins, J. E.; Baker, D. N.; Forbes, K. F.

2017-12-01

The 2015 National Space Weather Strategy and Space Weather Action Plan (SWAP) details the activities, outcomes, and timelines to build a "Space Weather Ready Nation." NOAA's Space Weather Prediction Center and Abt Associates are working together on two SWAP initiatives: (1) identifying, describing, and quantifying the socio-economic impacts of moderate and severe space weather; and (2) outreach to engineers and operators to better understand user requirements for space weather products and services. Both studies cover four technological sectors (electric power, commercial aviation, satellites, and GNSS users) and rely heavily on industry input. Findings from both studies are essential for decreasing vulnerabilities and enhancing preparedness.

Probability for Weather and Climate

Science.gov (United States)

Smith, L. A.

2013-12-01

Over the last 60 years, the availability of large-scale electronic computers has stimulated rapid and significant advances both in meteorology and in our understanding of the Earth System as a whole. The speed of these advances was due, in large part, to the sudden ability to explore nonlinear systems of equations. The computer allows the meteorologist to carry a physical argument to its conclusion; the time scales of weather phenomena then allow the refinement of physical theory, numerical approximation or both in light of new observations. Prior to this extension, as Charney noted, the practicing meteorologist could ignore the results of theory with good conscience. Today, neither the practicing meteorologist nor the practicing climatologist can do so, but to what extent, and in what contexts, should they place the insights of theory above quantitative simulation? And in what circumstances can one confidently estimate the probability of events in the world from model-based simulations? Despite solid advances of theory and insight made possible by the computer, the fidelity of our models of climate differs in kind from the fidelity of models of weather. While all prediction is extrapolation in time, weather resembles interpolation in state space, while climate change is fundamentally an extrapolation. The trichotomy of simulation, observation and theory which has proven essential in meteorology will remain incomplete in climate science. Operationally, the roles of probability, indeed the kinds of probability one has access too, are different in operational weather forecasting and climate services. Significant barriers to forming probability forecasts (which can be used rationally as probabilities) are identified. Monte Carlo ensembles can explore sensitivity, diversity, and (sometimes) the likely impact of measurement uncertainty and structural model error. The aims of different ensemble strategies, and fundamental differences in ensemble design to support of

Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA

Energy Technology Data Exchange (ETDEWEB)

Hou, Zhangshuan; Etingov, Pavel V.; Makarov, Yuri V.; Samaan, Nader A.

2014-10-27

In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of forecasts. We use automatically coupled wavelet transform and autoregressive integrated moving-average (ARIMA) forecasting to reflect multi-scale variability of forecast errors. The proposed analysis reveals slow-changing “quasi-deterministic” components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

The effect of weather on morphometric traits of juvenile cliff swallows

Science.gov (United States)

Roche, Erin A.; Brown, Mary Bomberger; Brown, Charles R.

2015-01-01

Episodes of food deprivation may change how nestling birds allocate energy to the growth of skeletal and feather morphological traits during development. Cliff swallows (Petrochelidon pyrrhonota) are colonial, insectivorous birds that regularly experience brief periods of severe weather-induced food deprivation during the nesting season which may affect offspring development. We investigated how annual variation in timing of rearing and weather were associated with length of wing and tail, skeletal traits, and body mass in juvenile cliff swallows reared in southwestern Nebraska during 2001–2006. As predicted under conditions of food deprivation, nestling skeletal and feather measurements were generally smaller in cooler years. However, variability explained by weather was small, suggesting that morphometric traits of juvenile cliff swallows were not highly sensitive to weather conditions experienced during this study. Measurements of juvenile morphological traits were positively correlated with measurements taken as adults, meaning that any variation among juveniles in response to rearing conditions showed evidence of persisting into a bird’s first breeding season. Our results show that body size in this species is phenotypically plastic and influenced, in part, by weather variables.

Topographic imprint on chemical weathering in deeply weathered soil-mantled landscapes (southern Brazil)

Science.gov (United States)

Vanacker, Veerle; Schoonejans, Jerome; Ameijeiras-Marino, Yolanda; Opfergelt, Sophie; Minella, Jean

2017-04-01

The regolith mantle is defined as the thin layer of unconsolidated material overlaying bedrock that contributes to shape the Earth's surface. The development of the regolith mantle in a landscape is the result of in-situ weathering, atmospheric input and downhill transport of weathering products. Bedrock weathering - the physical and chemical transformations of rock to soil - contributes to the vertical development of the regolith layer through downward propagation of the weathering front. Lateral transport of soil particles, aggregates and solutes by diffusive and concentrated particle and solute fluxes result in lateral redistribution of weathering products over the hillslope. In this study, we aim to expand the empirical basis on long-term soil evolution at the landscape scale through a detailed study of soil weathering in subtropical soils. Spatial variability in chemical mass fluxes and weathering intensity were studied along two toposequences with similar climate, lithology and vegetation but different slope morphology. This allowed us to isolate the topographic imprint on chemical weathering and soil development. The toposequences have convexo-concave slope morphology, and eight regolith profiles were analysed involving the flat upslope, steep midslope and flat toeslope part. Our data show a clear topographic imprint on soil development. Along hillslope, the chemical weathering intensity of the regolith profiles increases with distance from the crest. In contrast to the upslope positions, the soils in the basal concavities develop on in-situ and transported regolith. While the chemical weathering extent on the slope convexities (the upslope profiles) is similar for the steep and gentle toposequence, there is a clear difference in the rate of increase of the chemical weathering extent with distance from the crest. The increase of chemical weathering extent along hillslope is highest for the steep toposequence, suggesting that topography enhances soil particle

Modeling the evolution of natural cliffs subject to weathering. 1, Limit analysis approach

OpenAIRE

Utili, Stefano; Crosta, Giovanni B.

2011-01-01

Retrogressive landsliding evolution of natural slopes subjected to weathering has been modeled by assuming Mohr-Coulomb material behavior and by using an analytical method. The case of weathering-limited slope conditions, with complete erosion of the accumulated debris, has been modeled. The limit analysis upper-bound method is used to study slope instability induced by a homogeneous decrease of material strength in space and time. The only assumption required in the model concerns the degree...

Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

Directory of Open Access Journals (Sweden)

K. Steffens

2014-02-01

Full Text Available Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in south-western Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM, greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set (1970–1999 for an important agricultural production area in south-western Sweden based on monthly change factors for 2070–2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.

Reducing Uncertainty and Confronting Ignorance about the Possible Impacts of Weathering Plastic in the Marine Environment

OpenAIRE

Jahnke, Annika; Arp, Hans Petter Heinrich; Escher, Beate I.; Gewert, Berit; Gorokhova, Elena; Kühnel, Dana; Ogonowski, Martin; Potthof, Annegret; Rummel, Christophe Daniel; Schmitt-Jansen, Mechtild; Toorman, Erik; MacLeod, Matthew

2017-01-01

Plastic in the global oceans fulfills two of the three conditions for pollution to pose a planetary boundary threat because it is causing planetary-scale exposure that is not readily reversible. Plastic is a planetary boundary threat if it is having a currently unrecognized disruptive effect on a vital Earth system process. Discovering possible unknown effects is likely to be aided by achieving a fuller understanding of the environmental fate of plastic. Weathering of plastic generates microp...

Weather and emotional state

Science.gov (United States)

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

Casebook on application for weather

International Nuclear Information System (INIS)

2009-11-01

This book introduces the excellent cases on application using weather at the industry, research center and public office. It lists the names and application cases in 2008 and 2009, which includes research on decease in risk by weather in the industry by Sam sung institute of safety and environment, service on weather information for people by KT, application with weather information in the flight by Korean air, use on weather information for prevention of disasters by Masan city hall, upgrade for business with weather marketing, center for river forecast in NOAA and the case using weather management for high profit margins.

Expected frontiers: Incorporating weather uncertainty into a policy analysis using an integrated bi-level multi-objective optimization framework

Science.gov (United States)

Weather is the main driver in both plant use of nutrients and fate and transport of nutrients in the environment. In previous work, we evaluated a green tax for control of agricultural nutrients in a bi-level optimization framework that linked deterministic models. In this study,...

Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.

Energy Technology Data Exchange (ETDEWEB)

Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M. (Mathematics and Computer Science); (Univ. of Chicago); (New York Univ.)

2009-10-09

We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

Weather Instruments.

Science.gov (United States)

Brantley, L. Reed, Sr.; Demanche, Edna L.; Klemm, E. Barbara; Kyselka, Will; Phillips, Edwin A.; Pottenger, Francis M.; Yamamoto, Karen N.; Young, Donald B.

This booklet presents some activities to measure various weather phenomena. Directions for constructing a weather station are included. Instruments including rain gauges, thermometers, wind vanes, wind speed devices, humidity devices, barometers, atmospheric observations, a dustfall jar, sticky-tape can, detection of gases in the air, and pH of…

A Milestone in Commercial Space Weather: USTAR Center for Space Weather

Science.gov (United States)

Tobiska, W.; Schunk, R. W.; Sojka, J. J.; Thompson, D. C.; Scherliess, L.; Zhu, L.; Gardner, L. C.

2009-12-01

As of 2009, Utah State University (USU) hosts a new organization to develop commercial space weather applications using funding that has been provided by the State of Utah’s Utah Science Technology and Research (USTAR) initiative. The USTAR Center for Space Weather (UCSW) is located on the USU campus in Logan, Utah and is developing innovative applications for mitigating adverse space weather effects in technological systems. Space weather’s effects upon the near-Earth environment are due to dynamic changes in the Sun’s photons, particles, and fields. Of the space environment domains that are affected by space weather, the ionosphere is the key region that affects communication and navigation systems. The UCSW has developed products for users of systems that are affected by space weather-driven ionospheric changes. For example, on September 1, 2009 USCW released, in conjunction with Space Environment Technologies, the world’s first real-time space weather via an iPhone app. Space WX displays the real-time, current global ionosphere total electron content along with its space weather drivers; it is available through the Apple iTunes store and is used around the planet. The Global Assimilation of Ionospheric Measurements (GAIM) system is now being run operationally in real-time at UCSW with the continuous ingestion of hundreds of global data streams to dramatically improve the ionosphere’s characterization. We discuss not only funding and technical advances that have led to current products but also describe the direction for UCSW that includes partnering opportunities for moving commercial space weather into fully automated specification and forecasting over the next half decade.

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

Science.gov (United States)

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

Synoptic weather types associated with critical fire weather

Science.gov (United States)

Mark J. Schroeder; Monte Glovinsky; Virgil F. Hendricks; Frank C. Hood; Melvin K. Hull; Henry L. Jacobson; Robert Kirkpatrick; Daniel W. Krueger; Lester P. Mallory; Albert G. Oeztel; Robert H. Reese; Leo A. Sergius; Charles E. Syverson

1964-01-01

Recognizing that weather is an important factor in the spread of both urban and wildland fires, a study was made of the synoptic weather patterns and types which produce strong winds, low relative humidities, high temperatures, and lack of rainfall--the conditions conducive to rapid fire spread. Such historic fires as the San Francisco fire of 1906, the Berkeley fire...

Assessment of marine weather forecasts over the Indian sector of Southern Ocean

Science.gov (United States)

Gera, Anitha; Mahapatra, D. K.; Sharma, Kuldeep; Prakash, Satya; Mitra, A. K.; Iyengar, G. R.; Rajagopal, E. N.; Anilkumar, N.

2017-09-01

The Southern Ocean (SO) is one of the important regions where significant processes and feedbacks of the Earth's climate take place. Expeditions to the SO provide useful data for improving global weather/climate simulations and understanding many processes. Some of the uncertainties in these weather/climate models arise during the first few days of simulation/forecast and do not grow much further. NCMRWF issued real-time five day weather forecasts of mean sea level pressure, surface winds, winds at 500 hPa & 850 hPa and rainfall, daily to NCAOR to provide guidance for their expedition to Indian sector of SO during the austral summer of 2014-2015. Evaluation of the skill of these forecasts indicates possible error growth in the atmospheric model at shorter time scales. The error growth is assessed using the model analysis/reanalysis, satellite data and observations made during the expedition. The observed variability of sub-seasonal rainfall associated with mid-latitude systems is seen to exhibit eastward propagations and are well reproduced in the model forecasts. All cyclonic disturbances including the sub-polar lows and tropical cyclones that occurred during this period were well captured in the model forecasts. Overall, this model performs reasonably well over the Indian sector of the SO in medium range time scale.

Weatherization: Wyoming's Hidden Resource; Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

Wyoming demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

Weather derivatives or how an energy company can hedge its weather risks

International Nuclear Information System (INIS)

Tahghighi, A.; Carpentier, Ph.

2000-01-01

This paper gives a detailed overview of weather derivatives and explains where this new class of financial products falls. The emergence of weather derivatives came about as a response to a need in the energy sector to hedge this sector's weather risks. This article focuses on the nature of these financial contracts, what they include and how they are priced. This article concludes by stating that energy companies in Europe can no longer afford to remain exposed to weather risks in an increasingly privatized and competitive market

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

Science.gov (United States)

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

Formation of halloysite from feldspar: Low temperature, artificial weathering versus natural weathering

Science.gov (United States)

Parham, Walter E.

1969-01-01

Weathering products formed on surfaces of both potassium and plagioclase feldspar (An70), which were continuously leached in a Soxhlet extraction apparatus for 140 days with 7.21 of distilled water per day at a temperature of approximately 78°C, are morphologically identical to natural products developed on potassium feldspars weathered under conditions of good drainage in the humid tropics. The new products, which first appear as tiny bumps on the feldspar surface, start to develop mainly at exposed edges but also at apparently random sites on flat cleavage surfaces. As weathering continues, the bumps grow outward from the feldspar surface to form tapered projections, which then develop into wide-based thin films or sheets. The thin sheets of many projections merge laterally to form one continuous flame-shaped sheet. The sheets formed on potassium feldspars may then roll to form tubes that are inclined at a high angle to the feldspar surface. Etch pits of triangular outline on the artificially weathered potassium feldspars serve as sites for development of continuous, non-rolled, hollow tubes. It is inferred from its morphology that this weathering product is halloysite or its primitive form. The product of naturally weathered potassium feldspars is halloysite . 4H2O.The flame-shaped films or sheets formed on artificially weathered plagioclase feldspar do not develop into hollow tubes, but instead give rise to a platy mineral that is most probably boehmite. These plates form within the flame-shaped films, and with continued weathering are released as the film deteriorates. There is no indication from this experiment that platy pseudohexagonal kaolinite forms from any of these minerals under the initial stage of weathering.

Understanding, representing and communicating earth system processes in weather and climate within CNRCWP

Science.gov (United States)

Sushama, Laxmi; Arora, Vivek; de Elia, Ramon; Déry, Stephen; Duguay, Claude; Gachon, Philippe; Gyakum, John; Laprise, René; Marshall, Shawn; Monahan, Adam; Scinocca, John; Thériault, Julie; Verseghy, Diana; Zwiers, Francis

2017-04-01

The Canadian Network for Regional Climate and Weather Processes (CNRCWP) provides significant advances and innovative research towards the ultimate goal of reducing uncertainty in numerical weather prediction and climate projections for Canada's Northern and Arctic regions. This talk will provide an overview of the Network and selected results related to the assessment of the added value of high-resolution modelling that has helped fill critical knowledge gaps in understanding the dynamics of extreme temperature and precipitation events and the complex land-atmosphere interactions and feedbacks in Canada's northern and Arctic regions. In addition, targeted developments in the Canadian regional climate model, that facilitate direct application of model outputs in impact and adaptation studies, particularly those related to the water, energy and infrastructure sectors will also be discussed. The close collaboration between the Network and its partners and end users contributed significantly to this effort.

Assessment of statistical uncertainty in the quantitative analysis of solid samples in motion using laser-induced breakdown spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Cabalin, L.M.; Gonzalez, A. [Department of Analytical Chemistry, University of Malaga, E-29071 Malaga (Spain); Ruiz, J. [Department of Applied Physics I, University of Malaga, E-29071 Malaga (Spain); Laserna, J.J., E-mail: laserna@uma.e [Department of Analytical Chemistry, University of Malaga, E-29071 Malaga (Spain)

2010-08-15

Statistical uncertainty in the quantitative analysis of solid samples in motion by laser-induced breakdown spectroscopy (LIBS) has been assessed. For this purpose, a LIBS demonstrator was designed and constructed in our laboratory. The LIBS system consisted of a laboratory-scale conveyor belt, a compact optical module and a Nd:YAG laser operating at 532 nm. The speed of the conveyor belt was variable and could be adjusted up to a maximum speed of 2 m s{sup -1}. Statistical uncertainty in the analytical measurements was estimated in terms of precision (reproducibility and repeatability) and accuracy. The results obtained by LIBS on shredded scrap samples under real conditions have demonstrated that the analytical precision and accuracy of LIBS is dependent on the sample geometry, position on the conveyor belt and surface cleanliness. Flat, relatively clean scrap samples exhibited acceptable reproducibility and repeatability; by contrast, samples with an irregular shape or a dirty surface exhibited a poor relative standard deviation.

Assessment of statistical uncertainty in the quantitative analysis of solid samples in motion using laser-induced breakdown spectroscopy

Science.gov (United States)

Cabalín, L. M.; González, A.; Ruiz, J.; Laserna, J. J.

2010-08-01

Statistical uncertainty in the quantitative analysis of solid samples in motion by laser-induced breakdown spectroscopy (LIBS) has been assessed. For this purpose, a LIBS demonstrator was designed and constructed in our laboratory. The LIBS system consisted of a laboratory-scale conveyor belt, a compact optical module and a Nd:YAG laser operating at 532 nm. The speed of the conveyor belt was variable and could be adjusted up to a maximum speed of 2 m s - 1 . Statistical uncertainty in the analytical measurements was estimated in terms of precision (reproducibility and repeatability) and accuracy. The results obtained by LIBS on shredded scrap samples under real conditions have demonstrated that the analytical precision and accuracy of LIBS is dependent on the sample geometry, position on the conveyor belt and surface cleanliness. Flat, relatively clean scrap samples exhibited acceptable reproducibility and repeatability; by contrast, samples with an irregular shape or a dirty surface exhibited a poor relative standard deviation.

Assessment of statistical uncertainty in the quantitative analysis of solid samples in motion using laser-induced breakdown spectroscopy

International Nuclear Information System (INIS)

Cabalin, L.M.; Gonzalez, A.; Ruiz, J.; Laserna, J.J.

2010-01-01

Statistical uncertainty in the quantitative analysis of solid samples in motion by laser-induced breakdown spectroscopy (LIBS) has been assessed. For this purpose, a LIBS demonstrator was designed and constructed in our laboratory. The LIBS system consisted of a laboratory-scale conveyor belt, a compact optical module and a Nd:YAG laser operating at 532 nm. The speed of the conveyor belt was variable and could be adjusted up to a maximum speed of 2 m s -1 . Statistical uncertainty in the analytical measurements was estimated in terms of precision (reproducibility and repeatability) and accuracy. The results obtained by LIBS on shredded scrap samples under real conditions have demonstrated that the analytical precision and accuracy of LIBS is dependent on the sample geometry, position on the conveyor belt and surface cleanliness. Flat, relatively clean scrap samples exhibited acceptable reproducibility and repeatability; by contrast, samples with an irregular shape or a dirty surface exhibited a poor relative standard deviation.

Waste glass weathering

International Nuclear Information System (INIS)

Bates, J.K.; Buck, E.C.

1994-01-01

The weathering of glass is reviewed by examining processes that affect the reaction of commercial, historical, natural, and nuclear waste glass under conditions of contact with humid air and slowly dripping water, which may lead to immersion in nearly static solution. Radionuclide release data from weathered glass under conditions that may exist in an unsaturated environment are presented and compared to release under standard leaching conditions. While the comparison between the release under weathering and leaching conditions is not exact, due to variability of reaction in humid air, evidence is presented of radionuclide release under a variety of conditions. These results suggest that both the amount and form of radionuclide release can be affected by the weathering of glass

Weather Information Processing

Science.gov (United States)

1991-01-01

Science Communications International (SCI), formerly General Science Corporation, has developed several commercial products based upon experience acquired as a NASA Contractor. Among them are METPRO, a meteorological data acquisition and processing system, which has been widely used, RISKPRO, an environmental assessment system, and MAPPRO, a geographic information system. METPRO software is used to collect weather data from satellites, ground-based observation systems and radio weather broadcasts to generate weather maps, enabling potential disaster areas to receive advance warning. GSC's initial work for NASA Goddard Space Flight Center resulted in METPAK, a weather satellite data analysis system. METPAK led to the commercial METPRO system. The company also provides data to other government agencies, U.S. embassies and foreign countries.

Calibration Uncertainties in the Droplet Measurement Technologies Cloud Condensation Nuclei Counter

Science.gov (United States)

Hibert, Kurt James

Cloud condensation nuclei (CCN) serve as the nucleation sites for the condensation of water vapor in Earth's atmosphere and are important for their effect on climate and weather. The influence of CCN on cloud radiative properties (aerosol indirect effect) is the most uncertain of quantified radiative forcing changes that have occurred since pre-industrial times. CCN influence the weather because intrinsic and extrinsic aerosol properties affect cloud formation and precipitation development. To quantify these effects, it is necessary to accurately measure CCN, which requires accurate calibrations using a consistent methodology. Furthermore, the calibration uncertainties are required to compare measurements from different field projects. CCN uncertainties also aid the integration of CCN measurements with atmospheric models. The commercially available Droplet Measurement Technologies (DMT) CCN Counter is used by many research groups, so it is important to quantify its calibration uncertainty. Uncertainties in the calibration of the DMT CCN counter exist in the flow rate and supersaturation values. The concentration depends on the accuracy of the flow rate calibration, which does not have a large (4.3 %) uncertainty. The supersaturation depends on chamber pressure, temperature, and flow rate. The supersaturation calibration is a complex process since the chamber's supersaturation must be inferred from a temperature difference measurement. Additionally, calibration errors can result from the Kohler theory assumptions, fitting methods utilized, the influence of multiply-charged particles, and calibration points used. In order to determine the calibration uncertainties and the pressure dependence of the supersaturation calibration, three calibrations are done at each pressure level: 700, 840, and 980 hPa. Typically 700 hPa is the pressure used for aircraft measurements in the boundary layer, 840 hPa is the calibration pressure at DMT in Boulder, CO, and 980 hPa is the

Sensitivity and uncertainty analysis for fission product decay heat calculations

International Nuclear Information System (INIS)

Rebah, J.; Lee, Y.K.; Nimal, J.C.; Nimal, B.; Luneville, L.; Duchemin, B.

1994-01-01

The calculated uncertainty in decay heat due to the uncertainty in basic nuclear data given in the CEA86 Library, is presented. Uncertainties in summation calculation arise from several sources: fission product yields, half-lives and average decay energies. The correlation between basic data is taken into account. The uncertainty analysis were obtained for thermal-neutron-induced fission of U235 and Pu239 in the case of burst fission and irradiation time. The calculated decay heat in this study is compared with experimental results and with new calculation using the JEF2 Library. (from authors) 6 figs., 19 refs

Wacky Weather

Science.gov (United States)

Sabarre, Amy; Gulino, Jacqueline

2013-01-01

What do a leaf blower, water hose, fan, and ice cubes have in common? Ask the students who participated in an integrative science, technology, engineering, and mathematics (I-STEM) education unit, "Wacky Weather," and they will tell say "fun and severe weather"--words one might not have expected! The purpose of the unit…

The Weather and Ménière’s Disease: A Longitudinal Analysis in the UK

Science.gov (United States)

Schmidt, Wiebke; Sarran, Christophe; Ronan, Natalie; Barrett, George; Whinney, David J.; Fleming, Lora E.; Osborne, Nicholas J.; Tyrrell, Jessica

2016-01-01

Hypothesis Changes in the weather influence symptom severity in Ménière’s disease (MD). Background MD is an unpredictable condition that significantly impacts on quality of life. It is suggested that fluctuations in the weather, especially atmospheric pressure may influence the symptoms of MD. However, to date, limited research has investigated the impact of the weather on MD. Methods In a longitudinal study, a mobile phone application collected data from 397 individuals (277 females and 120 males with an average age of 50 yr) from the UK reporting consultant-diagnosed MD. Daily symptoms (vertigo, aural fullness, tinnitus, hearing loss, and attack prevalence) and GPS locations were collected; these data were linked with Met Office weather data (including atmospheric pressure, humidity, temperature, visibility, and wind speed). Results Symptom severity and attack prevalence were reduced on days when atmospheric pressure was higher. When atmospheric pressure was below 1,013 hectopascals, the risk of an attack was 1.30 (95% confidence interval: 1.10, 1.54); when the humidity was above 90%, the risk of an attack was 1.26 (95% confidence interval 1.06, 1.49). Conclusion This study provides the strongest evidence to date that changes in atmospheric pressure and humidity are associated with symptom exacerbation in MD. Improving our understanding of the role of weather and other environmental triggers in Ménière’s may reduce the uncertainty associated with living with this condition, significantly contributing to improved quality of life. PMID:27861300

The uncertainties in estimating measurement uncertainties

International Nuclear Information System (INIS)

Clark, J.P.; Shull, A.H.

1994-01-01

All measurements include some error. Whether measurements are used for accountability, environmental programs or process support, they are of little value unless accompanied by an estimate of the measurements uncertainty. This fact is often overlooked by the individuals who need measurements to make decisions. This paper will discuss the concepts of measurement, measurements errors (accuracy or bias and precision or random error), physical and error models, measurement control programs, examples of measurement uncertainty, and uncertainty as related to measurement quality. Measurements are comparisons of unknowns to knowns, estimates of some true value plus uncertainty; and are no better than the standards to which they are compared. Direct comparisons of unknowns that match the composition of known standards will normally have small uncertainties. In the real world, measurements usually involve indirect comparisons of significantly different materials (e.g., measuring a physical property of a chemical element in a sample having a matrix that is significantly different from calibration standards matrix). Consequently, there are many sources of error involved in measurement processes that can affect the quality of a measurement and its associated uncertainty. How the uncertainty estimates are determined and what they mean is as important as the measurement. The process of calculating the uncertainty of a measurement itself has uncertainties that must be handled correctly. Examples of chemistry laboratory measurement will be reviewed in this report and recommendations made for improving measurement uncertainties

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.

Science.gov (United States)

MacLeod, D A; Morse, A P

2014-12-02

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Quantification of Airfoil Geometry-Induced Aerodynamic Uncertainties---Comparison of Approaches

KAUST Repository

Liu, Dishi

2015-04-14

Uncertainty quantification in aerodynamic simulations calls for efficient numerical methods to reduce computational cost, especially for uncertainties caused by random geometry variations which involve a large number of variables. This paper compares five methods, including quasi-Monte Carlo quadrature, polynomial chaos with coefficients determined by sparse quadrature and by point collocation, radial basis function and a gradient-enhanced version of kriging, and examines their efficiency in estimating statistics of aerodynamic performance upon random perturbation to the airfoil geometry which is parameterized by independent Gaussian variables. The results show that gradient-enhanced surrogate methods achieve better accuracy than direct integration methods with the same computational cost.

Quantification of Airfoil Geometry-Induced Aerodynamic Uncertainties---Comparison of Approaches

KAUST Repository

Liu, Dishi; Litvinenko, Alexander; Schillings, Claudia; Schulz, Volker

2015-01-01

Uncertainty quantification in aerodynamic simulations calls for efficient numerical methods to reduce computational cost, especially for uncertainties caused by random geometry variations which involve a large number of variables. This paper compares five methods, including quasi-Monte Carlo quadrature, polynomial chaos with coefficients determined by sparse quadrature and by point collocation, radial basis function and a gradient-enhanced version of kriging, and examines their efficiency in estimating statistics of aerodynamic performance upon random perturbation to the airfoil geometry which is parameterized by independent Gaussian variables. The results show that gradient-enhanced surrogate methods achieve better accuracy than direct integration methods with the same computational cost.

THE APPLICABILITY OF EXISTING COMPUTER TECHNOLOGY TO AUTOMATE FUZZY SYNTHESIS OF TRAFFIC LIGHT UAV IN ADVERSE WEATHER CONDITIONS

Directory of Open Access Journals (Sweden)

L. N. Lysenko

2014-01-01

Full Text Available The results of the analysis of the applicability of known application software systems for automated synthesis of fuzzy control traffic light UAV during its flight in adverse weather conditions. The solution is based on a previously formulated and put into consideration the principle of permissible limited a priori estimation of the uncertainty of aerodynamic characteristics of UAVs.

Weather Radar Stations

Data.gov (United States)

Department of Homeland Security — These data represent Next-Generation Radar (NEXRAD) and Terminal Doppler Weather Radar (TDWR) weather radar stations within the US. The NEXRAD radar stations are...

Potential and costs of carbon dioxide removal by enhanced weathering of rocks

Science.gov (United States)

Strefler, Jessica; Amann, Thorben; Bauer, Nico; Kriegler, Elmar; Hartmann, Jens

2018-03-01

The chemical weathering of rocks currently absorbs about 1.1 Gt CO2 a-1 being mainly stored as bicarbonate in the ocean. An enhancement of this slow natural process could remove substantial amounts of CO2 from the atmosphere, aiming to offset some unavoidable anthropogenic emissions in order to comply with the Paris Agreement, while at the same time it may decrease ocean acidification. We provide the first comprehensive assessment of economic costs, energy requirements, technical parameterization, and global and regional carbon removal potential. The crucial parameters defining this potential are the grain size and weathering rates. The main uncertainties about the potential relate to weathering rates and rock mass that can be integrated into the soil. The discussed results do not specifically address the enhancement of weathering through microbial processes, feedback of geogenic nutrient release, and bioturbation. We do not only assess dunite rock, predominantly bearing olivine (in the form of forsterite) as the mineral that has been previously proposed to be best suited for carbon removal, but focus also on basaltic rock to minimize potential negative side effects. Our results show that enhanced weathering is an option for carbon dioxide removal that could be competitive already at 60 US  t-1 CO2 removed for dunite, but only at 200 US  t-1 CO2 removed for basalt. The potential carbon removal on cropland areas could be as large as 95 Gt CO2 a-1 for dunite and 4.9 Gt CO2 a-1 for basalt. The best suited locations are warm and humid areas, particularly in India, Brazil, South-East Asia and China, where almost 75% of the global potential can be realized. This work presents a techno-economic assessment framework, which also allows for the incorporation of further processes.

Internet Weather Source

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The National Weather Service (NWS) National Telecommunications Gateway provides weather, hydrologic, and climate forecasts and warnings for the United States, its...

Uncertainty analysis of atmospheric friction torque on the solid Earth

Directory of Open Access Journals (Sweden)

Haoming Yan

2016-05-01

Full Text Available The wind stress acquired from European Centre for Medium-Range Weather Forecasts (ECMWF, National Centers for Environmental Prediction (NCEP climate models and QSCAT satellite observations are analyzed by using frequency-wavenumber spectrum method. The spectrum of two climate models, i.e., ECMWF and NCEP, is similar for both 10 m wind data and model output wind stress data, which indicates that both the climate models capture the key feature of wind stress. While the QSCAT wind stress data shows the similar characteristics with the two climate models in both spectrum domain and the spatial distribution, but with a factor of approximately 1.25 times larger than that of climate models in energy. These differences show the uncertainty in the different wind stress products, which inevitably cause the atmospheric friction torque uncertainties on solid Earth with a 60% departure in annual amplitude, and furtherly affect the precise estimation of the Earth's rotation.

