WorldWideScience

Sample records for model meam weatherization

  1. Weather Prediction Models

    Science.gov (United States)

    Bacmeister, Julio T.

    Awareness of weather and concern about weather in the proximate future certainly must have accompanied the emergence of human self-consciousness. Although weather is a basic idea in human existence, it is difficult to define precisely.

  2. Operational, regional-scale, chemical weather forecasting models in Europe

    NARCIS (Netherlands)

    Kukkonen, J.; Balk, 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.; Karatzas, K.; San José, R.; Astitha, M.; Kallos, G.; Schaap, M.; Reimer, E.; Jakobs, H.; Eben, K.

    2011-01-01

    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

  3. 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...

  4. 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.

  5. MEAM Simulation of Distribution of Nb Atoms in TiAl+Nb System

    Institute of Scientific and Technical Information of China (English)

    Xiaodong NI; Guoliang CHEN; Xitao WANG; Xudong HUI

    2001-01-01

    An accurate MEAM (modified embedded atom method) potential including angular dependence for TiAl compound has been developed. The properties of TiAl compound can be reproduced well. With this potential, the distribution of Nb atoms in L10 type TiAl compound with various composition are calculated by using an average-atom model similar to B-W (Bragg-Williams)method. The results of calculation showed that Nb atoms prefer to occupy the Ti sublattice of L10 structure, and with increasing atomic percent of Nb and Al, Nb atoms exhibited a trend of ordered distribution in Ti sublattice, and result in the formation of L10 derivative superlattice structure.

  6. 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.; Stout, Quentin F.; Glocer, Alex; Ma, Ying-Juan; Opher, Merav

    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

  7. Weather forecasting based on hybrid neural model

    Science.gov (United States)

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

    2017-02-01

    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.

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. Decision Making Models Using Weather Forecast Information

    OpenAIRE

    Hiramatsu, Akio; Huynh, Van-Nam; Nakamori, Yoshiteru

    2007-01-01

    The quality of weather forecast has gradually improved, but weather information such as precipitation forecast is still uncertainty. Meteorologists have studied the use and economic value of weather information, and users have to translate weather information into their most desirable action. To maximize the economic value of users, the decision maker should select the optimum course of action for his company or project, based on an appropriate decision strategy under uncertain situations. In...

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

    DEFF Research Database (Denmark)

    Andersen, Ove; Torp, Kristian

    2017-01-01

    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...

  14. Objective calibration of numerical weather prediction models

    Science.gov (United States)

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

    2017-07-01

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

  15. 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...

  16. Characterizing and modelling 'ghost-rock' weathered limestones

    Science.gov (United States)

    Dubois, Caroline; Goderniaux, Pascal; Deceuster, John; Poulain, Angélique; Kaufmann, Olivier

    2016-04-01

    'Ghost-rock' karst aquifer has recently been highlighted. In this particular type of aquifer, the karst is not expressed as open conduits but consists in zones where the limestone is weathered. The in-situ weathering of limestone leaves a soft porous material called 'alterite'. The hydro-mechanical properties of this material differs significantly from those of the host rock: the weathering enhances the storage capacity and the conductivity of the rock. This type of weathered karst aquifer has never been studied from a hydrogeological point of view. In this study, we present the hydraulic characterization of such weathered zones. We also present a modelling approach derived from the common Equivalent Porous Medium (EPM) approach, but including the spatial distribution of hydrogeological properties through the weathered features, from the hard rock to the alterite, according to a weathering index. Unlike the Discrete Fracture Network (DFN) approaches, which enable to take into account a limited number of fractures, this new approach allows creating models including thousands of weathered features. As the properties of the alterite have to be considered at a centimeter scale, it is necessary to upscale these properties to carry out simulations over large areas. Therefore, an upscaling method was developed, taking into account the anisotropy of the weathered features. Synthetic models are built, upscaled and different hydrogeological simulations are run to validate the method. This methodology is finally tested on a real case study: the modelling of the dewatering drainage flow of an exploited quarry in a weathered karst aquifer in Belgium.

  17. Origin of unrealistic blunting during atomistic fracture simulations based on MEAM potentials

    Science.gov (United States)

    Ko, Won-Seok; Lee, Byeong-Joo

    2014-06-01

    Atomistic simulations based on interatomic potentials have frequently failed to correctly reproduce the brittle fracture of materials, showing an unrealistic blunting. We analyse the origin of the unrealistic blunting during atomistic simulations by modified embedded-atom method (MEAM) potentials for experimentally well-known brittle materials such as bcc tungsten and diamond silicon. The radial cut-off which has been thought to give no influence on MEAM calculations is found to have a decisive effect on the crack propagation behaviour. Extending both cut-off distance and truncation range can prevent the unrealistic blunting, reproducing many well-known fracture behaviour which have been difficult to reproduce. The result provides a guideline for future atomistic simulations that focus on various fracture-related phenomena including the failure of metallic-covalent bonding material systems using MEAM potentials.

  18. Interatomic Potential for Hydrocarbons on the Basis of the Modified Embedded-Atom Method with Bond Order (MEAM-BO).

    Science.gov (United States)

    Mun, Sungkwang; Bowman, Andrew L; Nouranian, Sasan; Gwaltney, Steven R; Baskes, Michael I; Horstemeyer, Mark F

    2017-02-23

    In this paper, we develop a new modified embedded atom method (MEAM) potential that includes the bond order (MEAM-BO) to describe the energetics of unsaturated hydrocarbons (double and triple carbon bonds) and also develop improved parameters for saturated hydrocarbons from those of our previous work. Such quantities like bond lengths, bond angles, and atomization energies at 0 K, dimer molecule interactions, rotational barriers, and the pressure-volume-temperature relationships of dense systems of small molecules give a comparable or more accurate property relative to experimental and first-principles data than the classical reactive force fields REBO and ReaxFF. Our extension of the MEAM potential for unsaturated hydrocarbons (MEAM-BO) is a step toward developing more reliable and accurate polymer simulations with their associated structure-property relationships, such as reactive multicomponent (organic/metal) systems, polymer-metal interfaces, and nanocomposites. When the constants for the BO are zero, MEAM-BO reduces to the original MEAM potential. As such, this MEAM-BO potential describing the interaction of organic materials with metals within the same MEAM formalism is a significant advancement for computational materials science.

  19. 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...

  20. 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...

  1. Divacancy binding energy, formation energy and surface energy of BCC transition metals using MEAM potentials

    Science.gov (United States)

    Uniyal, Shweta; Chand, Manesh; Joshi, Subodh; Semalty, P. D.

    2016-05-01

    The modified embedded atom method (MEAM) potential parameters have been employed to calculate the unrelaxed divacancy formation energy, binding energy and surface energies for low index planes in bcc transition metals. The calculated results of divacancy binding energy and vacancy formation energy compare well with experimental and other available calculated results.

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

    NARCIS (Netherlands)

    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, K.

    2012-01-01

    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

  3. Modeling the role of weathering in shore platform development

    Science.gov (United States)

    Trenhaile, Alan S.

    2008-02-01

    A mathematical, wave-erosional model was modified to study the additional effect of weathering by wetting and drying and salt weathering on the development of shore platforms in macro- to mesotidal environments. Model rates of downwearing by these processes, at different tidal elevations, were based on data obtained from a series of laboratory experiments on sandstones from eastern Canada. Backwearing by mechanical wave erosion was calculated using basic wave equations. There were several types of run which were designed to determine the effect of: weathering and the production of fine-grained sediment; the periodic accumulation of debris on weathering in the upper intertidal zone; and weathering in reducing rock resistance and facilitating wave quarrying. The results implied that, compared to mechanical wave erosion, the direct effect of weathering and fine-grained sediment production makes only a small contribution to the long-term development of shore platforms. The relationship between cliff-foot debris occurrence and platform development and morphology was inconsistent because of the negative feedback relationship between erosion rates, surface gradients, and rates of wave attenuation. The model suggested that weathering can play an important, indirect role in assisting wave quarrying of joint blocks and other rock fragments.

  4. On the Influence of Weather Forecast Errors in Short-Term Load Forecasting Models

    OpenAIRE

    Fay, D; Ringwood, John; Condon, M.

    2004-01-01

    Weather information is an important factor in load forecasting models. This weather information usually takes the form of actual weather readings. However, online operation of load forecasting models requires the use of weather forecasts, with associated weather forecast errors. A technique is proposed to model weather forecast errors to reflect current accuracy. A load forecasting model is then proposed which combines the forecasts of several load forecasting models. This approach allows the...

  5. The Future of Planetary Climate Modeling and Weather Prediction

    Science.gov (United States)

    Del Genio, A. D.; Domagal-Goldman, S. D.; Kiang, N. Y.; Kopparapu, R. K.; Schmidt, G. A.; Sohl, L. E.

    2017-01-01

    Modeling of planetary climate and weather has followed the development of tools for studying Earth, with lags of a few years. Early Earth climate studies were performed with 1-dimensionalradiative-convective models, which were soon fol-lowed by similar models for the climates of Mars and Venus and eventually by similar models for exoplan-ets. 3-dimensional general circulation models (GCMs) became common in Earth science soon after and within several years were applied to the meteorology of Mars, but it was several decades before a GCM was used to simulate extrasolar planets. Recent trends in Earth weather and and climate modeling serve as a useful guide to how modeling of Solar System and exoplanet weather and climate will evolve in the coming decade.

  6. Integrated modelling of physical, chemical and biological weather

    DEFF Research Database (Denmark)

    Kurganskiy, Alexander

    Integrated modelling of physical, chemical and biological weather has been widely considered during the recent decades. Such modelling includes interactions of atmospheric physics and chemical/biological aerosol concentrations. Emitted aerosols are subject to atmospheric transport, dispersion...... and deposition, but in turn they impact the radiation as well as cloud and precipitation formation. The present study focuses on birch pollen modelling as well as on physical and chemical weather with emphasis on black carbon (BC) aerosol modelling. The Enviro-HIRLAM model has been used for the study...

  7. 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.

  8. 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.

  9. Aerosol Radiative Forcing and Weather Forecasts in the ECMWF Model

    Science.gov (United States)

    Bozzo, A.; Benedetti, A.; Rodwell, M. J.; Bechtold, P.; Remy, S.

    2015-12-01

    Aerosols play an important role in the energy balance of the Earth system via direct scattering and absorpiton of short-wave and long-wave radiation and indirect interaction with clouds. Diabatic heating or cooling by aerosols can also modify the vertical stability of the atmosphere and influence weather pattern with potential impact on the skill of global weather prediction models. The Copernicus Atmosphere Monitoring Service (CAMS) provides operational daily analysis and forecast of aerosol optical depth (AOD) for five aerosol species using a prognostic model which is part of the Integrated Forecasting System of the European Centre for Medium-Range Weather Forecasts (ECMWF-IFS). The aerosol component was developed during the research project Monitoring Atmospheric Composition and Climate (MACC). Aerosols can have a large impact on the weather forecasts in case of large aerosol concentrations as found during dust storms or strong pollution events. However, due to its computational burden, prognostic aerosols are not yet feasible in the ECMWF operational weather forecasts, and monthly-mean climatological fields are used instead. We revised the aerosol climatology used in the operational ECMWF IFS with one derived from the MACC reanalysis. We analyse the impact of changes in the aerosol radiative effect on the mean model climate and in medium-range weather forecasts, also in comparison with prognostic aerosol fields. The new climatology differs from the previous one by Tegen et al 1997, both in the spatial distribution of the total AOD and the optical properties of each aerosol species. The radiative impact of these changes affects the model mean bias at various spatial and temporal scales. On one hand we report small impacts on measures of large-scale forecast skill but on the other hand details of the regional distribution of aerosol concentration have a large local impact. This is the case for the northern Indian Ocean where the radiative impact of the mineral

  10. Ambient Weather Model Research and Development: Final Report.

    Energy Technology Data Exchange (ETDEWEB)

    Walker, Stel Nathan; Wade, John Edward

    1990-08-31

    Ratings for Bonneville Power Administration (BPA) transmission lines are based upon the IEEE Standard for Calculation of Bare Overhead Conductor Temperatures and Ampacity under Steady-State Conditions (1985). This steady-state model is very sensitive to the ambient weather conditions of temperature and wind speed. The model does not account for wind yaw, turbulence, or conductor roughness as proposed by Davis (1976) for a real time rating system. The objective of this research has been to determine (1) how conservative the present rating system is for typical ambient weather conditions, (2) develop a probability-based methodology, (3) compile available weather data into a compatible format, and (4) apply the rating methodology to a hypothetical line. The potential benefit from this research is to rate transmission lines statistically which will allow BPA to take advantage of any unknown thermal capacity. The present deterministic weather model is conservative overall and studies suggest a refined model will uncover additional unknown capacity. 14 refs., 40 figs., 7 tabs.

  11. 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

  12. Modeling the influence of organic acids on soil weathering

    Science.gov (United States)

    Lawrence, Corey; Harden, Jennifer; Maher, Kate

    2014-08-01

    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.

  13. 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.

  14. Space Weather: Measurements, Models and Predictions

    Science.gov (United States)

    2014-03-21

    and record high levels of cosmic ray flux. There were broad-ranging terrestrial responses to this inactivity of the Sun. BC was involved in the...techniques for converting from one coordinate system (e.g., the invariant coordinate system used for the model) to another (e.g., the latitude- radius

  15. Radiation Belt Environment Model: Application to Space Weather and Beyond

    Science.gov (United States)

    Fok, Mei-Ching H.

