WorldWideScience

Sample records for model meam weatherization

  1. Models of Weather Impact on Air Traffic

    Science.gov (United States)

    Kulkarni, Deepak; Wang, Yao

    2017-01-01

    Flight delays have been a serious problem in the national airspace system costing about $30B per year. About 70 of the delays are attributed to weather and upto two thirds of these are avoidable. Better decision support tools would reduce these delays and improve air traffic management tools. Such tools would benefit from models of weather impacts on the airspace operations. This presentation discusses use of machine learning methods to mine various types of weather and traffic data to develop such models.

  2. 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...

  3. An introduction to Space Weather Integrated Modeling

    Science.gov (United States)

    Zhong, D.; Feng, X.

    2012-12-01

    The need for a software toolkit that integrates space weather models and data is one of many challenges we are facing with when applying the models to space weather forecasting. To meet this challenge, we have developed Space Weather Integrated Modeling (SWIM) that is capable of analysis and visualizations of the results from a diverse set of space weather models. SWIM has a modular design and is written in Python, by using NumPy, matplotlib, and the Visualization ToolKit (VTK). SWIM provides data management module to read a variety of spacecraft data products and a specific data format of Solar-Interplanetary Conservation Element/Solution Element MHD model (SIP-CESE MHD model) for the study of solar-terrestrial phenomena. Data analysis, visualization and graphic user interface modules are also presented in a user-friendly way to run the integrated models and visualize the 2-D and 3-D data sets interactively. With these tools we can locally or remotely analysis the model result rapidly, such as extraction of data on specific location in time-sequence data sets, plotting interplanetary magnetic field lines, multi-slicing of solar wind speed, volume rendering of solar wind density, animation of time-sequence data sets, comparing between model result and observational data. To speed-up the analysis, an in-situ visualization interface is used to support visualizing the data 'on-the-fly'. We also modified some critical time-consuming analysis and visualization methods with the aid of GPU and multi-core CPU. We have used this tool to visualize the data of SIP-CESE MHD model in real time, and integrated the Database Model of shock arrival, Shock Propagation Model, Dst forecasting model and SIP-CESE MHD model developed by SIGMA Weather Group at State Key Laboratory of Space Weather/CAS.

  4. Adaptive Numerical Algorithms in Space Weather Modeling

    Science.gov (United States)

    Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.; hide

    2010-01-01

    Space weather describes the various processes in the Sun-Earth system that present danger to human health and technology. The goal of space weather forecasting is to provide an opportunity to mitigate these negative effects. Physics-based space weather modeling is characterized by disparate temporal and spatial scales as well as by different physics in different domains. A multi-physics system can be modeled by a software framework comprising of several components. Each component corresponds to a physics domain, and each component is represented by one or more numerical models. The publicly available Space Weather Modeling Framework (SWMF) can execute and couple together several components distributed over a parallel machine in a flexible and efficient manner. The framework also allows resolving disparate spatial and temporal scales with independent spatial and temporal discretizations in the various models. Several of the computationally most expensive domains of the framework are modeled by the Block-Adaptive Tree Solar wind Roe Upwind Scheme (BATS-R-US) code that can solve various forms of the magnetohydrodynamics (MHD) equations, including Hall, semi-relativistic, multi-species and multi-fluid MHD, anisotropic pressure, radiative transport and heat conduction. Modeling disparate scales within BATS-R-US is achieved by a block-adaptive mesh both in Cartesian and generalized coordinates. Most recently we have created a new core for BATS-R-US: the Block-Adaptive Tree Library (BATL) that provides a general toolkit for creating, load balancing and message passing in a 1, 2 or 3 dimensional block-adaptive grid. We describe the algorithms of BATL and demonstrate its efficiency and scaling properties for various problems. BATS-R-US uses several time-integration schemes to address multiple time-scales: explicit time stepping with fixed or local time steps, partially steady-state evolution, point-implicit, semi-implicit, explicit/implicit, and fully implicit numerical

  5. Weather forecasting based on hybrid neural model

    Science.gov (United States)

    Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.

    2017-11-01

    Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.

  6. Weather Research and Forecasting (WRF) Regional Atmospheric Model: Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 7-day hourly forecast for the region surrounding the islands of Samoa at...

  7. Weather Research and Forecasting (WRF) Regional Atmospheric Model: Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 7-day hourly forecast for the region surrounding the island of Guam at...

  8. Weather Research and Forecasting (WRF) Regional Atmospheric Model: Oahu

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 3.5-day hourly forecast for the region surrounding the Hawaiian island of Oahu at...

  9. Weather Research and Forecasting (WRF) Regional Atmospheric Model: CNMI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 7-day hourly forecast for the region surrounding the Commonwealth of the Northern...

  10. Space Weather Models at the CCMC And Their Capabilities

    Science.gov (United States)

    Hesse, Michael; Rastatter, Lutz; MacNeice, Peter; Kuznetsova, Masha

    2007-01-01

    The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second focus of CCMC activities is on validation and verification of space weather models, and on the transition of appropriate models to space weather forecast centers. As part of the latter activity, the CCMC develops real-time simulation systems that stress models through routine execution. A by-product of these real-time calculations is the ability to derive model products, which may be useful for space weather operators. In this presentation, we will provide an overview of the community-provided, space weather-relevant, model suite, which resides at CCMC. We will discuss current capabilities, and analyze expected future developments of space weather related modeling.

  11. Hydrological modeling using a multi-site stochastic weather generator

    Science.gov (United States)

    Weather data is usually required at several locations over a large watershed, especially when using distributed models for hydrological simulations. In many applications, spatially correlated weather data can be provided by a multi-site stochastic weather generator which considers the spatial correl...

  12. Validation of the Middlesex Elderly Assessment of Mental State (MEAMS) as a cognitive screening test in patients with acquired brain injury in Turkey.

    Science.gov (United States)

    Kutlay, Sehim; Kuçukdeveci, Ayse A; Elhan, Atilla H; Yavuzer, Gunes; Tennant, Alan

    2007-02-28

    Assessment of cognitive impairment with a valid cognitive screening tool is essential in neurorehabilitation. The aim of this study was to test the reliability and validity of the Turkish-adapted version of the Middlesex Elderly Assessment of Mental State (MEAMS) among acquired brain injury patients in Turkey. Some 155 patients with acquired brain injury admitted for rehabilitation were assessed by the adapted version of MEAMS at admission and discharge. Reliability was tested by internal consistency, intra-class correlation coefficient (ICC) and person separation index; internal construct validity by Rasch analysis; external construct validity by associations with physical and cognitive disability (FIM); and responsiveness by Effect Size. Reliability was found to be good with Cronbach's alpha of 0.82 at both admission and discharge; and likewise an ICC of 0.80. Person separation index was 0.813. Internal construct validity was good by fit of the data to the Rasch model (mean item fit -0.178; SD 1.019). Items were substantially free of differential item functioning. External construct validity was confirmed by expected associations with physical and cognitive disability. Effect size was 0.42 compared with 0.22 for cognitive FIM. The reliability and validity of the Turkish version of MEAMS as a cognitive impairment screening tool in acquired brain injury has been demonstrated.

  13. 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...

  14. Modeling rock weathering in small watersheds

    NARCIS (Netherlands)

    Pacheco, F.A.L.; van der Weijden, C.H.

    2014-01-01

    Many mountainous watersheds are conceived as aquifer media where multiple groundwater flow systems have developed (Tóth, 1963), and as bimodal landscapes where differential weathering of bare and soil-mantled rock has occurred (Wahrhaftig, 1965). The results of a weathering algorithm (Pacheco and

  15. Space weather: Modeling and forecasting ionospheric

    International Nuclear Information System (INIS)

    Calzadilla Mendez, A.

    2008-01-01

    Full text: Space weather is the set of phenomena and interactions that take place in the interplanetary medium. It is regulated primarily by the activity originating in the Sun and affects both the artificial satellites that are outside of the protective cover of the Earth's atmosphere as the rest of the planets in the solar system. Among the phenomena that are of great relevance and impact on Earth are the auroras and geomagnetic storms , these are a direct result of irregularities in the flow of the solar wind and the interplanetary magnetic field . Given the high complexity of the physical phenomena involved (magnetic reconnection , particle inlet and ionizing radiation to the atmosphere) one of the great scientific challenges today is to forecast the state of plasmatic means either the interplanetary medium , the magnetosphere and ionosphere , for their importance to the development of various human activities such as radio , global positioning , navigation, etc. . It briefly address some of the international ionospheric modeling methods and contributions and participation that currently has the space group of the Institute of Geophysics Geophysics and Astronomy (IGA) in these activities of modeling and forecasting ionospheric. (author)

  16. Simple model for crop photosynthesis in terms of weather variables ...

    African Journals Online (AJOL)

    A theoretical mathematical model for describing crop photosynthetic rate in terms of the weather variables and crop characteristics is proposed. The model utilizes a series of efficiency parameters, each of which reflect the fraction of possible photosynthetic rate permitted by the different weather elements or crop architecture.

  17. Quality assurance of weather data for agricultural system model input

    Science.gov (United States)

    It is well known that crop production and hydrologic variation on watersheds is weather related. Rarely, however, is meteorological data quality checks reported for agricultural systems model research. We present quality assurance procedures for agricultural system model weather data input. Problems...

  18. Supercomputing for weather and climate modelling: convenience or necessity

    CSIR Research Space (South Africa)

    Landman, WA

    2009-12-01

    Full Text Available Weather and climate modelling require dedicated computer infrastructure in order to generate high-resolution, large ensemble, various models with different configurations, etc. in order to optimise operational forecasts and climate projections. High...

  19. 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.

  20. Adaptation of Mesoscale Weather Models to Local Forecasting

    Science.gov (United States)

    Manobianco, John T.; Taylor, Gregory E.; Case, Jonathan L.; Dianic, Allan V.; Wheeler, Mark W.; Zack, John W.; Nutter, Paul A.

    2003-01-01

    Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes

  1. A Data Model for Determining Weather's Impact on Travel Time

    DEFF Research Database (Denmark)

    Andersen, Ove; Torp, Kristian

    2016-01-01

    Accurate estimating travel times in road networks is a complex task because travel times depends on factors such as the weather. In this paper, we present a generic model for integrating weather data with GPS data to improve the accuracy of the estimated travel times. First, we present a data model...... for storing and map-matching GPS data, and integrating this data with detailed weather data. The model is generic in the sense that it can be used anywhere GPS data and weather data is available. Next, we analyze the correlation between travel time and the weather classes dry, fog, rain, and snow along...... with winds impact on travel time. Using a data set of 1.6 billion GPS records collected from 10,560 vehicles, over a 5 year period from all of Denmark, we show that snow can increase the travel time up to 27% and strong headwind can increase the travel time with up to 19% (compared to dry calm weather...

  2. Validation of crop weather models for crop assessment arid yield ...

    African Journals Online (AJOL)

    IRSIS and CRPSM models were used in this study to see how closely they could predict grain yields for selected stations in Tanzania. Input for the models comprised of weather, crop and soil data collected from five selected stations. Simulation results show that IRSIS model tends to over predict grain yields of maize, ...

  3. Model for expressing leaf photosynthesis in terms of weather variables

    African Journals Online (AJOL)

    A theoretical mathematical model for describing photosynthesis in individual leaves in terms of weather variables is proposed. The model utilizes a series of efficiency parameters, each of which reflect the fraction of potential photosynthetic rate permitted by the different environmental elements. These parameters are useful ...

  4. Managing wildland fires: integrating weather models into fire projections

    Science.gov (United States)

    Anne M. Rosenthal; Francis Fujioka

    2004-01-01

    Flames from the Old Fire sweep through lands north of San Bernardino during late fall of 2003. Like many Southern California fires, the Old Fire consumed susceptible forests at the urban-wildland interface and spread to nearby city neighborhoods. By incorporating weather models into fire perimeter projections, scientist Francis Fujioka is improving fire modeling as a...

  5. Modeling Silicate Weathering for Elevated CO2 and Temperature

    Science.gov (United States)

    Bolton, E. W.

    2016-12-01

    A reactive transport model (RTM) is used to assess CO2 drawdown by silicate weathering over a wide range of temperature, pCO2, and infiltration rates for basalts and granites. Although RTM's have been used extensively to model weathering of basalts and granites for present-day conditions, we extend such modeling to higher CO2 that could have existed during the Archean and Proterozoic. We also consider a wide range of surface temperatures and infiltration rates. We consider several model basalt and granite compositions. We normally impose CO2 in equilibrium with the various atmospheric ranges modeled and CO2 is delivered to the weathering zone by aqueous transport. We also consider models with fixed CO2 (aq) throughout the weathering zone as could occur in soils with partial water saturation or with plant respiration, which can strongly influence pH and mineral dissolution rates. For the modeling, we use Kinflow: a model developed at Yale that includes mineral dissolution and precipitation under kinetic control, aqueous speciation, surface erosion, dynamic porosity, permeability, and mineral surface areas via sub-grid-scale grain models, and exchange of volatiles at the surface. Most of the modeling is done in 1D, but some comparisons to 2D domains with heterogeneous permeability are made. We find that when CO2 is fixed only at the surface, the pH tends toward higher values for basalts than granites, in large part due to the presence of more divalent than monovalent cations in the primary minerals, tending to decrease rates of mineral dissolution. Weathering rates increase (as expected) with increasing CO2 and temperature. This modeling is done with the support of the Virtual Planetary Laboratory.

  6. Assessing normative cut points through differential item functioning analysis: An example from the adaptation of the Middlesex Elderly Assessment of Mental State (MEAMS for use as a cognitive screening test in Turkey

    Directory of Open Access Journals (Sweden)

    Kutlay Sehim

    2006-03-01

    Full Text Available Abstract Background The Middlesex Elderly Assessment of Mental State (MEAMS was developed as a screening test to detect cognitive impairment in the elderly. It includes 12 subtests, each having a 'pass score'. A series of tasks were undertaken to adapt the measure for use in the adult population in Turkey and to determine the validity of existing cut points for passing subtests, given the wide range of educational level in the Turkish population. This study focuses on identifying and validating the scoring system of the MEAMS for Turkish adult population. Methods After the translation procedure, 350 normal subjects and 158 acquired brain injury patients were assessed by the Turkish version of MEAMS. Initially, appropriate pass scores for the normal population were determined through ANOVA post-hoc tests according to age, gender and education. Rasch analysis was then used to test the internal construct validity of the scale and the validity of the cut points for pass scores on the pooled data by using Differential Item Functioning (DIF analysis within the framework of the Rasch model. Results Data with the initially modified pass scores were analyzed. DIF was found for certain subtests by age and education, but not for gender. Following this, pass scores were further adjusted and data re-fitted to the model. All subtests were found to fit the Rasch model (mean item fit 0.184, SD 0.319; person fit -0.224, SD 0.557 and DIF was then found to be absent. Thus the final pass scores for all subtests were determined. Conclusion The MEAMS offers a valid assessment of cognitive state for the adult Turkish population, and the revised cut points accommodate for age and education. Further studies are required to ascertain the validity in different diagnostic groups.

  7. Assessing normative cut points through differential item functioning analysis: an example from the adaptation of the Middlesex Elderly Assessment of Mental State (MEAMS) for use as a cognitive screening test in Turkey.

    Science.gov (United States)

    Tennant, Alan; Küçükdeveci, Ayse A; Kutlay, Sehim; Elhan, Atilla H

    2006-03-23

    The Middlesex Elderly Assessment of Mental State (MEAMS) was developed as a screening test to detect cognitive impairment in the elderly. It includes 12 subtests, each having a 'pass score'. A series of tasks were undertaken to adapt the measure for use in the adult population in Turkey and to determine the validity of existing cut points for passing subtests, given the wide range of educational level in the Turkish population. This study focuses on identifying and validating the scoring system of the MEAMS for Turkish adult population. After the translation procedure, 350 normal subjects and 158 acquired brain injury patients were assessed by the Turkish version of MEAMS. Initially, appropriate pass scores for the normal population were determined through ANOVA post-hoc tests according to age, gender and education. Rasch analysis was then used to test the internal construct validity of the scale and the validity of the cut points for pass scores on the pooled data by using Differential Item Functioning (DIF) analysis within the framework of the Rasch model. Data with the initially modified pass scores were analyzed. DIF was found for certain subtests by age and education, but not for gender. Following this, pass scores were further adjusted and data re-fitted to the model. All subtests were found to fit the Rasch model (mean item fit 0.184, SD 0.319; person fit -0.224, SD 0.557) and DIF was then found to be absent. Thus the final pass scores for all subtests were determined. The MEAMS offers a valid assessment of cognitive state for the adult Turkish population, and the revised cut points accommodate for age and education. Further studies are required to ascertain the validity in different diagnostic groups.

  8. The sensitivity and specificity of the Middlesex Elderly Assessment of Mental State (MEAMS) for detecting cognitive impairment after stroke.

    Science.gov (United States)

    Cartoni, A; Lincoln, N B

    2005-03-01

    The aim of the study was to assess the sensitivity and specificity of the MEAMS (Golding, 1989) for detecting cognitive impairment after stroke. Stroke patients admitted to hospital received a cognitive screening assessment, the MEAMS, and a detailed cognitive assessment. The information obtained from the detailed assessment was summarised in a structured written report. From the conclusions in these reports, patients were classified as "impaired" or "not impaired" in perception, memory, executive function and language. The sensitivity and specificity of the MEAMS subtests and the overall number of tests passed were determined in relation to the presence of impairment, as given in the overall conclusion of the written reports. There were 30 stroke patients, aged 58 to 92 (mean 75.80, SD 7.94) years. Of these, 17 were men and 13 were women. The sensitivity of the MEAMS subtests ranged from 11% to 100% and the specificity ranged from 69% to 100%. The sensitivity of the overall MEAMS score was 52% and the specificity was 100%, using a cut-off score of 3 or more fails to indicate impairment. Three subtests, Orientation, Naming and Unusual views had 81% sensitivity and 50% specificity for detecting problems in language, perception or memory. The MEAMS was not a sensitive screen for overall cognitive impairment or for memory, perceptual, language, or executive function problems after stroke, but it was specific. Although screening for cognitive impairment is important, the MEAMS is not recommended as the sole method, as it produces an unacceptably high false negative rate. Three subtests (Orientation, Naming and Unusual views) had 81% sensitivity and 50% specificity for detecting cognitive problems in language, perception or memory after stroke.

  9. Modeling and Forecasting Average Temperature for Weather Derivative Pricing

    Directory of Open Access Journals (Sweden)

    Zhiliang Wang

    2015-01-01

    Full Text Available The main purpose of this paper is to present a feasible model for the daily average temperature on the area of Zhengzhou and apply it to weather derivatives pricing. We start by exploring the background of weather derivatives market and then use the 62 years of daily historical data to apply the mean-reverting Ornstein-Uhlenbeck process to describe the evolution of the temperature. Finally, Monte Carlo simulations are used to price heating degree day (HDD call option for this city, and the slow convergence of the price of the HDD call can be found through taking 100,000 simulations. The methods of the research will provide a frame work for modeling temperature and pricing weather derivatives in other similar places in China.

  10. Weather Derivatives and Stochastic Modelling of Temperature

    Directory of Open Access Journals (Sweden)

    Fred Espen Benth

    2011-01-01

    Full Text Available We propose a continuous-time autoregressive model for the temperature dynamics with volatility being the product of a seasonal function and a stochastic process. We use the Barndorff-Nielsen and Shephard model for the stochastic volatility. The proposed temperature dynamics is flexible enough to model temperature data accurately, and at the same time being analytically tractable. Futures prices for commonly traded contracts at the Chicago Mercantile Exchange on indices like cooling- and heating-degree days and cumulative average temperatures are computed, as well as option prices on them.

  11. Impact of bacterial ice nucleating particles on weather predicted by a numerical weather prediction model

    Science.gov (United States)

    Sahyoun, Maher; Korsholm, Ulrik S.; Sørensen, Jens H.; Šantl-Temkiv, Tina; Finster, Kai; Gosewinkel, Ulrich; Nielsen, Niels W.

    2017-12-01

    Bacterial ice-nucleating particles (INP) have the ability to facilitate ice nucleation from super-cooled cloud droplets at temperatures just below the melting point. Bacterial INP have been detected in cloud water, precipitation, and dry air, hence they may have an impact on weather and climate. In modeling studies, the potential impact of bacteria on ice nucleation and precipitation formation on global scale is still uncertain due to their small concentration compared to other types of INP, i.e. dust. Those earlier studies did not account for the yet undetected high concentration of nanoscale fragments of bacterial INP, which may be found free or attached to soil dust in the atmosphere. In this study, we investigate the sensitivity of modeled cloud ice, precipitation and global solar radiation in different weather scenarios to changes in the fraction of cloud droplets containing bacterial INP, regardless of their size. For this purpose, a module that calculates the probability of ice nucleation as a function of ice nucleation rate and bacterial INP fraction was developed and implemented in a numerical weather prediction model. The threshold value for the fraction of cloud droplets containing bacterial INP needed to produce a 1% increase in cloud ice was determined at 10-5 to 10-4. We also found that increasing this fraction causes a perturbation in the forecast, leading to significant differences in cloud ice and smaller differences in convective and total precipitation and in net solar radiation reaching the surface. These effects were most pronounced in local convective events. Our results show that bacterial INP can be considered as a trigger factor for precipitation, but not an enhancement factor.

  12. Weathering of oils at sea: model/field data comparisons

    International Nuclear Information System (INIS)

    Daling, Per S.; Stroem, Tove

    1999-01-01

    The SINTEF Oil Weathering Model (OWM) has been extensively tested with results from full-scale field trials with experimental oil slicks in the Norwegian NOFO Sea trials in 1994 and 1995 and the AEA 1997 trials in UK. The comparisons between oil weathering values predicted by the model and ground-truth obtained from the field trials are presented and discussed. Good laboratory weathering data of the specific oil as input to the model is essential for obtaining reliable weathering predictions. Predications provided by the SINTEF-OWM enable oil spill personnel to estimate the most appropriate 'window of opportunity' for use of chemical dispersants under various spill situations. Pre-spill scenario analysis with the SINTEF Oil Spill Contingency and Response (OSCAR) model system, in which the SINTEF-OWM is one of several components, has become an important part of contingency plans as well as contingency training of oil spill personnel at refineries, oil terminals and offshore installations in Norway. (Author)

  13. Geodetic Space Weather Monitoring by means of Ionosphere Modelling

    Science.gov (United States)

    Schmidt, Michael

    2017-04-01

    The term space weather indicates physical processes and phenomena in space caused by radiation of energy mainly from the Sun. Manifestations of space weather are (1) variations of the Earth's magnetic field, (2) the polar lights in the northern and southern hemisphere, (3) variations within the ionosphere as part of the upper atmosphere characterized by the existence of free electrons and ions, (4) the solar wind, i.e. the permanent emission of electrons and photons, (5) the interplanetary magnetic field, and (6) electric currents, e.g. the van Allen radiation belt. It can be stated that ionosphere disturbances are often caused by so-called solar storms. A solar storm comprises solar events such as solar flares and coronal mass ejections (CMEs) which have different effects on the Earth. Solar flares may cause disturbances in positioning, navigation and communication. CMEs can effect severe disturbances and in extreme cases damages or even destructions of modern infrastructure. Examples are interruptions to satellite services including the global navigation satellite systems (GNSS), communication systems, Earth observation and imaging systems or a potential failure of power networks. Currently the measurements of solar satellite missions such as STEREO and SOHO are used to forecast solar events. Besides these measurements the Earth's ionosphere plays another key role in monitoring the space weather, because it responses to solar storms with an increase of the electron density. Space-geodetic observation techniques, such as terrestrial GNSS, satellite altimetry, space-borne GPS (radio occultation), DORIS and VLBI provide valuable global information about the state of the ionosphere. Additionally geodesy has a long history and large experience in developing and using sophisticated analysis and combination techniques as well as empirical and physical modelling approaches. Consequently, geodesy is predestinated for strongly supporting space weather monitoring via

  14. Modeling the influence of organic acids on soil weathering

    Science.gov (United States)

    Lawrence, Corey R.; Harden, Jennifer W.; Maher, Kate

    2014-01-01

    Biological inputs and organic matter cycling have long been regarded as important factors in the physical and chemical development of soils. In particular, the extent to which low molecular weight organic acids, such as oxalate, influence geochemical reactions has been widely studied. Although the effects of organic acids are diverse, there is strong evidence that organic acids accelerate the dissolution of some minerals. However, the influence of organic acids at the field-scale and over the timescales of soil development has not been evaluated in detail. In this study, a reactive-transport model of soil chemical weathering and pedogenic development was used to quantify the extent to which organic acid cycling controls mineral dissolution rates and long-term patterns of chemical weathering. Specifically, oxalic acid was added to simulations of soil development to investigate a well-studied chronosequence of soils near Santa Cruz, CA. The model formulation includes organic acid input, transport, decomposition, organic-metal aqueous complexation and mineral surface complexation in various combinations. Results suggest that although organic acid reactions accelerate mineral dissolution rates near the soil surface, the net response is an overall decrease in chemical weathering. Model results demonstrate the importance of organic acid input concentrations, fluid flow, decomposition and secondary mineral precipitation rates on the evolution of mineral weathering fronts. In particular, model soil profile evolution is sensitive to kaolinite precipitation and oxalate decomposition rates. The soil profile-scale modeling presented here provides insights into the influence of organic carbon cycling on soil weathering and pedogenesis and supports the need for further field-scale measurements of the flux and speciation of reactive organic compounds.

  15. A reactive transport model for Marcellus shale weathering

    Science.gov (United States)

    Heidari, Peyman; Li, Li; Jin, Lixin; Williams, Jennifer Z.; Brantley, Susan L.

    2017-11-01

    Shale formations account for 25% of the land surface globally and contribute a large proportion of the natural gas used in the United States. One of the most productive shale-gas formations is the Marcellus, a black shale that is rich in organic matter and pyrite. As a first step toward understanding how Marcellus shale interacts with water in the surface or deep subsurface, we developed a reactive transport model to simulate shale weathering under ambient temperature and pressure conditions, constrained by soil and water chemistry data. The simulation was carried out for 10,000 years since deglaciation, assuming bedrock weathering and soil genesis began after the last glacial maximum. Results indicate weathering was initiated by pyrite dissolution for the first 1000 years, leading to low pH and enhanced dissolution of chlorite and precipitation of iron hydroxides. After pyrite depletion, chlorite dissolved slowly, primarily facilitated by the presence of CO2 and organic acids, forming vermiculite as a secondary mineral. A sensitivity analysis indicated that the most important controls on weathering include the presence of reactive gases (CO2 and O2), specific surface area, and flow velocity of infiltrating meteoric water. The soil chemistry and mineralogy data could not be reproduced without including the reactive gases. For example, pyrite remained in the soil even after 10,000 years if O2 was not continuously present in the soil column; likewise, chlorite remained abundant and porosity remained small if CO2 was not present in the soil gas. The field observations were only simulated successfully when the modeled specific surface areas of the reactive minerals were 1-3 orders of magnitude smaller than surface area values measured for powdered minerals. Small surface areas could be consistent with the lack of accessibility of some fluids to mineral surfaces due to surface coatings. In addition, some mineral surface is likely interacting only with equilibrated pore

  16. ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS

    Energy Technology Data Exchange (ETDEWEB)

    Chiswell, S.; Buckley, R.

    2009-01-15

    During the year 2008, the United States National Weather Service (NWS) completed an eight fold increase in sampling capability for weather radars to 250 m resolution. This increase is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current NWS operational model domains utilize grid spacing an order of magnitude larger than the radar data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of radar reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution was investigated under a Laboratory Directed Research and Development (LDRD) 'quick hit' grant to determine the impact of improved data resolution on model predictions with specific initial proof of concept application to daily Savannah River Site operations and emergency response. Development of software to process NWS radar reflectivity and radial velocity data was undertaken for assimilation of observations into numerical models. Data values within the radar data volume undergo automated quality control (QC) analysis routines developed in support of this project to eliminate empty/missing data points, decrease anomalous propagation values, and determine error thresholds by utilizing the calculated variances among data values. The Weather Research and Forecasting model (WRF) three dimensional variational data assimilation package (WRF-3DVAR) was used to incorporate the QC'ed radar data into input and boundary conditions. The lack of observational data in the vicinity of SRS available to NWS operational models signifies an important data void where radar observations can provide significant input. These observations greatly enhance the knowledge of storm structures and the environmental conditions which influence their development. As the increase in computational power and availability has

  17. A Reactive Transport Model for Marcellus Shale Weathering

    Science.gov (United States)

    Li, L.; Heidari, P.; Jin, L.; Williams, J.; Brantley, S.

    2017-12-01

    Shale formations account for 25% of the land surface globally. One of the most productive shale-gas formations is the Marcellus, a black shale that is rich in organic matter and pyrite. As a first step toward understanding how Marcellus shale interacts with water, we developed a reactive transport model to simulate shale weathering under ambient temperature and pressure conditions, constrained by soil chemistry and water data. The simulation was carried out for 10,000 years, assuming bedrock weathering and soil genesis began right after the last glacial maximum. Results indicate weathering was initiated by pyrite dissolution for the first 1,000 years, leading to low pH and enhanced dissolution of chlorite and precipitation of iron hydroxides. After pyrite depletion, chlorite dissolved slowly, primarily facilitated by the presence of CO2 and organic acids, forming vermiculite as a secondary mineral. A sensitivity analysis indicated that the most important controls on weathering include the presence of reactive gases (CO2 and O2), specific surface area, and flow velocity of infiltrating meteoric water. The soil chemistry and mineralogy data could not be reproduced without including the reactive gases. For example, pyrite remained in the soil even after 10,000 years if O2 was not continuously present in the soil column; likewise, chlorite remained abundant and porosity remained small with the presence of soil CO2. The field observations were only simulated successfully when the specific surface areas of the reactive minerals were 1-3 orders of magnitude smaller than surface area values measured for powdered minerals, reflecting the lack of accessibility of fluids to mineral surfaces and potential surface coating. An increase in the water infiltration rate enhanced weathering by removing dissolution products and maintaining far-from-equilibrium conditions. We conclude that availability of reactive surface area and transport of H2O and gases are the most important

  18. Atlas : A library for numerical weather prediction and climate modelling

    Science.gov (United States)

    Deconinck, Willem; Bauer, Peter; Diamantakis, Michail; Hamrud, Mats; Kühnlein, Christian; Maciel, Pedro; Mengaldo, Gianmarco; Quintino, Tiago; Raoult, Baudouin; Smolarkiewicz, Piotr K.; Wedi, Nils P.

    2017-11-01

    The algorithms underlying numerical weather prediction (NWP) and climate models that have been developed in the past few decades face an increasing challenge caused by the paradigm shift imposed by hardware vendors towards more energy-efficient devices. In order to provide a sustainable path to exascale High Performance Computing (HPC), applications become increasingly restricted by energy consumption. As a result, the emerging diverse and complex hardware solutions have a large impact on the programming models traditionally used in NWP software, triggering a rethink of design choices for future massively parallel software frameworks. In this paper, we present Atlas, a new software library that is currently being developed at the European Centre for Medium-Range Weather Forecasts (ECMWF), with the scope of handling data structures required for NWP applications in a flexible and massively parallel way. Atlas provides a versatile framework for the future development of efficient NWP and climate applications on emerging HPC architectures. The applications range from full Earth system models, to specific tools required for post-processing weather forecast products. The Atlas library thus constitutes a step towards affordable exascale high-performance simulations by providing the necessary abstractions that facilitate the application in heterogeneous HPC environments by promoting the co-design of NWP algorithms with the underlying hardware.

  19. Evaluation of weather-based rice yield models in India

    Science.gov (United States)

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

    2013-01-01

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

  20. A Product Development Decision Model for Cockpit Weather Information Systems

    Science.gov (United States)

    Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin

    2003-01-01

    There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.

  1. A Product Development Decision Model for Cockpit Weather Information System

    Science.gov (United States)

    Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin; Johnson, Edward J., Jr. (Technical Monitor)

    2003-01-01

    There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.

  2. 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

  3. Modeling Apple Surface Temperature Dynamics Based on Weather Data

    Directory of Open Access Journals (Sweden)

    Lei Li

    2014-10-01

    Full Text Available The exposure of fruit surfaces to direct sunlight during the summer months can result in sunburn damage. Losses due to sunburn damage are a major economic problem when marketing fresh apples. The objective of this study was to develop and validate a model for simulating fruit surface temperature (FST dynamics based on energy balance and measured weather data. A series of weather data (air temperature, humidity, solar radiation, and wind speed was recorded for seven hours between 11:00–18:00 for two months at fifteen minute intervals. To validate the model, the FSTs of “Fuji” apples were monitored using an infrared camera in a natural orchard environment. The FST dynamics were measured using a series of thermal images. For the apples that were completely exposed to the sun, the RMSE of the model for estimating FST was less than 2.0 °C. A sensitivity analysis of the emissivity of the apple surface and the conductance of the fruit surface to water vapour showed that accurate estimations of the apple surface emissivity were important for the model. The validation results showed that the model was capable of accurately describing the thermal performances of apples under different solar radiation intensities. Thus, this model could be used to more accurately estimate the FST relative to estimates that only consider the air temperature. In addition, this model provides useful information for sunburn protection management.

  4. Modeling apple surface temperature dynamics based on weather data.

    Science.gov (United States)

    Li, Lei; Peters, Troy; Zhang, Qin; Zhang, Jingjin; Huang, Danfeng

    2014-10-27

    The exposure of fruit surfaces to direct sunlight during the summer months can result in sunburn damage. Losses due to sunburn damage are a major economic problem when marketing fresh apples. The objective of this study was to develop and validate a model for simulating fruit surface temperature (FST) dynamics based on energy balance and measured weather data. A series of weather data (air temperature, humidity, solar radiation, and wind speed) was recorded for seven hours between 11:00-18:00 for two months at fifteen minute intervals. To validate the model, the FSTs of "Fuji" apples were monitored using an infrared camera in a natural orchard environment. The FST dynamics were measured using a series of thermal images. For the apples that were completely exposed to the sun, the RMSE of the model for estimating FST was less than 2.0 °C. A sensitivity analysis of the emissivity of the apple surface and the conductance of the fruit surface to water vapour showed that accurate estimations of the apple surface emissivity were important for the model. The validation results showed that the model was capable of accurately describing the thermal performances of apples under different solar radiation intensities. Thus, this model could be used to more accurately estimate the FST relative to estimates that only consider the air temperature. In addition, this model provides useful information for sunburn protection management.

  5. Time series regression model for infectious disease and weather.

    Science.gov (United States)

    Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

    2015-10-01

    Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  6. Test-retest reliability of the Middlesex Assessment of Mental State (MEAMS): a preliminary investigation in people with probable dementia.

    Science.gov (United States)

    Powell, T; Brooker, D J; Papadopolous, A

    1993-05-01

    Relative and absolute test-retest reliability of the MEAMS was examined in 12 subjects with probable dementia and 12 matched controls. Relative reliability was good. Measures of absolute reliability showed scores changing by up to 3 points over an interval of a week. A version effect was found to be in evidence.

  7. Susceptibility of Bemisia tabaci MEAM1 (Hemiptera: Aleyrodidae) to imidacloprid, thiamethoxam, dinotefuran and flupyradifurone in south Florida

    Science.gov (United States)

    Populations of Bemisa tabaci Middle East Asia Minor 1 (MEAM 1) were established from nineteen locations in south Florida, primarily from commercial tomato fields, and were tested using a cotton leaf petiole systemic uptake method for susceptibility to the nicotinic acetylcholine agonist insecticides...

  8. Parameterisation of sea and lake ice in numerical weather prediction models of the German Weather Service

    Directory of Open Access Journals (Sweden)

    Dmitrii Mironov

    2012-04-01

    Full Text Available A bulk thermodynamic (no rheology sea-ice parameterisation scheme for use in numerical weather prediction (NWP is presented. The scheme is based on a self-similar parametric representation (assumed shape of the evolving temperature profile within the ice and on the integral heat budget of the ice slab. The scheme carries ordinary differential equations (in time for the ice surface temperature and the ice thickness. The proposed sea-ice scheme is implemented into the NWP models GME (global and COSMO (limited-area of the German Weather Service. In the present operational configuration, the horizontal distribution of the sea ice is governed by the data assimilation scheme, no fractional ice cover within the GME/COSMO grid box is considered, and the effect of snow above the ice is accounted for through an empirical temperature dependence of the ice surface albedo with respect to solar radiation. The lake ice is treated similarly to the sea ice, except that freeze-up and break-up of lakes occurs freely, independent of the data assimilation. The sea and lake ice schemes (the latter is a part of the fresh-water lake parameterisation scheme FLake show a satisfactory performance in GME and COSMO. The ice characteristics are not overly sensitive to the details of the treatment of heat transfer through the ice layer. This justifies the use of a simplified but computationally efficient bulk approach to model the ice thermodynamics in NWP, where the ice surface temperature is a major concern whereas details of the temperature distribution within the ice are of secondary importance. In contrast to the details of the heat transfer through the ice, the cloud cover is of decisive importance for the ice temperature as it controls the radiation energy budget at the ice surface. This is particularly true for winter, when the long-wave radiation dominates the surface energy budget. During summer, the surface energy budget is also sensitive to the grid-box mean ice

  9. Asymmetric consequences of host plant occupation on the competition between the whiteflies Bemisia tabaci cryptic species MEAM1 and Trialeurodes vaporariorum (Hemiptera: Aleyrodidae).

    Science.gov (United States)

    Zhang, Gui-Fen; Lövei, Gábor L; Hu, Man; Wan, Fang-Hao

    2014-12-01

    The two common whitefly species, Bemisia tabaci (Gennadius) MEAM1 and Trialeurodes vaporariorum (Westwood), often co-occur on their host plants. The effect of host plant occupation by one species on later-arriving conspecific individuals or on the other competing species was examined. Resource preoccupied by T. vaporariorum had mostly negative effects on the life history parameters of later-arriving conspecifics. Red-eyed nymph and immature survival of T. vaporariorum decreased when resource was preoccupied by conspecifics, irrespective of the previous occupation scenario. However, resource preoccupied by T. vaporariorum had only minor detrimental effects on the performance of later-arriving B. tabaci MEAM1. In the opposite colonisation sequence, previous occupation by B. tabaci MEAM1 had no significant effects on the life history parameters of later-arriving conspecifics, but severe detrimental effects were observed on the performance of later-arriving T. vaporariorum. Total immature survival of T. vaporariorum decreased in both weak and strong previous occupation situations by B. tabaci MEAM1. The interspecific interactions between B. tabaci MEAM1 and T. vaporariorum were asymmetric, with B. tabaci MEAM1 being the superior competitor. This superiority could partially explain the rapid spread of B. tabaci MEAM1 in China. © 2013 Society of Chemical Industry.

  10. Traffic analysis toolbox volume XI : weather and traffic analysis, modeling and simulation.

    Science.gov (United States)

    2010-12-01

    This document presents a weather module for the traffic analysis tools program. It provides traffic engineers, transportation modelers and decisions makers with a guide that can incorporate weather impacts into transportation system analysis and mode...

  11. Weather Research and Forecasting (WRF) Regional Atmospheric Model: Maui-Oahu

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 7-day hourly forecast for the region surrounding the Hawaiian islands of Oahu,...

  12. Weather Research and Forecasting (WRF) Regional Atmospheric Model: Main Hawaiian Islands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model 7-day hourly forecast for the region surrounding the Main Hawaiian Islands (MHI)...

  13. The origins of computer weather prediction and climate modeling

    International Nuclear Information System (INIS)

    Lynch, Peter

    2008-01-01

    Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed

  14. Weather regimes in past climate atmospheric general circulation model simulations

    Energy Technology Data Exchange (ETDEWEB)

    Kageyama, M.; Ramstein, G. [CEA Saclay, Gif-sur-Yvette (France). Lab. des Sci. du Climat et de l' Environnement; D' Andrea, F.; Vautard, R. [Laboratoire de Meteorologie Dynamique, Ecole Normale Superieure, Paris (France); Valdes, P.J. [Department of Meteorology, University of Reading (United Kingdom)

    1999-10-01

    We investigate the climates of the present-day, inception of the last glaciation (115000 y ago) and last glacial maximum (21000 y ago) in the extratropical north Atlantic and Europe, as simulated by the laboratoire de Meteorologie dynamique atmospheric general circulation model. We use these simulations to investigate the low-frequency variability of the model in different climates. The aim is to evaluate whether changes in the intraseasonal variability, which we characterize using weather regimes, can help describe the impact of different boundary conditions on climate and give a better understanding of climate change processes. Weather regimes are defined as the most recurrent patterns in the 500 hPa geopotential height, using a clustering algorithm method. The regimes found in the climate simulations of the present-day and inception of the last glaciation are similar in their number and their structure. It is the regimes' populations which are found to be different for these climates, with an increase of the model's blocked regime and a decrease in the zonal regime at the inception of the last glaciation. This description reinforces the conclusions from a study of the differences between the climatological averages of the different runs and confirms the northeastward shift to the tail of the Atlantic storm-track, which would favour more precipitation over the site of growth of the Fennoscandian ice-sheet. On the other hand, the last glacial maximum results over this sector are not found to be classifiable, showing that the change in boundary conditions can be responsible for severe changes in the weather regime and low-frequency dynamics. The LGM Atlantic low-frequency variability appears to be dominated by a large-scale retrogressing wave with a period 40 to 50 days. (orig.)

  15. The effect of different weather data sets and their resolution on climate-based daylight modelling

    DEFF Research Database (Denmark)

    Iversen, A; Svendsen, Svend; Nielsen, Toke Rammer

    2013-01-01

    Climate-based daylight modelling is based on the available weather data, which means that the weather data used as input to the daylight simulations are of great importance. In this paper, the effect on the outcome of the daylight simulations of using one weather data file rather than another...

  16. Modeling the weather impact on aviation in a global air traffic model

    Science.gov (United States)

    Himmelsbach, S.; Hauf, T.; Rokitansky, C. H.

    2009-09-01

    Weather has a strong impact on aviation safety and efficiency. For a better understanding of that impact, especially of thunderstorms and similar other severe hazards, we pursued a modeling approach. We used the detailed simulation software (NAVSIM) of worldwide air traffic, developed by Rokitansky [Eurocontrol, 2005] and implemented a specific weather module. NAVSIM models each aircraft with its specific performance characteristics separately along preplanned and prescribed routes. The specific weather module in its current version simulates a thunderstorm as an impenetrable 3D object, which forces an aircraft to circumvent the latter. We refer to that object in general terms as a weather object. The Cb-weather object, as a specific weather object, is a heuristic model of a real thunderstorm, with its characteristics based on actually observed satellite and precipitation radar data. It is comprised of an upper volume, mostly the anvil, and a bottom volume, the up- and downdrafts and the lower outflow area [Tafferner and Forster, 2009; Kober and Tafferner 2009; Zinner et al, 2008]. The Cb-weather object is already implemented in NAVSIM, other weather objects like icing and turbulence will follow. This combination of NAVSIM with a weather object allows a detailed investigation of situations where conflicts exist between planned flight routes and adverse weather. The first objective is to simulate the observed circum-navigation in NAVSIM. Real occurring routes will be compared with simulated ones. Once this has successfully completed, NAVSIM offers a platform to assess existing rules and develop more efficient strategies to cope with adverse weather. An overview will be given over the implementation status of weather objects within NAVSIM and first results will be presented. Cb-object data provision by A. Tafferner, C. Forster, T. Zinner, K. Kober, M. Hagen (DLR Oberpfaffenhofen) is greatly acknowledged. References: Eurocontrol, VDL Mode 2 Capacity Analysis through

  17. 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...

  18. Space Weather Forecasting and Research at the Community Coordinated Modeling Center

    Science.gov (United States)

    Aronne, M.

    2015-12-01

    The Space Weather Research Center (SWRC), within the Community Coordinated Modeling Center (CCMC), provides experimental research forecasts and analysis for NASA's robotic mission operators. Space weather conditions are monitored to provide advance warning and forecasts based on observations and modeling using the integrated Space Weather Analysis Network (iSWA). Space weather forecasters come from a variety of backgrounds, ranging from modelers to astrophysicists to undergraduate students. This presentation will discuss space weather operations and research from an undergraduate perspective. The Space Weather Research, Education, and Development Initiative (SW REDI) is the starting point for many undergraduate opportunities in space weather forecasting and research. Space weather analyst interns play an active role year-round as entry-level space weather analysts. Students develop the technical and professional skills to forecast space weather through a summer internship that includes a two week long space weather boot camp, mentorship, poster session, and research opportunities. My unique development of research projects includes studying high speed stream events as well as a study of 20 historic, high-impact solar energetic particle events. This unique opportunity to combine daily real-time analysis with related research prepares students for future careers in Heliophysics.

  19. Economics of extreme weather events: Terminology and regional impact models

    OpenAIRE

    Jahn, Malte

    2015-01-01

    Impacts of extreme weather events are relevant for regional (in the sense of subnational) economies and in particular cities in many aspects. Cities are the cores of economic activity and the amount of people and assets endangered by extreme weather events is large, even under the current climate. A changing climate with changing extreme weather patterns and the process of urbanization will make the whole issue even more relevant in the future. In this paper, definitions and terminology in th...

  20. Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

    Science.gov (United States)

    Zavodsky, Bradley; Case, Jonathan L.; Gotway, John H.; White, Kristopher; Medlin, Jeffrey; Wood, Lance; Radell, Dave

    2014-01-01

    Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use

  1. Weather Radar Estimations Feeding an Artificial Neural Network Model Weather Radar Estimations Feeding an Artificial Neural Network Model

    Directory of Open Access Journals (Sweden)

    Dawei Han

    2012-02-01

    Full Text Available The application of ANNs (Artifi cial Neural Networks has been studied by many researchers in modelling rainfall runoff processes. However, the work so far has been focused on the rainfall data from traditional raingauges. Weather radar is a modern technology which could provide high resolution rainfall in time and space. In this study, a comparison in rainfall runoff modelling between the raingauge and weather radar has been carried out. The data were collected from Brue catchment in Southwest of England, with 49 raingauges covering 136 km2 and two C-band weather radars. This raingauge network is extremely dense (for research purposes and does not represent the usual raingauge density in operational flood forecasting systems. The ANN models were set up with both lumped and spatial rainfall input. The results showed that raingauge data outperformed radar data in all the events tested, regardless of the lumped and spatial input. La aplicación de Redes Neuronales Artificiales (RNA en el modelado de lluvia-flujo ha sido estudiada ampliamente. Sin embargo, hasta ahora se han utilizado datos provenientes de pluviómetros tradicionales. Los radares meteorológicos son una tecnología moderna que puede proveer datos de lluvia de alta resolución en tiempo y espacio. Este es un trabajo de comparación en el modelado lluvia-flujo entre pluviómetros y radares meteorológicos. Los datos provienen de la cuenca del río Brue en el suroeste de Inglaterra, con 49 pluviómetros cubriendo 136 km2 y dos radares meteorológicos en la banda C. Esta red de pluviómetros es extremadamente densa (para investigación y no representa la densidad usual en sistemas de predicción de inundaciones. Los modelos de RNA fueron implementados con datos de entrada de lluvia tanto espaciados como no distribuidos. Los resultados muestran que los datos de los pluviómetros fueron mejores que los datos de los radares en todos los eventos probados.

  2. User's guide to the weather model: a component of the western spruce budworm modeling system.

    Science.gov (United States)

    W. P. Kemp; N. L. Crookston; P. W. Thomas

    1989-01-01

    A stochastic model useful in simulating daily maximum and minimum temperature and precipitation developed by Bruhn and others has been adapted for use in the western spruce budworm modeling system. This document describes how to use the weather model and illustrates some aspects of its behavior.

  3. Spatially explicit modelling of extreme weather and climate events ...

    African Journals Online (AJOL)

    The reality of climate change continues to influence the intensity and frequency of extreme weather events such as heat waves, droughts, floods, and landslides. The impacts of the cumulative interplay of these extreme weather and climate events variation continue to perturb governments causing a scramble into formation ...

  4. Weather forecasting for Eastern Amazon with OLAM model

    Directory of Open Access Journals (Sweden)

    Renato Ramos da Silva

    2014-12-01

    Full Text Available The OLAM model has as its characteristics the advantage to represent simultaneously the global and regional meteorological phenomena using the application of a grid refinement scheme. During the REMAM project the model was applied for a few case studies to evaluate its performance on numerical weather prediction for the eastern Amazon region. Case studies were performed for the twelve months of the year of 2009. The model results for those numerical experiments were compared with the observed data for the region of study. Precipitation data analysis showed that OLAM is able to represent the average mean accumulated precipitation and the seasonal features of the events occurrence, but can't predict the local total amount of precipitation. However, individual evaluation for a few cases had shown that OLAM was able to represent the dynamics and forecast a few days in advance the development of coastal meteorological systems such as the squall lines that are one of the most important precipitating systems of the Amazon.

  5. A review of operational, regional-scale, chemical weather forecasting models in Europe

    Directory of Open Access Journals (Sweden)

    J. Kukkonen

    2012-01-01

    Full Text Available Numerical models that combine weather forecasting and atmospheric chemistry are here referred to as chemical weather forecasting models. Eighteen operational chemical weather forecasting models on regional and continental scales in Europe are described and compared in this article. Topics discussed in this article include how weather forecasting and atmospheric chemistry models are integrated into chemical weather forecasting systems, how physical processes are incorporated into the models through parameterization schemes, how the model architecture affects the predicted variables, and how air chemistry and aerosol processes are formulated. In addition, we discuss sensitivity analysis and evaluation of the models, user operational requirements, such as model availability and documentation, and output availability and dissemination. In this manner, this article allows for the evaluation of the relative strengths and weaknesses of the various modelling systems and modelling approaches. Finally, this article highlights the most prominent gaps of knowledge for chemical weather forecasting models and suggests potential priorities for future research directions, for the following selected focus areas: emission inventories, the integration of numerical weather prediction and atmospheric chemical transport models, boundary conditions and nesting of models, data assimilation of the various chemical species, improved understanding and parameterization of physical processes, better evaluation of models against data and the construction of model ensembles.

  6. Mountain range specific analog weather forecast model for ...

    Indian Academy of Sciences (India)

    used to draw weather forecast for that mountain range in operational weather forecasting mode, three days ... various road management activities and for better .... −0.8. 1.5. 0.0. Pir Panjal range (HP). 1989–90 to 2002–03. 14. Snow day. 2.2. −4.1 ..... ed days,. S. = snow day,. N. S. = no-snow day and. P. C. = per cent correct).

  7. Wind field near complex terrain using numerical weather prediction model

    Science.gov (United States)

    Chim, Kin-Sang

    The PennState/NCAR MM5 model was modified to simulate an idealized flow pass through a 3D obstacle in the Micro- Alpha Scale domain. The obstacle used were the idealized Gaussian obstacle and the real topography of Lantau Island of Hong Kong. The Froude number under study is ranged from 0.22 to 1.5. Regime diagrams for both the idealized Gaussian obstacle and Lantau island were constructed. This work is divided into five parts. The first part is the problem definition and the literature review of the related publications. The second part briefly discuss as the PennState/NCAR MM5 model and a case study of long- range transport is included. The third part is devoted to the modification and the verification of the PennState/NCAR MM5 model on the Micro-Alpha Scale domain. The implementation of the Orlanski (1976) open boundary condition is included with the method of single sounding initialization of the model. Moreover, an upper dissipative layer, Klemp and Lilly (1978), is implemented on the model. The simulated result is verified by the Automatic Weather Station (AWS) data and the Wind Profiler data. Four different types of Planetary Boundary Layer (PBL) parameterization schemes have been investigated in order to find out the most suitable one for Micro-Alpha Scale domain in terms of both accuracy and efficiency. Bulk Aerodynamic type of PBL parameterization scheme is found to be the most suitable PBL parameterization scheme. Investigation of the free- slip lower boundary condition is performed and the simulated result is compared with that with friction. The fourth part is the use of the modified PennState/NCAR MM5 model for an idealized flow simulation. The idealized uniform flow used is nonhydrostatic and has constant Froude number. Sensitivity test is performed by varying the Froude number and the regime diagram is constructed. Moreover, nondimensional drag is found to be useful for regime identification. The model result is also compared with the analytic

  8. 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.