Mariners Weather Log

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Mariners Weather Log (MWL) is a publication containing articles, news and information about marine weather events and phenomena, worldwide environmental impact...

Pilot Weather Reports

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Aviation weather reports relayed from pilots to FAA air traffic controllers or National Weather Service personnel. Elements include sky cover, turbulence, wind...

Do oil shocks predict economic policy uncertainty?

Science.gov (United States)

Rehman, Mobeen Ur

2018-05-01

Oil price fluctuations have influential role in global economic policies for developed as well as emerging countries. I investigate the role of international oil prices disintegrated into structural (i) oil supply shock, (ii) aggregate demand shock and (iii) oil market specific demand shocks, based on the work of Kilian (2009) using structural VAR framework on economic policies uncertainty of sampled markets. Economic policy uncertainty, due to its non-linear behavior is modeled in a regime switching framework with disintegrated structural oil shocks. Our results highlight that Indian, Spain and Japanese economic policy uncertainty responds to the global oil price shocks, however aggregate demand shocks fail to induce any change. Oil specific demand shocks are significant only for China and India in high volatility state.

Surface Weather Observations

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Surface Weather Observation Collection consists primarily of hourly, synoptic, daily, and monthly forms submitted to the archive by the National Weather Service...

Radar Weather Observation

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Radar Weather Observation is a set of archived historical manuscripts stored on microfiche. The primary source of these radar weather observations manuscript records...

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

Science.gov (United States)

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

Daily Weather Records

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These daily weather records were compiled from a subset of stations in the Global Historical Climatological Network (GHCN)-Daily dataset. A weather record is...

Differences in the importance of weather and weather-based decisions among campers in Ontario parks (Canada)

Science.gov (United States)

Hewer, Micah J.; Scott, Daniel J.; Gough, William A.

2017-10-01

Parks and protected areas represent an important resource for tourism in Canada, in which camping is a common recreational activity. The important relationship between weather and climate with recreation and tourism has been widely acknowledged within the academic literature. Howbeit, the need for activity-specific assessments has been identified as an on-going need for future research in the field of tourism climatology. Furthermore, very little is known about the interrelationships between personal characteristics and socio-demographics with weather preferences and behavioural thresholds. This study uses a stated climate preferences approach (survey responses) to explore differences in the importance of weather and related weather-based decisions among summer campers in Ontario parks. Statistically significant differences were found among campers for each of the four dependent variables tested in this study. Physically active campers placed greater importance on weather but were still more tolerant of adverse weather conditions. Older campers placed greater importance on weather. Campers travelling shorter distances placed greater importance on weather and were more likely to leave the park early due to adverse weather. Campers staying for longer periods of time were less likely to leave early due to weather and were willing to endure longer durations of adverse weather conditions. Beginner campers placed greater importance on weather, were more likely to leave early due to weather and recorded lower temporal weather thresholds. The results of this study contribute to the study of tourism climatology by furthering understanding of how personal characteristics such as gender, age, activity selection, trip duration, distance travelled, travel experience and life cycles affect weather preferences and decisions, focusing this time on recreational camping in a park tourism context.

Space Weather Effects Produced by the Ring Current Particles

Science.gov (United States)

Ganushkina, Natalia; Jaynes, Allison; Liemohn, Michael

2017-11-01

One of the definitions of space weather describes it as the time-varying space environment that may be hazardous to technological systems in space and/or on the ground and/or endanger human health or life. The ring current has its contributions to space weather effects, both in terms of particles, ions and electrons, which constitute it, and magnetic and electric fields produced and modified by it at the ground and in space. We address the main aspects of the space weather effects from the ring current starting with brief review of ring current discovery and physical processes and the Dst-index and predictions of the ring current and storm occurrence based on it. Special attention is paid to the effects on satellites produced by the ring current electrons. The ring current is responsible for several processes in the other inner magnetosphere populations, such as the plasmasphere and radiation belts which is also described. Finally, we discuss the ring current influence on the ionosphere and the generation of geomagnetically induced currents (GIC).

NASA Aviation Safety Program Weather Accident Prevention/weather Information Communications (WINCOMM)

Science.gov (United States)

Feinberg, Arthur; Tauss, James; Chomos, Gerald (Technical Monitor)

2002-01-01

Weather is a contributing factor in approximately 25-30 percent of general aviation accidents. The lack of timely, accurate and usable weather information to the general aviation pilot in the cockpit to enhance pilot situational awareness and improve pilot judgment remains a major impediment to improving aviation safety. NASA Glenn Research Center commissioned this 120 day weather datalink market survey to assess the technologies, infrastructure, products, and services of commercial avionics systems being marketed to the general aviation community to address these longstanding safety concerns. A market survey of companies providing or proposing to provide graphical weather information to the general aviation cockpit was conducted. Fifteen commercial companies were surveyed. These systems are characterized and evaluated in this report by availability, end-user pricing/cost, system constraints/limits and technical specifications. An analysis of market survey results and an evaluation of product offerings were made. In addition, recommendations to NASA for additional research and technology development investment have been made as a result of this survey to accelerate deployment of cockpit weather information systems for enhancing aviation safety.

GEOSS interoperability for Weather, Ocean and Water

Science.gov (United States)

Richardson, David; Nyenhuis, Michael; Zsoter, Ervin; Pappenberger, Florian

2013-04-01

"Understanding the Earth system — its weather, climate, oceans, atmosphere, water, land, geodynamics, natural resources, ecosystems, and natural and human-induced hazards — is crucial to enhancing human health, safety and welfare, alleviating human suffering including poverty, protecting the global environment, reducing disaster losses, and achieving sustainable development. Observations of the Earth system constitute critical input for advancing this understanding." With this in mind, the Group on Earth Observations (GEO) started implementing the Global Earth Observation System of Systems (GEOSS). GEOWOW, short for "GEOSS interoperability for Weather, Ocean and Water", is supporting this objective. GEOWOW's main challenge is to improve Earth observation data discovery, accessibility and exploitability, and to evolve GEOSS in terms of interoperability, standardization and functionality. One of the main goals behind the GEOWOW project is to demonstrate the value of the TIGGE archive in interdisciplinary applications, providing a vast amount of useful and easily accessible information to the users through the GEO Common Infrastructure (GCI). GEOWOW aims at developing funcionalities that will allow easy discovery, access and use of TIGGE archive data and of in-situ observations, e.g. from the Global Runoff Data Centre (GRDC), to support applications such as river discharge forecasting.TIGGE (THORPEX Interactive Grand Global Ensemble) is a key component of THORPEX: a World Weather Research Programme to accelerate the improvements in the accuracy of 1-day to 2 week high-impact weather forecasts for the benefit of humanity. The TIGGE archive consists of ensemble weather forecast data from ten global NWP centres, starting from October 2006, which has been made available for scientific research. The TIGGE archive has been used to analyse hydro-meteorological forecasts of flooding in Europe as well as in China. In general the analysis has been favourable in terms of

'Weather Value at Risk': A uniform approach to describe and compare sectoral income risks from climate change.

Science.gov (United States)

Prettenthaler, Franz; Köberl, Judith; Bird, David Neil

2016-02-01

We extend the concept of 'Weather Value at Risk' - initially introduced to measure the economic risks resulting from current weather fluctuations - to describe and compare sectoral income risks from climate change. This is illustrated using the examples of wheat cultivation and summer tourism in (parts of) Sardinia. Based on climate scenario data from four different regional climate models we study the change in the risk of weather-related income losses between some reference (1971-2000) and some future (2041-2070) period. Results from both examples suggest an increase in weather-related risks of income losses due to climate change, which is somewhat more pronounced for summer tourism. Nevertheless, income from wheat cultivation is at much higher risk of weather-related losses than income from summer tourism, both under reference and future climatic conditions. A weather-induced loss of at least 5% - compared to the income associated with average reference weather conditions - shows a 40% (80%) probability of occurrence in the case of wheat cultivation, but only a 0.4% (16%) probability of occurrence in the case of summer tourism, given reference (future) climatic conditions. Whereas in the agricultural example increases in the weather-related income risks mainly result from an overall decrease in average wheat yields, the heightened risk in the tourism example stems mostly from a change in the weather-induced variability of tourism incomes. With the extended 'Weather Value at Risk' concept being able to capture both, impacts from changes in the mean and the variability of the climate, it is a powerful tool for presenting and disseminating the results of climate change impact assessments. Due to its flexibility, the concept can be applied to any economic sector and therefore provides a valuable tool for cross-sectoral comparisons of climate change impacts, but also for the assessment of the costs and benefits of adaptation measures. Copyright © 2015 Elsevier B

Weatherization Makes Headlines in Connecticut: Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

Connecticut demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

Weatherization Makes Headlines in Connecticut: Weatherization Assistance Close-Up Fact Sheet

Energy Technology Data Exchange (ETDEWEB)

D& R International

2001-10-10

Connecticut demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes.

Winter Weather Emergencies

Science.gov (United States)

Severe winter weather can lead to health and safety challenges. You may have to cope with Cold related health problems, including ... there are no guarantees of safety during winter weather emergencies, you can take actions to protect yourself. ...

New York Signals Weatherization Savings: Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

New York demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

New York Signals Weatherization Savings: Weatherization Assistance Close-Up Fact Sheet

Energy Technology Data Exchange (ETDEWEB)

D& R International

2001-10-10

New York demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes.

NASA GSFC Space Weather Center - Innovative Space Weather Dissemination: Web-Interfaces, Mobile Applications, and More

Science.gov (United States)

Maddox, Marlo; Zheng, Yihua; Rastaetter, Lutz; Taktakishvili, A.; Mays, M. L.; Kuznetsova, M.; Lee, Hyesook; Chulaki, Anna; Hesse, Michael; Mullinix, Richard;

The effects of weathering on the physical and mechanical properties of igneous and metamorphic saprolites

DEFF Research Database (Denmark)

Rocchi, Irene; Coop, M. R.; Maccarini, M.

2017-01-01

The present paper presents three extensive datasets of laboratory testing on weathered geomaterials, which are emblematic of soil types widely found worldwide. The overall dataset includes soils originating from igneous and metamorphic rocks, either coarse or fine grained and having either felsic...... or mafic minerals. In particular, the data are interpreted to highlight the effects that weathering has on the physical and mechanical properties of these natural geomaterials comparing them with published data with the aim to provide a general framework of interpretation that takes into account...... this geological process and links soil mechanics to engineering geology. Generally, weathering induces a reduction in the grain size, both due to physical actions (e.g. opening of grain contacts) and to the chemical decomposition of minerals resulting in the formation of clay minerals. As weathering proceeds...

The waviness of the extratropical jet and daily weather extremes

Science.gov (United States)

Röthlisberger, Matthias; Martius, Olivia; Pfahl, Stephan

2016-04-01

In recent years the Northern Hemisphere mid-latitudes have experienced a large number of weather extremes with substantial socio-economic impact, such as the European and Russian heat waves in 2003 and 2010, severe winter floods in the United Kingdom in 2013/2014 and devastating winter storms such as Lothar (1999) and Xynthia (2010) in Central Europe. These have triggered an engaged debate within the scientific community on the role of human induced climate change in the occurrence of such extremes. A key element of this debate is the hypothesis that the waviness of the extratropical jet is linked to the occurrence of weather extremes, with a wavier jet stream favouring more extremes. Previous work on this topic is expanded in this study by analyzing the linkage between a regional measure of jet waviness and daily temperature, precipitation and wind gust extremes. We show that indeed such a linkage exists in many regions of the world, however this waviness-extremes linkage varies spatially in strength and sign. Locally, it is strong only where the relevant weather systems, in which the extremes occur, are affected by the jet waviness. Its sign depends on how the frequency of occurrence of the relevant weather systems is correlated with the occurrence of high and low jet waviness. These results go beyond previous studies by noting that also a decrease in waviness could be associated with an enhanced number of some weather extremes, especially wind gust and precipitation extremes over western Europe.

Critical loads - assessment of uncertainty

Energy Technology Data Exchange (ETDEWEB)

Barkman, A.

1998-10-01

The effects of data uncertainty in applications of the critical loads concept were investigated on different spatial resolutions in Sweden and northern Czech Republic. Critical loads of acidity (CL) were calculated for Sweden using the biogeochemical model PROFILE. Three methods with different structural complexity were used to estimate the adverse effects of S0{sub 2} concentrations in northern Czech Republic. Data uncertainties in the calculated critical loads/levels and exceedances (EX) were assessed using Monte Carlo simulations. Uncertainties within cumulative distribution functions (CDF) were aggregated by accounting for the overlap between site specific confidence intervals. Aggregation of data uncertainties within CDFs resulted in lower CL and higher EX best estimates in comparison with percentiles represented by individual sites. Data uncertainties were consequently found to advocate larger deposition reductions to achieve non-exceedance based on low critical loads estimates on 150 x 150 km resolution. Input data were found to impair the level of differentiation between geographical units at all investigated resolutions. Aggregation of data uncertainty within CDFs involved more constrained confidence intervals for a given percentile. Differentiation as well as identification of grid cells on 150 x 150 km resolution subjected to EX was generally improved. Calculation of the probability of EX was shown to preserve the possibility to differentiate between geographical units. Re-aggregation of the 95%-ile EX on 50 x 50 km resolution generally increased the confidence interval for each percentile. Significant relationships were found between forest decline and the three methods addressing risks induced by S0{sub 2} concentrations. Modifying S0{sub 2} concentrations by accounting for the length of the vegetation period was found to constitute the most useful trade-off between structural complexity, data availability and effects of data uncertainty. Data

Fair weather atmospheric electricity

International Nuclear Information System (INIS)

Harrison, R G

2011-01-01

Not long after Franklin's iconic studies, an atmospheric electric field was discovered in 'fair weather' regions, well away from thunderstorms. The origin of the fair weather field was sought by Lord Kelvin, through development of electrostatic instrumentation and early data logging techniques, but was ultimately explained through the global circuit model of C.T.R. Wilson. In Wilson's model, charge exchanged by disturbed weather electrifies the ionosphere, and returns via a small vertical current density in fair weather regions. New insights into the relevance of fair weather atmospheric electricity to terrestrial and planetary atmospheres are now emerging. For example, there is a possible role of the global circuit current density in atmospheric processes, such as cloud formation. Beyond natural atmospheric processes, a novel practical application is the use of early atmospheric electrostatic investigations to provide quantitative information on past urban air pollution.

Aviation & Space Weather Policy Research: Integrating Space Weather Observations & Forecasts into Operations

Science.gov (United States)

Fisher, G.; Jones, B.

2006-12-01

The American Meteorological Society and SolarMetrics Limited are conducting a policy research project leading to recommendations that will increase the safety, reliability, and efficiency of the nation's airline operations through more effective use of space weather forecasts and information. This study, which is funded by a 3-year National Science Foundation grant, also has the support of the Federal Aviation Administration and the Joint Planning and Development Office (JPDO) who is planning the Next Generation Air Transportation System. A major component involves interviewing and bringing together key people in the aviation industry who deal with space weather information. This research also examines public and industrial strategies and plans to respond to space weather information. The focus is to examine policy issues in implementing effective application of space weather services to the management of the nation's aviation system. The results from this project will provide government and industry leaders with additional tools and information to make effective decisions with respect to investments in space weather research and services. While space weather can impact the entire aviation industry, and this project will address national and international issues, the primary focus will be on developing a U.S. perspective for the airlines.

Space Weather Services of Korea

Science.gov (United States)

Yoon, K.; Hong, S.; Jangsuk, C.; Dong Kyu, K.; Jinyee, C.; Yeongoh, C.

2016-12-01

The Korean Space Weather Center (KSWC) of the National Radio Research Agency (RRA) is a government agency which is the official source of space weather information for Korean Government and the primary action agency of emergency measure to severe space weather condition. KSWC's main role is providing alerts, watches, and forecasts in order to minimize the space weather impacts on both of public and commercial sectors of satellites, aviation, communications, navigations, power grids, and etc. KSWC is also in charge of monitoring the space weather condition and conducting research and development for its main role of space weather operation in Korea. In this study, we will present KSWC's recent efforts on development of application-oriented space weather research products and services on user needs, and introduce new international collaborative projects, such as IPS-Driven Enlil model, DREAM model estimating electron in satellite orbit, global network of DSCOVR and STEREO satellites tracking, and ARMAS (Automated Radiation Measurement for Aviation Safety).

Towards assimilation of InSAR data in operational weather models

Science.gov (United States)

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

Weather Information Communications (WINCOMM) Project: Dissemination of Weather Information for the Reduction of Aviation Weather-Related Accident Causal Factors

Science.gov (United States)

Jarrell, Michael; Tanger, Thomas

2004-01-01

Weather Information Communications (WINCOMM) is part of the Weather Accident Prevention (WxAP) Project, which is part of the NASA's Aviation Safety and Security Program. The goals of WINCOMM are to facilitate the exchange of tactical and strategic weather information between air and ground. This viewgraph presentation provides information on data link decision factors, architectures, validation goals. WINCOMM is capable of providing en-route communication air-to-ground, ground-to-air, and air-to-air, even on international or intercontinental flights. The presentation also includes information on the capacity, cost, and development of data links.

Evaluating the influence of chemical weathering on the composition of the continental crust using lithium and its isotopes

Science.gov (United States)

Rudnick, R. L.; Liu, X.

2011-12-01

The continental crust has an "intermediate" bulk composition that is distinct from primary melts of peridotitic mantle (basalt or picrite). This mismatch between the "building blocks" and the "edifice" of the continental crust points to the operation of processes that preferentially remove mafic to ultramafic material from the continents. Such processes include lower crustal recycling (via density foundering or lower crustal subduction - e.g., relamination, Hacker et al., 2011, EPSL), generation of evolved melts via slab melting, and/or chemical weathering. Stable isotope systems document the influence of chemical weathering on the bulk crust composition: the oxygen isotope composition of the bulk crust is distinctly heavier than that of primary, mantle-derived melts (Simon and Lecuyer, 2005, G-cubed) and the Li isotopic composition of the bulk crust is distinctly lighter than that of mantle-derive melts (Teng et al., 2004, GCA; 2008, Chem. Geol.). Both signatures mark the imprint of chemical weathering on the bulk crust composition. Here, we use a simple mass balance model for lithium inputs and outputs from the continental crust to quantify the mass lost due to chemical weathering. We find that a minimum of 15%, a maximum of 60%, and a best estimate of ~40% of the original juvenile rock mass may have been lost via chemical weathering. The accumulated percentage of mass loss due to chemical weathering leads to an average global chemical weathering rate (CWR) of ~ 8×10^9 to 2×10^10 t/yr since 3.5 Ga, which is about an order of magnitude higher than the minimum estimates based on modern rivers (Gaillardet et al., 1999, Chem. Geol.). While we cannot constrain the exact portion of crustal mass loss via chemical weathering, given the uncertainties of the calculation, we can demonstrate that the weathering flux is non-zero. Therefore, chemical weathering must play a role in the evolution of the composition and mass of the continental crust.

Natural weathering of archaeo-metallurgical slags: an analog for present day vitrified wastes

International Nuclear Information System (INIS)

Mahe-le-Carlier, C.

2000-01-01

The study of the natural alteration of ancient vitreous slags (100 to 4000 years) suggests a single global mechanism. In a first stage, weathering consists of a selective extraction of the modifier cations of glass (including Pb and Ba). This phenomenon is associated with an increase of the solution pH, inducing the glass dissolution (Al, Fe). Pb and Ba are extracted from weathered glass. Pb is located in Fe-hydroxides, Ba may form sulfides. The rate of alteration varies from 20 to 180 μm per 1000 years. (authors)

Impacts of extreme weather events on transport infrastructure in Norway

Science.gov (United States)

Frauenfelder, Regula; Solheim, Anders; Isaksen, Ketil; Romstad, Bård; Dyrrdal, Anita V.; Ekseth, Kristine H. H.; Gangstø Skaland, Reidun; Harbitz, Alf; Harbitz, Carl B.; Haugen, Jan E.; Hygen, Hans O.; Haakenstad, Hilde; Jaedicke, Christian; Jónsson, Árni; Klæboe, Ronny; Ludvigsen, Johanna; Meyer, Nele K.; Rauken, Trude; Sverdrup-Thygeson, Kjetil

2016-04-01

century. The increase, both in total precipitation, and in the frequency and intensity of extreme events, is greatest in the west and southwest, and in parts of northern Norway, areas with the highest present precipitation. - Snowfall will increase due to increased precipitation in cold areas inland and at high elevations. In lower lying parts of the country, and along the coast, more precipitation as rain will replace snowfall. - The frequency of near-zero events, with freeze-thaw cycles, which can trigger rock falls, will decrease due to the generally increased temperatures. - The greatest uncertainties in the weather trends are linked to uncertainties in climate and emission scenarios, and to the downscaling. - More than 30% of the total length of road and railroads in Norway is exposed to snow avalanche and rock fall/slide hazard. As an example, one of the most exposed railroads, Raumabanen, has an annual probability of 1/3 to be hit by snow avalanches. - Total costs of geohazard impact on the road infrastructure (major roads only) were estimated to be roughly 100 mill. NOK per year, of which the costs of road closures comprise 70%. The numbers are unevenly distributed throughout the country, reflecting the topographic and climatic variability in Norway.

Combining historical eyewitness accounts on tsunami-induced waves and numerical simulations for getting insights in uncertainty of source parameters

Science.gov (United States)

Rohmer, Jeremy; Rousseau, Marie; Lemoine, Anne; Pedreros, Rodrigo; Lambert, Jerome; benki, Aalae

2017-04-01

Recent tsunami events including the 2004 Indian Ocean tsunami and the 2011 Tohoku tsunami have caused many casualties and damages to structures. Advances in numerical simulation of tsunami-induced wave processes have tremendously improved forecast, hazard and risk assessment and design of early warning for tsunamis. Among the major challenges, several studies have underlined uncertainties in earthquake slip distributions and rupture processes as major contributor on tsunami wave height and inundation extent. Constraining these uncertainties can be performed by taking advantage of observations either on tsunami waves (using network of water level gauge) or on inundation characteristics (using field evidence and eyewitness accounts). Despite these successful applications, combining tsunami observations and simulations still faces several limitations when the problem is addressed for past tsunamis events like 1755 Lisbon. 1) While recent inversion studies can benefit from current modern networks (e.g., tide gauges, sea bottom pressure gauges, GPS-mounted buoys), the number of tide gauges can be very scarce and testimonies on tsunami observations can be limited, incomplete and imprecise for past tsunamis events. These observations often restrict to eyewitness accounts on wave heights (e.g., maximum reached wave height at the coast) instead of the full observed waveforms; 2) Tsunami phenomena involve a large span of spatial scales (from ocean basin scales to local coastal wave interactions), which can make the modelling very demanding: the computation time cost of tsunami simulation can be very prohibitive; often reaching several hours. This often limits the number of allowable long-running simulations for performing the inversion, especially when the problem is addressed from a Bayesian inference perspective. The objective of the present study is to overcome both afore-described difficulties in the view to combine historical observations on past tsunami-induced waves

Alaska Native Weatherization Training and Jobs Program First Steps Toward Tribal Weatherization – Human Capacity Development

Energy Technology Data Exchange (ETDEWEB)

Wiita, Joanne

2013-07-30

The Alaska Native Weatherization Training and Jobs Project expanded weatherization services for tribal members’ homes in southeast Alaska while providing weatherization training and on the job training (OJT) for tribal citizens that lead to jobs and most probably careers in weatherization-related occupations. The program resulted in; (a) 80 Alaska Native citizens provided with skills training in five weatherization training units that were delivered in cooperation with University of Alaska Southeast, in accordance with the U.S. Department of Energy Core Competencies for Weatherization Training that prepared participants for employment in three weatherizationrelated occupations: Installer, Crew Chief, and Auditor; (b) 25 paid OJT training opportunities for trainees who successfully completed the training course; and (c) employed trained personnel that have begun to rehab on over 1,000 housing units for weatherization.

Convection Weather Detection by General Aviation Pilots with Convectional and Data-Linked Graphical Weather Information Sources

Science.gov (United States)

Chamberlain, James P.; Latorella, Kara A.

2001-01-01

This study compares how well general aviation (GA) pilots detect convective weather in flight with different weather information sources. A flight test was conducted in which GA pilot test subjects were given different in-flight weather information cues and flown toward convective weather of moderate or greater intensity. The test subjects were not actually flying the aircraft, but were given pilot tasks representative of the workload and position awareness requirements of the en route portion of a cross country GA flight. On each flight, one test subject received weather cues typical of a flight in visual meteorological conditions (VMC), another received cues typical of flight in instrument meteorological conditions (IMC), and a third received cues typical of flight in IMC but augmented with a graphical weather information system (GWIS). The GWIS provided the subject with near real time data-linked weather products, including a weather radar mosaic superimposed on a moving map with a symbol depicting the aircraft's present position and direction of track. At several points during each flight, the test subjects completed short questionnaires which included items addressing their weather situation awareness and flight decisions. In particular, test subjects were asked to identify the location of the nearest convective cells. After the point of nearest approach to convective weather, the test subjects were asked to draw the location of convective weather on an aeronautical chart, along with the aircraft's present position. This paper reports preliminary results on how accurately test subjects provided with these different weather sources could identify the nearest cell of moderate or greater intensity along their route of flight. Additional flight tests are currently being conducted to complete the data set.

The scope of the Weatherization Assistance Program: The weatherized population and the resource base

Energy Technology Data Exchange (ETDEWEB)

Power, M.; Eisenberg, J.F.; Michels, E. (Economic Opportunity Research Inst., Washington, DC (United States)); Witherspoon, M.J. (National Association for State Community Service Programs, Washington, DC (United States)); Brown, M.A. (Oak Ridge National Lab., TN (United States))

1992-05-01

This study is one of five parts of the US Department of Energy's national evaluation of its Weatherization Assistance Program (WAP). It has three major goals: (1) to enumerate the size and sources of investment in low-income weatherization; (2) to provide a count of the number of low-income units weatherized by all weatherization programs and characterized the type and tenure of those homes; and (3) to document the extent to which the DOE/WAP funding has been expanded though use of external resources.

The scope of the Weatherization Assistance Program: The weatherized population and the resource base

Energy Technology Data Exchange (ETDEWEB)

Power, M.; Eisenberg, J.F.; Michels, E. [Economic Opportunity Research Inst., Washington, DC (United States); Witherspoon, M.J. [National Association for State Community Service Programs, Washington, DC (United States); Brown, M.A. [Oak Ridge National Lab., TN (United States)

1992-05-01

This study is one of five parts of the US Department of Energy`s national evaluation of its Weatherization Assistance Program (WAP). It has three major goals: (1) to enumerate the size and sources of investment in low-income weatherization; (2) to provide a count of the number of low-income units weatherized by all weatherization programs and characterized the type and tenure of those homes; and (3) to document the extent to which the DOE/WAP funding has been expanded though use of external resources.

Space Weather- Physics and Effects

CERN Document Server

Bothmer, Volker

2007-01-01

This book is a state-of-the-art review on the physics of space weather and on space weather impacts on human technology, including manned spaceflight. With contributions from a team of international experts, this comprehensive work covers all aspects of space weather physical processes, and all known aspects of space hazards from humans, both in space and on Earth. Space Weather - Physics and Effects provides the first comprehensive, scientific background of space storms caused by the sun and its impact on geospace focuses on weather issues that have become vital for the development of nationwide technological infrastructures explains magnetic storms on Earth, including the effects of EUV radiation on the atmosphere is an invaluable aid in establishing real-time weather forecasts details the threat that solar effects might have on modern telecommunication systems, including national power grid systems, aircraft and manned spaceflight.

Fabulous Weather Day

Science.gov (United States)

Marshall, Candice; Mogil, H. Michael

2007-01-01

Each year, first graders at Kensington Parkwood Elementary School in Kensington, Maryland, look forward to Fabulous Weather Day. Students learn how meteorologists collect data about the weather, how they study wind, temperature, precipitation, basic types/characteristics of clouds, and how they forecast. The project helps the students grow in…

Seasonal Forecasting of Fire Weather Based on a New Global Fire Weather Database

Science.gov (United States)

Dowdy, Andrew J.; Field, Robert D.; Spessa, Allan C.

2016-01-01

Seasonal forecasting of fire weather is examined based on a recently produced global database of the Fire Weather Index (FWI) system beginning in 1980. Seasonal average values of the FWI are examined in relation to measures of the El Nino-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). The results are used to examine seasonal forecasts of fire weather conditions throughout the world.

Space Weather Products and Tools Used in Auroral Monitoring and Forecasting at CCMC/SWRC

Science.gov (United States)

Zheng, Yihua; Rastaetter, Lutz

2015-01-01

Key points discussed in this chapter are (1) the importance of aurora research to scientific advances and space weather applications, (2) space weather products at CCMC that are relevant to aurora monitoring and forecasting, and (3) the need for more effort from the whole community to achieve a better and long-lead-time forecast of auroral activity. Aurora, as manifestations of solar wind-magnetosphere-ionosphere coupling that occurs in a region of space that is relatively easy to access for sounding rockets, satellites, and other types of observational platforms, serves as a natural laboratory for studying the underlying physics of the complex system. From a space weather application perspective, auroras can cause surface charging of technological assets passing through the region, result in scintillation effects affecting communication and navigation, and cause radar cluttering that hinders military and civilian applications. Indirectly, an aurora and its currents can induce geomagnetically induced currents (GIC) on the ground, which poses major concerns for the wellbeing and operation of power grids, particularly during periods of intense geomagnetic activity. In addition, accurate auroral forecasting is desired for auroral tourism. In this chapter, we first review some of the existing auroral models and discuss past validation efforts. Such efforts are crucial in transitioning a model(s) from research to operations and for further model improvement and development that also benefits scientific endeavors. Then we will focus on products and tools that are used for auroral monitoring and forecasting at the Space Weather Research Center (SWRC). As part of the CCMC (Community Coordinated Modeling Center), SWRC has been providing space weather services since 2010.

Weatherization is a Hit in Michigan: Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

Michigan demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

Weatherization Builds on Delaware's Innovative Past: Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

Delaware demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

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

Science.gov (United States)

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.

Training Early Career Space Weather Researchers and other Space Weather Professionals at the CISM Space Weather Summer School

Science.gov (United States)

Gross, N. A.; Hughes, W.

2011-12-01

This talk will outline the organization of a summer school designed to introduce young professions to a sub-discipline of geophysics. Through out the 10 year life time of the Center for Integrated Space Weather Modeling (CISM) the CISM Team has offered a two week summer school that introduces new graduate students and other interested professional to the fundamentals of space weather. The curriculum covers basic concepts in space physics, the hazards of space weather, and the utility of computer models of the space environment. Graduate students attend from both inside and outside CISM, from all the sub-disciplines involved in space weather (solar, heliosphere, geomagnetic, and aeronomy), and from across the nation and around the world. In addition, between 1/4 and 1/3 of the participants each year are professionals involved in space weather in some way, such as: forecasters from NOAA and the Air Force, Air Force satellite program directors, NASA specialists involved in astronaut radiation safety, and representatives from industries affected by space weather. The summer school has adopted modern pedagogy that has been used successfully at the undergraduate level. A typical daily schedule involves three morning lectures followed by an afternoon lab session. During the morning lectures, student interaction is encouraged using "Timeout to Think" questions and peer instruction, along with question cards for students to ask follow up questions. During the afternoon labs students, working in groups of four, answer thought provoking questions using results from simulations and observation data from a variety of source. Through the interactions with each other and the instructors, as well as social interactions during the two weeks, students network and form bonds that will last them through out their careers. We believe that this summer school can be used as a model for summer schools in a wide variety of disciplines.