    2011-01-01

    Understanding the dynamics and variability of the radiation belts are of great scientific and space weather significance. A physics-based Radiation Belt Environment (RBE) model has been developed to simulate and predict the radiation particle intensities. The RBE model considers the influences from the solar wind, ring current and plasmasphere. It takes into account the particle drift in realistic, time-varying magnetic and electric field, and includes diffusive effects of wave-particle interactions with various wave modes in the magnetosphere. The RBE model has been used to perform event studies and real-time prediction of energetic electron fluxes. In this talk, we will describe the RBE model equation, inputs and capabilities. Recent advancement in space weather application and artificial radiation belt study will be discussed as well.

  16. Forecasts of time averages with a numerical weather prediction model

    Science.gov (United States)

    Roads, J. O.

    1986-01-01

    Forecasts of time averages of 1-10 days in duration by an operational numerical weather prediction model are documented for the global 500 mb height field in spectral space. Error growth in very idealized models is described in order to anticipate various features of these forecasts and in order to anticipate what the results might be if forecasts longer than 10 days were carried out by present day numerical weather prediction models. The data set for this study is described, and the equilibrium spectra and error spectra are documented; then, the total error is documented. It is shown how forecasts can immediately be improved by removing the systematic error, by using statistical filters, and by ignoring forecasts beyond about a week. Temporal variations in the error field are also documented.

  17. 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

  18. Modeling the weather with a data flow supercomputer

    Science.gov (United States)

    Dennis, J. B.; Gao, G.-R.; Todd, K. W.

    1984-01-01

    A static concept of data flow architecture is considered for a supercomputer for weather modeling. The machine level instructions are loaded into specific memory locations before computation is initiated, with only one instruction active at a time. The machine would have processing element, functional unit, array memory, memory routing and distribution routing network elements all contained on microprocessors. A value-oriented algorithmic language (VAL) would be employed and would have, as basic operations, simple functions deriving results from operand values. Details of the machine language format, computations with an array and file processing procedures are outlined. A global weather model is discussed in terms of a static architecture and the potential computation rate is analyzed. The results indicate that detailed design studies are warranted to quantify costs and parts fabrication requirements.

  19. A Modeler's Perspective on Space Weather Forecasting (Invited)

    Science.gov (United States)

    Wiltberger, M. J.

    2010-12-01

    Space physics is moving into a new era where numerical models originally developed for answering science questions are used as the basis for making operational space weather forecasts. Answering this challenge requires developments on multiple fronts requiring collaborations across space physics disciplines and between the research and operations communities. Since space weather in geospace is driven by the solar wind conditions a natural solution to improving the forecast lead time is to couple geospace models to heliospheric models. The quality of these forecast is dependent upon the ability of the heliospheric models to accurately model IMF Bz. Another challenge presented by moving into the forecasting arena is preparing the models for real-time operation which includes both computational performance and data redundancy issues. Moving into operations also presents modelers with an opportunity to assess their models performance over calculation intervals unprecedented duration. A key collaboration in the transition of models to operation is the discussion between forecasters and developers on what forecast parameters can accurately be predicted by the current generation of numerical models. This collaboration naturally includes a discussion of the definition of the best metrics to be used in quantitatively assessing performance.

  20. 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.

  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. 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.

  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. 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.

  5. Weather modeling and forecasting of PV systems operation

    CERN Document Server

    Paulescu, Marius; Gravila, Paul; Badescu, Viorel

    2012-01-01

    In the past decade, there has been a substantial increase of grid-feeding photovoltaic applications, thus raising the importance of solar electricity in the energy mix. This trend is expected to continue and may even increase. Apart from the high initial investment cost, the fluctuating nature of the solar resource raises particular insertion problems in electrical networks. Proper grid managing demands short- and long-time forecasting of solar power plant output. Weather modeling and forecasting of PV systems operation is focused on this issue. Models for predicting the state of the sky, nowc

  6. Identification of the MEAM1 cryptic species of Bemisia tabaci (Hemiptera: Aleyrodidae) by loop-mediated isothermal amplification

    Science.gov (United States)

    There are two major invasive cryptic species within the Bemisia tabaci cryptic species complex in Florida, called MEAM1 or biotype B, and MED or biotype Q. We used loop-mediated isothermal amplification of DNA to detect these groups. Primer sets developed in house and those previously published wer...

  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. 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,...

  10. 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)...

  11. Weather model verification using Sodankylä mast measurements

    Directory of Open Access Journals (Sweden)

    M. Kangas

    2015-12-01

    Full Text Available Sodankylä, in the heart of Arctic Research Centre of the Finnish Meteorological Institute (FMI ARC in northern Finland, is an ideal site for atmospheric and environmental research in the boreal and sub-arctic zone. With temperatures ranging from −50 to +30 °C, it provides a challenging testing ground for numerical weather forecasting (NWP models as well as weather forecasting in general. An extensive set of measurements has been carried out in Sodankylä for more than 100 years. In 2000, a 48 m high micrometeorological mast was erected in the area. In this article, the use of Sodankylä mast measurements in NWP model verification is described. Started in 2000 with NWP model HIRLAM and Sodankylä measurements, the verification system has now been expanded to include comparisons between 12 NWP models and seven measurement masts. A case study, comparing forecasted and observed radiation fluxes, is also presented. It was found that three different radiation schemes, applicable in NWP model HARMONIE-AROME, produced during cloudy days somewhat different downwelling long-wave radiation fluxes, which however did not change the overall cold bias of the predicted screen-level temperature.

  12. Space Weather Education: Learning to Forecast at the Community Coordinated Modeling Center

    Science.gov (United States)

    Wold, A.

    2015-12-01

    Enhancing space weather education is important to space science endeavors. While participating in the Space Weather Research, Education and Development Initiative (SW REDI) Bootcamp and working as a Space Weather Analyst Intern, several innovative technologies and tools were integral to my learning and understanding of space weather analysis and forecasting. Two of the tools utilized in learning about space weather were the Integrated Space Weather Analysis System (iSWA) and the Space Weather Database Of Notifications, Knowledge, Information (DONKI). iSWA, a web-based dissemination system, hosts many state-of-the-art space weather models as well as real time space weather data from spacecraft such as Solar Dynamics Observatory and the Advanced Composition Explorer. As a customizable tool that operates in real-time while providing access also to historical data, iSWA proved essential in my understanding the drivers and impacts of space weather. DONKI was instrumental in accessing historical space weather events to understand the connections between solar phenomena and their effects on Earth environments. DONKI operates as a database of space weather events including linkages between causes and effects of space weather events. iSWA and DONKI are tools available also to the public. They not only enrich the space weather learning process but also allow researchers and model developers access to essential heliophysics and magnetospheric data.

  13. Improving Weather Research and Forecasting Model Initial Conditions via Surface Pressure Analysis

    Science.gov (United States)

    2015-09-01

    Obsgrid) that creates input data for the Advanced Research version of the Weather Research and Forecasting model (WRF-ARW) is modified to perform a...Configuration  The Advanced Research version of the Weather Research and Forecasting model (WRF-ARW) V3.6.1 (Skamarock et al. 2008) is applied with 56 vertical...those with more benign weather. On 7 February a trough moved onshore and led to widespread precipitation in the region . More quiescent weather was in

  14. Stability of theoretical model for catastrophic weather prediction

    Institute of Scientific and Technical Information of China (English)

    SHI Wei-hui; WANG Yue-peng

    2007-01-01

    Stability related to theoretical model for catastrophic weather prediction,which includes non-hydrostatic perfect elastic model and anelastic model, is discussed and analyzed in detail. It is proved that non-hydrostatic perfect elastic equations set is stable in the class of infinitely differentiable function. However, for the anelastic equations set, its continuity equation is changed in form because of the particular hypothesis for fluid, so "the matching consisting of both viscosity coefficient and incompressible assumption" appears, thereby the most important equations set of this class in practical prediction shows the same instability in topological property as Navier-Stokes equation,which should be avoided first in practical numerical prediction. In light of this, the referenced suggestions to amend the applied model are finally presented.

  15. Space Weathering of Olivine: Samples, Experiments and Modeling

    Science.gov (United States)

    Keller, L. P.; Berger, E. L.; Christoffersen, R.

    2016-01-01

    Olivine is a major constituent of chondritic bodies and its response to space weathering processes likely dominates the optical properties of asteroid regoliths (e.g. S- and many C-type asteroids). Analyses of olivine in returned samples and laboratory experiments provide details and insights regarding the mechanisms and rates of space weathering. Analyses of olivine grains from lunar soils and asteroid Itokawa reveal that they display solar wind damaged rims that are typically not amorphized despite long surface exposure ages, which are inferred from solar flare track densities (up to 10 (sup 7 y)). The olivine damaged rim width rapidly approaches approximately 120 nm in approximately 10 (sup 6 y) and then reaches steady-state with longer exposure times. The damaged rims are nanocrystalline with high dislocation densities, but crystalline order exists up to the outermost exposed surface. Sparse nanophase Fe metal inclusions occur in the damaged rims and are believed to be produced during irradiation through preferential sputtering of oxygen from the rims. The observed space weathering effects in lunar and Itokawa olivine grains are difficult to reconcile with laboratory irradiation studies and our numerical models that indicate that olivine surfaces should readily blister and amorphize on relatively short time scales (less than 10 (sup 3 y)). These results suggest that it is not just the ion fluence alone, but other variable, the ion flux that controls the type and extent of irradiation damage that develops in olivine. This flux dependence argues for caution in extrapolating between high flux laboratory experiments and the natural case. Additional measurements, experiments, and modeling are required to resolve the discrepancies among the observations and calculations involving solar wind processing of olivine.

  16. Modeling Inclement Weather Impacts on Traffic Stream Behavior

    Directory of Open Access Journals (Sweden)

    Hesham Rakha, PhD., P.Eng.

    2012-03-01

    Full Text Available The research identifies the steady-state car-following model parameters within state-of-the-practice traffic simulation software that require calibration to reflect inclement weather and roadway conditions. The research then develops procedures for calibrating non-steady state car-following models to capture inclement weather impacts and applies the procedures to the INTEGRATION software on a sample network. The results demonstrate that the introduction of rain precipitation results in a 5% reduction in light-duty vehicle speeds and a 3% reduction in heavy-duty vehicle speeds. An increase in the rain intensity further reduces light-duty vehicle and heavy-duty truck speeds resulting in a maximum reduction of 9.5% and 5.5% at the maximum rain intensity of 1.5 cm/h, respectively. The results also demonstrate that the impact of rain on traffic stream speed increases with the level of congestion and is more significant than speed differences attributed to various traffic operational improvements and thus should be accounted for in the analysis of alternatives. In the case of snow precipitation, the speed reductions are much more significant (in the range of 55%. Furthermore, the speed reductions are minimally impacted by the snow precipitation intensity. The study further demonstrates that precipitation intensity has no impact on the relative merit of various scenarios (i.e. the ranking of the scenario results are consistent across the various rain intensity levels. This finding is important given that it demonstrates that a recommendation on the optimal scenario is not impacted by the weather conditions that are considered in the analysis.

  17. Operational Space Weather Models: Trials, Tribulations and Rewards

    Science.gov (United States)

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

    2009-12-01

    There are many empirical, physics-based, and data assimilation models that can probably be used for space weather applications and the models cover the entire domain from the surface of the Sun to the Earth’s surface. At Utah State University we developed two physics-based data assimilation models of the terrestrial ionosphere as part of a program called Global Assimilation of Ionospheric Measurements (GAIM). One of the data assimilation models is now in operational use at the Air Force Weather Agency (AFWA) in Omaha, Nebraska. This model is a Gauss-Markov Kalman Filter (GAIM-GM) model, and it uses a physics-based model of the ionosphere and a Kalman filter as a basis for assimilating a diverse set of real-time (or near real-time) measurements. The physics-based model is the Ionosphere Forecast Model (IFM), which is global and covers the E-region, F-region, and topside ionosphere from 90 to 1400 km. It takes account of five ion species (NO+, O2+, N2+, O+, H+), but the main output of the model is a 3-dimensional electron density distribution at user specified times. The second data assimilation model uses a physics-based Ionosphere-Plasmasphere Model (IPM) and an ensemble Kalman filter technique as a basis for assimilating a diverse set of real-time (or near real-time) measurements. This Full Physics model (GAIM-FP) is global, covers the altitude range from 90 to 30,000 km, includes six ions (NO+, O2+, N2+, O+, H+, He+), and calculates the self-consistent ionospheric drivers (electric fields and neutral winds). The GAIM-FP model is scheduled for delivery in 2012. Both of these GAIM models assimilate bottom-side Ne profiles from a variable number of ionosondes, slant TEC from a variable number of ground GPS/TEC stations, in situ Ne from four DMSP satellites, line-of-sight UV emissions measured by satellites, and occultation data. Quality control algorithms for all of the data types are provided as an integral part of the GAIM models and these models take account of

  18. Models and applications for space weather forecasting and analysis at the Community Coordinated Modeling Center.

    Science.gov (United States)

    Kuznetsova, Maria

    The Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) was established at the dawn of the new millennium as a long-term flexible solution to the problem of transition of progress in space environment modeling to operational space weather forecasting. CCMC hosts an expanding collection of state-of-the-art space weather models developed by the international space science community. Over the years the CCMC acquired the unique experience in preparing complex models and model chains for operational environment and developing and maintaining custom displays and powerful web-based systems and tools ready to be used by researchers, space weather service providers and decision makers. In support of space weather needs of NASA users CCMC is developing highly-tailored applications and services that target specific orbits or locations in space and partnering with NASA mission specialists on linking CCMC space environment modeling with impacts on biological and technological systems in space. Confidence assessment of model predictions is an essential element of space environment modeling. CCMC facilitates interaction between model owners and users in defining physical parameters and metrics formats relevant to specific applications and leads community efforts to quantify models ability to simulate and predict space environment events. Interactive on-line model validation systems developed at CCMC make validation a seamless part of model development circle. The talk will showcase innovative solutions for space weather research, validation, anomaly analysis and forecasting and review on-going community-wide model validation initiatives enabled by CCMC applications.