  9. Climate and weather risk in natural resource models

    Science.gov (United States)

    Merrill, Nathaniel Henry

    This work, consisting of three manuscripts, addresses natural resource management under risk due to variation in climate and weather. In three distinct but theoretically related applications, I quantify the role of natural resources in stabilizing economic outcomes. In Manuscript 1, we address policy designed to effect the risk of cyanobacteria blooms in a drinking water reservoir through watershed wide policy. Combining a hydrologic and economic model for a watershed in Rhode Island, we solve for the efficient allocation of best management practices (BMPs) on livestock pastures to meet a monthly risk-based as well as mean-based water quality objective. In order to solve for the efficient allocations of nutrient control effort, we optimize a probabilistically constrained integer-programming problem representing the choices made on each farm and the resultant conditions that support cyanobacteria blooms. In doing so, we employ a genetic algorithm (GA). We hypothesize that management based on controlling the upper tail of the probability distribution of phosphorus loading implies different efficient management actions as compared to controlling mean loading. We find a shift to more intense effort on fewer acres when a probabilistic objective is specified with cost savings of meeting risk levels of up to 25% over mean loading based policies. Additionally, we illustrate the relative cost effectiveness of various policies designed to meet this risk-based objective. Rainfall and the subsequent overland runoff is the source of transportation of nutrients to a receiving water body, with larger amounts of phosphorus moving in more intense rainfall events. We highlight the importance of this transportation mechanism by comparing policies under climate change scenarios, where the intensity of rainfall is projected to increase and the time series process of rainfall to change. In Manuscript 2, we introduce a new economic groundwater model that incorporates the gradual shift

  10. Community Coordinated Modeling Center: A Powerful Resource in Space Science and Space Weather Education

    Science.gov (United States)

    Chulaki, A.; Kuznetsova, M. M.; Rastaetter, L.; MacNeice, P. J.; Shim, J. S.; Pulkkinen, A. A.; Taktakishvili, A.; Mays, M. L.; Mendoza, A. M. M.; Zheng, Y.; Mullinix, R.; Collado-Vega, Y. M.; Maddox, M. M.; Pembroke, A. D.; Wiegand, C.

    2015-12-01

    Community Coordinated Modeling Center (CCMC) is a NASA affiliated interagency partnership with the primary goal of aiding the transition of modern space science models into space weather forecasting while supporting space science research. Additionally, over the past ten years it has established itself as a global space science education resource supporting undergraduate and graduate education and research, and spreading space weather awareness worldwide. A unique combination of assets, capabilities and close ties to the scientific and educational communities enable this small group to serve as a hub for raising generations of young space scientists and engineers. CCMC resources are publicly available online, providing unprecedented global access to the largest collection of modern space science models (developed by the international research community). CCMC has revolutionized the way simulations are utilized in classrooms settings, student projects, and scientific labs and serves hundreds of educators, students and researchers every year. Another major CCMC asset is an expert space weather prototyping team primarily serving NASA's interplanetary space weather needs. Capitalizing on its unrivaled capabilities and experiences, the team provides in-depth space weather training to students and professionals worldwide, and offers an amazing opportunity for undergraduates to engage in real-time space weather monitoring, analysis, forecasting and research. In-house development of state-of-the-art space weather tools and applications provides exciting opportunities to students majoring in computer science and computer engineering fields to intern with the software engineers at the CCMC while also learning about the space weather from the NASA scientists.

  11. Space Weather Models and Their Validation and Verification at the CCMC

    Science.gov (United States)

    Hesse, Michael

    2010-01-01

    The Community Coordinated l\\lodeling Center (CCMC) is a US multi-agency activity with a dual mission. With equal emphasis, CCMC strives to provide science support to the international space research community through the execution of advanced space plasma simulations, and it endeavors to support the space weather needs of the CS and partners. Space weather support involves a broad spectrum, from designing robust forecasting systems and transitioning them to forecasters, to providing space weather updates and forecasts to NASA's robotic mission operators. All of these activities have to rely on validation and verification of models and their products, so users and forecasters have the means to assign confidence levels to the space weather information. In this presentation, we provide an overview of space weather models resident at CCMC, as well as of validation and verification activities undertaken at CCMC or through the use of CCMC services.

  12. 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...

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

    Science.gov (United States)

    Krissansen-Totton, Joshua; Catling, David C

    2017-05-22

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

  14. Integrating topography, hydrology and rock structure in weathering rate models of spring watersheds

    NARCIS (Netherlands)

    Pacheco, F.A.L.; Weijden, C.H. van der

    2012-01-01

    Weathering rate models designed for watersheds combine chemical data of discharging waters with morphologic and hydrologic parameters of the catchments. At the spring watershed scale, evaluation of morphologic parameters is subjective due to difficulties in conceiving the catchment geometry.

  15. Using Weather Data and Climate Model Output in Economic Analyses of Climate Change

    Energy Technology Data Exchange (ETDEWEB)

    Auffhammer, M.; Hsiang, S. M.; Schlenker, W.; Sobel, A.

    2013-06-28

    Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

  16. 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)

  17. Weather models as virtual sensors to data-driven rainfall predictions in urban watersheds

    Science.gov (United States)

    Cozzi, Lorenzo; Galelli, Stefano; Pascal, Samuel Jolivet De Marc; Castelletti, Andrea

    2013-04-01

    Weather and climate predictions are a key element of urban hydrology where they are used to inform water management and assist in flood warning delivering. Indeed, the modelling of the very fast dynamics of urbanized catchments can be substantially improved by the use of weather/rainfall predictions. For example, in Singapore Marina Reservoir catchment runoff processes have a very short time of concentration (roughly one hour) and observational data are thus nearly useless for runoff predictions and weather prediction are required. Unfortunately, radar nowcasting methods do not allow to carrying out long - term weather predictions, whereas numerical models are limited by their coarse spatial scale. Moreover, numerical models are usually poorly reliable because of the fast motion and limited spatial extension of rainfall events. In this study we investigate the combined use of data-driven modelling techniques and weather variables observed/simulated with a numerical model as a way to improve rainfall prediction accuracy and lead time in the Singapore metropolitan area. To explore the feasibility of the approach, we use a Weather Research and Forecast (WRF) model as a virtual sensor network for the input variables (the states of the WRF model) to a machine learning rainfall prediction model. More precisely, we combine an input variable selection method and a non-parametric tree-based model to characterize the empirical relation between the rainfall measured at the catchment level and all possible weather input variables provided by WRF model. We explore different lead time to evaluate the model reliability for different long - term predictions, as well as different time lags to see how past information could improve results. Results show that the proposed approach allow a significant improvement of the prediction accuracy of the WRF model on the Singapore urban area.

  18. 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.

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

    Science.gov (United States)

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

    2009-01-01

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

  20. Analysis and Modeling of Influenza Outbreaks as Driven by Weather

    Science.gov (United States)

    Thrastarson, H. T.; Teixeira, J.; Serman, E. A.; Parekh, A.; Yeo, E.

    2017-12-01

    Seasonal influenza outbreaks are a major source of illness, mortality and economic burden worldwide. Attributing what drives the seasonality of the outbreaks is still an unsettled problem. But in temperate regions absolute humidity conditions are a strong candidate (Shaman et al., 2010) and some studies have associated temperature conditions with influenza outbreaks. We use humidity and temperature data from NASA's AIRS (Atmospheric Infra-Red Sounder) instrument as well as data for influenza incidence in the US and South Africa to explore the connection between weather and influenza seasonality at different spatial scales. We also incorporate influenza surveillance data, satellite data and humidity forecasts into a numerical epidemiological prediction system. Our results give support for the role of local weather conditions as drivers of the seasonality of influenza in temperate regions. This can have implications for public health efforts where forecasting of the timing and intensity of influenza outbreaks has a great potential role (e.g., aiding management and organization of vaccines, drugs and other resources).

  1. DEM investigation of weathered rocks using a novel bond contact model

    Directory of Open Access Journals (Sweden)

    Zhenming Shi

    2015-06-01

    Full Text Available The distinct element method (DEM incorporated with a novel bond contact model was applied in this paper to shed light on the microscopic physical origin of macroscopic behaviors of weathered rock, and to achieve the changing laws of microscopic parameters from observed decaying properties of rocks during weathering. The changing laws of macroscopic mechanical properties of typical rocks were summarized based on the existing research achievements. Parametric simulations were then conducted to analyze the relationships between macroscopic and microscopic parameters, and to derive the changing laws of microscopic parameters for the DEM model. Equipped with the microscopic weathering laws, a series of DEM simulations of basic laboratory tests on weathered rock samples was performed in comparison with analytical solutions. The results reveal that the relationships between macroscopic and microscopic parameters of rocks against the weathering period can be successfully attained by parametric simulations. In addition, weathering has a significant impact on both stress–strain relationship and failure pattern of rocks.

  2. Assessing Individual Weather Risk-Taking and Its Role in Modeling Likelihood of Hurricane Evacuation

    Science.gov (United States)

    Stewart, A. E.

    2017-12-01

    This research focuses upon measuring an individual's level of perceived risk of different severe and extreme weather conditions using a new self-report measure, the Weather Risk-Taking Scale (WRTS). For 32 severe and extreme situations in which people could perform an unsafe behavior (e. g., remaining outside with lightning striking close by, driving over roadways covered with water, not evacuating ahead of an approaching hurricane, etc.), people rated: 1.their likelihood of performing the behavior, 2. The perceived risk of performing the behavior, 3. the expected benefits of performing the behavior, and 4. whether the behavior has actually been performed in the past. Initial development research with the measure using 246 undergraduate students examined its psychometric properties and found that it was internally consistent (Cronbach's a ranged from .87 to .93 for the four scales) and that the scales possessed good temporal (test-retest) reliability (r's ranged from .84 to .91). A second regression study involving 86 undergraduate students found that taking weather risks was associated with having taken similar risks in one's past and with the personality trait of sensation-seeking. Being more attentive to the weather and perceiving its risks when it became extreme was associated with lower likelihoods of taking weather risks (overall regression model, R2adj = 0.60). A third study involving 334 people examined the contributions of weather risk perceptions and risk-taking in modeling the self-reported likelihood of complying with a recommended evacuation ahead of a hurricane. Here, higher perceptions of hurricane risks and lower perceived benefits of risk-taking along with fear of severe weather and hurricane personal self-efficacy ratings were all statistically significant contributors to the likelihood of evacuating ahead of a hurricane. Psychological rootedness and attachment to one's home also tend to predict lack of evacuation. This research highlights the

  3. Don Quixote Pond: A Small Scale Model of Weathering and Salt Accumulation

    Science.gov (United States)

    Englert, P.; Bishop, J. L.; Patel, S. N.; Gibson, E. K.; Koeberl, C.

    2015-01-01

    The formation of Don Quixote Pond in the North Fork of Wright Valley, Antarctica, is a model for unique terrestrial calcium, chlorine, and sulfate weathering, accumulation, and distribution processes. The formation of Don Quixote Pond by simple shallow and deep groundwater contrasts more complex models for Don Juan Pond in the South Fork of Wright Valley. Our study intends to understand the formation of Don Quixote Pond as unique terrestrial processes and as a model for Ca, C1, and S weathering and distribution on Mars.

  4. Implementation of an atmospheric sulfur scheme in the HIRLAM regional weather forecast model

    International Nuclear Information System (INIS)

    Ekman, Annica

    2000-02-01

    Sulfur chemistry has been implemented into the regional weather forecast model HIRLAM in order to simulate sulfur fields during specific weather situations. The model calculates concentrations of sulfur dioxide in air (SO 2 (a)), sulfate in air (SO 4 (a)), sulfate in cloud water (SO 4 (aq)) and hydrogen peroxide (H 2 O 2 ). Modeled concentrations of SO 2 (a), SO 4 (a) and SO 4 (aq) in rain water are compared with observations for two weather situations, one winter case with an extensive stratiform cloud cover and one summer case with mostly convective clouds. A comparison of the weather forecast parameters precipitation, relative humidity, geopotential and temperature with observations is also performed. The results show that the model generally overpredicts the SO 2 (a) concentration and underpredicts the SO 4 (a) concentration. The agreement between modeled and observed SO 4 (aq) in rain water is poor. Calculated turnover times are approximately 1 day for SO 2 (a) and 2-2.5 days for SO 4 (a). For SO 2 (a) this is in accordance with earlier simulated global turnover times, but for SO 4 (a) it is substantially lower. Several sensitivity simulations show that the fractional mean bias and root mean square error decreases, mainly for SO 4 (a) and SO 4 (aq), if an additional oxidant for converting SO 2 (a) to SO 4 (a) is included in the model. All weather forecast parameters, except precipitation, agree better with observations than the sulfur variables do. Wet scavenging is responsible for about half of the deposited sulfur and in addition, a major part of the sulfate production occurs through in-cloud oxidation. Hence, the distribution of clouds and precipitation must be better simulated by the weather forecast model in order to improve the agreement between observed and simulated sulfur concentrations

  5. Training the next generation of scientists in Weather Forecasting: new approaches with real models

    Science.gov (United States)

    Carver, Glenn; Váňa, Filip; Siemen, Stephan; Kertesz, Sandor; Keeley, Sarah

    2014-05-01

    The European Centre for Medium Range Weather Forecasts operationally produce medium range forecasts using what is internationally acknowledged as the world leading global weather forecast model. Future development of this scientifically advanced model relies on a continued availability of experts in the field of meteorological science and with high-level software skills. ECMWF therefore has a vested interest in young scientists and University graduates developing the necessary skills in numerical weather prediction including both scientific and technical aspects. The OpenIFS project at ECMWF maintains a portable version of the ECMWF forecast model (known as IFS) for use in education and research at Universities, National Meteorological Services and other research and education organisations. OpenIFS models can be run on desktop or high performance computers to produce weather forecasts in a similar way to the operational forecasts at ECMWF. ECMWF also provide the Metview desktop application, a modern, graphical, and easy to use tool for analysing and visualising forecasts that is routinely used by scientists and forecasters at ECMWF and other institutions. The combination of Metview with the OpenIFS models has the potential to deliver classroom-friendly tools allowing students to apply their theoretical knowledge to real-world examples using a world-leading weather forecasting model. In this paper we will describe how the OpenIFS model has been used for teaching. We describe the use of Linux based 'virtual machines' pre-packaged on USB sticks that support a technically easy and safe way of providing 'classroom-on-a-stick' learning environments for advanced training in numerical weather prediction. We welcome discussions with interested parties.

  6. A critical view on temperature modelling for application in weather derivatives markets

    International Nuclear Information System (INIS)

    Šaltytė Benth, Jūratė; Benth, Fred Espen

    2012-01-01

    In this paper we present a stochastic model for daily average temperature. The model contains seasonality, a low-order autoregressive component and a variance describing the heteroskedastic residuals. The model is estimated on daily average temperature records from Stockholm (Sweden). By comparing the proposed model with the popular model of Campbell and Diebold (2005), we point out some important issues to be addressed when modelling the temperature for application in weather derivatives market. - Highlights: ► We present a stochastic model for daily average temperature, containing seasonality, a low-order autoregressive component and a variance describing the heteroskedastic residuals. ► We compare the proposed model with the popular model of Campbell and Diebold (2005). ► Some important issues to be addressed when modelling the temperature for application in weather derivatives market are pointed out.

  7. What is a Proper Resolution of Weather Radar Precipitation Estimates for Urban Drainage Modelling?

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Rasmussen, Michael R.; Thorndahl, Søren Liedtke

    2012-01-01

    The resolution of distributed rainfall input for drainage models is the topic of this paper. The study is based on data from high resolution X-band weather radar used together with an urban drainage model of a medium size Danish village. The flow, total run-off volume and CSO volume are evaluated...

  8. A short-range multi-model ensemble weather prediction system for South Africa

    CSIR Research Space (South Africa)

    Landman, S

    2010-09-01

    Full Text Available prediction system (EPS) at the South African Weather Service (SAWS) are examined. The ensemble consists of different forecasts from the 12-km LAM of the UK Met Office Unified Model (UM) and the Conformal-Cubic Atmospheric Model (CCAM) covering the South...

  9. Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Ames Code I Private Cloud Computing Environment

    Science.gov (United States)

    Molthan, Andrew; Case, Jonathan; Venner, Jason; Moreno-Madrinan, Max J.; Delgado, Francisco

    2012-01-01

    Two projects at NASA Marshall Space Flight Center have collaborated to develop a high resolution weather forecast model for Mesoamerica: The NASA Short-term Prediction Research and Transition (SPoRT) Center, which integrates unique NASA satellite and weather forecast modeling capabilities into the operational weather forecasting community. NASA's SERVIR Program, which integrates satellite observations, ground-based data, and forecast models to improve disaster response in Central America, the Caribbean, Africa, and the Himalayas.

  10. 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

  11. Predictive Models for Photovoltaic Electricity Production in Hot Weather Conditions

    Directory of Open Access Journals (Sweden)

    Jabar H. Yousif

    2017-07-01

    Full Text Available The process of finding a correct forecast equation for photovoltaic electricity production from renewable sources is an important matter, since knowing the factors affecting the increase in the proportion of renewable energy production and reducing the cost of the product has economic and scientific benefits. This paper proposes a mathematical model for forecasting energy production in photovoltaic (PV panels based on a self-organizing feature map (SOFM model. The proposed model is compared with other models, including the multi-layer perceptron (MLP and support vector machine (SVM models. Moreover, a mathematical model based on a polynomial function for fitting the desired output is proposed. Different practical measurement methods are used to validate the findings of the proposed neural and mathematical models such as mean square error (MSE, mean absolute error (MAE, correlation (R, and coefficient of determination (R2. The proposed SOFM model achieved a final MSE of 0.0007 in the training phase and 0.0005 in the cross-validation phase. In contrast, the SVM model resulted in a small MSE value equal to 0.0058, while the MLP model achieved a final MSE of 0.026 with a correlation coefficient of 0.9989, which indicates a strong relationship between input and output variables. The proposed SOFM model closely fits the desired results based on the R2 value, which is equal to 0.9555. Finally, the comparison results of MAE for the three models show that the SOFM model achieved a best result of 0.36156, whereas the SVM and MLP models yielded 4.53761 and 3.63927, respectively. A small MAE value indicates that the output of the SOFM model closely fits the actual results and predicts the desired output.

  12. Report 3: Guidance document on practices to model and implement Extreme Weather hazards in extended PSA

    International Nuclear Information System (INIS)

    Alzbutas, R.; Ostapchuk, S.; Borysiewicz, M.; Decker, K.; Kumar, Manorma; Haeggstroem, A.; Nitoi, M.; Groudev, P.; Parey, S.; Potempski, S.; Raimond, E.; Siklossy, T.

    2016-01-01

    The goal of this report is to provide guidance on practices to model Extreme Weather hazards and implement them in extended level 1 PSA. This report is a joint deliverable of work package 21 (WP21) and work package 22 (WP22). The general objective of WP21 is to provide guidance on all of the individual hazards selected at the End Users Workshop. This guidance is focusing on extreme weather hazards, namely: extreme wind, extreme temperature and snow pack. Other hazards, however, are considered in cases where they are correlated/ associated with the hazard under discussion. Guidance developed refers to existing guidance whenever possible. As it was recommended by end users this guidance covers questions of developing integrated and/or separated extreme weathers PSA models. (authors)

  13. Plausible Effect of Weather on Atlantic Meridional Overturning Circulation with a Coupled General Circulation Model

    Science.gov (United States)

    Liu, Zedong; Wan, Xiuquan

    2018-04-01

    The Atlantic meridional overturning circulation (AMOC) is a vital component of the global ocean circulation and the heat engine of the climate system. Through the use of a coupled general circulation model, this study examines the role of synoptic systems on the AMOC and presents evidence that internally generated high-frequency, synoptic-scale weather variability in the atmosphere could play a significant role in maintaining the overall strength and variability of the AMOC, thereby affecting climate variability and change. Results of a novel coupling technique show that the strength and variability of the AMOC are greatly reduced once the synoptic weather variability is suppressed in the coupled model. The strength and variability of the AMOC are closely linked to deep convection events at high latitudes, which could be strongly affected by the weather variability. Our results imply that synoptic weather systems are important in driving the AMOC and its variability. Thus, interactions between atmospheric weather variability and AMOC may be an important feedback mechanism of the global climate system and need to be taken into consideration in future climate change studies.

  14. Investigation of time and weather effects on crash types using full Bayesian multivariate Poisson lognormal models.

    Science.gov (United States)

    El-Basyouny, Karim; Barua, Sudip; Islam, Md Tazul

    2014-12-01

    Previous research shows that various weather elements have significant effects on crash occurrence and risk; however, little is known about how these elements affect different crash types. Consequently, this study investigates the impact of weather elements and sudden extreme snow or rain weather changes on crash type. Multivariate models were used for seven crash types using five years of daily weather and crash data collected for the entire City of Edmonton. In addition, the yearly trend and random variation of parameters across the years were analyzed by using four different modeling formulations. The proposed models were estimated in a full Bayesian context via Markov Chain Monte Carlo simulation. The multivariate Poisson lognormal model with yearly varying coefficients provided the best fit for the data according to Deviance Information Criteria. Overall, results showed that temperature and snowfall were statistically significant with intuitive signs (crashes decrease with increasing temperature; crashes increase as snowfall intensity increases) for all crash types, while rainfall was mostly insignificant. Previous snow showed mixed results, being statistically significant and positively related to certain crash types, while negatively related or insignificant in other cases. Maximum wind gust speed was found mostly insignificant with a few exceptions that were positively related to crash type. Major snow or rain events following a dry weather condition were highly significant and positively related to three crash types: Follow-Too-Close, Stop-Sign-Violation, and Ran-Off-Road crashes. The day-of-the-week dummy variables were statistically significant, indicating a possible weekly variation in exposure. Transportation authorities might use the above results to improve road safety by providing drivers with information regarding the risk of certain crash types for a particular weather condition. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Integrated modelling of physical, chemical and biological weather

    DEFF Research Database (Denmark)

    Kurganskiy, Alexander

    . This is an online-coupled meteorology-chemistry model where chemical constituents and different types of aerosols are an integrated part of the dynamical model, i.e., these constituents are transported in the same way as, e.g., water vapor and cloud water, and, at the same time, the aerosols can interactively...... impact radiation and cloud micro-physics. The birch pollen modelling study has been performed for domains covering Europe and western Russia. Verification of the simulated birch pollen concentrations against in-situ observations showed good agreement obtaining the best score for two Danish sites...

  16. Evaluation and Application of the Weather Research and Forecast Model

    National Research Council Canada - National Science Library

    Passner, Jeffrey E

    2007-01-01

    ... by the U.S. Army Research Laboratory (ARL) to determine how accurate and robust the model is under a variety of meteorological conditions, with an emphasis on fine resolution, short-range forecasts in complex terrain...

  17. A review of operational, regional-scale, chemical weather forecasting models in Europe

    Czech Academy of Sciences Publication Activity Database

    Kukkonen, J.; Olsson, T.; Schultz, D.M.; Baklanov, A.; Klein, T.; Miranda, A.I.; Monteiro, A.; Hirtl, M.; Tarvainen, V.; Boy, M.; Peuch, V.H.; PoupKou, A.; Kioutsioukis, I.; Finardi, S.; Sofiev, M.; Sokhi, R.; Lehtinen, K.E.J.; Karatzas, K.; San José, R.; Astitha, M.; Kallos, G.; Schaap, M.; Reimer, E.; Jakobs, H.; Eben, Kryštof

    2012-01-01

    Roč. 12, - (2012), s. 1-87 ISSN 1680-7316 Institutional research plan: CEZ:AV0Z10300504 Keywords : chemical weather * numerical models * operational forecasting * air Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 5.510, year: 2012

  18. GLUE Based Uncertainty Estimation of Urban Drainage Modeling Using Weather Radar Precipitation Estimates

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2011-01-01

    Distributed weather radar precipitation measurements are used as rainfall input for an urban drainage model, to simulate the runoff from a small catchment of Denmark. It is demonstrated how the Generalized Likelihood Uncertainty Estimation (GLUE) methodology can be implemented and used to estimate...

  19. Reproducibility of Carbon and Water Cycle by an Ecosystem Process Based Model Using a Weather Generator and Effect of Temporal Concentration of Precipitation on Model Outputs

    Science.gov (United States)

    Miyauchi, T.; Machimura, T.

    2014-12-01

    GCM is generally used to produce input weather data for the simulation of carbon and water cycle by ecosystem process based models under climate change however its temporal resolution is sometimes incompatible to requirement. A weather generator (WG) is used for temporal downscaling of input weather data for models, where the effect of WG algorithms on reproducibility of ecosystem model outputs must be assessed. In this study simulated carbon and water cycle by Biome-BGC model using weather data measured and generated by CLIMGEN weather generator were compared. The measured weather data (daily precipitation, maximum, minimum air temperature) at a few sites for 30 years was collected from NNDC Online weather data. The generated weather data was produced by CLIMGEN parameterized using the measured weather data. NPP, heterotrophic respiration (HR), NEE and water outflow were simulated by Biome-BGC using measured and generated weather data. In the case of deciduous broad leaf forest in Lushi, Henan Province, China, 30 years average monthly NPP by WG was 10% larger than that by measured weather in the growing season. HR by WG was larger than that by measured weather in all months by 15% in average. NEE by WG was more negative in winter and was close to that by measured weather in summer. These differences in carbon cycle were because the soil water content by WG was larger than that by measured weather. The difference between monthly water outflow by WG and by measured weather was large and variable, and annual outflow by WG was 50% of that by measured weather. The inconsistency in carbon and water cycle by WG and measured weather was suggested be affected by the difference in temporal concentration of precipitation, which was assessed.

  20. Creating Weather System Ensembles Through Synergistic Process Modeling and Machine Learning

    Science.gov (United States)

    Chen, B.; Posselt, D. J.; Nguyen, H.; Wu, L.; Su, H.; Braverman, A. J.

    2017-12-01

    Earth's weather and climate are sensitive to a variety of control factors (e.g., initial state, forcing functions, etc). Characterizing the response of the atmosphere to a change in initial conditions or model forcing is critical for weather forecasting (ensemble prediction) and climate change assessment. Input - response relationships can be quantified by generating an ensemble of multiple (100s to 1000s) realistic realizations of weather and climate states. Atmospheric numerical models generate simulated data through discretized numerical approximation of the partial differential equations (PDEs) governing the underlying physics. However, the computational expense of running high resolution atmospheric state models makes generation of more than a few simulations infeasible. Here, we discuss an experiment wherein we approximate the numerical PDE solver within the Weather Research and Forecasting (WRF) Model using neural networks trained on a subset of model run outputs. Once trained, these neural nets can produce large number of realization of weather states from a small number of deterministic simulations with speeds that are orders of magnitude faster than the underlying PDE solver. Our neural network architecture is inspired by the governing partial differential equations. These equations are location-invariant, and consist of first and second derivations. As such, we use a 3x3 lon-lat grid of atmospheric profiles as the predictor in the neural net to provide the network the information necessary to compute the first and second moments. Results indicate that the neural network algorithm can approximate the PDE outputs with high degree of accuracy (less than 1% error), and that this error increases as a function of the prediction time lag.

  1. Preparing Middle School Teachers to Use Science Models Effectively when Teaching about Weather and Climate Topics

    Science.gov (United States)

    Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.

    2012-12-01

    According to the National Science Education Standards (NSES), teachers are encouraged to use science models in the classroom as a way to aid in the understanding of the nature of the scientific process. This is of particular importance to the atmospheric science community because climate and weather models are very important when it comes to understanding current and future behaviors of our atmosphere. Although familiar with weather forecasts on television and the Internet, most people do not understand the process of using computer models to generate weather and climate forecasts. As a result, the public often misunderstands claims scientists make about their daily weather as well as the state of climate change. Therefore, it makes sense that recent research in science education indicates that scientific models and modeling should be a topic covered in K-12 classrooms as part of a comprehensive science curriculum. The purpose of this research study is to describe how three middle school teachers use science models to teach about topics in climate and weather, as well as the challenges they face incorporating models effectively into the classroom. Participants in this study took part in a week long professional development designed to orient them towards appropriate use of science models for a unit on weather, climate, and energy concepts. The course design was based on empirically tested features of effective professional development for science teachers and was aimed at teaching content to the teachers while simultaneously orienting them towards effective use of science models in the classroom in a way that both aids in learning about the content knowledge as well as how models are used in scientific inquiry. Results indicate that teachers perceive models to be physical representations that can be used as evidence to convince students that the teacher's conception of the concept is correct. Additionally, teachers tended to use them as ways to explain an idea to

  2. Waterspout Forecasting Method Over the Eastern Adriatic Using a High-Resolution Numerical Weather Model

    Science.gov (United States)

    Renko, Tanja; Ivušić, Sarah; Telišman Prtenjak, Maja; Šoljan, Vinko; Horvat, Igor

    2018-03-01

    In this study, a synoptic and mesoscale analysis was performed and Szilagyi's waterspout forecasting method was tested on ten waterspout events in the period of 2013-2016. Data regarding waterspout occurrences were collected from weather stations, an online survey at the official website of the National Meteorological and Hydrological Service of Croatia and eyewitness reports from newspapers and the internet. Synoptic weather conditions were analyzed using surface pressure fields, 500 hPa level synoptic charts, SYNOP reports and atmospheric soundings. For all observed waterspout events, a synoptic type was determined using the 500 hPa geopotential height chart. The occurrence of lightning activity was determined from the LINET lightning database, and waterspouts were divided into thunderstorm-related and "fair weather" ones. Mesoscale characteristics (with a focus on thermodynamic instability indices) were determined using the high-resolution (500 m grid length) mesoscale numerical weather model and model results were compared with the available observations. Because thermodynamic instability indices are usually insufficient for forecasting waterspout activity, the performance of the Szilagyi Waterspout Index (SWI) was tested using vertical atmospheric profiles provided by the mesoscale numerical model. The SWI successfully forecasted all waterspout events, even the winter events. This indicates that the Szilagyi's waterspout prognostic method could be used as a valid prognostic tool for the eastern Adriatic.

  3. Mapping Nuclear Fallout Using the Weather Research & Forecasting (WRF) Model

    Science.gov (United States)

    2012-09-01

    Meterological Magazine, 47, pp. 295-308, 1998. [17] Air Resources Laboratory. (2012, April) Air Resources Laboratory. [Online]. http://www.arl.noaa.gov...Reanalysis Project," Bulletin of the American Meterological Society, pp. 437-471, 1996. [25] Steve Warner, Nathan Platt, and James F. Heagy, "User...Oriented Two-Dimensional Measure of Effectiveness for the Evaluation of Transport and Dispersion Models," Journal of Applied Meterology Vol. 43, pp. 58

  4. Weathering model for the quantification of atmospheric oxygen evolution during the Paleoproterozoic

    Science.gov (United States)

    Yokota, Kohei; Kanzaki, Yoshiki; Murakami, Takashi

    2013-09-01

    A weathering model has been developed to quantify atmospheric oxygen evolution during the Paleoproterozoic. The weathering model calculates the concentrations of Fe2+ dissolved from Fe2+-bearing primary minerals and oxidized Fe3+ out of the dissolved Fe2+ at a given partial pressure of atmospheric oxygen (PO2) during weathering and establishes the relationships between PO2 and ϕ, where ϕ is the ratio of oxidized and then precipitated Fe3+ out of the Fe2+ dissolved from primary minerals to the dissolved Fe2+ in a whole weathering profile. The weathering model considers controlling factors of the redistribution of Fe during weathering, that is, the dissolution rate of Fe2+-bearing primary minerals, the oxidation rate of Fe2+, and the groundwater flow rate. The validity of the model was confirmed by applying the model to the experimental data of olivine dissolution carried out under low O2 conditions. The sensitivity analysis of the model has revealed that the formation time of weathering, the mineral dissolution rate and the diffusion of O2 into a weathering profile have no or slight influence on ϕ, resulting in ˜0, 0 and 0.3 changes in log(PO2) caused by four orders of magnitude change of the formation time, more than 10 orders change of the mineral dissolution rate, and assumed change of the O2 diffusion, respectively. On the other hand, the temperature, the pH and the groundwater flow rate have moderate to large effects on ϕ: 0.6, 1.4 and 1.5 changes in log(PO2) for changes of 5 °C in temperature, 0.5 in pH, and one order of magnitude in groundwater flow rate, respectively. Using possible surface temperature, pH and groundwater flow rate estimated from the literature, we calculated the ϕ-PO2 relationships which were then applied to the ϕ values of paleosols (fossil weathering profiles) formed between 2.5 and 1.8 Ga. Taking account of the constraints given by the records of mass independent fractionation in sulfur isotopes and other geological proxies (i

  5. CrowdSourced weather reports: An implementation of the µ model for spotting weather information in Twitter

    CSIR Research Space (South Africa)

    Butgereit, L

    2014-05-01

    Full Text Available Twitter is a microblogging facility that allows people to post 140 character status updates about various topics. In times of special events (such as extreme weather, emergencies, sporting goals, etc), status updates on Twitter often give people a...

  6. Review and Extension of Suitability Assessment Indicators of Weather Model Output for Analyzing Decentralized Energy Systems

    Directory of Open Access Journals (Sweden)

    Hans Schermeyer

    2015-12-01

    Full Text Available Electricity from renewable energy sources (RES-E is gaining more and more influence in traditional energy and electricity markets in Europe and around the world. When modeling RES-E feed-in on a high temporal and spatial resolution, energy systems analysts frequently use data generated by numerical weather models as input since there is no spatial inclusive and comprehensive measurement data available. However, the suitability of such model data depends on the research questions at hand and should be inspected individually. This paper focuses on new methodologies to carry out a performance evaluation of solar irradiation data provided by a numerical weather model when investigating photovoltaic feed-in and effects on the electricity grid. Suitable approaches of time series analysis are researched from literature and applied to both model and measurement data. The findings and limits of these approaches are illustrated and a new set of validation indicators is presented. These novel indicators complement the assessment by measuring relevant key figures in energy systems analysis: e.g., gradients in energy supply, maximum values and volatility. Thus, the results of this paper contribute to the scientific community of energy systems analysts and researchers who aim at modeling RES-E feed-in on a high temporal and spatial resolution using weather model data.

  7. A statistical model to estimate the local vulnerability to severe weather

    Science.gov (United States)

    Pardowitz, Tobias

    2018-06-01

    We present a spatial analysis of weather-related fire brigade operations in Berlin. By comparing operation occurrences to insured losses for a set of severe weather events we demonstrate the representativeness and usefulness of such data in the analysis of weather impacts on local scales. We investigate factors influencing the local rate of operation occurrence. While depending on multiple factors - which are often not available - we focus on publicly available quantities. These include topographic features, land use information based on satellite data and information on urban structure based on data from the OpenStreetMap project. After identifying suitable predictors such as housing coverage or local density of the road network we set up a statistical model to be able to predict the average occurrence frequency of local fire brigade operations. Such model can be used to determine potential hotspots for weather impacts even in areas or cities where no systematic records are available and can thus serve as a basis for a broad range of tools or applications in emergency management and planning.

  8. Noodles: a tool for visualization of numerical weather model ensemble uncertainty.

    Science.gov (United States)

    Sanyal, Jibonananda; Zhang, Song; Dyer, Jamie; Mercer, Andrew; Amburn, Philip; Moorhead, Robert J

    2010-01-01

    Numerical weather prediction ensembles are routinely used for operational weather forecasting. The members of these ensembles are individual simulations with either slightly perturbed initial conditions or different model parameterizations, or occasionally both. Multi-member ensemble output is usually large, multivariate, and challenging to interpret interactively. Forecast meteorologists are interested in understanding the uncertainties associated with numerical weather prediction; specifically variability between the ensemble members. Currently, visualization of ensemble members is mostly accomplished through spaghetti plots of a single mid-troposphere pressure surface height contour. In order to explore new uncertainty visualization methods, the Weather Research and Forecasting (WRF) model was used to create a 48-hour, 18 member parameterization ensemble of the 13 March 1993 "Superstorm". A tool was designed to interactively explore the ensemble uncertainty of three important weather variables: water-vapor mixing ratio, perturbation potential temperature, and perturbation pressure. Uncertainty was quantified using individual ensemble member standard deviation, inter-quartile range, and the width of the 95% confidence interval. Bootstrapping was employed to overcome the dependence on normality in the uncertainty metrics. A coordinated view of ribbon and glyph-based uncertainty visualization, spaghetti plots, iso-pressure colormaps, and data transect plots was provided to two meteorologists for expert evaluation. They found it useful in assessing uncertainty in the data, especially in finding outliers in the ensemble run and therefore avoiding the WRF parameterizations that lead to these outliers. Additionally, the meteorologists could identify spatial regions where the uncertainty was significantly high, allowing for identification of poorly simulated storm environments and physical interpretation of these model issues.

  9. Implementation of an atmospheric sulfur scheme in the HIRLAM regional weather forecast model

    Energy Technology Data Exchange (ETDEWEB)

    Ekman, Annica [Stockholm Univ. (Sweden). Dept. of Meteorology

    2000-02-01

    Sulfur chemistry has been implemented into the regional weather forecast model HIRLAM in order to simulate sulfur fields during specific weather situations. The model calculates concentrations of sulfur dioxide in air (SO{sub 2}(a)), sulfate in air (SO{sub 4}(a)), sulfate in cloud water (SO{sub 4}(aq)) and hydrogen peroxide (H{sub 2}O{sub 2}). Modeled concentrations of SO{sub 2}(a), SO{sub 4}(a) and SO{sub 4}(aq) in rain water are compared with observations for two weather situations, one winter case with an extensive stratiform cloud cover and one summer case with mostly convective clouds. A comparison of the weather forecast parameters precipitation, relative humidity, geopotential and temperature with observations is also performed. The results show that the model generally overpredicts the SO{sub 2}(a) concentration and underpredicts the SO{sub 4}(a) concentration. The agreement between modeled and observed SO{sub 4}(aq) in rain water is poor. Calculated turnover times are approximately 1 day for SO{sub 2}(a) and 2-2.5 days for SO{sub 4}(a). For SO{sub 2}(a) this is in accordance with earlier simulated global turnover times, but for SO{sub 4}(a) it is substantially lower. Several sensitivity simulations show that the fractional mean bias and root mean square error decreases, mainly for SO{sub 4}(a) and SO{sub 4}(aq), if an additional oxidant for converting SO{sub 2}(a) to SO{sub 4}(a) is included in the model. All weather forecast parameters, except precipitation, agree better with observations than the sulfur variables do. Wet scavenging is responsible for about half of the deposited sulfur and in addition, a major part of the sulfate production occurs through in-cloud oxidation. Hence, the distribution of clouds and precipitation must be better simulated by the weather forecast model in order to improve the agreement between observed and simulated sulfur concentrations.

  10. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  11. The NASA Community Coordinated Modeling Center (CCMC) Next Generation Space Weather Data Warehouse

    Science.gov (United States)

    Maddox, M. M.; Kuznetsova, M. M.; Pulkkinen, A. A.; Zheng, Y.; Rastaetter, L.; Chulaki, A.; Pembroke, A. D.; Wiegand, C.; Mullinix, R.; Boblitt, J.; Mendoza, A. M. M.; Swindell, M. J., IV; Bakshi, S. S.; Mays, M. L.; Shim, J. S.; Hesse, M.; Collado-Vega, Y. M.; Taktakishvili, A.; MacNeice, P. J.

    2014-12-01

    The Community Coordinated Modeling Center (CCMC) at NASA Goddard Space Flight Center enables, supports, and performs research and development for next generation space science and space weather models. The CCMC currently hosts a large and expanding collection of state-or-the-art, physics-based space weather models that have been developed by the international research community. There are many tools and services provided by the CCMC that are currently available world-wide, along with the ongoing development of new innovative systems and software for research, discovery, validation, visualization, and forecasting. Over the history of the CCMC's existence, there has been one constant engineering challenge - describing, managing, and disseminating data. To address the challenges that accompany an ever-expanding number of models to support, along with a growing catalog of simulation output - the CCMC is currently developing a flexible and extensible space weather data warehouse to support both internal and external systems and applications. This paper intends to chronicle the evolution and future of the CCMC's data infrastructure, and the current infrastructure re-engineering activities that seek to leverage existing community data model standards like SPASE and the IMPEx Simulation Data Model.

  12. How reliable is the offline linkage of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model?

    Science.gov (United States)

    The aim for this research is to evaluate the ability of the offline linkage of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model to produce hydrological, e.g. evaporation (ET), soil moisture (SM), runoff, and baseflow. First, the VIC mo...

  13. Susceptibility of Bemisia tabaci MEAM1 (Hemiptera: Aleyrodidae to Imidacloprid, Thiamethoxam, Dinotefuran and Flupyradifurone in South Florida

    Directory of Open Access Journals (Sweden)

    Hugh A. Smith

    2016-10-01

    Full Text Available Populations of Bemisa tabaci MEAM1 were established from nineteen locations in south Florida, primarily from commercial tomato fields, and were tested using a cotton leaf petiole systemic uptake method for susceptibility to the nicotinic acetylcholine agonist insecticides imidacloprid, thiamethoxam, dinotefuran and flupyradifurone. Eleven populations produced LC50s for one or more chemicals that were not significantly different from the susceptible laboratory colony based on overlapping fiducial limits, indicating some degree of susceptibility. LC50s more than a 100-fold the laboratory colony were measured in at least one population for each material tested, indicating tolerance. LC50s (ppm from field populations ranged from 0.901–24.952 for imidacloprid, 0.965–24.430 for thiamethoxam, 0.043–3.350 for dinotefuran and 0.011–1.471 for flupyradifurone. Based on overlapping fiducial limits, there were no significant differences in relative mean potency estimates for flupyradifurone and dinotefuran in relation to imidacloprid and thiamethoxam.

  14. Atomic interaction of the MEAM type for the study of intermetallics in the Al–U alloy

    Energy Technology Data Exchange (ETDEWEB)

    Pascuet, M.I. [CONICET, Avda. Rivadavia 1917, 1033 Buenos Aires (Argentina); Fernández, J.R., E-mail: julrfern@cnea.gov.ar [CONICET, Avda. Rivadavia 1917, 1033 Buenos Aires (Argentina); CAC-CNEA, Avda. Gral Paz 1499, 1650 Buenos Aires (Argentina); UNSAM, Avda. Gral Paz 1499, 1650 Buenos Aires (Argentina)

    2015-12-15

    Interaction for both pure Al and Al–U alloys of the MEAM type are developed. The obtained Al interatomic potential assures its compatibility with the details of the framework presently adopted. The Al–U interaction fits various properties of the Al{sub 2}U, Al{sub 3}U and Al{sub 4}U intermetallics. The potential verifies the stability of the intermetallic structures in a temperature range compatible with that observed in the phase diagram, and also takes into account the greater stability of these structures relative to others that are competitive in energy. The intermetallics are characterized by calculating elastic and thermal properties and point defect parameters. Molecular dynamics simulations show a growth of the Al{sub 3}U intermetallic in the Al/U interface in agreement with experimental evidence. - Highlights: • Potential parameters for Al and Al–U systems are obtained. • Intermetallics are characterized by calculating elastic and thermal properties. • Point defect diffusivities are calculated for the three intermetallics. • Growth of the Al{sub 3}U intermetallic is shown to occur in the Al/U interface as in the real alloy.

  15. Atomic interaction of the MEAM type for the study of intermetallics in the Al–U alloy

    International Nuclear Information System (INIS)

    Pascuet, M.I.; Fernández, J.R.

    2015-01-01

    Interaction for both pure Al and Al–U alloys of the MEAM type are developed. The obtained Al interatomic potential assures its compatibility with the details of the framework presently adopted. The Al–U interaction fits various properties of the Al_2U, Al_3U and Al_4U intermetallics. The potential verifies the stability of the intermetallic structures in a temperature range compatible with that observed in the phase diagram, and also takes into account the greater stability of these structures relative to others that are competitive in energy. The intermetallics are characterized by calculating elastic and thermal properties and point defect parameters. Molecular dynamics simulations show a growth of the Al_3U intermetallic in the Al/U interface in agreement with experimental evidence. - Highlights: • Potential parameters for Al and Al–U systems are obtained. • Intermetallics are characterized by calculating elastic and thermal properties. • Point defect diffusivities are calculated for the three intermetallics. • Growth of the Al_3U intermetallic is shown to occur in the Al/U interface as in the real alloy.

  16. 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.

  17. Coding a Weather Model: DOE-FIU Science & Technology Workforce Development Program.

    Energy Technology Data Exchange (ETDEWEB)

    Bradley, Jon David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-12-01

    DOE Fellow, Andres Cremisini, completed a 10-week internship with Sandia National Laboratories (SNL) in Albuquerque, New Mexico. Under the management of Kristopher Klingler and the mentorship of Jon Bradley, he was tasked with conceiving and coding a realistic weather model for use in physical security applications. The objective was to make a weather model that could use real data to accurately predict wind and precipitation conditions at any location of interest on the globe at any user-determined time. The intern received guidance on software design, the C++ programming language and clear communication of project goals and ongoing progress. In addition, Mr. Cremisini was given license to structure the program however he best saw fit, an experience that will benefit ongoing research endeavors.

  18. Processing of 3D Weather Radar Data with Application for Assimilation in the NWP Model

    Directory of Open Access Journals (Sweden)

    Ośródka Katarzyna

    2014-09-01

    Full Text Available The paper is focused on the processing of 3D weather radar data to minimize the impact of a number of errors from different sources, both meteorological and non-meteorological. The data is also quantitatively characterized in terms of its quality. A set of dedicated algorithms based on analysis of the reflectivity field pattern is described. All the developed algorithms were tested on data from the Polish radar network POLRAD. Quality control plays a key role in avoiding the introduction of incorrect information into applications using radar data. One of the quality control methods is radar data assimilation in numerical weather prediction models to estimate initial conditions of the atmosphere. The study shows an experiment with quality controlled radar data assimilation in the COAMPS model using the ensemble Kalman filter technique. The analysis proved the potential of radar data for such applications; however, further investigations will be indispensable.

  19. Characteristic 'fingerprints' of crop model responses data at different spatial resolutions to weather input

    Czech Academy of Sciences Publication Activity Database

    Angulo, C.; Rotter, R.; Trnka, Miroslav; Pirttioja, N. K.; Gaiser, T.; Hlavinka, Petr; Ewert, F.

    2013-01-01

    Roč. 49, AUG 2013 (2013), s. 104-114 ISSN 1161-0301 R&D Projects: GA MŠk(CZ) EE2.3.20.0248; GA MŠk(CZ) EE2.4.31.0056 Institutional support: RVO:67179843 Keywords : Crop model * Weather data resolution * Aggregation * Yield distribution Subject RIV: EH - Ecology, Behaviour Impact factor: 2.918, year: 2013

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

    Science.gov (United States)

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

    2017-11-01

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

  1. Introducing a rainfall compound distribution model based on weather patterns sub-sampling

    Directory of Open Access Journals (Sweden)

    F. Garavaglia

    2010-06-01

    Full Text Available This paper presents a probabilistic model for daily rainfall, using sub-sampling based on meteorological circulation. We classified eight typical but contrasted synoptic situations (weather patterns for France and surrounding areas, using a "bottom-up" approach, i.e. from the shape of the rain field to the synoptic situations described by geopotential fields. These weather patterns (WP provide a discriminating variable that is consistent with French climatology, and allows seasonal rainfall records to be split into more homogeneous sub-samples, in term of meteorological genesis.

    First results show how the combination of seasonal and WP sub-sampling strongly influences the identification of the asymptotic behaviour of rainfall probabilistic models. Furthermore, with this level of stratification, an asymptotic exponential behaviour of each sub-sample appears as a reasonable hypothesis. This first part is illustrated with two daily rainfall records from SE of France.

    The distribution of the multi-exponential weather patterns (MEWP is then defined as the composition, for a given season, of all WP sub-sample marginal distributions, weighted by the relative frequency of occurrence of each WP. This model is finally compared to Exponential and Generalized Pareto distributions, showing good features in terms of robustness and accuracy. These final statistical results are computed from a wide dataset of 478 rainfall chronicles spread on the southern half of France. All these data cover the 1953–2005 period.

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

    Science.gov (United States)

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

    2009-12-01

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

  3. Comparison of Microclimate Simulated weather data to ASHRAE Clear Sky Model and Measured Data

    Energy Technology Data Exchange (ETDEWEB)

    Bhandari, Mahabir S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-06-01

    In anticipation of emerging global urbanization and its impact on microclimate, a need exists to better understand and quantify microclimate effects on building energy use. Satisfaction of this need will require coordinated research of microclimate impacts on and from “human systems.” The Urban Microclimate and Energy Tool (Urban-MET) project seeks to address this need by quantifying and analyzing the relationships among climatic conditions, urban morphology, land cover, and energy use; and using these relationships to inform energy-efficient urban development and planning. Initial research will focus on analysis of measured and modeled energy efficiency of various building types in selected urban areas and temporal variations in energy use for different urban morphologies under different microclimatic conditions. In this report, we analyze the differences between microclimate weather data sets for the Oak Ridge National Laboratory campus produced by ENVI-met and Weather Research Forecast (WRF) models, the ASHRAE clear sky which defines the maximum amounts of solar radiation that can be expected, and measured data from a weather station on campus. Errors with climate variables and their impact on building energy consumption will be shown for the microclimate simulations to help prioritize future improvement for use in microclimate simulation impacts to energy use of buildings.

  4. Using Science Data and Models for Space Weather Forecasting - Challenges and Opportunities

    Science.gov (United States)

    Hesse, Michael; Pulkkinen, Antti; Zheng, Yihua; Maddox, Marlo; Berrios, David; Taktakishvili, Sandro; Kuznetsova, Masha; Chulaki, Anna; Lee, Hyesook; Mullinix, Rick; hide

    2012-01-01

    Space research, and, consequently, space weather forecasting are immature disciplines. Scientific knowledge is accumulated frequently, which changes our understanding or how solar eruptions occur, and of how they impact targets near or on the Earth, or targets throughout the heliosphere. Along with continuous progress in understanding, space research and forecasting models are advancing rapidly in capability, often providing substantially increases in space weather value over time scales of less than a year. Furthermore, the majority of space environment information available today is, particularly in the solar and heliospheric domains, derived from research missions. An optimal forecasting environment needs to be flexible enough to benefit from this rapid development, and flexible enough to adapt to evolving data sources, many of which may also stem from non-US entities. This presentation will analyze the experiences obtained by developing and operating both a forecasting service for NASA, and an experimental forecasting system for Geomagnetically Induced Currents.

  5. Numerical weather prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

    International Nuclear Information System (INIS)

    Voyant, Cyril; Muselli, Marc; Paoli, Christophe; Nivet, Marie-Laure

    2012-01-01

    We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (NWP). We particularly look at the multi-layer perceptron (MLP). After optimizing our architecture with NWP and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ARMA model from a rule based on the analysis of hourly data series. This model has been used to forecast the hourly global radiation for five places in Mediterranean area. Our technique outperforms classical models for all the places. The nRMSE for our hybrid model MLP/ARMA is 14.9% compared to 26.2% for the naïve persistence predictor. Note that in the standalone ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of the forecaster outputs, a complementary study concerning the confidence interval of each prediction is proposed. -- Highlights: ► Time series forecasting with hybrid method based on the use of ALADIN numerical weather model, ANN and ARMA. ► Innovative pre-input layer selection method. ► Combination of optimized MLP and ARMA model obtained from a rule based on the analysis of hourly data series. ► Stationarity process (method and control) for the global radiation time series.

  6. Modeling the Warming Impact of Urban Land Expansion on Hot Weather Using the Weather Research and Forecasting Model: A Case Study of Beijing, China

    Science.gov (United States)

    Liu, Xiaojuan; Tian, Guangjin; Feng, Jinming; Ma, Bingran; Wang, Jun; Kong, Lingqiang

    2018-06-01

    The impacts of three periods of urban land expansion during 1990-2010 on near-surface air temperature in summer in Beijing were simulated in this study, and then the interrelation between heat waves and urban warming was assessed. We ran the sensitivity tests using the mesoscaleWeather Research and Forecasting model coupled with a single urban canopy model, as well as high-resolution land cover data. The warming area expanded approximately at the same scale as the urban land expansion. The average regional warming induced by urban expansion increased but the warming speed declined slightly during 2000-2010. The smallest warming occurred at noon and then increased gradually in the afternoon before peaking at around 2000 LST—the time of sunset. In the daytime, urban warming was primarily caused by the decrease in latent heat flux at the urban surface. Urbanization led to more ground heat flux during the day and then more release at night, which resulted in nocturnal warming. Urban warming at night was higher than that in the day, although the nighttime increment in sensible heat flux was smaller. This was because the shallower planetary boundary layer at night reduced the release efficiency of near-surface heat. The simulated results also suggested that heat waves or high temperature weather enhanced urban warming intensity at night. Heat waves caused more heat to be stored in the surface during the day, greater heat released at night, and thus higher nighttime warming. Our results demonstrate a positive feedback effect between urban warming and heat waves in urban areas.