Powernext weather, benchmark indices for effective weather risk management; Powernext Weather, des indices de reference pour gerer le risque meteo

Energy Technology Data Exchange (ETDEWEB)

NONE

2006-07-01

According to the U.S. Department of Energy, an estimated 25% of the GNP is affected by weather-related events. The variations in temperature - even small ones - can also have long-lasting effects on the operational results of a company. Among other, the Energy supply sector is sensitive to weather risks: a milder or harsher than usual winter leads to a decrease or increase of energy consumption. The price of electricity on power trading facilities like Powernext is especially sensitive to odd changes in temperatures. Powernext and Meteo-France (the French meteorological agency) have joined expertise in order to promote the use of weather indices in term of decision making or underlying of hedging tools to energy actors, end users from any other sector of activity and specialists of the weather risk hedging. The Powernext Weather indices are made from information collected by Meteo-France's main observation network according to the norms of international meteorology, in areas carefully selected. The gross data are submitted to a thorough review allowing the correction of abnormalities and the reconstitution of missing data. Each index is fashioned to take into account the economic activity in the various regions of the country as represented by each region's population. This demographic information represents a fair approximation of the weight of the regional economic activity. This document presents the Powernext/Meteo France partnership for the elaboration of efficient weather-related risk management indices. (J.S.)

Space Weather Impacts to Conjunction Assessment: A NASA Robotic Orbital Safety Perspective

Science.gov (United States)

Ghrist, Richard; Ghrist, Richard; DeHart, Russel; Newman, Lauri

2013-01-01

National Aeronautics and Space Administration (NASA) recognizes the risk of on-orbit collisions from other satellites and debris objects and has instituted a process to identify and react to close approaches. The charter of the NASA Robotic Conjunction Assessment Risk Analysis (CARA) task is to protect NASA robotic (unmanned) assets from threats posed by other space objects. Monitoring for potential collisions requires formulating close-approach predictions a week or more in the future to determine analyze, and respond to orbital conjunction events of interest. These predictions require propagation of the latest state vector and covariance assuming a predicted atmospheric density and ballistic coefficient. Any differences between the predicted drag used for propagation and the actual drag experienced by the space objects can potentially affect the conjunction event. Therefore, the space environment itself, in particular how space weather impacts atmospheric drag, is an essential element to understand in order effectively to assess the risk of conjunction events. The focus of this research is to develop a better understanding of the impact of space weather on conjunction assessment activities: both accurately determining the current risk and assessing how that risk may change under dynamic space weather conditions. We are engaged in a data-- ]mining exercise to corroborate whether or not observed changes in a conjunction event's dynamics appear consistent with space weather changes and are interested in developing a framework to respond appropriately to uncertainty in predicted space weather. In particular, we use historical conjunction event data products to search for dynamical effects on satellite orbits from changing atmospheric drag. Increased drag is expected to lower the satellite specific energy and will result in the satellite's being 'later' than expected, which can affect satellite conjunctions in a number of ways depending on the two satellites' orbits

Climate Prediction - NOAA's National Weather Service

Science.gov (United States)

Statistical Models... MOS Prod GFS-LAMP Prod Climate Past Weather Predictions Weather Safety Weather Radio National Weather Service on FaceBook NWS on Facebook NWS Director Home > Climate > Predictions Climate Prediction Long range forecasts across the U.S. Climate Prediction Web Sites Climate Prediction

Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

Directory of Open Access Journals (Sweden)

Fei Wang

2017-12-01

Full Text Available Accurate solar photovoltaic (PV power forecasting is an essential tool for mitigating the negative effects caused by the uncertainty of PV output power in systems with high penetration levels of solar PV generation. Weather classification based modeling is an effective way to increase the accuracy of day-ahead short-term (DAST solar PV power forecasting because PV output power is strongly dependent on the specific weather conditions in a given time period. However, the accuracy of daily weather classification relies on both the applied classifiers and the training data. This paper aims to reveal how these two factors impact the classification performance and to delineate the relation between classification accuracy and sample dataset scale. Two commonly used classification methods, K-nearest neighbors (KNN and support vector machines (SVM are applied to classify the daily local weather types for DAST solar PV power forecasting using the operation data from a grid-connected PV plant in Hohhot, Inner Mongolia, China. We assessed the performance of SVM and KNN approaches, and then investigated the influences of sample scale, the number of categories, and the data distribution in different categories on the daily weather classification results. The simulation results illustrate that SVM performs well with small sample scale, while KNN is more sensitive to the length of the training dataset and can achieve higher accuracy than SVM with sufficient samples.

Uncertainty in projected climate change arising from uncertain fossil-fuel emission factors

Science.gov (United States)

Quilcaille, Y.; Gasser, T.; Ciais, P.; Lecocq, F.; Janssens-Maenhout, G.; Mohr, S.

2018-04-01

Emission inventories are widely used by the climate community, but their uncertainties are rarely accounted for. In this study, we evaluate the uncertainty in projected climate change induced by uncertainties in fossil-fuel emissions, accounting for non-CO2 species co-emitted with the combustion of fossil-fuels and their use in industrial processes. Using consistent historical reconstructions and three contrasted future projections of fossil-fuel extraction from Mohr et al we calculate CO2 emissions and their uncertainties stemming from estimates of fuel carbon content, net calorific value and oxidation fraction. Our historical reconstructions of fossil-fuel CO2 emissions are consistent with other inventories in terms of average and range. The uncertainties sum up to a ±15% relative uncertainty in cumulative CO2 emissions by 2300. Uncertainties in the emissions of non-CO2 species associated with the use of fossil fuels are estimated using co-emission ratios varying with time. Using these inputs, we use the compact Earth system model OSCAR v2.2 and a Monte Carlo setup, in order to attribute the uncertainty in projected global surface temperature change (ΔT) to three sources of uncertainty, namely on the Earth system’s response, on fossil-fuel CO2 emission and on non-CO2 co-emissions. Under the three future fuel extraction scenarios, we simulate the median ΔT to be 1.9, 2.7 or 4.0 °C in 2300, with an associated 90% confidence interval of about 65%, 52% and 42%. We show that virtually all of the total uncertainty is attributable to the uncertainty in the future Earth system’s response to the anthropogenic perturbation. We conclude that the uncertainty in emission estimates can be neglected for global temperature projections in the face of the large uncertainty in the Earth system response to the forcing of emissions. We show that this result does not hold for all variables of the climate system, such as the atmospheric partial pressure of CO2 and the

Graphical tools for TV weather presentation

Science.gov (United States)

Najman, M.

2010-09-01

Contemporary meteorology and its media presentation faces in my opinion following key tasks: - Delivering the meteorological information to the end user/spectator in understandable and modern fashion, which follows industry standard of video output (HD, 16:9) - Besides weather icons show also the outputs of numerical weather prediction models, climatological data, satellite and radar images, observed weather as actual as possible. - Does not compromise the accuracy of presented data. - Ability to prepare and adjust the weather show according to actual synoptic situtation. - Ability to refocus and completely adjust the weather show to actual extreme weather events. - Ground map resolution weather data presentation need to be at least 20 m/pixel to be able to follow the numerical weather prediction model resolution. - Ability to switch between different numerical weather prediction models each day, each show or even in the middle of one weather show. - The graphical weather software need to be flexible and fast. The graphical changes nee to be implementable and airable within minutes before the show or even live. These tasks are so demanding and the usual original approach of custom graphics could not deal with it. It was not able to change the show every day, the shows were static and identical day after day. To change the content of the weather show daily was costly and most of the time impossible with the usual approach. The development in this area is fast though and there are several different options for weather predicting organisations such as national meteorological offices and private meteorological companies to solve this problem. What are the ways to solve it? What are the limitations and advantages of contemporary graphical tools for meteorologists? All these questions will be answered.

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

Science.gov (United States)

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...

National Convective Weather Diagnostic

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Current convective hazards identified by the National Convective Weather Detection algorithm. The National Convective Weather Diagnostic (NCWD) is an automatically...

Natural Weathering Exposure Station

Data.gov (United States)

Federal Laboratory Consortium — The Corps of Engineers' Treat Island Natural Weathering Exposure Station is a long-term natural weathering facility used to study concrete durability. Located on the...

Pilot's Automated Weather Support System (PAWSS) concepts demonstration project. Phase 1: Pilot's weather information requirements and implications for weather data systems design

Science.gov (United States)

Crabill, Norman L.; Dash, Ernie R.

1991-01-01

The weather information requirements for pilots and the deficiencies of the current aviation weather support system in meeting these requirements are defined. As the amount of data available to pilots increases significantly in the near future, expert system technology will be needed to assist pilots in assimilating that information. Some other desirable characteristics of an automation-assisted system for weather data acquisition, dissemination, and assimilation are also described.

Managing weather and climate risks to agriculture in North America, Central America and the Caribbean

Directory of Open Access Journals (Sweden)

Harlan D. Shannon

2015-12-01

Full Text Available In recent decades, numerous weather- and climate-related natural disasters have impacted North America, Central America, and the Caribbean, repeatedly demonstrating how vulnerable local agriculture is to extreme episodic events. Given this recent history, and expectations that the frequency and intensity of some episodic events will increase with climate change, it is becoming increasingly important for farmers to proactively manage weather and climate risks to agriculture to protect their livelihoods. Some farmers in this region already apply various strategies to help reduce weather and climate risks and uncertainties, including farming in multiple locations, diversifying crops and varieties, seeking alternative sources of income, and purchasing crop insurance. Such efforts often help farmers maintain a more stable income while also protecting and preserving the productivity of the land. Other farmers, however, have failed to implement basic risk management strategies despite the clear benefits. Reasons for these failures can be attributed to inadequate farmer education and training, a lack of tools to help facilitate the practical application of risk management concepts, and poor communications between the agrometeorological and farming communities. The agrometeorological community can help overcome these obstacles by building upon existing efforts that have successfully educated farmers about weather and climate risks to agriculture and have equipped farmers with the data, tools, and applications necessary to manage these risks. Farmer input is critical to preparing effective educational and training materials and developing user-friendly risk management tools. The agrometeorological community should solicit input from farmers regularly to ensure that farmers are obtaining the information necessary to effectively manage weather and climate risks to agriculture.

Generalized uncertainty principles, effective Newton constant and regular black holes

OpenAIRE

Li, Xiang; Ling, Yi; Shen, You-Gen; Liu, Cheng-Zhou; He, Hong-Sheng; Xu, Lan-Fang

2016-01-01

In this paper, we explore the quantum spacetimes that are potentially connected with the generalized uncertainty principles. By analyzing the gravity-induced quantum interference pattern and the Gedanken for weighting photon, we find that the generalized uncertainty principles inspire the effective Newton constant as same as our previous proposal. A characteristic momentum associated with the tidal effect is suggested, which incorporates the quantum effect with the geometric nature of gravity...

Weather forecast

CERN Document Server

Courtier, P

1994-02-07

Weather prediction is performed using the numerical model of the atmosphere evolution.The evolution equations are derived from the Navier Stokes equation for the adiabatic part but the are very much complicated by the change of phase of water, the radiation porocess and the boundary layer.The technique used operationally is described. Weather prediction is an initial value problem and accurate initial conditions need to be specified. Due to the small number of observations available (105 ) as compared to the dimension of the model state variable (107),the problem is largely underdetermined. Techniques of optimal control and inverse problems are used and have been adapted to the large dimension of our problem. our problem.The at mosphere is a chaotic system; the implication for weather prediction is discussed. Ensemble prediction is used operationally and the technique for generating initial conditions which lead to a numerical divergence of the subsequent forecasts is described.

Surface Weather Observations Hourly

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Standard hourly observations taken at Weather Bureau/National Weather Service offices and airports throughout the United States. Hourly observations began during the...

Land Surface Weather Observations

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — METAR is the international standard code format for hourly surface weather observations. The acronym roughly translates from French as Aviation Routine Weather...

Decomposing the uncertainty in climate impact projections of Dynamic Vegetation Models: a test with the forest models LANDCLIM and FORCLIM

Science.gov (United States)

Cailleret, Maxime; Snell, Rebecca; von Waldow, Harald; Kotlarski, Sven; Bugmann, Harald

2015-04-01

Different levels of uncertainty should be considered in climate impact projections by Dynamic Vegetation Models (DVMs), particularly when it comes to managing climate risks. Such information is useful to detect the key processes and uncertainties in the climate model - impact model chain and may be used to support recommendations for future improvements in the simulation of both climate and biological systems. In addition, determining which uncertainty source is dominant is an important aspect to recognize the limitations of climate impact projections by a multi-model ensemble mean approach. However, to date, few studies have clarified how each uncertainty source (baseline climate data, greenhouse gas emission scenario, climate model, and DVM) affects the projection of ecosystem properties. Focusing on one greenhouse gas emission scenario, we assessed the uncertainty in the projections of a forest landscape model (LANDCLIM) and a stand-scale forest gap model (FORCLIM) that is caused by linking climate data with an impact model. LANDCLIM was used to assess the uncertainty in future landscape properties of the Visp valley in Switzerland that is due to (i) the use of different 'baseline' climate data (gridded data vs. data from weather stations), and (ii) differences in climate projections among 10 GCM-RCM chains. This latter point was also considered for the projections of future forest properties by FORCLIM at several sites along an environmental gradient in Switzerland (14 GCM-RCM chains), for which we also quantified the uncertainty caused by (iii) the model chain specific statistical properties of the climate time-series, and (iv) the stochasticity of the demographic processes included in the model, e.g., the annual number of saplings that establish, or tree mortality. Using methods of variance decomposition analysis, we found that (i) The use of different baseline climate data strongly impacts the prediction of forest properties at the lowest and highest, but

Attribution of extreme weather and climate-related events.

Science.gov (United States)

Stott, Peter A; Christidis, Nikolaos; Otto, Friederike E L; Sun, Ying; Vanderlinden, Jean-Paul; van Oldenborgh, Geert Jan; Vautard, Robert; von Storch, Hans; Walton, Peter; Yiou, Pascal; Zwiers, Francis W

2016-01-01

Extreme weather and climate-related events occur in a particular place, by definition, infrequently. It is therefore challenging to detect systematic changes in their occurrence given the relative shortness of observational records. However, there is a clear interest from outside the climate science community in the extent to which recent damaging extreme events can be linked to human-induced climate change or natural climate variability. Event attribution studies seek to determine to what extent anthropogenic climate change has altered the probability or magnitude of particular events. They have shown clear evidence for human influence having increased the probability of many extremely warm seasonal temperatures and reduced the probability of extremely cold seasonal temperatures in many parts of the world. The evidence for human influence on the probability of extreme precipitation events, droughts, and storms is more mixed. Although the science of event attribution has developed rapidly in recent years, geographical coverage of events remains patchy and based on the interests and capabilities of individual research groups. The development of operational event attribution would allow a more timely and methodical production of attribution assessments than currently obtained on an ad hoc basis. For event attribution assessments to be most useful, remaining scientific uncertainties need to be robustly assessed and the results clearly communicated. This requires the continuing development of methodologies to assess the reliability of event attribution results and further work to understand the potential utility of event attribution for stakeholder groups and decision makers. WIREs Clim Change 2016, 7:23-41. doi: 10.1002/wcc.380 For further resources related to this article, please visit the WIREs website.

Probabilistic numerics and uncertainty in computations.

Science.gov (United States)

Hennig, Philipp; Osborne, Michael A; Girolami, Mark

2015-07-08

We deliver a call to arms for probabilistic numerical methods : algorithms for numerical tasks, including linear algebra, integration, optimization and solving differential equations, that return uncertainties in their calculations. Such uncertainties, arising from the loss of precision induced by numerical calculation with limited time or hardware, are important for much contemporary science and industry. Within applications such as climate science and astrophysics, the need to make decisions on the basis of computations with large and complex data have led to a renewed focus on the management of numerical uncertainty. We describe how several seminal classic numerical methods can be interpreted naturally as probabilistic inference. We then show that the probabilistic view suggests new algorithms that can flexibly be adapted to suit application specifics, while delivering improved empirical performance. We provide concrete illustrations of the benefits of probabilistic numeric algorithms on real scientific problems from astrometry and astronomical imaging, while highlighting open problems with these new algorithms. Finally, we describe how probabilistic numerical methods provide a coherent framework for identifying the uncertainty in calculations performed with a combination of numerical algorithms (e.g. both numerical optimizers and differential equation solvers), potentially allowing the diagnosis (and control) of error sources in computations.

Uncertainties in elemental quantitative analysis by PIXE

International Nuclear Information System (INIS)

Montenegro, E.C.; Baptista, G.B.; Paschoa, A.S.; Barros Leite, C.V.

1979-01-01

The effects of the degree of non-uniformity of the particle beam, matrix composition and matrix thickness in a quantitative elemental analysis by particle induced X-ray emission (PIXE) are discussed and a criterion to evaluate the resulting degree of uncertainty in the mass determination by this method is established. (Auth.)

Coupling of physical erosion and chemical weathering after phases of intense human activity

Science.gov (United States)

Schoonejans, Jerome; Vanacker, Veerle; Opfergelt, Sophie; Ameijeiras-Mariño, Yolanda; Kubik, Peter W.

2014-05-01

Anthropogenic disturbance of natural vegetation profoundly alters the lateral and vertical fluxes of soil nutrients and particles at the land surface. Human-induced acceleration of soil erosion can thereby result in an imbalance between physical erosion, soil production and chemical weathering. The (de-)coupling between physical erosion and chemical weathering in ecosystems with strong anthropogenic disturbances is not yet fully understood, as earlier studies mostly focused on natural ecosystems. In this study, we explore the chemical weathering intensity for four study sites located in the Internal Zone of the Spanish Betic Cordillera. Most of the sites belong to the Nevado-Filabres complex, but are characterized by different rates of long-term exhumation, 10Be catchment-wide denudation and hill slope morphology. Denudation rates are generally low, but show large variation between the three sites (from 23 to 246 mm kyr-1). The magnitude of denudation rates is consistent with longer-term uplift rates derived from marine deposits, fission-track measurements and vertical fault slip rates. Two to three soil profiles were sampled per study site at exposed ridge tops. All soils overly fractured mica schist, and are very thin (< 60cm). In each soil profile, we sampled 5 depth slices, rock fragments and the (weathered) bedrock. In total, 38 soil and 20 rock samples were analyzed for their chemical composition. The chemical weathering intensity is constrained by the Chemical Depletion Fraction that is based on a chemical mass balance approach using Zr as an immobile element. Chemical weathering accounts for 5 to 35% of the total mass lost due to denudation. We observe systematically higher chemical weathering intensities (CDFs) in sites with lower denudation rates (and vice versa), suggesting that weathering is supply-limited. Our measurements of soil elemental losses from 10 soil profiles suggest that the observed variation in chemical weathering is strongly associated

Sun, weather, and climate

International Nuclear Information System (INIS)

Herman, J.R.; Goldberg, R.A.

1985-01-01

The general field of sun-weather/climate relationships that is, apparent weather and climate responses to solar activity is introduced and theoretical and experimental suggestions for further research to identify and investigate the unknown casual mechanisms are provided. Topics of discussion include: (1) solar-related correlation factors and energy sources; (2) long-term climate trends; (3) short-term meteorological correlations; (4) miscellaneous obscuring influences; (5) physical processes and mechanisms; (6) recapitulation of sun-weather relationships; and (7) guidelines for experiments. 300 references

Dealing with unquantifiable uncertainties in landslide modelling for urban risk reduction in developing countries

Science.gov (United States)

Almeida, Susana; Holcombe, Liz; Pianosi, Francesca; Wagener, Thorsten

2016-04-01

Landslides have many negative economic and societal impacts, including the potential for significant loss of life and damage to infrastructure. Slope stability assessment can be used to guide decisions about the management of landslide risk, but its usefulness can be challenged by high levels of uncertainty in predicting landslide occurrence. Prediction uncertainty may be associated with the choice of model that is used to assess slope stability, the quality of the available input data, or a lack of knowledge of how future climatic and socio-economic changes may affect future landslide risk. While some of these uncertainties can be characterised by relatively well-defined probability distributions, for other uncertainties, such as those linked to climate change, no probability distribution is available to characterise them. This latter type of uncertainty, often referred to as deep uncertainty, means that robust policies need to be developed that are expected to perform acceptably well over a wide range of future conditions. In our study the impact of deep uncertainty on slope stability predictions is assessed in a quantitative and structured manner using Global Sensitivity Analysis (GSA) and the Combined Hydrology and Stability Model (CHASM). In particular, we use several GSA methods including the Method of Morris, Regional Sensitivity Analysis and Classification and Regression Trees (CART), as well as advanced visualization tools, to assess the combination of conditions that may lead to slope failure. Our example application is a slope in the Caribbean, an area that is naturally susceptible to landslides due to a combination of high rainfall rates during the hurricane season, steep slopes, and highly weathered residual soils. Rapid unplanned urbanisation and changing climate may further exacerbate landslide risk in the future. Our example shows how we can gain useful information in the presence of deep uncertainty by combining physically based models with GSA in

"Share weather" : Design and evaluation of a new concept for sharing weather information

OpenAIRE

Elevant, Katarina

2013-01-01

Already centuries ago, humans had observed the weather in their everyday lives, seeking ways to understand, comprehend, and predict it. Until the present day, weather has had tremendous impacts on our lives and with climate change human civilizations as well. With new media technologies weather constitutes a part of the information services used by many residents of modern cities, people and businesses worldwide. The rise of Web 2.0, a cyberspace where individuals may connect and interact und...

Space Weather in Operation

Data.gov (United States)

National Aeronautics and Space Administration — The “Space Weather in Operations” effort will provide on-demand and near-real time space weather event information to the Data Access Toolkit (DAT), which is the...

Weather Augmented Risk Determination (WARD) System

Science.gov (United States)

Niknejad, M.; Mazdiyasni, O.; Momtaz, F.; AghaKouchak, A.

2017-12-01

Extreme climatic events have direct and indirect impacts on society, economy and the environment. Based on the United States Bureau of Economic Analysis (BEA) data, over one third of the U.S. GDP can be considered as weather-sensitive involving some degree of weather risk. This expands from a local scale concrete foundation construction to large scale transportation systems. Extreme and unexpected weather conditions have always been considered as one of the probable risks to human health, productivity and activities. The construction industry is a large sector of the economy, and is also greatly influenced by weather-related risks including work stoppage and low labor productivity. Identification and quantification of these risks, and providing mitigation of their effects are always the concerns of construction project managers. In addition to severe weather conditions' destructive effects, seasonal changes in weather conditions can also have negative impacts on human health. Work stoppage and reduced labor productivity can be caused by precipitation, wind, temperature, relative humidity and other weather conditions. Historical and project-specific weather information can improve better project management and mitigation planning, and ultimately reduce the risk of weather-related conditions. This paper proposes new software for project-specific user-defined data analysis that offers (a) probability of work stoppage and the estimated project length considering weather conditions; (b) information on reduced labor productivity and its impacts on project duration; and (c) probabilistic information on the project timeline based on both weather-related work stoppage and labor productivity. The software (WARD System) is designed such that it can be integrated into the already available project management tools. While the system and presented application focuses on the construction industry, the developed software is general and can be used for any application that involves

Statistical uncertainty of extreme wind storms over Europe derived from a probabilistic clustering technique

Science.gov (United States)

Walz, Michael; Leckebusch, Gregor C.

2016-04-01

Extratropical wind storms pose one of the most dangerous and loss intensive natural hazards for Europe. However, due to only 50 years of high quality observational data, it is difficult to assess the statistical uncertainty of these sparse events just based on observations. Over the last decade seasonal ensemble forecasts have become indispensable in quantifying the uncertainty of weather prediction on seasonal timescales. In this study seasonal forecasts are used in a climatological context: By making use of the up to 51 ensemble members, a broad and physically consistent statistical base can be created. This base can then be used to assess the statistical uncertainty of extreme wind storm occurrence more accurately. In order to determine the statistical uncertainty of storms with different paths of progression, a probabilistic clustering approach using regression mixture models is used to objectively assign storm tracks (either based on core pressure or on extreme wind speeds) to different clusters. The advantage of this technique is that the entire lifetime of a storm is considered for the clustering algorithm. Quadratic curves are found to describe the storm tracks most accurately. Three main clusters (diagonal, horizontal or vertical progression of the storm track) can be identified, each of which have their own particulate features. Basic storm features like average velocity and duration are calculated and compared for each cluster. The main benefit of this clustering technique, however, is to evaluate if the clusters show different degrees of uncertainty, e.g. more (less) spread for tracks approaching Europe horizontally (diagonally). This statistical uncertainty is compared for different seasonal forecast products.

A new Method for the Estimation of Initial Condition Uncertainty Structures in Mesoscale Models

Science.gov (United States)

Keller, J. D.; Bach, L.; Hense, A.

2012-12-01

The estimation of fast growing error modes of a system is a key interest of ensemble data assimilation when assessing uncertainty in initial conditions. Over the last two decades three methods (and variations of these methods) have evolved for global numerical weather prediction models: ensemble Kalman filter, singular vectors and breeding of growing modes (or now ensemble transform). While the former incorporates a priori model error information and observation error estimates to determine ensemble initial conditions, the latter two techniques directly address the error structures associated with Lyapunov vectors. However, in global models these structures are mainly associated with transient global wave patterns. When assessing initial condition uncertainty in mesoscale limited area models, several problems regarding the aforementioned techniques arise: (a) additional sources of uncertainty on the smaller scales contribute to the error and (b) error structures from the global scale may quickly move through the model domain (depending on the size of the domain). To address the latter problem, perturbation structures from global models are often included in the mesoscale predictions as perturbed boundary conditions. However, the initial perturbations (when used) are often generated with a variant of an ensemble Kalman filter which does not necessarily focus on the large scale error patterns. In the framework of the European regional reanalysis project of the Hans-Ertel-Center for Weather Research we use a mesoscale model with an implemented nudging data assimilation scheme which does not support ensemble data assimilation at all. In preparation of an ensemble-based regional reanalysis and for the estimation of three-dimensional atmospheric covariance structures, we implemented a new method for the assessment of fast growing error modes for mesoscale limited area models. The so-called self-breeding is development based on the breeding of growing modes technique

Reward Draws the Eye, Uncertainty Holds the Eye: Associative Learning Modulates Distractor Interference in Visual Search

Directory of Open Access Journals (Sweden)

Stephan Koenig

2017-07-01

Full Text Available Stimuli in our sensory environment differ with respect to their physical salience but moreover may acquire motivational salience by association with reward. If we repeatedly observed that reward is available in the context of a particular cue but absent in the context of another cue the former typically attracts more attention than the latter. However, we also may encounter cues uncorrelated with reward. A cue with 50% reward contingency may induce an average reward expectancy but at the same time induces high reward uncertainty. In the current experiment we examined how both values, reward expectancy and uncertainty, affected overt attention. Two different colors were established as predictive cues for low reward and high reward respectively. A third color was followed by high reward on 50% of the trials and thus induced uncertainty. Colors then were introduced as distractors during search for a shape target, and we examined the relative potential of the color distractors to capture and hold the first fixation. We observed that capture frequency corresponded to reward expectancy while capture duration corresponded to uncertainty. The results may suggest that within trial reward expectancy is represented at an earlier time window than uncertainty.

Taking Weatherization to New Heights in Colorado: Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

Colorado demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

Weatherization is a Natural Choice for Montana: Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

Montana demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

Weatherization is a Natural Choice for Montana: Weatherization Assistance Close-Up Fact Sheet

Energy Technology Data Exchange (ETDEWEB)

D& R International

2001-10-10

Montana demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes.

Weatherization Sails on Maryland's Legacy of Innovation: Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

Maryland demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

Weatherization Plays a Starring Role in Mississippi: Weatherization Assistance Close-Up Fact Sheet

Energy Technology Data Exchange (ETDEWEB)

D& R International

2001-10-10

Mississippi demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes.

Weatherization Savings Takes Root in New Mexico: Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

New Mexico demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

AWE: Aviation Weather Data Visualization Environment

Science.gov (United States)

Spirkovska, Lilly; Lodha, Suresh K.; Norvig, Peter (Technical Monitor)

2000-01-01

Weather is one of the major causes of aviation accidents. General aviation (GA) flights account for 92% of all the aviation accidents, In spite of all the official and unofficial sources of weather visualization tools available to pilots, there is an urgent need for visualizing several weather related data tailored for general aviation pilots. Our system, Aviation Weather Data Visualization Environment AWE), presents graphical displays of meteorological observations, terminal area forecasts, and winds aloft forecasts onto a cartographic grid specific to the pilot's area of interest. Decisions regarding the graphical display and design are made based on careful consideration of user needs. Integral visual display of these elements of weather reports is designed for the use of GA pilots as a weather briefing and route selection tool. AWE provides linking of the weather information to the flight's path and schedule. The pilot can interact with the system to obtain aviation-specific weather for the entire area or for his specific route to explore what-if scenarios and make "go/no-go" decisions. The system, as evaluated by some pilots at NASA Ames Research Center, was found to be useful.

Understanding uncertainty

CERN Document Server

Lindley, Dennis V

2013-01-01

Praise for the First Edition ""...a reference for everyone who is interested in knowing and handling uncertainty.""-Journal of Applied Statistics The critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty to be handled sensibly in everyday life. These ideas were extended to embrace the scientific method and to show how decisions, containing an uncertain element, could be rationally made.

Robustness for slope stability modelling under deep uncertainty

Science.gov (United States)

Almeida, Susana; Holcombe, Liz; Pianosi, Francesca; Wagener, Thorsten

2015-04-01

Landslides can have large negative societal and economic impacts, such as loss of life and damage to infrastructure. However, the ability of slope stability assessment to guide management is limited by high levels of uncertainty in model predictions. Many of these uncertainties cannot be easily quantified, such as those linked to climate change and other future socio-economic conditions, restricting the usefulness of traditional decision analysis tools. Deep uncertainty can be managed more effectively by developing robust, but not necessarily optimal, policies that are expected to perform adequately under a wide range of future conditions. Robust strategies are particularly valuable when the consequences of taking a wrong decision are high as is often the case of when managing natural hazard risks such as landslides. In our work a physically based numerical model of hydrologically induced slope instability (the Combined Hydrology and Stability Model - CHASM) is applied together with robust decision making to evaluate the most important uncertainties (storm events, groundwater conditions, surface cover, slope geometry, material strata and geotechnical properties) affecting slope stability. Specifically, impacts of climate change on long-term slope stability are incorporated, accounting for the deep uncertainty in future climate projections. Our findings highlight the potential of robust decision making to aid decision support for landslide hazard reduction and risk management under conditions of deep uncertainty.

Weatherization and Intergovernmental Program - Weatherization Assistance Program

Energy Technology Data Exchange (ETDEWEB)

None

2010-06-01

The U.S. Department of Energy’s (DOE) Weatherization Assistance Program reduces energy costs for low-income households by increasing the energy efficiency of their homes, while ensuring their health and safety.