  19. Prediction model for spring dust weather frequency in North China

    Institute of Scientific and Technical Information of China (English)

    LANG XianMei

    2008-01-01

    It is of great social and scientific importance and also very difficult to make reliable prediction for dust weather frequency (DWF) in North China. In this paper, the correlation between spring DWF in Beijing and Tianjin observation stations, taken as examples in North China, and seasonally averaged surface air temperature, precipitation, Arctic Oscillation, Antarctic Oscillation, South Oscillation, near surface meridional wind and Eurasian westerly index is respectively calculated so as to construct a prediction model for spring DWF in North China by using these climatic factors. Two prediction models, I.e. Model-Ⅰ and model-Ⅱ, are then set up respectively based on observed climate data and the 32-year (1970--2001) extra-seasonal hindcast experiment data as reproduced by the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM). It is indicated that the correlation coefficient between the observed and predicted DWF reaches 0.933 in the model-Ⅰ, suggesting a high prediction skill one season ahead. The corresponding value is high up to 0.948 for the subsequent model-Ⅱ, which involves synchronous spring climate data reproduced by the IAP9L-AGCM relative to the model-Ⅰ. The model-Ⅱ can not only make more precise prediction but also can bring forward the lead time of real-time prediction from the model-Ⅰ's one season to half year. At last, the real-time predictability of the two models is evaluated. It follows that both the models display high prediction skill for both the interannual variation and linear trend of spring DWF in North China, and each is also featured by different advantages. As for the model-Ⅱ, the prediction skill is much higher than that of original approach by use of the IAP9L-AGCM alone. Therefore, the prediction idea put forward here should be popularized in other regions in China where dust weather occurs frequently.

  20. Prediction model for spring dust weather frequency in North China

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    It is of great social and scientific importance and also very difficult to make reliable prediction for dust weather frequency (DWF) in North China. In this paper, the correlation between spring DWF in Beijing and Tianjin observation stations, taken as examples in North China, and seasonally averaged surface air temperature, precipitation, Arctic Oscillation, Antarctic Oscillation, South Oscillation, near surface meridional wind and Eurasian westerly index is respectively calculated so as to construct a prediction model for spring DWF in North China by using these climatic factors. Two prediction models, i.e. model-I and model-II, are then set up respectively based on observed climate data and the 32-year (1970 -2001) extra-seasonal hindcast experiment data as reproduced by the nine-level Atmospheric General Circulation Model developed at the Institute of Atmospheric Physics (IAP9L-AGCM). It is indicated that the correlation coefficient between the observed and predicted DWF reaches 0.933 in the model-I, suggesting a high prediction skill one season ahead. The corresponding value is high up to 0.948 for the subsequent model-II, which involves synchronous spring climate data reproduced by the IAP9L-AGCM relative to the model-I. The model-II can not only make more precise prediction but also can bring forward the lead time of real-time prediction from the model-I’s one season to half year. At last, the real-time predictability of the two models is evaluated. It follows that both the models display high prediction skill for both the interannual variation and linear trend of spring DWF in North China, and each is also featured by different advantages. As for the model-II, the prediction skill is much higher than that of original approach by use of the IAP9L-AGCM alone. Therefore, the prediction idea put forward here should be popularized in other regions in China where dust weather occurs frequently.

  1. Weather Driven Renewable Energy Analysis, Modeling New Technologies

    Science.gov (United States)

    Paine, J.; Clack, C.; Picciano, P.; Terry, L.

    2015-12-01

    Carbon emission reduction is essential to hampering anthropogenic climate change. While there are several methods to broach carbon reductions, the National Energy with Weather System (NEWS) model focuses on limiting electrical generation emissions by way of a national high-voltage direct-current transmission that takes advantage of the strengths of different regions in terms of variable sources of energy. Specifically, we focus upon modeling concentrating solar power (CSP) as another source to contribute to the electric grid. Power tower solar fields are optimized taking into account high spatial and temporal resolution, 13km and hourly, numerical weather prediction model data gathered by NOAA from the years of 2006-2008. Importantly, the optimization of these CSP power plants takes into consideration factors that decrease the optical efficiency of the heliostats reflecting solar irradiance. For example, cosine efficiency, atmospheric attenuation, and shadowing are shown here; however, it should be noted that they are not the only limiting factors. While solar photovoltaic plants can be combined for similar efficiency to the power tower and currently at a lower cost, they do not have a cost-effective capability to provide electricity when there are interruptions in solar irradiance. Power towers rely on a heat transfer fluid, which can be used for thermal storage changing the cost efficiency of this energy source. Thermal storage increases the electric stability that many other renewable energy sources lack, and thus, the ability to choose between direct electric conversion and thermal storage is discussed. The figure shown is a test model of a CSP plant made up of heliostats. The colors show the optical efficiency of each heliostat at a single time of the day.

  2. Towards an improved modeling of chemical weathering in the SoilGen soil evolution model

    Science.gov (United States)

    Opolot, Emmanuel; Finke, Peter

    2014-05-01

    As the need for soil information particularly in the fields of agriculture, land evaluation, hydrology, biogeochemistry and climate change keeps increasing, models for soil evolution are increasingly becoming valuable tools to provide such soil information. Although still limited, such models are progressively being developed. The SoilGen model is one of such models with capabilities to provide soil information such as soil texture, pH, base saturation, organic carbon, CEC, etc over multi-millennia time scale. SoilGen is a mechanistic water flow driven pedogenetic model describing soil forming processes such as carbon cycling, clay migration, decalcification, bioturbation, physical weathering and chemical weathering. The model has been calibrated and confronted with field measurements in a number of case studies, giving plausible results. Discrepancies between measured and simulated soil properties as concluded from case studies have been mainly attributed to (i) the simple chemical weathering system (ii) poor estimates of initial data inputs such as bulk density and element fluxes, and (iii) incorrect values of variables that describe boundary conditions such as precipitation and potential evapotranspiration. This study focuses on extending the chemical weathering system, such that it can deal with a more heterogeneous composition of primary minerals and includes more elements such as Fe and Si. We propose and discuss here an extended description of chemical weathering in the model that is based on more primary minerals, taking into account the role of the specific area of these minerals, and the effect of physical weathering on these specific areas over time. In the initial stage, the proposed chemical weathering mechanism is also implemented in PHREEQC (a widely applied geochemical code with capabilities to simulate equilibrium reactions involving water and minerals, surface complexes and ion exchangers, etc.) to facilitate comparison with the model results

  3. 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.

  4. Using a Numerical Weather Model to Improve Geodesy

    CERN Document Server

    Niell, A

    2004-01-01

    The use of a Numerical Weather Model (NWM) to provide in situ atmosphere information for mapping functions of atmosphere delay has been evaluated using Very Long Baseline Interferometry (VLBI) data spanning eleven years. Parameters required by the IMF mapping functions (Niell 2000, 2001) have been calculated from the NWM of the National Centers for Environmental Prediction (NCEP) and incorporated in the CALC/SOLVE VLBI data analysis program. Compared with the use of the NMF mapping functions (Niell 1996) the application of IMF for global solutions demonstrates that the hydrostatic mapping function, IMFh, provides both significant improvement in baseline length repeatability and noticeable reduction in the amplitude of the residual harmonic site position variations at semidiurnal to long-period bands. For baseline length repeatability the reduction in the observed mean square deviations achieves 80 of the maximum that is expected for the change from NMF to IMF. On the other hand, the use of the wet mapping fun...

  5. Numerical weather prediction model tuning via ensemble prediction system

    Science.gov (United States)

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

    2011-12-01

    This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

  6. Mountain range specific analog weather forecast model for northwest Himalaya in India

    Indian Academy of Sciences (India)

    D Singh; A Ganju

    2008-10-01

    Mountain range specific analog weather forecast model is developed utilizing surface weather observations of reference stations in each mountain range in northwest Himalaya (NW-Himalaya).The model searches past similar cases from historical dataset of reference observatory in each mountain range based on current situation.The searched past similar cases of each mountain range are used to draw weather forecast for that mountain range in operational weather forecasting mode, three days in advance.The developed analog weather forecast model is tested with the independent dataset of more than 717 days (542 days for Pir Panjal range in HP)of the past 4 winters (2003 –2004 to 2006 –2007).Independent test results are reasonably good and suggest that there is some possibility of forecasting weather in operational weather forecasting mode employing analog method over different mountain ranges in NW-Himalaya.Significant difference in overall accuracy of the model is found for prediction of snow day and no-snow day over different mountain ranges, when weather is predicted under snow day and no-snow day weather forecast categories respectively.In the same mountain range,signi ficant difference is also found in overall accuracy of the model for prediction of snow day and no-snow day for different areas.This can be attributed to their geographical position and topographical differences.The analog weather forecast model performs better than persistence and climatological forecast for day-1 predictions for all the mountain ranges except Karakoram range in NW-Himalaya.The developed analog weather forecast model may help as a guidance tool for forecasting weather in operational weather forecasting mode in different mountain ranges in NW-Himalaya.

  7. 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

  8. Mixing height computation from a numerical weather prediction model

    Energy Technology Data Exchange (ETDEWEB)

    Jericevic, A. [Croatian Meteorological and Hydrological Service, Zagreb (Croatia); Grisogono, B. [Univ. of Zagreb, Zagreb (Croatia). Andrija Mohorovicic Geophysical Inst., Faculty of Science

    2004-07-01

    Dispersion models require hourly values of the mixing height, H, that indicates the existence of turbulent mixing. The aim of this study was to investigate a model ability and characteristics in the prediction of H. The ALADIN, limited area numerical weather prediction (NWP) model for short-range 48-hour forecasts was used. The bulk Richardson number (R{sub iB}) method was applied to determine the height of the atmospheric boundary layer at one grid point nearest to Zagreb, Croatia. This specific location was selected because there were available radio soundings and the verification of the model could be done. Critical value of bulk Richardson number R{sub iBc}=0.3 was used. The values of H, modelled and measured, for 219 days at 12 UTC are compared, and the correlation coefficient of 0.62 is obtained. This indicates that ALADIN can be used for the calculation of H in the convective boundary layer. For the stable boundary layer (SBL), the model underestimated H systematically. Results showed that R{sub iBc} evidently increases with the increase of stability. Decoupling from the surface in the very SBL was detected, which is a consequence of the flow ease resulting in R{sub iB} becoming very large. Verification of the practical usage of the R{sub iB} method for H calculations from NWP model was performed. The necessity for including other stability parameters (e.g., surface roughness length) was evidenced. Since ALADIN model is in operational use in many European countries, this study would help the others in pre-processing NWP data for input to dispersion models. (orig.)

  9. Effects of high-gossypol cotton on the development and reproduction of Bemisia tabaci (Hemiptera: Aleyrodidae) MEAM1 cryptic species.

    Science.gov (United States)

    Guo, Jian-Ying; Wu, Gang; Wan, Fang-Hao

    2013-06-01

    Use of plant secondary metabolic compounds is an important method for insect pest control. In this study, the survival, development, and reproduction of Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) MEAM1 cryptic species were compared over two consecutive generations on three cotton cultivars of different gossypol levels. Both cotton cultivar and generation significantly affected the fitness of the whitefly. In both generations, the immature development times on the low-gossypol cultivar ZMS13 were significantly longer than those on the high-gossypol cultivar M9101 or medium-gossypol cultivar HZ401. The female fecundity and rate of population increase of the whitefly ranked in the following order: ZMS13 > HZ401 > M9101. On each cultivar, the immature development time was shorter and the immature survival rate was higher in the second generation than those in the first generation. Rate of increase was also higher in the second generation. These results demonstrated that the fitness of B. tabaci MEAM1 cryptic species on the low-gossypol cotton cultivar ZMS13 was higher than that on the medium- or high-gossypol cultivar. The comparison of the life histories of B. tabaci MEAM1 cryptic species on different cotton varieties is important for the development of an integrated pest management program of the whitefly by using plant secondary metabolic compounds.

  10. 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.

  11. Tools and Products of Real-Time Modeling: Opportunities for Space Weather Forecasting

    Science.gov (United States)

    Hesse, Michael

    2009-01-01

    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 CCMC activity is to support Space Weather forecasting at national Space Weather Forecasting Centers. This second activity involves model evaluations, model transitions to operations, and the development of draft Space Weather forecasting tools. This presentation will focus on the last element. Specifically, we will discuss present capabilities, and the potential to derive further tools. These capabilities will be interpreted in the context of a broad-based, bootstrapping activity for modern Space Weather forecasting.

  12. Wildland fire probabilities estimated from weather model-deduced monthly mean fire danger indices

    Science.gov (United States)

    Haiganoush K. Preisler; Shyh-Chin Chen; Francis Fujioka; John W. Benoit; Anthony L. Westerling

    2008-01-01

    The National Fire Danger Rating System indices deduced from a regional simulation weather model were used to estimate probabilities and numbers of large fire events on monthly and 1-degree grid scales. The weather model simulations and forecasts are ongoing experimental products from the Experimental Climate Prediction Center at the Scripps Institution of Oceanography...

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

    Institute of Scientific and Technical Information of China (English)

    Zhenming Shi; Tao Jiang; Mingjing Jiang; Fang Liu; Ning Zhang

    2015-01-01

    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 para-metric simulations. In addition, weathering has a significant impact on both stressestrain relationship and failure pattern of rocks.