  7. Software for Generating Troposphere Corrections for InSAR Using GPS and Weather Model Data

    Science.gov (United States)

    Moore, Angelyn W.; Webb, Frank H.; Fishbein, Evan F.; Fielding, Eric J.; Owen, Susan E.; Granger, Stephanie L.; Bjoerndahl, Fredrik; Loefgren, Johan; Fang, Peng; Means, James D.; hide

    2013-01-01

    Atmospheric errors due to the troposphere are a limiting error source for spaceborne interferometric synthetic aperture radar (InSAR) imaging. This software generates tropospheric delay maps that can be used to correct atmospheric artifacts in InSAR data. The software automatically acquires all needed GPS (Global Positioning System), weather, and Digital Elevation Map data, and generates a tropospheric correction map using a novel algorithm for combining GPS and weather information while accounting for terrain. Existing JPL software was prototypical in nature, required a MATLAB license, required additional steps to acquire and ingest needed GPS and weather data, and did not account for topography in interpolation. Previous software did not achieve a level of automation suitable for integration in a Web portal. This software overcomes these issues. GPS estimates of tropospheric delay are a source of corrections that can be used to form correction maps to be applied to InSAR data, but the spacing of GPS stations is insufficient to remove short-wavelength tropospheric artifacts. This software combines interpolated GPS delay with weather model precipitable water vapor (PWV) and a digital elevation model to account for terrain, increasing the spatial resolution of the tropospheric correction maps and thus removing short wavelength tropospheric artifacts to a greater extent. It will be integrated into a Web portal request system, allowing use in a future L-band SAR Earth radar mission data system. This will be a significant contribution to its technology readiness, building on existing investments in in situ space geodetic networks, and improving timeliness, quality, and science value of the collected data

  8. Relative performance of different numerical weather prediction models for short term predition of wind wnergy

    Energy Technology Data Exchange (ETDEWEB)

    Giebel, G; Landberg, L [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark); Moennich, K; Waldl, H P [Carl con Ossietzky Univ., Faculty of Physics, Dept. of Energy and Semiconductor, Oldenburg (Germany)

    1999-03-01

    In several approaches presented in other papers in this conference, short term forecasting of wind power for a time horizon covering the next two days is done on the basis of Numerical Weather Prediction (NWP) models. This paper explores the relative merits of HIRLAM, which is the model used by the Danish Meteorological Institute, the Deutschlandmodell from the German Weather Service and the Nested Grid Model used in the US. The performance comparison will be mainly done for a site in Germany which is in the forecasting area of both the Deutschlandmodell and HIRLAM. In addition, a comparison of measured data with the forecasts made for one site in Iowa will be included, which allows conclusions on the merits of all three models. Differences in the relative performances could be due to a better tailoring of one model to its country, or to a tighter grid, or could be a function of the distance between the grid points and the measuring site. Also the amount, in which the performance can be enhanced by the use of model output statistics (topic of other papers in this conference) could give insights into the performance of the models. (au)

  9. Weathering model in paleomagnetic field intensity measurements on ancient fired clays

    International Nuclear Information System (INIS)

    Singalas, I.; Gangas, N-H.J.; Danon, J.

    1978-03-01

    Nonlinearities observed in Thellier's plots are explained in terms of a weathering model. This model is based on the reduction in size of the originaly present iron oxide particles, due to leaching. In the general case, the slope of the Thellier's plot is a function of the particle size destributions of the magnetic particles, both newly formed and leached ones. In the special case in which the newly formed magnetic particles are superparamagnetic, the limiting value of the slope of th Thellier's plot towards the magnetic ordering temperature is equal to the ratio of the ancient field intensity to the modern one

  10. Evaluating Weather Research and Forecasting Model Sensitivity to Land and Soil Conditions Representative of Karst Landscapes

    Science.gov (United States)

    Johnson, Christopher M.; Fan, Xingang; Mahmood, Rezaul; Groves, Chris; Polk, Jason S.; Yan, Jun

    2018-03-01

    Due to their particular physiographic, geomorphic, soil cover, and complex surface-subsurface hydrologic conditions, karst regions produce distinct land-atmosphere interactions. It has been found that floods and droughts over karst regions can be more pronounced than those in non-karst regions following a given rainfall event. Five convective weather events are simulated using the Weather Research and Forecasting model to explore the potential impacts of land-surface conditions on weather simulations over karst regions. Since no existing weather or climate model has the ability to represent karst landscapes, simulation experiments in this exploratory study consist of a control (default land-cover/soil types) and three land-surface conditions, including barren ground, forest, and sandy soils over the karst areas, which mimic certain karst characteristics. Results from sensitivity experiments are compared with the control simulation, as well as with the National Centers for Environmental Prediction multi-sensor precipitation analysis Stage-IV data, and near-surface atmospheric observations. Mesoscale features of surface energy partition, surface water and energy exchange, the resulting surface-air temperature and humidity, and low-level instability and convective energy are analyzed to investigate the potential land-surface impact on weather over karst regions. We conclude that: (1) barren ground used over karst regions has a pronounced effect on the overall simulation of precipitation. Barren ground provides the overall lowest root-mean-square errors and bias scores in precipitation over the peak-rain periods. Contingency table-based equitable threat and frequency bias scores suggest that the barren and forest experiments are more successful in simulating light to moderate rainfall. Variables dependent on local surface conditions show stronger contrasts between karst and non-karst regions than variables dominated by large-scale synoptic systems; (2) significant

  11. Asteroid age distributions determined by space weathering and collisional evolution models

    Science.gov (United States)

    Willman, Mark; Jedicke, Robert

    2011-01-01

    We provide evidence of consistency between the dynamical evolution of main belt asteroids and their color evolution due to space weathering. The dynamical age of an asteroid's surface (Bottke, W.F., Durda, D.D., Nesvorný, D., Jedicke, R., Morbidelli, A., Vokrouhlický, D., Levison, H. [2005]. Icarus 175 (1), 111-140; Nesvorný, D., Jedicke, R., Whiteley, R.J., Ivezić, Ž. [2005]. Icarus 173, 132-152) is the time since its last catastrophic disruption event which is a function of the object's diameter. The age of an S-complex asteroid's surface may also be determined from its color using a space weathering model (e.g. Willman, M., Jedicke, R., Moskovitz, N., Nesvorný, D., Vokrouhlický, D., Mothé-Diniz, T. [2010]. Icarus 208, 758-772; Jedicke, R., Nesvorný, D., Whiteley, R.J., Ivezić, Ž., Jurić, M. [2004]. Nature 429, 275-277; Willman, M., Jedicke, R., Nesvorny, D., Moskovitz, N., Ivezić, Ž., Fevig, R. [2008]. Icarus 195, 663-673. We used a sample of 95 S-complex asteroids from SMASS and obtained their absolute magnitudes and u, g, r, i, z filter magnitudes from SDSS. The absolute magnitudes yield a size-derived age distribution. The u, g, r, i, z filter magnitudes lead to the principal component color which yields a color-derived age distribution by inverting our color-age relationship, an enhanced version of the 'dual τ' space weathering model of Willman et al. (2010). We fit the size-age distribution to the enhanced dual τ model and found characteristic weathering and gardening times of τw = 2050 ± 80 Myr and τg=4400-500+700Myr respectively. The fit also suggests an initial principal component color of -0.05 ± 0.01 for fresh asteroid surface with a maximum possible change of the probable color due to weathering of Δ PC = 1.34 ± 0.04. Our predicted color of fresh asteroid surface matches the color of fresh ordinary chondritic surface of PC1 = 0.17 ± 0.39.

  12. Configuring the HYSPLIT Model for National Weather Service Forecast Office and Spaceflight Meteorology Group Applications

    Science.gov (United States)

    Dreher, Joseph G.

    2009-01-01

    For expedience in delivering dispersion guidance in the diversity of operational situations, National Weather Service Melbourne (MLB) and Spaceflight Meteorology Group (SMG) are becoming increasingly reliant on the PC-based version of the HYSPLIT model run through a graphical user interface (GUI). While the GUI offers unique advantages when compared to traditional methods, it is difficult for forecasters to run and manage in an operational environment. To alleviate the difficulty in providing scheduled real-time trajectory and concentration guidance, the Applied Meteorology Unit (AMU) configured a Linux version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) (HYSPLIT) model that ingests the National Centers for Environmental Prediction (NCEP) guidance, such as the North American Mesoscale (NAM) and the Rapid Update Cycle (RUC) models. The AMU configured the HYSPLIT system to automatically download the NCEP model products, convert the meteorological grids into HYSPLIT binary format, run the model from several pre-selected latitude/longitude sites, and post-process the data to create output graphics. In addition, the AMU configured several software programs to convert local Weather Research and Forecast (WRF) model output into HYSPLIT format.

  13. Coupled Weather and Wildfire Behavior Modeling at Los Alamos: An Overview

    Energy Technology Data Exchange (ETDEWEB)

    Bossert, James E.; Harlow, Francis H.; Linn, Rodman R.; Reisner, Jon M.; White, Andrew B.; Winterkamp, Judith L.

    1997-12-31

    Over the past two years, researchers at Los Alamos National Laboratory (LANL) have been engaged in coupled weather/wildfire modeling as part of a broader initiative to predict the unfolding of crisis events. Wildfire prediction was chosen for the following reasons: (1) few physics-based wild-fire prediction models presently exist; (2) LANL has expertise in the fields required to develop such a capability; and (3) the development of this predictive capability would be enhanced by LANL`s strength in high performance computing. Wildfire behavior models have historically been used to predict fire spread and heat release for a prescribed set of fuel, slope, and wind conditions (Andrews 1986). In the vicinity of a fire, however, atmospheric conditions are constantly changing due to non-local weather influences and the intense heat of the fire itself. This non- linear process underscores the need for physics-based models that treat the atmosphere-fire feedback. Actual wildfire prediction with full-physics models is both time-critical and computationally demanding, since it must include regional- to local-scale weather forecasting together with the capability to accurately simulate both intense gradients across a fireline, and atmosphere/fire/fuel interactions. Los Alamos has recently (January 1997) acquired a number of SGI/Cray Origin 2000 machines, each presently having 32 to 64 processors. These high performance computing systems are part of the Department of Energy`s Accelerated Strategic Computing Initiative (ASCI). While offering impressive performance now, upgrades to the system promise to deliver over 1 Teraflop (10(12) floating point operations per second) at peak performance before the turn of the century.

  14. Modelling weather effects for impact analysis of residential time-of-use electricity pricing

    International Nuclear Information System (INIS)

    Miller, Reid; Golab, Lukasz; Rosenberg, Catherine

    2017-01-01

    Analyzing the impact of pricing policies such as time-of-use (TOU) is challenging in the presence of confounding factors such as weather. Motivated by a lack of consensus and model selection details in prior work, we present a methodology for modelling the effect of weather on residential electricity demand. The best model is selected according to explanatory power, out-of-sample prediction accuracy, goodness of fit and interpretability. We then evaluate the effect of mandatory TOU pricing in a local distribution company in southwestern Ontario, Canada. We use a smart meter dataset of over 20,000 households which is particularly suited to our analysis: it contains data from the summer before and after the implementation of TOU pricing in November 2011, and all customers transitioned from tiered rates to TOU rates at the same time. We find that during the summer rate season, TOU pricing results in electricity conservation across all price periods. The average demand change during on-peak and mid-peak periods is −2.6% and −2.4% respectively. Changes during off-peak periods are not statistically significant. These TOU pricing effects are less pronounced compared to previous studies, underscoring the need for clear, reproducible impact analyses which include full details about the model selection process. - Highlights: • We study models for the effect of weather on residential electricity demand. • We evaluate the effect of mandatory TOU pricing in a local distribution company in Ontario, Canada. • We find the effect of TOU pricing to be less pronounced compared to previous studies.

  15. Numerical Weather Prediction Models on Linux Boxes as tools in meteorological education in Hungary

    Science.gov (United States)

    Gyongyosi, A. Z.; Andre, K.; Salavec, P.; Horanyi, A.; Szepszo, G.; Mille, M.; Tasnadi, P.; Weidiger, T.

    2012-04-01

    Education of Meteorologist in Hungary - according to the Bologna Process - has three stages: BSc, MSc and PhD, and students graduating at each stage get the respective degree (BSc, MSc and PhD). The three year long base BSc course in Meteorology can be chosen by undergraduate students in the fields of Geosciences, Environmental Sciences and Physics. BasicsFundamentals in Mathematics (Calculus), Physics (General and Theoretical) Physics and Informatics are emphasized during their elementary education. The two year long MSc course - in which about 15 to 25 students are admitted each year - can be studied only at our the Eötvös Loránd uUniversity in the our country. Our aim is to give a basic education in all fields of Meteorology. Main topics are: Climatology, Atmospheric Physics, Atmospheric Chemistry, Dynamic and Synoptic Meteorology, Numerical Weather Prediction, modeling Modeling of surfaceSurface-atmosphere Iinteractions and Cclimate change. Education is performed in two branches: Climate Researcher and Forecaster. Education of Meteorologist in Hungary - according to the Bologna Process - has three stages: BSc, MSc and PhD, and students graduating at each stage get the respective degree. The three year long BSc course in Meteorology can be chosen by undergraduate students in the fields of Geosciences, Environmental Sciences and Physics. Fundamentals in Mathematics (Calculus), (General and Theoretical) Physics and Informatics are emphasized during their elementary education. The two year long MSc course - in which about 15 to 25 students are admitted each year - can be studied only at the Eötvös Loránd University in our country. Our aim is to give a basic education in all fields of Meteorology: Climatology, Atmospheric Physics, Atmospheric Chemistry, Dynamic and Synoptic Meteorology, Numerical Weather Prediction, Modeling of Surface-atmosphere Interactions and Climate change. Education is performed in two branches: Climate Researcher and Forecaster

  16. Numerical Modeling of the Severe Cold Weather Event over Central Europe (January 2006

    Directory of Open Access Journals (Sweden)

    D. Hari Prasad

    2010-01-01

    Full Text Available Cold waves commonly occur in higher latitudes under prevailing high pressure systems especially during winter season which cause serious economical loss and cold related death. Accurate prediction of such severe weather events is important for decision making by administrators and for mitigation planning. An Advanced high resolution Weather Research and Forecasting mesoscale model is used to simulate a severe cold wave event occurred during January 2006 over Europe. The model is integrated for 31 days starting from 00UTC of 1 January 2006 with 30 km horizontal resolution. Comparison of the model derived area averaged daily mean temperatures at 2m height from different zones over the central Europe with observations indicates that the model is able to simulate the occurrence of the cold wave with the observed time lag of 1 to 3days but with lesser intensity. The temperature, winds, surface pressure and the geopential heights at 500 hPa reveal that the cold wave development associates with the southward progression of a high pressure system and cold air advection. The results have good agreement with the analysis fields indicates that the model has the ability to reproduce the time evolution of the cold wave event.

  17. Biologically enhanced mineral weathering: what does it look like, can we model it?

    Science.gov (United States)

    Schulz, M. S.; Lawrence, C. R.; Harden, J. W.; White, A. F.

    2011-12-01

    The interaction between plants and minerals in soils is hugely important and poorly understood as it relates to the fate of soil carbon. Plant roots, fungi and bacteria inhabit the mineral soil and work symbiotically to extract nutrients, generally through low molecular weight exudates (organic acids, extracelluar polysachrides (EPS), siderophores, etc.). Up to 60% of photosynthetic carbon is allocated below ground as roots and exudates, both being important carbon sources in soils. Some exudates accelerate mineral weathering. To test whether plant exudates are incorporated into poorly crystalline secondary mineral phases during precipitation, we are investigating the biologic-mineral interface. We sampled 5 marine terraces along a soil chronosequence (60 to 225 ka), near Santa Cruz, CA. The effects of the biologic interactions with mineral surfaces were characterized through the use of Scanning Electron Microscopy (SEM). Morphologically, mycorrhizal fungi were observed fully surrounding minerals, fungal hyphae were shown to tunnel into primary silicate minerals and we have observed direct hyphal attachment to mineral surfaces. Fungal tunneling was seen in all 5 soils by SEM. Additionally, specific surface area (using a nitrogen BET method) of primary minerals was measured to determine if the effects of mineral tunneling are quantifiable in older soils. Results suggest that fungal tunneling is more extensive in the primary minerals of older soils. We have also examined the influence of organic acids on primary mineral weathering during soil development using a geochemical reactive transport model (CrunchFlow). Addition of organic acids in our models of soil development at Santa Cruz result in decreased activity of Fe and Al in soil pore water, which subsequently alters the spatial extent of primary mineral weathering and kaolinite precipitation. Overall, our preliminary modeling results suggest biological processes may be an important but underrepresented aspect of

  18. Explicit simulation of ice particle habits in a Numerical Weather Prediction Model

    Science.gov (United States)

    Hashino, Tempei

    2007-05-01

    This study developed a scheme for explicit simulation of ice particle habits in Numerical Weather Prediction (NWP) Models. The scheme is called Spectral Ice Habit Prediction System (SHIPS), and the goal is to retain growth history of ice particles in the Eulerian dynamics framework. It diagnoses characteristics of ice particles based on a series of particle property variables (PPVs) that reflect history of microphysieal processes and the transport between mass bins and air parcels in space. Therefore, categorization of ice particles typically used in bulk microphysical parameterization and traditional bin models is not necessary, so that errors that stem from the categorization can be avoided. SHIPS predicts polycrystals as well as hexagonal monocrystals based on empirically derived habit frequency and growth rate, and simulates the habit-dependent aggregation and riming processes by use of the stochastic collection equation with predicted PPVs. Idealized two dimensional simulations were performed with SHIPS in a NWP model. The predicted spatial distribution of ice particle habits and types, and evolution of particle size distributions showed good quantitative agreement with observation This comprehensive model of ice particle properties, distributions, and evolution in clouds can be used to better understand problems facing wide range of research disciplines, including microphysics processes, radiative transfer in a cloudy atmosphere, data assimilation, and weather modification.

  19. Latest Community Coordinated Modeling Center (CCMC) services and innovative tools supporting the space weather research and operational communities.

    Science.gov (United States)

    Mendoza, A. M. M.; Rastaetter, L.; Kuznetsova, M. M.; Mays, M. L.; Chulaki, A.; Shim, J. S.; MacNeice, P. J.; Taktakishvili, A.; Collado-Vega, Y. M.; Weigand, C.; Zheng, Y.; Mullinix, R.; Patel, K.; Pembroke, A. D.; Pulkkinen, A. A.; Boblitt, J. M.; Bakshi, S. S.; Tsui, T.

    2017-12-01

    The Community Coordinated Modeling Center (CCMC), with the fundamental goal of aiding the transition of modern space science models into space weather forecasting while supporting space science research, has been serving as an integral hub for over 15 years, providing invaluable resources to both space weather scientific and operational communities. CCMC has developed and provided innovative web-based point of access tools varying from: Runs-On-Request System - providing unprecedented global access to the largest collection of state-of-the-art solar and space physics models, Integrated Space Weather Analysis (iSWA) - a powerful dissemination system for space weather information, Advanced Online Visualization and Analysis tools for more accurate interpretation of model results, Standard Data formats for Simulation Data downloads, and Mobile apps to view space weather data anywhere to the scientific community. In addition to supporting research and performing model evaluations, CCMC also supports space science education by hosting summer students through local universities. In this poster, we will showcase CCMC's latest innovative tools and services, and CCMC's tools that revolutionized the way we do research and improve our operational space weather capabilities. CCMC's free tools and resources are all publicly available online (http://ccmc.gsfc.nasa.gov).

  20. On the assimilation of satellite derived soil moisture in numerical weather prediction models

    Science.gov (United States)

    Drusch, M.

    2006-12-01

    Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

  1. 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.

  2. 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...

  3. Model Development for Risk Assessment of Driving on Freeway under Rainy Weather Conditions.

    Directory of Open Access Journals (Sweden)

    Xiaonan Cai

    Full Text Available Rainy weather conditions could result in significantly negative impacts on driving on freeways. However, due to lack of enough historical data and monitoring facilities, many regions are not able to establish reliable risk assessment models to identify such impacts. Given the situation, this paper provides an alternative solution where the procedure of risk assessment is developed based on drivers' subjective questionnaire and its performance is validated by using actual crash data. First, an ordered logit model was developed, based on questionnaire data collected from Freeway G15 in China, to estimate the relationship between drivers' perceived risk and factors, including vehicle type, rain intensity, traffic volume, and location. Then, weighted driving risk for different conditions was obtained by the model, and further divided into four levels of early warning (specified by colors using a rank order cluster analysis. After that, a risk matrix was established to determine which warning color should be disseminated to drivers, given a specific condition. Finally, to validate the proposed procedure, actual crash data from Freeway G15 were compared with the safety prediction based on the risk matrix. The results show that the risk matrix obtained in the study is able to predict driving risk consistent with actual safety implications, under rainy weather conditions.

  4. Evaluation of snowmelt simulation in the Weather Research and Forecasting model

    Science.gov (United States)

    Jin, Jiming; Wen, Lijuan

    2012-05-01

    The objective of this study is to better understand and improve snowmelt simulations in the advanced Weather Research and Forecasting (WRF) model by coupling it with the Community Land Model (CLM) Version 3.5. Both WRF and CLM are developed by the National Center for Atmospheric Research. The automated Snow Telemetry (SNOTEL) station data over the Columbia River Basin in the northwestern United States are used to evaluate snowmelt simulations generated with the coupled WRF-CLM model. These SNOTEL data include snow water equivalent (SWE), precipitation, and temperature. The simulations cover the period of March through June 2002 and focus mostly on the snowmelt season. Initial results show that when compared to observations, WRF-CLM significantly improves the simulations of SWE, which is underestimated when the release version of WRF is coupled with the Noah and Rapid Update Cycle (RUC) land surface schemes, in which snow physics is oversimplified. Further analysis shows that more realistic snow surface energy allocation in CLM is an important process that results in improved snowmelt simulations when compared to that in Noah and RUC. Additional simulations with WRF-CLM at different horizontal spatial resolutions indicate that accurate description of topography is also vital to SWE simulations. WRF-CLM at 10 km resolution produces the most realistic SWE simulations when compared to those produced with coarser spatial resolutions in which SWE is remarkably underestimated. The coupled WRF-CLM provides an important tool for research and forecasts in weather, climate, and water resources at regional scales.

  5. Configuring the HYSPLIT Model for National Weather Service Forecast Office and Spaceflight Meteorology Group Applications

    Science.gov (United States)

    Dreher, Joseph; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian; Van Speybroeck, Kurt

    2009-01-01

    The National Weather Service Forecast Office in Melbourne, FL (NWS MLB) is responsible for providing meteorological support to state and county emergency management agencies across East Central Florida in the event of incidents involving the significant release of harmful chemicals, radiation, and smoke from fires and/or toxic plumes into the atmosphere. NWS MLB uses the National Oceanic and Atmospheric Administration Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to provide trajectory, concentration, and deposition guidance during such events. Accurate and timely guidance is critical for decision makers charged with protecting the health and well-being of populations at risk. Information that can describe the geographic extent of areas possibly affected by a hazardous release, as well as to indicate locations of primary concern, offer better opportunity for prompt and decisive action. In addition, forecasters at the NWS Spaceflight Meteorology Group (SMG) have expressed interest in using the HYSPLIT model to assist with Weather Flight Rules during Space Shuttle landing operations. In particular, SMG would provide low and mid-level HYSPLIT trajectory forecasts for cumulus clouds associated with smoke plumes, and high-level trajectory forecasts for thunderstorm anvils. Another potential benefit for both NWS MLB and SMG is using the HYSPLIT model concentration and deposition guidance in fog situations.

  6. Improving weather predictability by including land-surface model parameter uncertainty

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

    2016-04-01

    The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by

  7. Prediction skill of rainstorm events over India in the TIGGE weather prediction models

    Science.gov (United States)

    Karuna Sagar, S.; Rajeevan, M.; Vijaya Bhaskara Rao, S.; Mitra, A. K.

    2017-12-01

    Extreme rainfall events pose a serious threat of leading to severe floods in many countries worldwide. Therefore, advance prediction of its occurrence and spatial distribution is very essential. In this paper, an analysis has been made to assess the skill of numerical weather prediction models in predicting rainstorms over India. Using gridded daily rainfall data set and objective criteria, 15 rainstorms were identified during the monsoon season (June to September). The analysis was made using three TIGGE (THe Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble) models. The models considered are the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centre for Environmental Prediction (NCEP) and the UK Met Office (UKMO). Verification of the TIGGE models for 43 observed rainstorm days from 15 rainstorm events has been made for the period 2007-2015. The comparison reveals that rainstorm events are predictable up to 5 days in advance, however with a bias in spatial distribution and intensity. The statistical parameters like mean error (ME) or Bias, root mean square error (RMSE) and correlation coefficient (CC) have been computed over the rainstorm region using the multi-model ensemble (MME) mean. The study reveals that the spread is large in ECMWF and UKMO followed by the NCEP model. Though the ensemble spread is quite small in NCEP, the ensemble member averages are not well predicted. The rank histograms suggest that the forecasts are under prediction. The modified Contiguous Rain Area (CRA) technique was used to verify the spatial as well as the quantitative skill of the TIGGE models. Overall, the contribution from the displacement and pattern errors to the total RMSE is found to be more in magnitude. The volume error increases from 24 hr forecast to 48 hr forecast in all the three models.

  8. Generating daily weather data for ecosystem modelling in the Congo River Basin

    Science.gov (United States)

    Petritsch, Richard; Pietsch, Stephan A.

    2010-05-01

    Daily weather data are an important constraint for diverse applications in ecosystem research. In particular, temperature and precipitation are the main drivers for forest ecosystem productivity. Mechanistic modelling theory heavily relies on daily values for minimum and maximum temperatures, precipitation, incident solar radiation and vapour pressure deficit. Although the number of climate measurement stations increased during the last centuries, there are still regions with limited climate data. For example, in the WMO database there are only 16 stations located in Gabon with daily weather measurements. Additionally, the available time series are heavily affected by measurement errors or missing values. In the WMO record for Gabon, on average every second day is missing. Monthly means are more robust and may be estimated over larger areas. Therefore, a good alternative is to interpolate monthly mean values using a sparse network of measurement stations, and based on these monthly data generate daily weather data with defined characteristics. The weather generator MarkSim was developed to produce climatological time series for crop modelling in the tropics. It provides daily values for maximum and minimum temperature, precipitation and solar radiation. The monthly means can either be derived from the internal climate surfaces or prescribed as additional inputs. We compared the generated outputs observations from three climate stations in Gabon (Lastourville, Moanda and Mouilla) and found that maximum temperature and solar radiation were heavily overestimated during the long dry season. This is due to the internal dependency of the solar radiation estimates to precipitation. With no precipitation a cloudless sky is assumed and thus high incident solar radiation and a large diurnal temperature range. However, in reality it is cloudy in the Congo River Basin during the long dry season. Therefore, we applied a correction factor to solar radiation and temperature range

  9. Advanced Corrections for InSAR Using GPS and Numerical Weather Models

    Science.gov (United States)

    Cossu, F.; Foster, J. H.; Amelung, F.; Varugu, B. K.; Businger, S.; Cherubini, T.

    2017-12-01

    We present results from an investigation into the application of numerical weather models for generating tropospheric correction fields for Interferometric Synthetic Aperture Radar (InSAR). We apply the technique to data acquired from a UAVSAR campaign as well as from the CosmoSkyMed satellites. The complex spatial and temporal changes in the atmospheric propagation delay of the radar signal remain the single biggest factor limiting InSAR's potential for hazard monitoring and mitigation. A new generation of InSAR systems is being built and launched, and optimizing the science and hazard applications of these systems requires advanced methodologies to mitigate tropospheric noise. We use the Weather Research and Forecasting (WRF) model to generate a 900 m spatial resolution atmospheric models covering the Big Island of Hawaii and an even higher, 300 m resolution grid over the Mauna Loa and Kilauea volcanoes. By comparing a range of approaches, from the simplest, using reanalyses based on typically available meteorological observations, through to the "kitchen-sink" approach of assimilating all relevant data sets into our custom analyses, we examine the impact of the additional data sets on the atmospheric models and their effectiveness in correcting InSAR data. We focus particularly on the assimilation of information from the more than 60 GPS sites in the island. We ingest zenith tropospheric delay estimates from these sites directly into the WRF analyses, and also perform double-difference tomography using the phase residuals from the GPS processing to robustly incorporate heterogeneous information from the GPS data into the atmospheric models. We assess our performance through comparisons of our atmospheric models with external observations not ingested into the model, and through the effectiveness of the derived phase screens in reducing InSAR variance. Comparison of the InSAR data, our atmospheric analyses, and assessments of the active local and mesoscale

  10. Data-Model and Inter-Model Comparisons of the GEM Outflow Events Using the Space Weather Modeling Framework

    Science.gov (United States)

    Welling, D. T.; Eccles, J. V.; Barakat, A. R.; Kistler, L. M.; Haaland, S.; Schunk, R. W.; Chappell, C. R.

    2015-12-01

    Two storm periods were selected by the Geospace Environment Modeling Ionospheric Outflow focus group for community collaborative study because of its high magnetospheric activity and extensive data coverage: the September 27 - October 4, 2002 corotating interaction region event and the October 22 - 29 coronal mass ejection event. During both events, the FAST, Polar, Cluster, and other missions made key observations, creating prime periods for data-model comparison. The GEM community has come together to simulate this period using many different methods in order to evaluate models, compare results, and expand our knowledge of ionospheric outflow and its effects on global dynamics. This paper presents Space Weather Modeling Framework (SWMF) simulations of these important periods compared against observations from the Polar TIDE, Cluster CODIF and EFW instruments. Emphasis will be given to the second event. Density and velocity of oxygen and hydrogen throughout the lobes, plasma sheet, and inner magnetosphere will be the focus of these comparisons. For these simulations, the SWMF couples the multifluid version of BATS-R-US MHD to a variety of ionospheric outflow models of varying complexity. The simplest is outflow arising from constant MHD inner boundary conditions. Two first-principles-based models are also leveraged: the Polar Wind Outflow Model (PWOM), a fluid treatment of outflow dynamics, and the Generalized Polar Wind (GPW) model, which combines fluid and particle-in-cell approaches. Each model is capable of capturing a different set of energization mechanisms, yielding different outflow results. The data-model comparisons will illustrate how well each approach captures reality and which energization mechanisms are most important. Inter-model comparisons will illustrate how the different outflow specifications affect the magnetosphere. Specifically, it is found that the GPW provides increased heavy ion outflow over a broader spatial range than the alternative

  11. Urban weather data and building models for the inclusion of the urban heat island effect in building performance simulation.

    Science.gov (United States)

    Palme, M; Inostroza, L; Villacreses, G; Lobato, A; Carrasco, C

    2017-10-01

    This data article presents files supporting calculation for urban heat island (UHI) inclusion in building performance simulation (BPS). Methodology is used in the research article "From urban climate to energy consumption. Enhancing building performance simulation by including the urban heat island effect" (Palme et al., 2017) [1]. In this research, a Geographical Information System (GIS) study is done in order to statistically represent the most important urban scenarios of four South-American cities (Guayaquil, Lima, Antofagasta and Valparaíso). Then, a Principal Component Analysis (PCA) is done to obtain reference Urban Tissues Categories (UTC) to be used in urban weather simulation. The urban weather files are generated by using the Urban Weather Generator (UWG) software (version 4.1 beta). Finally, BPS is run out with the Transient System Simulation (TRNSYS) software (version 17). In this data paper, four sets of data are presented: 1) PCA data (excel) to explain how to group different urban samples in representative UTC; 2) UWG data (text) to reproduce the Urban Weather Generation for the UTC used in the four cities (4 UTC in Lima, Guayaquil, Antofagasta and 5 UTC in Valparaíso); 3) weather data (text) with the resulting rural and urban weather; 4) BPS models (text) data containing the TRNSYS models (four building models).

  12. Urban weather data and building models for the inclusion of the urban heat island effect in building performance simulation

    Directory of Open Access Journals (Sweden)

    M. Palme

    2017-10-01

    Full Text Available This data article presents files supporting calculation for urban heat island (UHI inclusion in building performance simulation (BPS. Methodology is used in the research article “From urban climate to energy consumption. Enhancing building performance simulation by including the urban heat island effect” (Palme et al., 2017 [1]. In this research, a Geographical Information System (GIS study is done in order to statistically represent the most important urban scenarios of four South-American cities (Guayaquil, Lima, Antofagasta and Valparaíso. Then, a Principal Component Analysis (PCA is done to obtain reference Urban Tissues Categories (UTC to be used in urban weather simulation. The urban weather files are generated by using the Urban Weather Generator (UWG software (version 4.1 beta. Finally, BPS is run out with the Transient System Simulation (TRNSYS software (version 17. In this data paper, four sets of data are presented: 1 PCA data (excel to explain how to group different urban samples in representative UTC; 2 UWG data (text to reproduce the Urban Weather Generation for the UTC used in the four cities (4 UTC in Lima, Guayaquil, Antofagasta and 5 UTC in Valparaíso; 3 weather data (text with the resulting rural and urban weather; 4 BPS models (text data containing the TRNSYS models (four building models.

  13. 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.

  14. 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...

  15. High resolution weather data for urban hydrological modelling and impact assessment, ICT requirements and future challenges

    Science.gov (United States)

    ten Veldhuis, Marie-claire; van Riemsdijk, Birna

    2013-04-01

    Hydrological analysis of urban catchments requires high resolution rainfall and catchment information because of the small size of these catchments, high spatial variability of the urban fabric, fast runoff processes and related short response times. Rainfall information available from traditional radar and rain gauge networks does no not meet the relevant scales of urban hydrology. A new type of weather radars, based on X-band frequency and equipped with Doppler and dual polarimetry capabilities, promises to provide more accurate rainfall estimates at the spatial and temporal scales that are required for urban hydrological analysis. Recently, the RAINGAIN project was started to analyse the applicability of this new type of radars in the context of urban hydrological modelling. In this project, meteorologists and hydrologists work closely together in several stages of urban hydrological analysis: from the acquisition procedure of novel and high-end radar products to data acquisition and processing, rainfall data retrieval, hydrological event analysis and forecasting. The project comprises of four pilot locations with various characteristics of weather radar equipment, ground stations, urban hydrological systems, modelling approaches and requirements. Access to data processing and modelling software is handled in different ways in the pilots, depending on ownership and user context. Sharing of data and software among pilots and with the outside world is an ongoing topic of discussion. The availability of high resolution weather data augments requirements with respect to the resolution of hydrological models and input data. This has led to the development of fully distributed hydrological models, the implementation of which remains limited by the unavailability of hydrological input data. On the other hand, if models are to be used in flood forecasting, hydrological models need to be computationally efficient to enable fast responses to extreme event conditions. This

  16. Revisiting source identification, weathering models, and phase discrimination for Exxon Valdez oil

    International Nuclear Information System (INIS)

    Driskell, W.B.; Payne, J.R.; Shigenaka, G.

    2005-01-01

    A large chemistry data set for polycyclic aromatic hydrocarbon (PAH) and saturated hydrocarbon (SHC) contamination in sediment, water and tissue samples has emerged in the aftermath of the 1989 Exxon Valdez oil spill in Prince William Sound, Alaska. When the oil was fresh, source identification was a primary objective and fairly reliable. However, source identification became problematic as the oil weathered and its signatures changed. In response to concerns regarding when the impacted area will be clean again, this study focused on developing appropriate tools to confirm hydrocarbon source identifications and assess weathering in various matrices. Previous efforts that focused only on the whole or particulate-phase oil are not adequate to track dissolved-phase signal with low total PAH values. For that reason, a particulate signature index (PSI) and dissolved signature index (DSI) screening tool was developed in this study to discriminate between these 2 phases. The screening tool was used to measure the dissolved or water-soluble fraction of crude oil which occurs at much lower levels than the particulate phase, but which is more widely circulated and equally as important as the particulate oil phase. The discrimination methods can also identify normally-discarded, low total PAH samples which can increase the amount of usable data needed to model other effects of oil spills. 37 refs., 3 tabs., 10 figs

  17. Crossing the chasm: how to develop weather and climate models for next generation computers?

    Directory of Open Access Journals (Sweden)

    B. N. Lawrence

    2018-05-01

    Full Text Available Weather and climate models are complex pieces of software which include many individual components, each of which is evolving under pressure to exploit advances in computing to enhance some combination of a range of possible improvements (higher spatio-temporal resolution, increased fidelity in terms of resolved processes, more quantification of uncertainty, etc.. However, after many years of a relatively stable computing environment with little choice in processing architecture or programming paradigm (basically X86 processors using MPI for parallelism, the existing menu of processor choices includes significant diversity, and more is on the horizon. This computational diversity, coupled with ever increasing software complexity, leads to the very real possibility that weather and climate modelling will arrive at a chasm which will separate scientific aspiration from our ability to develop and/or rapidly adapt codes to the available hardware. In this paper we review the hardware and software trends which are leading us towards this chasm, before describing current progress in addressing some of the tools which we may be able to use to bridge the chasm. This brief introduction to current tools and plans is followed by a discussion outlining the scientific requirements for quality model codes which have satisfactory performance and portability, while simultaneously supporting productive scientific evolution. We assert that the existing method of incremental model improvements employing small steps which adjust to the changing hardware environment is likely to be inadequate for crossing the chasm between aspiration and hardware at a satisfactory pace, in part because institutions cannot have all the relevant expertise in house. Instead, we outline a methodology based on large community efforts in engineering and standardisation, which will depend on identifying a taxonomy of key activities – perhaps based on existing efforts to develop

  18. Crossing the chasm: how to develop weather and climate models for next generation computers?

    Science.gov (United States)

    Lawrence, Bryan N.; Rezny, Michael; Budich, Reinhard; Bauer, Peter; Behrens, Jörg; Carter, Mick; Deconinck, Willem; Ford, Rupert; Maynard, Christopher; Mullerworth, Steven; Osuna, Carlos; Porter, Andrew; Serradell, Kim; Valcke, Sophie; Wedi, Nils; Wilson, Simon

    2018-05-01

    Weather and climate models are complex pieces of software which include many individual components, each of which is evolving under pressure to exploit advances in computing to enhance some combination of a range of possible improvements (higher spatio-temporal resolution, increased fidelity in terms of resolved processes, more quantification of uncertainty, etc.). However, after many years of a relatively stable computing environment with little choice in processing architecture or programming paradigm (basically X86 processors using MPI for parallelism), the existing menu of processor choices includes significant diversity, and more is on the horizon. This computational diversity, coupled with ever increasing software complexity, leads to the very real possibility that weather and climate modelling will arrive at a chasm which will separate scientific aspiration from our ability to develop and/or rapidly adapt codes to the available hardware. In this paper we review the hardware and software trends which are leading us towards this chasm, before describing current progress in addressing some of the tools which we may be able to use to bridge the chasm. This brief introduction to current tools and plans is followed by a discussion outlining the scientific requirements for quality model codes which have satisfactory performance and portability, while simultaneously supporting productive scientific evolution. We assert that the existing method of incremental model improvements employing small steps which adjust to the changing hardware environment is likely to be inadequate for crossing the chasm between aspiration and hardware at a satisfactory pace, in part because institutions cannot have all the relevant expertise in house. Instead, we outline a methodology based on large community efforts in engineering and standardisation, which will depend on identifying a taxonomy of key activities - perhaps based on existing efforts to develop domain-specific languages

  19. Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

    Science.gov (United States)

    Zhou, C.; Zhang, X.; Gong, S.; Wang, Y.; Xue, M.

    2016-01-01

    A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme has been developed under a China Meteorological Administration (CMA) chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment). Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme - WDM6) and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

  20. Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

    Directory of Open Access Journals (Sweden)

    C. Zhou

    2016-01-01

    Full Text Available A comprehensive aerosol–cloud–precipitation interaction (ACI scheme has been developed under a China Meteorological Administration (CMA chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment. Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme – WDM6 and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

  1. Employing Tropospheric Numerical Weather Prediction Model for High-Precision GNSS Positioning

    Science.gov (United States)

    Alves, Daniele; Gouveia, Tayna; Abreu, Pedro; Magário, Jackes

    2014-05-01

    In the past few years is increasing the necessity of realizing high accuracy positioning. In this sense, the spatial technologies have being widely used. The GNSS (Global Navigation Satellite System) has revolutionized the geodetic positioning activities. Among the existent methods one can emphasize the Precise Point Positioning (PPP) and network-based positioning. But, to get high accuracy employing these methods, mainly in real time, is indispensable to realize the atmospheric modeling (ionosphere and troposphere) accordingly. Related to troposphere, there are the empirical models (for example Saastamoinen and Hopfield). But when highly accuracy results (error of few centimeters) are desired, maybe these models are not appropriated to the Brazilian reality. In order to minimize this limitation arises the NWP (Numerical Weather Prediction) models. In Brazil the CPTEC/INPE (Center for Weather Prediction and Climate Studies / Brazilian Institute for Spatial Researches) provides a regional NWP model, currently used to produce Zenithal Tropospheric Delay (ZTD) predictions (http://satelite.cptec.inpe.br/zenital/). The actual version, called eta15km model, has a spatial resolution of 15 km and temporal resolution of 3 hours. In this paper the main goal is to accomplish experiments and analysis concerning the use of troposphere NWP model (eta15km model) in PPP and network-based positioning. Concerning PPP it was used data from dozens of stations over the Brazilian territory, including Amazon forest. The results obtained with NWP model were compared with Hopfield one. NWP model presented the best results in all experiments. Related to network-based positioning it was used data from GNSS/SP Network in São Paulo State, Brazil. This network presents the best configuration in the country to realize this kind of positioning. Actually the network is composed by twenty stations (http://www.fct.unesp.br/#!/pesquisa/grupos-de-estudo-e-pesquisa/gege//gnss-sp-network2789/). The

  2. Coupling a Mesoscale Numerical Weather Prediction Model with Large-Eddy Simulation for Realistic Wind Plant Aerodynamics Simulations (Poster)

    Energy Technology Data Exchange (ETDEWEB)

    Draxl, C.; Churchfield, M.; Mirocha, J.; Lee, S.; Lundquist, J.; Michalakes, J.; Moriarty, P.; Purkayastha, A.; Sprague, M.; Vanderwende, B.

    2014-06-01

    Wind plant aerodynamics are influenced by a combination of microscale and mesoscale phenomena. Incorporating mesoscale atmospheric forcing (e.g., diurnal cycles and frontal passages) into wind plant simulations can lead to a more accurate representation of microscale flows, aerodynamics, and wind turbine/plant performance. Our goal is to couple a numerical weather prediction model that can represent mesoscale flow [specifically the Weather Research and Forecasting model] with a microscale LES model (OpenFOAM) that can predict microscale turbulence and wake losses.

  3. Integrating K-means Clustering with Kernel Density Estimation for the Development of a Conditional Weather Generation Downscaling Model

    Science.gov (United States)

    Chen, Y.; Ho, C.; Chang, L.

    2011-12-01

    In previous decades, the climate change caused by global warming increases the occurrence frequency of extreme hydrological events. Water supply shortages caused by extreme events create great challenges for water resource management. To evaluate future climate variations, general circulation models (GCMs) are the most wildly known tools which shows possible weather conditions under pre-defined CO2 emission scenarios announced by IPCC. Because the study area of GCMs is the entire earth, the grid sizes of GCMs are much larger than the basin scale. To overcome the gap, a statistic downscaling technique can transform the regional scale weather factors into basin scale precipitations. The statistic downscaling technique can be divided into three categories include transfer function, weather generator and weather type. The first two categories describe the relationships between the weather factors and precipitations respectively based on deterministic algorithms, such as linear or nonlinear regression and ANN, and stochastic approaches, such as Markov chain theory and statistical distributions. In the weather type, the method has ability to cluster weather factors, which are high dimensional and continuous variables, into weather types, which are limited number of discrete states. In this study, the proposed downscaling model integrates the weather type, using the K-means clustering algorithm, and the weather generator, using the kernel density estimation. The study area is Shihmen basin in northern of Taiwan. In this study, the research process contains two steps, a calibration step and a synthesis step. Three sub-steps were used in the calibration step. First, weather factors, such as pressures, humidities and wind speeds, obtained from NCEP and the precipitations observed from rainfall stations were collected for downscaling. Second, the K-means clustering grouped the weather factors into four weather types. Third, the Markov chain transition matrixes and the

  4. Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula

    Science.gov (United States)

    Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.

    2012-08-01

    This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.

  5. Influence of weathering and pre-existing large scale fractures on gravitational slope failure: insights from 3-D physical modelling

    Directory of Open Access Journals (Sweden)

    D. Bachmann

    2004-01-01

    Full Text Available Using a new 3-D physical modelling technique we investigated the initiation and evolution of large scale landslides in presence of pre-existing large scale fractures and taking into account the slope material weakening due to the alteration/weathering. The modelling technique is based on the specially developed properly scaled analogue materials, as well as on the original vertical accelerator device enabling increases in the 'gravity acceleration' up to a factor 50. The weathering primarily affects the uppermost layers through the water circulation. We simulated the effect of this process by making models of two parts. The shallower one represents the zone subject to homogeneous weathering and is made of low strength material of compressive strength σl. The deeper (core part of the model is stronger and simulates intact rocks. Deformation of such a model subjected to the gravity force occurred only in its upper (low strength layer. In another set of experiments, low strength (σw narrow planar zones sub-parallel to the slope surface (σwl were introduced into the model's superficial low strength layer to simulate localized highly weathered zones. In this configuration landslides were initiated much easier (at lower 'gravity force', were shallower and had smaller horizontal size largely defined by the weak zone size. Pre-existing fractures were introduced into the model by cutting it along a given plan. They have proved to be of small influence on the slope stability, except when they were associated to highly weathered zones. In this latter case the fractures laterally limited the slides. Deep seated rockslides initiation is thus directly defined by the mechanical structure of the hillslope's uppermost levels and especially by the presence of the weak zones due to the weathering. The large scale fractures play a more passive role and can only influence the shape and the volume of the sliding units.

  6. A Two-Dimensional Gridded Solar Forecasting System using Situation-Dependent Blending of Multiple Weather Models

    Science.gov (United States)

    Lu, S.; Hwang, Y.; Shao, X.; Hamann, H.

    2015-12-01

    Previously, we reported the application of a "weather situation" dependent multi-model blending approach to improve the forecast accuracy of solar irradiance and other atmospheric parameters. The approach uses machine-learning techniques to classify "weather situations" by a set of atmospheric parameters. The "weather situation" classification is location-dependent and each "weather situation" has characteristic forecast errors from a set of individual input numerical weather prediction (NWP) models. The input models are thus corrected or combined differently for different "weather situations" to minimize the overall forecast error. While the original implementation of the model-blending is applicable to only point-like locations having historical data of both measurements and forecasts, here we extend the approach to provide two-dimensional (2D) gridded forecasts. An experimental 2D forecasting system has been set up to provide gridded forecasts of solar irradiance (global horizontal irradiance), temperature, wind speed, and humidity for the contiguous United States (CONUS). Validation results show around 30% enhancement of 0 to 48 hour ahead solar irradiance forecast accuracy compared to the best input NWP model. The forecasting system may be leveraged by other site- or region-specific solar energy forecast products. To enable the 2D forecasting system, historical solar irradiance measurements from around 1,600 selected sites of the remote automated weather stations (RAWS) network have been employed. The CONUS was divided into smaller sub-regions, each containing a group of 10 to 20 RAWS sites. A group of sites, as classified by statistical analysis, have similar "weather patterns", i.e. the NWPs have similar "weather situation" dependent forecast errors for all sites in a group. The model-blending trained by the historical data from a group of sites is then applied for all locations in the corresponding sub-region. We discuss some key techniques developed for

  7. Trends of air pollution in Denmark - Normalised by a simple weather index model

    International Nuclear Information System (INIS)

    Kiilsholm, S.; Rasmussen, A.

    2000-01-01

    This report is a part of the Traffic Pool projects on 'Traffic and Environments', 1995-99, financed by the Danish Ministry of Transport. The Traffic Pool projects included five different projects on 'Surveillance of the Air Quality', 'Atmospheric Modelling', 'Atmospheric Chemistry Modelling', 'Smog and ozone' and 'Greenhouse effects and Climate', [Rasmussen, 2000]. This work is a part of the project on 'Surveillance of the Air Quality' with the main objectives to make trend analysis of levels of air pollution from traffic in Denmark. Other participants were from the Road Directory mainly focusing on measurement of traffic and trend analysis of the air quality utilising a nordic model for the air pollution in street canyons called BLB (Beregningsmodel for Luftkvalitet i Byluftgader) [Vejdirektoratet 2000], National Environmental Research Institute (HERI) mainly focusing on. measurements of air pollution and trend analysis with the Operational Street Pollution Model (OSPM) [DMU 2000], and the Copenhagen Environmental Protection Agency mainly focusing on measurements. In this study a more simple statistical model has been developed for trend analysis of the air quality. The model is filtering out the influence of the variations from year to year in the meteorological conditions on the air pollution levels. The weather factors found most important are wind speed, wind direction and mixing height. Measurements of CO, NO and NO 2 from three streets in Copenhagen have been used, these streets are Jagtvej, Bredgade and H. C. Andersen's Boulevard (HCAB). The years 1994-1996 were used for evaluation of the method and annual indexes of air pollution index dependent only on meteorological parameters, called WEATHIX, were calculated for the years 1990-1997 and used for normalisation of the observed air pollution trends. Meteorological data were taken from either the background stations at the H.C. Oersted - building situated close to one of the street stations or the synoptic

  8. Ensemble downscaling in coupled solar wind-magnetosphere modeling for space weather forecasting.

    Science.gov (United States)

    Owens, M J; Horbury, T S; Wicks, R T; McGregor, S L; Savani, N P; Xiong, M

    2014-06-01

    Advanced forecasting of space weather requires simulation of the whole Sun-to-Earth system, which necessitates driving magnetospheric models with the outputs from solar wind models. This presents a fundamental difficulty, as the magnetosphere is sensitive to both large-scale solar wind structures, which can be captured by solar wind models, and small-scale solar wind "noise," which is far below typical solar wind model resolution and results primarily from stochastic processes. Following similar approaches in terrestrial climate modeling, we propose statistical "downscaling" of solar wind model results prior to their use as input to a magnetospheric model. As magnetospheric response can be highly nonlinear, this is preferable to downscaling the results of magnetospheric modeling. To demonstrate the benefit of this approach, we first approximate solar wind model output by smoothing solar wind observations with an 8 h filter, then add small-scale structure back in through the addition of random noise with the observed spectral characteristics. Here we use a very simple parameterization of noise based upon the observed probability distribution functions of solar wind parameters, but more sophisticated methods will be developed in the future. An ensemble of results from the simple downscaling scheme are tested using a model-independent method and shown to add value to the magnetospheric forecast, both improving the best estimate and quantifying the uncertainty. We suggest a number of features desirable in an operational solar wind downscaling scheme. Solar wind models must be downscaled in order to drive magnetospheric models Ensemble downscaling is more effective than deterministic downscaling The magnetosphere responds nonlinearly to small-scale solar wind fluctuations.

  9. Predicting the weathering of fuel and oil spills: A diffusion-limited evaporation model.

    Science.gov (United States)

    Kotzakoulakis, Konstantinos; George, Simon C

    2018-01-01

    The majority of the evaporation models currently available in the literature for the prediction of oil spill weathering do not take into account diffusion-limited mass transport and the formation of a concentration gradient in the oil phase. The altered surface concentration of the spill caused by diffusion-limited transport leads to a slower evaporation rate compared to the predictions of diffusion-agnostic evaporation models. The model presented in this study incorporates a diffusive layer in the oil phase and predicts the diffusion-limited evaporation rate. The information required is the composition of the fluid from gas chromatography or alternatively the distillation data. If the density or a single viscosity measurement is available the accuracy of the predictions is higher. Environmental conditions such as water temperature, air pressure and wind velocity are taken into account. The model was tested with synthetic mixtures, petroleum fuels and crude oils with initial viscosities ranging from 2 to 13,000 cSt. The tested temperatures varied from 0 °C to 23.4 °C and wind velocities from 0.3 to 3.8 m/s. The average absolute deviation (AAD) of the diffusion-limited model ranged between 1.62% and 24.87%. In comparison, the AAD of a diffusion-agnostic model ranged between 2.34% and 136.62% against the same tested fluids. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Weather Correlations to Calculate Infiltration Rates for U. S. Commercial Building Energy Models.