Mechanisms for chemostatic behavior in catchments: implications for CO2 consumption by mineral weathering

Science.gov (United States)

Clow, David W.; Mast, M. Alisa

2010-01-01

Concentrations of weathering products in streams often show relatively little variation compared to changes in discharge, both at event and annual scales. In this study, several hypothesized mechanisms for this “chemostatic behavior” were evaluated, and the potential for those mechanisms to influence relations between climate, weathering fluxes, and CO2 consumption via mineral weathering was assessed. Data from Loch Vale, an alpine catchment in the Colorado Rocky Mountains, indicates that cation exchange and seasonal precipitation and dissolution of amorphous or poorly crystalline aluminosilicates are important processes that help regulate solute concentrations in the stream; however, those processes have no direct effect on CO2 consumption in catchments. Hydrograph separation analyses indicate that old water stored in the subsurface over the winter accounts for about one-quarter of annual streamflow, and almost one-half of annual fluxes of Na and SiO2 in the stream; thus, flushing of old water by new water (snowmelt) is an important component of chemostatic behavior. Hydrologic flushing of subsurface materials further induces chemostatic behavior by reducing mineral saturation indices and increasing reactive mineral surface area, which stimulate mineral weathering rates. CO2 consumption by carbonic acid mediated mineral weathering was quantified using mass-balance calculations; results indicated that silicate mineral weathering was responsible for approximately two-thirds of annual CO2 consumption, and carbonate weathering was responsible for the remaining one-third. CO2 consumption was strongly dependent on annual precipitation and temperature; these relations were captured in a simple statistical model that accounted for 71% of the annual variation in CO2 consumption via mineral weathering in Loch Vale.

Extreme Events in China under Climate Change: Uncertainty and related impacts (CSSP-FOREX)

Science.gov (United States)

Leckebusch, Gregor C.; Befort, Daniel J.; Hodges, Kevin I.

2016-04-01

Suitable adaptation strategies or the timely initiation of related mitigation efforts in East Asia will strongly depend on robust and comprehensive information about future near-term as well as long-term potential changes in the climate system. Therefore, understanding the driving mechanisms associated with the East Asian climate is of major importance. The FOREX project (Fostering Regional Decision Making by the Assessment of Uncertainties of Future Regional Extremes and their Linkage to Global Climate System Variability for China and East Asia) focuses on the investigation of extreme wind and rainfall related events over Eastern Asia and their possible future changes. Here, analyses focus on the link between local extreme events and their driving weather systems. This includes the coupling between local rainfall extremes and tropical cyclones, the Meiyu frontal system, extra-tropical teleconnections and monsoonal activity. Furthermore, the relation between these driving weather systems and large-scale variability modes, e.g. NAO, PDO, ENSO is analysed. Thus, beside analysing future changes of local extreme events, the temporal variability of their driving weather systems and related large-scale variability modes will be assessed in current CMIP5 global model simulations to obtain more robust results. Beyond an overview of FOREX itself, first results regarding the link between local extremes and their steering weather systems based on observational and reanalysis data are shown. Special focus is laid on the contribution of monsoonal activity, tropical cyclones and the Meiyu frontal system on the inter-annual variability of the East Asian summer rainfall.

Assessing Weather Curiosity in University Students

Science.gov (United States)

Stewart, A. E.

2017-12-01

This research focuses upon measuring an individual's level of trait curiosity about the weather using the Weather Curiosity Scale (WCS). The measure consists of 15 self-report items that describe weather preferences and/or behaviors that people may perform more or less frequently. The author reports on two initial studies of the WCS that have used the responses of 710 undergraduate students from a large university in the southeastern United States. In the first study, factor analysis of the 15 items indicated that the measure was unidimensional - suggesting that its items singularly assessed weather curiosity. The WCS also was internally consistent as evidenced by an acceptable Cronbach's alpha, a = .81). The second study sought to identify other personality variables that may relate with the WCS scores and thus illuminate the nature of weather curiosity. Several clusters of personality variables appear to underlie the curiosity levels people exhibited, the first of which related to perceptual curiosity (r = .59). Being curious about sights, sounds, smells, and textures generally related somewhat to curiosity about weather. Two measures of trait sensitivity to environmental stimulation, the Highly Sensitive Person Scale (r = .47) and the Orientation Sensitivity Scale of the Adult Temperament Questionnaire (r = .43), also predicted weather curiosity levels. Finally, possessing extraverted personality traits (r = .34) and an intense style of experiencing one's emotions (r = .33) related to weather curiosity. How can this measure be used in K-12 or post-secondary settings to further climate literacy? First, the WCS can identify students with natural curiosities about weather and climate so these students may be given more challenging instruction that will leverage their natural interests. Second, high-WCS students may function as weather and climate ambassadors during inquiry-based learning activities and thus help other students who are not as oriented to the

Verification of Space Weather Forecasts using Terrestrial Weather Approaches

Science.gov (United States)

Henley, E.; Murray, S.; Pope, E.; Stephenson, D.; Sharpe, M.; Bingham, S.; Jackson, D.

2015-12-01

The Met Office Space Weather Operations Centre (MOSWOC) provides a range of 24/7 operational space weather forecasts, alerts, and warnings, which provide valuable information on space weather that can degrade electricity grids, radio communications, and satellite electronics. Forecasts issued include arrival times of coronal mass ejections (CMEs), and probabilistic forecasts for flares, geomagnetic storm indices, and energetic particle fluxes and fluences. These forecasts are produced twice daily using a combination of output from models such as Enlil, near-real-time observations, and forecaster experience. Verification of forecasts is crucial for users, researchers, and forecasters to understand the strengths and limitations of forecasters, and to assess forecaster added value. To this end, the Met Office (in collaboration with Exeter University) has been adapting verification techniques from terrestrial weather, and has been working closely with the International Space Environment Service (ISES) to standardise verification procedures. We will present the results of part of this work, analysing forecast and observed CME arrival times, assessing skill using 2x2 contingency tables. These MOSWOC forecasts can be objectively compared to those produced by the NASA Community Coordinated Modelling Center - a useful benchmark. This approach cannot be taken for the other forecasts, as they are probabilistic and categorical (e.g., geomagnetic storm forecasts give probabilities of exceeding levels from minor to extreme). We will present appropriate verification techniques being developed to address these forecasts, such as rank probability skill score, and comparing forecasts against climatology and persistence benchmarks. As part of this, we will outline the use of discrete time Markov chains to assess and improve the performance of our geomagnetic storm forecasts. We will also discuss work to adapt a terrestrial verification visualisation system to space weather, to help

Uncertainty in Citizen Science observations: from measurement to user perception

Science.gov (United States)

Lahoz, William; Schneider, Philipp; Castell, Nuria

2016-04-01

Citizen Science activities concern general public engagement in scientific research activities when citizens actively contribute to science either with their intellectual effort or surrounding knowledge or with their tools and resources. The advent of technologies such as the Internet and smartphones, and the growth in their usage, has significantly increased the potential benefits from Citizen Science activities. Citizen Science observations from low-cost sensors, smartphones and Citizen Observatories, provide a novel and recent development in platforms for observing the Earth System, with the opportunity to extend the range of observational platforms available to society to spatio-temporal scales (10-100s m; 1 hr or less) highly relevant to citizen needs. The potential value of Citizen Science is high, with applications in science, education, social aspects, and policy aspects, but this potential, particularly for citizens and policymakers, remains largely untapped. Key areas where Citizen Science data start to have demonstrable benefits include GEOSS Societal Benefit Areas such as Health and Weather. Citizen Science observations have many challenges, including simulation of smaller spatial scales, noisy data, combination with traditional observational methods (satellite and in situ data), and assessment, representation and visualization of uncertainty. Within these challenges, that of the assessment and representation of uncertainty and its communication to users is fundamental, as it provides qualitative and/or quantitative information that influences the belief users will have in environmental information. This presentation will discuss the challenges in assessment and representation of uncertainty in Citizen Science observations, its communication to users, including the use of visualization, and the perception of this uncertainty information by users of Citizen Science observations.

Assessing climate change and socio-economic uncertainties in long term management of water resources

Science.gov (United States)

Jahanshahi, Golnaz; Dawson, Richard; Walsh, Claire; Birkinshaw, Stephen; Glenis, Vassilis

2015-04-01

Long term management of water resources is challenging for decision makers given the range of uncertainties that exist. Such uncertainties are a function of long term drivers of change, such as climate, environmental loadings, demography, land use and other socio economic drivers. Impacts of climate change on frequency of extreme events such as drought make it a serious threat to water resources and water security. The release of probabilistic climate information, such as the UKCP09 scenarios, provides improved understanding of some uncertainties in climate models. This has motivated a more rigorous approach to dealing with other uncertainties in order to understand the sensitivity of investment decisions to future uncertainty and identify adaptation options that are as far as possible robust. We have developed and coupled a system of models that includes a weather generator, simulations of catchment hydrology, demand for water and the water resource system. This integrated model has been applied in the Thames catchment which supplies the city of London, UK. This region is one of the driest in the UK and hence sensitive to water availability. In addition, it is one of the fastest growing parts of the UK and plays an important economic role. Key uncertainties in long term water resources in the Thames catchment, many of which result from earth system processes, are identified and quantified. The implications of these uncertainties are explored using a combination of uncertainty analysis and sensitivity testing. The analysis shows considerable uncertainty in future rainfall, river flow and consequently water resource. For example, results indicate that by the 2050s, low flow (Q95) in the Thames catchment will range from -44 to +9% compared with the control scenario (1970s). Consequently, by the 2050s the average number of drought days are expected to increase 4-6 times relative to the 1970s. Uncertainties associated with urban growth increase these risks further

New Technologies for Weather Accident Prevention

Science.gov (United States)

Stough, H. Paul, III; Watson, James F., Jr.; Daniels, Taumi S.; Martzaklis, Konstantinos S.; Jarrell, Michael A.; Bogue, Rodney K.

2005-01-01

Weather is a causal factor in thirty percent of all aviation accidents. Many of these accidents are due to a lack of weather situation awareness by pilots in flight. Improving the strategic and tactical weather information available and its presentation to pilots in flight can enhance weather situation awareness and enable avoidance of adverse conditions. This paper presents technologies for airborne detection, dissemination and display of weather information developed by the National Aeronautics and Space Administration (NASA) in partnership with the Federal Aviation Administration (FAA), National Oceanic and Atmospheric Administration (NOAA), industry and the research community. These technologies, currently in the initial stages of implementation by industry, will provide more precise and timely knowledge of the weather and enable pilots in flight to make decisions that result in safer and more efficient operations.

Insurance against weather risk : use of heating degree-days from non-local stations for weather derivatives

NARCIS (Netherlands)

Asseldonk, van M.A.P.M.

2003-01-01

Weather derivatives enable policy-holders to safeguard themselves against extreme weather conditions. The effectiveness and the efficiency of the risk transfer is determined by the spatial risk basis, which is the stochastic dependency of the local weather outcome being insured and the outcome of

Evaluating uncertainty estimates in hydrologic models: borrowing measures from the forecast verification community

Directory of Open Access Journals (Sweden)

K. J. Franz

2011-11-01

Full Text Available The hydrologic community is generally moving towards the use of probabilistic estimates of streamflow, primarily through the implementation of Ensemble Streamflow Prediction (ESP systems, ensemble data assimilation methods, or multi-modeling platforms. However, evaluation of probabilistic outputs has not necessarily kept pace with ensemble generation. Much of the modeling community is still performing model evaluation using standard deterministic measures, such as error, correlation, or bias, typically applied to the ensemble mean or median. Probabilistic forecast verification methods have been well developed, particularly in the atmospheric sciences, yet few have been adopted for evaluating uncertainty estimates in hydrologic model simulations. In the current paper, we overview existing probabilistic forecast verification methods and apply the methods to evaluate and compare model ensembles produced from two different parameter uncertainty estimation methods: the Generalized Uncertainty Likelihood Estimator (GLUE, and the Shuffle Complex Evolution Metropolis (SCEM. Model ensembles are generated for the National Weather Service SACramento Soil Moisture Accounting (SAC-SMA model for 12 forecast basins located in the Southeastern United States. We evaluate the model ensembles using relevant metrics in the following categories: distribution, correlation, accuracy, conditional statistics, and categorical statistics. We show that the presented probabilistic metrics are easily adapted to model simulation ensembles and provide a robust analysis of model performance associated with parameter uncertainty. Application of these methods requires no information in addition to what is already available as part of traditional model validation methodology and considers the entire ensemble or uncertainty range in the approach.

Validating Satellite-Retrieved Cloud Properties for Weather and Climate Applications

Science.gov (United States)

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

Can the Weather Affect My Child's Asthma?

Science.gov (United States)

... English Español Can the Weather Affect My Child's Asthma? KidsHealth / For Parents / Can the Weather Affect My ... Asthma? Print Can the Weather Affect My Child's Asthma? Yes. Weather conditions can bring on asthma symptoms. ...

NWS Weather Fatality, Injury and Damage Statistics

Science.gov (United States)

... Weather Awareness Floods, Wind Chill, Tornadoes, Heat... Education Weather Terms, Teachers, Statistics government web resources and services. Natural Hazard Statistics Statistics U.S. Summaries 78-Year List of Severe Weather Fatalities Preliminary Hazardous Weather Statistics for 2017 Now

Uncertainty in predictions of forest carbon dynamics: separating driver error from model error.

Science.gov (United States)

Spadavecchia, L; Williams, M; Law, B E

2011-07-01

We present an analysis of the relative magnitude and contribution of parameter and driver uncertainty to the confidence intervals on estimates of net carbon fluxes. Model parameters may be difficult or impractical to measure, while driver fields are rarely complete, with data gaps due to sensor failure and sparse observational networks. Parameters are generally derived through some optimization method, while driver fields may be interpolated from available data sources. For this study, we used data from a young ponderosa pine stand at Metolius, Central Oregon, and a simple daily model of coupled carbon and water fluxes (DALEC). An ensemble of acceptable parameterizations was generated using an ensemble Kalman filter and eddy covariance measurements of net C exchange. Geostatistical simulations generated an ensemble of meteorological driving variables for the site, consistent with the spatiotemporal autocorrelations inherent in the observational data from 13 local weather stations. Simulated meteorological data were propagated through the model to derive the uncertainty on the CO2 flux resultant from driver uncertainty typical of spatially extensive modeling studies. Furthermore, the model uncertainty was partitioned between temperature and precipitation. With at least one meteorological station within 25 km of the study site, driver uncertainty was relatively small ( 10% of the total net flux), while parameterization uncertainty was larger, 50% of the total net flux. The largest source of driver uncertainty was due to temperature (8% of the total flux). The combined effect of parameter and driver uncertainty was 57% of the total net flux. However, when the nearest meteorological station was > 100 km from the study site, uncertainty in net ecosystem exchange (NEE) predictions introduced by meteorological drivers increased by 88%. Precipitation estimates were a larger source of bias in NEE estimates than were temperature estimates, although the biases partly

... AND HERE COMES THE WEATHER - Austrian TV and radio weather news in the eye of the public

Science.gov (United States)

Keul, A.; Holzer, A. M.; Wostal, T.

2010-09-01

Media weather reports as the main avenue of meteorological and climatological information to the general public have always been in the focus of critical investigation. Former research found that although weather reports are high-interest topics, the amount of information recalled by non-experts is rather low, and criticized this. A pilot study (Keul et al., 2009) by the Salzburg University in cooperation with ORF, the Austrian Broadcasting Corporation, used historic radio files on a fair-weather and a storm situation. It identified the importance of intelligible wording of the weather forecast messages for lay people. Without quality control, weather information can stimulate rumours, false comfort or false alarms. More qualitative and experimental research, also on TV weather, seems justified. This need for further research was addressed by a second and larger field experiment in the spring of 2010. The survey took place in Salzburg City, Austria, with a quota sample of about 90 lay persons. This time TV and radio weather reports were used and a more realistic listening and viewing situation was created by presenting the latest weather forecasts of the given day to the test persons in the very next hours after originally broadcasting them. It asked lay people what they find important in the weather reports and what they remember for their actual next-day use. Reports of a fairweather prognosis were compared with a warning condition. The weather media mix of the users was explored. A second part of the study was a questionnaire which tested the understanding of typical figures of speech used in weather forecasts or even meteorological terms, which might also be important for fully understanding the severe weather warnings. This leads to quantitative and qualitative analysis from which the most important and unexpected results are presented. Short presentation times (1.5 to 2 minutes) make Austrian radio and TV weather reports a narrow compromise between general

Manufacturing Data Uncertainties Propagation Method in Burn-Up Problems

Directory of Open Access Journals (Sweden)

Thomas Frosio

2017-01-01

Full Text Available A nuclear data-based uncertainty propagation methodology is extended to enable propagation of manufacturing/technological data (TD uncertainties in a burn-up calculation problem, taking into account correlation terms between Boltzmann and Bateman terms. The methodology is applied to reactivity and power distributions in a Material Testing Reactor benchmark. Due to the inherent statistical behavior of manufacturing tolerances, Monte Carlo sampling method is used for determining output perturbations on integral quantities. A global sensitivity analysis (GSA is performed for each manufacturing parameter and allows identifying and ranking the influential parameters whose tolerances need to be better controlled. We show that the overall impact of some TD uncertainties, such as uranium enrichment, or fuel plate thickness, on the reactivity is negligible because the different core areas induce compensating effects on the global quantity. However, local quantities, such as power distributions, are strongly impacted by TD uncertainty propagations. For isotopic concentrations, no clear trends appear on the results.

Climate change impact assessment on flow regime by incorporating spatial correlation and scenario uncertainty

Science.gov (United States)

Vallam, P.; Qin, X. S.

2017-07-01

Flooding risk is increasing in many parts of the world and may worsen under climate change conditions. The accuracy of predicting flooding risk relies on reasonable projection of meteorological data (especially rainfall) at the local scale. The current statistical downscaling approaches face the difficulty of projecting multi-site climate information for future conditions while conserving spatial information. This study presents a combined Long Ashton Research Station Weather Generator (LARS-WG) stochastic weather generator and multi-site rainfall simulator RainSim (CLWRS) approach to investigate flow regimes under future conditions in the Kootenay Watershed, Canada. To understand the uncertainty effect stemming from different scenarios, the climate output is fed into a hydrologic model. The results showed different variation trends of annual peak flows (in 2080-2099) based on different climate change scenarios and demonstrated that the hydrological impact would be driven by the interaction between snowmelt and peak flows. The proposed CLWRS approach is useful where there is a need for projection of potential climate change scenarios.

An uncertainty inventory demonstration - a primary step in uncertainty quantification

Energy Technology Data Exchange (ETDEWEB)

Langenbrunner, James R. [Los Alamos National Laboratory; Booker, Jane M [Los Alamos National Laboratory; Hemez, Francois M [Los Alamos National Laboratory; Salazar, Issac F [Los Alamos National Laboratory; Ross, Timothy J [UNM

2009-01-01

Tools, methods, and theories for assessing and quantifying uncertainties vary by application. Uncertainty quantification tasks have unique desiderata and circumstances. To realistically assess uncertainty requires the engineer/scientist to specify mathematical models, the physical phenomena of interest, and the theory or framework for assessments. For example, Probabilistic Risk Assessment (PRA) specifically identifies uncertainties using probability theory, and therefore, PRA's lack formal procedures for quantifying uncertainties that are not probabilistic. The Phenomena Identification and Ranking Technique (PIRT) proceeds by ranking phenomena using scoring criteria that results in linguistic descriptors, such as importance ranked with words, 'High/Medium/Low.' The use of words allows PIRT to be flexible, but the analysis may then be difficult to combine with other uncertainty theories. We propose that a necessary step for the development of a procedure or protocol for uncertainty quantification (UQ) is the application of an Uncertainty Inventory. An Uncertainty Inventory should be considered and performed in the earliest stages of UQ.

A Severe Weather Laboratory Exercise for an Introductory Weather and Climate Class Using Active Learning Techniques

Science.gov (United States)

Grundstein, Andrew; Durkee, Joshua; Frye, John; Andersen, Theresa; Lieberman, Jordan

2011-01-01

This paper describes a new severe weather laboratory exercise for an Introductory Weather and Climate class, appropriate for first and second year college students (including nonscience majors), that incorporates inquiry-based learning techniques. In the lab, students play the role of meteorologists making forecasts for severe weather. The…

Engaging Earth- and Environmental-Science Undergraduates Through Weather Discussions and an eLearning Weather Forecasting Contest

Science.gov (United States)

Schultz, David M.; Anderson, Stuart; Seo-Zindy, Ryo

2013-06-01

For students who major in meteorology, engaging in weather forecasting can motivate learning, develop critical-thinking skills, improve their written communication, and yield better forecasts. Whether such advances apply to students who are not meteorology majors has been less demonstrated. To test this idea, a weather discussion and an eLearning weather forecasting contest were devised for a meteorology course taken by third-year undergraduate earth- and environmental-science students. The discussion consisted of using the recent, present, and future weather to amplify the topics of the week's lectures. Then, students forecasted the next day's high temperature and the probability of precipitation for Woodford, the closest official observing site to Manchester, UK. The contest ran for 10 weeks, and the students received credit for participation. The top students at the end of the contest received bonus points on their final grade. A Web-based forecast contest application was developed to register the students, receive their forecasts, and calculate weekly standings. Students who were successful in the forecast contest were not necessarily those who achieved the highest scores on the tests, demonstrating that the contest was possibly testing different skills than traditional learning. Student evaluations indicate that the weather discussion and contest were reasonably successful in engaging students to learn about the weather outside of the classroom, synthesize their knowledge from the lectures, and improve their practical understanding of the weather. Therefore, students taking a meteorology class, but not majoring in meteorology, can derive academic benefits from weather discussions and forecast contests. Nevertheless, student evaluations also indicate that better integration of the lectures, weather discussions, and the forecasting contests is necessary.

Effect of activation cross-section uncertainties on the radiological assessment of the MFE/DEMO first wall

Energy Technology Data Exchange (ETDEWEB)

Cabellos, O. [Instituto de Fusion Nuclear, Universidad Politecnica de Madrid, Madrid (Spain)]. E-mail: cabellos@din.upm.es; Reyes, S. [Lawrence Livermore National Laboratory, Livermore, CA (United States); Sanz, J. [Instituto de Fusion Nuclear, Universidad Politecnica de Madrid, Madrid (Spain); University Nacional Educacion a Distancia, Dep. Ingenieria Energetica, Juan del Rosal 12, 28040 Madrid (Spain); Rodriguez, A. [University Nacional Educacion a Distancia, Dep. Ingenieria Energetica, Juan del Rosal 12, 28040 Madrid (Spain); Youssef, M. [University of California, Los Angeles, CA (United States); Sawan, M. [University of Wisconsin, Madison, WI (United States)

2006-02-15

A Monte Carlo procedure has been applied in this work in order to address the impact of activation cross-sections (XS) uncertainties on contact dose rate and decay heat calculations for the outboard first wall (FW) of a magnetic fusion energy (MFE) demonstration (DEMO) reactor. The XSs inducing the major uncertainty in the prediction of activation related quantities have been identified. Results have shown that for times corresponding to maintenance activities the uncertainties effect is insignificant since the dominant XSs involved in these calculations are based on accurate experimental data evaluations. However, for times corresponding to waste management/recycling activities, the errors induced by the XSs uncertainties, which in this case are evaluated using systematic models, must be considered. It has been found that two particular isotopes, {sup 6}Co and {sup 94}Nb, are key contributors to the global DEMO FW activation uncertainty results. In these cases, the benefit from further improvements in the accuracy of the critical reaction XSs is discussed.

Effect of activation cross-section uncertainties on the radiological assessment of the MFE/DEMO first wall

International Nuclear Information System (INIS)

Cabellos, O.; Reyes, S.; Sanz, J.; Rodriguez, A.; Youssef, M.; Sawan, M.

2006-01-01

A Monte Carlo procedure has been applied in this work in order to address the impact of activation cross-sections (XS) uncertainties on contact dose rate and decay heat calculations for the outboard first wall (FW) of a magnetic fusion energy (MFE) demonstration (DEMO) reactor. The XSs inducing the major uncertainty in the prediction of activation related quantities have been identified. Results have shown that for times corresponding to maintenance activities the uncertainties effect is insignificant since the dominant XSs involved in these calculations are based on accurate experimental data evaluations. However, for times corresponding to waste management/recycling activities, the errors induced by the XSs uncertainties, which in this case are evaluated using systematic models, must be considered. It has been found that two particular isotopes, 6 Co and 94 Nb, are key contributors to the global DEMO FW activation uncertainty results. In these cases, the benefit from further improvements in the accuracy of the critical reaction XSs is discussed

Recognizing and responding to uncertainty: a grounded theory of nurses' uncertainty.

Science.gov (United States)

Cranley, Lisa A; Doran, Diane M; Tourangeau, Ann E; Kushniruk, Andre; Nagle, Lynn

2012-08-01

There has been little research to date exploring nurses' uncertainty in their practice. Understanding nurses' uncertainty is important because it has potential implications for how care is delivered. The purpose of this study is to develop a substantive theory to explain how staff nurses experience and respond to uncertainty in their practice. Between 2006 and 2008, a grounded theory study was conducted that included in-depth semi-structured interviews. Fourteen staff nurses working in adult medical-surgical intensive care units at two teaching hospitals in Ontario, Canada, participated in the study. The theory recognizing and responding to uncertainty characterizes the processes through which nurses' uncertainty manifested and how it was managed. Recognizing uncertainty involved the processes of assessing, reflecting, questioning, and/or being unable to predict aspects of the patient situation. Nurses' responses to uncertainty highlighted the cognitive-affective strategies used to manage uncertainty. Study findings highlight the importance of acknowledging uncertainty and having collegial support to manage uncertainty. The theory adds to our understanding the processes involved in recognizing uncertainty, strategies and outcomes of managing uncertainty, and influencing factors. Tailored nursing education programs should be developed to assist nurses in developing skills in articulating and managing their uncertainty. Further research is needed to extend, test and refine the theory of recognizing and responding to uncertainty to develop strategies for managing uncertainty. This theory advances the nursing perspective of uncertainty in clinical practice. The theory is relevant to nurses who are faced with uncertainty and complex clinical decisions, to managers who support nurses in their clinical decision-making, and to researchers who investigate ways to improve decision-making and care delivery. ©2012 Sigma Theta Tau International.

Operational forecasting based on a modified Weather Research and Forecasting model

Energy Technology Data Exchange (ETDEWEB)

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18

Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

Ca isotopes, chemical weathering, and geomorphic controls on long-term climate

Science.gov (United States)

Moore, J.; Jacobson, A. D.; Holmden, C. E.; Craw, D.

2009-12-01

Calcium isotope geochemistry (δ44Ca) offers a unique opportunity to directly quantify proportions of riverine Ca originating from silicate versus carbonate weathering, which is essential for understanding how geomorphic processes affecting landscape evolution, such as tectonic uplift and glaciation, influence the long-term cycling of atmospheric CO2. We measured the elemental and δ44Ca chemistry of river and rock samples from the New Zealand Southern Alps. In combination with our geochemical data, we used runoff and suspended sediment fluxes to elucidate relationships between chemical weathering, mechanical erosion, and long-term climate. The S. Alps have uniform bedrock chemistry but significant tectonic and climatic gradients. West of the main topographic divide, watersheds drain schist and experience high runoff, uplift, and erosion rates. East of the main divide, watersheds drain greywacke or schist and experience lower runoff, uplift, and erosion rates. Glaciated watersheds with high erosion rates are present throughout the mountain range. Both schist and greywacke contain up to 3% metamorphic and hydrothermal calcite. Waters exhibit two-component mixing between calcite and silicate end-members when plotted as δ44Ca versus Ca/Sr. Scatter about the mixing curve is generally smaller than the analytical uncertainty of the measurements and likely reflects variability of the end-member compositions rather than fractionation. We used the mixing relationships to calculate percentages of Ca from silicate weathering. Rivers draining greywacke average 27.6% of Ca from silicate weathering with glaciated and non-glaciated watersheds yielding 41.8 and 19.5%, respectively. Rivers draining schist average 9.8% with glaciated and non-glaciated watersheds yielding 17.7 and 3.9%, respectively. Although Ca fluxes are larger west of the main divide where erosion and runoff are higher, the percentage of Ca from silicate weathering is smaller. Hence, long-term atmospheric CO2

Regional-seasonal weather forecasting

Energy Technology Data Exchange (ETDEWEB)

Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

1980-08-01

In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

Parameterization and Uncertainty Analysis of SWAT model in Hydrological Simulation of Chaohe River Basin

Science.gov (United States)

Jie, M.; Zhang, J.; Guo, B. B.

2017-12-01

As a typical distributed hydrological model, the SWAT model also has a challenge in calibrating parameters and analysis their uncertainty. This paper chooses the Chaohe River Basin China as the study area, through the establishment of the SWAT model, loading the DEM data of the Chaohe river basin, the watershed is automatically divided into several sub-basins. Analyzing the land use, soil and slope which are on the basis of the sub-basins and calculating the hydrological response unit (HRU) of the study area, after running SWAT model, the runoff simulation values in the watershed are obtained. On this basis, using weather data, known daily runoff of three hydrological stations, combined with the SWAT-CUP automatic program and the manual adjustment method are used to analyze the multi-site calibration of the model parameters. Furthermore, the GLUE algorithm is used to analyze the parameters uncertainty of the SWAT model. Through the sensitivity analysis, calibration and uncertainty study of SWAT, the results indicate that the parameterization of the hydrological characteristics of the Chaohe river is successful and feasible which can be used to simulate the Chaohe river basin.

From Forecasters to the General Public: A Communication Tool to Understand Decision-making Challenges in Weather-related Early Warning Systems

Science.gov (United States)

Terti, G.; Ruin, I.; Kalas, M.; Lorini, V.; Sabbatini, T.; i Alonso, A. C.

2017-12-01

New technologies are currently adopted worldwide to improve weather forecasts and communication of the corresponding warnings to the end-users. "EnhANcing emergency management and response to extreme WeatHER and climate Events" (ANYWHERE) project is an innovating action that aims at developing and implementing a European decision-support platform for weather-related risks integrating cutting-edge forecasting technology. The initiative is built in a collaborative manner where researchers, developers, potential users and other stakeholders meet frequently to define needs, capabilities and challenges. In this study, we propose a role-playing game to test the added value of the ANYWHERE platform on i) the decision-making process and the choice of warning levels under uncertainty, ii) the management of the official emergency response and iii) the crisis communication and triggering of protective actions at different levels of the warning system (from hazard detection to citizen response). The designed game serves as an interactive communication tool. Here, flood and flash flood focused simulations seek to enhance participant's understanding of the complexities and challenges embedded in various levels of the decision-making process under the threat of weather disasters (e.g., forecasting/warnings, official emergency actions, self-protection). Also, we facilitate collaboration and coordination between the participants who belong to different national or local agencies/authorities across Europe. The game is first applied and tested in ANYWHERE's workshop in Helsinki (September, 2017) where about 30-50 people, including researchers, forecasters, civil protection and representatives of related companies, are anticipated to play the simulation. The main idea is to provide to the players a virtual case study that well represents realistic uncertainties and dilemmas embedded in the real-time forecasting-warning processes. At the final debriefing step the participants are

Hillslope chemical weathering across Paraná, Brazil: A data mining-GIS hybrid approach

Science.gov (United States)

Iwashita, Fabio; Friedel, Michael J.; Filho, Carlos Roberto de Souza; Fraser, Stephen J.