  14. Improved wet weather wastewater influent modelling at Viikinmäki WWTP by on-line weather radar information.

    Science.gov (United States)

    Heinonen, M; Jokelainen, M; Fred, T; Koistinen, J; Hohti, H

    2013-01-01

    Municipal wastewater treatment plant (WWTP) influent is typically dependent on diurnal variation of urban production of liquid waste, infiltration of stormwater runoff and groundwater infiltration. During wet weather conditions the infiltration phenomenon typically increases the risk of overflows in the sewer system as well as the risk of having to bypass the WWTP. Combined sewer infrastructure multiplies the role of rainwater runoff in the total influent. Due to climate change, rain intensity and magnitude is tending to rise as well, which can already be observed in the normal operation of WWTPs. Bypass control can be improved if the WWTP is prepared for the increase of influent, especially if there is some storage capacity prior to the treatment plant. One option for this bypass control is utilisation of on-line weather-radar-based forecast data of rainfall as an input for the on-line influent model. This paper reports the Viikinmäki WWTP wet weather influent modelling project results where gridded exceedance probabilities of hourly rainfall accumulations for the next 3 h from the Finnish Meteorological Institute are utilised as on-line input data for the influent model.

  15. Computational Analysis of Optical Neural Network Models to Weather Forecasting

    OpenAIRE

    A. C. Subhajini; V. Joseph Raj

    2010-01-01

    Neural networks have been in use in numerous meteorological applications including weather forecasting. They are found to be more powerful than any traditional expert system in the classification of meteorological patterns, in performing pattern classification tasks as they learn from examples without explicitly stating the rules and being non linear they solve complex problems more than linear techniques. A weather forecasting problem - rain fall estimation has been experimented using differ...

  16. Improving High-resolution Weather Forecasts using the Weather Research and Forecasting (WRF) Model with Upgraded Kain-Fritsch Cumulus Scheme

    Science.gov (United States)

    High-resolution weather forecasting is affected by many aspects, i.e. model initial conditions, subgrid-scale cumulus convection and cloud microphysics schemes. Recent 12km grid studies using the Weather Research and Forecasting (WRF) model have identified the importance of inco...

  17. Successes and Challenges Porting Weather and Climate Models to GPUs

    Science.gov (United States)

    Govett, M. W.; Middlecoff, J.; Henderson, T. B.; Rosinski, J.; Madden, P.

    2011-12-01

    NOAA ESRL has had significant success parallelizing and running the Non-Hydrostatic Icosahedral Model (NIM) dynamical core on GPUs. A key ingredient in the success was the development of our Fortran-to-CUDA compiler (called F2C-ACC) to convert the model code. Compiler directives, inserted by the user, define regions of code to be run on the GPU, identify where fine-grain parallelism can be exploited, and manage data transfers between CPU and GPU. In 2009, we demonstrated that our compiler, with limited analysis capabilities, was able to produce code that ran the NIM 25x faster on a single GPU than a similar generation CPU. As F2C-ACC matured, fewer hand-translations were required until the GPU parallelization of NIM became fully automatic. The usefulness of F2C-ACC as a language translation tool will diminish as commercial compilers from CAPS, PGI and Cray mature; however, porting codes to GPUs will continue to require significant user involvement due to limited tools to support parallelization. Code inspection and analysis is currently very challenging and requires heavy user involvement to parallelize, debug, and achieve respectable speedup on GPUs. Users must inspect their code to locate fine grain parallelism, determine performance bottlenecks, manage data transfers, identify data dependencies, place inter-GPU communications, and manage a myriad of other issues in porting CPU-based codes to GPU architectures. This talk will describe the F2C-ACC compiler, discuss code porting challenges, and describe further development of the analysis capabilities of F2C-ACC to improve GPU parallelization of Fortran-based, Numerical Weather Prediction codes.

  18. Wildfire, Ecosystems and Climate in Siberia: Developing Weather and Climate Data Sets for Use in Fire Weather and Bioclimatic Models

    Science.gov (United States)

    Westberg, D. J.; Soja, A. J.; Stackhouse, P. W.

    2007-12-01

    A primary driving force of land cover change in boreal regions is fire, and extreme fire seasons are influenced by local weather and ultimately climate. It is predicted that fire frequency, area burned, fire severity, fire season length, and severe fire seasons will increase under current climate change scenarios. Already, there is evidence of an increased number of extreme fire seasons in Siberia that correlate with current warming. Our overall goal is to explore the degree to which current and future climate variability has and will affect wildfire-induced land cover change and to highlight the significance of the interaction between the biosphere and the climate system. Developing reliable weather and climate data provides the backbone of this research, which is to examine the relationships between weather, extreme fire events, and fire-induced land cover change in the changing climate of Siberia. The primary focus in this presentation is the description of the assembled weather and climate data sets and the verification efforts, followed by an example where the data set is used in a fire prediction application. Ground- based weather observations from the National Climatic Data Center (NCDC) for the years 1983-2006, have been used to verify various modeled meteorological parameters from the NASA Goddard Earth Observing System version 4 (GEOS-4) data. Specifically, we have extracted "Summary of the Day" and "Integrated Surface Hourly (ISH)" weather data from the NCDC. The ISH data has been processed to obtain hourly observation times for all stations in Siberia, including Mongolia and parts of northern China. A subset of these stations have been selected for validation purposes if they meet a criteria of having at least 75% of the possible reporting observations per day and 75% of the possible days in each month. GEOS-4 data interpolated to a 1x1 degree grid have compared well with the NCDC station data, covering the burning season from April through September

  19. 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

  20. The importance of weather data in crop growth simulation models and assessment of climatic change effects

    NARCIS (Netherlands)

    Nonhebel, S.

    1993-01-01

    Yields of agricultural crops are largely determined by the weather conditions during the growing season. Weather data are therefore important input variables for crop growth simulation models. In practice, these data are accepted at their face value. This is not realistic. Like all measured

  1. Comparison of three weather generators for crop modeling: a case study for subtropical environments

    NARCIS (Netherlands)

    Hartkamp, A.D.; White, J.W.; Hoogenboom, G.

    2003-01-01

    The use and application of decision support systems (DDS) that consider variation in climate and soil conditions has expanded in recent years. Most of these DSS are based on crop simulation models that require daily weather data, so access to weather data, at single sites as well as large amount of

  2. 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.

  3. Ensemble superparameterization versus stochastic parameterization: A comparison of model uncertainty representation in tropical weather prediction

    Science.gov (United States)

    Subramanian, Aneesh C.; Palmer, Tim N.

    2017-06-01

    Stochastic schemes to represent model uncertainty in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system has helped improve its probabilistic forecast skill over the past decade by both improving its reliability and reducing the ensemble mean error. The largest uncertainties in the model arise from the model physics parameterizations. In the tropics, the parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate. Superparameterization is a promising alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model (CRM) embedded within a global climate model (GCM). In this paper, we compare the impact of initial random perturbations in embedded CRMs, within the ECMWF ensemble prediction system, with stochastically perturbed physical tendency (SPPT) scheme as a way to represent model uncertainty in medium-range tropical weather forecasts. We especially focus on forecasts of tropical convection and dynamics during MJO events in October-November 2011. These are well-studied events for MJO dynamics as they were also heavily observed during the DYNAMO field campaign. We show that a multiscale ensemble modeling approach helps improve forecasts of certain aspects of tropical convection during the MJO events, while it also tends to deteriorate certain large-scale dynamic fields with respect to stochastically perturbed physical tendencies approach that is used operationally at ECMWF.type="synopsis">type="main">Plain Language SummaryProbabilistic weather forecasts, especially for tropical weather, is still a significant challenge for global weather forecasting systems. Expressing uncertainty along with weather forecasts is important for informed decision making. Hence, we explore the use of a relatively new approach in using super-parameterization, where a cloud resolving model is embedded within a global

  4. Discussion Part 2: Metrics and Validation Needs for Space Weather Models and Services

    Science.gov (United States)

    Glover, Alexi; Onsager, Terrance; Kuznetsova, Maria; Bingham, Suzy

    2016-07-01

    We invite the space weather community to contribute to a discussion on the main themes of this PSW1 event, with the aim of identifying and prioritising key issues and formulating recommendations and guidelines for policy makers, stakeholders, and data and service providers. This event particularly encourages dialogue between modellers, application developers, service providers and users of space weather products and services in order to review the state of model and service validation activities, to build upon successes, to identify challenges, and to develop a strategy for continuous assessment of space weather predictive capabilities and tracing the improvement over time, as recommended in the COSPAR Space Weather Roadmap. We discuss space weather verification & validation needs for the current generation of activities under development and in planning globally, together with perspectives for modellers and scientific community to further participate in the space weather endeavour. All Assembly participants are welcome to participate in this PSW discussion session and all are invited to submit input for the discussion to the authors ahead of the Assembly. The discussion will take place in two parts at the start and end of the PSW1 event. It is intended that the outcome of these discussion sessions will be formulated as a panel position paper on metrics and validation needs for space weather models and services.

  5. Introduction and Discussion Part 1: Metrics and Validation Needs for Space Weather Models and Services.

    Science.gov (United States)

    Glover, Alexi; Onsager, Terrance; Kuznetsova, Maria; Bingham, Suzy

    2016-07-01

    We invite the space weather community to contribute to a discussion on the main themes of this PSW1 event, with the aim of identifying and prioritising key issues and formulating recommendations and guidelines for policy makers, stakeholders, and data and service providers. This event particularly encourages dialogue between modellers, application developers, service providers and users of space weather products and services in order to review the state of model and service validation activities, to build upon successes, to identify challenges, and to develop a strategy for continuous assessment of space weather predictive capabilities and tracing the improvement over time, as recommended in the COSPAR Space Weather Roadmap. We discuss space weather verification & validation needs for the current generation of activities under development and in planning globally, together with perspectives for modellers and scientific community to further participate in the space weather endeavour. All Assembly participants are welcome to participate in this PSW discussion session and all are invited to submit input for the discussion to the authors ahead of the Assembly. The discussion will take place in two parts at the start and end of the PSW1 event. It is intended that the outcome of these discussion sessions will be formulated as a panel position paper on metrics and validation needs for space weather models and services.

  6. 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. Besides

  7. Predictive models of poly(ethylene-terephthalate) film degradation under multi-factor accelerated weathering exposures

    National Research Council Canada - National Science Library

    Abdulkerim Gok; David K Ngendahimana; Cara L Fagerholm; Roger H French; Jiayang Sun; Laura S Bruckman

    2017-01-01

    Accelerated weathering exposures were performed on poly(ethylene-terephthalate) (PET) films. Longitudinal multi-level predictive models as a function of PET grades and exposure types were developed for the change in yellowness index...

  8. 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.

  9. Stochastic Parameterization: Towards a new view of Weather and Climate Models

    CERN Document Server

    Berner, Judith; Batte, Lauriane; De La Camara, Alvaro; Crommelin, Daan; Christensen, Hannah; Colangeli, Matteo; Dolaptchiev, Stamen; Franzke, Christian L E; Friederichs, Petra; Imkeller, Peter; Jarvinen, Heikki; Juricke, Stephan; Kitsios, Vassili; Lott, Franois; Lucarini, Valerio; Mahajan, Salil; Palmer, Timothy N; Penland, Cecile; Von Storch, Jin-Song; Sakradzija, Mirjana; Weniger, Michael; Weisheimer, Antje; Williams, Paul D; Yano, Jun-Ichi

    2015-01-01

    The last decade has seen the success of stochastic parameterizations in short-term, medium-range and seasonal ensembles: operational weather centers now routinely use stochastic parameterization schemes to better represent model inadequacy and improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides more skillful estimates of uncertainty, but is also extremely promising for reducing longstanding climate biases and relevant for determining the climate response to forcings such as e.g., an increase of CO2. This article highlights recent results from different research groups which show that the stochastic representation of unresolved processes in the atmosphere, oceans, land surface and cryosphere of comprehensive weather and climate models a) gives rise to more reliable probabilistic forecasts of weather and climate and b) reduces systematic model bias. We make a case that the use of mathematically ...

  10. Space Weather Data Dissemination Tools from the Community Coordinated Modeling Center

    Science.gov (United States)

    Donti, N.; Berrios, D.; Boblitt, J.; LaSota, J.; Maddox, M. M.; Mullinix, R.; Hesse, M.

    2011-12-01

    The Community Coordinated Modeling Center (CCMC) at NASA Goddard Space Flight Center has developed new space weather data dissemination products. These include a Java-based conversion software for space weather simulation data, an interactive and customizable timeline tool for time series data, and Android phone and tablet versions of the NASA Space Weather App for mobile devices. We highlight the new features of all the updated services, discuss the back-end capabilities required to realize these services, and talk about future services in development.

  11. Description of Mixed-Phase Clouds in Weather Forecast and Climate Models

    Science.gov (United States)

    2014-09-30

    1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Description of Mixed-Phase Clouds in Weather Forecast...TERM GOALS To develop improved parameterizations of so-called mixed-phase stratocumulus in numerical models of weather and climate, and of their...impact on the surface energy budget over the Arctic Ocean, their impact on the vertical structure of the lower troposphere and relationships to larger

  12. Applying Forecast Models from the Center for Integrated Space Weather Modeling

    Science.gov (United States)

    Gehmeyr, M.; Baker, D. N.; Millward, G.; Odstrcil, D.