    Science.gov (United States)

    Ng, Lisa C; Quiles, Nelson Ojeda; Dols, W Stuart; Emmerich, Steven J

    2018-01-01

    As building envelope performance improves, a greater percentage of building energy loss will occur through envelope leakage. Although the energy impacts of infiltration on building energy use can be significant, current energy simulation software have limited ability to accurately account for envelope infiltration and the impacts of improved airtightness. This paper extends previous work by the National Institute of Standards and Technology that developed a set of EnergyPlus inputs for modeling infiltration in several commercial reference buildings using Chicago weather. The current work includes cities in seven additional climate zones and uses the updated versions of the prototype commercial building types developed by the Pacific Northwest National Laboratory for the U. S. Department of Energy. Comparisons were made between the predicted infiltration rates using three representations of the commercial building types: PNNL EnergyPlus models, CONTAM models, and EnergyPlus models using the infiltration inputs developed in this paper. The newly developed infiltration inputs in EnergyPlus yielded average annual increases of 3 % and 8 % in the HVAC electrical and gas use, respectively, over the original infiltration inputs in the PNNL EnergyPlus models. When analyzing the benefits of building envelope airtightening, greater HVAC energy savings were predicted using the newly developed infiltration inputs in EnergyPlus compared with using the original infiltration inputs. These results indicate that the effects of infiltration on HVAC energy use can be significant and that infiltration can and should be better accounted for in whole-building energy models.

  11. Relative importance of fuel management, ignition management and weather for area burned: Evidence from five landscape-fire-succession models

    Science.gov (United States)

    Geoffrey J. Cary; Mike D. Flannigan; Robert E. Keane; Ross A. Bradstock; Ian D. Davies; James M. Lenihan; Chao Li; Kimberley A. Logan; Russell A. Parsons

    2009-01-01

    The behaviour of five landscape fire models (CAFE, FIRESCAPE, LAMOS(HS), LANDSUM and SEMLAND) was compared in a standardised modelling experiment. The importance of fuel management approach, fuel management effort, ignition management effort and weather in determining variation in area burned and number of edge pixels burned (a measure of potential impact on assets...

  12. Reference Evapotranspiration Retrievals from a Mesoscale Model Based Weather Variables for Soil Moisture Deficit Estimation

    Directory of Open Access Journals (Sweden)

    Prashant K. Srivastava

    2017-10-01

    Full Text Available Reference Evapotranspiration (ETo and soil moisture deficit (SMD are vital for understanding the hydrological processes, particularly in the context of sustainable water use efficiency in the globe. Precise estimation of ETo and SMD are required for developing appropriate forecasting systems, in hydrological modeling and also in precision agriculture. In this study, the surface temperature downscaled from Weather Research and Forecasting (WRF model is used to estimate ETo using the boundary conditions that are provided by the European Center for Medium Range Weather Forecast (ECMWF. In order to understand the performance, the Hamon’s method is employed to estimate the ETo using the temperature from meteorological station and WRF derived variables. After estimating the ETo, a range of linear and non-linear models is utilized to retrieve SMD. The performance statistics such as RMSE, %Bias, and Nash Sutcliffe Efficiency (NSE indicates that the exponential model (RMSE = 0.226; %Bias = −0.077; NSE = 0.616 is efficient for SMD estimation by using the Observed ETo in comparison to the other linear and non-linear models (RMSE range = 0.019–0.667; %Bias range = 2.821–6.894; NSE = 0.013–0.419 used in this study. On the other hand, in the scenario where SMD is estimated using WRF downscaled meteorological variables based ETo, the linear model is found promising (RMSE = 0.017; %Bias = 5.280; NSE = 0.448 as compared to the non-linear models (RMSE range = 0.022–0.707; %Bias range = −0.207–−6.088; NSE range = 0.013–0.149. Our findings also suggest that all the models are performing better during the growing season (RMSE range = 0.024–0.025; %Bias range = −4.982–−3.431; r = 0.245–0.281 than the non−growing season (RMSE range = 0.011–0.12; %Bias range = 33.073–32.701; r = 0.161–0.244 for SMD estimation.

  13. Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Nebula Cloud Computing Environment

    Science.gov (United States)

    Molthan, Andrew L.; Case, Jonathan L.; Venner, Jason; Moreno-Madrinan, Max. J.; Delgado, Francisco

    2012-01-01

    Over the past two years, scientists in the Earth Science Office at NASA fs Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real ]time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA fs Short ]term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface ] and satellite ]based observations.

  14. A hybrid convection scheme for use in non-hydrostatic numerical weather prediction models

    Directory of Open Access Journals (Sweden)

    Volker Kuell

    2008-12-01

    Full Text Available The correct representation of convection in numerical weather prediction (NWP models is essential for quantitative precipitation forecasts. Due to its small horizontal scale convection usually has to be parameterized, e.g. by mass flux convection schemes. Classical schemes originally developed for use in coarse grid NWP models assume zero net convective mass flux, because the whole circulation of a convective cell is confined to the local grid column and all convective mass fluxes cancel out. However, in contemporary NWP models with grid sizes of a few kilometers this assumption becomes questionable, because here convection is partially resolved on the grid. To overcome this conceptual problem we propose a hybrid mass flux convection scheme (HYMACS in which only the convective updrafts and downdrafts are parameterized. The generation of the larger scale environmental subsidence, which may cover several grid columns, is transferred to the grid scale equations. This means that the convection scheme now has to generate a net convective mass flux exerting a direct dynamical forcing to the grid scale model via pressure gradient forces. The hybrid convection scheme implemented into the COSMO model of Deutscher Wetterdienst (DWD is tested in an idealized simulation of a sea breeze circulation initiating convection in a realistic manner. The results are compared with analogous simulations with the classical Tiedtke and Kain-Fritsch convection schemes.

  15. Selection for the best ETS (error, trend, seasonal) model to forecast weather in the Aceh Besar District

    Science.gov (United States)

    Amora Jofipasi, Chesilia; Miftahuddin; Hizir

    2018-05-01

    Weather is a phenomenon that occurs in certain areas that indicate a change in natural activity. Weather can be predicted using data in previous periods over a period. The purpose of this study is to get the best ETS model to predict the weather in Aceh Besar. The ETS model is a time series univariate forecasting method; its use focuses on trend and seasonal components. The data used are air temperature, dew point, sea level pressure, station pressure, visibility, wind speed, and sea surface temperature from January 2006 to December 2016. Based on AIC, AICc and BIC the smallest values obtained the conclusion that the ETS (M, N, A) is used to predict air temperature, and sea surface temperature, ETS (A, N, A) is used to predict dew point, sea level pressure and station pressure, ETS (A, A, N) is used to predict visibility, and ETS (A, N, N) is used to predict wind speed.

  16. Weather Research and Forecasting Model Wind Sensitivity Study at Edwards Air Force Base, CA

    Science.gov (United States)

    Watson, Leela R.; Bauman, William H., III; Hoeth, Brian

    2009-01-01

    This abstract describes work that will be done by the Applied Meteorology Unit (AMU) in assessing the success of different model configurations in predicting "wind cycling" cases at Edwards Air Force Base, CA (EAFB), in which the wind speeds and directions oscillate among towers near the EAFB runway. The Weather Research and Forecasting (WRF) model allows users to choose among two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model - the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Having a series of initialization options and WRF cores, as well as many options within each core, creates challenges for local forecasters, such as determining which configuration options are best to address specific forecast concerns. The goal of this project is to assess the different configurations available and determine which configuration will best predict surface wind speed and direction at EAFB.

  17. Modeling very large-fire occurrences over the continental United States from weather and climate forcing

    International Nuclear Information System (INIS)

    Barbero, R; Abatzoglou, J T; Steel, E A; K Larkin, Narasimhan

    2014-01-01

    Very large-fires (VLFs) have widespread impacts on ecosystems, air quality, fire suppression resources, and in many regions account for a majority of total area burned. Empirical generalized linear models of the largest fires (>5000 ha) across the contiguous United States (US) were developed at ∼60 km spatial and weekly temporal resolutions using solely atmospheric predictors. Climate−fire relationships on interannual timescales were evident, with wetter conditions than normal in the previous growing season enhancing VLFs probability in rangeland systems and with concurrent long-term drought enhancing VLFs probability in forested systems. Information at sub-seasonal timescales further refined these relationships, with short-term fire weather being a significant predictor in rangelands and fire danger indices linked to dead fuel moisture being a significant predictor in forested lands. Models demonstrated agreement in capturing the observed spatial and temporal variability including the interannual variability of VLF occurrences within most ecoregions. Furthermore the model captured the observed increase in VLF occurrences across parts of the southwestern and southeastern US from 1984 to 2010 suggesting that, irrespective of changes in fuels and land management, climatic factors have become more favorable for VLF occurrence over the past three decades in some regions. Our modeling framework provides a basis for simulations of future VLF occurrences from climate projections. (letter)

  18. Analysis of errors introduced by geographic coordinate systems on weather numeric prediction modeling

    Directory of Open Access Journals (Sweden)

    Y. Cao

    2017-09-01

    Full Text Available Most atmospheric models, including the Weather Research and Forecasting (WRF model, use a spherical geographic coordinate system to internally represent input data and perform computations. However, most geographic information system (GIS input data used by the models are based on a spheroid datum because it better represents the actual geometry of the earth. WRF and other atmospheric models use these GIS input layers as if they were in a spherical coordinate system without accounting for the difference in datum. When GIS layers are not properly reprojected, latitudinal errors of up to 21 km in the midlatitudes are introduced. Recent studies have suggested that for very high-resolution applications, the difference in datum in the GIS input data (e.g., terrain land use, orography should be taken into account. However, the magnitude of errors introduced by the difference in coordinate systems remains unclear. This research quantifies the effect of using a spherical vs. a spheroid datum for the input GIS layers used by WRF to study greenhouse gas transport and dispersion in northeast Pennsylvania.

  19. Validation of mixing heights derived from the operational NWP models at the German weather service

    Energy Technology Data Exchange (ETDEWEB)

    Fay, B.; Schrodin, R.; Jacobsen, I. [Deutscher Wetterdienst, Offenbach (Germany); Engelbart, D. [Deutscher Wetterdienst, Meteorol. Observ. Lindenberg (Germany)

    1997-10-01

    NWP models incorporate an ever-increasing number of observations via four-dimensional data assimilation and are capable of providing comprehensive information about the atmosphere both in space and time. They describe not only near surface parameters but also the vertical structure of the atmosphere. They operate daily, are well verified and successfully used as meteorological pre-processors in large-scale dispersion modelling. Applications like ozone forecasts, emission or power plant control calculations require highly resolved, reliable, and routine values of the temporal evolution of the mixing height (MH) which is a critical parameter in determining the mixing and transformation of substances and the resulting pollution levels near the ground. The purpose of development at the German Weather Service is a straightforward mixing height scheme that uses only parameters derived from NWP model variables and thus automatically provides spatial and temporal fields of mixing heights on an operational basis. An universal parameter to describe stability is the Richardson number Ri. Compared to the usual diagnostic or rate equations, the Ri number concept of determining mixing heights has the advantage of using not only surface layer parameters but also regarding the vertical structure of the boundary layer resolved in the NWP models. (au)

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

    Science.gov (United States)

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

    2016-12-01

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

  1. Strategies for Effective Implementation of Science Models into 6-9 Grade Classrooms on Climate, Weather, and Energy Topics

    Science.gov (United States)

    Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.

    2011-12-01

    As atmospheric scientists, we depend on Numerical Weather Prediction (NWP) models. We use them to predict weather patterns, to understand external forcing on the atmosphere, and as evidence to make claims about atmospheric phenomenon. Therefore, it is important that we adequately prepare atmospheric science students to use computer models. However, the public should also be aware of what models are in order to understand scientific claims about atmospheric issues, such as climate change. Although familiar with weather forecasts on television and the Internet, the general public does not understand the process of using computer models to generate a weather and climate forecasts. As a result, the public often misunderstands claims scientists make about their daily weather as well as the state of climate change. Since computer models are the best method we have to forecast the future of our climate, scientific models and modeling should be a topic covered in K-12 classrooms as part of a comprehensive science curriculum. According to the National Science Education Standards, teachers are encouraged to science models into the classroom as a way to aid in the understanding of the nature of science. However, there is very little description of what constitutes a science model, so the term is often associated with scale models. Therefore, teachers often use drawings or scale representations of physical entities, such as DNA, the solar system, or bacteria. In other words, models used in classrooms are often used as visual representations, but the purpose of science models is often overlooked. The implementation of a model-based curriculum in the science classroom can be an effective way to prepare students to think critically, problem solve, and make informed decisions as a contributing member of society. However, there are few resources available to help teachers implement science models into the science curriculum effectively. Therefore, this research project looks at

  2. Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

    Science.gov (United States)

    Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

    2017-12-01

    The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

  3. Machine learning and linear regression models to predict catchment-level base cation weathering rates across the southern Appalachian Mountain region, USA

    Science.gov (United States)

    Nicholas A. Povak; Paul F. Hessburg; Todd C. McDonnell; Keith M. Reynolds; Timothy J. Sullivan; R. Brion Salter; Bernard J. Crosby

    2014-01-01

    Accurate estimates of soil mineral weathering are required for regional critical load (CL) modeling to identify ecosystems at risk of the deleterious effects from acidification. Within a correlative modeling framework, we used modeled catchment-level base cation weathering (BCw) as the response variable to identify key environmental correlates and predict a continuous...

  4. Tile Low Rank Cholesky Factorization for Climate/Weather Modeling Applications on Manycore Architectures

    KAUST Repository

    Akbudak, Kadir; Ltaief, Hatem; Mikhalev, Aleksandr; Keyes, David E.

    2017-01-01

    Covariance matrices are ubiquitous in computational science and engineering. In particular, large covariance matrices arise from multivariate spatial data sets, for instance, in climate/weather modeling applications to improve prediction using statistical methods and spatial data. One of the most time-consuming computational steps consists in calculating the Cholesky factorization of the symmetric, positive-definite covariance matrix problem. The structure of such covariance matrices is also often data-sparse, in other words, effectively of low rank, though formally dense. While not typically globally of low rank, covariance matrices in which correlation decays with distance are nearly always hierarchically of low rank. While symmetry and positive definiteness should be, and nearly always are, exploited for performance purposes, exploiting low rank character in this context is very recent, and will be a key to solving these challenging problems at large-scale dimensions. The authors design a new and flexible tile row rank Cholesky factorization and propose a high performance implementation using OpenMP task-based programming model on various leading-edge manycore architectures. Performance comparisons and memory footprint saving on up to 200K×200K covariance matrix size show a gain of more than an order of magnitude for both metrics, against state-of-the-art open-source and vendor optimized numerical libraries, while preserving the numerical accuracy fidelity of the original model. This research represents an important milestone in enabling large-scale simulations for covariance-based scientific applications.

  5. Predicting the Storm Surge Threat of Hurricane Sandy with the National Weather Service SLOSH Model

    Directory of Open Access Journals (Sweden)

    Cristina Forbes

    2014-05-01

    Full Text Available Numerical simulations of the storm tide that flooded the US Atlantic coastline during Hurricane Sandy (2012 are carried out using the National Weather Service (NWS Sea Lakes and Overland Surges from Hurricanes (SLOSH storm surge prediction model to quantify its ability to replicate the height, timing, evolution and extent of the water that was driven ashore by this large, destructive storm. Recent upgrades to the numerical model, including the incorporation of astronomical tides, are described and simulations with and without these upgrades are contrasted to assess their contributions to the increase in forecast accuracy. It is shown, through comprehensive verifications of SLOSH simulation results against peak water surface elevations measured at the National Oceanic and Atmospheric Administration (NOAA tide gauge stations, by storm surge sensors deployed and hundreds of high water marks collected by the U.S. Geological Survey (USGS, that the SLOSH-simulated water levels at 71% (89% of the data measurement locations have less than 20% (30% relative error. The RMS error between observed and modeled peak water levels is 0.47 m. In addition, the model’s extreme computational efficiency enables it to run large, automated ensembles of predictions in real-time to account for the high variability that can occur in tropical cyclone forecasts, thus furnishing a range of values for the predicted storm surge and inundation threat.

  6. Future intensification of hydro-meteorological extremes: downscaling using the weather research and forecasting model

    KAUST Repository

    El-Samra, R.

    2017-02-15

    A set of ten downscaling simulations at high spatial resolution (3 km horizontally) were performed using the Weather Research and Forecasting (WRF) model to generate future climate projections of annual and seasonal temperature and precipitation changes over the Eastern Mediterranean (with a focus on Lebanon). The model was driven with the High Resolution Atmospheric Model (HiRAM), running over the whole globe at a resolution of 25 km, under the conditions of two Representative Concentration Pathways (RCP) (4.5 and 8.5). Each downscaling simulation spanned one year. Two past years (2003 and 2008), also forced by HiRAM without data assimilation, were simulated to evaluate the model’s ability to capture the cold and wet (2003) and hot and dry (2008) extremes. The downscaled data were in the range of recent observed climatic variability, and therefore corrected for the cold bias of HiRAM. Eight future years were then selected based on an anomaly score that relies on the mean annual temperature and accumulated precipitation to identify the worst year per decade from a water resources perspective. One hot and dry year per decade, from 2011 to 2050, and per scenario was simulated and compared to the historic 2008 reference. The results indicate that hot and dry future extreme years will be exacerbated and the study area might be exposed to a significant decrease in annual precipitation (rain and snow), reaching up to 30% relative to the current extreme conditions.

  7. Tile Low Rank Cholesky Factorization for Climate/Weather Modeling Applications on Manycore Architectures

    KAUST Repository

    Akbudak, Kadir

    2017-05-11

    Covariance matrices are ubiquitous in computational science and engineering. In particular, large covariance matrices arise from multivariate spatial data sets, for instance, in climate/weather modeling applications to improve prediction using statistical methods and spatial data. One of the most time-consuming computational steps consists in calculating the Cholesky factorization of the symmetric, positive-definite covariance matrix problem. The structure of such covariance matrices is also often data-sparse, in other words, effectively of low rank, though formally dense. While not typically globally of low rank, covariance matrices in which correlation decays with distance are nearly always hierarchically of low rank. While symmetry and positive definiteness should be, and nearly always are, exploited for performance purposes, exploiting low rank character in this context is very recent, and will be a key to solving these challenging problems at large-scale dimensions. The authors design a new and flexible tile row rank Cholesky factorization and propose a high performance implementation using OpenMP task-based programming model on various leading-edge manycore architectures. Performance comparisons and memory footprint saving on up to 200K×200K covariance matrix size show a gain of more than an order of magnitude for both metrics, against state-of-the-art open-source and vendor optimized numerical libraries, while preserving the numerical accuracy fidelity of the original model. This research represents an important milestone in enabling large-scale simulations for covariance-based scientific applications.

  8. Numerical simulation of rainfall and temperature over Kenya using weather research and forecasting-environmental modelling system (WRF-EMS

    Directory of Open Access Journals (Sweden)

    Sagero Obaigwa Philip

    2016-01-01

    Full Text Available This paper focuses on one of the high resolution models used for weather forecasting at Kenya Meteorological Department (KMD. It reviews the skill and accuracy of the Weather Research and Forecasting (WRF - Environmental Modeling System (EMS model, in simulating weather over Kenya. The study period was March to May 2011, during the rainy season over Kenya. The model output was compared with the observed data from 27 synoptic stations spread over the study area, to determine the performance of the model in terms of its skill and accuracy in forecasting. The spatial distribution of rainfall and temperature showed that the WRF model was capable of reproducing the observed general pattern especially for temperature. The model has skill in forecasting both rainfall and temperature over the study area. However, the model may underestimate rainfall of more than 10 mm/day and displace its location and overestimate rainfall of less than 1 mm/day. Therefore, during the period of enhanced rainfall especially in the month of April and part of May the model forecast needs to be complemented by other models or forecasting methods before giving a forecast. There is need to improve its performance over the domain through review of the parameterization of small scale physical processes and more observed data need to be simulated into the model.

  9. 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.

  10. Parameterizing road construction in route-based road weather models: can ground-penetrating radar provide any answers?

    International Nuclear Information System (INIS)

    Hammond, D S; Chapman, L; Thornes, J E

    2011-01-01

    A ground-penetrating radar (GPR) survey of a 32 km mixed urban and rural study route is undertaken to assess the usefulness of GPR as a tool for parameterizing road construction in a route-based road weather forecast model. It is shown that GPR can easily identify even the smallest of bridges along the route, which previous thermal mapping surveys have identified as thermal singularities with implications for winter road maintenance. Using individual GPR traces measured at each forecast point along the route, an inflexion point detection algorithm attempts to identify the depth of the uppermost subsurface layers at each forecast point for use in a road weather model instead of existing ordinal road-type classifications. This approach has the potential to allow high resolution modelling of road construction and bridge decks on a scale previously not possible within a road weather model, but initial results reveal that significant future research will be required to unlock the full potential that this technology can bring to the road weather industry. (technical design note)

  11. Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria

    Czech Academy of Sciences Publication Activity Database

    Eitzinger, Josef; Thaler, S.; Schmid, E.; Strauss, F.; Ferrise, R.; Moriondo, M.; Bindi, M.; Palosuo, T.; Rötter, R.; Kersebaum, K. C.; Olesen, J. E.; Patil, R. H.; Saylan, L.; Çaldag, B.; Caylak, O.

    2013-01-01

    Roč. 151, č. 6 (2013), s. 813-835 ISSN 0021-8596 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073 Institutional support: RVO:67179843 Keywords : crop models * weather conditions * winter wheat * Austria Subject RIV: EH - Ecology, Behaviour Impact factor: 2.891, year: 2013

  12. Preliminary results of an attempt to provide soil moisture datasets in order to verify numerical weather prediction models

    International Nuclear Information System (INIS)

    Cassardo, C.; Loglisci, N.

    2005-01-01

    In the recent years, there has been a significant growth in the recognition of the soil moisture importance in large-scale hydrology and climate modelling. Soil moisture is a lower boundary condition, which rules the partitioning of energy in terms of sensible and latent heat flux. Wrong estimations of soil moisture lead to wrong simulation of the surface layer evolution and hence precipitations and cloud cover forecasts could be consequently affected. This is true for large scale medium-range weather forecasts as well as for local-scale short range weather forecasts, particularly in those situations in which local convection is well developed. Unfortunately; despite the importance of this physical parameter there are only few soil moisture data sets sparse in time and in space around in the world. Due to this scarcity of soil moisture observations, we developed an alternative method to provide soil moisture datasets in order to verify numerical weather prediction models. In this paper are presented the preliminary results of an attempt to verify soil moisture fields predicted by a mesoscale model. The data for the comparison were provided by the simulations of the diagnostic land surface scheme LSPM (Land Surface Process Model), widely used at the Piedmont Regional Weather Service for agro-meteorological purposes. To this end, LSPM was initialized and driven by Synop observations, while the surface (vegetation and soil) parameter values were initialized by ECOCLIMAP global dataset at 1km 2 resolution

  13. Simulation of Flash-Flood-Producing Storm Events in Saudi Arabia Using the Weather Research and Forecasting Model

    KAUST Repository

    Deng, Liping; McCabe, Matthew; Stenchikov, Georgiy L.; Evans, Jason P.; Kucera, Paul A.

    2015-01-01

    The challenges of monitoring and forecasting flash-flood-producing storm events in data-sparse and arid regions are explored using the Weather Research and Forecasting (WRF) Model (version 3.5) in conjunction with a range of available satellite

  14. A New Framework to Compare Mass-Flux Schemes Within the AROME Numerical Weather Prediction Model

    Science.gov (United States)

    Riette, Sébastien; Lac, Christine

    2016-08-01

    In the Application of Research to Operations at Mesoscale (AROME) numerical weather forecast model used in operations at Météo-France, five mass-flux schemes are available to parametrize shallow convection at kilometre resolution. All but one are based on the eddy-diffusivity-mass-flux approach, and differ in entrainment/detrainment, the updraft vertical velocity equation and the closure assumption. The fifth is based on a more classical mass-flux approach. Screen-level scores obtained with these schemes show few discrepancies and are not sufficient to highlight behaviour differences. Here, we describe and use a new experimental framework, able to compare and discriminate among different schemes. For a year, daily forecast experiments were conducted over small domains centred on the five French metropolitan radio-sounding locations. Cloud base, planetary boundary-layer height and normalized vertical profiles of specific humidity, potential temperature, wind speed and cloud condensate were compared with observations, and with each other. The framework allowed the behaviour of the different schemes in and above the boundary layer to be characterized. In particular, the impact of the entrainment/detrainment formulation, closure assumption and cloud scheme were clearly visible. Differences mainly concerned the transport intensity thus allowing schemes to be separated into two groups, with stronger or weaker updrafts. In the AROME model (with all interactions and the possible existence of compensating errors), evaluation diagnostics gave the advantage to the first group.

  15. Spatial analysis and modeling to assess and map current vulnerability to extreme weather events in the Grijalva - Usumacinta watershed, Mexico

    International Nuclear Information System (INIS)

    Lopez L, D

    2009-01-01

    One of the major concerns over a potential change in climate is that it will cause an increase in extreme weather events. In Mexico, the exposure factors as well as the vulnerability to the extreme weather events have increased during the last three or four decades. In this study spatial analysis and modeling were used to assess and map settlement and crop systems vulnerability to extreme weather events in the Grijalva - Usumacinta watershed. Sensitivity and coping adaptive capacity maps were constructed using decision models; these maps were then combined to produce vulnerability maps. The most vulnerable area in terms of both settlement and crop systems is the highlands, where the sensitivity is high and the adaptive capacity is low. In lowlands, despite the very high sensitivity, the higher adaptive capacity produces only moderate vulnerability. I conclude that spatial analysis and modeling are powerful tools to assess and map vulnerability. These preliminary results can guide the formulation of adaptation policies to an increasing risk of extreme weather events.

  16. Spatial analysis and modeling to assess and map current vulnerability to extreme weather events in the Grijalva - Usumacinta watershed, Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Lopez L, D, E-mail: dlopez@centrogeo.org.m [Centro de Investigacion en GeografIa y Geomatica, Ing. Jorge L. Tamayo A.C., Contoy 137, col. Lomas de Padierna, del Tlalpan, Maxico D.F (Mexico)

    2009-11-01

    One of the major concerns over a potential change in climate is that it will cause an increase in extreme weather events. In Mexico, the exposure factors as well as the vulnerability to the extreme weather events have increased during the last three or four decades. In this study spatial analysis and modeling were used to assess and map settlement and crop systems vulnerability to extreme weather events in the Grijalva - Usumacinta watershed. Sensitivity and coping adaptive capacity maps were constructed using decision models; these maps were then combined to produce vulnerability maps. The most vulnerable area in terms of both settlement and crop systems is the highlands, where the sensitivity is high and the adaptive capacity is low. In lowlands, despite the very high sensitivity, the higher adaptive capacity produces only moderate vulnerability. I conclude that spatial analysis and modeling are powerful tools to assess and map vulnerability. These preliminary results can guide the formulation of adaptation policies to an increasing risk of extreme weather events.

  17. Fractionaly Integrated Flux model and Scaling Laws in Weather and Climate

    Science.gov (United States)

    Schertzer, Daniel; Lovejoy, Shaun

    2013-04-01

    The Fractionaly Integrated Flux model (FIF) has been extensively used to model intermittent observables, like the velocity field, by defining them with the help of a fractional integration of a conservative (i.e. strictly scale invariant) flux, such as the turbulent energy flux. It indeed corresponds to a well-defined modelling that yields the observed scaling laws. Generalised Scale Invariance (GSI) enables FIF to deal with anisotropic fractional integrations and has been rather successful to define and model a unique regime of scaling anisotropic turbulence up to planetary scales. This turbulence has an effective dimension of 23/9=2.55... instead of the classical hypothesised 2D and 3D turbulent regimes, respectively for large and small spatial scales. It therefore theoretically eliminates a non plausible "dimension transition" between these two regimes and the resulting requirement of a turbulent energy "mesoscale gap", whose empirical evidence has been brought more and more into question. More recently, GSI-FIF was used to analyse climate, therefore at much larger time scales. Indeed, the 23/9-dimensional regime necessarily breaks up at the outer spatial scales. The corresponding transition range, which can be called "macroweather", seems to have many interesting properties, e.g. it rather corresponds to a fractional differentiation in time with a roughly flat frequency spectrum. Furthermore, this transition yields the possibility to have at much larger time scales scaling space-time climate fluctuations with a much stronger scaling anisotropy between time and space. Lovejoy, S. and D. Schertzer (2013). The Weather and Climate: Emergent Laws and Multifractal Cascades. Cambridge Press (in press). Schertzer, D. et al. (1997). Fractals 5(3): 427-471. Schertzer, D. and S. Lovejoy (2011). International Journal of Bifurcation and Chaos 21(12): 3417-3456.

  18. Wind gust estimation by combining numerical weather prediction model and statistical post-processing

    Science.gov (United States)

    Patlakas, Platon; Drakaki, Eleni; Galanis, George; Spyrou, Christos; Kallos, George

    2017-04-01

    The continuous rise of off-shore and near-shore activities as well as the development of structures, such as wind farms and various offshore platforms, requires the employment of state-of-the-art risk assessment techniques. Such analysis is used to set the safety standards and can be characterized as a climatologically oriented approach. Nevertheless, a reliable operational support is also needed in order to minimize cost drawbacks and human danger during the construction and the functioning stage as well as during maintenance activities. One of the most important parameters for this kind of analysis is the wind speed intensity and variability. A critical measure associated with this variability is the presence and magnitude of wind gusts as estimated in the reference level of 10m. The latter can be attributed to different processes that vary among boundary-layer turbulence, convection activities, mountain waves and wake phenomena. The purpose of this work is the development of a wind gust forecasting methodology combining a Numerical Weather Prediction model and a dynamical statistical tool based on Kalman filtering. To this end, the parameterization of Wind Gust Estimate method was implemented to function within the framework of the atmospheric model SKIRON/Dust. The new modeling tool combines the atmospheric model with a statistical local adaptation methodology based on Kalman filters. This has been tested over the offshore west coastline of the United States. The main purpose is to provide a useful tool for wind analysis and prediction and applications related to offshore wind energy (power prediction, operation and maintenance). The results have been evaluated by using observational data from the NOAA's buoy network. As it was found, the predicted output shows a good behavior that is further improved after the local adjustment post-process.

  19. Evaluating accuracy of DSSAT model for soybean yield estimation using satellite weather data

    Science.gov (United States)

    Ovando, Gustavo; Sayago, Silvina; Bocco, Mónica

    2018-04-01

    Crop models allow simulating the development and yield of the crops, to represent and to evaluate the influence of multiple factors. The DSSAT cropping system model is one of the most widely used and contains CROPGRO module for soybean. This crop has a great importance for many southern countries of Latin America and for Argentina. Solar radiation and rainfall are necessary variables as inputs for crop models; however these data are not as readily available. The satellital products from Clouds and Earth's Radiant Energy System (CERES) and Tropic Rainfall Measurement Mission (TRMM) provide continuous spatial and temporal information of solar radiation and precipitation, respectively. This study evaluates and quantifies the uncertainty in estimating soybean yield using a DSSAT model, when recorded weather data are replaced with CERES and TRMM ones. Different percentages of data replacements, soybean maturity groups and planting dates are considered, for 2006-2016 period in Oliveros (Argentina). Results show that CERES and TRMM products can be used for soybean yield estimation with DSSAT considering that: percentage of data replacement, campaign, planting date and maturity group, determine the amounts and trends of yield errors. Replacements with CERES data up to 30% result in %RMSE lower than 10% in 87% of the cases; while the replacement with TRMM data presents the best statisticals in campaigns with high yields. Simulations based entirely on CERES solar radiation give better results than those with TRMM. In general, similar percentages of replacement show better performance in the estimation of soybean yield for solar radiation than the replacement of precipitation values.

  20. Use of medium-range numerical weather prediction model output to produce forecasts of streamflow

    Science.gov (United States)

    Clark, M.P.; Hay, L.E.

    2004-01-01

    This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output for predictions of streamflow. This analysis shows the biases in the NCEP forecasts to be quite extreme. In many regions, systematic precipitation biases exceed 100% of the mean, with temperature biases exceeding 3??C. In some locations, biases are even higher. The accuracy of NCEP precipitation and 2-m maximum temperature forecasts is computed by interpolating the NCEP model output for each forecast day to the location of each station in the NWS cooperative network and computing the correlation with station observations. Results show that the accuracy of the NCEP forecasts is rather low in many areas of the country. Most apparent is the generally low skill in precipitation forecasts (particularly in July) and low skill in temperature forecasts in the western United States, the eastern seaboard, and the southern tier of states. These results outline a clear need for additional processing of the NCEP Medium-Range Forecast Model (MRF) output before it is used for hydrologic predictions. Techniques of model output statistics (MOS) are used in this paper to downscale the NCEP forecasts to station locations. Forecasted atmospheric variables (e.g., total column precipitable water, 2-m air temperature) are used as predictors in a forward screening multiple linear regression model to improve forecasts of precipitation and temperature for stations in the National Weather Service cooperative network. This procedure effectively removes all systematic biases in the raw NCEP precipitation and temperature forecasts. MOS guidance also results in substantial improvements in the accuracy of maximum and minimum temperature forecasts throughout the country. For precipitation, forecast improvements were less impressive. MOS guidance increases

  1. A model for the identification of tropical weather systems over South ...

    African Journals Online (AJOL)

    drinie

    2002-07-03

    Jul 3, 2002 ... with, these two high-pressure systems, controls to a large extent, the weather of ... researchers provided general rules to differentiate between tropical- ..... inclusion of this graph therefore does not serve as a verification of.

  2. An Integrated Decision-Making Model for Categorizing Weather Products and Decision Aids

    Science.gov (United States)

    Elgin, Peter D.; Thomas, Rickey P.

    2004-01-01

    The National Airspace System s capacity will experience considerable growth in the next few decades. Weather adversely affects safe air travel. The FAA and NASA are working to develop new technologies that display weather information to support situation awareness and optimize pilot decision-making in avoiding hazardous weather. Understanding situation awareness and naturalistic decision-making is an important step in achieving this goal. Information representation and situation time stress greatly influence attentional resource allocation and working memory capacity, potentially obstructing accurate situation awareness assessments. Three naturalistic decision-making theories were integrated to provide an understanding of the levels of decision making incorporated in three operational situations and two conditions. The task characteristics associated with each phase of flight govern the level of situation awareness attained and the decision making processes utilized. Weather product s attributes and situation task characteristics combine to classify weather products according to the decision-making processes best supported. In addition, a graphical interface is described that affords intuitive selection of the appropriate weather product relative to the pilot s current flight situation.

  3. Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

    Science.gov (United States)

    Li, Xia; Mitra, Chandana; Dong, Li; Yang, Qichun

    2018-02-01

    To explore potential climatic consequences of land cover change in the Kolkata Metropolitan Development area, we projected microclimate conditions in this area using the Weather Research and Forecasting (WRF) model driven by future land use scenarios. Specifically, we considered two land conversion scenarios including an urbanization scenario that all the wetlands and croplands would be converted to built-up areas, and an irrigation expansion scenario in which all wetlands and dry croplands would be replaced by irrigated croplands. Results indicated that land use and land cover (LULC) change would dramatically increase regional temperature in this area under the urbanization scenario, but expanded irrigation tended to have a cooling effect. In the urbanization scenario, precipitation center tended to move eastward and lead to increased rainfall in eastern parts of this region. Increased irrigation stimulated rainfall in central and eastern areas but reduced rainfall in southwestern and northwestern parts of the study area. This study also demonstrated that urbanization significantly reduced latent heat fluxes and albedo of land surface; while increased sensible heat flux changes following urbanization suggested that developed land surfaces mainly acted as heat sources. In this study, climate change projection not only predicts future spatiotemporal patterns of multiple climate factors, but also provides valuable insights into policy making related to land use management, water resource management, and agriculture management to adapt and mitigate future climate changes in this populous region.

  4. Bridging the Gap Between Research and Operations in the National Weather Service: The Huntsville Model

    Science.gov (United States)

    Darden, C.; Carroll, B.; Lapenta, W.; Jedlovec, G.; Goodman, S.; Bradshaw, T.; Gordon, J.; Arnold, James E. (Technical Monitor)

    2002-01-01

    The National Weather Service Office (WFO) in Huntsville, Alabama (HUN) is slated to begin full-time operations in early 2003. With the opening of the Huntsville WFO, a unique opportunity has arisen for close and productive collaboration with scientists at NASA Marshall Space Flight Center (MSFC) and the University of Alabama Huntsville (UAH). As a part of the collaboration effort, NASA has developed the Short-term Prediction Research and Transition (SPoRT) Center. The mission of the SPoRT center is to incorporate NASA earth science technology and research into the NWS operational environment. Emphasis will be on improving mesoscale and short-term forecasting in the first 24 hours of the forecast period. As part of the collaboration effort, the NWS and NASA will develop an implementation and evaluation plan to streamline the integration of the latest technologies and techniques into the operational forecasting environment. The desire of WFO HUN, NASA, and UAH is to provide a model for future collaborative activities between research and operational communities across the country.

  5. Modelling the perception of weather conditions by users of outdoor public spaces

    Science.gov (United States)

    Andrade, H.; Oliveira, S.; Alcoforado, M.-J.

    2009-09-01

    Outdoor public spaces play an important role for the quality of life in urban areas. Their usage depends, among other factors, on the bioclimatic comfort of the users. Climate change can modify the uses of outdoor spaces, by changing temperature and rainfall patterns. Understanding the way people perceive the microclimatic conditions is an important tool to the design of more comfortable outdoor spaces and in anticipating future needs to cope with climate change impacts. The perception of bioclimatic comfort by users of two different outdoor spaces was studied in Lisbon. A survey of about one thousand inquires was carried out simultaneously with weather measurements (air temperature, wind speed, relative humidity and solar and long wave radiation), during the years 2006 and 2007. The aim was to assess the relationships between weather variables, the individual characteristics of people (such as age and gender, among others) and their bioclimatic comfort. The perception of comfort was evaluated through the preference votes of the interviewees, which consisted on their answers concerning the desire to decrease, maintain or increase the values of the different weather parameters, in order to improve their comfort at the moment of the interview. The perception of the atmospheric conditions and of the bioclimatic comfort are highly influenced by subjective factors, which are difficult to integrate in a model. Nonetheless, the use of the multiple logistic regression allows the definition of patterns in the quantitative relation between preference votes and environmental and personal parameters. The thermal preference depends largely on the season and is associated with wind speed. Comfort in relation to wind depends not only on the speed but also on turbulence: a high variability in wind speed is generally perceived as uncomfortable. It was also found that the acceptability of warmer conditions is higher than for cooler conditions and the majority of people declared

  6. Statistical analysis and modelling of weather radar beam propagation conditions in the Po Valley (Italy

    Directory of Open Access Journals (Sweden)

    A. Fornasiero

    2006-01-01

    Full Text Available Ground clutter caused by anomalous propagation (anaprop can affect seriously radar rain rate estimates, particularly in fully automatic radar processing systems, and, if not filtered, can produce frequent false alarms. A statistical study of anomalous propagation detected from two operational C-band radars in the northern Italian region of Emilia Romagna is discussed, paying particular attention to its diurnal and seasonal variability. The analysis shows a high incidence of anaprop in summer, mainly in the morning and evening, due to the humid and hot summer climate of the Po Valley, particularly in the coastal zone. Thereafter, a comparison between different techniques and datasets to retrieve the vertical profile of the refractive index gradient in the boundary layer is also presented. In particular, their capability to detect anomalous propagation conditions is compared. Furthermore, beam path trajectories are simulated using a multilayer ray-tracing model and the influence of the propagation conditions on the beam trajectory and shape is examined. High resolution radiosounding data are identified as the best available dataset to reproduce accurately the local propagation conditions, while lower resolution standard TEMP data suffers from interpolation degradation and Numerical Weather Prediction model data (Lokal Model are able to retrieve a tendency to superrefraction but not to detect ducting conditions. Observing the ray tracing of the centre, lower and upper limits of the radar antenna 3-dB half-power main beam lobe it is concluded that ducting layers produce a change in the measured volume and in the power distribution that can lead to an additional error in the reflectivity estimate and, subsequently, in the estimated rainfall rate.

  7. Space Weathering of Super-Earths: Model Simulations of Exospheric Sodium Escape from 61 Virgo b

    Energy Technology Data Exchange (ETDEWEB)

    Yoneda, M.; Berdyugina, S.; Kuhn, J. [Kiepenheuer Institute for Solar Physics, Schöneckstraße 6, 79104 Freiburg im Breisgau (Germany)

    2017-10-01

    Rocky exoplanets are expected to be eroded by space weather in a similar way as in the solar system. In particular, Mercury is one of the dramatically eroded planets whose material continuously escapes into its exosphere and further into space. This escape is well traced by sodium atoms scattering sunlight. Due to solar wind impact, micrometeorite impacts, photo-stimulated desorption and thermal desorption, sodium atoms are released from surface regolith. Some of these released sodium atoms are escaping from Mercury’s gravitational-sphere. They are dragged anti-Sun-ward and form a tail structure. We expect similar phenomena on exoplanets. The hot super-Earth 61 Vir b orbiting a G3V star at only 0.05 au may show a similar structure. Because of its small separation from the star, the sodium release mechanisms may be working more efficiently on hot super-Earths than on Mercury, although the strong gravitational force of Earth-sized or even more massive planets may be keeping sodium atoms from escaping from the planet. Here, we performed model simulations for Mercury (to verify our model) and 61 Vir b as a representative super-Earth. We have found that sodium atoms can escape from this exoplanet due to stellar wind sputtering and micrometeorite impacts, to form a sodium tail. However, in contrast to Mercury, the tail on this hot super-Earth is strongly aligned with the anti-starward direction because of higher light pressure. Our model suggests that 61 Vir b seems to have an exo-base atmosphere like that of Mercury.

  8. Space Weathering of Super-Earths: Model Simulations of Exospheric Sodium Escape from 61 Virgo b

    International Nuclear Information System (INIS)

    Yoneda, M.; Berdyugina, S.; Kuhn, J.

    2017-01-01

    Rocky exoplanets are expected to be eroded by space weather in a similar way as in the solar system. In particular, Mercury is one of the dramatically eroded planets whose material continuously escapes into its exosphere and further into space. This escape is well traced by sodium atoms scattering sunlight. Due to solar wind impact, micrometeorite impacts, photo-stimulated desorption and thermal desorption, sodium atoms are released from surface regolith. Some of these released sodium atoms are escaping from Mercury’s gravitational-sphere. They are dragged anti-Sun-ward and form a tail structure. We expect similar phenomena on exoplanets. The hot super-Earth 61 Vir b orbiting a G3V star at only 0.05 au may show a similar structure. Because of its small separation from the star, the sodium release mechanisms may be working more efficiently on hot super-Earths than on Mercury, although the strong gravitational force of Earth-sized or even more massive planets may be keeping sodium atoms from escaping from the planet. Here, we performed model simulations for Mercury (to verify our model) and 61 Vir b as a representative super-Earth. We have found that sodium atoms can escape from this exoplanet due to stellar wind sputtering and micrometeorite impacts, to form a sodium tail. However, in contrast to Mercury, the tail on this hot super-Earth is strongly aligned with the anti-starward direction because of higher light pressure. Our model suggests that 61 Vir b seems to have an exo-base atmosphere like that of Mercury.

  9. Predicting favorable conditions for early leaf spot of peanut using output from the Weather Research and Forecasting (WRF) model

    Science.gov (United States)

    Olatinwo, Rabiu O.; Prabha, Thara V.; Paz, Joel O.; Hoogenboom, Gerrit

    2012-03-01

    Early leaf spot of peanut ( Arachis hypogaea L.), a disease caused by Cercospora arachidicola S. Hori, is responsible for an annual crop loss of several million dollars in the southeastern United States alone. The development of early leaf spot on peanut and subsequent spread of the spores of C. arachidicola relies on favorable weather conditions. Accurate spatio-temporal weather information is crucial for monitoring the progression of favorable conditions and determining the potential threat of the disease. Therefore, the development of a prediction model for mitigating the risk of early leaf spot in peanut production is important. The specific objective of this study was to demonstrate the application of the high-resolution Weather Research and Forecasting (WRF) model for management of early leaf spot in peanut. We coupled high-resolution weather output of the WRF, i.e. relative humidity and temperature, with the Oklahoma peanut leaf spot advisory model in predicting favorable conditions for early leaf spot infection over Georgia in 2007. Results showed a more favorable infection condition in the southeastern coastline of Georgia where the infection threshold were met sooner compared to the southwestern and central part of Georgia where the disease risk was lower. A newly introduced infection threat index indicates that the leaf spot threat threshold was met sooner at Alma, GA, compared to Tifton and Cordele, GA. The short-term prediction of weather parameters and their use in the management of peanut diseases is a viable and promising technique, which could help growers make accurate management decisions, and lower disease impact through optimum timing of fungicide applications.

  10. On The Development of One-way Nesting of Air-pollution Model Smog Into Numerical Weather Prediction Model Eta

    Science.gov (United States)

    Halenka, T.; Bednar, J.; Brechler, J.

    The spatial distribution of air pollution on the regional scale (Bohemian region) is simulated by means of Charles University puff model SMOG. The results are used for the assessment of the concentration fields of ozone, nitrogen oxides and other ozone precursors. Current improved version of the model covers up to 16 groups of basic compounds and it is based on trajectory computation and puff interaction both by means of Gaussian diffusion mixing and chemical reactions of basic species. Gener- ally, the method used for trajectory computation is valuable mainly for episodes sim- ulation, nevertheless, climatological study can be solved as well by means of average wind rose. For the study being presented huge database of real emission sources was incorporated with all kind of sources included. Some problem with the background values of concentrations was removed. The model SMOG has been nested into the forecast model ETA to obtain appropriate meteorological data input. We can estimate air pollution characteristics both for episodes analysis and the prediction of future air quality conditions. Necessary prognostic variables from the numerical weather pre- diction model are taken for the region of the central Bohemia, where the original puff model was tested. We used mainly 850 hPa wind field for computation of prognos- tic trajectories, the influence of surface temperature as a parameter of photochemistry reactions as well as the effect of cloudness has been tested.

  11. 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.

  12. Modelling natural electromagnetic interference in man-made conductors for space weather applications

    Science.gov (United States)

    Trichtchenko, Larisa

    2016-04-01

    Power transmission lines above the ground, cables and pipelines in the ground and under the sea, and in general all man-made long grounded conductors are exposed to the variations of the natural electromagnetic field. The resulting currents in the networks (commonly named geomagnetically induced currents, GIC), are produced by the conductive and/or inductive coupling and can compromise or even disrupt system operations and, in extreme cases, cause power blackouts, railway signalling mis-operation, or interfere with pipeline corrosion protection systems. To properly model the GIC in order to mitigate their impacts it is necessary to know the frequency dependence of the response of these systems to the geomagnetic variations which naturally span a wide frequency range. For that, the general equations of the electromagnetic induction in a multi-layered infinitely long cylinder (representing cable, power line wire, rail or pipeline) embedded in uniform media have been solved utilising methods widely used in geophysics. The derived electromagnetic fields and currents include the effects of the electromagnetic properties of each layer and of the different types of the surrounding media. This exact solution then has been used to examine the electromagnetic response of particular samples of long conducting structures to the external electromagnetic wave for a wide range of frequencies. Because the exact solution has a rather complicated structure, simple approximate analytical formulas have been proposed, analysed and compared with the results from the exact model. These approximate formulas show good coincidence in the frequency range spanning from geomagnetic storms (less than mHz) to pulsations (mHz to Hz) to atmospherics (kHz) and above, and can be recommended for use in space weather applications.

  13. Storm time dynamics of auroral electrojets: CHAMP observation and the Space Weather Modeling Framework comparison

    Directory of Open Access Journals (Sweden)

    H. Wang

    2008-03-01

    Full Text Available We investigate variations of the location and intensity of auroral currents during two magnetic storm periods based on magnetic field measurements from CHAMP separately for both hemispheres, as well as for the dayside and nightside. The corresponding auroral electrojet current densities are on average enhanced by about a factor of 7 compared to the quiet time current strengths. The nightside westward current densities are on average 1.8 (2.2 times larger than the dayside eastward current densities in the Northern (Southern Hemisphere. Both eastward and westward currents are present during the storm periods with the most intense electrojets appearing during the main phase of the storm, before the ring current maximizes in strength. The eastward and westward electrojet centers can expand to 55° MLat during intense storms, as is observed on 31 March 2001 with Dst=−387 nT. The equatorward shift of auroral currents on the dayside is closely controlled by the southward IMF, while the latitudinal variations on the nightside are better described by the variations of the Dst index. However, the equatorward and poleward motion of the nightside auroral currents occur earlier than the Dst variations. The Space Weather Modeling Framework (SWMF can capture the general dynamics of the storm time current variations. Both the model and the actual data show that the currents tend to saturate when the merging electric field is larger than 10 mV/m. However, the exact prediction of the temporal development of the currents is still not satisfactory.

  14. Storm time dynamics of auroral electrojets: CHAMP observation and the Space Weather Modeling Framework comparison

    Directory of Open Access Journals (Sweden)

    H. Wang

    2008-03-01

    Full Text Available We investigate variations of the location and intensity of auroral currents during two magnetic storm periods based on magnetic field measurements from CHAMP separately for both hemispheres, as well as for the dayside and nightside. The corresponding auroral electrojet current densities are on average enhanced by about a factor of 7 compared to the quiet time current strengths. The nightside westward current densities are on average 1.8 (2.2 times larger than the dayside eastward current densities in the Northern (Southern Hemisphere. Both eastward and westward currents are present during the storm periods with the most intense electrojets appearing during the main phase of the storm, before the ring current maximizes in strength. The eastward and westward electrojet centers can expand to 55° MLat during intense storms, as is observed on 31 March 2001 with Dst=−387 nT. The equatorward shift of auroral currents on the dayside is closely controlled by the southward IMF, while the latitudinal variations on the nightside are better described by the variations of the Dst index. However, the equatorward and poleward motion of the nightside auroral currents occur earlier than the Dst variations. The Space Weather Modeling Framework (SWMF can capture the general dynamics of the storm time current variations. Both the model and the actual data show that the currents tend to saturate when the merging electric field is larger than 10 mV/m. However, the exact prediction of the temporal development of the currents is still not satisfactory.

  15. Climate Variability and Weather Extremes: Model-Simulated and Historical Data. Chapter 9

    Science.gov (United States)

    Schubert, Siegfried D.; Lim, Young-Kwon

    2012-01-01

    basic mechanisms by which extremes vary is incomplete. As noted in IPCC (2007), Incomplete global data sets and remaining model uncertainties still restrict understanding of changes in extremes and attribution of changes to causes, although understanding of changes in the intensity, frequency and risk of extremes has improved. Separating decadal and other shorter-term variability from climate change impacts on extremes requires a better understanding of the processes responsible for the changes. In particular, the physical processes linking sea surface temperature changes to regional climate changes, and a basic understanding of the inherent variability in weather extremes and how that is impacted by atmospheric circulation changes at subseasonal to decadal and longer time scales, are still inadequately understood. Given the fundamental limitations in the time span and quality of global observations, substantial progress on these issues will rely increasingly on improvements in models, with observations continuing to play a critical role, though less as a detection tool, and more as a tool for addressing physical processes, and to insure the quality of the climate models and the verisimilitude of the simulations (CCSP SAP 1.3, 2008).

  16. Developing a Time Series Predictive Model for Dengue in Zhongshan, China Based on Weather and Guangzhou Dengue Surveillance Data.