2011-09-01

Self-organizing map (SOM) and geographic information system (GIS) models were used to investigate the nonlinear relationships associated with geochemical weathering processes at local (~100 km 2) and regional (~50,000 km 2) scales. The data set consisted of 1) 22 B-horizon soil variables: P, C, pH, Al, total acidity, Ca, Mg, K, total cation exchange capacity, sum of exchangeable bases, base saturation, Cu, Zn, Fe, B, S, Mn, gammaspectrometry (total count, potassium, thorium, and uranium) and magnetic susceptibility measures; and 2) six topographic variables: elevation, slope, aspect, hydrological accumulated flux, horizontal curvature and vertical curvature. It is characterized at 304 locations from a quasi-regular grid spaced about 24 km across the state of Paraná. This data base was split into two subsets: one for analysis and modeling (274 samples) and the other for validation (30 samples) purposes. The self-organizing map and clustering methods were used to identify and classify the relations among solid-phase chemical element concentrations and GIS derived topographic models. The correlation between elevation and k-means clusters related the relative position inside hydrologic macro basins, which was interpreted as an expression of the weathering process reaching a steady-state condition at the regional scale. Locally, the chemical element concentrations were related to the vertical curvature representing concave-convex hillslope features, where concave hillslopes with convergent flux tends to be a reducing environment and convex hillslopes with divergent flux, oxidizing environments. Stochastic cross validation demonstrated that the SOM produced unbiased classifications and quantified the relative amount of uncertainty in predictions. This work strengthens the hypothesis that, at B-horizon steady-state conditions, the terrain morphometry were linked with the soil geochemical weathering in a two-way dependent process: the topographic relief was a factor on

Hillslope chemical weathering across Paraná, Brazil: a data mining-GIS hybrid approach

Science.gov (United States)

Iwashita, Fabio; Friedel, Michael J.; Filho, Carlos Roberto de Souza; Fraser, Stephen J.

2011-01-01

Self-organizing map (SOM) and geographic information system (GIS) models were used to investigate the nonlinear relationships associated with geochemical weathering processes at local (~100 km2) and regional (~50,000 km2) scales. The data set consisted of 1) 22 B-horizon soil variables: P, C, pH, Al, total acidity, Ca, Mg, K, total cation exchange capacity, sum of exchangeable bases, base saturation, Cu, Zn, Fe, B, S, Mn, gammaspectrometry (total count, potassium, thorium, and uranium) and magnetic susceptibility measures; and 2) six topographic variables: elevation, slope, aspect, hydrological accumulated flux, horizontal curvature and vertical curvature. It is characterized at 304 locations from a quasi-regular grid spaced about 24 km across the state of Paraná. This data base was split into two subsets: one for analysis and modeling (274 samples) and the other for validation (30 samples) purposes. The self-organizing map and clustering methods were used to identify and classify the relations among solid-phase chemical element concentrations and GIS derived topographic models. The correlation between elevation and k-means clusters related the relative position inside hydrologic macro basins, which was interpreted as an expression of the weathering process reaching a steady-state condition at the regional scale. Locally, the chemical element concentrations were related to the vertical curvature representing concave–convex hillslope features, where concave hillslopes with convergent flux tends to be a reducing environment and convex hillslopes with divergent flux, oxidizing environments. Stochastic cross validation demonstrated that the SOM produced unbiased classifications and quantified the relative amount of uncertainty in predictions. This work strengthens the hypothesis that, at B-horizon steady-state conditions, the terrain morphometry were linked with the soil geochemical weathering in a two-way dependent process: the topographic relief was a factor on

Weather Derivatives – Origin, Types and Application

OpenAIRE

Piotr Binkowski

2008-01-01

The number of companies that are exposed to the revenues loss risk caused by weather variability is still increasing. The businesses that are mostly exposed to weather risk are following: energy, agriculture, constructions and transport. That situation has initiated dynamic growth of weather derivatives markets as well as the awareness of the weather risk among the market participants. Presently, the weather derivatives markets evaluate rapidly in all the mature economies: USA, Asia and Europ...

Weatherization in Arkansas: A Gem of a Program: Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

Arkansas demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

Weather Derivatives – Origin, Types and Application

Directory of Open Access Journals (Sweden)

Piotr Binkowski

2008-01-01

Full Text Available The number of companies that are exposed to the revenues loss risk caused by weather variability is still increasing. The businesses that are mostly exposed to weather risk are following: energy, agriculture, constructions and transport. That situation has initiated dynamic growth of weather derivatives markets as well as the awareness of the weather risk among the market participants. Presently, the weather derivatives markets evaluate rapidly in all the mature economies: USA, Asia and Europe. Constructing weather derivatives relies on qu- antifying climate factors in the form of indexes, what is quite simple task, more difficultly can be gathering precise historical data of required climate factors. Taking into consideration so far development of derivatives especially the financial derivatives based on different types of indexes financial market has at disposal wide range of different types of proved derivatives (futures, forward, options, swaps, which can be successfully utilised on the weather-driven markets both for hedging weather risk and speculating.

KSC Weather and Research

Science.gov (United States)

Maier, Launa; Huddleston, Lisa; Smith, Kristin

2016-01-01

This briefing outlines the history of Kennedy Space Center (KSC) Weather organization, past research sponsored or performed, current organization, responsibilities, and activities, the evolution of weather support, future technologies, and an update on the status of the buoys located offshore of Cape Canaveral Air Force Station and KSC.

Weather and road capacity

DEFF Research Database (Denmark)

Jensen, Thomas Christian

2014-01-01

The paper presents estimations of the effect of bad weather on the observed speed on a Danish highway section; Køge Bugt Motorvejen. The paper concludes that weather, primarily precipitation and snow, has a clear negative effect on speed when the road is not in hypercongestion mode. Furthermore...

Tales of future weather

NARCIS (Netherlands)

Hazeleger, W.; Van den Hurk, B.J.J.M.; Min, E.; Van Oldenborgh, G.J.; Petersen, A.C.; Stainforth, D.A.; Vasileiadou, E.; Smith, L.A.

2015-01-01

Society is vulnerable to extreme weather events and, by extension, to human impacts on future events. As climate changes weather patterns will change. The search is on for more effective methodologies to aid decision-makers both in mitigation to avoid climate change and in adaptation to changes. The

49 CFR 195.224 - Welding: Weather.

Science.gov (United States)

2010-10-01

... 49 Transportation 3 2010-10-01 2010-10-01 false Welding: Weather. 195.224 Section 195.224 Transportation Other Regulations Relating to Transportation (Continued) PIPELINE AND HAZARDOUS MATERIALS SAFETY... PIPELINE Construction § 195.224 Welding: Weather. Welding must be protected from weather conditions that...

The Spirit of North Dakota: Alive in Weatherization; Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

North Dakota demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

A Tribute to Weatherization Solutions in South Dakota: Weatherization Assistance Close-Up Fact Sheet

International Nuclear Information System (INIS)

2001-01-01

South Dakota demonstrates its commitment to technology and efficiency through the Weatherization Program. Weatherization uses advanced technologies and techniques to reduce energy costs for low-income families by increasing the energy efficiency of their homes

On-site ocean horizontal aerosol extinction coefficient inversion under different weather conditions on the Bo-hai and Huang-hai Seas

Science.gov (United States)

Zeng, Xianjiang; Xia, Min; Ge, Yinghui; Guo, Wenping; Yang, Kecheng

2018-03-01

In this paper, we explore the horizontal extinction characteristics under different weather conditions on the ocean surface with on-site experiments on the Bo-hai and Huang-hai Seas in the summer of 2016. An experimental lidar system is designed to collect the on-site experimental data. By aiming at the inhomogeneity and uncertainty of the horizontal aerosol in practice, a joint retrieval method is proposed to retrieve the aerosol extinction coefficients (AEC) from the raw data along the optical path. The retrieval results of both the simulated and the real signals demonstrate that the joint retrieval method is practical. Finally, the sequence observation results of the on-site experiments under different weather conditions are reported and analyzed. These results can provide the attenuation information to analyze the atmospheric aerosol characteristics on the ocean surface.

Integrating Sphere-based Weathering Device

Data.gov (United States)

Federal Laboratory Consortium — Description:In the artificial ultraviolet (UV) weathering of materials, a need exists for weathering devices that can uniformly illuminate test specimens with a high...

Accelerated laboratory weathering of acrylic lens materials

Science.gov (United States)

Arndt, Thomas; Richter, Steffen; Kogler, René; Pasierb, Mike; Walby, Christopher

2015-09-01

Flat samples from various poly(methyl methacrylate) (PMMA) formulations were subjected to outdoor weathering in Arizona and Florida, EMMAQUA® accelerated outdoor weathering, and two accelerated laboratory weathering procedures at 3 Sun irradiance which, imitate dry (Arizona) and wet (Florida) conditions. The main mode of degradation is yellowing and not the generation of haze for any weathering procedure within the investigated radiant exposure. Higher UV absorber concentrations lead to smaller changes in optical properties and in the resulting relative concentrator photovoltaic (CPV) module efficiencies. Comparison of sample properties after various weathering procedures reveals that the influence of weathering factors other than radiant exposure depends on the sample as well.

36 CFR 910.71 - Weather protection.

Science.gov (United States)

2010-07-01

... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Weather protection. 910.71 Section 910.71 Parks, Forests, and Public Property PENNSYLVANIA AVENUE DEVELOPMENT CORPORATION GENERAL... DEVELOPMENT AREA Glossary of Terms § 910.71 Weather protection. Weather protection means a seasonal or...

Flight Deck Weather Avoidance Decision Support: Implementation and Evaluation

Science.gov (United States)

Wu, Shu-Chieh; Luna, Rocio; Johnson, Walter W.

2013-01-01

Weather related disruptions account for seventy percent of the delays in the National Airspace System (NAS). A key component in the weather plan of the Next Generation of Air Transportation System (NextGen) is to assimilate observed weather information and probabilistic forecasts into the decision process of flight crews and air traffic controllers. In this research we explore supporting flight crew weather decision making through the development of a flight deck predicted weather display system that utilizes weather predictions generated by ground-based radar. This system integrates and presents this weather information, together with in-flight trajectory modification tools, within a cockpit display of traffic information (CDTI) prototype. that the CDTI features 2D and perspective 3D visualization models of weather. The weather forecast products that we implemented were the Corridor Integrated Weather System (CIWS) and the Convective Weather Avoidance Model (CWAM), both developed by MIT Lincoln Lab. We evaluated the use of CIWS and CWAM for flight deck weather avoidance in two part-task experiments. Experiment 1 compared pilots' en route weather avoidance performance in four weather information conditions that differed in the type and amount of predicted forecast (CIWS current weather only, CIWS current and historical weather, CIWS current and forecast weather, CIWS current and forecast weather and CWAM predictions). Experiment 2 compared the use of perspective 3D and 21/2D presentations of weather for flight deck weather avoidance. Results showed that pilots could take advantage of longer range predicted weather forecasts in performing en route weather avoidance but more research will be needed to determine what combinations of information are optimal and how best to present them.

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

DEFF Research Database (Denmark)

Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen

2014-01-01

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...... 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...

North America Synoptic Weather Maps

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Series of Synoptic Weather Maps. Maps contains a surface analysis comprised of plotted weather station observations, isobars indicating low and high-pressure...

European drought under climate change and an assessment of the uncertainties in projections

Science.gov (United States)

Yu, R. M. S.; Osborn, T.; Conway, D.; Warren, R.; Hankin, R.

2012-04-01

Extreme weather/climate events have significant environmental and societal impacts, and anthropogenic climate change has and will continue to alter their characteristics (IPCC, 2011). Drought is one of the most damaging natural hazards through its effects on agricultural, hydrological, ecological and socio-economic systems. Climate change is stimulating demand, from public and private sector decision-makers and also other stakeholders, for better understanding of potential future drought patterns which could facilitate disaster risk management. There remain considerable levels of uncertainty in climate change projections, particularly in relation to extreme events. Our incomplete understanding of the behaviour of the climate system has led to the development of various emission scenarios, carbon cycle models and global climate models (GCMs). Uncertainties arise also from the different types and definitions of drought. This study examines climate change-induced changes in European drought characteristics, and illustrates the robustness of these projections by quantifying the effects of using different emission scenarios, carbon cycle models and GCMs. This is achieved by using the multi-institutional modular "Community Integrated Assessment System (CIAS)" (Warren et al., 2008), a flexible integrated assessment system for modelling climate change. Simulations generated by the simple climate model MAGICC6.0 are assessed. These include ten C4MIP carbon cycle models and eighteen CMIP3 GCMs under five IPCC SRES emission scenarios, four Representative Concentration Pathway (RCP) scenarios, and three mitigation scenarios with CO2-equivalent levels stabilising at 550 ppm, 500 ppm and 450 ppm. Using an ensemble of 2160 future precipitation scenarios, we present an analysis on both short (3-month) and long (12-month) meteorological droughts based on the Standardised Precipitation Index (SPI) for the baseline period (1951-2000) and two future periods of 2001-2050 and 2051

Quantification of margins and uncertainties: Alternative representations of epistemic uncertainty

International Nuclear Information System (INIS)

Helton, Jon C.; Johnson, Jay D.

2011-01-01

In 2001, the National Nuclear Security Administration of the U.S. Department of Energy in conjunction with the national security laboratories (i.e., Los Alamos National Laboratory, Lawrence Livermore National Laboratory and Sandia National Laboratories) initiated development of a process designated Quantification of Margins and Uncertainties (QMU) for the use of risk assessment methodologies in the certification of the reliability and safety of the nation's nuclear weapons stockpile. A previous presentation, 'Quantification of Margins and Uncertainties: Conceptual and Computational Basis,' describes the basic ideas that underlie QMU and illustrates these ideas with two notional examples that employ probability for the representation of aleatory and epistemic uncertainty. The current presentation introduces and illustrates the use of interval analysis, possibility theory and evidence theory as alternatives to the use of probability theory for the representation of epistemic uncertainty in QMU-type analyses. The following topics are considered: the mathematical structure of alternative representations of uncertainty, alternative representations of epistemic uncertainty in QMU analyses involving only epistemic uncertainty, and alternative representations of epistemic uncertainty in QMU analyses involving a separation of aleatory and epistemic uncertainty. Analyses involving interval analysis, possibility theory and evidence theory are illustrated with the same two notional examples used in the presentation indicated above to illustrate the use of probability to represent aleatory and epistemic uncertainty in QMU analyses.

Uncertainty analysis guide

International Nuclear Information System (INIS)

Andres, T.H.

2002-05-01

This guide applies to the estimation of uncertainty in quantities calculated by scientific, analysis and design computer programs that fall within the scope of AECL's software quality assurance (SQA) manual. The guide weaves together rational approaches from the SQA manual and three other diverse sources: (a) the CSAU (Code Scaling, Applicability, and Uncertainty) evaluation methodology; (b) the ISO Guide,for the Expression of Uncertainty in Measurement; and (c) the SVA (Systems Variability Analysis) method of risk analysis. This report describes the manner by which random and systematic uncertainties in calculated quantities can be estimated and expressed. Random uncertainty in model output can be attributed to uncertainties of inputs. The propagation of these uncertainties through a computer model can be represented in a variety of ways, including exact calculations, series approximations and Monte Carlo methods. Systematic uncertainties emerge from the development of the computer model itself, through simplifications and conservatisms, for example. These must be estimated and combined with random uncertainties to determine the combined uncertainty in a model output. This report also addresses the method by which uncertainties should be employed in code validation, in order to determine whether experiments and simulations agree, and whether or not a code satisfies the required tolerance for its application. (author)

Uncertainty analysis guide

Energy Technology Data Exchange (ETDEWEB)

Andres, T.H

2002-05-01

This guide applies to the estimation of uncertainty in quantities calculated by scientific, analysis and design computer programs that fall within the scope of AECL's software quality assurance (SQA) manual. The guide weaves together rational approaches from the SQA manual and three other diverse sources: (a) the CSAU (Code Scaling, Applicability, and Uncertainty) evaluation methodology; (b) the ISO Guide,for the Expression of Uncertainty in Measurement; and (c) the SVA (Systems Variability Analysis) method of risk analysis. This report describes the manner by which random and systematic uncertainties in calculated quantities can be estimated and expressed. Random uncertainty in model output can be attributed to uncertainties of inputs. The propagation of these uncertainties through a computer model can be represented in a variety of ways, including exact calculations, series approximations and Monte Carlo methods. Systematic uncertainties emerge from the development of the computer model itself, through simplifications and conservatisms, for example. These must be estimated and combined with random uncertainties to determine the combined uncertainty in a model output. This report also addresses the method by which uncertainties should be employed in code validation, in order to determine whether experiments and simulations agree, and whether or not a code satisfies the required tolerance for its application. (author)

Weather Risk Management in Agriculture

Directory of Open Access Journals (Sweden)

Martina Bobriková

2016-01-01

Full Text Available The paper focuses on valuation of a weather derivative with payoffs depending on temperature. We use historical data from the weather station in the Slovak town Košice to obtain unique prices of option contracts in an incomplete market. Numerical examples of prices of some contracts are presented, using the Burn analysis. We provide an example of how a weather contract can be designed to hedge the financial risk of a suboptimal temperature condition. The comparative comparison of the selected option hedging strategies has shown the best results for the producers in agricultural industries who hedges against an unfavourable weather conditions. The results of analysis proved that by buying put option or call option, the farmer establishes the highest payoff in the case of temperature decrease or increase. The Long Straddle Strategy is the most expensive but is available to the farmer who hedges against a high volatility in temperature movement. We conclude with the findings that weather derivatives could be useful tools to diminish the financial losses for agricultural industries highly dependent for temperature.

On the uncertainties in effective dose estimates of adult CT head scans

International Nuclear Information System (INIS)

Gregory, Kent J.; Bibbo, Giovanni; Pattison, John E.

2008-01-01

Estimates of the effective dose to adult patients from computed tomography (CT) head scanning can be calculated using a number of different methods. These estimates can be used for a variety of purposes, such as improving scanning protocols, comparing different CT imaging centers, and weighing the benefits of the scan against the risk of radiation-induced cancer. The question arises: What is the uncertainty in these effective dose estimates? This study calculates the uncertainty of effective dose estimates produced by three computer programs (CT-EXPO, CTDosimetry, and ImpactDose) and one method that makes use of dose-length product (DLP) values. Uncertainties were calculated in accordance with an internationally recognized uncertainty analysis guide. For each of the four methods, the smallest and largest overall uncertainties (stated at the 95% confidence interval) were: 20%-31% (CT-EXPO), 15%-28% (CTDosimetry), 20%-36% (ImpactDose), and 22%-32% (DLP), respectively. The overall uncertainties for each method vary due to differences in the uncertainties of factors used in each method. The smallest uncertainties apply when the CT dose index for the scanner has been measured using a calibrated pencil ionization chamber

Geography and Weather: Mountain Meterology.

Science.gov (United States)

Mogil, H. Michael; Collins, H. Thomas

1990-01-01

Provided are 26 ideas to help children explore the effects of mountains on the weather. Weather conditions in Nepal and Colorado are considered separately. Nine additional sources of information are listed. (CW)

Using Artificial Intelligence to Inform Pilots of Weather

Science.gov (United States)

Spirkovska, Lilly; Lodha, Suresh K.

2006-01-01

An automated system to assist a General Aviation (GA) pilot in improving situational awareness of weather in flight is now undergoing development. This development is prompted by the observation that most fatal GA accidents are attributable to loss of weather awareness. Loss of weather awareness, in turn, has been attributed to the difficulty of interpreting traditional preflight weather briefings and the difficulty of both obtaining and interpreting traditional in-flight weather briefings. The developmental automated system not only improves weather awareness but also substantially reduces the time a pilot must spend in acquiring and maintaining weather awareness.

Committed Vulnerability to Extreme Weather Events in the United States (Invited)

Science.gov (United States)

Preston, B. L.

2013-12-01

Despite improvements in disaster risk management in the United States, a trend toward increasing economic losses from extreme weather events has been observed. This trend has been attributed to growth in socioeconomic exposure to extremes driven by the concentration of population and wealth on hazardous landscapes. As geographic patterns of demography and economic development are associated with strong path dependence, the United States is ';locked-in' to future increases in exposure and associated economic losses in the decades ahead, irrespective of the influence of climate change. To understand the influence of path dependence on past and future losses, an index of potential socioeconomic exposure was developed at the U.S. county level based upon population size and inflation-adjusted wealth proxies. Since 1960, exposure has increased preferentially in the U.S. Southeast, particularly coastal and urban counties and Southwest relative to the Great Plains and Northeast. Projected changes in exposure from 2009 to 2054 based upon scenarios of future demographic and economic change suggest a long-term commitment to increasing, but spatially heterogeneous, exposure to extremes, independent of climate change. The implications of this path dependence are examined in the context of several natural hazards. Annualized county-level losses from 1960-2008 for five climate-related natural hazards were normalized to 2009 values and then scaled based upon projected changes in exposure and two different estimates of the exposure elasticity of losses. Results indicate that losses from extreme events will grow by a factor of 1.3-1.7 and 1.8-3.9 by 2025 and 2050, respectively, with the exposure elasticity representing a major source of uncertainty. At more local scales, however, such as rapidly growing metropolitan areas, losses are anticipated to grow more rapidly. As such, improving understanding of the societal implications of the extreme weather events of the future

Effects of Weather on Tourism and its Moderation

Science.gov (United States)

Park, J. H.; Kim, S.; Lee, D. K.

2016-12-01

Tourism is weather sensitive industry (Gómez Martín, 2005). As climate change has been intensifying, the concerns about negative effects of weather on tourism also have been increasing. This study attempted to find ways that mitigate the negative effects from weather on tourism, by analyzing a path of the effects of weather on intention to revisit and its moderation. The data of the study were collected by a self-recording online questionnaire survey of South Korean domestic tourists during August 2015, and 2,412 samples were gathered. A path model of effects of weather on intention to revisit that including moderating effects from physical attraction satisfaction and service satisfaction was ran. Season was controlled in the path model. The model fit was adequate (CMIN/DF=2.372(p=.000), CFI=.974, RMSEA=.024, SRMR=0.040), and the Model Comparison, which assumes that the base model to be correct with season constrained model, showed that there was a seasonal differences in the model ( DF=24, CMIN=32.430, P=.117). By the analysis, it was figured out that weather and weather expectation affected weather satisfaction, and the weather satisfaction affected intention to revisit (spring/fall: .167**, summer: .104**, and winter: .114**). Meanwhile physical attraction satisfaction (.200**), and service satisfaction (.210**) of tourism positively moderated weather satisfaction in summer, and weather satisfaction positively moderated physical attraction (.238**) satisfaction and service satisfaction (.339**). In other words, in summer, dissatisfaction from hot weather was moderated by satisfaction from physical attractions and services, and in spring/fall, comfort weather conditions promoted tourists to accept tourism experience and be satisfied from attractions and services positively. Based on the result, it was expected that if industries focus on offering the good attractions and services based on weather conditions, there would be positive effects to alleviate tourists

Estimating uncertainty in multivariate responses to selection.

Science.gov (United States)

Stinchcombe, John R; Simonsen, Anna K; Blows, Mark W

2014-04-01

Predicting the responses to natural selection is one of the key goals of evolutionary biology. Two of the challenges in fulfilling this goal have been the realization that many estimates of natural selection might be highly biased by environmentally induced covariances between traits and fitness, and that many estimated responses to selection do not incorporate or report uncertainty in the estimates. Here we describe the application of a framework that blends the merits of the Robertson-Price Identity approach and the multivariate breeder's equation to address these challenges. The approach allows genetic covariance matrices, selection differentials, selection gradients, and responses to selection to be estimated without environmentally induced bias, direct and indirect selection and responses to selection to be distinguished, and if implemented in a Bayesian-MCMC framework, statistically robust estimates of uncertainty on all of these parameters to be made. We illustrate our approach with a worked example of previously published data. More generally, we suggest that applying both the Robertson-Price Identity and the multivariate breeder's equation will facilitate hypothesis testing about natural selection, genetic constraints, and evolutionary responses. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Designing a Weather Station

Science.gov (United States)

Roman, Harry T.

2012-01-01

The collection and analysis of weather data is crucial to the location of alternate energy systems like solar and wind. This article presents a design challenge that gives students a chance to design a weather station to collect data in advance of a large wind turbine installation. Data analysis is a crucial part of any science or engineering…

Prevalence of weather sensitivity in Germany and Canada

Science.gov (United States)

Mackensen, Sylvia; Hoeppe, Peter; Maarouf, Abdel; Tourigny, Pierre; Nowak, Dennis

2005-01-01

Several studies have shown that atmospheric conditions can affect well-being or disease, and that some individuals seem to be more sensitive to weather than others. Since epidemiological data on the prevalence of weather-related health effects are lacking, two representative weather sensitivity (WS) surveys were conducted independently in Germany and Canada. The objectives of this paper are: (1) to identify the prevalence of WS in Germany and Canada, (2) to describe weather-related symptoms and the corresponding weather conditions, and (3) to compare the findings in the two countries. In Germany 1,064 citizens (age >16 years) were interviewed in January 2001, and in Canada 1,506 persons (age >18 years) were interviewed in January 1994. The results showed that 19.2% of the German population thought that weather affected their health “to a strong degree,” 35.3% that weather had “some influence on their health” (sum of both = 54.5% weather sensitive), whereas the remaining 45.5% did not consider that weather had an effect on their health status. In Canada 61% of the respondents considered themselves to be sensitive to the weather. The highest prevalence of WS (high + some influence) in Germans was found in the age group older than 60 years (68%), which was almost identical in the Canadian population (69%). The highest frequencies of weather-related symptoms were reported in Germany for stormy weather (30%) and when it became colder (29%). In Canada mainly cold weather (46%), dampness (21%) and rain (20%) were considered to affect health more than other weather types. The most frequent symptoms reported in Germany were headache/migraine (61%), lethargy (47%), sleep disturbances (46%), fatigue (42%), joint pain (40%), irritation (31%), depression (27%), vertigo (26%), concentration problems (26%) and scar pain (23%). Canadian weather-sensitive persons reported colds (29%), psychological effects (28%) and painful joints, muscles or arthritis (10%). In Germany 32

Effect of uncertainties on probabilistic-based design capacity of hydrosystems

Science.gov (United States)

Tung, Yeou-Koung

2018-02-01

Hydrosystems engineering designs involve analysis of hydrometric data (e.g., rainfall, floods) and use of hydrologic/hydraulic models, all of which contribute various degrees of uncertainty to the design process. Uncertainties in hydrosystem designs can be generally categorized into aleatory and epistemic types. The former arises from the natural randomness of hydrologic processes whereas the latter are due to knowledge deficiency in model formulation and model parameter specification. This study shows that the presence of epistemic uncertainties induces uncertainty in determining the design capacity. Hence, the designer needs to quantify the uncertainty features of design capacity to determine the capacity with a stipulated performance reliability under the design condition. Using detention basin design as an example, the study illustrates a methodological framework by considering aleatory uncertainty from rainfall and epistemic uncertainties from the runoff coefficient, curve number, and sampling error in design rainfall magnitude. The effects of including different items of uncertainty and performance reliability on the design detention capacity are examined. A numerical example shows that the mean value of the design capacity of the detention basin increases with the design return period and this relation is found to be practically the same regardless of the uncertainty types considered. The standard deviation associated with the design capacity, when subject to epistemic uncertainty, increases with both design frequency and items of epistemic uncertainty involved. It is found that the epistemic uncertainty due to sampling error in rainfall quantiles should not be ignored. Even with a sample size of 80 (relatively large for a hydrologic application) the inclusion of sampling error in rainfall quantiles resulted in a standard deviation about 2.5 times higher than that considering only the uncertainty of the runoff coefficient and curve number. Furthermore, the

Five case studies of multifamily weatherization programs

Energy Technology Data Exchange (ETDEWEB)

Kinney, L; Wilson, T.; Lewis, G. [Synertech Systems Corp. (United States); MacDonald, M. [Oak Ridge National Lab., TN (United States)

1997-12-31

The multifamily case studies that are the subject of this report were conducted to provide a better understanding of the approach taken by program operators in weatherizing large buildings. Because of significant variations in building construction and energy systems across the country, five states were selected based on their high level of multifamily weatherization. This report summarizes findings from case studies conducted by multifamily weatherization operations in five cities. The case studies were conducted between January and November 1994. Each of the case studies involved extensive interviews with the staff of weatherization subgrantees conducting multifamily weatherization, the inspection of 4 to 12 buildings weatherized between 1991 and 1993, and the analysis of savings and costs. The case studies focused on innovative techniques which appear to work well.

Severe Weather Data Inventory (SWDI)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Severe Weather Data Inventory (SWDI) is an integrated database of severe weather records for the United States. SWDI enables a user to search through a variety...

Laboratory weathering of combusted oil shale

International Nuclear Information System (INIS)

Essington, M.E.

1991-01-01

The objective of this study was to examine the mineralogy and leachate chemistry of three combusted oil shales (two Green River Formation and one New Albany) in a laboratory weathering environment using the humidity cell technique. The mineralogy of the combusted western oil shales (Green River Formation) is process dependent. In general, processing resulted in the formation of anhydrite, lime, periclase, and hematite. During the initial stages of weathering, lime, periclase, and hematite. During the initial stages of weathering, lime, periclase, and anhydrite dissolve and ettringite precipitates. The initial leachates are highly alkaline, saline, and dominated by Na, hydroxide, and SO 4 . As weathering continues, ettringite precipitates. The initial leachates are highly alkaline, saline, and dominated by Na, hydroxide, and SO 4 . As weathering continues, ettringite dissolves, gypsum and calcite precipitate, and the leachates are dominated by Mg, SO 4 , and CO 3 . Leachate pH is rapidly reduced to between 8.5 and 9 with leaching. The combusted eastern oil shale (New Albany) is composed of quartz, illite, hematite, and orthoclase. Weathering results in the precipitation of gypsum. The combusted eastern oil shale did not display a potential to produce acid drainage. Leachate chemistry was dominated by Ca and SO 4 . Element concentrations continually decreased with weathering. IN a western disposal environment receiving minimal atmospheric precipitation, spent oil shale will remain in the initial stages of weathering, and highly alkaline and saline conditions will dominate leachate chemistry. In an eastern disposal environment, soluble salts will be rapidly removed from the spent oil shale to potentially affect the surrounding environment

CO2 consumption and bicarbonate fluxes by chemical weathering in North America.

Science.gov (United States)

Jansen, Nils; Hartmann, Jens; Lauerwald, Ronny

2010-05-01

) that chemical weathering induced CO2 consumption in North America is above world average, and 2) that some regions (e.g. the Rocky Mountains) show extraordinary high CO2 consumption. 8% of the area of North America are responsible for 50% of the total bicarbonate flux and associated CO2 consumption by chemical weathering. The successful implementation of land cover as predictor in the bicarbonate flux model of North America allows the representation of biological factors which may be relevant for processes in the critical zone.

Portable Weather Applications for General Aviation Pilots.