    2007-12-01

    The Center for Integrated Space Weather Modeling (CISM) has developed three forecast models (FMs) for the Sun-Earth chain. They have been matured by various degrees toward the operational stage. The Sun-Earth FM suite comprises empirical and physical models: the Planetary Equivalent Amplitude (AP-FM), the Solar Wind (SW- FM), and the Geospace (GS-FM) models. We give a brief overview of these forecast models and touch briefly on the associated validation studies. We demonstrate the utility of the models: AP-FM supporting the operations of the AIM (Aeronomy of Ice in the Mesosphere) mission soon after launch; SW-FM providing assistance with the interpretation of the STEREO beacon data; and GS-FM combining model and observed data to characterize the aurora borealis. We will then discuss space weather tools in a more general sense, point out where the current capabilities and shortcomings are, and conclude with a look forward to what areas need improvement to facilitate better real-time forecasts.

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

    DEFF Research Database (Denmark)

    Zhang, Gui-Fen; Lövei, Gabor L; Hu, Man

    2014-01-01

    BACKGROUND: 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...

  14. Sensitivity of mineral dissolution rates to physical weathering : A modeling approach

    Science.gov (United States)

    Opolot, Emmanuel; Finke, Peter

    2015-04-01

    There is continued interest on accurate estimation of natural weathering rates owing to their importance in soil formation, nutrient cycling, estimation of acidification in soils, rivers and lakes, and in understanding the role of silicate weathering in carbon sequestration. At the same time a challenge does exist to reconcile discrepancies between laboratory-determined weathering rates and natural weathering rates. Studies have consistently reported laboratory rates to be in orders of magnitude faster than the natural weathering rates (White, 2009). These discrepancies have mainly been attributed to (i) changes in fluid composition (ii) changes in primary mineral surfaces (reactive sites) and (iii) the formation of secondary phases; that could slow natural weathering rates. It is indeed difficult to measure the interactive effect of the intrinsic factors (e.g. mineral composition, surface area) and extrinsic factors (e.g. solution composition, climate, bioturbation) occurring at the natural setting, in the laboratory experiments. A modeling approach could be useful in this case. A number of geochemical models (e.g. PHREEQC, EQ3/EQ6) already exist and are capable of estimating mineral dissolution / precipitation rates as a function of time and mineral mass. However most of these approaches assume a constant surface area in a given volume of water (White, 2009). This assumption may become invalid especially at long time scales. One of the widely used weathering models is the PROFILE model (Sverdrup and Warfvinge, 1993). The PROFILE model takes into account the mineral composition, solution composition and surface area in determining dissolution / precipitation rates. However there is less coupling with other processes (e.g. physical weathering, clay migration, bioturbation) which could directly or indirectly influence dissolution / precipitation rates. We propose in this study a coupling between chemical weathering mechanism (defined as a function of reactive area

  15. An integrated user-oriented weather forecast system for air traffic using real-time observations and model data

    OpenAIRE

    Forster, Caroline; Tafferner, Arnold

    2009-01-01

    This paper presents the Weather Forecast User-oriented System Including Object Nowcasting (WxFUSION), an integrated weather forecast system for air traffic. The system is currently under development within a new project named “Weather and Flying” under the leadership of the Institute of Atmospheric Physics (IPA) at the German Aerospace Center (DLR). WxFUSION aims at combining data from various sources, as there are weather observations, remote sensing, nowcasting and numerical model forecast ...

  16. The weather@home regional climate modelling project for Australia and New Zealand

    Science.gov (United States)

    Black, Mitchell T.; Karoly, David J.; Rosier, Suzanne M.; Dean, Sam M.; King, Andrew D.; Massey, Neil R.; Sparrow, Sarah N.; Bowery, Andy; Wallom, David; Jones, Richard G.; Otto, Friederike E. L.; Allen, Myles R.

    2016-09-01

    A new climate modelling project has been developed for regional climate simulation and the attribution of weather and climate extremes over Australia and New Zealand. The project, known as weather@home Australia-New Zealand, uses public volunteers' home computers to run a moderate-resolution global atmospheric model with a nested regional model over the Australasian region. By harnessing the aggregated computing power of home computers, weather@home is able to generate an unprecedented number of simulations of possible weather under various climate scenarios. This combination of large ensemble sizes with high spatial resolution allows extreme events to be examined with well-constrained estimates of sampling uncertainty. This paper provides an overview of the weather@home Australia-New Zealand project, including initial evaluation of the regional model performance. The model is seen to be capable of resolving many climate features that are important for the Australian and New Zealand regions, including the influence of El Niño-Southern Oscillation on driving natural climate variability. To date, 75 model simulations of the historical climate have been successfully integrated over the period 1985-2014 in a time-slice manner. In addition, multi-thousand member ensembles have also been generated for the years 2013, 2014 and 2015 under climate scenarios with and without the effect of human influences. All data generated by the project are freely available to the broader research community.

  17. Modeled Forecasts of Dengue Fever in San Juan, Puerto Rico Using NASA Satellite Enhanced Weather Forecasts

    Science.gov (United States)

    Morin, C.; Quattrochi, D. A.; Zavodsky, B.; Case, J.

    2015-12-01

    Dengue fever (DF) is an important mosquito transmitted disease that is strongly influenced by meteorological and environmental conditions. Recent research has focused on forecasting DF case numbers based on meteorological data. However, these forecasting tools have generally relied on empirical models that require long DF time series to train. Additionally, their accuracy has been tested retrospectively, using past meteorological data. Consequently, the operational utility of the forecasts are still in question because the error associated with weather and climate forecasts are not reflected in the results. Using up-to-date weekly dengue case numbers for model parameterization and weather forecast data as meteorological input, we produced weekly forecasts of DF cases in San Juan, Puerto Rico. Each week, the past weeks' case counts were used to re-parameterize a process-based DF model driven with updated weather forecast data to generate forecasts of DF case numbers. Real-time weather forecast data was produced using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) system enhanced using additional high-resolution NASA satellite data. This methodology was conducted in a weekly iterative process with each DF forecast being evaluated using county-level DF cases reported by the Puerto Rico Department of Health. The one week DF forecasts were accurate especially considering the two sources of model error. First, weather forecasts were sometimes inaccurate and generally produced lower than observed temperatures. Second, the DF model was often overly influenced by the previous weeks DF case numbers, though this phenomenon could be lessened by increasing the number of simulations included in the forecast. Although these results are promising, we would like to develop a methodology to produce longer range forecasts so that public health workers can better prepare for dengue epidemics.

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

    Science.gov (United States)

    Smith, Hugh A; Nagle, Curtis A; MacVean, Charles A; McKenzie, Cindy L

    2016-10-20

    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.

  19. 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.

  20. An extreme value model for maximum wave heights based on weather types

    Science.gov (United States)

    Rueda, Ana; Camus, Paula; Méndez, Fernando J.; Tomás, Antonio; Luceño, Alberto

    2016-02-01

    Extreme wave heights are climate-related events. Therefore, special attention should be given to the large-scale weather patterns responsible for wave generation in order to properly understand wave climate variability. We propose a classification of weather patterns to statistically downscale daily significant wave height maxima to a local area of interest. The time-dependent statistical model obtained here is based on the convolution of the stationary extreme value model associated to each weather type. The interdaily dependence is treated by a climate-related extremal index. The model's ability to reproduce different time scales (daily, seasonal, and interannual) is presented by means of its application to three locations in the North Atlantic: Mayo (Ireland), La Palma Island, and Coruña (Spain).

  1. Implementation of the Immersed Boundary Method in the Weather Research and Forecasting model

    Energy Technology Data Exchange (ETDEWEB)

    Lundquist, Katherine Ann [Univ. of California, Berkeley, CA (United States)

    2006-01-01

    Accurate simulations of atmospheric boundary layer flow are vital for predicting dispersion of contaminant releases, particularly in densely populated urban regions where first responders must react within minutes and the consequences of forecast errors are potentially disastrous. Current mesoscale models do not account for urban effects, and conversely urban scale models do not account for mesoscale weather features or atmospheric physics. The ultimate goal of this research is to develop and implement an immersed boundary method (IBM) along with a surface roughness parameterization into the mesoscale Weather Research and Forecasting (WRF) model. IBM will be used in WRF to represent the complex boundary conditions imposed by urban landscapes, while still including forcing from regional weather patterns and atmospheric physics. This document details preliminary results of this research, including the details of three distinct implementations of the immersed boundary method. Results for the three methods are presented for the case of a rotation influenced neutral atmospheric boundary layer over flat terrain.

  2. Improving the Performance of Water Demand Forecasting Models by Using Weather Input

    NARCIS (Netherlands)

    Bakker, M.; Van Duist, H.; Van Schagen, K.; Vreeburg, J.; Rietveld, L.

    2014-01-01

    Literature shows that water demand forecasting models which use water demand as single input, are capable of generating a fairly accurate forecast. However, at changing weather conditions the forecasting errors are quite large. In this paper three different forecasting models are studied: an Adaptiv

  3. 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...

  4. The Effects of Use of Average Instead of Daily Weather Data in Crop Growth Simulation Models

    NARCIS (Netherlands)

    Nonhebel, Sanderine

    1994-01-01

    Development and use of crop growth simulation models has increased in the last decades. Most crop growth models require daily weather data as input values. These data are not easy to obtain and therefore in many studies daily data are generated, or average values are used as input data for these

  5. Coupling Advanced Modeling and Visualization to Improve High-Impact Tropical Weather Prediction

    Science.gov (United States)

    Shen, Bo-Wen; Tao, Wei-Kuo; Green, Bryan

    2009-01-01

    To meet the goals of extreme weather event warning, this approach couples a modeling and visualization system that integrates existing NASA technologies and improves the modeling system's parallel scalability to take advantage of petascale supercomputers. It also streamlines the data flow for fast processing and 3D visualizations, and develops visualization modules to fuse NASA satellite data.

  6. Improving the Performance of Water Demand Forecasting Models by Using Weather Input

    NARCIS (Netherlands)

    Bakker, M.; Van Duist, H.; Van Schagen, K.; Vreeburg, J.; Rietveld, L.

    2014-01-01

    Literature shows that water demand forecasting models which use water demand as single input, are capable of generating a fairly accurate forecast. However, at changing weather conditions the forecasting errors are quite large. In this paper three different forecasting models are studied: an Adaptiv

  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. 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.

  9. 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

  10. 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.

  11. Community Coordinated Modeling Center: Addressing Needs of Operational Space Weather Forecasting

    Science.gov (United States)

    Kuznetsova, M.; Maddox, M.; Pulkkinen, A.; Hesse, M.; Rastaetter, L.; Macneice, P.; Taktakishvili, A.; Berrios, D.; Chulaki, A.; Zheng, Y.; Mullinix, R.

    2012-01-01

    Models are key elements of space weather forecasting. The Community Coordinated Modeling Center (CCMC, http://ccmc.gsfc.nasa.gov) hosts a broad range of state-of-the-art space weather models and enables access to complex models through an unmatched automated web-based runs-on-request system. Model output comparisons with observational data carried out by a large number of CCMC users open an unprecedented mechanism for extensive model testing and broad community feedback on model performance. The CCMC also evaluates model's prediction ability as an unbiased broker and supports operational model selections. The CCMC is organizing and leading a series of community-wide projects aiming to evaluate the current state of space weather modeling, to address challenges of model-data comparisons, and to define metrics for various user s needs and requirements. Many of CCMC models are continuously running in real-time. Over the years the CCMC acquired the unique experience in developing and maintaining real-time systems. CCMC staff expertise and trusted relations with model owners enable to keep up to date with rapid advances in model development. The information gleaned from the real-time calculations is tailored to specific mission needs. Model forecasts combined with data streams from NASA and other missions are integrated into an innovative configurable data analysis and dissemination system (http://iswa.gsfc.nasa.gov) that is accessible world-wide. The talk will review the latest progress and discuss opportunities for addressing operational space weather needs in innovative and collaborative ways.

  12. Enhancing Hydrologic Modelling in the Coupled Weather Research and Forecasting-Urban Modelling System

    Science.gov (United States)

    Yang, Jiachuan; Wang, Zhi-Hua; Chen, Fei; Miao, Shiguang; Tewari, Mukul; Voogt, James A.; Myint, Soe

    2015-04-01

    Urbanization modifies surface energy and water budgets, and has significant impacts on local and regional hydroclimate. In recent decades, a number of urban canopy models have been developed and implemented into the Weather Research and Forecasting (WRF) model to capture urban land-surface processes. Most of these models are inadequate due to the lack of realistic representation of urban hydrological processes. Here, we implement physically-based parametrizations of urban hydrological processes into the single layer urban canopy model in the WRF model. The new single-layer urban canopy model features the integration of, (1) anthropogenic latent heat, (2) urban irrigation, (3) evaporation from paved surfaces, and (4) the urban oasis effect. The new WRF-urban modelling system is evaluated against field measurements for four different cities; results show that the model performance is substantially improved as compared to the current schemes, especially for latent heat flux. In particular, to evaluate the performance of green roofs as an urban heat island mitigation strategy, we integrate in the urban canopy model a multilayer green roof system, enabled by the physical urban hydrological schemes. Simulations show that green roofs are capable of reducing surface temperature and sensible heat flux as well as enhancing building energy efficiency.