    Science.gov (United States)

    Zhang, Yingtao; Wang, Tao; Liu, Kangkang; Xia, Yao; Lu, Yi; Jing, Qinlong; Yang, Zhicong; Hu, Wenbiao; Lu, Jiahai

    2016-02-01

    Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information. We obtained weekly dengue case data from 1st January, 2005 to 31st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC) curves and k-fold cross-validation. Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR) = 2.016, 95% Confidence Interval (CI): 1.845-2.203), controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC) for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938-0.967). The sensitivity and specificity

  17. Developing a Time Series Predictive Model for Dengue in Zhongshan, China Based on Weather and Guangzhou Dengue Surveillance Data.

    Directory of Open Access Journals (Sweden)

    Yingtao Zhang

    2016-02-01

    Full Text Available Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information.We obtained weekly dengue case data from 1st January, 2005 to 31st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC curves and k-fold cross-validation.Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR = 2.016, 95% Confidence Interval (CI: 1.845-2.203, controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938-0.967. The sensitivity and

  18. The HIRLAM fast radiation scheme for mesoscale numerical weather prediction models

    Science.gov (United States)

    Rontu, Laura; Gleeson, Emily; Räisänen, Petri; Pagh Nielsen, Kristian; Savijärvi, Hannu; Hansen Sass, Bent

    2017-07-01

    This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the model, without compromising on computational efficiency. In mesoscale models fast interactions between clouds and radiation and the surface and radiation can be of greater importance than accounting for the spectral details of clear-sky radiation; thus calling the routines more frequently can be of greater benefit than the deterioration due to loss of spectral details. Fast but physically based radiation parametrizations are expected to be valuable for high-resolution ensemble forecasting, because as well as the speed of their execution, they may provide realistic physical perturbations. Results from single-column diagnostic experiments based on CIRC benchmark cases and an evaluation of 10 years of radiation output from the FMI operational archive of HIRLAM forecasts indicate that HLRADIA performs sufficiently well with respect to the clear-sky downwelling SW and longwave LW fluxes at the surface. In general, HLRADIA tends to overestimate surface fluxes, with the exception of LW fluxes under cold and dry conditions. The most obvious overestimation of the surface SW flux was seen in the cloudy cases in the 10-year comparison; this bias may be related to using a cloud inhomogeneity correction, which was too large. According to the CIRC comparisons, the outgoing LW and SW fluxes at the top of atmosphere are mostly overestimated by HLRADIA and the net LW flux is underestimated above clouds. The absorption of SW radiation by the atmosphere seems to be underestimated and LW absorption seems to be overestimated. Despite these issues, the overall results are satisfying and work on the improvement of HLRADIA for the use in HARMONIE-AROME NWP system

  19. Applying volumetric weather radar data for rainfall runoff modeling: The importance of error correction.

    Science.gov (United States)

    Hazenberg, P.; Leijnse, H.; Uijlenhoet, R.; Delobbe, L.; Weerts, A.; Reggiani, P.

    2009-04-01

    data. It is expected that these difference are even larger when a distributed hydrological model is used. Therefore, we apply the representative elementary watershed (REW) model which has already been calibrated using raingauge data and shows the ability of correctly estimating discharge values both at the outlet and upstream points. The overall goal of this study is to make use of the benefits of the high spatial and temporal resolution of weather radar data compared to a conventional raingauge network in order to gain a better understanding of the hydrological behavior of the Ourthe catchment.

  20. A Mathematical Model and Algorithm for Routing Air Traffic Under Weather Uncertainty

    Science.gov (United States)

    Sadovsky, Alexander V.

    2016-01-01

    A central challenge in managing today's commercial en route air traffic is the task of routing the aircraft in the presence of adverse weather. Such weather can make regions of the airspace unusable, so all affected flights must be re-routed. Today this task is carried out by conference and negotiation between human air traffic controllers (ATC) responsible for the involved sectors of the airspace. One can argue that, in so doing, ATC try to solve an optimization problem without giving it a precise quantitative formulation. Such a formulation gives the mathematical machinery for constructing and verifying algorithms that are aimed at solving the problem. This paper contributes one such formulation and a corresponding algorithm. The algorithm addresses weather uncertainty and has closed form, which allows transparent analysis of correctness, realism, and computational costs.

  1. Evaluation of weather forecast systems for storm surge modeling in the Chesapeake Bay

    Science.gov (United States)

    Garzon, Juan L.; Ferreira, Celso M.; Padilla-Hernandez, Roberto

    2018-01-01

    Accurate forecast of sea-level heights in coastal areas depends, among other factors, upon a reliable coupling of a meteorological forecast system to a hydrodynamic and wave system. This study evaluates the predictive skills of the coupled circulation and wind-wave model system (ADCIRC+SWAN) for simulating storm tides in the Chesapeake Bay, forced by six different products: (1) Global Forecast System (GFS), (2) Climate Forecast System (CFS) version 2, (3) North American Mesoscale Forecast System (NAM), (4) Rapid Refresh (RAP), (5) European Center for Medium-Range Weather Forecasts (ECMWF), and (6) the Atlantic hurricane database (HURDAT2). This evaluation is based on the hindcasting of four events: Irene (2011), Sandy (2012), Joaquin (2015), and Jonas (2016). By comparing the simulated water levels to observations at 13 monitoring stations, we have found that the ADCIR+SWAN System forced by the following: (1) the HURDAT2-based system exhibited the weakest statistical skills owing to a noteworthy overprediction of the simulated wind speed; (2) the ECMWF, RAP, and NAM products captured the moment of the peak and moderately its magnitude during all storms, with a correlation coefficient ranging between 0.98 and 0.77; (3) the CFS system exhibited the worst averaged root-mean-square difference (excepting HURDAT2); (4) the GFS system (the lowest horizontal resolution product tested) resulted in a clear underprediction of the maximum water elevation. Overall, the simulations forced by NAM and ECMWF systems induced the most accurate results best accuracy to support water level forecasting in the Chesapeake Bay during both tropical and extra-tropical storms.

  2. Weather-Driven Variation in Dengue Activity in Australia Examined Using a Process-Based Modeling Approach

    Science.gov (United States)

    Bannister-Tyrrell, Melanie; Williams, Craig; Ritchie, Scott A.; Rau, Gina; Lindesay, Janette; Mercer, Geoff; Harley, David

    2013-01-01

    The impact of weather variation on dengue transmission in Cairns, Australia, was determined by applying a process-based dengue simulation model (DENSiM) that incorporated local meteorologic, entomologic, and demographic data. Analysis showed that inter-annual weather variation is one of the significant determinants of dengue outbreak receptivity. Cross-correlation analyses showed that DENSiM simulated epidemics of similar relative magnitude and timing to those historically recorded in reported dengue cases in Cairns during 1991–2009, (r = 0.372, P < 0.01). The DENSiM model can now be used to study the potential impacts of future climate change on dengue transmission. Understanding the impact of climate variation on the geographic range, seasonality, and magnitude of dengue transmission will enhance development of adaptation strategies to minimize future disease burden in Australia. PMID:23166197

  3. 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…

  4. 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…

  5. The Alligator rivers natural analogue - Modelling of uranium and thorium migration in the weathered zone at Koongarra

    International Nuclear Information System (INIS)

    Skagius, K.; Lindgren, M.; Boghammar, A.; Brandberg, F.; Pers, K.; Widen, H.

    1993-08-01

    The Koongarra Uranium Deposit in the Alligator Rivers Region in the Northern Territory of Australia is a natural analogue being investigated with the aim to contribute to the understanding of the scientific basis for the long term prediction of radionuclide migration within geological environments relevant to radioactive waste repositories. The dispersion of uranium and decay products in the weathered zone has been modelled with a simple advection-dispersion-reversible sorption model and with a model extended to also consider α-recoil and transfer of radionuclides between different mineral phases of the rock. The modelling work was carried out in several iterations, each including a review of available laboratory and field data, selection of the system to be modelled and suitable model, and a comparison of modelling results with field observations. Uranium concentrations in bulk rock calculated with the simple advection-dispersion- reversible sorption model were in fair agreement with observed data using parameter values within ranges recommended based on independent interpretations. The advection-dispersion-reversible sorption model is a large simplification of the system among other things because the partitioning of radionuclides between water and solid phase is described with a sorption equilibrium term only. Although the results from this study not are enough to validate simple performance assessment models in a strict sense, it has been shown that even simple models are able to describe the present day distribution of uranium in the weathered zone at Koongarra. 23 refs, 61 figs

  6. The Alligator rivers natural analogue - Modelling of uranium and thorium migration in the weathered zone at Koongarra

    Energy Technology Data Exchange (ETDEWEB)

    Skagius, K; Lindgren, M; Boghammar, A; Brandberg, F; Pers, K; Widen, H [Kemakta, Stockholm (Sweden)

    1993-08-01

    The Koongarra Uranium Deposit in the Alligator Rivers Region in the Northern Territory of Australia is a natural analogue being investigated with the aim to contribute to the understanding of the scientific basis for the long term prediction of radionuclide migration within geological environments relevant to radioactive waste repositories. The dispersion of uranium and decay products in the weathered zone has been modelled with a simple advection-dispersion-reversible sorption model and with a model extended to also consider {alpha}-recoil and transfer of radionuclides between different mineral phases of the rock. The modelling work was carried out in several iterations, each including a review of available laboratory and field data, selection of the system to be modelled and suitable model, and a comparison of modelling results with field observations. Uranium concentrations in bulk rock calculated with the simple advection-dispersion- reversible sorption model were in fair agreement with observed data using parameter values within ranges recommended based on independent interpretations. The advection-dispersion-reversible sorption model is a large simplification of the system among other things because the partitioning of radionuclides between water and solid phase is described with a sorption equilibrium term only. Although the results from this study not are enough to validate simple performance assessment models in a strict sense, it has been shown that even simple models are able to describe the present day distribution of uranium in the weathered zone at Koongarra. 23 refs, 61 figs.

  7. Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

    Science.gov (United States)

    Bell, Jordan R.; Case, Jonathan L.; Molthan, Andrew L.

    2011-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center develops new products and techniques that can be used in operational meteorology. The majority of these products are derived from NASA polar-orbiting satellite imagery from the Earth Observing System (EOS) platforms. One such product is a Greenness Vegetation Fraction (GVF) dataset, which is produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the new SPoRT-MODIS GVF dataset on land surface models apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. The second phase of the project is to examine the impacts of the SPoRT GVF dataset on NWP using the Weather Research and Forecasting (WRF) model. Two separate WRF model simulations were made for individual severe weather case days using the NCEP GVF (control) and SPoRT GVF (experimental), with all other model parameters remaining the same. Based on the sensitivity results in these case studies, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). The opposite was true

  8. Application of the Fractions Skill Score for Tracking the Effectiveness of Improvements Made to Weather Research and Forecasting Model Simulations

    Science.gov (United States)

    2017-11-22

    Sciences Directorate ATTN: RDRL-CIE-M White Sands Missile Range, NM 88002 8. PERFORMING ORGANIZATION REPORT NUMBER ARL-TR-8217 9. SPONSORING...assessment of the weather running estimate−nowcast (WRE−N). White Sands Missile Range (NM): Army Research Laboratory (US); 2016 Aug. Report No.: ARL-TR...observations into the model so that forecast quality is improved (Stauffer and Seaman 1994; Deng et al. 2009). The US Army Research Laboratory (ARL

  9. Winter weather demand considerations.

    Science.gov (United States)

    2015-04-01

    Winter weather has varied effects on travel behavior. Using 418 survey responses from the Northern Virginia : commuting area of Washington, D.C. and binary logit models, this study examines travel related changes under : different types of winter wea...

  10. Wind-Farm Forecasting Using the HARMONIE Weather Forecast Model and Bayes Model Averaging for Bias Removal.

    Science.gov (United States)

    O'Brien, Enda; McKinstry, Alastair; Ralph, Adam

    2015-04-01

    Building on previous work presented at EGU 2013 (http://www.sciencedirect.com/science/article/pii/S1876610213016068 ), more results are available now from a different wind-farm in complex terrain in southwest Ireland. The basic approach is to interpolate wind-speed forecasts from an operational weather forecast model (i.e., HARMONIE in the case of Ireland) to the precise location of each wind-turbine, and then use Bayes Model Averaging (BMA; with statistical information collected from a prior training-period of e.g., 25 days) to remove systematic biases. Bias-corrected wind-speed forecasts (and associated power-generation forecasts) are then provided twice daily (at 5am and 5pm) out to 30 hours, with each forecast validation fed back to BMA for future learning. 30-hr forecasts from the operational Met Éireann HARMONIE model at 2.5km resolution have been validated against turbine SCADA observations since Jan. 2014. An extra high-resolution (0.5km grid-spacing) HARMONIE configuration has been run since Nov. 2014 as an extra member of the forecast "ensemble". A new version of HARMONIE with extra filters designed to stabilize high-resolution configurations has been run since Jan. 2015. Measures of forecast skill and forecast errors will be provided, and the contributions made by the various physical and computational enhancements to HARMONIE will be quantified.

  11. Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

    Science.gov (United States)

    Bell, Jordan R.; Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.

    2012-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the SPoRT-MODIS GVF dataset on a land surface model (LSM) apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. In the West, higher latent heat fluxes prevailed, which enhanced the rates of evapotranspiration and soil moisture depletion in the LSM. By late Summer and Autumn, both the average sensible and latent heat fluxes increased in the West as a result of the more rapid soil drying and higher coverage of GVF. The impacts of the SPoRT GVF dataset on NWP was also examined for a single severe weather case study using the Weather Research and Forecasting (WRF) model. Two separate coupled LIS/WRF model simulations were made for the 17 July 2010 severe weather event in the Upper Midwest using the NCEP and SPoRT GVFs, with all other model parameters remaining the same. Based on the sensitivity results, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and

  12. 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.

  13. Modeling fire behavior on tropical islands with high-resolution weather data

    Science.gov (United States)

    John W. Benoit; Francis M. Fujioka; David R. Weise

    2009-01-01

    In this study, we consider fire behavior simulation in tropical island scenarios such as Hawaii and Puerto Rico. The development of a system to provide real-time fire behavior prediction in Hawaii is discussed. This involves obtaining fuels and topography information at a fine scale, as well as supplying daily high-resolution weather forecast data for the area of...

  14. Comparison of radar and numerical weather model rainfall forecasts in the perspective of urban flood prediction

    DEFF Research Database (Denmark)

    Lovring, Maite Monica; Löwe, Roland; Courdent, Vianney Augustin Thomas

    An early flood warning system has been developed for urban catchments and is currently running in online operation in Copenhagen. The system is highly dependent on the quality of rainfall forecast inputs. An investigation of precipitation inputs from Radar Nowcast (RN), Numerical Weather Prediction...

  15. Assesment of a soil moisture retrieval with numerical weather prediction model temperature

    Science.gov (United States)

    The effect of using a Numerical Weather Prediction (NWP) soil temperature product instead of estimates provided by concurrent 37 GHz data on satellite-based passive microwave retrieval of soil moisture retrieval was evaluated. This was prompted by the change in system configuration of preceding mult...

  16. Application of Volumetric Weather Radar Data and the Distributed Rainfall Runoff Model REW in the Ourthe Catchment

    Science.gov (United States)

    Hazenberg, P.; Leijnse, H.; Torfs, P.; Uijlenhoet, R.; Weerts, A.; Reggiani, P.; Delobbe, L.

    2008-12-01

    In the southern Ardennes region of Belgium near the border with Luxembourg, the Royal Meteorological Institute of Belgium (RMI) installed a C-band Doppler weather radar at an elevation of 600 m in the year 2001. This volumetric weather radar scans over multiple elevations at a temporal resolution of 5 minutes. The current study explores the possibility of using the volumetric information of the precipitation field to correct for the effects of the Vertical Profile of Reflectivity (VPR) over the period October 1, 2002 until March 31, 2003. During this winter half year storm events are mainly stratiform, giving rise to bright band effects which can decrease the performance of the radar. Previous studies have shown multiple drawbacks in applying a single estimated VPR profile to correct such reflectivity data. Therefore, the focus here is on the temporal variability of the VPR as measured by the radar and its variability over different spatial scales. This information is applied to generate a number of possible rainfall fields. These realizations are employed to try to quantify some of the discrepancies in precipitation intensities as estimated by the weather radar and those measured by a raingauge network. The final step then is to assess their potential within a distributed rainfall runoff model. The 1597 km2 Ourthe catchment lies within 60 km of the radar. Over this medium sized watershed ten raingauges measuring at an hourly interval are more or less equally distributed. Near the outlet discharge data are collected at the same time step. The distributed hydrological Representative Elementary Watershed (REW) model is applied to model the hydrological behavior of the Ourthe over the six month period. The benefits of the high spatial and temporal resolution of weather radar data compared to a conventional raingauge network plus the possibility of generating multiple realizations of the precipitation field are expected to yield more information about the hydrological

  17. Post-harvest quality model of pineapple guava fruit according to storage and weather conditions of cultivation

    Directory of Open Access Journals (Sweden)

    Alfonso Parra-Coronado

    Full Text Available ABSTRACT The post-harvest quality of pineapple guava fruit is determined by the storage and prevailing weather conditions during growth and development. This study proposes a model for post-harvest fruit quality according to the storage and weather conditions in the pineapple guava growing region. Physiologically ripe fruit were collected during two harvests from two locations within the Department of Cundinamarca (Colombia: Tenjo and San Francisco de Sales. The fruits were stored at 18 ± 1 °C (76 ± 5% relative humidity (RH, over 11 days and at 5 ± 1 °C (87 ± 5% RH, over 31 days, and the quality attributes were evaluated every two days. Models of the most significant physio-chemical quality characteristics of the post-harvest fruit were developed by using the Excel® Solver tool for all data obtained in the two crop periods. The results showed that storage and prevailing weather conditions, which differed according to the altitude of the growing site, had considerable impacts on the physio-chemical characteristics of the fruit throughout the post-harvest ripening process.

  18. Application of fuzzy – Neuro to model weather parameter variability impacts on electrical load based on long-term forecasting

    Directory of Open Access Journals (Sweden)

    Danladi Ali

    2018-03-01

    Full Text Available Long-term load forecasting provides vital information about future load and it helps the power industries to make decision regarding electrical energy generation and delivery. In this work, fuzzy – neuro model is developed to forecast a year ahead load in relation to weather parameter (temperature and humidity in Mubi, Adamawa State. It is observed that: electrical load increased with increase in temperature and relative humidity does not show notable effect on electrical load. The accuracy of the prediction is obtained at 98.78% with the corresponding mean absolute percentage error (MAPE of 1.22%. This confirms that fuzzy – neuro is a good tool for load forecasting. Keywords: Electrical load, Load forecasting, Fuzzy logic, Back propagation, Neuro-fuzzy, Weather parameter

  19. Frost Monitoring and Forecasting Using MODIS Land Surface Temperature Data and a Numerical Weather Prediction Model Forecasts for Eastern Africa

    Science.gov (United States)

    Kabuchanga, Eric; Flores, Africa; Malaso, Susan; Mungai, John; Sakwa, Vincent; Shaka, Ayub; Limaye, Ashutosh

    2014-01-01

    Frost is a major challenge across Eastern Africa, severely impacting agricultural farms. Frost damages have wide ranging economic implications on tea and coffee farms, which represent a major economic sector. Early monitoring and forecasting will enable farmers to take preventive actions to minimize the losses. Although clearly important, timely information on when to protect crops from freezing is relatively limited. MODIS Land Surface Temperature (LST) data, derived from NASA's Terra and Aqua satellites, and 72-hr weather forecasts from the Kenya Meteorological Service's operational Weather Research Forecast model are enabling the Regional Center for Mapping of Resources for Development (RCMRD) and the Tea Research Foundation of Kenya to provide timely information to farmers in the region. This presentation will highlight an ongoing collaboration among the Kenya Meteorological Service, RCMRD, and the Tea Research Foundation of Kenya to identify frost events and provide farmers with potential frost forecasts in Eastern Africa.

  20. Progress in Space Weather Modeling and Observations Needed to Improve the Operational NAIRAS Model Aircraft Radiation Exposure Predictions

    Science.gov (United States)

    Mertens, C. J.; Kress, B. T.; Wiltberger, M. J.; Tobiska, W.; Xu, X.

    2011-12-01

    The Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) is a prototype operational model for predicting commercial aircraft radiation exposure from galactic and solar cosmic rays. NAIRAS predictions are currently streaming live from the project's public website, and the exposure rate nowcast is also available on the SpaceWx smartphone app for iPhone, IPad, and Android. Cosmic rays are the primary source of human exposure to high linear energy transfer radiation at aircraft altitudes, which increases the risk of cancer and other adverse health effects. Thus, the NAIRAS model addresses an important national need with broad societal, public health and economic benefits. The processes responsible for the variability in the solar wind, interplanetary magnetic field, solar energetic particle spectrum, and the dynamical response of the magnetosphere to these space environment inputs, strongly influence the composition and energy distribution of the atmospheric ionizing radiation field. During the development of the NAIRAS model, new science questions were identified that must be addressed in order to obtain a more reliable and robust operational model of atmospheric radiation exposure. Addressing these science questions require improvements in both space weather modeling and observations. The focus of this talk is to present these science questions, the proposed methodologies for addressing these science questions, and the anticipated improvements to the operational predictions of atmospheric radiation exposure. The overarching goal of this work is to provide a decision support tool for the aviation industry that will enable an optimal balance to be achieved between minimizing health risks to passengers and aircrew while simultaneously minimizing costs to the airline companies.

  1. The representation of low-level clouds during the West African monsoon in weather and climate models

    Science.gov (United States)

    Kniffka, Anke; Hannak, Lisa; Knippertz, Peter; Fink, Andreas

    2016-04-01

    The West African monsoon is one of the most important large-scale circulation features in the tropics and the associated seasonal rainfalls are crucial to rain-fed agriculture and water resources for hundreds of millions of people. However, numerical weather and climate models still struggle to realistically represent salient features of the monsoon across a wide range of scales. Recently it has been shown that substantial errors in radiation and clouds exist in the southern parts of West Africa (8°W-8°E, 5-10°N) during summer. This area is characterised by strong low-level jets associated with the formation of extensive ultra-low stratus clouds. Often persisting long after sunrise, these clouds have a substantial impact on the radiation budget at the surface and thus the diurnal evolution of the planetary boundary layer (PBL). Here we present some first results from a detailed analysis of the representation of these clouds and the associated PBL features across a range of weather and climate models. Recent climate model simulations for the period 1991-2010 run in the framework of the Year of Tropical Convection (YOTC) offer a great opportunity for this analysis. The models are those used for the latest Assessment Report of the Intergovernmental Panel on Climate Change, but for YOTC the model output has a much better temporal resolution, allowing to resolve the diurnal cycle, and includes diabatic terms, allowing to much better assess physical reasons for errors in low-level temperature, moisture and thus cloudiness. These more statistical climate model analyses are complemented by experiments using ICON (Icosahedral non-hydrostatic general circulation model), the new numerical weather prediction model of the German Weather Service and the Max Planck Institute for Meteorology. ICON allows testing sensitivities to model resolution and numerical schemes. These model simulations are validated against (re-)analysis data, satellite observations (e.g. CM SAF cloud and

  2. Application of a COSMO Mesoscale Model to Assess the Influence of Forest Cover Changes on Regional Weather Conditions

    Science.gov (United States)

    Olchev, A.; Rozinkina, I.; Kuzmina, E.; Nikitin, M.; Rivin, G. S.

    2017-12-01

    Modern changes in land use and forest cover have a significant influence on local, regional, and global weather and climate conditions. In this study, the mesoscale model COSMO is used to estimate the possible influence of forest cover change in the central part of the East European Plain on regional weather conditions. The "model region" of the study is surrounded by geographical coordinates 55° and 59°N and 28° and 37°E and situated in the central part of a large modeling domain (50° - 70° N and 15° 55° E), covering almost the entire East European Plain in Northern Eurasia. The forests cover about 50% of the area of the "model region". The modeling study includes 3 main numerical experiments. The first assumes total deforestation of the "model region" and replacement of forests by grasslands. The second is represented by afforestation of the "model region." In the third, weather conditions are simulated with present land use and vegetation structures of the "model region." Output of numerical experiments is at 13.2 km grid resolution, and the ERA-Interim global atmospheric reanalysis (with 6-h resolution in time and 0.75°×0.75° in space) is used to quantify initial and boundary conditions. Numerical experiments for the warm period of 2010 taken as an example show that deforestation and afforestation processes in the selected region can lead to significant changes in weather conditions. Deforestation processes in summer conditions can result in increased air temperature and wind speed, reduction of precipitation, lower clouds, and relative humidity. The afforestation process can result in opposite effects (decreased air temperature, increased precipitation, higher air humidity and fog frequency, and strengthened storm winds). Maximum meteorological changes under forest cover changes are projected for the summer months (July and August). It was also shown that changes of some meteorological characteristics (e.g., air temperature) is observed in the

  3. Tracking sensitive source areas of different weather pollution types using GRAPES-CUACE adjoint model

    Science.gov (United States)

    Wang, Chao; An, Xingqin; Zhai, Shixian; Hou, Qing; Sun, Zhaobin

    2018-02-01

    In this study, the sustained pollution processes were selected during which daily PM2.5 concentration exceeded 75 μg/m3 for three days continuously based on the hourly data of Beijing observation sites from July 2012 to December 2015. Using the China Meteorological Administration (CMA) MICAPS meteorological processing system, synoptic situation during PM2.5 pollution processes was classified into five weather types: low pressure and weak high pressure alternating control, weak high pressure, low pressure control, high rear, and uniform pressure field. Then, we chose the representative pollution cases corresponding to each type, adopted the GRAPES-CUACE adjoint model tracking the sensitive source areas of the five types, and analyzed the critical discharge periods of Beijing and neighboring provinces as well as their contribution to the PM2.5 peak concentration in Beijing. The results showed that the local source plays the main theme in the 30 h before the objective time, and prior to 72 h before the objective time contribution of local sources for the five pollution types are 37.5%, 25.0%, 39.4%, 31.2%, and 42.4%, respectively; the Hebei source contributes constantly in the 57 h ahead of the objective time with the contribution proportion ranging from 37% to 64%; the contribution period and rate of Tianjin and Shanxi sources are shorter and smaller. Based on the adjoint sensitivity analysis, we further discussed the effect of emission reduction control measures in different types, finding that the effect of local source reduction in the first 20 h of the objective time is better, and if the local source is reduced 50% within 72 h before the objective time, the decline rates of PM2.5 in the five types are 11.6%, 9.4%, 13.8%, 9.9% and 15.2% respectively. And the reduction effect of the neighboring sources is better within the 3-57 h before the objective time.

  4. Aviation Model: A Fine-Scale Numerical Weather Prediction System for Aviation Applications at the Hong Kong International Airport

    Directory of Open Access Journals (Sweden)

    Wai-Kin Wong

    2013-01-01

    Full Text Available The Hong Kong Observatory (HKO is planning to implement a fine-resolution Numerical Weather Prediction (NWP model for supporting the aviation weather applications at the Hong Kong International Airport (HKIA. This new NWP model system, called Aviation Model (AVM, is configured at a horizontal grid spacing of 600 m and 200 m. It is based on the WRF-ARW (Advance Research WRF model that can have sufficient computation efficiency in order to produce hourly updated forecasts up to 9 hours ahead on a future high performance computer system with theoretical peak performance of around 10 TFLOPS. AVM will be nested inside the operational mesoscale NWP model of HKO with horizontal resolution of 2 km. In this paper, initial numerical experiment results in forecast of windshear events due to seabreeze and terrain effect are discussed. The simulation of sea-breeze-related windshear is quite successful, and the headwind change observed from flight data could be reproduced in the model forecast. Some impacts of physical processes on generating the fine-scale wind circulation and development of significant convection are illustrated. The paper also discusses the limitations in the current model setup and proposes methods for the future development of AVM.

  5. Preliminary quantification of a shape model for etch-pits formed during natural weathering of olivine

    International Nuclear Information System (INIS)

    Nowicki, M. Anna; Velbel, Michael A.

    2011-01-01

    Many etch-pits on olivine grains occur as a pair of cone-shaped pits sharing a base, which consequently appear as diamond-shaped etch-pits in cross-section. Quantitative image analysis of back-scattered electron images establishes empirical dimensions of olivine etch-pits in naturally weathered samples from Hawaii and North Carolina. Images of naturally etched olivine were acquired from polished thin-sections by scanning electron microscopy. An average cone-radius-to-height ratio (r:h) of 1.78 was determined for diamond-shaped cross-sections of etch-pits occurring in naturally weathered olivine grains, largely consistent with previous qualitative results. Olivine etch-pit shape as represented by r:h varies from slightly more than half the average value to slightly more than twice the average. Etch-pit shape does not appear to vary systematically with etch-pit size.

  6. Approach to Integrate Global-Sun Models of Magnetic Flux Emergence and Transport for Space Weather Studies

    Science.gov (United States)

    Mansour, Nagi N.; Wray, Alan A.; Mehrotra, Piyush; Henney, Carl; Arge, Nick; Godinez, H.; Manchester, Ward; Koller, J.; Kosovichev, A.; Scherrer, P.; hide

    2013-01-01

    The Sun lies at the center of space weather and is the source of its variability. The primary input to coronal and solar wind models is the activity of the magnetic field in the solar photosphere. Recent advancements in solar observations and numerical simulations provide a basis for developing physics-based models for the dynamics of the magnetic field from the deep convection zone of the Sun to the corona with the goal of providing robust near real-time boundary conditions at the base of space weather forecast models. The goal is to develop new strategic capabilities that enable characterization and prediction of the magnetic field structure and flow dynamics of the Sun by assimilating data from helioseismology and magnetic field observations into physics-based realistic magnetohydrodynamics (MHD) simulations. The integration of first-principle modeling of solar magnetism and flow dynamics with real-time observational data via advanced data assimilation methods is a new, transformative step in space weather research and prediction. This approach will substantially enhance an existing model of magnetic flux distribution and transport developed by the Air Force Research Lab. The development plan is to use the Space Weather Modeling Framework (SWMF) to develop Coupled Models for Emerging flux Simulations (CMES) that couples three existing models: (1) an MHD formulation with the anelastic approximation to simulate the deep convection zone (FSAM code), (2) an MHD formulation with full compressible Navier-Stokes equations and a detailed description of radiative transfer and thermodynamics to simulate near-surface convection and the photosphere (Stagger code), and (3) an MHD formulation with full, compressible Navier-Stokes equations and an approximate description of radiative transfer and heating to simulate the corona (Module in BATS-R-US). CMES will enable simulations of the emergence of magnetic structures from the deep convection zone to the corona. Finally, a plan

  7. Evaluating winds and vertical wind shear from Weather Research and Forecasting model forecasts using seven planetary boundary layer schemes

    DEFF Research Database (Denmark)

    Draxl, Caroline; Hahmann, Andrea N.; Pena Diaz, Alfredo

    2014-01-01

    with different PBL parameterizations at one coastal site over western Denmark. The evaluation focuses on determining which PBL parameterization performs best for wind energy forecasting, and presenting a validation methodology that takes into account wind speed at different heights. Winds speeds at heights...... regarding wind energy at these levels partly depends on the formulation and implementation of planetary boundary layer (PBL) parameterizations in these models. This study evaluates wind speeds and vertical wind shears simulated by theWeather Research and Forecasting model using seven sets of simulations...

  8. EMD-regression for modelling multi-scale relationships, and application to weather-related cardiovascular mortality

    Science.gov (United States)

    Masselot, Pierre; Chebana, Fateh; Bélanger, Diane; St-Hilaire, André; Abdous, Belkacem; Gosselin, Pierre; Ouarda, Taha B. M. J.

    2018-01-01

    In a number of environmental studies, relationships between natural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of advantages. First, it accounts of the issues of non-stationarity associated to the data series. Second, this approach acts as a scan for the relationship between a response variable and the predictors at different time scales, providing new insights about this relationship. To illustrate the proposed methodology it is applied to study the relationship between weather and cardiovascular mortality in Montreal, Canada. The results shed new knowledge concerning the studied relationship. For instance, they show that the humidity can cause excess mortality at the monthly time scale, which is a scale not visible in classical models. A comparison is also conducted with state of the art methods which are the generalized additive models and distributed lag models, both widely used in weather-related health studies. The comparison shows that EMD-regression achieves better prediction performances and provides more details than classical models concerning the relationship.

  9. The Planeterrella: an Analog Model for Teaching About the Invisible Electromagnetic Processes Driving Space Weather

    Science.gov (United States)

    Masongsong, E. V.; Glesener, G. B.; Angelopoulos, V.; Lilensten, J.; Bingley, L.

    2015-12-01

    The Planeterrella can be used as an analog to help students visualize and understand the electromagnetic processes driving space weather that affect our daily lives. Solar storms and solar wind charged particles (plasma) cause "space weather" via their interaction with Earth's protective magnetic shield, the magnetosphere. The Planeterrella uses magnetized spheres in a vacuum chamber to demonstrate solar wind energy transfer to Earth and planets, with polar localization of aurora due to charged particles traveling along geomagnetic field lines. The Planeterrella provides a unique opportunity to experience and manipulate plasma, the dominant form of matter in our universe, yet seldom observable on Earth. Severe space weather events produce spectacular auroral displays as well as devastating consequences: radiation exposure to air and space travelers, prolonged radio blackouts, and damage to critical GPS and communications satellites. We will (1) discuss ways in which the Planeterrella may be most useful in classroom settings, including large lecture halls, laboratories, and small discussion sessions; (2) provide information on how instructors can produce their own Planeterrella for their courses; and (3) invite meeting attendees to engage in a discussion on how we might be able to improve on the current design of the Planeterrella, and how to reach students in more parts of the world.

  10. Implementation of a generalized actuator line model for wind turbine parameterization in the Weather Research and Forecasting model

    Energy Technology Data Exchange (ETDEWEB)

    Marjanovic, Nikola [Department of Civil and Environmental Engineering, University of California, Berkeley, MC 1710, Berkeley, California 94720-1710, USA; Atmospheric, Earth and Energy Division, Lawrence Livermore National Laboratory, PO Box 808, L-103, Livermore, California 94551, USA; Mirocha, Jeffrey D. [Atmospheric, Earth and Energy Division, Lawrence Livermore National Laboratory, PO Box 808, L-103, Livermore, California 94551, USA; Kosović, Branko [Research Applications Laboratory, Weather Systems and Assessment Program, University Corporation for Atmospheric Research, PO Box 3000, Boulder, Colorado 80307, USA; Lundquist, Julie K. [Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Campus Box 311, Boulder, Colorado 80309, USA; National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, USA; Chow, Fotini Katopodes [Department of Civil and Environmental Engineering, University of California, Berkeley, MC 1710, Berkeley, California 94720-1710, USA

    2017-11-01

    A generalized actuator line (GAL) wind turbine parameterization is implemented within the Weather Research and Forecasting model to enable high-fidelity large-eddy simulations of wind turbine interactions with boundary layer flows under realistic atmospheric forcing conditions. Numerical simulations using the GAL parameterization are evaluated against both an already implemented generalized actuator disk (GAD) wind turbine parameterization and two field campaigns that measured the inflow and near-wake regions of a single turbine. The representation of wake wind speed, variance, and vorticity distributions is examined by comparing fine-resolution GAL and GAD simulations and GAD simulations at both fine and coarse-resolutions. The higher-resolution simulations show slightly larger and more persistent velocity deficits in the wake and substantially increased variance and vorticity when compared to the coarse-resolution GAD. The GAL generates distinct tip and root vortices that maintain coherence as helical tubes for approximately one rotor diameter downstream. Coarse-resolution simulations using the GAD produce similar aggregated wake characteristics to both fine-scale GAD and GAL simulations at a fraction of the computational cost. The GAL parameterization provides the capability to resolve near wake physics, including vorticity shedding and wake expansion.

  11. Application of global weather and climate model output to the design and operation of wind-energy systems

    Energy Technology Data Exchange (ETDEWEB)

    Curry, Judith [Climate Forecast Applications Network, Atlanta, GA (United States)

    2015-05-21

    This project addressed the challenge of providing weather and climate information to support the operation, management and planning for wind-energy systems. The need for forecast information is extending to longer projection windows with increasing penetration of wind power into the grid and also with diminishing reserve margins to meet peak loads during significant weather events. Maintenance planning and natural gas trading is being influenced increasingly by anticipation of wind generation on timescales of weeks to months. Future scenarios on decadal time scales are needed to support assessment of wind farm siting, government planning, long-term wind purchase agreements and the regulatory environment. The challenge of making wind forecasts on these longer time scales is associated with a wide range of uncertainties in general circulation and regional climate models that make them unsuitable for direct use in the design and planning of wind-energy systems. To address this challenge, CFAN has developed a hybrid statistical/dynamical forecasting scheme for delivering probabilistic forecasts on time scales from one day to seven months using what is arguably the best forecasting system in the world (European Centre for Medium Range Weather Forecasting, ECMWF). The project also provided a framework to assess future wind power through developing scenarios of interannual to decadal climate variability and change. The Phase II research has successfully developed an operational wind power forecasting system for the U.S., which is being extended to Europe and possibly Asia.

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

    Science.gov (United States)

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

    2011-02-01

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

  13. 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).

  14. A Mathematical Model of Hourly Solar Radiation in Varying Weather Conditions for a Dynamic Simulation of the Solar Organic Rankine Cycle

    Directory of Open Access Journals (Sweden)

    Taehong Sung

    2015-07-01

    Full Text Available A mathematical model of hourly solar radiation with weather variability is proposed based on the simple sky model. The model uses a superposition of trigonometric functions with short and long periods. We investigate the effects of the model variables on the clearness (kD and the probability of persistence (POPD indices and also evaluate the proposed model for all of the kD-POPD weather classes. A simple solar organic Rankine cycle (SORC system with thermal storage is simulated using the actual weather conditions, and then, the results are compared with the simulation results using the proposed model and the simple sky model. The simulation results show that the proposed model provides more accurate system operation characteristics than the simple sky model.

  15. Analysis of a severe weather event over Mecca, Kingdom of Saudi Arabia, using observations and high-resolution modelling

    KAUST Repository

    Dasari, Hari Prasad; Attada, Raju; Knio, Omar; Hoteit, Ibrahim

    2017-01-01

    The dynamic and thermodynamic characteristics of a severe weather event that caused heavy wind and rainfall over Mecca, Kingdom of Saudi Arabia, on 11 September 2015 were investigated using available observations and the Weather Research and Forecasting model configured at 1 km resolution. Analysis of surface, upper air observations and model outputs reveals that the event was initiated by synoptic scale conditions that intensified by interaction with the local topography, triggering strong winds and high convective rainfall. The model predicted the observed characteristics of both rainfall and winds well, accurately predicting the maximum wind speed of 20–25 m s−1 that was sustained for about 2 h. A time series analysis of various atmospheric variables suggests a sudden fall in pressure, temperature and outgoing long wave radiation before the development of the storm, followed by a significant increase in wind speed, latent and moisture fluxes and change in wind direction during the mature stage of the storm. The model outputs suggest that the heavy rainfall was induced by a low-level moisture supply from the Red Sea combined with orographic lifting. Latent heat release from microphysical processes increased the vertical velocities in the mid-troposphere, further increasing the low-level convergence that strengthened the event.

  16. Analysis of a severe weather event over Mecca, Kingdom of Saudi Arabia, using observations and high-resolution modelling

    KAUST Repository

    Dasari, Hari Prasad

    2017-08-10

    The dynamic and thermodynamic characteristics of a severe weather event that caused heavy wind and rainfall over Mecca, Kingdom of Saudi Arabia, on 11 September 2015 were investigated using available observations and the Weather Research and Forecasting model configured at 1 km resolution. Analysis of surface, upper air observations and model outputs reveals that the event was initiated by synoptic scale conditions that intensified by interaction with the local topography, triggering strong winds and high convective rainfall. The model predicted the observed characteristics of both rainfall and winds well, accurately predicting the maximum wind speed of 20–25 m s−1 that was sustained for about 2 h. A time series analysis of various atmospheric variables suggests a sudden fall in pressure, temperature and outgoing long wave radiation before the development of the storm, followed by a significant increase in wind speed, latent and moisture fluxes and change in wind direction during the mature stage of the storm. The model outputs suggest that the heavy rainfall was induced by a low-level moisture supply from the Red Sea combined with orographic lifting. Latent heat release from microphysical processes increased the vertical velocities in the mid-troposphere, further increasing the low-level convergence that strengthened the event.

  17. Surface Temperature Variation Prediction Model Using Real-Time Weather Forecasts

    Science.gov (United States)

    Karimi, M.; Vant-Hull, B.; Nazari, R.; Khanbilvardi, R.

    2015-12-01

    Combination of climate change and urbanization are heating up cities and putting the lives of millions of people in danger. More than half of the world's total population resides in cities and urban centers. Cities are experiencing urban Heat Island (UHI) effect. Hotter days are associated with serious health impacts, heart attaches and respiratory and cardiovascular diseases. Densely populated cities like Manhattan, New York can be affected by UHI impact much more than less populated cities. Even though many studies have been focused on the impact of UHI and temperature changes between urban and rural air temperature, not many look at the temperature variations within a city. These studies mostly use remote sensing data or typical measurements collected by local meteorological station networks. Local meteorological measurements only have local coverage and cannot be used to study the impact of UHI in a city and remote sensing data such as MODIS, LANDSAT and ASTER have with very low resolution which cannot be used for the purpose of this study. Therefore, predicting surface temperature in urban cities using weather data can be useful.Three months of Field campaign in Manhattan were used to measure spatial and temporal temperature variations within an urban setting by placing 10 fixed sensors deployed to measure temperature, relative humidity and sunlight. Fixed instrument shelters containing relative humidity, temperature and illumination sensors were mounted on lampposts in ten different locations in Manhattan (Vant-Hull et al, 2014). The shelters were fixed 3-4 meters above the ground for the period of three months from June 23 to September 20th of 2013 making measurements with the interval of 3 minutes. These high resolution temperature measurements and three months of weather data were used to predict temperature variability from weather forecasts. This study shows that the amplitude of spatial and temporal variation in temperature for each day can be predicted

  18. 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

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

    Science.gov (United States)

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

    2017-12-01

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

  20. Representation of the Saharan atmospheric boundary layer in the Weather and Research Forecast (WRF) model: A sensitivity analysis.

    Science.gov (United States)

    Todd, Martin; Cavazos, Carolina; Wang, Yi

    2013-04-01

    The Saharan atmospheric boundary layer (SABL) during summer is one of the deepest on Earth, and is crucial in controlling the vertical redistribution and long-range transport of dust in the Sahara. The SABL is typically made up of an actively growing convective layer driven by high sensible heating at the surface, with a deep, near-neutrally stratified Saharan residual layer (SRL) above it, which is mostly well mixed in humidity and temperature and reaches a height of ˜5-6km. These two layers are usually separated by a weak (≤1K) temperature inversion. Model representation of the SPBL structure and evolution is important for accurate weather/climate and aerosol prediction. In this work, we evaluate model performance of the Weather Research and Forecasting (WRF) to represent key multi-scale processes in the SABL during summer 2011, including depiction of the diurnal cycle. For this purpose, a sensitivity analysis is performed to examine the performance of seven PBL schemes (YSU, MYJ, QNSE, MYNN, ACM, Boulac and MRF) and two land-surface model (Noah and RUC) schemes. In addition, the sensitivity to the choice of lateral boundary conditions (ERA-Interim and NCEP) and land use classification maps (USGS and MODIS-based) is tested. Model outputs were confronted upper-air and surface observations from the Fennec super-site at Bordj Moktar and automatic weather station (AWS) in Southern Algeria Vertical profiles of wind speed, potential temperature and water vapour mixing ratio were examined to diagnose differences in PBL heights and model efficacy to reproduce the diurnal cycle of the SABL. We find that the structure of the model SABL is most sensitive the choice of land surface model and lateral boundary conditions and relatively insensitive to the PBL scheme. Overall the model represents well the diurnal cycle in the structure of the SABL. Consistent model biases include (i) a moist (1-2 gkg-1) and slightly cool (~1K) bias in the daytime convective boundary layer (ii

  1. Implementation of 5-layer thermal diffusion scheme in weather research and forecasting model with Intel Many Integrated Cores

    Science.gov (United States)

    Huang, Melin; Huang, Bormin; Huang, Allen H.

    2014-10-01

    For weather forecasting and research, the Weather Research and Forecasting (WRF) model has been developed, consisting of several components such as dynamic solvers and physical simulation modules. WRF includes several Land- Surface Models (LSMs). The LSMs use atmospheric information, the radiative and precipitation forcing from the surface layer scheme, the radiation scheme, and the microphysics/convective scheme all together with the land's state variables and land-surface properties, to provide heat and moisture fluxes over land and sea-ice points. The WRF 5-layer thermal diffusion simulation is an LSM based on the MM5 5-layer soil temperature model with an energy budget that includes radiation, sensible, and latent heat flux. The WRF LSMs are very suitable for massively parallel computation as there are no interactions among horizontal grid points. The features, efficient parallelization and vectorization essentials, of Intel Many Integrated Core (MIC) architecture allow us to optimize this WRF 5-layer thermal diffusion scheme. In this work, we present the results of the computing performance on this scheme with Intel MIC architecture. Our results show that the MIC-based optimization improved the performance of the first version of multi-threaded code on Xeon Phi 5110P by a factor of 2.1x. Accordingly, the same CPU-based optimizations improved the performance on Intel Xeon E5- 2603 by a factor of 1.6x as compared to the first version of multi-threaded code.

  2. Projected changes of extreme weather events in the eastern United States based on a high resolution climate modeling system

    International Nuclear Information System (INIS)

    Gao, Y; Fu, J S; Drake, J B; Liu, Y; Lamarque, J-F

    2012-01-01

    This study is the first evaluation of dynamical downscaling using the Weather Research and Forecasting (WRF) Model on a 4 km × 4 km high resolution scale in the eastern US driven by the new Community Earth System Model version 1.0 (CESM v1.0). First we examined the global and regional climate model results, and corrected an inconsistency in skin temperature during the downscaling process by modifying the land/sea mask. In comparison with observations, WRF shows statistically significant improvement over CESM in reproducing extreme weather events, with improvement for heat wave frequency estimation as high as 98%. The fossil fuel intensive scenario Representative Concentration Pathway (RCP) 8.5 was used to study a possible future mid-century climate extreme in 2057–9. Both the heat waves and the extreme precipitation in 2057–9 are more severe than the present climate in the Eastern US. The Northeastern US shows large increases in both heat wave intensity (3.05 °C higher) and annual extreme precipitation (107.3 mm more per year). (letter)

  3. Production of solar radiation bankable datasets from high-resolution solar irradiance derived with dynamical downscaling Numerical Weather prediction model

    Directory of Open Access Journals (Sweden)

    Yassine Charabi

    2016-11-01

    Full Text Available A bankable solar radiation database is required for the financial viability of solar energy project. Accurate estimation of solar energy resources in a country is very important for proper siting, sizing and life cycle cost analysis of solar energy systems. During the last decade an important progress has been made to develop multiple solar irradiance database (Global Horizontal Irradiance (GHI and Direct Normal Irradiance (DNI, using satellite of different resolution and sophisticated models. This paper assesses the performance of High-resolution solar irradiance derived with dynamical downscaling Numerical Weather Prediction model with, GIS topographical solar radiation model, satellite data and ground measurements, for the production of bankable solar radiation datasets. For this investigation, NWP model namely Consortium for Small-scale Modeling (COSMO is used for the dynamical downscaling of solar radiation. The obtained results increase confidence in solar radiation data base obtained from dynamical downscaled NWP model. The mean bias of dynamical downscaled NWP model is small, on the order of a few percents for GHI, and it could be ranked as a bankable datasets. Fortunately, these data are usually archived in the meteorological department and gives a good idea of the hourly, monthly, and annual incident energy. Such short time-interval data are valuable in designing and operating the solar energy facility. The advantage of the NWP model is that it can be used for solar radiation forecast since it can estimate the weather condition within the next 72–120 hours. This gives a reasonable estimation of the solar radiation that in turns can be used to forecast the electric power generation by the solar power plant.

  4. Integration of Weather Avoidance and Traffic Separation

    Science.gov (United States)

    Consiglio, Maria C.; Chamberlain, James P.; Wilson, Sara R.

    2011-01-01

    This paper describes a dynamic convective weather avoidance concept that compensates for weather motion uncertainties; the integration of this weather avoidance concept into a prototype 4-D trajectory-based Airborne Separation Assurance System (ASAS) application; and test results from a batch (non-piloted) simulation of the integrated application with high traffic densities and a dynamic convective weather model. The weather model can simulate a number of pseudo-random hazardous weather patterns, such as slow- or fast-moving cells and opening or closing weather gaps, and also allows for modeling of onboard weather radar limitations in range and azimuth. The weather avoidance concept employs nested "core" and "avoid" polygons around convective weather cells, and the simulations assess the effectiveness of various avoid polygon sizes in the presence of different weather patterns, using traffic scenarios representing approximately two times the current traffic density in en-route airspace. Results from the simulation experiment show that the weather avoidance concept is effective over a wide range of weather patterns and cell speeds. Avoid polygons that are only 2-3 miles larger than their core polygons are sufficient to account for weather uncertainties in almost all cases, and traffic separation performance does not appear to degrade with the addition of weather polygon avoidance. Additional "lessons learned" from the batch simulation study are discussed in the paper, along with insights for improving the weather avoidance concept. Introduction

  5. Quantifying the VNIR Effects of Nanophase Iron Generated through the Space Weathering of Silicates: Reconciling Modeled Data with Laboratory Observations

    Science.gov (United States)

    Legett, C., IV; Glotch, T. D.; Lucey, P. G.

    2015-12-01

    Space weathering is a diverse set of processes that occur on the surfaces of airless bodies due to exposure to the space environment. One of the effects of space weathering is the generation of nanophase iron particles in glassy rims on mineral grains due to sputtering of iron-bearing minerals. These particles have a size-dependent effect on visible and near infrared (VNIR) reflectance spectra with smaller diameter particles (behavior), while larger particles (> 300 nm) darken without reddening. Between these two sizes, a gradual shift between these two behaviors occurs. In this work, we present results from the Multiple Sphere T-Matrix (MSTM) scattering model in combination with Hapke theory to explore the particle size and iron content parameter spaces with respect to VNIR (700-1700 nm) spectral slope. Previous work has shown that the MSTM-Hapke hybrid model offers improvements over Mie-Hapke models. Virtual particles are constructed out of an arbitrary number of spheres, and each sphere is assigned a refractive index and extinction coefficient for each wavelength of interest. The model then directly solves Maxwell's Equations at every wave-particle interface to predict the scattering, extinction and absorption efficiencies. These are then put into a simplified Hapke bidirectional reflectance model that yields a predicted reflectance. Preliminary results show an area of maximum slopes for iron particle diameters planned to better refine the extent of this region. Companion laboratory work using mixtures of powdered aerogel and nanophase iron particles provides a point of comparison to modeling efforts. The effects on reflectance and emissivity values due to particle size in a nearly ideal scatterer (aerogel) are also observed with comparisons to model data.

  6. Modeled Forecasts of Dengue Fever in San Juan, PR Using NASA Satellite Enhanced Weather Forecasts

    Science.gov (United States)

    Morin, Cory; Quattrochi, Dale; Zavodsky, Bradley; Case, Jonathan

    2015-01-01

    Dengue virus is transmitted between humans and mosquitoes of the genus Aedes and causes approximately 96 million cases of disease (dengue fever) each year (Bhatet al. 2013). Symptoms of dengue fever include fever, headache, nausea, vomiting, and eye, muscle and joint pain (CDC). More sever manifestations such as abdominal pain, bleeding from nose and gums, vomiting of blood, and clammy skin occur in rare cases of dengue hemorrhagic fever (CDC). Dengue fever occurs throughout tropical and sub-tropical regions worldwide, however, the geographical range and size of epidemics is increasing. Weather and climate are drivers of dengue virus transmission dynamics (Morin et al. 2013) by affecting mosquito proliferation and the virus extrinsic incubation period (i.e. required time for the virus to replicate and disseminate within the mosquito before it can retransmit the virus).

  7. Numerical study of Asian dust transport during the springtime of 2001 simulated with the Chemical Weather Forecasting System (CFORS) model

    Science.gov (United States)

    Uno, Itsushi; Satake, Shinsuke; Carmichael, Gregory R.; Tang, Youhua; Wang, Zifa; Takemura, Toshihiko; Sugimoto, Nobuo; Shimizu, Atsushi; Murayama, Toshiyuki; Cahill, Thomas A.; Cliff, Steven; Uematsu, Mitsuo; Ohta, Sachio; Quinn, Patricia K.; Bates, Timothy S.