Science.gov (United States)

Ahlstrom, Ulf; Ohneiser, Oliver; Caddigan, Eamon

2016-09-01

The objective of this study was to examine the potential benefits and impact on pilot behavior from the use of portable weather applications. Seventy general aviation (GA) pilots participated in the study. Each pilot was randomly assigned to an experimental or a control group and flew a simulated single-engine GA aircraft, initially under visual meteorological conditions (VMC). The experimental group was equipped with a portable weather application during flight. We recorded measures for weather situation awareness (WSA), decision making, cognitive engagement, and distance from the aircraft to hazardous weather. We found positive effects from the use of the portable weather application, with an increased WSA for the experimental group, which resulted in credibly larger route deviations and credibly greater distances to hazardous weather (≥30 dBZ cells) compared with the control group. Nevertheless, both groups flew less than 20 statute miles from hazardous weather cells, thus failing to follow current weather-avoidance guidelines. We also found a credibly higher cognitive engagement (prefrontal oxygenation levels) for the experimental group, possibly reflecting increased flight planning and decision making on the part of the pilots. Overall, the study outcome supports our hypothesis that portable weather displays can be used without degrading pilot performance on safety-related flight tasks, actions, and decisions as measured within the constraints of the present study. However, it also shows that an increased WSA does not automatically translate to enhanced flight behavior. The study outcome contributes to our knowledge of the effect of portable weather applications on pilot behavior and decision making. © 2016, Human Factors and Ergonomics Society.

Internet-accessible real-time weather information system

Digital Repository Service at National Institute of Oceanography (India)

Desai, R.G.P.; Joseph, A.; Desa, E.; Mehra, P.; Desa, E.; Gouveia, A.D.

An internet-accessible real-time weather information system has been developed. This system provides real-time accessibility to weather information from a multitude of spatially distributed weather stations. The Internet connectivity also offers...

Bacterially Induced Weathering of Ultramafic Rock and Its Implications for Phytoextraction

Science.gov (United States)

Kidd, Petra; Kuffner, Melanie; Prieto-Fernández, Ángeles; Hann, Stephan; Monterroso, Carmela; Sessitsch, Angela; Wenzel, Walter; Puschenreiter, Markus

2013-01-01

The bioavailability of metals in soil is often cited as a limiting factor of phytoextraction (or phytomining). Bacterial metabolites, such as organic acids, siderophores, or biosurfactants, have been shown to mobilize metals, and their use to improve metal extraction has been proposed. In this study, the weathering capacities of, and Ni mobilization by, bacterial strains were evaluated. Minimal medium containing ground ultramafic rock was inoculated with either of two Arthrobacter strains: LA44 (indole acetic acid [IAA] producer) or SBA82 (siderophore producer, PO4 solubilizer, and IAA producer). Trace elements and organic compounds were determined in aliquots taken at different time intervals after inoculation. Trace metal fractionation was carried out on the remaining rock at the end of the experiment. The results suggest that the strains act upon different mineral phases. LA44 is a more efficient Ni mobilizer, apparently solubilizing Ni associated with Mn oxides, and this appeared to be related to oxalate production. SBA82 also leads to release of Ni and Mn, albeit to a much lower extent. In this case, the concurrent mobilization of Fe and Si indicates preferential weathering of Fe oxides and serpentine minerals, possibly related to the siderophore production capacity of the strain. The same bacterial strains were tested in a soil-plant system: the Ni hyperaccumulator Alyssum serpyllifolium subsp. malacitanum was grown in ultramafic soil in a rhizobox system and inoculated with each bacterial strain. At harvest, biomass production and shoot Ni concentrations were higher in plants from inoculated pots than from noninoculated pots. Ni yield was significantly enhanced in plants inoculated with LA44. These results suggest that Ni-mobilizing inoculants could be useful for improving Ni uptake by hyperaccumulator plants. PMID:23793627

Directable weathering of concave rock using curvature estimation.

Science.gov (United States)

Jones, Michael D; Farley, McKay; Butler, Joseph; Beardall, Matthew

2010-01-01

We address the problem of directable weathering of exposed concave rock for use in computer-generated animation or games. Previous weathering models that admit concave surfaces are computationally inefficient and difficult to control. In nature, the spheroidal and cavernous weathering rates depend on the surface curvature. Spheroidal weathering is fastest in areas with large positive mean curvature and cavernous weathering is fastest in areas with large negative mean curvature. We simulate both processes using an approximation of mean curvature on a voxel grid. Both weathering rates are also influenced by rock durability. The user controls rock durability by editing a durability graph before and during weathering simulation. Simulations of rockfall and colluvium deposition further improve realism. The profile of the final weathered rock matches the shape of the durability graph up to the effects of weathering and colluvium deposition. We demonstrate the top-down directability and visual plausibility of the resulting model through a series of screenshots and rendered images. The results include the weathering of a cube into a sphere and of a sheltered inside corner into a cavern as predicted by the underlying geomorphological models.

Detection of Weather Radar Clutter

DEFF Research Database (Denmark)

Bøvith, Thomas

2008-01-01

classification and use a range of different techniques and input data. The first method uses external information from multispectral satellite images to detect clutter. The information in the visual, near-infrared, and infrared parts of the spectrum can be used to distinguish between cloud and cloud-free areas......Weather radars provide valuable information on precipitation in the atmosphere but due to the way radars work, not only precipitation is observed by the weather radar. Weather radar clutter, echoes from non-precipitating targets, occur frequently in the data, resulting in lowered data quality....... Especially in the application of weather radar data in quantitative precipitation estimation and forecasting a high data quality is important. Clutter detection is one of the key components in achieving this goal. This thesis presents three methods for detection of clutter. The methods use supervised...

The uncertainty of reference standards--a guide to understanding factors impacting uncertainty, uncertainty calculations, and vendor certifications.

Science.gov (United States)

Gates, Kevin; Chang, Ning; Dilek, Isil; Jian, Huahua; Pogue, Sherri; Sreenivasan, Uma

2009-10-01

Certified solution standards are widely used in forensic toxicological, clinical/diagnostic, and environmental testing. Typically, these standards are purchased as ampouled solutions with a certified concentration. Vendors present concentration and uncertainty differently on their Certificates of Analysis. Understanding the factors that impact uncertainty and which factors have been considered in the vendor's assignment of uncertainty are critical to understanding the accuracy of the standard and the impact on testing results. Understanding these variables is also important for laboratories seeking to comply with ISO/IEC 17025 requirements and for those preparing reference solutions from neat materials at the bench. The impact of uncertainty associated with the neat material purity (including residual water, residual solvent, and inorganic content), mass measurement (weighing techniques), and solvent addition (solution density) on the overall uncertainty of the certified concentration is described along with uncertainty calculations.

Heisenberg's principle of uncertainty and the uncertainty relations

International Nuclear Information System (INIS)

Redei, Miklos

1987-01-01

The usual verbal form of the Heisenberg uncertainty principle and the usual mathematical formulation (the so-called uncertainty theorem) are not equivalent. The meaning of the concept 'uncertainty' is not unambiguous and different interpretations are used in the literature. Recently a renewed interest has appeared to reinterpret and reformulate the precise meaning of Heisenberg's principle and to find adequate mathematical form. The suggested new theorems are surveyed and critically analyzed. (D.Gy.) 20 refs

Measurement Uncertainty

Science.gov (United States)

Koch, Michael

Measurement uncertainty is one of the key issues in quality assurance. It became increasingly important for analytical chemistry laboratories with the accreditation to ISO/IEC 17025. The uncertainty of a measurement is the most important criterion for the decision whether a measurement result is fit for purpose. It also delivers help for the decision whether a specification limit is exceeded or not. Estimation of measurement uncertainty often is not trivial. Several strategies have been developed for this purpose that will shortly be described in this chapter. In addition the different possibilities to take into account the uncertainty in compliance assessment are explained.

The greenhouse effect and extreme weather

International Nuclear Information System (INIS)

Groenaas, Sigbjoern; Kvamstoe, Nils Gunnar

2002-01-01

The article asserts that an anthropogenic global warming is occurring. This greenhouse effect is expected to cause more occurrences of extreme weather. It is extremely difficult, however, to relate specific weather catastrophes to global warming with certainty, since such extreme weather conditions are rare historically. The subject is controversial. The article also discusses the public debate and the risk of floods

Uncertainty evaluation of a regional real-time system for rain-induced landslides

Science.gov (United States)

Kirschbaum, Dalia; Stanley, Thomas; Yatheendradas, Soni

2015-04-01

A new prototype regional model and evaluation framework has been developed over Central America and the Caribbean region using satellite-based information including precipitation estimates, modeled soil moisture, topography, soils, as well as regionally available datasets such as road networks and distance to fault zones. The algorithm framework incorporates three static variables: a susceptibility map; a 24-hr rainfall triggering threshold; and an antecedent soil moisture variable threshold, which have been calibrated using historic landslide events. The thresholds are regionally heterogeneous and are based on the percentile distribution of the rainfall or antecedent moisture time series. A simple decision tree algorithm framework integrates all three variables with the rainfall and soil moisture time series and generates a landslide nowcast in real-time based on the previous 24 hours over this region. This system has been evaluated using several available landslide inventories over the Central America and Caribbean region. Spatiotemporal uncertainty and evaluation metrics of the model are presented here based on available landslides reports. This work also presents a probabilistic representation of potential landslide activity over the region which can be used to further refine and improve the real-time landslide hazard assessment system as well as better identify and characterize the uncertainties inherent in this type of regional approach. The landslide algorithm provides a flexible framework to improve hazard estimation and reduce uncertainty at any spatial and temporal scale.

Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

Science.gov (United States)

Besha, A. A.; Steele, C. M.; Fernald, A.

2014-12-01

Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

Extreme weather events and infectious disease outbreaks.

Science.gov (United States)

McMichael, Anthony J

2015-01-01

Human-driven climatic changes will fundamentally influence patterns of human health, including infectious disease clusters and epidemics following extreme weather events. Extreme weather events are projected to increase further with the advance of human-driven climate change. Both recent and historical experiences indicate that infectious disease outbreaks very often follow extreme weather events, as microbes, vectors and reservoir animal hosts exploit the disrupted social and environmental conditions of extreme weather events. This review article examines infectious disease risks associated with extreme weather events; it draws on recent experiences including Hurricane Katrina in 2005 and the 2010 Pakistan mega-floods, and historical examples from previous centuries of epidemics and 'pestilence' associated with extreme weather disasters and climatic changes. A fuller understanding of climatic change, the precursors and triggers of extreme weather events and health consequences is needed in order to anticipate and respond to the infectious disease risks associated with human-driven climate change. Post-event risks to human health can be constrained, nonetheless, by reducing background rates of persistent infection, preparatory action such as coordinated disease surveillance and vaccination coverage, and strengthened disaster response. In the face of changing climate and weather conditions, it is critically important to think in ecological terms about the determinants of health, disease and death in human populations.

Carbon dioxide efficiency of terrestrial enhanced weathering.

Science.gov (United States)

Moosdorf, Nils; Renforth, Phil; Hartmann, Jens

2014-05-06

Terrestrial enhanced weathering, the spreading of ultramafic silicate rock flour to enhance natural weathering rates, has been suggested as part of a strategy to reduce global atmospheric CO2 levels. We budget potential CO2 sequestration against associated CO2 emissions to assess the net CO2 removal of terrestrial enhanced weathering. We combine global spatial data sets of potential source rocks, transport networks, and application areas with associated CO2 emissions in optimistic and pessimistic scenarios. The results show that the choice of source rocks and material comminution technique dominate the CO2 efficiency of enhanced weathering. CO2 emissions from transport amount to on average 0.5-3% of potentially sequestered CO2. The emissions of material mining and application are negligible. After accounting for all emissions, 0.5-1.0 t CO2 can be sequestered on average per tonne of rock, translating into a unit cost from 1.6 to 9.9 GJ per tonne CO2 sequestered by enhanced weathering. However, to control or reduce atmospheric CO2 concentrations substantially with enhanced weathering would require very large amounts of rock. Before enhanced weathering could be applied on large scales, more research is needed to assess weathering rates, potential side effects, social acceptability, and mechanisms of governance.

A (Creative) Portrait of the Uncertain Individual: Self-Uncertainty and Individualism Enhance Creative Generation.

Science.gov (United States)

Rios, Kimberly; Markman, Keith D; Schroeder, Juliana; Dyczewski, Elizabeth A

2014-08-01

Building on findings that self-uncertainty motivates attempts to restore certainty about the self, particularly in ways that highlight one's distinctiveness from others, we show that self-uncertainty, relative to uncertainty in general, increases creative generation among individualists. In Studies 1 to 3, high (but not low) individualists performed better on a creative generation task after being primed with self-uncertainty as opposed to general uncertainty. In Study 4, this effect emerged only among those who were told that the task measured creative as opposed to analytical thinking, suggesting that the positive effects of self-uncertainty on performance are specific to tasks that bolster perceptions of uniqueness. In Study 5, self-uncertain individualists experienced a restoration of self-clarity after being induced to think about themselves as more (vs. less) creative. Implications for compensatory responses to self-uncertainty and factors that influence creativity are discussed. © 2014 by the Society for Personality and Social Psychology, Inc.

Estimating predictive hydrological uncertainty by dressing deterministic and ensemble forecasts; a comparison, with application to Meuse and Rhine

Science.gov (United States)

Verkade, J. S.; Brown, J. D.; Davids, F.; Reggiani, P.; Weerts, A. H.

2017-12-01

Two statistical post-processing approaches for estimation of predictive hydrological uncertainty are compared: (i) 'dressing' of a deterministic forecast by adding a single, combined estimate of both hydrological and meteorological uncertainty and (ii) 'dressing' of an ensemble streamflow forecast by adding an estimate of hydrological uncertainty to each individual streamflow ensemble member. Both approaches aim to produce an estimate of the 'total uncertainty' that captures both the meteorological and hydrological uncertainties. They differ in the degree to which they make use of statistical post-processing techniques. In the 'lumped' approach, both sources of uncertainty are lumped by post-processing deterministic forecasts using their verifying observations. In the 'source-specific' approach, the meteorological uncertainties are estimated by an ensemble of weather forecasts. These ensemble members are routed through a hydrological model and a realization of the probability distribution of hydrological uncertainties (only) is then added to each ensemble member to arrive at an estimate of the total uncertainty. The techniques are applied to one location in the Meuse basin and three locations in the Rhine basin. Resulting forecasts are assessed for their reliability and sharpness, as well as compared in terms of multiple verification scores including the relative mean error, Brier Skill Score, Mean Continuous Ranked Probability Skill Score, Relative Operating Characteristic Score and Relative Economic Value. The dressed deterministic forecasts are generally more reliable than the dressed ensemble forecasts, but the latter are sharper. On balance, however, they show similar quality across a range of verification metrics, with the dressed ensembles coming out slightly better. Some additional analyses are suggested. Notably, these include statistical post-processing of the meteorological forecasts in order to increase their reliability, thus increasing the reliability

Nonenergy Benefits from the Weatherization Assistance Program: A Summary of Findings from the Recent Literature

Energy Technology Data Exchange (ETDEWEB)

Schweitzer, M.

2002-04-25

The purpose of this project is to summarize findings reported in the recent literature on nonenergy benefits attributable to the weatherizing of low income homes. This study is a follow-up to the seminal research conducted on the nonenergy benefits attributable to the Department of Energy's national Weatherization Assistance Program by Brown et al. (1993). For this review, nonenergy benefits were broken into three major categories: (1) ratepayer benefits; (2) household benefits; and (3) societal benefits. The ratepayer benefits can be divided into two main subcategories: payment-related benefits and service provision benefits. Similarly, there are two key types of household benefits: those associated with affordable housing and those related to safety, health, and comfort. Societal benefits can be classified as either environmental, social, or economic. Fig. E.S. 1 presents point estimates of the average lifetime monetary value per weatherized home resulting from low income weatherization programs for the key benefit types listed above. These benefits represent net present value estimates (i.e., estimates of the current worth of all benefits expected over the lifetime of the weatherization measures), assuming a 20-year lifetime for installed energy efficiency measures and a 3.2% discount rate. Overall, societal benefits are estimated to be substantially larger than ratepayer and household benefits. Ranges for the societal benefits are also much greater than for the other two categories of nonenergy benefits. The total monetized value for all nonenergy benefit categories associated with weatherizing a home is estimated to be $3346, in 2001 dollars. This represents a national average which, like any point estimate, has considerable uncertainty associated with it. This figure is substantially higher than the total value of nonenergy benefits presented a decade ago in the national weatherization evaluation (Brown et al. 1993) because the current study quantified a

Uncertainty of simulated groundwater levels arising from stochastic transient climate change scenarios

Science.gov (United States)

Goderniaux, Pascal; Brouyère, Serge; Blenkinsop, Stephen; Burton, Aidan; Fowler, Hayley; Dassargues, Alain

2010-05-01

applied not only to the mean of climatic variables, but also across the statistical distributions of these variables. This is important as these distributions are expected to change in the future, with more extreme rainfall events, separated by longer dry periods. (2) The novel approach used in this study can simulate transient climate change from 2010 to 2085, rather than time series representative of a stationary climate for the period 2071-2100. (3) The weather generator is used to generate a large number of equiprobable climate change scenarios for each RCM, representative of the natural variability of the weather. All of these scenarios are applied as input to the Geer basin model to assess the projected impact of climate change on groundwater levels, the uncertainty arising for different RCM projections and the uncertainty linked to natural climatic variability. Using the output results from all scenarios, 95% confidence intervals are calculated for each year and month between 2010 and 2085. The climate change scenarios for the Geer basin model predict hotter and drier summers and warmer and wetter winters. Considering the results of this study, it is very likely that groundwater levels and surface flow rates in the Geer basin will decrease by the end of the century. This is of concern because it also means that groundwater quantities available for abstraction will also decrease. However, this study also shows that the uncertainty of these projections is relatively large compared to the projected changes so that it remains difficult to confidently determine the magnitude of the decrease. The use and combination of an integrated surface - subsurface model and stochastic climate change scenarios has never been used in previous climate change impact studies on groundwater resources. It constitutes an innovation and is an important tool for helping water managers to take decisions.

Cost-Loss Analysis of Ensemble Solar Wind Forecasting: Space Weather Use of Terrestrial Weather Tools

Science.gov (United States)

Henley, E. M.; Pope, E. C. D.

2017-12-01

This commentary concerns recent work on solar wind forecasting by Owens and Riley (2017). The approach taken makes effective use of tools commonly used in terrestrial weather—notably, via use of a simple model—generation of an "ensemble" forecast, and application of a "cost-loss" analysis to the resulting probabilistic information, to explore the benefit of this forecast to users with different risk appetites. This commentary aims to highlight these useful techniques to the wider space weather audience and to briefly discuss the general context of application of terrestrial weather approaches to space weather.

Uncertainties in modeling low-energy neutrino-induced reactions on iron-group nuclei

International Nuclear Information System (INIS)

Paar, N.; Vretenar, D.; Suzuki, T.; Honma, M.; Marketin, T.

2011-01-01

Charged-current neutrino-nucleus cross sections for 54,56 Fe and 58,60 Ni are calculated and compared using frameworks based on relativistic and Skyrme energy-density functionals and on the shell model. The current theoretical uncertainties in modeling neutrino-nucleus cross sections are assessed in relation to the predicted Gamow-Teller transition strength and available data, to multipole decomposition of the cross sections, and to cross sections averaged over the Michel flux and Fermi-Dirac distribution. By employing different microscopic approaches and models, the decay-at-rest (DAR) neutrino- 56 Fe cross section and its theoretical uncertainty are estimated to be th =(258±57)x10 -42 cm 2 , in very good agreement with the experimental value exp =(256±108±43)x10 -42 cm 2 .

Federal Aviation Administration weather program to improve aviation safety

Science.gov (United States)

Wedan, R. W.

1983-01-01

The implementation of the National Airspace System (NAS) will improve safety services to aviation. These services include collision avoidance, improved landing systems and better weather data acquisition and dissemination. The program to improve the quality of weather information includes the following: Radar Remote Weather Display System; Flight Service Automation System; Automatic Weather Observation System; Center Weather Processor, and Next Generation Weather Radar Development.

Weatherization Works--Summary of Findings from the Retrospective Evaluation of the U.S. DOE's Weatherization Assistance Program

Energy Technology Data Exchange (ETDEWEB)

Tonn, Bruce Edward [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Carroll, David [APPRISE, Inc., Princeton, NJ (United States); Pigg, Scott [Energy Center of Wisconsin, Madison, WI (United States); Blasnik, Michael [Blasnik & Associates, Roslindale, MA (United States); Dalhoff, Greg [Dalhoff & Associates, Verona, WI (United States); Berger, Jacqueline [APPRISE, Inc., Princeton, NJ (United States); Rose, Erin M [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hawkins, Beth A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Eisenberg, Joel Fred [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ucar, Ferit [APPRISE, Inc., Princeton, NJ (United States); Bensch, Ingo [Energy Center of Wisconsin, Madison, WI (United States); Cowan, Claire [Energy Center of Wisconsin, Madison, WI (United States)

2015-10-01

This report presents a summary of the studies and analyses that compose the retrospective evaluation of the U.S. Department of Energy s low-income Weatherization Assistance Program (WAP). WAP provides grants to Grantees (i.e., states) that then provide grants to Subgrantees (i.e., local weatherization agencies) to weatherize low-income homes. This evaluation focused on the WAP Program Year 2008. The retrospective evaluation produced twenty separate reports, including this summary. Four separate reports address the energy savings, energy cost savings, and cost effectiveness of WAP across four housing types: single family, mobile home, small multifamily, and large multifamily. Other reports address the environmental emissions, macroeconomic, and health and household-related benefits attributable to WAP, and characterize the program, its recipients, and those eligible for the program. Major field studies are also summarized, including a major indoor air quality study and a follow-up ventilation study, an in-depth in-field assessment of weatherization work and quality, and a study that assesses reasons for variations in energy savings across homes. Results of surveys of weatherization staff, occupants, occupants satisfaction with weatherization services provided, and weatherization trainees are summarized. Lastly, this report summarizes a set of fifteen case studies of high-performing and unique local weatherization agencies.

Risk, unexpected uncertainty, and estimation uncertainty: Bayesian learning in unstable settings.

Directory of Open Access Journals (Sweden)

Elise Payzan-LeNestour

Full Text Available Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating.

The impact of weather and ocean forecasting on hydrocarbon production and pollution management in the Gulf of Mexico

International Nuclear Information System (INIS)

Kaiser, Mark J.; Pulsipher, Allan G.

2007-01-01

Over the past 2 years, the vulnerability of offshore production in the Gulf of Mexico (GOM) has been brought to light by extensive damage to oil and gas facilities and pipelines resulting from Hurricanes Ivan, Katrina, and Rita. The occurrences of extreme weather regularly force operators to shut-down production, cease drilling and construction activities, and evacuate personnel. Loop currents and eddies can also impact offshore operations and delay installation and drilling activities and reduce the effectiveness of oil spill response strategies. The purpose of this paper is to describe how weather and ocean forecasting impact production activities and pollution management in the GOM. Physical outcome and decision models in support of production and development activities and oil spill response management are presented, and the expected economic benefits that may result from the implementation of an integrated ocean observation network in the region are summarized. Improved ocean observation systems are expected to reduce the uncertainty of forecasting and to enhance the value of ocean/weather information throughout the Gulf region. The source of benefits and the size of activity from which improved ocean observation benefits may be derived are estimated for energy development and production activities and oil spill response management

Using Music to Communicate Weather and Climate

Science.gov (United States)

Williams, P.; Aplin, K. L.; Brown, S.

2017-12-01

Depictions of weather and other atmospheric phenomena are common throughout the arts. Unlike in the visual arts, however, there has been little study of meteorological inspiration in music. This presentation will discuss the frequencies with which different weather types have been depicted in music over time, covering the period from the seventeenth century to the present day. Beginning with classical orchestral music, we find that composers were generally influenced by their own country's climate in the type of weather they chose to represent. Depictions of weather vary from explicit mimicry using traditional and specialized orchestral instruments, through to subtle suggestions. Pieces depicting stormy weather tend to be in minor keys, whereas pieces depicting fair weather tend to be in major keys. As befits the national stereotype, British composers seem disproportionately keen to depict the UK's variable weather patterns and stormy coastline. Moving onto modern popular music, we have identified and analyzed over 750 songs referring to different weather types. We find that lyrical references to bad weather peaked in songs written during the stormy 1950s and 60s, when there were many hurricanes, before declining in the relatively calm 1970s and 80s. This finding again suggests a causal link between song-writers' meteorological environments and compositional outputs. Composers and song-writers have a unique ability to emotionally connect their listeners to the environment. This ability could be exploited to communicate environmental science to a broader audience. Our work provides a catalogue of cultural responses to weather before (and during the early stages of) climate change. The effects of global warming may influence musical expression in future, in which case our work will provide a baseline for comparison.

Chromium isotope fractionation during oxidative weathering of a modern basaltic weathering profile

DEFF Research Database (Denmark)

D'Arcy, Joan Mary; Døssing, Lasse Nørbye; Frei, Robert

Chromium can be used as a tracer of redox sensitive environmental processes. In soils Cr (III) is inert, immobile and resides predominantly in minerals, clays and oxides. Cr (VI) is toxic, soluble and mobile and is usually lost from the soil to local run off. Chromium isotopes have been shown...... to fractionate under both reducing and oxidizing conditions [1, 2]. Recent studies on d53Cr isotopes in laterite soils show that oxidative weathering of Cr-bearing rocks is accompanied by an isotopic fractionation, where by the lighter isotopes are retained in the residual soil and the heavier isotope...... is enriched in local runoff [1]. This study aims to quantify the stable Cr isotope composition of two modern basaltic weathering profiles, to help better understand the processes that oxidize inert Cr (III) to toxic Cr (VI). We sampled basaltic weathering profiles and associated river waters from areas of two...

Space Weather Research: Indian perspective

Science.gov (United States)

Bhardwaj, Anil; Pant, Tarun Kumar; Choudhary, R. K.; Nandy, Dibyendu; Manoharan, P. K.

2016-12-01

Space weather, just like its meteorological counterpart, is of extreme importance when it comes to its impact on terrestrial near- and far-space environments. In recent years, space weather research has acquired an important place as a thrust area of research having implications both in space science and technology. The presence of satellites and other technological systems from different nations in near-Earth space necessitates that one must have a comprehensive understanding not only of the origin and evolution of space weather processes but also of their impact on technology and terrestrial upper atmosphere. To address this aspect, nations across the globe including India have been investing in research concerning Sun, solar processes and their evolution from solar interior into the interplanetary space, and their impact on Earth's magnetosphere-ionosphere-thermosphere system. In India, over the years, a substantial amount of work has been done in each of these areas by various agencies/institutions. In fact, India has been, and continues to be, at the forefront of space research and has ambitious future programs concerning these areas encompassing space weather. This review aims at providing a glimpse of this Indian perspective on space weather research to the reader and presenting an up-to-date status of the same.

Quantitative impact of aerosols on numerical weather prediction. Part II: Impacts to IR radiance assimilation

Science.gov (United States)

Marquis, J. W.; Campbell, J. R.; Oyola, M. I.; Ruston, B. C.; Zhang, J.

2017-12-01

This is part II of a two-part series examining the impacts of aerosol particles on weather forecasts. In this study, the aerosol indirect effects on weather forecasts are explored by examining the temperature and moisture analysis associated with assimilating dust contaminated hyperspectral infrared radiances. The dust induced temperature and moisture biases are quantified for different aerosol vertical distribution and loading scenarios. The overall impacts of dust contamination on temperature and moisture forecasts are quantified over the west coast of Africa, with the assistance of aerosol retrievals from AERONET, MPL, and CALIOP. At last, methods for improving hyperspectral infrared data assimilation in dust contaminated regions are proposed.

Propagation of hydro-meteorological uncertainty in a model cascade framework to inundation prediction

Science.gov (United States)

Rodríguez-Rincón, J. P.; Pedrozo-Acuña, A.; Breña-Naranjo, J. A.

2015-07-01

This investigation aims to study the propagation of meteorological uncertainty within a cascade modelling approach to flood prediction. The methodology was comprised of a numerical weather prediction (NWP) model, a distributed rainfall-runoff model and a 2-D hydrodynamic model. The uncertainty evaluation was carried out at the meteorological and hydrological levels of the model chain, which enabled the investigation of how errors that originated in the rainfall prediction interact at a catchment level and propagate to an estimated inundation area and depth. For this, a hindcast scenario is utilised removing non-behavioural ensemble members at each stage, based on the fit with observed data. At the hydrodynamic level, an uncertainty assessment was not incorporated; instead, the model was setup following guidelines for the best possible representation of the case study. The selected extreme event corresponds to a flood that took place in the southeast of Mexico during November 2009, for which field data (e.g. rain gauges; discharge) and satellite imagery were available. Uncertainty in the meteorological model was estimated by means of a multi-physics ensemble technique, which is designed to represent errors from our limited knowledge of the processes generating precipitation. In the hydrological model, a multi-response validation was implemented through the definition of six sets of plausible parameters from past flood events. Precipitation fields from the meteorological model were employed as input in a distributed hydrological model, and resulting flood hydrographs were used as forcing conditions in the 2-D hydrodynamic model. The evolution of skill within the model cascade shows a complex aggregation of errors between models, suggesting that in valley-filling events hydro-meteorological uncertainty has a larger effect on inundation depths than that observed in estimated flood inundation extents.

Space Weather and Real-Time Monitoring

Directory of Open Access Journals (Sweden)

S Watari

2009-04-01

Full Text Available Recent advance of information and communications technology enables to collect a large amount of ground-based and space-based observation data in real-time. The real-time data realize nowcast of space weather. This paper reports a history of space weather by the International Space Environment Service (ISES in association with the International Geophysical Year (IGY and importance of real-time monitoring in space weather.

Seafloor weathering buffering climate: numerical experiments

Science.gov (United States)

Farahat, N. X.; Archer, D. E.; Abbot, D. S.

2013-12-01

Continental silicate weathering is widely held to consume atmospheric CO2 at a rate controlled in part by temperature, resulting in a climate-weathering feedback [Walker et al., 1981]. It has been suggested that weathering of oceanic crust of warm mid-ocean ridge flanks also has a CO2 uptake rate that is controlled by climate [Sleep and Zahnle, 2001; Brady and Gislason, 1997]. Although this effect might not be significant on present-day Earth [Caldeira, 1995], seafloor weathering may be more pronounced during snowball states [Le Hir et al., 2008], during the Archean when seafloor spreading rates were faster [Sleep and Zahnle, 2001], and on waterworld planets [Abbot et al., 2012]. Previous studies of seafloor weathering have made significant contributions using qualitative, generally one-box, models, and the logical next step is to extend this work using a spatially resolved model. For example, experiments demonstrate that seafloor weathering reactions are temperature dependent, but it is not clear whether the deep ocean temperature affects the temperature at which the reactions occur, or if instead this temperature is set only by geothermal processes. Our goal is to develop a 2-D numerical model that can simulate hydrothermal circulation and resulting alteration of oceanic basalts, and can therefore address such questions. A model of diffusive and convective heat transfer in fluid-saturated porous media simulates hydrothermal circulation through porous oceanic basalt. Unsteady natural convection is solved for using a Darcy model of porous media flow that has been extensively benchmarked. Background hydrothermal circulation is coupled to mineral reaction kinetics of basaltic alteration and hydrothermal mineral precipitation. In order to quantify seafloor weathering as a climate-weathering feedback process, this model focuses on hydrothermal reactions that influence carbon uptake as well as ocean alkalinity: silicate rock dissolution, calcium and magnesium leaching

Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

Science.gov (United States)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

observations and several years of archived forecasts, overall empirical error distributions termed 'overall error' were for each gauge derived for a range of relevant forecast lead times. b) The error distributions vary strongly with the hydrometeorological situation, therefore a subdivision into the hydrological cases 'low flow, 'rising flood', 'flood', flood recession' was introduced. c) For the sake of numerical compression, theoretical distributions were fitted to the empirical distributions using the method of moments. Here, the normal distribution was generally best suited. d) Further data compression was achieved by representing the distribution parameters as a function (second-order polynome) of lead time. In general, the 'overall error' obtained from the above procedure is most useful in regions where large human impact occurs and where the influence of the meteorological forecast is limited. In upstream regions however, forecast uncertainty is strongly dependent on the current predictability of the atmosphere, which is contained in the spread of an ensemble forecast. Including this dynamically in the hydrological forecast uncertainty estimation requires prior elimination of the contribution of the weather forecast to the 'overall error'. This was achieved by calculating long series of hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The resulting error distribution is termed 'model error' and can be applied on hydrological ensemble forecasts, where ensemble rainfall forecasts are used as forcing. The concept will be illustrated by examples (good and bad ones) covering a wide range of catchment sizes, hydrometeorological regimes and quality of hydrological model calibration. The methodology to combine the static and dynamic shares of uncertainty will be presented in part II of this study.