  13. Testing the SWAT Model with Gridded Weather Data of Different Spatial Resolutions

    Directory of Open Access Journals (Sweden)

    Youen Grusson

    2017-01-01

    Full Text Available This study explored the influence of the spatial resolution of a gridded weather dataset when inputted in the soil and water assessment tool (SWAT over the Garonne River watershed. Several datasets are compared: ground-based weather stations, the 8-km SAFRAN product (Système d’Analyse Fournissant des Renseignements Adaptés à la Nivologie, the 0.5° CFSR product (Climate Forecasting System Reanalysis and several derived SAFRAN grids upscaled to 16, 32, 64 and 128 km. The SWAT model, calibrated on weather stations, was successively run with each gridded weather dataset. Performances with SAFRAN up to 64 or 128 km were poor, due to a contraction of the spatial variance of daily precipitation. Performances with 8-km SAFRAN are similar to that of the aggregated 16- and 32-km SAFRAN grids. The ~30-km CFSR product was found to perform well at some sites, while in others, its performance was considerably inferior because of grid points where precipitation was overestimated. The same problem was found in the calibration, where data at some weather stations did not appear to be representative of the subwatershed in which they are used to compute hydrology. These results suggest that the difference in the representation of the climate was more influential than its spatial resolution, an analysis that was confirmed by similar performances obtained with the SWAT model calibrated on the 16- and 32-km SAFRAN grids. However, the better performances obtained from these two weather datasets than from the ground-based stations’ dataset confirmed the advantage of using the SAFRAN product in SWAT modelling.

  14. An approach to secure weather and climate models against hardware faults

    Science.gov (United States)

    Düben, Peter; Dawson, Andrew

    2017-04-01

    Enabling Earth System models to run efficiently on future supercomputers is a serious challenge for model development. Many publications study efficient parallelisation to allow better scaling of performance on an increasing number of computing cores. However, one of the most alarming threats for weather and climate predictions on future high performance computing architectures is widely ignored: the presence of hardware faults that will frequently hit large applications as we approach exascale supercomputing. Changes in the structure of weather and climate models that would allow them to be resilient against hardware faults are hardly discussed in the model development community. We present an approach to secure the dynamical core of weather and climate models against hardware faults using a backup system that stores coarse resolution copies of prognostic variables. Frequent checks of the model fields on the backup grid allow the detection of severe hardware faults, and prognostic variables that are changed by hardware faults on the model grid can be restored from the backup grid to continue model simulations with no significant delay. To justify the approach, we perform simulations with a C-grid shallow water model in the presence of frequent hardware faults. As long as the backup system is used, simulations do not crash and a high level of model quality can be maintained. The overhead due to the backup system is reasonable and additional storage requirements are small. Runtime is increased by only 13% for the shallow water model.

  15. Modeling and projection of dengue fever cases in Guangzhou based on variation of weather factors.

    Science.gov (United States)

    Li, Chenlu; Wang, Xiaofeng; Wu, Xiaoxu; Liu, Jianing; Ji, Duoying; Du, Juan

    2017-12-15

    Dengue fever is one of the most serious vector-borne infectious diseases, especially in Guangzhou, China. Dengue viruses and their vectors Aedes albopictus are sensitive to climate change primarily in relation to weather factors. Previous research has mainly focused on identifying the relationship between climate factors and dengue cases, or developing dengue case models with some non-climate factors. However, there has been little research addressing the modeling and projection of dengue cases only from the perspective of climate change. This study considered this topic using long time series data (1998-2014). First, sensitive weather factors were identified through meta-analysis that included literature review screening, lagged analysis, and collinear analysis. Then, key factors that included monthly average temperature at a lag of two months, and monthly average relative humidity and monthly average precipitation at lags of three months were determined. Second, time series Poisson analysis was used with the generalized additive model approach to develop a dengue model based on key weather factors for January 1998 to December 2012. Data from January 2013 to July 2014 were used to validate that the model was reliable and reasonable. Finally, future weather data (January 2020 to December 2070) were input into the model to project the occurrence of dengue cases under different climate scenarios (RCP 2.6 and RCP 8.5). Longer time series analysis and scientifically selected weather variables were used to develop a dengue model to ensure reliability. The projections suggested that seasonal disease control (especially in summer and fall) and mitigation of greenhouse gas emissions could help reduce the incidence of dengue fever. The results of this study hope to provide a scientifically theoretical basis for the prevention and control of dengue fever in Guangzhou. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Stochastic Parameterization: Towards a new view of Weather and Climate Models

    NARCIS (Netherlands)

    Crommelin, D.T.; et al, not CWI

    2015-01-01

    The last decade has seen the success of stochastic parameterizations in short-term, medium-range and seasonal ensembles: operational weather centers now routinely use stochastic parameterization schemes to better represent model inadequacy and improve the quantification of forecast uncertainty. Dev

  17. Numerical modelling of the effect of weathering on the progressive failure of underground limestone mines

    CERN Document Server

    Ghabezloo, Siavash

    2008-01-01

    The observations show that the collapse of underground limestone mines results from a progressive failure due to gradual weathering of the rockmass. The following stages can be considered for the limestone weathering and degradation process in underground mines: condensation of the water on the roof of the gallery, infiltration of water in the porous rock, migration of the air CO2 molecules in the rock pore water by convection and molecular diffusion, dissolution of limestone by CO2 rich water and consequently, reduction of the strength properties of rock. Considering this process, a set of equations governing different hydrochemo-mechanical aspects of the weathering phenomenon and progressive failure occurring in these mines is presented. Then the feasibility of numerical modelling of this process is studied and a simple example of application is presented.

  18. Radar Scan Strategies for the Patrick Air Force Base Weather Surveillance Radar, Model-74C, Replacement

    Science.gov (United States)

    Short, David

    2008-01-01

    The 45th Weather Squadron (45 WS) is replacing the Weather Surveillance Radar, Model 74C (WSR-74C) at Patrick Air Force Base (PAFB), with a Doppler, dual polarization radar, the Radtec 43/250. A new scan strategy is needed for the Radtec 43/250, to provide high vertical resolution data over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) launch pads, while taking advantage of the new radar's advanced capabilities for detecting severe weather phenomena associated with convection within the 45 WS area of responsibility. The Applied Meteorology Unit (AMU) developed several scan strategies customized for the operational needs of the 45 WS. The AMU also developed a plan for evaluating the scan strategies in the period prior to operational acceptance, currently scheduled for November 2008.

  19. Weather modeling for hazard and consequence assessment operations during the 2006 Winter Olympic Games

    Science.gov (United States)

    Hayes, P.; Trigg, J. L.; Stauffer, D.; Hunter, G.; McQueen, J.

    2006-05-01

    Consequence assessment (CA) operations are those processes that attempt to mitigate negative impacts of incidents involving hazardous materials such as chemical, biological, radiological, nuclear, and high explosive (CBRNE) agents, facilities, weapons, or transportation. Incident types range from accidental spillage of chemicals at/en route to/from a manufacturing plant, to the deliberate use of radiological or chemical material as a weapon in a crowded city. The impacts of these incidents are highly variable, from little or no impact to catastrophic loss of life and property. Local and regional scale atmospheric conditions strongly influence atmospheric transport and dispersion processes in the boundary layer, and the extent and scope of the spread of dangerous materials in the lower levels of the atmosphere. Therefore, CA personnel charged with managing the consequences of CBRNE incidents must have detailed knowledge of current and future weather conditions to accurately model potential effects. A meteorology team was established at the U.S. Defense Threat Reduction Agency (DTRA) to provide weather support to CA personnel operating DTRA's CA tools, such as the Hazard Prediction and Assessment Capability (HPAC) tool. The meteorology team performs three main functions: 1) regular provision of meteorological data for use by personnel using HPAC, 2) determination of the best performing medium-range model forecast for the 12 - 48 hour timeframe and 3) provision of real-time help-desk support to users regarding acquisition and use of weather in HPAC CA applications. The normal meteorology team operations were expanded during a recent modeling project which took place during the 2006 Winter Olympic Games. The meteorology team took advantage of special weather observation datasets available in the domain of the Winter Olympic venues and undertook a project to improve weather modeling at high resolution. The varied and complex terrain provided a special challenge to the

  20. weather@home 2: validation of an improved global-regional climate modelling system

    Science.gov (United States)

    Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.

    2017-05-01

    Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.

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

    Science.gov (United States)

    2016-01-14

    distribution is unlimited. TOWARD SEAMLESS WEATHER- CLIMATE PREDICTION WITH A GLOBAL CLOUD RESOLVING MODEL PI: Tim Li IPRC/SOEST, University of Hawaii at...under global warming This study uses the MRI high-resolution Atmospheric Climate Model to determine whether environmental parameters that control...ENSO Amplitude under Global Warming in Four CMIP5 Models , J. Climate , 28 (8), 3250-3274. 6. Chung, P.-H., and T. Li, 2015: Characteristics of tropical

  2. Estimating Rice Yield under Changing Weather Conditions in Kenya Using CERES Rice Model

    OpenAIRE

    W. O. Nyang’au; Mati, B. M.; Kalamwa, K.; Wanjogu, R. K.; L. K. Kiplagat

    2014-01-01

    Effects of change in weather conditions on the yields of Basmati 370 and IR 2793-80-1 cultivated under System of Rice Intensification (SRI) in Mwea and Western Kenya irrigation schemes were assessed through sensitivity analysis using the Ceres rice model v 4.5 of the DSSAT modeling system. Genetic coefficients were determined using 2010 experimental data. The model was validated using rice growth and development data during the 2011 cropping season. Two SRI farmers were selected randomly from...

  3. Streamflow simulation by a watershed model using stochastically generated weather in New York City watersheds

    Science.gov (United States)

    Mukundan, R.; Acharya, N.; Gelda, R.; Owens, E. M.; Frei, A.; Schneiderman, E. M.

    2016-12-01

    Recent studies have reported increasing trends in total precipitation, and in the frequency and magnitude of extreme precipitation events in the West of Hudson (WOH) watersheds of the New York City (NYC) water supply. The potential effects of these changes may pose challenges for both water quality (such as increased sediment and nutrient loading) and quantity (such as reservoir storage and management). The NYC Dept. of Environmental Protection Climate Change Integrated Modeling Project (CCIMP) is using "bottom-up" or vulnerability based methods to explore climate impacts on water resources. Stochastic weather generators (SWGs) are an integral component of the bottom-up approach. Previous work has identified and evaluated the skill of alternative stochastic weather generators of varying complexity for simulating the statistical characteristics of observed minimum and maximum daily air temperature and occurrence and amount of precipitation. This evaluation focused on the skill in representing extreme streamflow event probabilities across NYC West of Hudson (WOH) watersheds. Synthetic weather time series from the selected (skewed normal) SWG were used to drive the Generalized Watershed Loading Function (GWLF) watershed model for a 600 year long period to simulate daily streamflows for WOH watersheds under a wide range of hydrologic conditions. Long-term average daily streamflows generated using the synthetic weather time series were comparable to values generated using observed long-term (1950-2009) weather time series. This study demonstrates the ability of the selected weather generator to adequately represent the hydrologic response in WOH watersheds with respect to the total, peak, and seasonality in streamflows. Future application of SWGs in NYC watersheds will include generating multiple scenarios of changing climate to evaluate water supply system vulnerability and selection of appropriate adaptation measures.

  4. SPARX: a modelling system for Solar Energetic Particle Radiation Space Weather forecasting

    CERN Document Server

    Marsh, M S; Dierckxsens, M; Laitinen, T; Crosby, N B

    2014-01-01

    The capability to predict the parameters of an SEP event such as its onset, peak flux, and duration is critical to assessing any potential space weather impact. We present a new operational modelling system simulating the propagation of Solar Energetic Particles (SEPs) from locations near the Sun to any given location in the heliosphere. The model is based on the test particle approach and is spatially 3D, thus allowing for the possibility of transport in the direction perpendicular to the magnetic field. The model naturally includes the effects of perpendicular propagation due to drifts and drift-induced deceleration. The modelling framework and the way in which parameters of relevance for Space Weather are obtained within a forecasting context are described. The first results from the modelling system are presented. These results demonstrate that corotation and drift of SEP streams play an essential role in shaping SEP flux profiles.

  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 quickly, such as during natural disasters, the status updates on Twitter are often more up-to-date than traditional news broadcasts. Research has shown that in Japan 96% of all earthquakes, which were stronger than 3 on the JMA (Japan Meteorological.... Both data sets had “ground truth” measurements for each day from the weather bureau. Although it is understood that the weather in Pretoria was in spring during the 60 days of the collection of this data, the algorithms would work with a larger...

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

    Science.gov (United States)

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

    1995-01-01

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

  7. The role of weathering in the formation of bedrock valleys on Earth and Mars: A numerical modeling investigation

    Science.gov (United States)

    Pelletier, Jon D.; Baker, Victor R.

    2011-11-01

    Numerical models of bedrock valley development generally do not include weathering explicitly. Nevertheless, weathering is an essential process that acts in concert with the transport of loose debris by seepage and runoff to form many bedrock valleys. Here we propose a numerical model for bedrock valley development that explicitly distinguishes weathering and the transport of loose debris and is capable of forming bedrock valleys similar to those observed in nature. In the model, weathering rates are assumed to increase with increasing water availability, a relationship that data suggest likely applies in many water-limited environments. We compare and contrast the model results for cases in which weathering is the result of runoff-induced infiltration versus cases in which it is the result of seepage- or subsurface-driven flow. The surface flow-driven version of our model represents an alternative to the stream-power model that explicitly shows how rates of both weathering and the transport of loose debris are related to topography or water flow. The subsurface flow-driven version of our model can be solved analytically using the linearized Boussinesq approximation. In such cases the model predicts theater-headed valleys that are parabolic in planform, a prediction broadly consistent with the observed shapes of theater-headed bedrock valleys on Mars that have been attributed to a combination of seepage weathering and episodic removal of weathered debris by runoff, seepage, and/or spring discharge.

  8. Integration of the Radiation Belt Environment Model Into the Space Weather Modeling Framework

    Science.gov (United States)

    Glocer, A.; Toth, G.; Fok, M.; Gombosi, T.; Liemohn, M.