    2004-10-01

    The regional-scale aerosol transport model Chemical Weather Forecasting System (CFORS) is used for analysis of large-scale dust phenomena during the Asian Pacific Regional Characterization Experiment (ACE-Asia) intensive observation. Dust modeling results are examined with the surface weather reports, satellite-derived dust index (Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI)), Mie-scattering lidar observation, and surface aerosol observations. The CFORS dust results are shown to accurately reproduce many of the important observed features. Model analysis shows that the simulated dust vertical loading correlates well with TOMS AI and that the dust loading is transported with the meandering of the synoptic-scale temperature field at the 500-hPa level. Quantitative examination of aerosol optical depth shows that model predictions are within 20% difference of the lidar observations for the major dust episodes. The structure of the ACE-Asia Perfect Dust Storm, which occurred in early April, is clarified with the help of the CFORS model analysis. This storm consisted of two boundary layer components and one elevated dust (>6-km height) feature (resulting from the movement of two large low-pressure systems). Time variation of the CFORS dust fields shows the correct onset timing of the elevated dust for each observation site, but the model results tend to overpredict dust concentrations at lower latitude sites. The horizontal transport flux at 130°E longitude is examined, and the overall dust transport flux at 130°E during March-April is evaluated to be 55 Tg.

  8. Medium-range reference evapotranspiration forecasts for the contiguous United States based on multi-model numerical weather predictions

    Science.gov (United States)

    Medina, Hanoi; Tian, Di; Srivastava, Puneet; Pelosi, Anna; Chirico, Giovanni B.

    2018-07-01

    Reference evapotranspiration (ET0) plays a fundamental role in agronomic, forestry, and water resources management. Estimating and forecasting ET0 have long been recognized as a major challenge for researchers and practitioners in these communities. This work explored the potential of multiple leading numerical weather predictions (NWPs) for estimating and forecasting summer ET0 at 101 U.S. Regional Climate Reference Network stations over nine climate regions across the contiguous United States (CONUS). Three leading global NWP model forecasts from THORPEX Interactive Grand Global Ensemble (TIGGE) dataset were used in this study, including the single model ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (EC), the National Centers for Environmental Prediction Global Forecast System (NCEP), and the United Kingdom Meteorological Office forecasts (MO), as well as multi-model ensemble forecasts from the combinations of these NWP models. A regression calibration was employed to bias correct the ET0 forecasts. Impact of individual forecast variables on ET0 forecasts were also evaluated. The results showed that the EC forecasts provided the least error and highest skill and reliability, followed by the MO and NCEP forecasts. The multi-model ensembles constructed from the combination of EC and MO forecasts provided slightly better performance than the single model EC forecasts. The regression process greatly improved ET0 forecast performances, particularly for the regions involving stations near the coast, or with a complex orography. The performance of EC forecasts was only slightly influenced by the size of the ensemble members, particularly at short lead times. Even with less ensemble members, EC still performed better than the other two NWPs. Errors in the radiation forecasts, followed by those in the wind, had the most detrimental effects on the ET0 forecast performances.

  9. Simulation of Flash-Flood-Producing Storm Events in Saudi Arabia Using the Weather Research and Forecasting Model

    KAUST Repository

    Deng, Liping

    2015-05-01

    The challenges of monitoring and forecasting flash-flood-producing storm events in data-sparse and arid regions are explored using the Weather Research and Forecasting (WRF) Model (version 3.5) in conjunction with a range of available satellite, in situ, and reanalysis data. Here, we focus on characterizing the initial synoptic features and examining the impact of model parameterization and resolution on the reproduction of a number of flood-producing rainfall events that occurred over the western Saudi Arabian city of Jeddah. Analysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) data suggests that mesoscale convective systems associated with strong moisture convergence ahead of a trough were the major initial features for the occurrence of these intense rain events. The WRF Model was able to simulate the heavy rainfall, with driving convective processes well characterized by a high-resolution cloud-resolving model. The use of higher (1 km vs 5 km) resolution along the Jeddah coastline favors the simulation of local convective systems and adds value to the simulation of heavy rainfall, especially for deep-convection-related extreme values. At the 5-km resolution, corresponding to an intermediate study domain, simulation without a cumulus scheme led to the formation of deeper convective systems and enhanced rainfall around Jeddah, illustrating the need for careful model scheme selection in this transition resolution. In analysis of multiple nested WRF simulations (25, 5, and 1 km), localized volume and intensity of heavy rainfall together with the duration of rainstorms within the Jeddah catchment area were captured reasonably well, although there was evidence of some displacements of rainstorm events.

  10. Forecasting optimal solar energy supply in Jiangsu Province (China): a systematic approach using hybrid of weather and energy forecast models.

    Science.gov (United States)

    Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel

    2014-01-01

    The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, "least-cost," and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

  11. Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones

    Science.gov (United States)

    Luitel, Beda; Villarini, Gabriele; Vecchi, Gabriel A.

    2018-01-01

    The goal of this study is the evaluation of the skill of five state-of-the-art numerical weather prediction (NWP) systems [European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC)] in forecasting rainfall from North Atlantic tropical cyclones (TCs). Analyses focus on 15 North Atlantic TCs that made landfall along the U.S. coast over the 2007-2012 period. As reference data we use gridded rainfall provided by the Climate Prediction Center (CPC). We consider forecast lead-times up to five days. To benchmark the skill of these models, we consider rainfall estimates from one radar-based (Stage IV) and four satellite-based [Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH)] rainfall products. Daily and storm total rainfall fields from each of these remote sensing products are compared to the reference data to obtain information about the range of errors we can expect from "observational data." The skill of the NWP models is quantified: (1) by visual examination of the distribution of the errors in storm total rainfall for the different lead-times, and numerical examination of the first three moments of the error distribution; (2) relative to climatology at the daily scale. Considering these skill metrics, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead-times up to 48 h, without a consistently best or worst NWP model.

  12. Forecasting Optimal Solar Energy Supply in Jiangsu Province (China: A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

    Directory of Open Access Journals (Sweden)

    Xiuli Zhao

    2014-01-01

    Full Text Available The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

  13. 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.

  14. Parameterization of synoptic weather systems in the South Atlantic Bight for modeling applications

    Science.gov (United States)

    Wu, Xiaodong; Voulgaris, George; Kumar, Nirnimesh

    2017-10-01

    An event based, long-term, climatological analysis is presented that allows the creation of coastal ocean atmospheric forcing on the coastal ocean that preserves both frequency of occurrence and event time history. An algorithm is developed that identifies individual storm event (cold fronts, warm fronts, and tropical storms) from meteorological records. The algorithm has been applied to a location along the South Atlantic Bight, off South Carolina, an area prone to cyclogenesis occurrence and passages of atmospheric fronts. Comparison against daily weather maps confirms that the algorithm is efficient in identifying cold fronts and warm fronts, while the identification of tropical storms is less successful. The average state of the storm events and their variability are represented by the temporal evolution of atmospheric pressure, air temperature, wind velocity, and wave directional spectral energy. The use of uncorrected algorithm-detected events provides climatologies that show a little deviation from those derived using corrected events. The effectiveness of this analysis method is further verified by numerically simulating the wave conditions driven by the characteristic wind forcing and comparing the results with the wave climatology that corresponds to each storm type. A high level of consistency found in the comparison indicates that this analysis method can be used for accurately characterizing event-based oceanic processes and long-term storm-induced morphodynamic processes on wind-dominated coasts.

  15. Evaluating meteorological data from weather stations, and from satellites and global models for a multi-site epidemiological study.

    Science.gov (United States)

    Colston, Josh M; Ahmed, Tahmeed; Mahopo, Cloupas; Kang, Gagandeep; Kosek, Margaret; de Sousa Junior, Francisco; Shrestha, Prakash Sunder; Svensen, Erling; Turab, Ali; Zaitchik, Benjamin

    2018-04-21

    Longitudinal and time series analyses are needed to characterize the associations between hydrometeorological parameters and health outcomes. Earth Observation (EO) climate data products derived from satellites and global model-based reanalysis have the potential to be used as surrogates in situations and locations where weather-station based observations are inadequate or incomplete. However, these products often lack direct evaluation at specific sites of epidemiological interest. Standard evaluation metrics of correlation, agreement, bias and error were applied to a set of ten hydrometeorological variables extracted from two quasi-global, commonly used climate data products - the Global Land Data Assimilation System (GLDAS) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) - to evaluate their performance relative to weather-station derived estimates at the specific geographic locations of the eight sites in a multi-site cohort study. These metrics were calculated for both daily estimates and 7-day averages and for a rotavirus-peak-season subset. Then the variables from the two sources were each used as predictors in longitudinal regression models to test their association with rotavirus infection in the cohort after adjusting for covariates. The availability and completeness of station-based validation data varied depending on the variable and study site. The performance of the two gridded climate models varied considerably within the same location and for the same variable across locations, according to different evaluation criteria and for the peak-season compared to the full dataset in ways that showed no obvious pattern. They also differed in the statistical significance of their association with the rotavirus outcome. For some variables, the station-based records showed a strong association while the EO-derived estimates showed none, while for others, the opposite was true. Researchers wishing to utilize publicly available climate data

  16. Numerical simulation for regional ozone concentrations: A case study by weather research and forecasting/chemistry (WRF/Chem) model

    Energy Technology Data Exchange (ETDEWEB)

    Habib Al Razi, Khandakar Md; Hiroshi, Moritomi [Environmental and Renewable Energy System, Graduate School of Engineering, Gifu University, 1-1 Yanagido, Gifu City, 501-1193 (Japan)

    2013-07-01

    The objective of this research is to better understand and predict the atmospheric concentration distribution of ozone and its precursor (in particular, within the Planetary Boundary Layer (Within 110 km to 12 km) over Kasaki City and the Greater Tokyo Area using fully coupled online WRF/Chem (Weather Research and Forecasting/Chemistry) model. In this research, a serious and continuous high ozone episode in the Greater Tokyo Area (GTA) during the summer of 14–18 August 2010 was investigated using the observation data. We analyzed the ozone and other trace gas concentrations, as well as the corresponding weather conditions in this high ozone episode by WRF/Chem model. The simulation results revealed that the analyzed episode was mainly caused by the impact of accumulation of pollution rich in ozone over the Greater Tokyo Area. WRF/Chem has shown relatively good performance in modeling of this continuous high ozone episode, the simulated and the observed concentrations of ozone, NOx and NO2 are basically in agreement at Kawasaki City, with best correlation coefficients of 0.87, 0.70 and 0.72 respectively. Moreover, the simulations of WRF/Chem with WRF preprocessing software (WPS) show a better agreement with meteorological observations such as surface winds and temperature profiles in the ground level of this area. As a result the surface ozone simulation performances have been enhanced in terms of the peak ozone and spatial patterns, whereas WRF/Chem has been succeeded to generate meteorological fields as well as ozone, NOx, NO2 and NO.

  17. 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 ...

  18. Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models: COST Action ES0905 Final Report

    Directory of Open Access Journals (Sweden)

    Jun–Ichi Yano

    2014-12-01

    Full Text Available The research network “Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models” was organized with European funding (COST Action ES0905 for the period of 2010–2014. Its extensive brainstorming suggests how the subgrid-scale parameterization problem in atmospheric modeling, especially for convection, can be examined and developed from the point of view of a robust theoretical basis. Our main cautions are current emphasis on massive observational data analyses and process studies. The closure and the entrainment–detrainment problems are identified as the two highest priorities for convection parameterization under the mass–flux formulation. The need for a drastic change of the current European research culture as concerns policies and funding in order not to further deplete the visions of the European researchers focusing on those basic issues is emphasized.

  19. DOE Workshop; Pan-Gass Conference on the Representation of Atmospheric Processes in Weather and Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Morrison, Hugh [National Center for Atmospheric Research, Boulder, CO (United States)

    2012-11-12

    This is the first meeting of the whole new GEWEX (Global Energy and Water Cycle Experiment) Atmospheric System Study (GASS) project that has been formed from the merger of the GEWEX Cloud System Study (GCSS) Project and the GEWEX Atmospheric Boundary Layer Studies (GABLS). As such, this meeting will play a major role in energizing GEWEX work in the area of atmospheric parameterizations of clouds, convection, stable boundary layers, and aerosol-cloud interactions for the numerical models used for weather and climate projections at both global and regional scales. The representation of these processes in models is crucial to GEWEX goals of improved prediction of the energy and water cycles at both weather and climate timescales. This proposal seeks funds to be used to cover incidental and travel expenses for U.S.-based graduate students and early career scientists (i.e., within 5 years of receiving their highest degree). We anticipate using DOE funding to support 5-10 people. We will advertise the availability of these funds by providing a box to check for interested participants on the online workshop registration form. We will also send a note to our participants' mailing lists reminding them that the funds are available and asking senior scientists to encourage their more junior colleagues to participate. All meeting participants are encouraged to submit abstracts for oral or poster presentations. The science organizing committee (see below) will base funding decisions on the relevance and quality of these abstracts, with preference given to under-represented populations (especially women and minorities) and to early career scientists being actively mentored at the meeting (e.g. students or postdocs attending the meeting with their adviser).

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

    Science.gov (United States)

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

    2015-02-01

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

  1. 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)

  2. Ground-based remote sensing profiling and numerical weather prediction model to manage nuclear power plants meteorological surveillance in Switzerland

    Directory of Open Access Journals (Sweden)

    B. Calpini

    2011-08-01

    Full Text Available The meteorological surveillance of the four nuclear power plants in Switzerland is of first importance in a densely populated area such as the Swiss Plateau. The project "Centrales Nucléaires et Météorologie" CN-MET aimed at providing a new security tool based on one hand on the development of a high resolution numerical weather prediction (NWP model. The latter is providing essential nowcasting information in case of a radioactive release from a nuclear power plant in Switzerland. On the other hand, the model input over the Swiss Plateau is generated by a dedicated network of surface and upper air observations including remote sensing instruments (wind profilers and temperature/humidity passive microwave radiometers. This network is built upon three main sites ideally located for measuring the inflow/outflow and central conditions of the main wind field in the planetary boundary layer over the Swiss Plateau, as well as a number of surface automatic weather stations (AWS. The network data are assimilated in real-time into the fine grid NWP model using a rapid update cycle of eight runs per day (one forecast every three hours. This high resolution NWP model has replaced the former security tool based on in situ observations (in particular one meteorological mast at each of the power plants and a local dispersion model. It is used to forecast the dynamics of the atmosphere in the planetary boundary layer (typically the first 4 km above ground layer and over a time scale of 24 h. This tool provides at any time (e.g. starting at the initial time of a nuclear power plant release the best picture of the 24-h evolution of the air mass over the Swiss Plateau and furthermore generates the input data (in the form of simulated values substituting in situ observations required for the local dispersion model used at each of the nuclear power plants locations. This paper is presenting the concept and two validation studies as well as the results of an

  3. GLOBE Atmosphere and AMS Diversity Program Content to Foster Weather and Climate Science Awareness at HBCUs: A Curriculum Enhancement Model

    Science.gov (United States)

    Padgett, D.

    2017-12-01

    Tennessee State University (TSU) is a member of the "Global Learning and Observations to Benefit the Environment (GLOBE) Mission Earth" project. The World Regional Geography (GEOG 1010/1020) courses are required for Education majors. Pre-service teachers must complete several exercises to be certified in the GLOBE Atmosphere Protocols. The pre-service teachers are required to develop GLOBE-based lessons to high school students. The exercise theme is "Exploring the Impacts of Urban Heat Islands (UHI) using Geospatial Technology." Surface temperature, ambient air temperature, and cloud cover data are collected. Sample point locations are logged using Garmin GPS receivers and then mapped using ArcGIS Online (http://arcg.is/1oiD379). The service learning outreach associated with this experience requires collegians to thoroughly understand the physical, social, and health science content associated with UHIs and then impart the information to younger learners. The precollegiate students are motivated due to their closeness in age and social context to the college students. All of the students have the advantage of engaging in hands-on problem-based learning of complex meteorology, climate science, and geospatial technology concepts. The optimal result is to have pre-service teachers enroll in the Weather and Climate (GEOG 3500) course, which is supported by the American Meteorological Society (AMS) Weather and Climate Studies Curriculum. Tennessee State University faculty have completed training to deliver the curriculum through the AMS Diversity Program. The AMS Weather Studies and Climate Studies programs have been institutionalized at Tennessee State University (TSU) since fall 2005. Approximately 250 undergraduate students have been exposed to the interactive AMS learning materials over the past 10-plus years. Non-STEM, and education majors are stimulated by the real-time course content and are encouraged to think critically about atmospheric systems science, and

  4. Modelling of secondary sedimentation under wet-weather and filamentous bulking conditions

    DEFF Research Database (Denmark)

    Ramin, Elham

    Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in wastewater treatment plants (WWTPs). Performance of SSTs influences the solids inventory in the activated sludge unit and consequently impacts the biological treatment efficiency. Moreover, SSTs limit......) tools were developed for the identification and calibration of the settling sub-model in the SST models. The developed CFD tool is a potential tool for the development of a more mechanistic based flow (and design) dependent hydraulic sub-model in the second-order 1-D SST. In this thesis, a rigorous...... comparative evaluation of the first- and second-order SST models in WWTP modelling was performed by means of GSA. In the first GSA study using the Benchmark Simulation Model No. 2 with first- and second-order SST models, the settling parameters were included in the sensitivity analysis. Interestingly...

  5. Computer Modeling of Hydrology, Weathering, and Isotopic Fractionation in Andrews Creek, Rocky Mountain National Park, Colorado for Water Years 1992 through 2012

    Science.gov (United States)

    Webb, R. M. T.; Parkhurst, D. L.; Mast, A.; Clow, D. W.

    2014-12-01

    The U.S. Geological Survey's (USGS) Water, Energy, and Biogeochemical Model (WEBMOD) was used to simulate hydrology, weathering, and isotopic fractionation in the 1.7 square kilometer Andrews Creek alpine watershed. WEBMOD includes hydrologic modules derived from the USGS Precipitation Runoff Modeling System, the National Weather Service Hydro-17 snow model, and TOPMODEL. PHREEQC, a geochemical reaction model, is coupled with the hydrologic model to simulate the geochemical evolution of waters as they evaporate, mix, and react within the landscape. Major solute concentrations and δ18O were modeled over the period 1992-2012. Variations of chloride and inorganic nitrogen respond almost entirely to variations in atmospheric deposition and preferential elution of snowpack. Both evaporation and melting result in isotopic enrichment of heavy isotopes in the residual snowpack throughout the summer. Magnesium and potassium, derived mostly from weathering with some atmospheric inputs, vary seasonally with uptake during the growing season and release during the fall and winter. The weathering of granitic minerals—oligoclase, biotite, chlorite, pyrite, calcite, and formation of secondary minerals—kaolinite, goethite, gibbsite, and smectite-illite—were selected as primary reactions based on mole-balance modeling of basin outflows. The rates of these reactions were quantified by calibrating WEBMOD to match observed concentrations and loads. Exported annual loads of most weathering products are highly correlated with discharge, whereas silica loads are less correlated with discharge, suggesting a source that is more active during dry years and less active during wet years. Potential sources include net dissolution of kaolinite and smectite-illite or mineralization of colloids with high silica content. WEBMOD is a valuable tool for simulating water quality variations in response to climate change, acid mine drainage, acid rain, biological transformations, and other

  6. Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

    Science.gov (United States)

    Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.

    2014-10-01

    Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

  7. The Flare Irradiance Spectral Model (FISM) and its Contributions to Space Weather Research, the Flare Energy Budget, and Instrument Design

    Science.gov (United States)

    Chamberlin, Phillip

    2008-01-01

    The Flare Irradiance Spectral Model (FISM) is an empirical model of the solar irradiance spectrum from 0.1 to 190 nm at 1 nm spectral resolution and on a 1-minute time cadence. The goal of FISM is to provide accurate solar spectral irradiances over the vacuum ultraviolet (VUV: 0-200 nm) range as input for ionospheric and thermospheric models. The seminar will begin with a brief overview of the FISM model, and also how the Solar Dynamics Observatory (SDO) EUV Variability Experiment (EVE) will contribute to improving FISM. Some current studies will then be presented that use FISM estimations of the solar VUV irradiance to quantify the contributions of the increased irradiance from flares to Earth's increased thermospheric and ionospheric densites. Initial results will also be presented from a study looking at the electron density increases in the Martian atmosphere during a solar flare. Results will also be shown quantifying the VUV contributions to the total flare energy budget for both the impulsive and gradual phases of solar flares. Lastly, an example of how FISM can be used to simplify the design of future solar VUV irradiance instruments will be discussed, using the future NOAA GOES-R Extreme Ultraviolet and X-Ray Sensors (EXIS) space weather instrument.

  8. Analysis of Hurricane Irene’s Wind Field Using the Advanced Research Weather Research and Forecast (WRF-ARW Model

    Directory of Open Access Journals (Sweden)

    Alfred M. Klausmann

    2014-01-01

    Full Text Available Hurricane Irene caused widespread and significant impacts along the U.S. east coast during 27–29 August 2011. During this period, the storm moved across eastern North Carolina and then tracked northward crossing into Long Island and western New England. Impacts included severe flooding from the mid-Atlantic states into eastern New York and western New England, widespread wind damage and power outages across a large portion of southern and central New England, and a major storm surge along portions of the Long Island coast. The objective of this study was to conduct retrospective simulations using the Advanced Research Weather Research and Forecast (WRF-ARW model in an effort to reconstruct the storm’s surface wind field during the period of 27–29 August 2011. The goal was to evaluate how to use the WRF modeling system as a tool for reconstructing the surface wind field from historical storm events to support storm surge studies. The results suggest that, with even modest data assimilation applied to these simulations, the model was able to resolve the detailed structure of the storm, the storm track, and the spatial surface wind field pattern very well. The WRF model shows real potential for being used as a tool to analyze historical storm events to support storm surge studies.

  9. Hydrologic Modeling at the National Water Center: Operational Implementation of the WRF-Hydro Model to support National Weather Service Hydrology

    Science.gov (United States)

    Cosgrove, B.; Gochis, D.; Clark, E. P.; Cui, Z.; Dugger, A. L.; Fall, G. M.; Feng, X.; Fresch, M. A.; Gourley, J. J.; Khan, S.; Kitzmiller, D.; Lee, H. S.; Liu, Y.; McCreight, J. L.; Newman, A. J.; Oubeidillah, A.; Pan, L.; Pham, C.; Salas, F.; Sampson, K. M.; Smith, M.; Sood, G.; Wood, A.; Yates, D. N.; Yu, W.; Zhang, Y.

    2015-12-01

    The National Weather Service (NWS) National Water Center(NWC) is collaborating with the NWS National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) to implement a first-of-its-kind operational instance of the Weather Research and Forecasting (WRF)-Hydro model over the Continental United States (CONUS) and contributing drainage areas on the NWS Weather and Climate Operational Supercomputing System (WCOSS) supercomputer. The system will provide seamless, high-resolution, continuously cycling forecasts of streamflow and other hydrologic outputs of value from both deterministic- and ensemble-type runs. WRF-Hydro will form the core of the NWC national water modeling strategy, supporting NWS hydrologic forecast operations along with emergency response and water management efforts of partner agencies. Input and output from the system will be comprehensively verified via the NWC Water Resource Evaluation Service. Hydrologic events occur on a wide range of temporal scales, from fast acting flash floods, to long-term flow events impacting water supply. In order to capture this range of events, the initial operational WRF-Hydro configuration will feature 1) hourly analysis runs, 2) short-and medium-range deterministic forecasts out to two day and ten day horizons and 3) long-range ensemble forecasts out to 30 days. All three of these configurations are underpinned by a 1km execution of the NoahMP land surface model, with channel routing taking place on 2.67 million NHDPlusV2 catchments covering the CONUS and contributing areas. Additionally, the short- and medium-range forecasts runs will feature surface and sub-surface routing on a 250m grid, while the hourly analyses will feature this same 250m routing in addition to nudging-based assimilation of US Geological Survey (USGS) streamflow observations. A limited number of major reservoirs will be configured within the model to begin to represent the first-order impacts of

  10. Exploring clouds, weather, climate, and modeling using bilingual content and activities from the Windows to the Universe program and the Center for Multiscale Modeling of Atmospheric Processes

    Science.gov (United States)

    Foster, S. Q.; Johnson, R. M.; Randall, D.; Denning, S.; Russell, R.; Gardiner, L.; Hatheway, B.; Genyuk, J.; Bergman, J.

    2008-12-01

    The need for improving the representation of cloud processes in climate models has been one of the most important limitations of the reliability of climate-change simulations. Now in its third year, the National Science Foundation-funded Center for Multi-scale Modeling of Atmospheric Processes (CMMAP) at Colorado State University is addressing this problem through a revolutionary new approach to representing cloud processes on their native scales, including the cloud-scale interaction processes that are active in cloud systems. CMMAP has set ambitious education and human-resource goals to share basic information about the atmosphere, clouds, weather, climate, and modeling with diverse K-12 and public audiences through its affiliation with the Windows to the Universe (W2U) program at University Corporation for Atmospheric Research (UCAR). W2U web pages are written at three levels in English and Spanish. This information targets learners at all levels, educators, and families who seek to understand and share resources and information about the nature of weather and the climate system, and career role models from related research fields. This resource can also be helpful to educators who are building bridges in the classroom between the sciences, the arts, and literacy. Visitors to the W2U's CMMAP web portal can access a beautiful new clouds image gallery; information about each cloud type and the atmospheric processes that produce them; a Clouds in Art interactive; collections of weather-themed poetry, art, and myths; links to games and puzzles for children; and extensive classroom- ready resources and activities for K-12 teachers. Biographies of CMMAP scientists and graduate students are featured. Basic science concepts important to understanding the atmosphere, such as condensation, atmosphere pressure, lapse rate, and more have been developed, as well as 'microworlds' that enable students to interact with experimental tools while building fundamental knowledge

  11. Toward Seamless Weather-Climate Prediction with a Global Cloud Resolving Model

    Science.gov (United States)

    2016-01-14

    PAGE 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON Tim Li 19b. TELEPHONE NUMBER (Include area code) 808...The coupled model initial condition was derived based on a nudging scheme in which the model prognostic variables such as U, V, SLP, geopotential...height, air temperature and SST were nudged toward NCEP final analysis (FNL) fields. There were 24 ensemble forecast members each day. TCs in the model

  12. Analysis of Highly Wind Power Integrated Power System model performance during Critical Weather conditions

    DEFF Research Database (Denmark)

    Basit, Abdul; Hansen, Anca Daniela; Sørensen, Poul Ejnar

    2014-01-01

    , is provided by the hour-ahead power balancing model, i.e. Simulation power Balancing model (SimBa. The regulating power plan is prepared from day-ahead power production plan and hour-ahead wind power forecast. The wind power (forecasts and available) are provided by the Correlated Wind power fluctuations (Cor......Wind) model, where the wind turbine storm controllers are also implemented....

  13. Do regional weather models contribute to better wind power forecasts? A few Norwegian case studies

    DEFF Research Database (Denmark)

    Bremnes, John Bjørnar; Giebel, Gregor

    2017-01-01

    resolution of this grid determines how accurate meteorological processes can be modeled and thereby also limits forecast quality. In this study, two global and four regional operational NWP models with spatial horizontal resolutions ranging from 1 to 32 km were applied to make wind power forecasts up to 66...

  14. Exploring the role of fire, succession, climate, and weather on landscape dynamics using comparative modeling

    Science.gov (United States)

    Robert E. Keane; Geoffrey J. Cary; Mike D. Flannigan; Russell A. Parsons; Ian D. Davies; Karen J. King; Chao Li; Ross A. Bradstock; Malcolm Gill

    2013-01-01

    An assessment of the relative importance of vegetation change and disturbance as agents of landscape change under current and future climates would (1) provide insight into the controls of landscape dynamics, (2) help inform the design and development of coarse scale spatially explicit ecosystem models such as Dynamic Global Vegetation Models (DGVMs), and (3) guide...

  15. Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

    Science.gov (United States)

    Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean; hide

    2016-01-01

    Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses out perform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

  16. Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

    Science.gov (United States)

    Tariku, Tebikachew Betru; Gan, Thian Yew

    2018-06-01

    Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional

  17. Sensitivity of the weather research and forecasting model to parameterization schemes for regional climate of Nile River Basin

    Science.gov (United States)

    Tariku, Tebikachew Betru; Gan, Thian Yew

    2017-08-01

    Regional climate models (RCMs) have been used to simulate rainfall at relatively high spatial and temporal resolutions useful for sustainable water resources planning, design and management. In this study, the sensitivity of the RCM, weather research and forecasting (WRF), in modeling the regional climate of the Nile River Basin (NRB) was investigated using 31 combinations of different physical parameterization schemes which include cumulus (Cu), microphysics (MP), planetary boundary layer (PBL), land-surface model (LSM) and radiation (Ra) schemes. Using the European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data as initial and lateral boundary conditions, WRF was configured to model the climate of NRB at a resolution of 36 km with 30 vertical levels. The 1999-2001 simulations using WRF were compared with satellite data combined with ground observation and the NCEP reanalysis data for 2 m surface air temperature (T2), rainfall, short- and longwave downward radiation at the surface (SWRAD, LWRAD). Overall, WRF simulated more accurate T2 and LWRAD (with correlation coefficients >0.8 and low root-mean-square error) than SWRAD and rainfall for the NRB. Further, the simulation of rainfall is more sensitive to PBL, Cu and MP schemes than other schemes of WRF. For example, WRF simulated less biased rainfall with Kain-Fritsch combined with MYJ than with YSU as the PBL scheme. The simulation of T2 is more sensitive to LSM and Ra than to Cu, PBL and MP schemes selected, SWRAD is more sensitive to MP and Ra than to Cu, LSM and PBL schemes, and LWRAD is more sensitive to LSM, Ra and PBL than Cu, and MP schemes. In summary, the following combination of schemes simulated the most representative regional climate of NRB: WSM3 microphysics, KF cumulus, MYJ PBL, RRTM longwave radiation and Dudhia shortwave radiation schemes, and Noah LSM. The above configuration of WRF coupled to the Noah LSM has also been shown to simulate representative regional

  18. Validation of foF2 and TEC Modeling During Geomagnetic Disturbed Times: Preliminary Outcomes of International Forum for Space Weather Modeling Capabilities Assessment

    Science.gov (United States)

    Shim, J. S.; Tsagouri, I.; Goncharenko, L. P.; Kuznetsova, M. M.

    2017-12-01

    To address challenges of assessment of space weather modeling capabilities, the CCMC (Community Coordinated Modeling Center) is leading the newly established "International Forum for Space Weather Modeling Capabilities Assessment." This presentation will focus on preliminary outcomes of the International Forum on validation of modeled foF2 and TEC during geomagnetic storms. We investigate the ionospheric response to 2013 Mar. geomagnetic storm event using ionosonde and GPS TEC observations in North American and European sectors. To quantify storm impacts on foF2 and TEC, we first quantify quiet-time variations of foF2 and TEC (e.g., the median and the average of the five quietest days for the 30 days during quiet conditions). It appears that the quiet time variation of foF2 and TEC are about 10% and 20-30%, respectively. Therefore, to quantify storm impact, we focus on foF2 and TEC changes during the storm main phase larger than 20% and 50%, respectively, compared to 30-day median. We find that in European sector, both foF2 and TEC response to the storm are mainly positive phase with foF2 increase of up to 100% and TEC increase of 150%. In North America sector, however, foF2 shows negative effects (up to about 50% decrease), while TEC shows positive response (the largest increase is about 200%). To assess modeling capability of reproducing the changes of foF2 and TEC due to the storm, we use various model simulations, which are obtained from empirical, physics-based, and data assimilation models. The performance of each model depends on the selected metrics, therefore, only one metrics is not enough to evaluate the models' predictive capabilities in capturing the storm impact. The performance of the model also varies with latitude and longitude.

  19. Optimal Physics Parameterization Scheme Combination of the Weather Research and Forecasting Model for Seasonal Precipitation Simulation over Ghana

    Directory of Open Access Journals (Sweden)

    Richard Yao Kuma Agyeman

    2017-01-01

    Full Text Available Seasonal predictions of precipitation, among others, are important to help mitigate the effects of drought and floods on agriculture, hydropower generation, disasters, and many more. This work seeks to obtain a suitable combination of physics schemes of the Weather Research and Forecasting (WRF model for seasonal precipitation simulation over Ghana. Using the ERA-Interim reanalysis as forcing data, simulation experiments spanning eight months (from April to November were performed for two different years: a dry year (2001 and a wet year (2008. A double nested approach was used with the outer domain at 50 km resolution covering West Africa and the inner domain covering Ghana at 10 km resolution. The results suggest that the WRF model generally overestimated the observed precipitation by a mean value between 3% and 64% for both years. Most of the scheme combinations overestimated (underestimated precipitation over coastal (northern zones of Ghana for both years but estimated precipitation reasonably well over forest and transitional zones. On the whole, the combination of WRF Single-Moment 6-Class Microphysics Scheme, Grell-Devenyi Ensemble Cumulus Scheme, and Asymmetric Convective Model Planetary Boundary Layer Scheme simulated the best temporal pattern and temporal variability with the least relative bias for both years and therefore is recommended for Ghana.

  20. Fog prediction using the modified asymptotic liquid water content vertical distribution formulation with the Weather Research and Forecasting model

    Science.gov (United States)

    Kim, E.; Lee, S.; Kim, J.; Chae, D.

    2017-12-01

    Fog forecasts have difficulty in forecasting due to temporal and spatial resolution problems, high numerical computations, complicated mechanisms related to turbulence in order to analyze the fog in the model, and a lack of appropriate fog physical processes. Conventional fog prediction is based on the surface visibility threshold "fog diagnosis method is based on the fog related variables near the surface, such as visibility, low stratus, relative humidity and wind speed but this method only predicts fog occurrence not fog intensity. To improve this, a new fog diagnostic scheme, based on an asymptotic analytical study of radiation fog (Zhou and Ferrier 2008, ZF08) is to increase the accuracy of fog prediction by calculating the vertical LWC considering cooling, turbulence and droplet settling, visibility, surface relative humidity and low stratus. In this study, we intend to improve fog prediction through the Weather Research and Forecasting (WRF) model using high-resolution data. Although the prediction accuracy can be improved by combining the WRF Planetary Boundary Layer (PBL) scheme and 1 dimension (1D) model, it is necessary to increase the vertical resolution in the boundary layer to implement the fog formation and persistence mechanism in the internal boundary layer in the PBL more accurately, we'll modify the algorithm to enhance the effects of turbulence and then compare the newly predicted fog and observations to determine the accuracy of the forecast of the fog occurring on the Korean peninsula.

  1. A nested-grid limited-area model for short term weather forecasting

    Science.gov (United States)

    Wong, V. C.; Zack, J. W.; Kaplan, M. L.; Coats, G. D.

    1983-01-01

    The present investigation is concerned with a mesoscale atmospheric simulation system (MASS), incorporating the sigma-coordinate primitive equations. The present version of this model (MASS 3.0) has 14 vertical layers, with the upper boundary at 100 mb. There are 128 x 96 grid points in each layer. The earlier version of this model (MASS 2.0) has been described by Kaplan et al. (1982). The current investigation provides a summary of major revisions to that version and a description of the parameterization schemes which are presently included in the model. The planetary boundary layer (PBL) is considered, taking into account aspects of generalized similarity theory and free convection, the surface energy budget, the surface moisture budget, and prognostic equations for the depth h of the PBL. A cloud model is discussed, giving attention to stable precipitation, and cumulus convection.

  2. Doppler Radar and Analysis for Climate Model Verification and Numerical Weather Prediction

    National Research Council Canada - National Science Library

    Xu, Qin

    1998-01-01

    ... (Qiu and Xu, 1996, Mon. Wea. Rev., 1132-1144). The LS method was further upgraded to including background wind fields and used to improve the initial condition for the ARPS model's short-term prediction...

  3. Discovery of rare protein-coding genes in model methylotroph Methylobacterium extorquens AM1.

    Science.gov (United States)

    Kumar, Dhirendra; Mondal, Anupam Kumar; Yadav, Amit Kumar; Dash, Debasis

    2014-12-01

    Proteogenomics involves the use of MS to refine annotation of protein-coding genes and discover genes in a genome. We carried out comprehensive proteogenomic analysis of Methylobacterium extorquens AM1 (ME-AM1) from publicly available proteomics data with a motive to improve annotation for methylotrophs; organisms capable of surviving in reduced carbon compounds such as methanol. Besides identifying 2482(50%) proteins, 29 new genes were discovered and 66 annotated gene models were revised in ME-AM1 genome. One such novel gene is identified with 75 peptides, lacks homolog in other methylobacteria but has glycosyl transferase and lipopolysaccharide biosynthesis protein domains, indicating its potential role in outer membrane synthesis. Many novel genes are present only in ME-AM1 among methylobacteria. Distant homologs of these genes in unrelated taxonomic classes and low GC-content of few genes suggest lateral gene transfer as a potential mode of their origin. Annotations of methylotrophy related genes were also improved by the discovery of a short gene in methylotrophy gene island and redefining a gene important for pyrroquinoline quinone synthesis, essential for methylotrophy. The combined use of proteogenomics and rigorous bioinformatics analysis greatly enhanced the annotation of protein-coding genes in model methylotroph ME-AM1 genome. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Evaluation of the Weather Research and Forecasting mesoscale model for GABLS3: Impact of boundary-layer schemes, boundary conditions and spin-up

    NARCIS (Netherlands)

    Kleczek, M.A.; Steeneveld, G.J.; Holtslag, A.A.M.

    2014-01-01

    We evaluated the performance of the three-dimensional Weather Research and Forecasting (WRF) mesoscale model, specifically the performance of the planetary boundary-layer (PBL) parametrizations. For this purpose, Cabauw tower observations were used, with the study extending beyond the third GEWEX

  5. Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

    Science.gov (United States)

    DY, C. Y.; Fung, J. C. H.

    2016-08-01

    A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

  6. Model predictive control for a smart solar tank based on weather and consumption forecasts

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Bacher, Peder; Perers, Bengt

    2012-01-01

    In this work the heat dynamics of a storage tank were modelled on the basis of data and maximum likelihood methods. The resulting grey-box model was used for Economic Model Predictive Control (MPC) of the energy in the tank. The control objective was to balance the energy from a solar collector...... and the heat consumption in a residential house. The storage tank provides heat in periods where there is low solar radiation and stores heat when there is surplus solar heat. The forecasts of consumption patterns were based on data obtained from meters in a group of single-family houses in Denmark. The tank...... can also be heated by electric heating elements if necessary, but the electricity costs of operating these heating elements should be minimized. Consequently, the heating elements should be used in periods with cheap electricity. It is proposed to integrate a price-sensitive control to enable...

  7. Evaluation of streamflow forecast for the National Water Model of U.S. National Weather Service

    Science.gov (United States)

    Rafieeinasab, A.; McCreight, J. L.; Dugger, A. L.; Gochis, D.; Karsten, L. R.; Zhang, Y.; Cosgrove, B.; Liu, Y.

    2016-12-01

    The National Water Model (NWM), an implementation of the community WRF-Hydro modeling system, is an operational hydrologic forecasting model for the contiguous United States. The model forecasts distributed hydrologic states and fluxes, including soil moisture, snowpack, ET, and ponded water. In particular, the NWM provides streamflow forecasts at more than 2.7 million river reaches for three forecast ranges: short (15 hr), medium (10 days), and long (30 days). In this study, we verify short and medium range streamflow forecasts in the context of the verification of their respective quantitative precipitation forecasts/forcing (QPF), the High Resolution Rapid Refresh (HRRR) and the Global Forecast System (GFS). The streamflow evaluation is performed for summer of 2016 at more than 6,000 USGS gauges. Both individual forecasts and forecast lead times are examined. Selected case studies of extreme events aim to provide insight into the quality of the NWM streamflow forecasts. A goal of this comparison is to address how much streamflow bias originates from precipitation forcing bias. To this end, precipitation verification is performed over the contributing areas above (and between assimilated) USGS gauge locations. Precipitation verification is based on the aggregated, blended StageIV/StageII data as the "reference truth". We summarize the skill of the streamflow forecasts, their skill relative to the QPF, and make recommendations for improving NWM forecast skill.

  8. Modeling very large-fire occurrences over the continental United States from weather and climate forcing

    Science.gov (United States)

    R Barbero; J T Abatzoglou; E A Steel

    2014-01-01

    Very large-fires (VLFs) have widespread impacts on ecosystems, air quality, fire suppression resources, and in many regions account for a majority of total area burned. Empirical generalized linear models of the largest fires (>5000 ha) across the contiguous United States (US) were developed at ¡­60 km spatial and weekly temporal resolutions using solely atmospheric...

  9. Seamless Modeling for Research & Predictability of Severe Tropical Storms from Weather-to-Climate Timescales

    Science.gov (United States)

    Ramaswamy, V.; Chen, J. H.; Delworth, T. L.; Knutson, T. R.; Lin, S. J.; Murakami, H.; Vecchi, G. A.

    2017-12-01

    Damages from catastrophic tropical storms such as the 2017 destructive hurricanes compel an acceleration of scientific advancements to understand the genesis, underlying mechanisms, frequency, track, intensity, and landfall of these storms. The advances are crucial to provide improved early information for planners and responders. We discuss the development and utilization of a global modeling capability based on a novel atmospheric dynamical core ("Finite-Volume Cubed Sphere or FV3") which captures the realism of the recent tropical storms and is a part of the NOAA Next-Generation Global Prediction System. This capability is also part of an emerging seamless modeling system at NOAA/ Geophysical Fluid Dynamics Laboratory for simulating the frequency of storms on seasonal and longer timescales with high fidelity e.g., Atlantic hurricane frequency over the past decades. In addition, the same modeling system has also been employed to evaluate the nature of projected storms on the multi-decadal scales under the influence of anthropogenic factors such as greenhouse gases and aerosols. The seamless modeling system thus facilitates research into and the predictability of severe tropical storms across diverse timescales of practical interest to several societal sectors.

  10. Reducing prediction uncertainty of weather controlled systems

    NARCIS (Netherlands)

    Doeswijk, T.G.

    2007-01-01

    In closed agricultural systems the weather acts both as a disturbance and as a resource. By using weather forecasts in control strategies the effects of disturbances can be minimized whereas the resources can be utilized. In this situation weather forecast uncertainty and model based control are

  11. 3DCORE: Forward modeling of solar storm magnetic flux ropes for space weather prediction

    Science.gov (United States)

    Möstl, C.; Amerstorfer, T.; Palmerio, E.; Isavnin, A.; Farrugia, C. J.; Lowder, C.; Winslow, R. M.; Donnerer, J. M.; Kilpua, E. K. J.; Boakes, P. D.

    2018-05-01

    3DCORE forward models solar storm magnetic flux ropes called 3-Dimensional Coronal Rope Ejection (3DCORE). The code is able to produce synthetic in situ observations of the magnetic cores of solar coronal mass ejections sweeping over planets and spacecraft. Near Earth, these data are taken currently by the Wind, ACE and DSCOVR spacecraft. Other suitable spacecraft making these kind of observations carrying magnetometers in the solar wind were MESSENGER, Venus Express, MAVEN, and even Helios.

  12. A Weather-Based Prediction Model of Malaria Prevalence in Amenfi West District, Ghana

    Directory of Open Access Journals (Sweden)

    Esther Love Darkoh

    2017-01-01

    Full Text Available This study investigated the effects of climatic variables, particularly, rainfall and temperature, on malaria incidence using time series analysis. Our preliminary analysis revealed that malaria incidence in the study area decreased at about 0.35% annually. Also, the month of November recorded approximately 21% more malaria cases than the other months while September had a decreased effect of about 14%. The forecast model developed for this investigation indicated that mean minimum (P=0.01928 and maximum (P=0.00321 monthly temperatures lagged at three months were significant predictors of malaria incidence while rainfall was not. Diagnostic tests using Ljung-Box and ARCH-LM tests revealed that the model developed was adequate for forecasting. Forecast values for 2016 to 2020 generated by our model suggest a possible future decline in malaria incidence. This goes to suggest that intervention strategies put in place by some nongovernmental and governmental agencies to combat the disease are effective and thus should be encouraged and routinely monitored to yield more desirable outcomes.

  13. Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

    Science.gov (United States)

    Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

    2018-02-01

    Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation

  14. Wind Resource Assessment in Complex Terrain with a High-Resolution Numerical Weather Prediction Model

    Science.gov (United States)

    Gruber, Karin; Serafin, Stefano; Grubišić, Vanda; Dorninger, Manfred; Zauner, Rudolf; Fink, Martin

    2014-05-01

    A crucial step in planning new wind farms is the estimation of the amount of wind energy that can be harvested in possible target sites. Wind resource assessment traditionally entails deployment of masts equipped for wind speed measurements at several heights for a reasonably long period of time. Simplified linear models of atmospheric flow are then used for a spatial extrapolation of point measurements to a wide area. While linear models have been successfully applied in the wind resource assessment in plains and offshore, their reliability in complex terrain is generally poor. This represents a major limitation to wind resource assessment in Austria, where high-altitude locations are being considered for new plant sites, given the higher frequency of sustained winds at such sites. The limitations of linear models stem from two key assumptions in their formulation, the neutral stratification and attached boundary-layer flow, both of which often break down in complex terrain. Consequently, an accurate modeling of near-surface flow over mountains requires the adoption of a NWP model with high horizontal and vertical resolution. This study explores the wind potential of a site in Styria in the North-Eastern Alps. The WRF model is used for simulations with a maximum horizontal resolution of 800 m. Three nested computational domains are defined, with the innermost one encompassing a stretch of the relatively broad Enns Valley, flanked by the main crest of the Alps in the south and the Nördliche Kalkalpen of similar height in the north. In addition to the simulation results, we use data from fourteen 10-m wind measurement sites (of which 7 are located within valleys and 5 near mountain tops) and from 2 masts with anemometers at several heights (at hillside locations) in an area of 1600 km2 around the target site. The potential for wind energy production is assessed using the mean wind speed and turbulence intensity at hub height. The capacity factor is also evaluated

  15. Insights into the diurnal cycle of global Earth outgoing radiation using a numerical weather prediction model

    Science.gov (United States)

    Gristey, Jake J.; Chiu, J. Christine; Gurney, Robert J.; Morcrette, Cyril J.; Hill, Peter G.; Russell, Jacqueline E.; Brindley, Helen E.

    2018-04-01

    A globally complete, high temporal resolution and multiple-variable approach is employed to analyse the diurnal cycle of Earth's outgoing energy flows. This is made possible via the use of Met Office model output for September 2010 that is assessed alongside regional satellite observations throughout. Principal component analysis applied to the long-wave component of modelled outgoing radiation reveals dominant diurnal patterns related to land surface heating and convective cloud development, respectively explaining 68.5 and 16.0 % of the variance at the global scale. The total variance explained by these first two patterns is markedly less than previous regional estimates from observations, and this analysis suggests that around half of the difference relates to the lack of global coverage in the observations. The first pattern is strongly and simultaneously coupled to the land surface temperature diurnal variations. The second pattern is strongly coupled to the cloud water content and height diurnal variations, but lags the cloud variations by several hours. We suggest that the mechanism controlling the delay is a moistening of the upper troposphere due to the evaporation of anvil cloud. The short-wave component of modelled outgoing radiation, analysed in terms of albedo, exhibits a very dominant pattern explaining 88.4 % of the variance that is related to the angle of incoming solar radiation, and a second pattern explaining 6.7 % of the variance that is related to compensating effects from convective cloud development and marine stratocumulus cloud dissipation. Similar patterns are found in regional satellite observations, but with slightly different timings due to known model biases. The first pattern is controlled by changes in surface and cloud albedo, and Rayleigh and aerosol scattering. The second pattern is strongly coupled to the diurnal variations in both cloud water content and height in convective regions but only cloud water content in marine

  16. Modeling systemic autoimmune rheumatic disease in rats under the adverse weather conditions

    Directory of Open Access Journals (Sweden)

    Yegudina Ye.D.

    2017-04-01

    Full Text Available Changes in the lungs, heart and kidneys are found in all animals with experimental systemic autoimmune rheumatic disease and respectively in 47%, 47% and 40% of cases of intact rats in a hostile environment with xenobiotics air pollution (ammonia + benzene + formalin, herewith in every third or fourth individual lesions of visceral vessels developed. The negative environmental situation increases the frequency of morphological signs of the disease, such as proliferation of endothelial vessels of the heart by 68% and renal arterioles by 52%, in addition, there are direct correlations of angiopathy degree in individual organs; this depends on the nature of pathological process modeling and demonstrates air pollution as a risk factor of disease in humans. The impact of pulmonary vessels sclerosis on the development of bronhosclerosis, perivascular infiltration of the heart muscle on the lymphocyte-macrophage infiltration of the stroma of the myocardium and sclerosis of renal arterioles on the degree of nephroslerosis of stroma is directly associated, with the model of systemic autoimmune rheumatic diseases whereas air pollution by xenobiotics determines dependences of the degree of cellular infiltration of alveolar septa from perivascular pulmonary infiltration, the development of cardiomyocytes hypertrophy from proliferation of the heart endothelial vessels, increase of kidney mesangial matrix from the proliferation of endothelial glomerular capillaries.

  17. 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...

  18. 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...

  19. Key Parameters for Urban Heat Island Assessment in A Mediterranean Context: A Sensitivity Analysis Using the Urban Weather Generator Model

    Science.gov (United States)

    Salvati, Agnese; Palme, Massimo; Inostroza, Luis

    2017-10-01

    Although Urban Heat Island (UHI) is a fundamental effect modifying the urban climate, being widely studied, the relative weight of the parameters involved in its generation is still not clear. This paper investigates the hierarchy of importance of eight parameters responsible for UHI intensity in the Mediterranean context. Sensitivity analyses have been carried out using the Urban Weather Generator model, considering the range of variability of: 1) city radius, 2) urban morphology, 3) tree coverage, 4) anthropogenic heat from vehicles, 5) building’s cooling set point, 6) heat released to canyon from HVAC systems, 7) wall construction properties and 8) albedo of vertical and horizontal surfaces. Results show a clear hierarchy of significance among the considered parameters; the urban morphology is the most important variable, causing a relative change up to 120% of the annual average UHI intensity in the Mediterranean context. The impact of anthropogenic sources of heat such as cooling systems and vehicles is also significant. These results suggest that urban morphology parameters can be used as descriptors of the climatic performance of different urban areas, easing the work of urban planners and designers in understanding a complex physical phenomenon, such as the UHI.

  20. The 2009–2010 Arctic stratospheric winter – general evolution, mountain waves and predictability of an operational weather forecast model

    Directory of Open Access Journals (Sweden)

    A. Dörnbrack

    2012-04-01

    Full Text Available The relatively warm 2009–2010 Arctic winter was an exceptional one as the North Atlantic Oscillation index attained persistent extreme negative values. Here, selected aspects of the Arctic stratosphere during this winter inspired by the analysis of the international field experiment RECONCILE are presented. First of all, and as a kind of reference, the evolution of the polar vortex in its different phases is documented. Special emphasis is put on explaining the formation of the exceptionally cold vortex in mid winter after a sequence of stratospheric disturbances which were caused by upward propagating planetary waves. A major sudden stratospheric warming (SSW occurring near the end of January 2010 concluded the anomalous cold vortex period. Wave ice polar stratospheric clouds were frequently observed by spaceborne remote-sensing instruments over the Arctic during the cold period in January 2010. Here, one such case observed over Greenland is analysed in more detail and an attempt is made to correlate flow information of an operational numerical weather prediction model to the magnitude of the mountain-wave induced temperature fluctuations. Finally, it is shown that the forecasts of the ECMWF ensemble prediction system for the onset of the major SSW were very skilful and the ensemble spread was very small. However, the ensemble spread increased dramatically after the major SSW, displaying the strong non-linearity and internal variability involved in the SSW event.

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

    Science.gov (United States)

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

    2010-12-01

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

  2. An Accurate Fire-Spread Algorithm in the Weather Research and Forecasting Model Using the Level-Set Method

    Science.gov (United States)

    Muñoz-Esparza, Domingo; Kosović, Branko; Jiménez, Pedro A.; Coen, Janice L.