Towards resiliency with micro-grids: Portfolio optimization and investment under uncertainty

Science.gov (United States)

Gharieh, Kaveh

Energy security and sustained supply of power are critical for community welfare and economic growth. In the face of the increased frequency and intensity of extreme weather conditions which can result in power grid outage, the value of micro-grids to improve the communities' power reliability and resiliency is becoming more important. Micro-grids capability to operate in islanded mode in stressed-out conditions, dramatically decreases the economic loss of critical infrastructure in power shortage occasions. More wide-spread participation of micro-grids in the wholesale energy market in near future, makes the development of new investment models necessary. However, market and price risks in short term and long term along with risk factors' impacts shall be taken into consideration in development of new investment models. This work proposes a set of models and tools to address different problems associated with micro-grid assets including optimal portfolio selection, investment and financing in both community and a sample critical infrastructure (i.e. wastewater treatment plant) levels. The models account for short-term operational volatilities and long-term market uncertainties. A number of analytical methodologies and financial concepts have been adopted to develop the aforementioned models as follows. (1) Capital budgeting planning and portfolio optimization models with Monte Carlo stochastic scenario generation are applied to derive the optimal investment decision for a portfolio of micro-grid assets considering risk factors and multiple sources of uncertainties. (2) Real Option theory, Monte Carlo simulation and stochastic optimization techniques are applied to obtain optimal modularized investment decisions for hydrogen tri-generation systems in wastewater treatment facilities, considering multiple sources of uncertainty. (3) Public Private Partnership (PPP) financing concept coupled with investment horizon approach are applied to estimate public and private

A fresh look at weather impact on peak electricity demand and energy use of buildings using 30-year actual weather data

International Nuclear Information System (INIS)

Hong, Tianzhen; Chang, Wen-Kuei; Lin, Hung-Wen

2013-01-01

Highlights: • Weather has a significant impact on both the peak electricity demand and energy use. • Weather impact varies with building type, building efficiency level, and location. • Simulated results using TMY3 weather data can under or over estimate those of AMY. • It is crucial to assess performance of buildings using long-term actual weather data. • Findings enable building stakeholders to make better decisions on weather impact. - Abstract: Buildings consume more than one third of the world’s total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980–2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: (1) annual weather variation has a greater impact on the peak electricity demand than it does

[Influence of Uncertainty and Uncertainty Appraisal on Self-management in Hemodialysis Patients].

Science.gov (United States)

Jang, Hyung Suk; Lee, Chang Suk; Yang, Young Hee

2015-04-01

This study was done to examine the relation of uncertainty, uncertainty appraisal, and self-management in patients undergoing hemodialysis, and to identify factors influencing self-management. A convenience sample of 92 patients receiving hemodialysis was selected. Data were collected using a structured questionnaire and medical records. The collected data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlations and multiple regression analysis with the SPSS/WIN 20.0 program. The participants showed a moderate level of uncertainty with the highest score being for ambiguity among the four uncertainty subdomains. Scores for uncertainty danger or opportunity appraisals were under the mid points. The participants were found to perform a high level of self-management such as diet control, management of arteriovenous fistula, exercise, medication, physical management, measurements of body weight and blood pressure, and social activity. The self-management of participants undergoing hemodialysis showed a significant relationship with uncertainty and uncertainty appraisal. The significant factors influencing self-management were uncertainty, uncertainty opportunity appraisal, hemodialysis duration, and having a spouse. These variables explained 32.8% of the variance in self-management. The results suggest that intervention programs to reduce the level of uncertainty and to increase the level of uncertainty opportunity appraisal among patients would improve the self-management of hemodialysis patients.

44 CFR 15.3 - Access to Mt. Weather.

Science.gov (United States)

2010-10-01

... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Access to Mt. Weather. 15.3... HOMELAND SECURITY GENERAL CONDUCT AT THE MT. WEATHER EMERGENCY ASSISTANCE CENTER AND AT THE NATIONAL EMERGENCY TRAINING CENTER § 15.3 Access to Mt. Weather. Mt. Weather contains classified material and areas...

The Challenge of Weather Prediction

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 3. The Challenge of Weather Prediction Old and Modern Ways of Weather Forecasting. B N Goswami. Series Article Volume 2 Issue 3 March 1997 pp 8-15. Fulltext. Click here to view fulltext PDF. Permanent link:

Three-dimensional visualization of ensemble weather forecasts – Part 1: The visualization tool Met.3D (version 1.0

Directory of Open Access Journals (Sweden)

M. Rautenhaus

2015-07-01

Full Text Available We present "Met.3D", a new open-source tool for the interactive three-dimensional (3-D visualization of numerical ensemble weather predictions. The tool has been developed to support weather forecasting during aircraft-based atmospheric field campaigns; however, it is applicable to further forecasting, research and teaching activities. Our work approaches challenging topics related to the visual analysis of numerical atmospheric model output – 3-D visualization, ensemble visualization and how both can be used in a meaningful way suited to weather forecasting. Met.3D builds a bridge from proven 2-D visualization methods commonly used in meteorology to 3-D visualization by combining both visualization types in a 3-D context. We address the issue of spatial perception in the 3-D view and present approaches to using the ensemble to allow the user to assess forecast uncertainty. Interactivity is key to our approach. Met.3D uses modern graphics technology to achieve interactive visualization on standard consumer hardware. The tool supports forecast data from the European Centre for Medium Range Weather Forecasts (ECMWF and can operate directly on ECMWF hybrid sigma-pressure level grids. We describe the employed visualization algorithms, and analyse the impact of the ECMWF grid topology on computing 3-D ensemble statistical quantities. Our techniques are demonstrated with examples from the T-NAWDEX-Falcon 2012 (THORPEX – North Atlantic Waveguide and Downstream Impact Experiment campaign.

Weatherization Beyond the Numbers: Case Studies of Fifteen High-performing Weatherization Agencies - Conducted May 2011 through July 2012

Energy Technology Data Exchange (ETDEWEB)

Tonn, Bruce Edward [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Rose, Erin M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hawkins, Beth A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2014-09-01

The report presents fifteen individual case studies of high-performing and unique local weatherization agencies. This research was one component of the retrospective evaluation of the U.S. Department of Energy s Weatherization Assistance Program. The agencies were chosen to represent a range of contexts and approaches to weatherization. For example, the set of agencies includes a mix of urban and rural agencies, those that mainly use in-house crews to weatherize homes versus those that use contractor crews, and a mix of locations, from very cold climates to moderate to hot humid and dry climates. The case studies were mainly based on site visits to the agencies that encompassed interviews with program directors, weatherization crews, and recipients of weatherization. This information was supplemented by secondary materials. The cases document the diversity of contexts and challenges faced by the agencies and how they operate on a day-by-day basis. The cases also high common themes found throughout the agencies, such as their focus on mission and respect for their clients.

Mercury's Weather-Beaten Surface: Understanding Mercury in the Context of Lunar and Asteroidal Space Weathering Studies

Science.gov (United States)

Domingue, Deborah L.; Chapman, Clark. R.; Killen, Rosemary M.; Zurbuchen, Thomas H.; Gilbert, Jason A.; Sarantos, Menelaos; Benna, Mehdi; Slavin, James A.; Schriver, David; Travnicek, Pavel M.;

Communicating Uncertainty about Climate Change for Application to Security Risk Management

Science.gov (United States)

Gulledge, J. M.

2011-12-01

The science of climate change has convincingly demonstrated that human activities, including the release of greenhouse gases, land-surface changes, particle emissions, and redistribution of water, are changing global and regional climates. Consequently, key institutions are now concerned about the potential social impacts of climate change. For example, the 2010 Quadrennial Defense Review Report from the U.S. Department of Defense states that "climate change, energy security, and economic stability are inextricably linked." Meanwhile, insured losses from climate and weather-related natural disasters have risen dramatically over the past thirty years. Although these losses stem largely from socioeconomic trends, insurers are concerned that climate change could exacerbate this trend and render certain types of climate risk non-diversifiable. Meanwhile, the climate science community-broadly defined as physical, biological, and social scientists focused on some aspect of climate change-remains largely focused scholarly activities that are valued in the academy but not especially useful to decision makers. On the other hand, climate scientists who engage in policy discussions have generally permitted vested interests who support or oppose climate policies to frame the discussion of climate science within the policy arena. Such discussions focus on whether scientific uncertainties are sufficiently resolved to justify policy and the vested interests overstate or understate key uncertainties to support their own agendas. Consequently, the scientific community has become absorbed defending scientific findings to the near exclusion of developing novel tools to aid in risk-based decision-making. For example, the Intergovernmental Panel on Climate Change (IPCC), established expressly for the purpose of informing governments, has largely been engaged in attempts to reduce unavoidable uncertainties rather than helping the world's governments define a science-based risk

49 CFR 192.231 - Protection from weather.

Science.gov (United States)

2010-10-01

... 49 Transportation 3 2010-10-01 2010-10-01 false Protection from weather. 192.231 Section 192.231 Transportation Other Regulations Relating to Transportation (Continued) PIPELINE AND HAZARDOUS MATERIALS SAFETY... weather. The welding operation must be protected from weather conditions that would impair the quality of...

[Effect of weather on odontogenic abscesses].

Science.gov (United States)

Nissen, G; Schmidseder, R

1978-11-01

An increased frequency of odontogenous abcesses was observed on certain days in the course of routine clinical practice. We therefore investigated the possibility of a statistically significant weather-related odontogenous soft-tissue purulence originating from chronic apical periodontitis. Medical reports of patients treated between 1970 and 1977 were used. Our study indicated that the frequency of odontogenous abcesses was significantly higher with cyclonic weather conditions, i.e., weather with low barometric pressure.

WRF-Fire: coupled weather-wildland fire modeling with the weather research and forecasting model

Science.gov (United States)

Janice L. Coen; Marques Cameron; John Michalakes; Edward G. Patton; Philip J. Riggan; Kara M. Yedinak

2012-01-01

A wildland fire behavior module (WRF-Fire) was integrated into the Weather Research and Forecasting (WRF) public domain numerical weather prediction model. The fire module is a surface fire behavior model that is two-way coupled with the atmospheric model. Near-surface winds from the atmospheric model are interpolated to a finer fire grid and used, with fuel properties...

Weathering of the Rio Blanco Quartz Diorite, Luquillo Mountains, Puerto Rico: Coupling Oxidation, Dissolution, And Fracturing

International Nuclear Information System (INIS)

Buss, H.L.; Sak, P.B.; Webb, S.M.; Brantley, S.L.

2008-01-01

In the mountainous Rio Icacos watershed in northeastern Puerto Rico, quartz diorite bedrock weathers spheroidally, producing a 0.2-2 m thick zone of partially weathered rock layers (∼2.5 cm thickness each) called rindlets, which form concentric layers around corestones. Spheroidal fracturing has been modeled to occur when a weathering reaction with a positive ΔV of reaction builds up elastic strain energy. The rates of spheroidal fracturing and saprolite formation are therefore controlled by the rate of the weathering reaction. Chemical, petrographic, and spectroscopic evidence demonstrates that biotite oxidation is the most likely fracture-inducing reaction. This reaction occurs with an expansion in d (0 0 1) from 10.0 to 10.5 (angstrom), forming 'altered biotite'. Progressive biotite oxidation across the rindlet zone was inferred from thin sections and gradients in K and Fe(II). Using the gradient in Fe(II) and constraints based on cosmogenic age dates, we calculated a biotite oxidation reaction rate of 8.2 x 10 -14 mol biotite m -2 s -1 . Biotite oxidation was documented within the bedrock corestone by synchrotron X-ray microprobe fluorescence imaging and XANES. X-ray microprobe images of Fe(II) and Fe(III) at 2 (micro)m resolution revealed that oxidized zones within individual biotite crystals are the first evidence of alteration of the otherwise unaltered corestone. Fluids entering along fractures lead to the dissolution of plagioclase within the rindlet zone. Within 7 cm surrounding the rindlet-saprolite interface, hornblende dissolves to completion at a rate of 6.3 x 10 -13 mol hornblende m -2 s -1 : the fastest reported rate of hornblende weathering in the field. This rate is consistent with laboratory-derived hornblende dissolution rates. By revealing the coupling of these mineral weathering reactions to fracturing and porosity formation we are able to describe the process by which the quartz diorite bedrock disaggregates and forms saprolite. In the

Efficient Ways to Learn Weather Radar Polarimetry

Science.gov (United States)

Cao, Qing; Yeary, M. B.; Zhang, Guifu

2012-01-01

The U.S. weather radar network is currently being upgraded with dual-polarization capability. Weather radar polarimetry is an interdisciplinary area of engineering and meteorology. This paper presents efficient ways to learn weather radar polarimetry through several basic and practical topics. These topics include: 1) hydrometeor scattering model…

Weatherization Innovation Pilot Program (WIPP): Technical Assistance Summary

Energy Technology Data Exchange (ETDEWEB)

Hollander, A.

2014-09-01

The U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy (EERE) Weatherization and Intergovernmental Programs Office (WIPO) launched the Weatherization Innovation Pilot Program (WIPP) to accelerate innovations in whole-house weatherization and advance DOE's goal of increasing the energy efficiency and health and safety of low-income residences without the utilization of additional taxpayer funding. Sixteen WIPP grantees were awarded a total of $30 million in Weatherization Assistance Program (WAP) funds in September 2010. These projects focused on: including nontraditional partners in weatherization service delivery; leveraging significant non-federal funding; and improving the effectiveness of low-income weatherization through the use of new materials, technologies, behavior-change models, and processes.

Instrument uncertainty predictions

International Nuclear Information System (INIS)

Coutts, D.A.

1991-07-01

The accuracy of measurements and correlations should normally be provided for most experimental activities. The uncertainty is a measure of the accuracy of a stated value or equation. The uncertainty term reflects a combination of instrument errors, modeling limitations, and phenomena understanding deficiencies. This report provides several methodologies to estimate an instrument's uncertainty when used in experimental work. Methods are shown to predict both the pretest and post-test uncertainty

Activities of NICT space weather project

Science.gov (United States)

Murata, Ken T.; Nagatsuma, Tsutomu; Watari, Shinichi; Shinagawa, Hiroyuki; Ishii, Mamoru

NICT (National Institute of Information and Communications Technology) has been in charge of space weather forecast service in Japan for more than 20 years. The main target region of the space weather is the geo-space in the vicinity of the Earth where human activities are dominant. In the geo-space, serious damages of satellites, international space stations and astronauts take place caused by energetic particles or electromagnetic disturbances: the origin of the causes is dynamically changing of solar activities. Positioning systems via GPS satellites are also im-portant recently. Since the most significant effect of positioning error comes from disturbances of the ionosphere, it is crucial to estimate time-dependent modulation of the electron density profiles in the ionosphere. NICT is one of the 13 members of the ISES (International Space Environment Service), which is an international assembly of space weather forecast centers under the UNESCO. With help of geo-space environment data exchanging among the member nations, NICT operates daily space weather forecast service every day to provide informa-tion on forecasts of solar flare, geomagnetic disturbances, solar proton event, and radio-wave propagation conditions in the ionosphere. The space weather forecast at NICT is conducted based on the three methodologies: observations, simulations and informatics (OSI model). For real-time or quasi real-time reporting of space weather, we conduct our original observations: Hiraiso solar observatory to monitor the solar activity (solar flare, coronal mass ejection, and so on), domestic ionosonde network, magnetometer HF radar observations in far-east Siberia, and south-east Asia low-latitude ionosonde network (SEALION). Real-time observation data to monitor solar and solar-wind activities are obtained through antennae at NICT from ACE and STEREO satellites. We have a middle-class super-computer (NEC SX-8R) to maintain real-time computer simulations for solar and solar

Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

DEFF Research Database (Denmark)

Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

2006-01-01

A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

Uncertainty in hydrological signatures

Science.gov (United States)

McMillan, Hilary; Westerberg, Ida

2015-04-01

Information that summarises the hydrological behaviour or flow regime of a catchment is essential for comparing responses of different catchments to understand catchment organisation and similarity, and for many other modelling and water-management applications. Such information types derived as an index value from observed data are known as hydrological signatures, and can include descriptors of high flows (e.g. mean annual flood), low flows (e.g. mean annual low flow, recession shape), the flow variability, flow duration curve, and runoff ratio. Because the hydrological signatures are calculated from observed data such as rainfall and flow records, they are affected by uncertainty in those data. Subjective choices in the method used to calculate the signatures create a further source of uncertainty. Uncertainties in the signatures may affect our ability to compare different locations, to detect changes, or to compare future water resource management scenarios. The aim of this study was to contribute to the hydrological community's awareness and knowledge of data uncertainty in hydrological signatures, including typical sources, magnitude and methods for its assessment. We proposed a generally applicable method to calculate these uncertainties based on Monte Carlo sampling and demonstrated it for a variety of commonly used signatures. The study was made for two data rich catchments, the 50 km2 Mahurangi catchment in New Zealand and the 135 km2 Brue catchment in the UK. For rainfall data the uncertainty sources included point measurement uncertainty, the number of gauges used in calculation of the catchment spatial average, and uncertainties relating to lack of quality control. For flow data the uncertainty sources included uncertainties in stage/discharge measurement and in the approximation of the true stage-discharge relation by a rating curve. The resulting uncertainties were compared across the different signatures and catchments, to quantify uncertainty

The role of situation assessment and flight experience in pilots' decisions to continue visual flight rules flight into adverse weather.

Science.gov (United States)

Wiegmann, Douglas A; Goh, Juliana; O'Hare, David

2002-01-01

Visual flight rules (VFR) flight into instrument meteorological conditions (IMC) is a major safety hazard in general aviation. In this study we examined pilots' decisions to continue or divert from a VFR flight into IMC during a dynamic simulation of a cross-country flight. Pilots encountered IMC either early or later into the flight, and the amount of time and distance pilots flew into the adverse weather prior to diverting was recorded. Results revealed that pilots who encountered the deteriorating weather earlier in the flight flew longer into the weather prior to diverting and had more optimistic estimates of weather conditions than did pilots who encountered the deteriorating weather later in the flight. Both the time and distance traveled into the weather prior to diverting were negatively correlated with pilots' previous flight experience. These findings suggest that VFR flight into IMC may be attributable, at least in part, to poor situation assessment and experience rather than to motivational judgment that induces risk-taking behavior as more time and effort are invested in a flight. Actual or potential applications of this research include the design of interventions that focus on improving weather evaluation skills in addition to addressing risk-taking attitudes.

A review of the generalized uncertainty principle

International Nuclear Information System (INIS)

Tawfik, Abdel Nasser; Diab, Abdel Magied

2015-01-01

Based on string theory, black hole physics, doubly special relativity and some ‘thought’ experiments, minimal distance and/or maximum momentum are proposed. As alternatives to the generalized uncertainty principle (GUP), the modified dispersion relation, the space noncommutativity, the Lorentz invariance violation, and the quantum-gravity-induced birefringence effects are summarized. The origin of minimal measurable quantities and the different GUP approaches are reviewed and the corresponding observations are analysed. Bounds on the GUP parameter are discussed and implemented in the understanding of recent PLANCK observations of cosmic inflation. The higher-order GUP approaches predict minimal length uncertainty with and without maximum momenta. Possible arguments against the GUP are discussed; for instance, the concern about its compatibility with the equivalence principles, the universality of gravitational redshift and the free fall and law of reciprocal action are addressed. (review)

Utilization of Live Localized Weather Information for Sustainable Agriculture

Science.gov (United States)

Anderson, J.; Usher, J.

2010-09-01

Authors: Jim Anderson VP, Global Network and Business Development WeatherBug® Professional Jeremy Usher Managing Director, Europe WeatherBug® Professional Localized, real-time weather information is vital for day-to-day agronomic management of all crops. The challenge for agriculture is twofold in that local and timely weather data is not often available for producers and farmers, and it is not integrated into decision-support tools they require. Many of the traditional sources of weather information are not sufficient for agricultural applications because of the long distances between weather stations, meaning the data is not always applicable for on-farm decision making processes. The second constraint with traditional weather information is the timeliness of the data. Most delivery systems are designed on a one-hour time step, whereas many decisions in agriculture are based on minute-by-minute weather conditions. This is especially true for decisions surrounding chemical and fertilizer application and frost events. This presentation will outline how the creation of an agricultural mesonet (weather network) can enable producers and farmers with live, local weather information from weather stations installed in farm/field locations. The live weather information collected from each weather station is integrated into a web-enabled decision support tool, supporting numerous on-farm agronomic activities such as pest management, or dealing with heavy rainfall and frost events. Agronomic models can be used to assess the potential of disease pressure, enhance the farmer's abilities to time pesticide applications, or assess conditions contributing to yield and quality fluctuations. Farmers and industry stakeholders may also view quality-assured historical weather variables at any location. This serves as a record-management tool for viewing previously uncharted agronomic weather events in graph or table form. This set of weather tools is unique and provides a

46 CFR 44.01-13 - Heavy weather plan.

Science.gov (United States)

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Heavy weather plan. 44.01-13 Section 44.01-13 Shipping... VOYAGES Administration § 44.01-13 Heavy weather plan. (a) Each heavy weather plan under § 44.01-12(b) must... Inspection. Approval of a heavy weather plan is limited to the current hurricane season. (b) The cognizant...

A Analysis of the Development of Weather Concepts

Science.gov (United States)

Mroz, Paul John

Weather information in all forms is poorly understood and often misinterpreted by the general public. Weather literacy is necessary for everyone if critical weather messages, designed to save lives and protect property, are to be effective. The purpose of this study was to seek content and causal evidence for a developmental concept of Weather Information Processing that was consistent with Piagetian Cognitive Stages of Development. Three ordinal Content Stages Of Weather Information Processing (phenomena, process and mechanism) and three ordinal Causal Explanation Stages Of Weather Information Processing (non-real, natural, and scientifically valid abstract ideas) were explored for their relationship with Piaget's Pre-Operational, Concrete and Formal Stages of Development. One hundred and fifty -five elementary and secondary school students from two school districts were administered a written Piagetian exam. Commonly available television weather programs were categorized, randomly assigned and viewed by 42 randomly selected students who were administered three Piagetian tasks. Students were clinically interviewed for the level of content information and causal explanations (reasoning). Results indicated that content information and causal reasoning of students to televised weather information is significantly related (p Cognitive Stages of Development. Two Piagetian logic operations (seriation and correlation) were established as significantly different (p Information Processing and have implications for teaching and presenting weather information to the public.

The Early Years: The Wonders of Weather

Science.gov (United States)

Ashbrook, Peggy

2013-01-01

This article reports on the wonders of winter weather, as it often inspires teachers' and students' interest in collecting weather data, especially if snow falls. Beginning weather data collection in preschool will introduce children to the concepts of making regular observations of natural phenomena, recording the observations (data),…

Towards a National Space Weather Predictive Capability

Science.gov (United States)

Fox, N. J.; Ryschkewitsch, M. G.; Merkin, V. G.; Stephens, G. K.; Gjerloev, J. W.; Barnes, R. J.; Anderson, B. J.; Paxton, L. J.; Ukhorskiy, A. Y.; Kelly, M. A.; Berger, T. E.; Bonadonna, L. C. M. F.; Hesse, M.; Sharma, S.

2015-12-01

National needs in the area of space weather informational and predictive tools are growing rapidly. Adverse conditions in the space environment can cause disruption of satellite operations, communications, navigation, and electric power distribution grids, leading to a variety of socio-economic losses and impacts on our security. Future space exploration and most modern human endeavors will require major advances in physical understanding and improved transition of space research to operations. At present, only a small fraction of the latest research and development results from NASA, NOAA, NSF and DoD investments are being used to improve space weather forecasting and to develop operational tools. The power of modern research and space weather model development needs to be better utilized to enable comprehensive, timely, and accurate operational space weather tools. The mere production of space weather information is not sufficient to address the needs of those who are affected by space weather. A coordinated effort is required to support research-to-applications transition efforts and to develop the tools required those who rely on this information. In this presentation we will review the space weather system developed for the Van Allen Probes mission, together with other datasets, tools and models that have resulted from research by scientists at JHU/APL. We will look at how these, and results from future missions such as Solar Probe Plus, could be applied to support space weather applications in coordination with other community assets and capabilities.

Quantifying uncertainty in soot volume fraction estimates using Bayesian inference of auto-correlated laser-induced incandescence measurements

Science.gov (United States)

Hadwin, Paul J.; Sipkens, T. A.; Thomson, K. A.; Liu, F.; Daun, K. J.

2016-01-01

Auto-correlated laser-induced incandescence (AC-LII) infers the soot volume fraction (SVF) of soot particles by comparing the spectral incandescence from laser-energized particles to the pyrometrically inferred peak soot temperature. This calculation requires detailed knowledge of model parameters such as the absorption function of soot, which may vary with combustion chemistry, soot age, and the internal structure of the soot. This work presents a Bayesian methodology to quantify such uncertainties. This technique treats the additional "nuisance" model parameters, including the soot absorption function, as stochastic variables and incorporates the current state of knowledge of these parameters into the inference process through maximum entropy priors. While standard AC-LII analysis provides a point estimate of the SVF, Bayesian techniques infer the posterior probability density, which will allow scientists and engineers to better assess the reliability of AC-LII inferred SVFs in the context of environmental regulations and competing diagnostics.

Newspaper Clippings and Articles (Weather-related)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Weather-related newspaper articles and photos, almost exclusively from Baltimore, MD and nearby areas. Includes storm damage, rainfall reports, and weather's affect...

Fire Danger and Fire Weather Records

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The National Weather Service (formerly Weather Bureau) and Forest Service developed a program to track meteorological conditions conducive to forest fires, resulting...

SIGWX Charts - High Level Significant Weather

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — High level significant weather (SIGWX) forecasts are provided for the en-route portion of international flights. NOAA's National Weather Service Aviation Center...

Case report of cold-weather-induced radiation recall dermatitis after chemoradiotherapy with cisplatin

Energy Technology Data Exchange (ETDEWEB)

Kindts, Isabelle; Stellamans, Karin; Planckaert, Nikie; Goethals, Laurence [AZ Groeninge Hospital, Department of Radiation Oncology, Kortrijk (Belgium); Bonny, Michiel [AZ Groeninge Hospital, Department of Dermatology, Kortrijk (Belgium)

2014-08-15

The radiation recall reaction (RRR) is an inflammatory reaction that occurs in previously irradiated areas. The phenomenon is probably due to an idiosyncratic hypersensitivity reaction, in which a second agent can recall the inflammatory reaction. This case report documents a cold-weather-induced radiation recall dermatitis (RRD). We observed a severe RRD in a patient after chemoradiotherapy treatment with cisplatin for a nasopharyngeal carcinoma, precipitated by cold temperatures, which developed 9 days after completion of therapy. In the medical literature, RRD following extreme cold temperatures seems to be a peculiar event. Until further information on the interaction is available, future studies on combined chemotherapy with cisplatin should be carefully monitored and any side effects clearly documented. This case suggests that environmental conditions may play a contributing role in the development of RRD. This case also implies that neither fraction size nor total radiation dose is a determining factor in the development of the dermatologic reaction. (orig.) [German] Die ''Radiation-Recall-Reaktion'' (RRR) ist eine Entzuendungsreaktion, die in zuvor bestrahlten Bereichen auftritt. Das Phaenomen wird wahrscheinlich durch eine spezifische Ueberempfindlichkeitsreaktion verursacht, bei der ein zweites Agens die Entzuendungsreaktion hervorruft. Dieser Fallbericht beschreibt eine kaltwetterinduzierte RR-Hautentzuendung. Wir beobachteten bei dem Patienten nach einer Radiochemotherapie mit Cisplatin aufgrund eines Nasopharynxkarzinoms eine heftige RR-Dermatitis (RRD) aufgrund kalter Temperaturen, die sich 9 Tage nach Therapiebeendigung entwickelte. In der medizinischen Literatur scheint eine RRD infolge extrem kalter Temperaturen ein besonderes Ereignis. Bis weitere Informationen zu der Interaktion verfuegbar sind, sollten zukuenftige Studien zur Kombinationstherapie mit Cisplatin sorgfaeltig ueberwacht und Nebenwirkungen eindeutig dokumentiert

Quantifying uncertainty in Transcranial Magnetic Stimulation - A high resolution simulation study in ICBM space.

Science.gov (United States)

Toschi, Nicola; Keck, Martin E; Welt, Tobias; Guerrisi, Maria

2012-01-01

Transcranial Magnetic Stimulation offers enormous potential for noninvasive brain stimulation. While it is known that brain tissue significantly "reshapes" induced field and charge distributions, most modeling investigations to-date have focused on single-subject data with limited generality. Further, the effects of the significant uncertainties which exist in the simulation (i.e. brain conductivity distributions) and stimulation (e.g. coil positioning and orientations) setup have not been quantified. In this study, we construct a high-resolution anisotropic head model in standard ICBM space, which can be used as a population-representative standard for bioelectromagnetic simulations. Further, we employ Monte-Carlo simulations in order to quantify how uncertainties in conductivity values propagate all the way to induced field and currents, demonstrating significant, regionally dependent dispersions in values which are commonly assumed "ground truth". This framework can be leveraged in order to quantify the effect of any type of uncertainty in noninvasive brain stimulation and bears relevance in all applications of TMS, both investigative and therapeutic.

Uncertainty and measurement

International Nuclear Information System (INIS)

Landsberg, P.T.

1990-01-01

This paper explores how the quantum mechanics uncertainty relation can be considered to result from measurements. A distinction is drawn between the uncertainties obtained by scrutinising experiments and the standard deviation type of uncertainty definition used in quantum formalism. (UK)

Weatherization Assistance Program Fact Sheet

Energy Technology Data Exchange (ETDEWEB)

None

2018-02-01

The U.S. Department of Energy’s (DOE) Weatherization Assistance Program reduces energy costs for low-income households by increasing the energy e ciency of their homes, while ensuring their health and safety. The Program supports 8,500 jobs and provides weatherization services to approximately 35,000 homes every year using DOE funds.