    2009-01-01

    We have integrated the Fok radiation belt environment (RBE) model into the space weather modeling framework (SWMF). RBE is coupled to the global magnetohydrodynamics component (represented by the Block-Adaptive-Tree Solar-wind Roe-type Upwind Scheme, BATS-R-US, code) and the Ionosphere Electrodynamics component of the SWMF, following initial results using the Weimer empirical model for the ionospheric potential. The radiation belt (RB) model solves the convection-diffusion equation of the plasma in the energy range of 10 keV to a few MeV. In stand-alone mode RBE uses Tsyganenko's empirical models for the magnetic field, and Weimer's empirical model for the ionospheric potential. In the SWMF the BATS-R-US model provides the time dependent magnetic field by efficiently tracing the closed magnetic field-lines and passing the geometrical and field strength information to RBE at a regular cadence. The ionosphere electrodynamics component uses a two-dimensional vertical potential solver to provide new potential maps to the RBE model at regular intervals. We discuss the coupling algorithm and show some preliminary results with the coupled code. We run our newly coupled model for periods of steady solar wind conditions and compare our results to the RB model using an empirical magnetic field and potential model. We also simulate the RB for an active time period and find that there are substantial differences in the RB model results when changing either the magnetic field or the electric field, including the creation of an outer belt enhancement via rapid inward transport on the time scale of tens of minutes.

  9. Feeding on a begomovirus-infected plant enhances fecundity via increased expression of an insulin-like peptide in the whitefly, MEAM1.

    Science.gov (United States)

    Guo, Jian-Yang; Cheng, Lu; Ye, Gong-Yin; Fang, Qi; Guo, Jian-Yang

    2014-03-01

    The Middle East-Minor 1 cryptic species (MEAM1), Bemisia tabaci (Gennadius) is a globally invasive pest. It spreads widely due to its high fecundity and mutualistic interactions with the virus they vector. Feeding on virus (tomato yellow leaf curl China virus, TYLCCNV)-infected host plants improves their fecundity, however, the key factor regulating the signaling transduction in reproduction of whitefly remains to be identified. Here, we cloned a full length cDNA encoding an insulin-like peptide in MEAM1 (BtILP1) and investigated its expression profile, functions, and the expression induced by feeding on virus-infected tobacco plants. The full length cDNA of BtILP1 was 590 bps and encoded an open reading frame containing 149 amino acid residues. Multiple sequences alignment results showed BtILP1 contained the structural features typical of the insulin family. Expression dynamics associated with development showed the expression level of BtILP1 peaked at 5 days posteclosion (PE). During 1 to 3 days PE, BtILP1 was expressed highly in the head and abdomen of female adults and highly in the head during 5 to 7 days PE. Knockdown of the BtILP1 expression also impaired vitellogenin gene expression at both transcript and protein levels. Downregulating BtILP1 expression decreased fecundity of female adults and hatching rate of eggs. Feeding on virus-infected tobacco increased BtILP1 expression in MEAM1 female adults. We infer feeding on begomovirus-infected tobacco enhances the reproduction of MEAM1 by inducing BtILP1 expression. Our results give a new sight into the mutualistic interactions between virus and its insect vector.

  10. Strong Scaling for Numerical Weather Prediction at Petascale with the Atmospheric Model NUMA

    CERN Document Server

    Müller, Andreas; Marras, Simone; Wilcox, Lucas C; Isaac, Tobin; Giraldo, Francis X

    2015-01-01

    Numerical weather prediction (NWP) has proven to be computationally challenging due to its inherent multiscale nature. Currently, the highest resolution NWP models use a horizontal resolution of approximately 15km. At this resolution many important processes in the atmosphere are not resolved. Needless to say this introduces errors. In order to increase the resolution of NWP models highly scalable atmospheric models are needed. The Non-hydrostatic Unified Model of the Atmosphere (NUMA), developed by the authors at the Naval Postgraduate School, was designed to achieve this purpose. NUMA is used by the Naval Research Laboratory, Monterey as the engine inside its next generation weather prediction system NEPTUNE. NUMA solves the fully compressible Navier-Stokes equations by means of high-order Galerkin methods (both spectral element as well as discontinuous Galerkin methods can be used). Mesh generation is done using the p4est library. NUMA is capable of running middle and upper atmosphere simulations since it ...

  11. 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...... the uncertainty of the weather radar rainfall input. The main findings of this work, is that the input uncertainty propagate through the urban drainage model with significant effects on the model result. The GLUE methodology is in general a usable way to explore this uncertainty although; the exact width...... of the prediction bands can be questioned, due to the subjective nature of the method. Moreover, the method also gives very useful information about the model and parameter behaviour....

  12. 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

    2008-01-01

    NASA prefers to land the space shuttle at Kennedy Space Center (KSC). When weather conditions violate Flight Rules at KSC, NASA will usually divert the shuttle landing to Edwards Air Force Base (EAFB) in Southern California. But forecasting surface winds at EAFB is a challenge for the Spaceflight Meteorology Group (SMG) forecasters due to the complex terrain that surrounds EAFB, One particular phenomena identified by SMG is that makes it difficult to forecast the EAFB surface winds is called "wind cycling". This occurs when wind speeds and directions oscillate among towers near the EAFB runway leading to a challenging deorbit bum forecast for shuttle landings. The large-scale numerical weather prediction models cannot properly resolve the wind field due to their coarse horizontal resolutions, so a properly tuned high-resolution mesoscale model is needed. The Weather Research and Forecasting (WRF) model meets this requirement. The AMU assessed the different WRF model options to determine which configuration best predicted surface wind speed and direction at EAFB, To do so, the AMU compared the WRF model performance using two hot start initializations with the Advanced Research WRF and Non-hydrostatic Mesoscale Model dynamical cores and compared model performance while varying the physics options.

  13. 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.

  14. Computer Models Used by AFGWC and NMC for Weather Analysis and Forecasting

    Science.gov (United States)

    1992-08-01

    significant amount of reference material available for the computer models used by Air Force weather forecasters, there is no single reference to all... material in this north-south plane is much more difficult to chapter includes the First-Guess forecast describe without the mathematics, but one model...VA 22304-6146 ............ 2 WSO, H & HSB Maimn Station Wee, MCA Tot.in CA 92710-000 ....... AULAE . Mazwell APB, AL 36112-6164

  15. Flood Forecast and Early Warning with High-Resolution Ensemble Rainfall from Numerical Weather Prediction Model

    OpenAIRE

    Yu, Wansik; NAKAKITA, Eiichi; Jung, Kwansue

    2016-01-01

    This paper investigates the applicability of ensemble forecasts of numerical weather prediction (NWP) model for flood forecasting. In this study, 10 km resolution ensemble rainfalls forecast and their downscaled forecasts of 2 km resolution were used in the hydrologic model as input data for flood forecasting and application of flood early warning. Ensemble data consists of 51 members and 48 hr forecast time. Ensemble outputs are verified spatially whether they can produce suitable rainfall p...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. TS07D Empirical Geomagnetic Field Model as a Space Weather Tool

    Science.gov (United States)

    Sharp, N. M.; Stephens, G. K.; Sitnov, M. I.

    2011-12-01

    Empirical modeling and forecasting of the geomagnetic field is a key element of the space weather research. A dramatic increase in the number of data available for the terrestrial magnetosphere required a new generation of empirical models with large numbers of degrees of freedom and sophisticated data-mining techniques. A set of the corresponding data binning, fitting and visualization procedures known as the TS07D model is now available at \\url{http://geomag_field.jhuapl.edu/model/} and it is used for detailed investigation of storm-scale phenomena in the magnetosphere. However, the transformation of this research model into a practical space weather application, which implies its extensive running for validation and interaction with other space weather codes, requires its presentation in the form of a single state-of-the-art code, well documented and optimized for the highest performance. To this end, the model is implemented in the Java programming language with extensive self-sufficient library and a set of optimization tools, including multi-thread operations that assume the use of the code in multi-core computers and clusters. The results of the new code validation and optimization of its binning, fitting and visualization parts are presented as well as some examples of the processed storms are discussed.

  1. Towards downscaling precipitation for Senegal - An approach based on generalized linear models and weather types

    Science.gov (United States)

    Rust, H. W.; Vrac, M.; Lengaigne, M.; Sultan, B.

    2012-04-01

    Changes in precipitation patterns with potentially less precipitation and an increasing risk for droughts pose a threat to water resources and agricultural yields in Senegal. Precipitation in this region is dominated by the West-African Monsoon being active from May to October, a seasonal pattern with inter-annual to decadal variability in the 20th century which is likely to be affected by climate change. We built a generalized linear model for a full spatial description of rainfall in Senegal. The model uses season, location, and a discrete set of weather types as predictors and yields a spatially continuous description of precipitation occurrences and intensities. Weather types have been defined on NCEP/NCAR reanalysis using zonal and meridional winds, as well as relative humidity. This model is suitable for downscaling precipitation, particularly precipitation occurrences relevant for drough risk mapping.

  2. An Improved, Downscaled, Fine Model for Simulation of Daily Weather States

    Institute of Scientific and Technical Information of China (English)

    JIANG Zhihong; DING Yuguo; ZHENG Chunyu; CHEN Weilin

    2011-01-01

    In this study,changes in daily weather states were treated as a complex Markov chain process,based on a continuous-time watershed model (soil water assessment tool,SWAT) developed by the Agricultural Research Service at the U.S.Department of Agriculture (USDA-ARS).A finer classification using total cloud amount for dry states was adopted,and dry days were classified into three states:clear,cloudy,and overcast (rain free). Multistate transition models for dry- and wet-day series were constructed to comprehensively downscale the simulation of regional daily climatic states.The results show that the finer,improved,downscaled model overcame the oversimplified treatment of a two-weather state model and is free of the shortcomings of a multistate model that neglects finer classification of dry days (i.e.,finer classification was applied only to wet days).As a result,overall simulation of weather states based on the SWAT greatly improved,and the improvement in simulating daily temperature and radiation was especially significant.

  3. 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.

  4. Initial Analysis of and Predictive Model Development for Weather Reroute Advisory Use

    Science.gov (United States)

    Arneson, Heather M.

    2016-01-01

    In response to severe weather conditions, traffic management coordinators specify reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options would assist the traffic management coordinators in making more efficient rerouting decisions. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. Essentially, using previous information to inform future decisions. This paper describes the initial steps and methodology used towards this goal. A method to extract relevant features from the large volume of weather data to quantify the convective weather scenario during a particular time range is presented. Similar routes are clustered. A description of the algorithm to identify which cluster of reroute advisories were actually followed by pilots is described. Models built for fifteen of the top twenty most frequently used reroute clusters correctly predict the use of the cluster for over 60 of the test examples. Results are preliminary but indicate that the methodology is worth pursuing with modifications based on insight gained from this analysis.

  5. Implementation of a new aerosol HAM model within the Weather Research and Forecasting (WRF modeling system

    Directory of Open Access Journals (Sweden)

    R. Mashayekhi

    2009-07-01

    Full Text Available A new coupled system of aerosol HAM model and the Weather, Research and Forecasting (WRF model is presented in this paper. Unlike the current aerosol schemes used in WRF model, the HAM is using a "pseudomodal" approach for the representation of the particle size distribution. The aerosol components considered are sulfate, black carbon, particulate organic matter, sea salt and mineral dust. The preliminary model results are presented for two different 6-day simulation periods from 22 to 28 February 2006 as a winter period and 6 to 12 May 2006 as a mild period. The mean shortwave radiation and thermal forcing were calculated from the model simulations with and without aerosols feedback for two simulation periods. A negative radiative forcing and cooling of the atmosphere were found mainly over the regions of high emission of mineral dust. The absorption of shortwave radiation by black carbon caused warming effects in some regions with positive radiative forcing. The simulated daily mean sulfate mass concentration showed a rather good agreement with the measurements in the European EMEP network. The diurnal variation of the simulated hourly PM10 mass concentration at Tehran was also qualitatively close to the observations in both simulation periods. The model captured diurnal cycle and the magnitude of the observed PM10 concentration during most of the simulation periods. The differences between the observed and simulated PM10 concentration resulted mostly from limitation of the model in simulating the clouds and precipitation, transport errors and uncertainties in the particulate emission rates. The inclusion of aerosols feedback in shortwave radiation scheme improved the simulated daily mean shortwave radiation fluxes in Tehran for both simulation periods.

  6. Upscaling Fracture Network Models to Continua: An Example Using Weathered Granitic Rock

    Science.gov (United States)

    Clark, A.; Doe, T.; Jones, J. W.