    2018-04-01

    The level-set method is typically used to track and propagate the fire perimeter in wildland fire models. Herein, a high-order level-set method using fifth-order WENO scheme for the discretization of spatial derivatives and third-order explicit Runge-Kutta temporal integration is implemented within the Weather Research and Forecasting model wildland fire physics package, WRF-Fire. The algorithm includes solution of an additional partial differential equation for level-set reinitialization. The accuracy of the fire-front shape and rate of spread in uncoupled simulations is systematically analyzed. It is demonstrated that the common implementation used by level-set-based wildfire models yields to rate-of-spread errors in the range 10-35% for typical grid sizes (Δ = 12.5-100 m) and considerably underestimates fire area. Moreover, the amplitude of fire-front gradients in the presence of explicitly resolved turbulence features is systematically underestimated. In contrast, the new WRF-Fire algorithm results in rate-of-spread errors that are lower than 1% and that become nearly grid independent. Also, the underestimation of fire area at the sharp transition between the fire front and the lateral flanks is found to be reduced by a factor of ≈7. A hybrid-order level-set method with locally reduced artificial viscosity is proposed, which substantially alleviates the computational cost associated with high-order discretizations while preserving accuracy. Simulations of the Last Chance wildfire demonstrate additional benefits of high-order accurate level-set algorithms when dealing with complex fuel heterogeneities, enabling propagation across narrow fuel gaps and more accurate fire backing over the lee side of no fuel clusters.

  3. GEM-AQ, an on-line global multiscale chemical weather modelling system: model description and evaluation of gas phase chemistry processes

    Directory of Open Access Journals (Sweden)

    J. W. Kaminski

    2008-06-01

    Full Text Available Tropospheric chemistry and air quality processes were implemented on-line in the Global Environmental Multiscale weather prediction model. The integrated model, GEM-AQ, was developed as a platform to investigate chemical weather at scales from global to urban. The current chemical mechanism is comprised of 50 gas-phase species, 116 chemical and 19 photolysis reactions, and is complemented by a sectional aerosol module with 5 aerosols types. All tracers are advected using the semi-Lagrangian scheme native to GEM. The vertical transport includes parameterized subgrid-scale turbulence and large scale deep convection. Dry deposition is included as a flux boundary condition in the vertical diffusion equation. Wet deposition of gas-phase species is treated in a simplified way, and only below-cloud scavenging is considered. The emissions used include yearly-averaged anthropogenic, and monthly-averaged biogenic, ocean, soil, and biomass burning emission fluxes, as well as NOx from lightning. In order to evaluate the ability to simulate seasonal variations and regional distributions of trace gases such as ozone, nitrogen dioxide and carbon monoxide, the model was run for a period of five years (2001–2005 on a global uniform 1.5°×1.5° horizontal resolution domain and 28 hybrid levels extending up to 10 hPa. Model results were compared with observations from satellites, aircraft measurement campaigns and balloon sondes. We find that GEM-AQ is able to capture the spatial details of the chemical fields in the middle and lower troposphere. The modelled ozone consistently shows good agreement with observations, except over tropical oceans. The comparison of carbon monoxide and nitrogen dioxide with satellite measurements emphasizes the need for more accurate, year-specific emissions fluxes for biomass burning and anthropogenic sources. Other species also compare well with available observations.

  4. GEM-AQ/EC, an on-line global multi-scale chemical weather modelling system: model development and evaluation of global aerosol climatology

    Directory of Open Access Journals (Sweden)

    S. L. Gong

    2012-09-01

    Full Text Available A global air quality modeling system GEM-AQ/EC was developed by implementing tropospheric chemistry and aerosol processes on-line into the Global Environmental Multiscale weather prediction model – GEM. Due to the multi-scale features of the GEM, the integrated model, GEM-AQ/EC, is able to investigate chemical weather at scales from global to urban domains. The current chemical mechanism is comprised of 50 gas-phase species, 116 chemical and 19 photolysis reactions, and is complemented by a sectional aerosol module CAM (The Canadian Aerosol Module with 5 aerosols types: sulphate, black carbon, organic carbon, sea-salt and soil dust. Monthly emission inventories of black carbon and organic carbon from boreal and temperate vegetation fires were assembled using the most reliable areas burned datasets by countries, from statistical databases and derived from remote sensing products of 1995–2004. The model was run for ten years from from 1995–2004 with re-analyzed meteorology on a global uniform 1° × 1° horizontal resolution domain and 28 hybrid levels extending up to 10 hPa. The simulating results were compared with various observations including surface network around the globe and satellite data. Regional features of global aerosols are reasonably captured including emission, surface concentrations and aerosol optical depth. For various types of aerosols, satisfactory correlations were achieved between modeled and observed with some degree of systematic bias possibly due to large uncertainties in the emissions used in this study. A global distribution of natural aerosol contributions to the total aerosols is obtained and compared with observations.

  5. High-Frequency and Low-Frequency Variability in Stochastic Daily Weather Generator and Its Effect on Agricultural and Hydrologic Modelling

    Czech Academy of Sciences Publication Activity Database

    Dubrovský, Martin; Buchtele, Josef; Žalud, Z.

    2004-01-01

    Roč. 63, 1-2 (2004), s. 145-179 ISSN 0165-0009 R&D Projects: GA ČR GA205/99/1561; GA AV ČR IAA3060002 Institutional research plan: CEZ:AV0Z3042911 Keywords : Weather Generator * Agricultural Modelling * Hydrologic Modelling Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 2.035, year: 2004

  6. Thallium contamination of soils/vegetation as affected by sphalerite weathering: a model rhizospheric experiment.

    Science.gov (United States)

    Vaněk, Aleš; Grösslová, Zuzana; Mihaljevič, Martin; Ettler, Vojtěch; Chrastný, Vladislav; Komárek, Michael; Tejnecký, Václav; Drábek, Ondřej; Penížek, Vít; Galušková, Ivana; Vaněčková, Barbora; Pavlů, Lenka; Ash, Christopher

    2015-01-01

    The environmental stability of Tl-rich sphalerite in two contrasting soils was studied. Rhizospheric conditions were simulated to assess the risk associated with sulfide microparticles entering agricultural (top)soils. The data presented here clearly demonstrate a significant effect of 500 μM citric acid, a model rhizospheric solution, on ZnS alteration followed by enhanced Tl and Zn release. The relative ZnS mass loss after 28 days of citrate incubation reached 0.05 and 0.03 wt.% in Cambisol and Leptosol samples respectively, and was up to 4 times higher, compared to H2O treatments. Incongruent (i.e., substantially increased) mobilization of Tl from ZnS was observed during the incubation time. Generally higher (long-term) stability of ZnS with lower Tl release is predicted for soils enriched in carbonates. Furthermore, the important role of silicates (mainly illite) in the stabilization of mobilized Tl, linked with structural (inter)layer Tl-K exchange, is suggested. Thallium was highly bioavailable, as indicated by its uptake by white mustard; maximum Tl amounts were detected in biomass grown on the acidic Cambisol. Despite the fact that sulfides are thought as relatively stable phases in soil environments, enhanced sulfide dissolution and Tl/trace element release (and bioaccumulation) can be assumed in rhizosphere systems. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. 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'.

  8. Modeling the variability of solar radiation data among weather stations by means of principal components analysis

    International Nuclear Information System (INIS)

    Zarzo, Manuel; Marti, Pau

    2011-01-01

    Research highlights: →Principal components analysis was applied to R s data recorded at 30 stations. → Four principal components explain 97% of the data variability. → The latent variables can be fitted according to latitude, longitude and altitude. → The PCA approach is more effective for gap infilling than conventional approaches. → The proposed method allows daily R s estimations at locations in the area of study. - Abstract: Measurements of global terrestrial solar radiation (R s ) are commonly recorded in meteorological stations. Daily variability of R s has to be taken into account for the design of photovoltaic systems and energy efficient buildings. Principal components analysis (PCA) was applied to R s data recorded at 30 stations in the Mediterranean coast of Spain. Due to equipment failures and site operation problems, time series of R s often present data gaps or discontinuities. The PCA approach copes with this problem and allows estimation of present and past values by taking advantage of R s records from nearby stations. The gap infilling performance of this methodology is compared with neural networks and alternative conventional approaches. Four principal components explain 66% of the data variability with respect to the average trajectory (97% if non-centered values are considered). A new method based on principal components regression was also developed for R s estimation if previous measurements are not available. By means of multiple linear regression, it was found that the latent variables associated to the four relevant principal components can be fitted according to the latitude, longitude and altitude of the station where data were recorded from. Additional geographical or climatic variables did not increase the predictive goodness-of-fit. The resulting models allow the estimation of daily R s values at any location in the area under study and present higher accuracy than artificial neural networks and some conventional approaches

  9. Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications

    Energy Technology Data Exchange (ETDEWEB)

    Mirocha, J. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kosovic, B. [National Center for Atmospheric Research, Boulder, CO (United States); Aitken, M. L. [Univ. of Colorado, Boulder, CO (United States); Lundquist, J. K. [Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab., Golden, CO (United States)

    2014-01-10

    A generalized actuator disk (GAD) wind turbine parameterization designed for large-eddy simulation (LES) applications was implemented into the Weather Research and Forecasting (WRF) model. WRF-LES with the GAD model enables numerical investigation of the effects of an operating wind turbine on and interactions with a broad range of atmospheric boundary layer phenomena. Numerical simulations using WRF-LES with the GAD model were compared with measurements obtained from the Turbine Wake and Inflow Characterization Study (TWICS-2011), the goal of which was to measure both the inflow to and wake from a 2.3-MW wind turbine. Data from a meteorological tower and two light-detection and ranging (lidar) systems, one vertically profiling and another operated over a variety of scanning modes, were utilized to obtain forcing for the simulations, and to evaluate characteristics of the simulated wakes. Simulations produced wakes with physically consistent rotation and velocity deficits. Two surface heat flux values of 20 W m–2 and 100 W m–2 were used to examine the sensitivity of the simulated wakes to convective instability. Simulations using the smaller heat flux values showed good agreement with wake deficits observed during TWICS-2011, whereas those using the larger value showed enhanced spreading and more-rapid attenuation. This study demonstrates the utility of actuator models implemented within atmospheric LES to address a range of atmospheric science and engineering applications. In conclusion, validated implementation of the GAD in a numerical weather prediction code such as WRF will enable a wide range of studies related to the interaction of wind turbines with the atmosphere and surface.

  10. Model analysis of urbanization impacts on boundary layer meteorology under hot weather conditions: a case study of Nanjing, China

    Science.gov (United States)

    Chen, Lei; Zhang, Meigen; Wang, Yongwei

    2016-08-01

    The Weather Research and Forecasting (WRF) model, configured with a single-layer urban canopy model, was employed to investigate the influence of urbanization on boundary layer meteorological parameters during a long-lasting heat wave. This study was conducted over Nanjing city, East China, from 26 July to 4 August 2010. The impacts of urban expansion and anthropogenic heat (AH) release were simulated to quantify their effects on 2-m temperature, 2-m water vapor mixing ratio, and 10-m wind speed and heat stress index. Urban sprawl increased the daily 2-m temperature in urbanized areas by around 1.6 °C and decreased the urban diurnal temperature range (DTR) by 1.24 °C. The contribution of AH release to the atmospheric warming was nearly 22 %, but AH had little influence on the DTR. The urban regional mean surface wind speed decreased by about 0.4 m s-1, and this decrease was successfully simulated from the surface to 300 m. The influence of urbanization on 2-m water vapor mixing ratio was significant over highly urbanized areas with a decrease of 1.1-1.8 g kg-1. With increased urbanization ratio, the duration of the inversion layer was about 4 h shorter, and the lower atmospheric layer was less stable. Urban heat island (UHI) intensity was significantly enhanced when synthesizing both urban sprawl and AH release and the daily mean UHI intensity increased by 0.74 °C. Urbanization increased the time under extreme heat stress (about 40 %) and worsened the living environment in urban areas.

  11. Revisiting Intel Xeon Phi optimization of Thompson cloud microphysics scheme in Weather Research and Forecasting (WRF) model

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen

    2015-10-01

    The Thompson cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Thompson scheme incorporates a large number of improvements. Thus, we have optimized the speed of this important part of WRF. Intel Many Integrated Core (MIC) ushers in a new era of supercomputing speed, performance, and compatibility. It allows the developers to run code at trillions of calculations per second using the familiar programming model. In this paper, we present our results of optimizing the Thompson microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The coprocessor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. New optimizations for an updated Thompson scheme are discusses in this paper. The optimizations improved the performance of the original Thompson code on Xeon Phi 7120P by a factor of 1.8x. Furthermore, the same optimizations improved the performance of the Thompson on a dual socket configuration of eight core Intel Xeon E5-2670 CPUs by a factor of 1.8x compared to the original Thompson code.

  12. Behavior of uranium and thorium isotopes in soils of the Boreon area, Mercantour Massif (S.E. France). Leaching and weathering rate modeling

    International Nuclear Information System (INIS)

    Rezzoug, S.; Michel, H.; Barci-Funel, G.; Barci, V.; Fernex, F.

    2009-01-01

    Four cores were collected in weathered rocks and soils in the Boreon forest area (1765 m, Mercantour Massif, France). The samples were analyzed for the isotopes 230 Th, 232 Th, 234 U and 238 U. The activity and isotopic ratio profiles suggest that uranium was mobilized (leaching and precipitation) during the weathering process, as well as thorium but in a much less proportion. A model was drawn up to evaluate the U leaching rate and the time that some levels of the weathered rocks have been subjected to weathering. It utilizes LATHAM and SCHWARCZ's two equations,15 expressed as 234 U/ 238 U and 230 Th/ 238 U activity ratios, which assume that the alpha recoil effect allows easier leaching for 234 U than 238 U and no Th mobility. But this last assumption does not correspond to the observations made in the Boreon area, since it appears that in some soil deeper layers 230 Th and 228 Th are in radioactive deficit relatively to their parents. As there are four unknown quantities (the time, the leaching rates of 238 U, 234 U, 230 Th), the problem to be solved requires two more equations; these can be obtained utilizing the U activity ratio in water, and taking into account the 232 Th behavior. In some sites the 238 U leaching rate is high in deeper soil levels (near the fresh rocks); this would correspond to a loss of half the U amount in less than 24 000 years. (author)

  13. 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

  14. Simulation of a model predictive room temperature control by use of an ideal weather forecast; Simulation einer praediktiven Raumtemperaturregelung unter Verwendung einer idealen Wettervorhersage

    Energy Technology Data Exchange (ETDEWEB)

    Goertler, Gregor [Fachhochschulstudiengaenge Burgenland GesmbH, Pinkafeld (Austria). Kernkompetenzbereich Energie- und Umweltmanagement; Beigelboeck, Barbara

    2010-12-15

    Due to the use of MPC (Model Predictive Control) for room heating applications users and constructors expect nameable energy savings. By usage of a simulation for a special case the energy saving potential of predictive control algorithm for room temperature control in connection with an ideal weather forecast, in comparison to established algorithms (PI-control, two level controller) is estimated. The controlled system with the control variable room temperature is a room with floor heating which was modelled in TRNSYS. A linear state space model of the controlled system was derived with suitable identification methods. This model was used by the predictive control algorithm, which was programmed in MATLAB. The weather data was taken from the TRNSYS library and has been made available also for the control algorithm, so that an ideal weather forecast was established. For the example considered in this paper, the amount of energy saving was 10 % per year with the MPC-controller compared to a PI-controller. (Copyright copyright 2010 Ernst and Sohn Verlag fuer Architektur und technische Wissenschaften GmbH and Co. KG, Berlin)

  15. Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

    Science.gov (United States)

    Sanchez-Gomez, Emilia; Somot, S.; Déqué, M.

    2009-10-01

    One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.

  16. Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961-2000

    Energy Technology Data Exchange (ETDEWEB)

    Somot, S.; Deque, M. [Meteo-France CNRM/GMGEC CNRS/GAME, Toulouse (France); Sanchez-Gomez, Emilia

    2009-10-15

    One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961-2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation. (orig.)

  17. Climatology of the Iberia coastal low-level wind jet: weather research forecasting model high-resolution results

    Directory of Open Access Journals (Sweden)

    Pedro M. M. Soares

    2013-01-01

    Full Text Available Coastal low-level jets (CLLJ are a low-tropospheric wind feature driven by the pressure gradient produced by a sharp contrast between high temperatures over land and lower temperatures over the sea. This contrast between the cold ocean and the warm land in the summer is intensified by the impact of the coastal parallel winds on the ocean generating upwelling currents, sharpening the temperature gradient close to the coast and giving rise to strong baroclinic structures at the coast. During summertime, the Iberian Peninsula is often under the effect of the Azores High and of a thermal low pressure system inland, leading to a seasonal wind, in the west coast, called the Nortada (northerly wind. This study presents a regional climatology of the CLLJ off the west coast of the Iberian Peninsula, based on a 9 km resolution downscaling dataset, produced using the Weather Research and Forecasting (WRF mesoscale model, forced by 19 years of ERA-Interim reanalysis (1989–2007. The simulation results show that the jet hourly frequency of occurrence in the summer is above 30% and decreases to about 10% during spring and autumn. The monthly frequencies of occurrence can reach higher values, around 40% in summer months, and reveal large inter-annual variability in all three seasons. In the summer, at a daily base, the CLLJ is present in almost 70% of the days. The CLLJ wind direction is mostly from north-northeasterly and occurs more persistently in three areas where the interaction of the jet flow with local capes and headlands is more pronounced. The coastal jets in this area occur at heights between 300 and 400 m, and its speed has a mean around 15 m/s, reaching maximum speeds of 25 m/s.

  18. Change in Weather Research and Forecasting (WRF) Model Accuracy with Age of Input Data from the Global Forecast System (GFS)

    Science.gov (United States)

    2016-09-01

    were downloaded from the University of Wyoming’s weather website (http://www.weather.uwyo.edu/upperair/sounding.html). An alternative site is the RAOB...Midwest US Amarillo, TX AMA 2016-01-02-12 37.12, –98.66 Dodge City, KS DDC and Lamont, OK LMN 2016-02-10-12 Norman, OK OUN...0-, 24-, 48-, 72-, or 96-h forecast from the same day, 1, 2, 3, or 4 days earlier, respectively. For example, for a 12 Coordinated Universal Time

  19. Future projections of synoptic weather types over the Arabian Peninsula during the twenty-first century using an ensemble of CMIP5 models

    KAUST Repository

    El Kenawy, Ahmed M.

    2016-07-28

    An assessment of future change in synoptic conditions over the Arabian Peninsula throughout the twenty-first century was performed using 20 climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. We employed the mean sea level pressure (SLP) data from model output together with NCEP/NCAR reanalysis data and compared the relevant circulation types produced by the Lamb classification scheme for the base period 1975–2000. Overall, model results illustrated good agreement with the reanalysis, albeit with a tendency to underestimate cyclonic (C) and southeasterly (SE) patterns and to overestimate anticyclones and directional flows. We also investigated future projections for each circulation-type during the rainy season (December–May) using three Representative Concentration Pathways (RCPs), comprising RCP2.6, RCP4.5, and RCP8.5. Overall, two scenarios (RCP4.5 and RCP 8.5) revealed a statistically significant increase in weather types favoring above normal rainfall in the region (e.g., C and E-types). In contrast, weather types associated with lower amounts of rainfall (e.g., anticyclones) are projected to decrease in winter but increase in spring. For all scenarios, there was consistent agreement on the sign of change (i.e., positive/negative) for the most frequent patterns (e.g., C, SE, E and A-types), whereas the sign was uncertain for less recurrent types (e.g., N, NW, SE, and W). The projected changes in weather type frequencies in the region can be viewed not only as indicators of change in rainfall response but may also be used to inform impact studies pertinent to water resource planning and management, extreme weather analysis, and agricultural production.

  20. Future projections of synoptic weather types over the Arabian Peninsula during the twenty-first century using an ensemble of CMIP5 models

    Science.gov (United States)

    El Kenawy, Ahmed M.; McCabe, Matthew F.

    2017-10-01

    An assessment of future change in synoptic conditions over the Arabian Peninsula throughout the twenty-first century was performed using 20 climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. We employed the mean sea level pressure (SLP) data from model output together with NCEP/NCAR reanalysis data and compared the relevant circulation types produced by the Lamb classification scheme for the base period 1975-2000. Overall, model results illustrated good agreement with the reanalysis, albeit with a tendency to underestimate cyclonic (C) and southeasterly (SE) patterns and to overestimate anticyclones and directional flows. We also investigated future projections for each circulation-type during the rainy season (December-May) using three Representative Concentration Pathways (RCPs), comprising RCP2.6, RCP4.5, and RCP8.5. Overall, two scenarios (RCP4.5 and RCP 8.5) revealed a statistically significant increase in weather types favoring above normal rainfall in the region (e.g., C and E-types). In contrast, weather types associated with lower amounts of rainfall (e.g., anticyclones) are projected to decrease in winter but increase in spring. For all scenarios, there was consistent agreement on the sign of change (i.e., positive/negative) for the most frequent patterns (e.g., C, SE, E and A-types), whereas the sign was uncertain for less recurrent types (e.g., N, NW, SE, and W). The projected changes in weather type frequencies in the region can be viewed not only as indicators of change in rainfall response but may also be used to inform impact studies pertinent to water resource planning and management, extreme weather analysis, and agricultural production.

  1. What is the benefit of driving a hydrological model with data from a multi-site weather generator compared to data from a simple delta change approach?"

    Science.gov (United States)

    Rössler, Ole; Keller, Denise; Fischer, Andreas

    2016-04-01

    . Recently, a multi-site weather generator was developed and tested for downscaling purposes over Switzerland. The weather generator is of type Richardson, that is run with spatially correlated random number streams to ensure spatial consistency. As a downside, multi-site weather generators are much more complex to develop, but they are a very promising alternative downscaling technique. A new multi-site-weather generator was developed for Switzerland in a previous study (Keller et al. 2014). In this study, we tested this new multi-site-weather generator against the "standard" delta change derived data in a hydrological impact assessment study that focused on runoff in the meso-scale catchment of the river Thur catchment. Two hydrological models of different complexity were run with the data sets under present (1980-2009) and under future conditions (2070-2099), assuming the SRES A1B emission2070-2100 scenario conditions. Eight meteorological stations were used to interpolate a meteorological field that served as input to calibrate and validate the two hydrological models against runoff. The downscaling intercomparison was done for We applied 10 GCM-RCM combinations simulations of the ENSEMBLES. In case of the weather generator, that allows for multiple synthetic realizations, we generated for which change factors for each station (delta change approach) were available and generated 25 realizations of multi-site weather. with each climate model projection. Results show that the delta change driven data constitutes only one appropriate representation compared to theof a bandwidth of runoff projections yielded by the multi-site weather generator data. Especially oOn average, differences between both the two approaches are small. Low and high runoff Runoff values to both extremes are however better reproduced with the weather generator driven data set. The stochastic representation of multiday rainfall events are considered as the main reason. Hence, tThere is a clear yet small

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

    Science.gov (United States)

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

    2016-12-01

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

  3. An integrated modeling framework for real-time irrigation scheduling: the benefit of spectroscopy and weather forecasts

    Science.gov (United States)

    Brook, Anna; Polinova, Maria; Housh, Mashor

    2016-04-01

    Agriculture and agricultural landscapes are increasingly under pressure to meet the demands of a constantly increasing human population and globally changing food patterns. At the same time, there is rising concern that climate change and food security will harm agriculture in many regions of the world (Nelson et al., 2009). Facing those treats, majority of Mediterranean countries had chosen irrigated agriculture. For crop plants water is one of the most important inputs, as it is responsible for crop growth, production and it ensures the efficiency of other inputs (e.g. seeds, fertilizers and pesticide) but its use is in competition with other local sectors (e.g. industry, urban human use). Thus, well-timed availability of water is vital to agriculture for ensured yields. The increasing demand for irrigation has necessitated the need for optimal irrigation scheduling techniques that coordinate the timing and amount of irrigation to optimally manage the water use in agriculture systems. The irrigation scheduling problem can be challenging as farmers try to deal with different conflicting objectives of maximizing their yield while minimizing irrigation water use. Another challenge in the irrigation scheduling problem is attributed to the uncertain factors involved in the plant growth process during the growing season. Most notable, the climatic factors such as evapotranspiration and rainfall, these uncertain factors add a third objective to the farmer perspective, namely, minimizing the risk associated with these uncertain factors. Nevertheless, advancements in weather forecasting reduced the uncertainty level associated with future climatic data. Thus, climatic forecasts can be reliably employed to guide optimal irrigation schedule scheme when coupled with stochastic optimization models (Housh et al., 2012). Many studies have concluded that optimal irrigation decisions can provide substantial economic value over conventional irrigation decisions (Wang and Cai 2009

  4. A Numerical Method to Generate High Temporal Resolution Precipitation Time Series by Combining Weather Radar Measurements with a Nowcast Model

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2014-01-01

    The topic of this paper is temporal interpolation of precipitation observed by weather radars. Precipitation measurements with high spatial and temporal resolution are, in general, desired for urban drainage applications. An advection-based interpolation method is developed which uses methods...

  5. Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria

    DEFF Research Database (Denmark)

    Eitzinger, J; Thaler, S; Schmid, E

    2013-01-01

    the start of flowering. Two locations in Austria, representing different agro-climatic zones and soil conditions, were included in the simulations over 2 years, 2003 and 2004, exhibiting contrasting weather conditions. In addition, soil management was modified at both sites by following either ploughing...

  6. Tropical and Subtropical Cloud Transitions in Weather and Climate Prediction Models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI)

    Science.gov (United States)

    Teixeira, J.; Cardoso, S.; Bonazzola, M.; Cole, J.; DeGenio, A.; DeMott, C.; Franklin, C.; Hannay, C.; Jakob, C.; Jiao, Y.; hide

    2011-01-01

    A model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/ WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June July August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the 40-yr ECMWF Re-Analysis (ERA-40) in the deep tropics (in particular) with the corresponding impact in the outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid water path and shortwave radiation; significant differences between the models in terms of vertical cross sections of cloud properties (in particular), vertical velocity, and relative humidity. An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of some models and ERA-40 in the stratocumulus regions [as compared to the first International Satellite Cloud Climatology Project (ISCCP)] is associated not only with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition that occurs too

  7. Management Strategies to Sustain Irrigated Agriculture with Combination of Remote Sensing, Weather Monitoring & Forecasting and SWAP Modeling

    Science.gov (United States)

    Ermolaeva, Olga; Zeyliger, Anatoly

    2017-04-01

    Today world's water systems face formidable threats due to climate change and increasing water withdraw for agriculture, industry and domestic use. Projected in many parts of the earth increases in temperature, evaporation, and drought frequency shrunk water availability and magnify water scarcity. Declining irrigation water supplies threaten the sustainability of irrigated agricultural production which plays a critical role in meeting global food needs. In irrigated agriculture there is a strong call for deep efforts in order on the one hand to improve water efficiency use and on the other to maximize yields. The aim of this research is to provide tool to optimize water application with crop irrigation by sprinkling in order to sustain irrigated agriculture under limited water supply by increasing net returns per unit of water. For this aim some field experimental results of 2012 year growing season of alfalfa, corn and soya irrigated by sprinkling machines crops at left bank of Volga River at Saratov Region of Russia. Additionally a combination of data sets was used which includes MODIS images, local meteorological station and results of SWAP (Soil-Water-Atmosphere-Plant) modeling. This combination was used to estimate crop water stress defined as ratio between actual (ETa) and potential (ETc) evapotranspiration. By this way it was determined the effect of applied irrigation scheduling and water application depths on evapotranspiration, crop productivity and water stress coefficient. Aggregation of actual values of crop water stress and biomass data predicted by SWAP agrohydrological model with weather forecasting and irrigation scheduling was used to indicate of both rational timing and amount of irrigation water allocation. This type of analysis facilitating an efficient water management can be extended to irrigated areas by developing maps of water efficiency application serving as an irrigation advice system for farmers at his fields and as a decision support

  8. Gap-filling of dry weather flow rate and water quality measurements in urban catchments by a time series modelling approach

    DEFF Research Database (Denmark)

    Sandoval, Santiago; Vezzaro, Luca; Bertrand-Krajewski, Jean-Luc

    2016-01-01

    seeks to evaluate the potential of the Singular Spectrum Analysis (SSA), a time-series modelling/gap-filling method, to complete dry weather time series. The SSA method is tested by reconstructing 1000 artificial discontinuous time series, randomly generated from real flow rate and total suspended......Flow rate and water quality dry weather time series in combined sewer systems might contain an important amount of missing data due to several reasons, such as failures related to the operation of the sensor or additional contributions during rainfall events. Therefore, the approach hereby proposed...... solids (TSS) online measurements (year 2007, 2 minutes time-step, combined system, Ecully, Lyon, France). Results show up the potential of the method to fill gaps longer than 0.5 days, especially between 0.5 days and 1 day (mean NSE > 0.6) in the flow rate time series. TSS results still perform very...

  9. 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.

  10. Using Haines Index coupled with fire weather model predicted from high resolution LAM forecasts to asses wildfire extreme behaviour in Southern Europe.

    Science.gov (United States)

    Gaetani, Francesco; Baptiste Filippi, Jean; Simeoni, Albert; D'Andrea, Mirko

    2010-05-01

    Haines Index (HI) was developed by USDA Forest Service to measure the atmosphere's contribution to the growth potential of a wildfire. The Haines Index combines two atmospheric factors that are known to have an effect on wildfires: Stability and Dryness. As operational tools, HI proved its ability to predict plume dominated high intensity wildfires. However, since HI does not take into account the fuel continuity, composition and moisture conditions and the effects of wind and topography on fire behaviour, its use as forecasting tool should be carefully considered. In this work we propose the use of HI, predicted from HR Limited Area Model forecasts, coupled with a Fire Weather model (i.e., RISICO system) fully operational in Italy since 2003. RISICO is based on dynamic models able to represent in space and in time the effects that environment and vegetal physiology have on fuels and, in turn, on the potential behaviour of wildfires. The system automatically acquires from remote databases a thorough data-set of input information both of in situ and spatial nature. Meteorological observations, radar data, Limited Area Model weather forecasts, EO data, and fuel data are managed by a Unified Interface able to process a wide set of different data. Specific semi-physical models are used in the system to simulate the dynamics of the fuels (load and moisture contents of dead and live fuel) and the potential fire behaviour (rate of spread and linear intensity). A preliminary validation of this approach will be provided with reference to Sardinia and Corsica Islands, two major islands of the Mediterranean See frequently affected by extreme plume dominated wildfires. A time series of about 3000 wildfires burnt in Sardinia and Corsica in 2007 and 2008 will be used to evaluate the capability of HI coupled with the outputs of the Fire Weather model to forecast the actual risk in time and in space.

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

    Science.gov (United States)

    Gupta, Amit; Shaina, Nagpal

    2017-08-01

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

  12. 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.

  13. 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.

  14. Sensitivity of Numerical Weather Prediction to the Choice of Variable for Atmospheric Moisture Analysis into the Brazilian Global Model Data Assimilation System

    Directory of Open Access Journals (Sweden)

    Thamiris B. Campos

    2018-03-01

    Full Text Available Due to the high spatial and temporal variability of atmospheric water vapor associated with the deficient methodologies used in its quantification and the imperfect physics parameterizations incorporated in the models, there are significant uncertainties in characterizing the moisture field. The process responsible for incorporating the information provided by observation into the numerical weather prediction is denominated data assimilation. The best result in atmospheric moisture depend on the correct choice of the moisture control variable. Normalized relative humidity and pseudo-relative humidity are the variables usually used by the main weather prediction centers. The objective of this study is to assess the sensibility of the Center for Weather Forecast and Climate Studies to choose moisture control variable in the data assimilation scheme. Experiments using these variables are carried out. The results show that the pseudo-relative humidity improves the variables that depend on temperature values but damage the moisture field. The opposite results show when the simulation used the normalized relative humidity. These experiments suggest that the pseudo-relative humidity should be used in the cyclical process of data assimilation and the normalized relative humidity should be used in non-cyclic process (e.g., nowcasting application in high resolution.

  15. 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.

  16. Simulating spatial and temporally related fire weather

    Science.gov (United States)

    Isaac C. Grenfell; Mark Finney; Matt Jolly

    2010-01-01

    Use of fire behavior models has assumed an increasingly important role for managers of wildfire incidents to make strategic decisions. For fire risk assessments and danger rating at very large spatial scales, these models depend on fire weather variables or fire danger indices. Here, we describe a method to simulate fire weather at a national scale that captures the...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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. ...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

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

    Science.gov (United States)

    Qi, Le; Zheng, Zhongyi; Gang, Longhui

    2017-10-01

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

  11. Model of pre-harvest quality of pineapple guava fruits (Acca sellowiana (O. berg burret as a function of weather conditions of the crops

    Directory of Open Access Journals (Sweden)

    Alfonso Parra-Coronado

    Full Text Available ABSTRACT Weather conditions influence the quality parameters of pineapple guava fruit during growth and development. The aim of this study was to propose a model of pre-harvest fruit quality as a function of weather conditions in the cultivation area. Twenty trees were flagged per farm in 2 localities of the Department of Cundinamarca, Colombia: Tenjo (2,580 m.a.s.l.; 12.5 °C; relative humidity between 74 and 86%; mean annual precipitation 765 mm and San Francisco de Sales (1,800 m.a.s.l.; 20.6 °C; relative humidity between 63 and 97%; mean annual precipitation 1,493 mm. Measurements were performed every 7 days during 2 harvest periods starting on days 96 (Tenjo and 99 (San Francisco de Sales after anthesis and until harvest. The models were obtained using Excel® Solver, and a set of data was obtained for the 2 different cultivar periods and each study site. The results showed that altitude, growing degree days, and accumulated precipitation are the weather variables with the highest influence on the physicochemical characteristics of the fruit during growth. The models of fresh weight, total titratable acidity, and skin firmness better predict the development of fruit quality during growth and development. Equations were obtained for increases of length and diameter as a function of fruit weight and for days from anthesis as a function of growing degree days and altitude. The regression analysis parameters showed that the models adequately predicted the fruit characteristics during growth for both localities, and a cross-validation analysis showed a good statistical fit between the estimated and observed values.

  12. 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 ...

  13. Simulating the meteorology and PM10 concentrations in Arizona dust storms using the Weather Research and Forecasting model with Chemistry (Wrf-Chem).

    Science.gov (United States)

    Hyde, Peter; Mahalov, Alex; Li, Jialun

    2018-03-01

    Nine dust storms in south-central Arizona were simulated with the Weather Research and Forecasting with Chemistry model (WRF-Chem) at 2 km resolution. The windblown dust emission algorithm was the Air Force Weather Agency model. In comparison with ground-based PM 10 observations, the model unevenly reproduces the dust-storm events. The model adequately estimates the location and timing of the events, but it is unable to precisely replicate the magnitude and timing of the elevated hourly concentrations of particles 10 µm and smaller ([PM 10 ]).Furthermore, the model underestimated [PM 10 ] in highly agricultural Pinal County because it underestimated surface wind speeds and because the model's erodible fractions of the land surface data were too coarse to effectively resolve the active and abandoned agricultural lands. In contrast, the model overestimated [PM 10 ] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) for which the surface-layer speeds were too strong. In Phoenix, AZ, the model's performance depended on the event, with both under- and overestimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM 10 ] highly relies on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM 10 ] in that region. Both 24-hr and 1-hr measured [PM 10 ] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as 10-fold and the latter exceeding health-based guidelines by as much as 70-fold. Monsoonal thunderstorms not only produce elevated [PM 10 ], but also cause urban flash floods and disrupt water resource deliveries. Given the severity and frequency of these dust storms, and conceding that the modeling system applied in this work did not produce the desired agreement between simulations and

  14. Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set

    Science.gov (United States)

    Drusch, M.

    2007-02-01

    Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.

  15. 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.

  16. Solar weather monitoring

    Directory of Open Access Journals (Sweden)

    J.-F. Hochedez

    2005-11-01

    Full Text Available Space Weather nowcasting and forecasting require solar observations because geoeffective disturbances can arise from three types of solar phenomena: coronal mass ejections (CMEs, flares and coronal holes. For each, we discuss their definition and review their precursors in terms of remote sensing and in-situ observations. The objectives of Space Weather require some specific instrumental features, which we list using the experience gained from the daily operations of the Solar Influences Data analysis Centre (SIDC at the Royal Observatory of Belgium. Nowcasting requires real-time monitoring to assess quickly and reliably the severity of any potentially geoeffective solar event. Both research and forecasting could incorporate more observations in order to feed case studies and data assimilation respectively. Numerical models will result in better predictions of geomagnetic storms and solar energetic particle (SEP events. We review the data types available to monitor solar activity and interplanetary conditions. They come from space missions and ground observatories and range from sequences of dopplergrams, magnetograms, white-light, chromospheric, coronal, coronagraphic and radio images, to irradiance and in-situ time-series. Their role is summarized together with indications about current and future solar monitoring instruments.

  17. Parametrization of the Richardson weather generator within the European Union

    NARCIS (Netherlands)

    Voet, van der P.; Kramer, K.; Diepen, van C.A.

    1996-01-01

    The Richardson model for mathematically generating daily weather data was parametrized. Thirty years' time-series of the 355 main meteorological stations in the European Union formed the database. Model parameters were derived from both observed weather station data and interpolated weather data on

  18. Application of Intel Many Integrated Core (MIC) architecture to the Yonsei University planetary boundary layer scheme in Weather Research and Forecasting model

    Science.gov (United States)

    Huang, Melin; Huang, Bormin; Huang, Allen H.

    2014-10-01

    The Weather Research and Forecasting (WRF) model provided operational services worldwide in many areas and has linked to our daily activity, in particular during severe weather events. The scheme of Yonsei University (YSU) is one of planetary boundary layer (PBL) models in WRF. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transports in the whole atmospheric column, determines the flux profiles within the well-mixed boundary layer and the stable layer, and thus provide atmospheric tendencies of temperature, moisture (including clouds), and horizontal momentum in the entire atmospheric column. The YSU scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. To accelerate the computation process of the YSU scheme, we employ Intel Many Integrated Core (MIC) Architecture as it is a multiprocessor computer structure with merits of efficient parallelization and vectorization essentials. Our results show that the MIC-based optimization improved the performance of the first version of multi-threaded code on Xeon Phi 5110P by a factor of 2.4x. Furthermore, the same CPU-based optimizations improved the performance on Intel Xeon E5-2603 by a factor of 1.6x as compared to the first version of multi-threaded code.

  19. Turbulence Dissipation Rates in the Planetary Boundary Layer from Wind Profiling Radars and Mesoscale Numerical Weather Prediction Models during WFIP2

    Science.gov (United States)

    Bianco, L.; McCaffrey, K.; Wilczak, J. M.; Olson, J. B.; Kenyon, J.

    2016-12-01

    When forecasting winds at a wind plant for energy production, the turbulence parameterizations in the forecast models are crucial for understanding wind plant performance. Recent research shows that the turbulence (eddy) dissipation rate in planetary boundary layer (PBL) parameterization schemes introduces significant uncertainty in the Weather Research and Forecasting (WRF) model. Thus, developing the capability to measure dissipation rates in the PBL will allow for identification of weaknesses in, and improvements to the parameterizations. During a preliminary field study at the Boulder Atmospheric Observatory in spring 2015, a 915-MHz wind profiling radar (WPR) measured dissipation rates concurrently with sonic anemometers mounted on a 300-meter tower. WPR set-up parameters (e.g., spectral resolution), post-processing techniques (e.g., filtering for non-atmospheric signals), and spectral averaging were optimized to capture the most accurate Doppler spectra for measuring spectral widths for use in the computation of the eddy dissipation rates. These encouraging results lead to the implementation of the observing strategy on a 915-MHz WPR in Wasco, OR, operating as part of the Wind Forecasting Improvement Project 2 (WFIP2). These observations are compared to dissipation rates calculated from the High-Resolution Rapid Refresh model, a WRF-based mesoscale numerical weather prediction model run for WFIP2 at 3000 m horizontal grid spacing and with a nest, which has 750-meter horizontal grid spacing, in the complex terrain region of the Columbia River Gorge. The observed profiles of dissipation rates are used to evaluate the PBL parameterization schemes used in the HRRR model, which are based on the modeled turbulent kinetic energy and a tunable length scale.

  20. 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.

  1. 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; hide

    2012-01-01

    The NASA GSFC Space Weather Center (http://swc.gsfc.nasa.gov) is committed to providing forecasts, alerts, research, and educational support to address NASA's space weather needs - in addition to the needs of the general space weather community. We provide a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, custom space weather alerts and products, weekly summaries and reports, and most recently - video casts. There are many challenges in providing accurate descriptions of past, present, and expected space weather events - and the Space Weather Center at NASA GSFC employs several innovative solutions to provide access to a comprehensive collection of both observational data, as well as space weather model/simulation data. We'll describe the challenges we've faced with managing hundreds of data streams, running models in real-time, data storage, and data dissemination. We'll also highlight several systems and tools that are utilized by the Space Weather Center in our daily operations, all of which are available to the general community as well. These systems and services include a web-based application called the Integrated Space Weather Analysis System (iSWA http://iswa.gsfc.nasa.gov), two mobile space weather applications for both IOS and Android devices, an external API for web-service style access to data, google earth compatible data products, and a downloadable client-based visualization tool.

  2. 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

  3. Statistical Analysis of Model Data for Operational Space Launch Weather Support at Kennedy Space Center and Cape Canaveral Air Force Station

    Science.gov (United States)

    Bauman, William H., III

    2010-01-01

    The 12-km resolution North American Mesoscale (NAM) model (MesoNAM) is used by the 45th Weather Squadron (45 WS) Launch Weather Officers at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to support space launch weather operations. The 45 WS tasked the Applied Meteorology Unit to conduct an objective statistics-based analysis of MesoNAM output compared to wind tower mesonet observations and then develop a an operational tool to display the results. The National Centers for Environmental Prediction began running the current version of the MesoNAM in mid-August 2006. The period of record for the dataset was 1 September 2006 - 31 January 2010. The AMU evaluated MesoNAM hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The MesoNAM forecast winds, temperature and dew point were compared to the observed values of these parameters from the sensors in the KSC/CCAFS wind tower network. The data sets were stratified by model initialization time, month and onshore/offshore flow for each wind tower. Statistics computed included bias (mean difference), standard deviation of the bias, root mean square error (RMSE) and a hypothesis test for bias = O. Twelve wind towers located in close proximity to key launch complexes were used for the statistical analysis with the sensors on the towers positioned at varying heights to include 6 ft, 30 ft, 54 ft, 60 ft, 90 ft, 162 ft, 204 ft and 230 ft depending on the launch vehicle and associated weather launch commit criteria being evaluated. These twelve wind towers support activities for the Space Shuttle (launch and landing), Delta IV, Atlas V and Falcon 9 launch vehicles. For all twelve towers, the results indicate a diurnal signal in the bias of temperature (T) and weaker but discernable diurnal signal in the bias of dewpoint temperature (T(sub d)) in the MesoNAM forecasts. Also, the standard deviation of the bias and RMSE of T, T(sub d), wind speed and wind

  4. 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.

  5. 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

  6. 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

  7. A Modulated-Gradient Parametrization for the Large-Eddy Simulation of the Atmospheric Boundary Layer Using the Weather Research and Forecasting Model

    Science.gov (United States)

    Khani, Sina; Porté-Agel, Fernando

    2017-12-01

    The performance of the modulated-gradient subgrid-scale (SGS) model is investigated using large-eddy simulation (LES) of the neutral atmospheric boundary layer within the weather research and forecasting model. Since the model includes a finite-difference scheme for spatial derivatives, the discretization errors may affect the simulation results. We focus here on understanding the effects of finite-difference schemes on the momentum balance and the mean velocity distribution, and the requirement (or not) of the ad hoc canopy model. We find that, unlike the Smagorinsky and turbulent kinetic energy (TKE) models, the calculated mean velocity and vertical shear using the modulated-gradient model, are in good agreement with Monin-Obukhov similarity theory, without the need for an extra near-wall canopy model. The structure of the near-wall turbulent eddies is better resolved using the modulated-gradient model in comparison with the classical Smagorinsky and TKE models, which are too dissipative and yield unrealistic smoothing of the smallest resolved scales. Moreover, the SGS fluxes obtained from the modulated-gradient model are much smaller near the wall in comparison with those obtained from the regular Smagorinsky and TKE models. The apparent inability of the LES model in reproducing the mean streamwise component of the momentum balance using the total (resolved plus SGS) stress near the surface is probably due to the effect of the discretization errors, which can be calculated a posteriori using the Taylor-series expansion of the resolved velocity field. Overall, we demonstrate that the modulated-gradient model is less dissipative and yields more accurate results in comparison with the classical Smagorinsky model, with similar computational costs.

  8. Very short-term rainfall forecasting by effectively using the ensemble outputs of numerical weather prediction models

    Science.gov (United States)

    Wu, Ming-Chang; Lin, Gwo-Fong; Feng, Lei; Hwang, Gong-Do

    2017-04-01

    In Taiwan, heavy rainfall brought by typhoons often causes serious disasters and leads to loss of life and property. In order to reduce the impact of these disasters, accurate rainfall forecasts are always important for civil protection authorities to prepare proper measures in advance. In this study, a methodology is proposed for providing very short-term (1- to 6-h ahead) rainfall forecasts in a basin-scale area. The proposed methodology is developed based on the use of analogy reasoning approach to effectively integrate the ensemble precipitation forecasts from a numerical weather prediction system in Taiwan. To demonstrate the potential of the proposed methodology, an application to a basin-scale area (the Choshui River basin located in west-central Taiwan) during five typhoons is conducted. The results indicate that the proposed methodology yields more accurate hourly rainfall forecasts, especially the forecasts with a lead time of 1 to 3 hours. On average, improvement of the Nash-Sutcliffe efficiency coefficient is about 14% due to the effective use of the ensemble forecasts through the proposed methodology. The proposed methodology is expected to be useful for providing accurate very short-term rainfall forecasts during typhoons.

  9. Assessment of Planetary-Boundary-Layer Schemes in the Weather Research and Forecasting Model Within and Above an Urban Canopy Layer

    Science.gov (United States)

    Ferrero, Enrico; Alessandrini, Stefano; Vandenberghe, Francois

    2018-03-01

    We tested several planetary-boundary-layer (PBL) schemes available in the Weather Research and Forecasting (WRF) model against measured wind speed and direction, temperature and turbulent kinetic energy (TKE) at three levels (5, 9, 25 m). The Urban Turbulence Project dataset, gathered from the outskirts of Turin, Italy and used for the comparison, provides measurements made by sonic anemometers for more than 1 year. In contrast to other similar studies, which have mainly focused on short-time periods, we considered 2 months of measurements (January and July) representing both the seasonal and the daily variabilities. To understand how the WRF-model PBL schemes perform in an urban environment, often characterized by low wind-speed conditions, we first compared six PBL schemes against observations taken by the highest anemometer located in the inertial sub-layer. The availability of the TKE measurements allows us to directly evaluate the performances of the model; results of the model evaluation are presented in terms of quantile versus quantile plots and statistical indices. Secondly, we considered WRF-model PBL schemes that can be coupled to the urban-surface exchange parametrizations and compared the simulation results with measurements from the two lower anemometers located inside the canopy layer. We find that the PBL schemes accounting for TKE are more accurate and the model representation of the roughness sub-layer improves when the urban model is coupled to each PBL scheme.

  10. 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…

  11. 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…

  12. 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.

  13. 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...

  14. 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

  15. 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.

  16. The impact of convection in the West African monsoon region on global weather forecasts - explicit vs. parameterised convection simulations using the ICON model

    Science.gov (United States)

    Pante, Gregor; Knippertz, Peter

    2017-04-01

    The West African monsoon is the driving element of weather and climate during summer in the Sahel region. It interacts with mesoscale convective systems (MCSs) and the African easterly jet and African easterly waves. Poor representation of convection in numerical models, particularly its organisation on the mesoscale, can result in unrealistic forecasts of the monsoon dynamics. Arguably, the parameterisation of convection is one of the main deficiencies in models over this region. Overall, this has negative impacts on forecasts over West Africa itself but may also affect remote regions, as waves originating from convective heating are badly represented. Here we investigate those remote forecast impacts based on daily initialised 10-day forecasts for July 2016 using the ICON model. One set of simulations employs the default setup of the global model with a horizontal grid spacing of 13 km. It is compared with simulations using the 2-way nesting capability of ICON. A second model domain over West Africa (the nest) with 6.5 km grid spacing is sufficient to explicitly resolve MCSs in this region. In the 2-way nested simulations, the prognostic variables of the global model are influenced by the results of the nest through relaxation. The nest with explicit convection is able to reproduce single MCSs much more realistically compared to the stand-alone global simulation with parameterised convection. Explicit convection leads to cooler temperatures in the lower troposphere (below 500 hPa) over the northern Sahel due to stronger evaporational cooling. Overall, the feedback of dynamic variables from the nest to the global model shows clear positive effects when evaluating the output of the global domain of the 2-way nesting simulation and the output of the stand-alone global model with ERA-Interim re-analyses. Averaged over the 2-way nested region, bias and root mean squared error (RMSE) of temperature, geopotential, wind and relative humidity are significantly reduced in

  17. Assessment of the ClimGen stochastic weather generator at ...

    African Journals Online (AJOL)

    Simulation of agricultural risk assessment and environmental management requires long series of daily weather data for the area being modelled. Acquiring and formatting this data can be very complex and time-consuming. This has led to the development of weather generation procedures and tools. Weather generators ...

  18. 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

  19. Enabling Philippine Farmers to Adapt to Climate Variability Using Seasonal Climate and Weather Forecast with a Crop Simulation Model in an SMS-based Farmer Decision Support System

    Science.gov (United States)

    Ebardaloza, J. B. R.; Trogo, R.; Sabido, D. J.; Tongson, E.; Bagtasa, G.; Balderama, O. F.

    2015-12-01

    Corn farms in the Philippines are rainfed farms, hence, it is of utmost importance to choose the start of planting date so that the critical growth stages that are in need of water will fall on dates when there is rain. Most farmers in the Philippines use superstitions and traditions as basis for farming decisions such as when to start planting [1]. Before climate change, superstitions like planting after a feast day of a saint has worked for them but with the recent progression of climate change, farmers now recognize that there is a need for technological intervention [1]. The application discussed in this paper presents a solution that makes use of meteorological station sensors, localized seasonal climate forecast, localized weather forecast and a crop simulation model to provide recommendations to farmers based on the crop cultivar, soil type and fertilizer type used by farmers. It is critical that the recommendations given to farmers are not generic as each farmer would have different needs based on their cultivar, soil, fertilizer, planting schedule and even location [2]. This application allows the farmer to inquire about whether it will rain in the next seven days, the best date to start planting based on the potential yield upon harvest, when to apply fertilizer and by how much, when to water and by how much. Short messaging service (SMS) is the medium chosen for this application because while mobile penetration in the Philippines is as high as 101%, the smart phone penetration is only at 15% [3]. SMS has been selected as it has been identified as the most effective way of reaching farmers with timely agricultural information and knowledge [4,5]. The recommendations while derived from making use of Automated Weather Station (AWS) sensor data, Weather Research Forecasting (WRF) models and DSSAT 4.5 [9], are translated into the local language of the farmers and in a format that is easily understood as recommended in [6,7,8]. A pilot study has been started

  20. Association between Empirically Estimated Monsoon Dynamics and Other Weather Factors and Historical Tea Yields in China: Results from a Yield Response Model

    Directory of Open Access Journals (Sweden)

    Rebecca Boehm

    2016-04-01

    Full Text Available Farmers in China’s tea-growing regions report that monsoon dynamics and other weather factors are changing and that this is affecting tea harvest decisions. To assess the effect of climate change on tea production in China, this study uses historical weather and production data from 1980 to 2011 to construct a yield response model that estimates the partial effect of weather factors on tea yields in China, with a specific focus on East Asian Monsoon dynamics. Tea (Camellia sinensis (L. Kunze has not been studied using these methods even though it is an important crop for human nutrition and the economic well-being of rural communities in many countries. Previous studies have approximated the monsoon period using historical average onset and retreat dates, which we believe limits our understanding of how changing monsoon patterns affect crop productivity. In our analysis, we instead estimate the monsoon season across China’s tea growing regions empirically by identifying the unknown breakpoints in the year-by-province cumulative precipitation. We find that a 1% increase in the monsoon retreat date is associated with 0.481%–0.535% reduction in tea yield. In the previous year, we also find that a 1% increase in the date of the monsoon retreat is associated with a 0.604% decrease in tea yields. For precipitation, we find that a 1% increase in average daily precipitation occurring during the monsoon period is associated with a 0.184%–0.262% reduction in tea yields. In addition, our models show that 1% increase in the average daily monsoon precipitation from the previous growing season is associated with 0.258%–0.327% decline in yields. We also find that a 1% decrease in solar radiation in the previous growing season is associated with 0.554%-0.864% decrease in tea yields. These findings suggest the need for adaptive management and harvesting strategies given climate change projections and the known negative association between excess

  1. 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

  2. On the use of wave parameterizations and a storm impact scaling model in National Weather Service Coastal Flood and decision support operations

    Science.gov (United States)

    Mignone, Anthony; Stockdon, H.; Willis, M.; Cannon, J.W.; Thompson, R.