An evaluation of the impact of aerosol particles on weather forecasts from a biomass burning aerosol event over the Midwestern United States: observational-based analysis of surface temperature

Directory of Open Access Journals (Sweden)

J. Zhang

2016-05-01

Full Text Available A major continental-scale biomass burning smoke event from 28–30 June 2015, spanning central Canada through the eastern seaboard of the United States, resulted in unforecasted drops in daytime high surface temperatures on the order of 2–5  °C in the upper Midwest. This event, with strong smoke gradients and largely cloud-free conditions, provides a natural laboratory to study how aerosol radiative effects may influence numerical weather prediction (NWP forecast outcomes. Here, we describe the nature of this smoke event and evaluate the differences in observed near-surface air temperatures between Bismarck (clear and Grand Forks (overcast smoke, to evaluate to what degree solar radiation forcing from a smoke plume introduces daytime surface cooling, and how this affects model bias in forecasts and analyses. For this event, mid-visible (550 nm smoke aerosol optical thickness (AOT, τ reached values above 5. A direct surface cooling efficiency of −1.5 °C per unit AOT (at 550 nm, τ550 was found. A further analysis of European Centre for Medium-Range Weather Forecasts (ECMWF, National Centers for Environmental Prediction (NCEP, United Kingdom Meteorological Office (UKMO near-surface air temperature forecasts for up to 54 h as a function of Moderate Resolution Imaging Spectroradiometer (MODIS Dark Target AOT data across more than 400 surface stations, also indicated the presence of the daytime aerosol direct cooling effect, but suggested a smaller aerosol direct surface cooling efficiency with magnitude on the order of −0.25 to −1.0 °C per unit τ550. In addition, using observations from the surface stations, uncertainties in near-surface air temperatures from ECMWF, NCEP, and UKMO model runs are estimated. This study further suggests that significant daily changes in τ550 above 1, at which the smoke-aerosol-induced direct surface cooling effect could be comparable in magnitude with model uncertainties, are rare events

Designing and Implementing Weather Generators as Web Services

Directory of Open Access Journals (Sweden)

Rassarin Chinnachodteeranun

2016-12-01

Full Text Available Climate and weather realizations are essential inputs for simulating crop growth and yields to analyze the risks associated with future conditions. To simplify the procedure of generating weather realizations and make them available over the Internet, we implemented novel mechanisms for providing weather generators as web services, as well as a mechanism for sharing identical weather realizations given a climatological information. A web service for preparing long-term climate data was implemented based on an international standard, Sensor Observation Service (SOS. The weather generator services, which are the core components of the framework, analyze climatological data, and can take seasonal climate forecasts as inputs for generating weather realizations. The generated weather realizations are encoded in a standard format, which are ready for use to crop modeling. All outputs are generated in SOS standard, which broadens the extent of data sharing and interoperability with other sectoral applications, e.g., water resources management. These services facilitate the development of other applications requiring input weather realizations, as these can be obtained easily by just calling the service. The workload of analysts related to data preparation and handling of legacy weather generator programs can be reduced. The architectural design and implementation presented here can be used as a prototype for constructing further services on top of an interoperable sensor network system.

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

Science.gov (United States)

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.

NOAA Weather and Climate Toolkit (WCT)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Weather and Climate Toolkit is an application that provides simple visualization and data export of weather and climatological data archived at NCDC. The...

Longing for Clouds - Does Beautiful Weather have to be Fine?

Directory of Open Access Journals (Sweden)

Mădălina Diaconu

2016-01-01

Full Text Available Any attempt to outline a meteorological aesthetics centered on so-called beautiful weather has to overcome several difficulties: In everyday life, the appreciation of the weather is mostly related to practical interests or reduced to the ideal of stereotypical fine weather that is conceived according to blue-sky thinking irrespective of climate diversity. Also, an aesthetics of fine weather seems, strictly speaking, to be impossible given that such weather conditions usually allow humans to focus on aspects other than weather, which contradicts the autotelic character of beauty. The unreflective equation of beautiful weather with moderately sunny weather and a cloudless sky also collides with the psychological need for variation: even living in a “paradisal” climate would be condemned to end in monotony. Finally, whereas fine weather is related in modern realistic literature to cosmic harmony and a universal natural order, contemporary literary examples show that in the age of the climate change, fine weather may be deceitful and its passive contemplation, irresponsible. This implies the necessity of a reflective aesthetic attitude on weather, as influenced by art, literature, and science, which discovers the poetics of bad weather and the wonder that underlies average weather conditions.

An end-to-end assessment of extreme weather impacts on food security

Science.gov (United States)

Chavez, Erik; Conway, Gordon; Ghil, Michael; Sadler, Marc

2015-11-01

Both governments and the private sector urgently require better estimates of the likely incidence of extreme weather events, their impacts on food crop production and the potential consequent social and economic losses. Current assessments of climate change impacts on agriculture mostly focus on average crop yield vulnerability to climate and adaptation scenarios. Also, although new-generation climate models have improved and there has been an exponential increase in available data, the uncertainties in their projections over years and decades, and at regional and local scale, have not decreased. We need to understand and quantify the non-stationary, annual and decadal climate impacts using simple and communicable risk metrics that will help public and private stakeholders manage the hazards to food security. Here we present an `end-to-end’ methodological construct based on weather indices and machine learning that integrates current understanding of the various interacting systems of climate, crops and the economy to determine short- to long-term risk estimates of crop production loss, in different climate and adaptation scenarios. For provinces north and south of the Yangtze River in China, we have found that risk profiles for crop yields that translate climate into economic variability follow marked regional patterns, shaped by drivers of continental-scale climate. We conclude that to be cost-effective, region-specific policies have to be tailored to optimally combine different categories of risk management instruments.

SPace weather applications in a technology-dependent society

Science.gov (United States)

Ngwira, C. M.

2017-12-01

Space weather can adversely key technology assets, such as, high-voltage electric power transmission grids, oil and gas pipelines, and communications systems that are critical to national security and economy. However, the term of "space weather" is not well known in our society. This presentation will introduce key concepts related to the space weather problem and show how space weather impacts our everyday life. The goal is to promote awareness among the general public. Also, this presentation will highlight how space weather is being used to promote STEM education for community college students through the NASA internship program.

World War II Weather Record Transmittances

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — World War II Weather Record Transmittances are a record of the weather and meteorological data observed during World War II and transferred to the archive. It...

Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10): a World Weather Research Programme Project

Science.gov (United States)

Isaac, G. A.; Joe, P. I.; Mailhot, J.; Bailey, M.; Bélair, S.; Boudala, F. S.; Brugman, M.; Campos, E.; Carpenter, R. L.; Crawford, R. W.; Cober, S. G.; Denis, B.; Doyle, C.; Reeves, H. D.; Gultepe, I.; Haiden, T.; Heckman, I.; Huang, L. X.; Milbrandt, J. A.; Mo, R.; Rasmussen, R. M.; Smith, T.; Stewart, R. E.; Wang, D.; Wilson, L. J.

2014-01-01

A World Weather Research Programme (WWRP) project entitled the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) was developed to be associated with the Vancouver 2010 Olympic and Paralympic Winter Games conducted between 12 February and 21 March 2010. The SNOW-V10 international team augmented the instrumentation associated with the Winter Games and several new numerical weather forecasting and nowcasting models were added. Both the additional observational and model data were available to the forecasters in real time. This was an excellent opportunity to demonstrate existing capability in nowcasting and to develop better techniques for short term (0-6 h) nowcasts of winter weather in complex terrain. Better techniques to forecast visibility, low cloud, wind gusts, precipitation rate and type were evaluated. The weather during the games was exceptionally variable with many periods of low visibility, low ceilings and precipitation in the form of both snow and rain. The data collected should improve our understanding of many physical phenomena such as the diabatic effects due to melting snow, wind flow around and over terrain, diurnal flow reversal in valleys associated with daytime heating, and precipitation reductions and increases due to local terrain. Many studies related to these phenomena are described in the Special Issue on SNOW-V10 for which this paper was written. Numerical weather prediction and nowcast models have been evaluated against the unique observational data set now available. It is anticipated that the data set and the knowledge learned as a result of SNOW-V10 will become a resource for other World Meteorological Organization member states who are interested in improving forecasts of winter weather.

Relationships between CO2, thermodynamic limits on silicate weathering, and the strength of the silicate weathering feedback

Science.gov (United States)

Winnick, Matthew J.; Maher, Kate

2018-03-01

Recent studies have suggested that thermodynamic limitations on chemical weathering rates exert a first-order control on riverine solute fluxes and by extension, global chemical weathering rates. As such, these limitations may play a prominent role in the regulation of carbon dioxide levels (pCO2) over geologic timescales by constraining the maximum global weathering flux. In this study, we develop a theoretical scaling relationship between equilibrium solute concentrations and pCO2 based on equilibrium constants and reaction stoichiometry relating primary mineral dissolution and secondary mineral precipitation. We test this theoretical scaling relationship against reactive transport simulations of chemical weathering profiles under open- and closed-system conditions, representing partially and fully water-saturated regolith, respectively. Under open-system conditions, equilibrium bicarbonate concentrations vary as a power-law function of pCO2 (y = kxn) where n is dependent on reaction stoichiometry and k is dependent on both reaction stoichiometry and the equilibrium constant. Under closed-system conditions, bicarbonate concentrations vary linearly with pCO2 at low values and approach open-system scaling at high pCO2. To describe the potential role of thermodynamic limitations in the global silicate weathering feedback, we develop a new mathematical framework to assess weathering feedback strength in terms of both (1) steady-state atmospheric pCO2 concentrations, and (2) susceptibility to secular changes in degassing rates and transient carbon cycle perturbations, which we term 1st and 2nd order feedback strength, respectively. Finally, we discuss the implications of these results for the effects of vascular land plant evolution on feedback strength, the potential role of vegetation in controlling modern solute fluxes, and the application of these frameworks to a more complete functional description of the silicate weathering feedback. Most notably, the dependence

Now, Here's the Weather Forecast...

Science.gov (United States)

Richardson, Mathew

2013-01-01

The Met Office has a long history of weather forecasting, creating tailored weather forecasts for customers across the world. Based in Exeter, the Met Office is also home to the Met Office Hadley Centre, a world-leading centre for the study of climate change and its potential impacts. Climate information from the Met Office Hadley Centre is used…

Uncertainty as Knowledge: Constraints on Policy Choices Provided by Analysis of Uncertainty

Science.gov (United States)

Lewandowsky, S.; Risbey, J.; Smithson, M.; Newell, B. R.

2012-12-01

Uncertainty forms an integral part of climate science, and it is often cited in connection with arguments against mitigative action. We argue that an analysis of uncertainty must consider existing knowledge as well as uncertainty, and the two must be evaluated with respect to the outcomes and risks associated with possible policy options. Although risk judgments are inherently subjective, an analysis of the role of uncertainty within the climate system yields two constraints that are robust to a broad range of assumptions. Those constraints are that (a) greater uncertainty about the climate system is necessarily associated with greater expected damages from warming, and (b) greater uncertainty translates into a greater risk of the failure of mitigation efforts. These ordinal constraints are unaffected by subjective or cultural risk-perception factors, they are independent of the discount rate, and they are independent of the magnitude of the estimate for climate sensitivity. The constraints mean that any appeal to uncertainty must imply a stronger, rather than weaker, need to cut greenhouse gas emissions than in the absence of uncertainty.

History of surface weather observations in the United States

Science.gov (United States)

Fiebrich, Christopher A.

2009-04-01

In this paper, the history of surface weather observations in the United States is reviewed. Local weather observations were first documented in the 17th Century along the East Coast. For many years, the progression of a weather observation from an initial reading to dissemination remained a slow and laborious process. The number of observers remained small and unorganized until agencies including the Surgeon General, Army, and General Land Office began to request regular observations at satellite locations in the 1800s. The Smithsonian was responsible for first organizing a large "network" of volunteer weather observers across the nation. These observers became the foundation for today's Cooperative Observer network. As applications of weather data continued to grow and users required the data with an ever-decreasing latency, automated weather networks saw rapid growth in the later part of the 20th century. Today, the number of weather observations across the U.S. totals in the tens of thousands due largely to privately-owned weather networks and amateur weather observers who submit observations over the internet.

Climate uncertainty and implications for U.S. state-level risk assessment through 2050.

Energy Technology Data Exchange (ETDEWEB)

Loose, Verne W.; Lowry, Thomas Stephen; Malczynski, Leonard A.; Tidwell, Vincent Carroll; Stamber, Kevin Louis; Kelic, Andjelka; Backus, George A.; Warren, Drake E.; Zagonel, Aldo A.; Ehlen, Mark Andrew; Klise, Geoffrey T.; Vargas, Vanessa N.

2009-10-01

Decisions for climate policy will need to take place in advance of climate science resolving all relevant uncertainties. Further, if the concern of policy is to reduce risk, then the best-estimate of climate change impacts may not be so important as the currently understood uncertainty associated with realizable conditions having high consequence. This study focuses on one of the most uncertain aspects of future climate change - precipitation - to understand the implications of uncertainty on risk and the near-term justification for interventions to mitigate the course of climate change. We show that the mean risk of damage to the economy from climate change, at the national level, is on the order of one trillion dollars over the next 40 years, with employment impacts of nearly 7 million labor-years. At a 1% exceedance-probability, the impact is over twice the mean-risk value. Impacts at the level of individual U.S. states are then typically in the multiple tens of billions dollar range with employment losses exceeding hundreds of thousands of labor-years. We used results of the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) climate-model ensemble as the referent for climate uncertainty over the next 40 years, mapped the simulated weather hydrologically to the county level for determining the physical consequence to economic activity at the state level, and then performed a detailed, seventy-industry, analysis of economic impact among the interacting lower-48 states. We determined industry GDP and employment impacts at the state level, as well as interstate population migration, effect on personal income, and the consequences for the U.S. trade balance.

A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data

Energy Technology Data Exchange (ETDEWEB)

Hong, Tianzhen; Chang, Wen-Kuei; Lin, Hung-Wen

2013-05-01

Buildings consume more than one third of the world?s total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980 to 2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: 1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; 2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; 3) the weather impact is greater for buildings in colder climates than warmer climates; 4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small

Weather-centric rangeland revegetation planning

Science.gov (United States)

Hardegree, Stuart P.; Abatzoglou, John T.; Brunson, Mark W.; Germino, Matthew; Hegewisch, Katherine C.; Moffet, Corey A.; Pilliod, David S.; Roundy, Bruce A.; Boehm, Alex R.; Meredith, Gwendwr R.

2018-01-01

Invasive annual weeds negatively impact ecosystem services and pose a major conservation threat on semiarid rangelands throughout the western United States. Rehabilitation of these rangelands is challenging due to interannual climate and subseasonal weather variability that impacts seed germination, seedling survival and establishment, annual weed dynamics, wildfire frequency, and soil stability. Rehabilitation and restoration outcomes could be improved by adopting a weather-centric approach that uses the full spectrum of available site-specific weather information from historical observations, seasonal climate forecasts, and climate-change projections. Climate data can be used retrospectively to interpret success or failure of past seedings by describing seasonal and longer-term patterns of environmental variability subsequent to planting. A more detailed evaluation of weather impacts on site conditions may yield more flexible adaptive-management strategies for rangeland restoration and rehabilitation, as well as provide estimates of transition probabilities between desirable and undesirable vegetation states. Skillful seasonal climate forecasts could greatly improve the cost efficiency of management treatments by limiting revegetation activities to time periods where forecasts suggest higher probabilities of successful seedling establishment. Climate-change projections are key to the application of current environmental models for development of mitigation and adaptation strategies and for management practices that require a multidecadal planning horizon. Adoption of new weather technology will require collaboration between land managers and revegetation specialists and modifications to the way we currently plan and conduct rangeland rehabilitation and restoration in the Intermountain West.

Uncertainty in social dilemmas

OpenAIRE

Kwaadsteniet, Erik Willem de

2007-01-01

This dissertation focuses on social dilemmas, and more specifically, on environmental uncertainty in these dilemmas. Real-life social dilemma situations are often characterized by uncertainty. For example, fishermen mostly do not know the exact size of the fish population (i.e., resource size uncertainty). Several researchers have therefore asked themselves the question as to how such uncertainty influences people’s choice behavior. These researchers have repeatedly concluded that uncertainty...

Uncertainty theory

CERN Document Server

Liu, Baoding

2015-01-01

When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, c...

Quantifying uncertainties in wind energy assessment

Science.gov (United States)

Patlakas, Platon; Galanis, George; Kallos, George

2015-04-01

The constant rise of wind energy production and the subsequent penetration in global energy markets during the last decades resulted in new sites selection with various types of problems. Such problems arise due to the variability and the uncertainty of wind speed. The study of the wind speed distribution lower and upper tail may support the quantification of these uncertainties. Such approaches focused on extreme wind conditions or periods below the energy production threshold are necessary for a better management of operations. Towards this direction, different methodologies are presented for the credible evaluation of potential non-frequent/extreme values for these environmental conditions. The approaches used, take into consideration the structural design of the wind turbines according to their lifespan, the turbine failures, the time needed for repairing as well as the energy production distribution. In this work, a multi-parametric approach for studying extreme wind speed values will be discussed based on tools of Extreme Value Theory. In particular, the study is focused on extreme wind speed return periods and the persistence of no energy production based on a weather modeling system/hind cast/10-year dataset. More specifically, two methods (Annual Maxima and Peaks Over Threshold) were used for the estimation of extreme wind speeds and their recurrence intervals. Additionally, two different methodologies (intensity given duration and duration given intensity, both based on Annual Maxima method) were implied to calculate the extreme events duration, combined with their intensity as well as the event frequency. The obtained results prove that the proposed approaches converge, at least on the main findings, for each case. It is also remarkable that, despite the moderate wind speed climate of the area, several consequent days of no energy production are observed.

Uncertainty and validation. Effect of user interpretation on uncertainty estimates

International Nuclear Information System (INIS)

Kirchner, G.; Peterson, R.

1996-11-01

variation between the best estimate predictions of the group. The assumptions of the users result in more uncertainty in the predictions (taking into account the 95% confidence intervals) than is shown by the confidence interval on the predictions of one user. Mistakes, being examples of incorrect user assumptions, cannot be ignored and must be accepted as contributing to the variability seen in the spread of predictions. The user's confidence in his/her understanding of a scenario description and/or confidence in working with a code does not necessarily mean that the predictions will be more accurate. Choice of parameter values contributed most to user-induced uncertainty followed by scenario interpretation. The contribution due to code implementation was low, but may have been limited due to the decision of the majority of the group not to submit predictions using the most complex of the three codes. Most modelers had difficulty adapting the models for certain expected output. Parameter values for wet and dry deposition, transfer from forage to milk and concentration ratios were mostly taken from the extensive database of Chernobyl fallout radionuclides, no matter what the scenario. Examples provided in the code manuals may influence code users considerably when preparing their own input files. A major problem concerns pasture concentrations given in fresh or dry weight: parameter values in codes have to be based on one or the other and the request for predictions in the scenario description may or may not be the same unit. This is a surprisingly common source of error. Most of the predictions showed order of magnitude discrepancies when best estimates are compared with the observations, although the participants had a highly professional background in radioecology and a good understanding of the importance of the processes modelled. When uncertainties are considered, however, mostly there was overlap between predictions and observations. A failure to reproduce the time

Uncertainty and validation. Effect of user interpretation on uncertainty estimates

Energy Technology Data Exchange (ETDEWEB)

Kirchner, G. [Univ. of Bremen (Germany); Peterson, R. [AECL, Chalk River, ON (Canada)] [and others

1996-11-01

variation between the best estimate predictions of the group. The assumptions of the users result in more uncertainty in the predictions (taking into account the 95% confidence intervals) than is shown by the confidence interval on the predictions of one user. Mistakes, being examples of incorrect user assumptions, cannot be ignored and must be accepted as contributing to the variability seen in the spread of predictions. The user's confidence in his/her understanding of a scenario description and/or confidence in working with a code does not necessarily mean that the predictions will be more accurate. Choice of parameter values contributed most to user-induced uncertainty followed by scenario interpretation. The contribution due to code implementation was low, but may have been limited due to the decision of the majority of the group not to submit predictions using the most complex of the three codes. Most modelers had difficulty adapting the models for certain expected output. Parameter values for wet and dry deposition, transfer from forage to milk and concentration ratios were mostly taken from the extensive database of Chernobyl fallout radionuclides, no matter what the scenario. Examples provided in the code manuals may influence code users considerably when preparing their own input files. A major problem concerns pasture concentrations given in fresh or dry weight: parameter values in codes have to be based on one or the other and the request for predictions in the scenario description may or may not be the same unit. This is a surprisingly common source of error. Most of the predictions showed order of magnitude discrepancies when best estimates are compared with the observations, although the participants had a highly professional background in radioecology and a good understanding of the importance of the processes modelled. When uncertainties are considered, however, mostly there was overlap between predictions and observations. A failure to reproduce the

Bringing Space Weather Down to Earth

Science.gov (United States)

Reiff, P. H.; Sumners, C.

2005-05-01

Most of the public has no idea what Space Weather is, but a number of innovative programs, web sites, magazine articles, TV shows and planetarium shows have taken space weather from an unknown quantity to a much more visible field. This paper reviews new developments, including the new Space Weather journal, the very popular spaceweather.com website, new immersive planetarium shows that can go "on the road", and well-publicized Sun-Earth Day activities. Real-time data and reasonably accurate spaceweather forecasts are available from several websites, with many subscribers. Even the renaissance of amateur radio because of Homeland Security brings a new generation of learners to wonder what is going on in the Sun today. The NSF Center for Integrated Space Weather Modeling has a dedicated team to reach both the public and a greater diversity of new scientists.

Measuring weather for aviation safety in the 1980's

Science.gov (United States)

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.

Weather conditions conducive to Beijing severe haze more frequent under climate change

Science.gov (United States)

Cai, Wenju; Li, Ke; Liao, Hong; Wang, Huijun; Wu, Lixin

2017-03-01

The frequency of Beijing winter severe haze episodes has increased substantially over the past decades, and is commonly attributed to increased pollutant emissions from China’s rapid economic development. During such episodes, levels of fine particulate matter are harmful to human health and the environment, and cause massive disruption to economic activities, as occurred in January 2013. Conducive weather conditions are an important ingredient of severe haze episodes, and include reduced surface winter northerlies, weakened northwesterlies in the midtroposphere, and enhanced thermal stability of the lower atmosphere. How such weather conditions may respond to climate change is not clear. Here we project a 50% increase in the frequency and an 80% increase in the persistence of conducive weather conditions similar to those in January 2013, in response to climate change. The frequency and persistence between the historical (1950-1999) and future (2050-2099) climate were compared in 15 models under Representative Concentration Pathway 8.5 (RCP8.5). The increased frequency is consistent with large-scale circulation changes, including an Arctic Oscillation upward trend, weakening East Asian winter monsoon, and faster warming in the lower troposphere. Thus, circulation changes induced by global greenhouse gas emissions can contribute to the increased Beijing severe haze frequency.

Automated Flight Routing Using Stochastic Dynamic Programming

Science.gov (United States)

Ng, Hok K.; Morando, Alex; Grabbe, Shon

2010-01-01

Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

Moving Beyond 2% Uncertainty: A New Framework for Quantifying Lidar Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Newman, Jennifer F.; Clifton, Andrew

2017-03-08

Remote sensing of wind using lidar is revolutionizing wind energy. However, current generations of wind lidar are ascribed a climatic value of uncertainty, which is based on a poor description of lidar sensitivity to external conditions. In this presentation, we show how it is important to consider the complete lidar measurement process to define the measurement uncertainty, which in turn offers the ability to define a much more granular and dynamic measurement uncertainty. This approach is a progression from the 'white box' lidar uncertainty method.

Weather during bloom affects pollination and yield of highbush blueberry.

Science.gov (United States)

Tuell, Julianna K; Isaacs, Rufus

2010-06-01

Weather plays an important role in spring-blooming fruit crops due to the combined effects on bee activity, flower opening, pollen germination, and fertilization. To determine the effects of weather on highbush blueberry, Vaccinium corymbosum L., productivity, we monitored bee activity and compared fruit set, weight, and seed number in a field stocked with honey bees, Apis mellifera L., and common eastern bumble bees, Bombus impatiens (Cresson). Flowers were subjected to one of five treatments during bloom: enclosed, open, open during poor weather only, open during good weather only, or open during poor and good weather. Fewer bees of all types were observed foraging and fewer pollen foragers returned to colonies during poor weather than during good weather. There were also changes in foraging community composition: honey bees dominated during good weather, whereas bumble bees dominated during poor weather. Berries from flowers exposed only during poor weather had higher fruit set in 1 yr and higher berry weight in the other year compared with enclosed clusters. In both years, clusters exposed only during good weather had > 5 times as many mature seeds, weighed twice as much, and had double the fruit set of those not exposed. No significant increase over flowers exposed during good weather was observed when clusters were exposed during good and poor weather. Our results are discussed in terms of the role of weather during bloom on the contribution of bees adapted to foraging during cool conditions.

Space Weather Laboratory

Data.gov (United States)

Federal Laboratory Consortium — The Space Weather Computational Laboratory is a Unix and PC based modeling and simulation facility devoted to research analysis of naturally occurring electrically...

Weather patterns and hydro-climatological precursors of extreme floods in Switzerland since 1868

International Nuclear Information System (INIS)

Stucki, Peter; Rickli, Ralph; Broennimann, Stefan; Martius, Olivia; Wanner, Heinz; Bern Univ.; Grebner, Dietmar; Luterbacher, Juerg

2012-01-01

The generation of 24 extreme floods in large catchments of the central Alps is analyzed from instrumental and documentary data, newly digitized observations of precipitation (DigiHom) and 20 th Century Reanalysis (20CR) data. Extreme floods are determined by the 95 th percentile of differences between an annual flood and a defined contemporary flood. For a selection of six events between 1868 and 1910, we describe preconditioning elements such as precipitation, temperature, and snow cover anomalies. Specific weather patterns are assessed through a subjective analysis of three-dimensional atmospheric circulation. A focus is placed on synoptic-scale features including mid-tropospheric ascent, low-level moisture transport, propagation of cyclones, and temperature anomalies. We propose a hydro-meteorological classification of all 24 investigated events according to flood-generating weather conditions. Key elements of the upper-level synoptic-scale flow are summarized by five types: (i) pivoting cut-off lows, (ii) elongated cut-off lows, (iii) elongated troughs, (iv) waves (with a kink), and (v) approximately zonal flow over the Alpine region. We found that the most extreme floods (as above, but ≥ 98 th percentile) in Switzerland since 1868 were caused by the interaction of severe hydro-climatologic conditions with a flood-inducing weather situation. The 20CR data provide plausible synoptic-scale meteorological patterns leading to heavy precipitation. The proposed catalogue of weather patterns and hydro-climatologic precursors can give direction when anticipating the possibility of severe floods in the Alpine region. (orig.)

Operational Numerical Weather Prediction at the Met Office and potential ways forward for operational space weather prediction systems

Science.gov (United States)

Jackson, David

NICT (National Institute of Information and Communications Technology) has been in charge of space weather forecast service in Japan for more than 20 years. The main target region of the space weather is the geo-space in the vicinity of the Earth where human activities are dominant. In the geo-space, serious damages of satellites, international space stations and astronauts take place caused by energetic particles or electromagnetic disturbances: the origin of the causes is dynamically changing of solar activities. Positioning systems via GPS satellites are also im-portant recently. Since the most significant effect of positioning error comes from disturbances of the ionosphere, it is crucial to estimate time-dependent modulation of the electron density profiles in the ionosphere. NICT is one of the 13 members of the ISES (International Space Environment Service), which is an international assembly of space weather forecast centers under the UNESCO. With help of geo-space environment data exchanging among the member nations, NICT operates daily space weather forecast service every day to provide informa-tion on forecasts of solar flare, geomagnetic disturbances, solar proton event, and radio-wave propagation conditions in the ionosphere. The space weather forecast at NICT is conducted based on the three methodologies: observations, simulations and informatics (OSI model). For real-time or quasi real-time reporting of space weather, we conduct our original observations: Hiraiso solar observatory to monitor the solar activity (solar flare, coronal mass ejection, and so on), domestic ionosonde network, magnetometer HF radar observations in far-east Siberia, and south-east Asia low-latitude ionosonde network (SEALION). Real-time observation data to monitor solar and solar-wind activities are obtained through antennae at NICT from ACE and STEREO satellites. We have a middle-class super-computer (NEC SX-8R) to maintain real-time computer simulations for solar and solar

Evaluation of seismic induced CDF and ΔCDF with considering the uncertainty reduction research results

International Nuclear Information System (INIS)

Hahm, Daegi; Choi, In Kil

2012-01-01

In the seismic probabilistic safety assessment (SPSA) of nuclear power plants (NPPs), the efficient and rational methodology to dealing the uncertainty factors are required to increase the reliability of the SPSA results. To reduce the uncertainties in the SPSA approach, many research activities were performed by Korea Atomic Energy Research Institute (KAERI) during the last 5 years mid and long term nuclear research and development program of the ministry of education, science and technology. These outcomes can be implemented to the update or reevaluation of previous NPP's SPSA results. In this study, we applied these uncertainty reduction research results to the update of the SPSA procedure of the target reference plant, i.e., Ulchin unit 5/6 NPP. The refined topics from the SPSA procedure are the seismic fragility, the seismic hazard, and the risk quantification. The detailed process and results are described in the next sections

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

Energy Technology Data Exchange (ETDEWEB)

Pigg, Scott [Energy Center of Wisconsin, Madison, WI (United States); Cautley, Dan [Energy Center of Wisconsin, Madison, WI (United States); Francisco, Paul [Univ. of Illinois, Urbana-Champaign, IL (United States); Hawkins, Beth A [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Brennan, Terry M [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

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.

Weather types in Sosnowiec (Poland during the period 1999-2013

Directory of Open Access Journals (Sweden)

Dobrowolska Ksenia

2014-09-01

Full Text Available The study presents the structure of weather types for the city of Sosnowiec during the period 1999-2013. The analysis was carried out on the basis of daily thermal data (the average daily air temperature, the minimum and maximum daily air temperature, cloudiness and precipitation. The data was obtained from a meteorological station belonging to the Department of Climatology at the Faculty of Earth Sciences at the University of Silesia. Weather types were established according to weather type classification after Woś (2010. 48 weather types were specified on the basis of a combination of 3 selected meteorological elements (temperature, cloudiness, precipitation. The number of days in the year and the frequency of particular thermal weather types, weather subtype, weather classes and weather types were characterized, and the changeability of weather types was analyzed. Furthermore, sequences of days with specific weather types were described. The analysis conducted has lead to the conclusion that, during the research period, the weather structure for the city of Sosnowiec was characterized by a great number of weather types observed, with relatively low frequency of occurrence. Weather throughout the year was dominated by warm weather types (3--, 2--, 2--, with weather marked as 310 – very warm, moderately cloudy, without precipitation (12.9% recorded as the most frequent, followed by 221 – moderately warm, very cloudy, with precipitation (11.6%, and 210 – moderately warm, moderately cloudy, without precipitation (11.4%as the least frequent one. A diversification in the number of particular classification units in consecutive years of the examined 15-year period does not display significant variability. Short sequences of 2 and 3 days dominated the selected sequences of specific weather types.