    2012-01-01

    National Weather Service (NWS) Weather Forecast Offices (WFO) are responsible for issuing coastal flood watches, warnings, advisories, and local statements to alert decision makers and the general public when rising water levels may lead to coastal impacts such as inundation, erosion, and wave battery. Both extratropical and tropical cyclones can generate the prerequisite rise in water level to set the stage for a coastal impact event. Forecasters use a variety of tools including computer model guidance and local studies to help predict the potential severity of coastal flooding. However, a key missing component has been the incorporation of the effects of waves in the prediction of total water level and the associated coastal impacts. Several recent studies have demonstrated the importance of incorporating wave action into the NWS coastal flood program. To follow up on these studies, this paper looks at the potential of applying recently developed empirical parameterizations of wave setup, swash, and runup to the NWS forecast process. Additionally, the wave parameterizations are incorporated into a storm impact scaling model that compares extreme water levels to beach elevation data to determine the mode of coastal change at predetermined “hotspots” of interest. Specifically, the storm impact model compares the approximate storm-induced still water level, which includes contributions from tides, storm surge, and wave setup, to dune crest elevation to determine inundation potential. The model also compares the combined effects of tides, storm surge, and the 2 % exceedance level for vertical wave runup (including both wave setup and swash) to dune toe and crest elevations to determine if erosion and/or ocean overwash may occur. The wave parameterizations and storm impact model are applied to two cases in 2009 that led to significant coastal impacts and unique forecast challenges in North Carolina: the extratropical “Nor'Ida” event during 11-14 November and

  3. 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

  4. Predicting the outbreak of hand, foot, and mouth disease in Nanjing, China: a time-series model based on weather variability

    Science.gov (United States)

    Liu, Sijun; Chen, Jiaping; Wang, Jianming; Wu, Zhuchao; Wu, Weihua; Xu, Zhiwei; Hu, Wenbiao; Xu, Fei; Tong, Shilu; Shen, Hongbing

    2017-10-01

    Hand, foot, and mouth disease (HFMD) is a significant public health issue in China and an accurate prediction of epidemic can improve the effectiveness of HFMD control. This study aims to develop a weather-based forecasting model for HFMD using the information on climatic variables and HFMD surveillance in Nanjing, China. Daily data on HFMD cases and meteorological variables between 2010 and 2015 were acquired from the Nanjing Center for Disease Control and Prevention, and China Meteorological Data Sharing Service System, respectively. A multivariate seasonal autoregressive integrated moving average (SARIMA) model was developed and validated by dividing HFMD infection data into two datasets: the data from 2010 to 2013 were used to construct a model and those from 2014 to 2015 were used to validate it. Moreover, we used weekly prediction for the data between 1 January 2014 and 31 December 2015 and leave-1-week-out prediction was used to validate the performance of model prediction. SARIMA (2,0,0)52 associated with the average temperature at lag of 1 week appeared to be the best model (R 2 = 0.936, BIC = 8.465), which also showed non-significant autocorrelations in the residuals of the model. In the validation of the constructed model, the predicted values matched the observed values reasonably well between 2014 and 2015. There was a high agreement rate between the predicted values and the observed values (sensitivity 80%, specificity 96.63%). This study suggests that the SARIMA model with average temperature could be used as an important tool for early detection and prediction of HFMD outbreaks in Nanjing, China.

  5. Uruguay - Surface Weather Observations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Surface weather observation forms for 26 stations in Uruguay. Period of record 1896-2005, with two to eight observations per day. Files created through a...

  6. 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.

  7. Oil Rig Weather Observations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Weather observations taken at offshore platforms along the United States coastlines. The majority are located in oil-rich areas of the Gulf of Mexico, Gulf of...

  8. 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

  9. Cape Kennedy Weather Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Digitized data taken from original weather observations taken at Cape Kennedy Air Force Station, Florida. Elements recorded are wind speed and direction,...

  10. NOAA Weather Radio

    Science.gov (United States)

    del tiempo incluido. Si eres quieres ser avisado de las advertencias y relojes de día o de noche, un Weather Radio relojes son independientes o basadas en el Condado (parroquia basados en Luisiana), aunque

  11. Space Weather Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Collection includes a variety of space weather datasets from the National Oceanic and Atmospheric Administration and from the World Data Service for Geophysics,...

  12. Daily Weather Maps

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Several different government offices have published the Daily weather maps over its history. The publication has also gone by different names over time. The U.S....

  13. Winter Weather: Indoor Safety

    Science.gov (United States)

    ... Extreme Heat Older Adults (Aged 65+) Infants and Children Chronic Medical Conditions Low Income Athletes Outdoor Workers Pets Hot Weather Tips Warning Signs and Symptoms FAQs Social Media How to Stay Cool Missouri Cooling Centers Extreme ...

  14. Winter Weather: Outdoor Safety

    Science.gov (United States)

    ... Extreme Heat Older Adults (Aged 65+) Infants and Children Chronic Medical Conditions Low Income Athletes Outdoor Workers Pets Hot Weather Tips Warning Signs and Symptoms FAQs Social Media How to Stay Cool Missouri Cooling Centers Extreme ...

  15. Winter Weather Checklists

    Science.gov (United States)

    ... Extreme Heat Older Adults (Aged 65+) Infants and Children Chronic Medical Conditions Low Income Athletes Outdoor Workers Pets Hot Weather Tips Warning Signs and Symptoms FAQs Social Media How to Stay Cool Missouri Cooling Centers Extreme ...

  16. Winter Weather: Frostbite

    Science.gov (United States)

    ... Extreme Heat Older Adults (Aged 65+) Infants and Children Chronic Medical Conditions Low Income Athletes Outdoor Workers Pets Hot Weather Tips Warning Signs and Symptoms FAQs Social Media How to Stay Cool Missouri Cooling Centers Extreme ...

  17. Surface Weather Observations Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Surface Weather Observation 1001 Forms is a set of historical manuscript records for the period 1893-1948. The collection includes two very similar form types: Form...

  18. Trait-based representation of hydrological functional properties of plants in weather and ecosystem models

    Directory of Open Access Journals (Sweden)

    Ashley M. Matheny

    2017-02-01

    Full Text Available Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings were both feasible and functional for early model generations, in light of the pace at which our knowledge of functional ecology, ecosystem demographics, and vegetation-climate feedbacks has advanced and the ever growing demand for enhanced model performance, these groupings have become antiquated and are identified as a key source of model uncertainty. The newest wave of model development is centered on shifting the vegetation paradigm away from plant functional types (PFTs and towards flexible trait-based representations. These models seek to improve errors in ecosystem fluxes that result from information loss due to over-aggregation of dissimilar species into the same functional class. We advocate the importance of the inclusion of plant hydraulic trait representation within the new paradigm through a framework of the whole-plant hydraulic strategy. Plant hydraulic strategy is known to play a critical role in the regulation of stomatal conductance and thus transpiration and latent heat flux. It is typical that coexisting plants employ opposing hydraulic strategies, and therefore have disparate patterns of water acquisition and use. Hydraulic traits are deterministic of drought resilience, response to disturbance, and other demographic processes. The addition of plant hydraulic properties in models may not only improve the simulation of carbon and water fluxes but also vegetation population distributions.

  19. Genetic programming-based mathematical modeling of influence of weather parameters in BOD5 removal by Lemna minor.

    Science.gov (United States)

    Chandrasekaran, Sivapragasam; Sankararajan, Vanitha; Neelakandhan, Nampoothiri; Ram Kumar, Mahalakshmi

    2017-11-04

    This study, through extensive experiments and mathematical modeling, reveals that other than retention time and wastewater temperature (T w ), atmospheric parameters also play important role in the effective functioning of aquatic macrophyte-based treatment system. Duckweed species Lemna minor is considered in this study. It is observed that the combined effect of atmospheric temperature (T atm ), wind speed (U w ), and relative humidity (RH) can be reflected through one parameter, namely the "apparent temperature" (T a ). A total of eight different models are considered based on the combination of input parameters and the best mathematical model is arrived at which is validated through a new experimental set-up outside the modeling period. The validation results are highly encouraging. Genetic programming (GP)-based models are found to reveal deeper understandings of the wetland process.

  20. From the Sun’s atmosphere to the Earth’s atmosphere: an overview of scientific models available for space weather developments

    Directory of Open Access Journals (Sweden)

    C. Lathuillère

    Full Text Available Space weather aims at setting operational numerical tools in order to nowcast, forecast and quantify the solar activity events, the magnetosphere, ionosphere and thermosphere responses and the consequences on our technological societies. These tools can be divided in two parts. The first has a geophysical base (Sun, interplanetary medium, magnetosphere, atmosphere. The second concerns technological applications (telecommunications, spacecraft orbits, power plants .... In this paper, we aim at giving an overview of the models that belong to the first class (geophysics that might serve in the future as a basis for building global operational codes. For each model, we consider the physics underneath, the input and output parameters, and whether it is already operational, whether it may become operational in the near future, or if it is an academic research tool. Relevant references are given in order to serve as a starting point for further readings.

    Key words. Interplanetary physics (general or miscellaneous, Ionosphere (modelling and forecasting, Magnetospheric physics (general or miscellaneous

  1. From the Sun’s atmosphere to the Earth’s atmosphere: an overview of scientific models available for space weather developments

    Directory of Open Access Journals (Sweden)

    C. Lathuillère

    2002-07-01

    Full Text Available Space weather aims at setting operational numerical tools in order to nowcast, forecast and quantify the solar activity events, the magnetosphere, ionosphere and thermosphere responses and the consequences on our technological societies. These tools can be divided in two parts. The first has a geophysical base (Sun, interplanetary medium, magnetosphere, atmosphere. The second concerns technological applications (telecommunications, spacecraft orbits, power plants .... In this paper, we aim at giving an overview of the models that belong to the first class (geophysics that might serve in the future as a basis for building global operational codes. For each model, we consider the physics underneath, the input and output parameters, and whether it is already operational, whether it may become operational in the near future, or if it is an academic research tool. Relevant references are given in order to serve as a starting point for further readings.Key words. Interplanetary physics (general or miscellaneous, Ionosphere (modelling and forecasting, Magnetospheric physics (general or miscellaneous

  2. Expansion of the Real-Time SPoRT-Land Information System for NOAA/National Weather Service Situational Awareness and Local Modeling Applications

    Science.gov (United States)

    Case, Jonathan L; White, Kristopher D.

    2014-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014.This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations.

  3. Mass-balance modeling of mineral weathering rates and CO2 consumption in the forested, metabasaltic Hauver Branch watershed, Catoctin Mountain, Maryland, USA

    Science.gov (United States)

    Rice, Karen; Price, Jason R.; Szymanski, David W.

    2013-01-01

    Mineral weathering rates and a forest macronutrient uptake stoichiometry were determined for the forested, metabasaltic Hauver Branch watershed in north-central Maryland, USA. Previous studies of Hauver Branch have had an insufficient number of analytes to permit determination of rates of all the minerals involved in chemical weathering, including biomass. More equations in the mass-balance matrix were added using existing mineralogic information. The stoichiometry of a deciduous biomass term was determined using multi-year weekly to biweekly stream-water chemistry for a nearby watershed, which drains relatively unreactive quartzite bedrock.At Hauver Branch, calcite hosts ~38 mol% of the calcium ion (Ca2+) contained in weathering minerals, but its weathering provides ~90% of the stream water Ca2+. This occurs in a landscape with a regolith residence time of more than several Ka (kiloannum). Previous studies indicate that such old regolith does not typically contain dissolving calcite that affects stream Ca2+/Na+ ratios. The relatively high calcite dissolution rate likely reflects dissolution of calcite in fractures of the deep critical zone.Of the carbon dioxide (CO2) consumed by mineral weathering, calcite is responsible for approximately 27%, with the silicate weathering consumption rate far exceeding that of the global average. The chemical weathering of mafic terrains in decaying orogens thus may be capable of influencing global geochemical cycles, and therefore, climate, on geological timescales. Based on carbon-balance calculations, atmospheric-derived sulfuric acid is responsible for approximately 22% of the mineral weathering occurring in the watershed. Our results suggest that rising air temperatures, driven by global warming and resulting in higher precipitation, will cause the rate of chemical weathering in the Hauver Branch watershed to increase until a threshold temperature is reached. Beyond the threshold temperature, increased recharge would

  4. Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

    Science.gov (United States)

    Spectral nudging – a scale-selective interior constraint technique – is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonst...

  5. Investigating Surface Bias Errors in the Weather Research and Forecasting (WRF) Model using a Geographic Information System (GIS)

    Science.gov (United States)

    2015-02-01

    Computational and Information Sciences Directorate Battlefield Environment Division (ATTN: RDRL- CIE -M) White Sands Missile Range, NM 88002-5501 8. PERFORMING...meteorological parameters, which became our focus. We found that elevation accounts for a significant portion of the variance in the model error. The...found that elevation accounts for a significant portion of the variance in the model error of surface temperature and relative humidity predictions

  6. Large-eddy simulation of stable atmospheric boundary layers to develop better turbulence closures for climate and weather models

    Science.gov (United States)

    Bou-Zeid, Elie; Huang, Jing; Golaz, Jean-Christophe

    2011-11-01

    A disconnect remains between our improved physical understanding of boundary layers stabilized by buoyancy and how we parameterize them in coarse atmospheric models. Most operational climate models require excessive turbulence mixing in such conditions to prevent decoupling of the atmospheric component from the land component, but the performance of such a model is unlikely to be satisfactory under weakly and moderately stable conditions. Using Large-eddy simulation, we revisit some of the basic challenges in parameterizing stable atmospheric boundary layers: eddy-viscosity closure is found to be more reliable due to an improved alignment of vertical Reynolds stresses and mean strains under stable conditions, but the dependence of the magnitude of the eddy viscosity on stability is not well represented by several models tested here. Thus, we propose a new closure that reproduces the different stability regimes better. Subsequently, tests of this model in the GFDL's single-column model (SCM) are found to yield good agreement with LES results in idealized steady-stability cases, as well as in cases with gradual and sharp changes of stability with time.

  7. Effects of forest cover changes in European Russia on regional weather conditions: results of numerical experiments with the COSMO-CLM model

    Science.gov (United States)

    Olchev, Alexander; Kuzmina, Ekaterina; Rozinkina, Inna; Nikitin, Mikhail; Rivin, Gdaly S.

    2017-04-01

    The forests have a significant effect on the climatic system. They capture CO2 from the atmosphere, regulate the surface evaporation and runoff, and influence the radiation and thermal conditions of the land surface. It is obvious, that their influence depends on many different factors including regional climate conditions, land use and vegetation structure, surface topography, etc. The main goal of the study is to assess the possible influence of forest cover changes (under deforestation and/or afforestation) on regional weather conditions in the central part of European Russia using the results of modeling experiments provided by the meso-scale COSMO-CLM model. The need of the study lies in a lack of the experimental and modeling data characterizing the influence of the forest and land-use changes on regional weather conditions in European part of Russia. The forest ecosystems in the study region play a very important biosphere role that is significantly increased in the last decades due to considerable strengthening of anthropogenic activity in the area of European Russia. The area selected for the study is located in the central part of European Russia between 55 and 59N and 28 and 37E. It comprises several geographical zones including dark-coniferous forests of the South-European taiga in the north, the mixed forests in the central part and the broad-leaved forests in the south. The forests within the study area are very heterogeneous. The total area covered by forests according to recent remote sensing data is about 50%. The numerical experiments were provided using the COSMO-CLM model with the spatial resolution 13.2 km. As initial and boundary conditions for the numerical experiments the global reanalysis ERA Interim (with the 6-hour resolution in time and 0.75° × 0.75° in space) were used. The weather conditions were simulated in a continuous cycle for several months for the entire area of European Russia using the results of global reanalysis on

  8. Expansion of the Real-time Sport-land Information System for NOAA/National Weather Service Situational Awareness and Local Modeling Applications

    Science.gov (United States)

    Case, Jonathan L.

    2014-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center has been running a real-time version of the Land Information System (LIS) since summer 2010 (hereafter, SPoRTLIS). The real-time SPoRT-LIS runs the Noah land surface model (LSM) in an offline capacity apart from a numerical weather prediction model, using input atmospheric and precipitation analyses (i.e., "forcings") to drive the Noah LSM integration at 3-km resolution. Its objectives are to (1) produce local-scale information about the soil state for NOAA/National Weather Service (NWS) situational awareness applications such as drought monitoring and assessing flood potential, and (2) provide land surface initialization fields for local modeling initiatives. The current domain extent has been limited by the input atmospheric analyses that drive the Noah LSM integration within SPoRT-LIS, specifically the National Centers for Environmental Prediction (NCEP) Stage IV precipitation analyses. Due to the nature of the geographical edges of the Stage IV precipitation grid and its limitations in the western U.S., the SPoRT-LIS was originally confined to a domain fully nested within the Stage IV grid, over the southeastern half of the Conterminous United States (CONUS). In order to expand the real-time SPoRT-LIS to a full CONUS domain, alternative precipitation forcing datasets were explored in year-long, offline comparison runs of the Noah LSM. Based on results of these comparison simulations, we chose to implement the radar/gauge-based precipitation analyses from the National Severe Storms Laboratory as a replacement to the Stage IV product. The Multi-Radar Multi-Sensor (MRMS; formerly known as the National Mosaic and multi-sensor Quantitative precipitation estimate) product has full CONUS coverage at higher-resolution, thereby providing better coverage and greater detail than that of the Stage IV product. This paper will describe the expanded/upgraded SPoRT-LIS, present comparisons between the

  9. The European tracer experiment ETEX: a real-time long range atmospheric dispersion model exercise in different weather conditions

    International Nuclear Information System (INIS)

    Graziani, G.; )

    1998-01-01

    Two long-range tracer experiments were conducted. An inert, non-depositing tracer was being released at Rennes in France for 12 hours. The 168 sampling ground stations were run by the National Meteorological Services. Twenty-four institutions took part in the real-time forecasting of the cloud evolution using 28 long-range dispersion models. The horizontal projection of the cloud evolution over Europe was combined with real-time aerial chemical analysis. The results of the comparison indicate that a limited group of models (7-8) were capable of obtaining a good reproduction of the cloud movement throughout Europe for the first release. Large differences were, however, found in the predicted tracer concentration at a particular location. For the second release, there were large differences between the measured and calculated cloud, particularly after a front passage, which indicates that some efforts have still to be spent before consensus on the model reliability is achieved. (P.A.)

  10. 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

  11. A short-range weather prediction system for South Africa based on a multi-model approach

    CSIR Research Space (South Africa)

    Landman, S

    2012-10-01

    Full Text Available stream_source_info Landman5_2012.pdf.txt stream_content_type text/plain stream_size 44898 Content-Encoding ISO-8859-1 stream_name Landman5_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 1 A short... to be skillful. Moreover, the system outscores the forecast skill of the individual models. Keywords: short-range, ensemble, forecasting, precipitation, multi-model, verification Tel: +27 12 367 6054...

  12. Towards the development of a climate model evaluation system in the Centre for Australian Weather and climate research

    International Nuclear Information System (INIS)

    Rikus, Lawrie; Hu, Ben; Dix, Martin; Watterson, Ian; Elliott, Tracey

    2010-01-01

    The paper describes the philosophy of the climate model evaluation scheme being developed within CAWCR as well as the database of observational data-sets which under-pins it. It argues that model evaluation should measure 'fitness-of-purpose', that it should be objective and that it should be based on the largest possible number of observational data-sets. Time series plots of smoothed observational data and the relevance of the disparity between data from different sources are discussed. The paper calls for active participation of the Australian climate research community in the project.

  13. Assessing the performance of the 'Simple Model of the Atmospheric Radiative Transfer of Sunshine' (SMARTS2) in a first tier of software using empirical weather data

    International Nuclear Information System (INIS)

    Askar, H.K.; Batty, W.J.

    2005-01-01

    Software is being developed to assess the performance of a new form of triple glazing system that can be used in hot arid countries. The method includes the insertion of an angled glazing element within the window cavity to maximize the reflection of incident direct insolation while maintaining an acceptable level of day lighting. SMARTS2 (Simple Model of the Atmospheric Radiative Transfer of Sunshine) is used as a first tier platform to provide solar input (i.e. direct, diffused and albedo) for tilted surfaces for simulations of optical performance, using the visible band of the electromagnetic spectrum. Results, thus, obtained can be used in a ray-tracing algorithm to calculate an optimal angle of insertion of the suggested element that corresponds to the solar geometry of particular latitudes. General weather files of eight countries were used for the analysis, which included an examination of detailed annual solar data and turbidity (i.e. dust) levels for Kuwait. SMARTS2 performance as a solar model was assessed within the narrow visible band

  14. Sensitivity of Turbine-Height Wind Speeds to Parameters in Planetary Boundary-Layer and Surface-Layer Schemes in the Weather Research and Forecasting Model

    Science.gov (United States)

    Yang, Ben; Qian, Yun; Berg, Larry K.; Ma, Po-Lun; Wharton, Sonia; Bulaevskaya, Vera; Yan, Huiping; Hou, Zhangshuan; Shaw, William J.

    2017-01-01

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

  15. Impact of the Assimilation of Hyperspectral Infrared Retrieved Profiles on Advanced Weather and Research Model Simulations of a Non-Convective Wind Event

    Science.gov (United States)

    Berndt, E. B.; Zavodsky, B. T.; Folmer, M. J.; Jedlovec, G. J.

    2014-01-01

    Non-convective wind events commonly occur with passing extratropical cyclones and have significant societal and economic impacts. Since non-convective winds often occur in the absence of specific phenomena such as a thunderstorm, tornado, or hurricane, the public are less likely to heed high wind warnings and continue daily activities. Thus non-convective wind events result in as many fatalities as straight line thunderstorm winds. One physical explanation for non-convective winds includes tropopause folds. Improved model representation of stratospheric air and associated non-convective wind events could improve non-convective wind forecasts and associated warnings. In recent years, satellite data assimilation has improved skill in forecasting extratropical cyclones; however errors still remain in forecasting the position and strength of extratropical cyclones as well as the tropopause folding process. The goal of this study is to determine the impact of assimilating satellite temperature and moisture retrieved profiles from hyperspectral infrared (IR) sounders (i.e. Atmospheric Infrared Sounder (AIRS), Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI)) on the model representation of the tropopause fold and an associated high wind event that impacted the Northeast United States on 09 February 2013. Model simulations using the Advanced Research Weather Research and Forecasting Model (ARW) were conducted on a 12-km grid with cycled data assimilation mimicking the operational North American Model (NAM). The results from the satellite assimilation run are compared to a control experiment (without hyperspectral IR retrievals), 32-km North American Regional Reanalysis (NARR) interpolated to a 12-km grid, and 13-km Rapid Refresh analyses.

  16. Impact of the Assimilation of Hyperspectral Infrared Profiles on Advanced Weather and Research Model Simulations of a Non-Convective Wind Event

    Science.gov (United States)

    Berndt, Emily B.; Zavodsky, Bradley T; Jedlovec, Gary J.; Elmer, Nicholas J.

    2013-01-01

    Non-convective wind events commonly occur with passing extratropical cyclones and have significant societal and economic impacts. Since non-convective winds often occur in the absence of specific phenomena such as a thunderstorm, tornado, or hurricane, the public are less likely to heed high wind warnings and continue daily activities. Thus non-convective wind events result in as many fatalities as straight line thunderstorm winds. One physical explanation for non-convective winds includes tropopause folds. Improved model representation of stratospheric air and associated non-convective wind events could improve non-convective wind forecasts and associated warnings. In recent years, satellite data assimilation has improved skill in forecasting extratropical cyclones; however errors still remain in forecasting the position and strength of extratropical cyclones as well as the tropopause folding process. The goal of this study is to determine the impact of assimilating satellite temperature and moisture retrieved profiles from hyperspectral infrared (IR) sounders (i.e. Atmospheric Infrared Sounder (AIRS), Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI)) on the model representation of the tropopause fold and an associated high wind event that impacted the Northeast United States on 09 February 2013. Model simulations using the Advanced Research Weather Research and Forecasting Model (ARW) were conducted on a 12-km grid with cycled data assimilation mimicking the operational North American Model (NAM). The results from the satellite assimilation run are compared to a control experiment (without hyperspectral IR retrievals), North American Regional Reanalysis (NARR) reanalysis, and Rapid Refresh analyses.

  17. The Impact of the Assimilation of Hyperspectral Infrared Retrieved Profiles on Advanced Weather and Research Model Simulations of a Non-Convective Wind Event

    Science.gov (United States)

    Berndt, Emily; Zavodsky, Bradley; Jedlovec, Gary; Elmer, Nicholas

    2013-01-01

    Non-convective wind events commonly occur with passing extratropical cyclones and have significant societal and economic impacts. Since non-convective winds often occur in the absence of specific phenomena such as a thunderstorm, tornado, or hurricane, the public are less likely to heed high wind warnings and continue daily activities. Thus non-convective wind events result in as many fatalities as straight line thunderstorm winds. One physical explanation for non-convective winds includes tropopause folds. Improved model representation of stratospheric air and associated non-convective wind events could improve non-convective wind forecasts and associated warnings. In recent years, satellite data assimilation has improved skill in forecasting extratropical cyclones; however errors still remain in forecasting the position and strength of extratropical cyclones as well as the tropopause folding process. The goal of this study is to determine the impact of assimilating satellite temperature and moisture retrieved profiles from hyperspectral infrared (IR) sounders (i.e. Atmospheric Infrared Sounder (AIRS), Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI)) on the model representation of the tropopause fold and an associated high wind event that impacted the Northeast United States on 09 February 2013. Model simulations using the Advanced Research Weather Research and Forecasting Model (ARW) were conducted on a 12-km grid with cycled data assimilation mimicking the operational North American Model (NAM). The results from the satellite assimilation run are compared to a control experiment (without hyperspectral IR retrievals), Modern Era-Retrospective Analysis for Research and Applications (MERRA) reanalysis, and Rapid Refresh analyses.

  18. 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.

  19. Assessing the impact of extreme air temperature on fruit trees by modeling weather dependent phenology with variety-specific thermal requirements

    Science.gov (United States)

    Alfieri, Silvia Maria; De Lorenzi, Francesca; Missere, Daniele; Buscaroli, Claudio; Menenti, Massimo

    2013-04-01

    Extremely high and extremely low temperature may have a terminal impact on the productivity of fruit tree if occurring at critical phases of development. Notorious examples are frost during flowering or extremely high temperature during fruit setting. The dates of occurrence of such critical phenological stages depend on the weather history from the start of the yearly development cycle in late autumn, thus the impact of climate extremes can only be evaluated correctly if the phenological development is modeled taking into account the weather history of the specific year being evaluated. Climate change impact may lead to a shift in timing of phenological stages and change in the duration of vegetative and reproductive phases. A changing climate can also exhibit a greater climatic variability producing quite large changes in the frequency of extreme climatic events. We propose a two-stage approach to evaluate the impact of predicted future climate on the productivity of fruit trees. The phenological development is modeled using phase - specific thermal times and variety specific thermal requirements for several cultivars of pear, apricot and peach. These requirements were estimated using phenological observations over several years in Emilia Romagna region and scientific literature. We calculated the dates of start and end of rest completion, bud swell, flowering, fruit setting and ripening stages , from late autumn through late summer. Then phase-specific minimum and maximum cardinal temperature were evaluated for present and future climate to estimate how frequently they occur during any critically sensitive phenological phase. This analysis has been done for past climate (1961 - 1990) and fifty realizations of a year representative of future climate (2021 - 2050). A delay in rest completion of about 10-20 days has been predicted for future climate for most of the cultivars. On the other hand the predicted rise in air temperature causes an earlier development of

  20. 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

  1. An operational weather radar-based Quantitative Precipitation Estimation and its application in catchment water resources modeling

    DEFF Research Database (Denmark)

    He, Xin; Vejen, Flemming; Stisen, Simon

    2011-01-01

    of precipitation compared with rain-gauge-based methods, thus providing the basis for better water resources assessments. The radar QPE algorithm called ARNE is a distance-dependent areal estimation method that merges radar data with ground surface observations. The method was applied to the Skjern River catchment...... in western Denmark where alternative precipitation estimates were also used as input to an integrated hydrologic model. The hydrologic responses from the model were analyzed by comparing radar- and ground-based precipitation input scenarios. Results showed that radar QPE products are able to generate...... reliable simulations of stream flow and water balance. The potential of using radar-based precipitation was found to be especially high at a smaller scale, where the impact of spatial resolution was evident from the stream discharge results. Also, groundwater recharge was shown to be sensitive...

  2. 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

  3. Modelling fire frequency and area burned across phytoclimatic regions in Spain using reanalysis data and the Canadian Fire Weather Index System

    Science.gov (United States)

    Bedia, J.; Herrera, S.; Gutiérrez, J. M.

    2013-09-01

    We develop fire occurrence and burned area models in peninsular Spain, an area of high variability in climate and fuel types, for the period 1990-2008. We based the analysis on a phytoclimatic classification aiming to the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climatic and fuel conditions. We used generalized linear models (GLM) and multivariate adaptive regression splines (MARS) as modelling algorithms and temperature, relative humidity, precipitation and wind speed, taken from the ERA-Interim reanalysis, as well as the components of the Canadian Forest Fire Weather Index (FWI) System as predictors. We also computed the standardized precipitation-evapotranspiration index (SPEI) as an additional predictor for the models of burned area. We found two contrasting fire regimes in terms of area burned and number of fires: one characterized by a bimodal annual pattern, characterizing the Nemoral and Oro-boreal phytoclimatic types, and another one exhibiting an unimodal annual cycle, with the fire season concentrated in the summer months in the Mediterranean and Arid regions. The fire occurrence models attained good skill in most of the phytoclimatic zones considered, yielding in some zones notably high correlation coefficients between the observed and modelled inter-annual fire frequencies. Total area burned also exhibited a high dependence on the meteorological drivers, although their ability to reproduce the observed annual burned area time series was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, and also SPEI in some of the burned area models, highlighting the adequacy of the FWI system for fire modelling applications and leaving the door opened to the development a more complex modelling framework based on these predictors. Furthermore, we demonstrate the potential usefulness

  4. Hydrologic applications of weather radar

    Science.gov (United States)

    Seo, Dong-Jun; Habib, Emad; Andrieu, Hervé; Morin, Efrat

    2015-12-01

    By providing high-resolution quantitative precipitation information (QPI), weather radars have revolutionized hydrology in the last two decades. With the aid of GIS technology, radar-based quantitative precipitation estimates (QPE) have enabled routine high-resolution hydrologic modeling in many parts of the world. Given the ever-increasing need for higher-resolution hydrologic and water resources information for a wide range of applications, one may expect that the use of weather radar will only grow. Despite the tremendous progress, a number of significant scientific, technological and engineering challenges remain to realize its potential. New challenges are also emerging as new areas of applications are discovered, explored and pursued. The purpose of this special issue is to provide the readership with some of the latest advances, lessons learned, experiences gained, and science issues and challenges related to hydrologic applications of weather radar. The special issue features 20 contributions on various topics which reflect the increasing diversity as well as the areas of focus in radar hydrology today. The contributions may be grouped as follows:

  5. SWIFF: Space weather integrated forecasting framework

    Directory of Open Access Journals (Sweden)

    Frederiksen Jacob Trier

    2013-02-01

    Full Text Available SWIFF is a project funded by the Seventh Framework Programme of the European Commission to study the mathematical-physics models that form the basis for space weather forecasting. The phenomena of space weather span a tremendous scale of densities and temperature with scales ranging 10 orders of magnitude in space and time. Additionally even in local regions there are concurrent processes developing at the electron, ion and global scales strongly interacting with each other. The fundamental challenge in modelling space weather is the need to address multiple physics and multiple scales. Here we present our approach to take existing expertise in fluid and kinetic models to produce an integrated mathematical approach and software infrastructure that allows fluid and kinetic processes to be modelled together. SWIFF aims also at using this new infrastructure to model specific coupled processes at the Solar Corona, in the interplanetary space and in the interaction at the Earth magnetosphere.

  6. Evaluation of cloud prediction and determination of critical relative humidity for a mesoscale numerical weather prediction model

    Energy Technology Data Exchange (ETDEWEB)

    Seaman, N.L.; Guo, Z.; Ackerman, T.P. [Pennsylvania State Univ., University Park, PA (United States)

    1996-04-01

    Predictions of cloud occurrence and vertical location from the Pennsylvannia State University/National Center for Atmospheric Research nonhydrostatic mesoscale model (MM5) were evaluated statistically using cloud observations obtained at Coffeyville, Kansas, as part of the Second International satellite Cloud Climatology Project Regional Experiment campaign. Seventeen cases were selected for simulation during a November-December 1991 field study. MM5 was used to produce two sets of 36-km simulations, one with and one without four-dimensional data assimilation (FDDA), and a set of 12-km simulations without FDDA, but nested within the 36-km FDDA runs.

  7. 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.

  8. 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.

  9. NATO Advanced Research Workshop on The Chemistry of Weathering

    CERN Document Server

    1985-01-01

    Several important developments in our understanding of the chemistry of weathering have occurred in the last few years: 1. There has been a major breakthrough in our understanding of the mechanisms controlling the kinetics of sil icate dissolution, and there have been major advances in computer modeling of weathering processes. 2. There has been a growing recognition of the importance of organic solutes in the weathering process, and hence of the inter-relationships between mineral weathering and the terrestrial ecosystem. 3. The impact of acid deposition ("acid rain") has been widely recognized. The processes by which acid deposition is neutral ized are closely related to the processes of normal chemical weathering; an understanding of the chemistry of weathering is thus essential for predicting the effects of acid deposition. 4. More high-qual ity data have become available on the chemical dynamics of smal I watersheds and large river systems, which represent the integrated effects of chemical weathering.

  10. Evaluation of a seven-year air quality simulation using the Weather Research and Forecasting (WRF)/Community Multiscale Air Quality (CMAQ) models in the eastern United States.

    Science.gov (United States)

    Zhang, Hongliang; Chen, Gang; Hu, Jianlin; Chen, Shu-Hua; Wiedinmyer, Christine; Kleeman, Michael; Ying, Qi

    2014-03-01

    The performance of the Weather Research and Forecasting (WRF)/Community Multi-scale Air Quality (CMAQ) system in the eastern United States is analyzed based on results from a seven-year modeling study with a 4-km spatial resolution. For 2-m temperature, the monthly averaged mean bias (MB) and gross error (GE) values are generally within the recommended performance criteria, although temperature is over-predicted with MB values up to 2K. Water vapor at 2-m is well-predicted but significant biases (>2 g kg(-1)) were observed in wintertime. Predictions for wind speed are satisfactory but biased towards over-prediction with 0nitrate and sulfate concentrations are also well reproduced. The other unresolved PM2.5 components (OTHER) are significantly overestimated by more than a factor of two. No conclusive explanations can be made regarding the possible cause of this universal overestimation, which warrants a follow-up study to better understand this problem. Copyright © 2013 Elsevier B.V. All rights reserved.

  11. Assessing the Impact of Surface and Upper-Air Observations on the Forecast Skill of the ACCESS Numerical Weather Prediction Model over Australia

    Directory of Open Access Journals (Sweden)

    Sergei Soldatenko

    2018-01-01

    Full Text Available The impact of the Australian Bureau of Meteorology’s in situ observations (land and sea surface observations, upper air observations by radiosondes, pilot balloons, wind profilers, and aircraft observations on the short-term forecast skill provided by the ACCESS (Australian Community Climate and Earth-System Simulator global numerical weather prediction (NWP system is evaluated using an adjoint-based method. This technique makes use of the adjoint perturbation forecast model utilized within the 4D-Var assimilation system, and is able to calculate the individual impact of each assimilated observation in a cycling NWP system. The results obtained show that synoptic observations account for about 60% of the 24-h forecast error reduction, with the remainder accounted for by aircraft (12.8%, radiosondes (10.5%, wind profilers (3.9%, pilot balloons (2.8%, buoys (1.7% and ships (1.2%. In contrast, the largest impact per observation is from buoys and aircraft. Overall, all observation types have a positive impact on the 24-h forecast skill. Such results help to support the decision-making process regarding the evolution of the observing network, particularly at the national level. Consequently, this 4D-Var-based approach has great potential as a tool to assist the design and running of an efficient and effective observing network.

  12. Weather In Some Islands

    Institute of Scientific and Technical Information of China (English)

    王良华

    2007-01-01

    There are four seasons in a year. When spring comes, the weather is mild(温和的). Summer comes after spring. Summer is the hottest season of the year. Autumn follows summer. It is the best season of the year. Winter is the coldest season of the year. Some islands(岛) have their own particular(特别的) seasons because their weather is very much affected(影响) by the oceans(海洋) around them. In Britain, winter is not very cold and summer is not very hot.

  13. Solar EUV irradiance for space weather applications

    Science.gov (United States)

    Viereck, R. A.

    2015-12-01

    Solar EUV irradiance is an important driver of space weather models. Large changes in EUV and x-ray irradiances create large variability in the ionosphere and thermosphere. Proxies such as the F10.7 cm radio flux, have provided reasonable estimates of the EUV flux but as the space weather models become more accurate and the demands of the customers become more stringent, proxies are no longer adequate. Furthermore, proxies are often provided only on a daily basis and shorter time scales are becoming important. Also, there is a growing need for multi-day forecasts of solar EUV irradiance to drive space weather forecast models. In this presentation we will describe the needs and requirements for solar EUV irradiance information from the space weather modeler's perspective. We will then translate these requirements into solar observational requirements such as spectral resolution and irradiance accuracy. We will also describe the activities at NOAA to provide long-term solar EUV irradiance observations and derived products that are needed for real-time space weather modeling.

  14. A revised radiation package of G-packed McICA and two-stream approximation: Performance evaluation in a global weather forecasting model

    Science.gov (United States)

    Baek, Sunghye

    2017-07-01

    For more efficient and accurate computation of radiative flux, improvements have been achieved in two aspects, integration of the radiative transfer equation over space and angle. First, the treatment of the Monte Carlo-independent column approximation (MCICA) is modified focusing on efficiency using a reduced number of random samples ("G-packed") within a reconstructed and unified radiation package. The original McICA takes 20% of CPU time of radiation in the Global/Regional Integrated Model systems (GRIMs). The CPU time consumption of McICA is reduced by 70% without compromising accuracy. Second, parameterizations of shortwave two-stream approximations are revised to reduce errors with respect to the 16-stream discrete ordinate method. Delta-scaled two-stream approximation (TSA) is almost unanimously used in Global Circulation Model (GCM) but contains systematic errors which overestimate forward peak scattering as solar elevation decreases. These errors are alleviated by adjusting the parameterizations of each scattering element—aerosol, liquid, ice and snow cloud particles. Parameterizations are determined with 20,129 atmospheric columns of the GRIMs data and tested with 13,422 independent data columns. The result shows that the root-mean-square error (RMSE) over the all atmospheric layers is decreased by 39% on average without significant increase in computational time. Revised TSA developed and validated with a separate one-dimensional model is mounted on GRIMs for mid-term numerical weather forecasting. Monthly averaged global forecast skill scores are unchanged with revised TSA but the temperature at lower levels of the atmosphere (pressure ≥ 700 hPa) is slightly increased (< 0.5 K) with corrected atmospheric absorption.

  15. 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.

  16. Chemical Weathering on Venus

    Science.gov (United States)

    Zolotov, Mikhail

    2018-01-01

    Chemical and phase compositions of Venus's surface could reflect history of gas- and fluid-rock interactions, recent and past climate changes, and a loss of water from the Earth's sister planet. The concept of chemical weathering on Venus through gas-solid type reactions has been established in 1960s after the discovery of hot and dense CO2-rich atmosphere inferred from Earth-based and Mariner 2 radio emission data. Initial works suggested carbonation, hydration, and oxidation of exposed igneous rocks and a control (buffering) of atmospheric gases by solid-gas type chemical equilibria in the near-surface lithosphere. Calcite, quartz, wollastonite, amphiboles, and Fe oxides were considered likely secondary minerals. Since the late 1970s, measurements of trace gases in the sub-cloud atmosphere by Pioneer Venus and Venera entry probes and Earth-based infrared spectroscopy doubted the likelihood of hydration and carbonation. The H2O gas content appeared to be low to allow a stable existence of hydrated and a majority of OH-bearing minerals. The concentration of SO2 was too high to allow the stability of calcite and Ca-rich silicates with respect to sulfatization to CaSO4. In 1980s, the supposed ongoing consumption of atmospheric SO2 to sulfates gained support by the detection of an elevated bulk S content at Venera and Vega landing sites. The induced composition of the near-surface atmosphere implied oxidation of ferrous minerals to magnetite and hematite, consistent with the infrared reflectance of surface materials. The likelihood of sulfatization and oxidation has been illustrated in modeling experiments at simulated Venus conditions. Venus's surface morphology suggests that hot surface rocks and fines of mainly mafic composition contacted atmospheric gases during several hundreds of millions years since a global volcanic resurfacing. Some exposed materials could have reacted at higher and lower temperatures in a presence of diverse gases at different altitudinal

  17. Dress for the Weather

    Science.gov (United States)

    Glen, Nicole J.; Smetana, Lara K.

    2010-01-01

    "If someone were traveling to our area for the first time during this time of year, what would you tell them to bring to wear? Why?" This question was used to engage students in a guided-inquiry unit about how climate differs from weather. In this lesson, students explored local and national data sets to give "travelers" advice…

  18. 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...

  19. Weather and Flight Testing

    Science.gov (United States)

    Wiley, Scott

    2007-01-01

    This viewgraph document reviews some of the weather hazards involved with flight testing. Some of the hazards reviewed are: turbulence, icing, thunderstorms and winds and windshear. Maps, pictures, satellite pictures of the meteorological phenomena and graphs are included. Also included are pictures of damaged aircraft.

  20. Introducing GFWED: The Global Fire Weather Database

    Science.gov (United States)

    Field, R. D.; Spessa, A. C.; Aziz, N. A.; Camia, A.; Cantin, A.; Carr, R.; de Groot, W. J.; Dowdy, A. J.; Flannigan, M. D.; Manomaiphiboon, K.; hide

    2015-01-01

    The Canadian Forest Fire Weather Index (FWI) System is the mostly widely used fire danger rating system in the world. We have developed a global database of daily FWI System calculations, beginning in 1980, called the Global Fire WEather Database (GFWED) gridded to a spatial resolution of 0.5 latitude by 2-3 longitude. Input weather data were obtained from the NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA), and two different estimates of daily precipitation from rain gauges over land. FWI System Drought Code calculations from the gridded data sets were compared to calculations from individual weather station data for a representative set of 48 stations in North, Central and South America, Europe, Russia,Southeast Asia and Australia. Agreement between gridded calculations and the station-based calculations tended to be most different at low latitudes for strictly MERRA based calculations. Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in Brazil reached unrealistically high values exceeding DCD1500 during the dry season but was too low over Southeast Asia during the dry season. These biases are consistent with those previously identified in MERRAs precipitation, and they reinforce the need to consider alternative sources of precipitation data. GFWED can be used for analyzing historical relationships between fire weather and fire activity at continental and global scales, in identifying large-scale atmosphereocean controls on fire weather, and calibration of FWI-based fire prediction models.

  1. 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

  2. Space Weather Forecasting and Supporting Research in the USA

    Science.gov (United States)

    Pevtsov, A. A.

    2017-12-01

    In the United State, scientific research in space weather is funded by several Government Agencies including the National Science Foundation (NSF) and the National Aeronautics and Space Agency (NASA). For civilian and commercial purposes, space weather forecast is done by the Space Weather Prediction Center (SWPC) of the National Oceanic and Atmospheric Administration (NOAA). Observational data for modeling come from the network of groundbased observatories funded via various sources, as well as from the instruments on spacecraft. Numerical models used in forecast are developed in framework of individual research projects. The article provides a brief review of current state of space weather-related research and forecasting in the USA.

  3. 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...

  4. 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...

  5. 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)

  6. Application of Weather Research and Forecasting Model with Chemistry (WRF/Chem) over northern China: Sensitivity study, comparative evaluation, and policy implications

    Science.gov (United States)

    Wang, Litao; Zhang, Yang; Wang, Kai; Zheng, Bo; Zhang, Qiang; Wei, Wei

    2016-01-01

    An extremely severe and persistent haze event occurred over the middle and eastern China in January 2013, with the record-breaking high concentrations of fine particulate matter (PM2.5). In this study, an online-coupled meteorology-air quality model, the Weather Research and Forecasting Model with Chemistry (WRF/Chem), is applied to simulate this pollution episode over East Asia and northern China at 36- and 12-km grid resolutions. A number of simulations are conducted to examine the sensitivities of the model predictions to various physical schemes. The results show that all simulations give similar predictions for temperature, wind speed, wind direction, and humidity, but large variations exist in the prediction for precipitation. The concentrations of PM2.5, particulate matter with aerodynamic diameter of 10 μm or less (PM10), sulfur dioxide (SO2), and nitrogen dioxide (NO2) are overpredicted partially due to the lack of wet scavenging by the chemistry-aerosol option with the 1999 version of the Statewide Air Pollution Research Center (SAPRC-99) mechanism with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) and the Volatility Basis Set (VBS) for secondary organic aerosol formation. The optimal set of configurations with the best performance is the simulation with the Gorddard shortwave and RRTM longwave radiation schemes, the Purdue Lin microphysics scheme, the Kain-Fritsch cumulus scheme, and a nudging coefficient of 1 × 10-5 for water vapor mixing ratio. The emission sensitivity simulations show that the PM2.5 concentrations are most sensitive to nitrogen oxide (NOx) and SO2 emissions in northern China, but to NOx and ammonia (NH3) emissions in southern China. 30% NOx emission reductions may result in an increase in PM2.5 concentrations in northern China because of the NH3-rich and volatile organic compound (VOC) limited conditions over this area. VOC emission reductions will lead to a decrease in PM2.5 concentrations in eastern China

  7. Weather and forecasting at Wilkins ice runway, Antarctica

    International Nuclear Information System (INIS)

    Carpentier, Scott

    2010-01-01

    Aviation forecasts for Wilkins ice runway in East Antarctica are developed within the conceptual framework of flow against a single dome shaped hill. Forecast challenges include the sudden onset of blizzards associated with the formation of an internal gravity wave; frontal weather; transient wake vortices and mesoscale lows; temperature limitations on runway use; and snow and fog events. These key weather aspects are presented within the context of synoptic to local scale climatologies and numerical weather prediction models.

  8. 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

  9. Evaluation of high-resolution forecasts with the non-hydrostaticnumerical weather prediction model Lokalmodell for urban air pollutionepisodes in Helsinki, Oslo and Valencia

    Directory of Open Access Journals (Sweden)

    B. Fay

    2006-01-01

    Full Text Available The operational numerical weather prediction model Lokalmodell LM with 7,km horizontal resolution was evaluated for forecasting meteorological conditions during observed urban air pollution episodes. The resolution was increased to experimental 2.8 km and 1.1 km resolution by one-way interactive nesting without introducing urbanisation of physiographic parameters or parameterisations. The episodes examined are two severe winter inversion-induced episodes in Helsinki in December 1995 and Oslo in January 2003, three suspended dust episodes in spring and autumn in Helsinki and Oslo, and a late-summer photochemical episode in the Valencia area. The evaluation was basically performed against observations and radiosoundings and focused on the LM skill at forecasting the key meteorological parameters characteristic for the specific episodes. These included temperature inversions, atmospheric stability and low wind speeds for the Scandinavian episodes and the development of mesoscale recirculations in the Valencia area. LM forecasts often improved due to higher model resolution especially in mountainous areas like Oslo and Valencia where features depending on topography like temperature, wind fields and mesoscale valley circulations were better described. At coastal stations especially in Helsinki, forecast gains were due to the improved physiographic parameters (land fraction, soil type, or roughness length. The Helsinki and Oslo winter inversions with extreme nocturnal inversion strengths of 18°C were not sufficiently predicted with all LM resolutions. In Helsinki, overprediction of surface temperatures and low-level wind speeds basically led to underpredicted inversion strength. In the Oslo episode, the situation was more complex involving erroneous temperature advection and mountain-induced effects for the higher resolutions. Possible explanations include the influence of the LM treatment of snow cover, sea ice and stability-dependence of transfer

  10. Central American Flying Weather

    Science.gov (United States)

    1985-12-01

    CEILING; VISIBILITY; WIND, PRECIPITATIDNc’--." HAZE, SMOKE, TEMPORALE ; MOUNTAIN WAVE; MILITARY METEOROLOGY. 4k- / ’A. bstract; Asummary of~ing weather...1 The " Temporale " ....................................1 Mountain Waves ......................I...............1 Severe Thunderstorms...charts. The for any part of Central America lies in having: Tactical Pilota.e Chart series , produced by the Df -.nse Mapping Agency, is * A good, basic

  11. World Weather Extremes. Revision,

    Science.gov (United States)

    1985-12-01

    Ext r-,ncs, Weekl Weather and Crop Bull, Vol. 43, No. 9, pp. 6-8, 27 Feb 56. 21A. ntoli, La Piu Alta Temperatura del Mondo," [The HiLhest Temperi... Temperatura in Libia", Boll Soc Geogr Ita’iana, ser. 8, Vol. 7, pp. 59-71, 1954. 23J. Gentilli, "Libyan Climate", Geograph Rev, V0 l. 45, No. 2, p. 269 S" Apr

  12. 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.

  13. 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.

  14. 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

  15. 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. ...

  16. 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.

  17. 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.

  18. Weather radar rainfall data in urban hydrology

    NARCIS (Netherlands)

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick; Ellerbæk Nielsen, Jesper; ten Veldhuis, J.A.E.; Arnbjerg-Nielsen, Karsten; Rasmussen, Michael R.; Molnar, Peter

    2017-01-01

    Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology

  19. Swarm Products and Space Weather Applications

    DEFF Research Database (Denmark)

    Stolle, Claudia; Olsen, Nils; Martini, Daniel

    The Swarm satellite constellation mission provides high precision magnetic field data and models and other observations that enable us to explore near Earth space for example in terms of in situ electron density and electric fields. On board GPS observables can be used for sounding ionospheric...... in aeronomy and space weather. We will emphasize results from the Swarm mission....

  20. Weather or Not To Teach Junior High Meteorology.

    Science.gov (United States)

    Knorr, Thomas P.

    1984-01-01

    Presents a technique for teaching meteorology allowing students to observe and analyze consecutive weather maps and relate local conditions; a model illustrating the three-dimensional nature of the atmosphere is employed. Instructional methods based on studies of daily weather maps to trace systems sweeping across the United States are discussed.…

  1. Weather shocks and cropland decisions in rural Mozambique

    DEFF Research Database (Denmark)

    Salazar Espinoza, César Antonio; Jones, Edward Samuel; Tarp, Finn

    2015-01-01

    to examine the effect of weather shocks on cropland decisions. We account for the bounded nature of land shares and estimate a Pooled Fractional Probit model for panel data. Our results show that crop choice is sensitive to past weather shocks. Farmers shift land use away from cash and permanent crops one...

  2. The Weather in Richmond

    OpenAIRE

    Harless, William Edwin

    2014-01-01

    ABSTRACT: The Weather in Richmond is a short documentary about the Oilers, the football team at Richmond High School in downtown Richmond, California, as they struggle in 2012 with the legacy of winning no games, with the exception of a forfeit, in two years. The video documents the city of Richmond’s poverty and violence, but it also is an account of the city’s cultural diversity, of the city’s industrial history and of the hopes of some of the people who grow up there. The...