    2006-12-01

    In the early 1990's, a proposed landfill site on the Campo Indian Reservation in San Diego County, California, was the object of a characterization program involving over ninety exploration and monitoring wells, geophysical investigations, flow meter logging, tracer testing, and fracture characterization. This intensively studied site rests on deeply weathered tonalite. The weathered zone extends several tens to about 100 feet below the surface; however, the deeply weathered material follows hydraulically active fractures to even greater depths. The flow meter logging was especially valuable both for locating conductive fractures but also, in un- pumped mode, for defining regions of upward and downward vertical flow. The deep weathering on the conductive fractures gives each pathway a large effective porosity that translates to lower flow velocities compared with unweathered fractures with similar transmissivities. The simulation of the groundwater flow at this site used a local-scale fracture network model which was upscaled to a continuum code at regional scales. At the largest scale we generated a small number of major fractures to match the topographic lineaments. At an intermediate scale we had geophysical lineaments that were deterministic under the site footprint, and stochastic elsewhere using generation parameters based on the lengths, orientations and intensities of the deterministic features. The fractures of the most detailed scale were background fractures that were stochastically generated from borehole data. The site-scale fracture network model was incorporated into a regional-scale MODFLOW model, by overlaying the MODFLOW grid on the fracture network model and calculating equivalent porous medium properties for each MODFLOW grid cell using the Oda tensor method. This fast algorithm calculates a permeability tensor for each MODFLOW grid cell by summing the oriented area-weighted permeabilities of each fracture. The resulting MODFLOW model was then

  7. Theories of multiple equilibria and weather regimes : A critical reexamination. II - Baroclinic two-layer models

    Science.gov (United States)

    Cehelsky, Priscilla; Tung, Ka Kit

    1987-01-01

    Previous results based on low- and intermediate-order truncations of the two-layer model suggest the existence of multiple equilibria and/or multiple weather regimes for the extratropical large-scale flow. The importance of the transient waves in the synoptic scales in organizing the large-scale flow and in the maintenance of weather regimes was emphasized. The result shows that multiple equilibria/weather regimes that are present in lower-order models examined disappear when a sufficient number of modes are kept in the spectral expansion of the solution to the governing partial differential equations. Much of the chaotic behavior of the large-scale flow that is present in intermediate-order models is now found to be spurious. Physical reasons for the drastic modification are offered. A peculiarity in the formulation of most existing two-layer models is noted that also tends to exaggerate the importance of baroclinic processes and increase the degree of unpredictability of the large-scale flow.

  8. A model for late Archean chemical weathering and world average river water

    Science.gov (United States)

    Hao, Jihua; Sverjensky, Dimitri A.; Hazen, Robert M.

    2017-01-01

    Interpretations of the geologic record of late Archean near-surface environments depend very strongly on an understanding of weathering and resultant riverine transport to the oceans. The late Archean atmosphere is widely recognized to be anoxic (pO2,g =10-5 to 10-13 bars; pH2,g =10-3 to 10-5 bars). Detrital siderite (FeCO3), pyrite (FeS2), and uraninite (UO2) in late Archean sedimentary rocks also suggest anoxic conditions. However, whether the observed detrital minerals could have been thermodynamically stable during weathering and riverine transport under such an atmosphere remains untested. Similarly, interpretations of fluctuations recorded by trace metals and isotopes are hampered by a lack of knowledge of the chemical linkages between the atmosphere, weathering, riverine transport, and the mineralogical record. In this study, we used theoretical reaction path models to simulate the chemistry involved in rainwater and weathering processes under present-day and hypothetical Archean atmospheric boundary conditions. We included new estimates of the thermodynamic properties of Fe(II)-smectites as well as smectite and calcite solid solutions. Simulation of present-day weathering of basalt + calcite by world-average rainwater produced hematite, kaolinite, Na-Mg-saponite, and chalcedony after 10-4 moles of reactant minerals kg-1 H2O were destroyed. Combination of the resultant water chemistry with results for granitic weathering produced a water composition comparable to present-day world average river water (WARW). In contrast, under late Archean atmospheric conditions (pCO2,g =10-1.5 and pH2,g =10-5.0 bars), weathering of olivine basalt + calcite to the same degree of reaction produced kaolinite, chalcedony, and Na-Fe(II)-rich-saponite. Late Archean weathering of tonalite-trondhjemite-granodiorite (TTG) formed Fe(II)-rich beidellite and chalcedony. Combining the waters from olivine basalt and TTG weathering resulted in a model for late Archean WARW with the

  9. 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.

  10. 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

    . For this purpose, the power system model has been developed that represents the relevant dynamic features of power plants and compensates for power imbalances caused by the forecasting error during critical weather conditions. The regulating power plan, as an input time series for the developed power system model......Secure power system operation of a highly wind power integrated power system is always at risk during critical weather conditions, e.g. in extreme high winds. The risk is even higher when 50% of the total electricity consumption has to be supplied by wind power, as the case for the future Danish...... power system in 2020. This paper analyses and compares the performance of the future Danish power system during extreme wind speeds, where wind power plants are either controlled through a traditional High Wind Shut Down storm controller or a new High Wind Extended Production storm controller...

  11. Blizzards to hurricanes: computer modeling of hydrology, weathering, and isotopic fractionation across hydroclimatic regions

    Science.gov (United States)

    Richard MT Webb; David L. Parkhurst

    2016-01-01

    The U.S. Geological Survey’s (USGS) Water, Energy, and Biogeochemical Model (WEBMOD) was used to simulate hydrology, weathering, and isotopic fractionation in the Andrews Creek watershed in Rocky Mountain National Park, Colorado and the Icacos River watershed in the Luquillo Experimental Forest, Puerto Rico. WEBMOD includes hydrologic modules derived from the USGS...

  12. Weathering Pathways and Limitations in Biogeochemical Models: Application to Earth System Evolution

    OpenAIRE

    Mills, Benjamin

    2012-01-01

    Current biogeochemical box models for Phanerozoic climate are reviewed and reduced to a robust, modular system, allowing application to the Precambrian. It is shown that stabilisation of climate following a Neoproterozoic snowball Earth should take more than 10(7) years, due to long-term geological limitation of global weathering rates. The timescale matches the observed gaps between extreme glaciations at this time, suggesting that the late Neoproterozoic system was oscillating around a s...

  13. 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.

  14. Estimating Rice Yield under Changing Weather Conditions in Kenya Using CERES Rice Model

    Directory of Open Access Journals (Sweden)

    W. O. Nyang’au

    2014-01-01

    Full Text Available Effects of change in weather conditions on the yields of Basmati 370 and IR 2793-80-1 cultivated under System of Rice Intensification (SRI in Mwea and Western Kenya irrigation schemes were assessed through sensitivity analysis using the Ceres rice model v 4.5 of the DSSAT modeling system. Genetic coefficients were determined using 2010 experimental data. The model was validated using rice growth and development data during the 2011 cropping season. Two SRI farmers were selected randomly from each irrigation scheme and their farms were used as research fields. Daily maximum and minimum temperatures and precipitation were collected from the weather station in each of the irrigation schemes while daily solar radiation was generated using weatherman in the DSSAT shell. The study revealed that increase in both maximum and minimum temperatures affects Basmati 370 and IR 2793-80-1 grain yield under SRI. Increase in atmospheric CO2 concentration led to an increase in grain yield for both Basmati and IR 2793-80-1 under SRI and increase in solar radiation also had an increasing impact on both Basmati 370 and IR 2793-80-1 grain yield. The results of the study therefore show that weather conditions in Kenya affect rice yield under SRI and should be taken into consideration to improve food security.

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

    CERN Document Server

    Willman, Mark; 10.1016/j.icarus.2010.02.017

    2010-01-01

    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 \\citep{bib.bot05a,bib.nes05} 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 \\citep[e.g.][]{bib.wil10,bib.jed04,bib.wil08,bib.mar06}. 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 $\\tau$' space weathering model of \\citet{bib.wil10}. We fit the size-age distribution to the enhanced dual $\\tau$ model and found characteristic w...

  16. NEURAL NETWORK BP MODEL APPROXIMATION AND PREDICTION OF COMPLICATED WEATHER SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    张韧; 余志豪; 蒋全荣

    2001-01-01

    An artificial neural network BP model and its revised algorithm are used to approximate quite successfully a Lorenz chaotic dynamic system and the mapping relation is established between the indices of Southern Oscillation and equatorial zonal wind and lagged equatorial eastern Pacific sea surface temperature (SST) in the context of NCEP/NCAR data, and thereby a model is prepared.The constructed net model shows fairly high fit precision and feasible prediction accuracy, thus making itself of some usefulness to the prognosis of intricate weather systems.

  17. The Joint Calibration Model in probabilistic weather forecasting: some preliminary issues

    Directory of Open Access Journals (Sweden)

    Patrizia Agati

    2013-05-01

    Full Text Available Ensemble Prediction Systems play today a fundamental role in weather forecasting. They can represent and measure uncertainty, thereby allowing distributional forecasting as well as deterministic-style forecasts. In this context, we show how the Joint Calibration Model (Agati et al., 2007 – based on a modelization of the Probability Integral Transform distribution – can provide a solution to the problem of information combining in probabilistic forecasting of continuous variables. A case study is presented, where the potentialities of the method are explored and the accuracy of deterministic-style forecasts from JCM is compared with that from Bayesian Model Averaging (Raftery et al., 2005.

  18. Chemical models for martian weathering profiles: Insights into formation of layered phyllosilicate and sulfate deposits

    Science.gov (United States)

    Zolotov, Mikhail Yu.; Mironenko, Mikhail V.

    2016-09-01

    Numerical chemical models for water-basalt interaction have been used to constrain the formation of stratified mineralogical sequences of Noachian clay-bearing rocks exposed in the Mawrth Vallis region and in other places on cratered martian highlands. The numerical approaches are based on calculations of water-rock type chemical equilibria and models which include rates of mineral dissolution. Results show that the observed clay-bearing sequences could have formed through downward percolation and neutralization of acidic H2SO4-HCl solutions. A formation of weathering profiles by slightly acidic fluids equilibrated with current atmospheric CO2 requires large volumes of water and is inconsistent with observations. Weathering by solutions equilibrated with putative dense CO2 atmospheres leads to consumption of CO2 to abundant carbonates which are not observed in clay stratigraphies. Weathering by H2SO4-HCl solutions leads to formation of amorphous silica, Al-rich clays, ferric oxides/oxyhydroxides, and minor titanium oxide and alunite at the top of weathering profiles. Mg-Fe phyllosilicates, Ca sulfates, zeolites, and minor carbonates precipitate from neutral and alkaline solutions at depth. Acidic weathering causes leaching of Na, Mg, and Ca from upper layers and accumulation of Mg-Na-Ca sulfate-chloride solutions at depth. Neutral MgSO4 type solutions dominate in middle parts of weathering profiles and could occur in deeper layers owing to incomplete alteration of Ca minerals and a limited trapping of Ca to sulfates. Although salts are not abundant in the Noachian geological formations, the results suggest the formation of Noachian salty solutions and their accumulation at depth. A partial freezing and migration of alteration solutions could have separated sulfate-rich compositions from low-temperature chloride brines and contributed to the observed diversity of salt deposits. A Hesperian remobilization and release of subsurface MgSO4 type solutions into newly

  19. 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

  20. Advanced corrections for InSAR using GPS and numerical weather models

    Science.gov (United States)

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

    2016-12-01

    The complex spatial and temporal changes in the atmospheric propagation delay of the radar signal remain the single biggest factor limiting Interferometric Synthetic Aperture Radar's (InSAR) 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 present preliminary results from an investigation into the application of GPS and numerical weather models for generating tropospheric correction fields. We use the Weather Research and Forecasting (WRF) model to generate a 900 m spatial resolution atmospheric model covering the Big Island of Hawaii and an even higher, 300 m resolution grid over 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 information on atmospheric heterogeneity from the GPS data into the 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. This work will produce best-practice recommendations for the use of weather models for InSAR correction, and inform efforts to design a global strategy for the NISAR mission, for both low-latency and definitive

  1. Latitude belt convection permitting simulation using the Weather Research and Forecasting (WRF) model

    Science.gov (United States)

    Warrach-Sagi, Kirsten; Schwitalla, Thomas; Wulfmeyer, Volker

    2015-04-01

    Extreme events like the heat wave in summer 2003 in Central Europe and in August 2010 in Russia (which was associated with floodings of the Odra an in Pakistan) and severe floodings in Germany were caused by persistent so-called omega and blocking Vb weather situations in Europe. They are caused when quasi-stationary, quasi-resonant enhanced and quasi-resonant Rossby waves develop in mid-latitudes. To simulate quasi-stationary Rossby waves in numerical weather prediction and climate models at least a resolution of 20 km is required, however, to simulate the associated extremes the simulations need to be convection permitting. Further the high resolution allows the small scale structures to feed back to the large scale systems. Most of the current limited area, high-resolution models apply a domain which is centered over the region of interest. Such limited area model applications may suffer from a deterioration of synoptic features like low pressure systems due to effects in the boundary relaxation zone when downscaling reanalysis or global model simulation data. For Europe this is mainly caused by the longitudinal boundaries. A way to overcome these types of difficulties is to run a latitude belt simulation model. We applied the Weather Research and Forecasting (WRF) model with 3 km horizontal resolution for July and August 2013 forcing the model 6-hourly with ECMWF analyses data at 20°N and 65°N and with daily sea surface temperature data from the OSTIA project of the UK Met Office at 6 km resolution. The model domain encompasses 12000*1500*57 grid cells. First results of this so far unique simulation will be presented.

  2. Modelling soil-plant-atmosphere interactions by coupling the regional weather model WRF to mechanistic plant models

    Science.gov (United States)

    Klein, C.; Hoffmann, P.; Priesack, E.

    2012-04-01

    Climate change causes altering distributions of meteorological factors influencing plant growth and its interactions between the land surface and the atmosphere. Recent studies show, that uncertainties in regional and global climate simulations are also caused by lacking descriptions of the soil-plant-atmosphere system. Therefore, we couple a mechanistic soil-plant model to a regional climate and forecast model. The detailed simulation of the water and energy exchanges, especially the transpiration of grassland and forests stands, are the key features of the modelling framework. The Weather Research and Forecasting model (WRF) (Skamarock 2008) is an open source mesoscale numerical weather prediction model. The WRF model was modified in a way, to either choose its native, static land surface model NOAH or the mechanistic eco-system model Expert-N 5.0 individually for every single grid point within the simulation domain. The Expert-N 5.0 modelling framework provides a highly modular structure, enabling the development and use of a large variety of different plant and soil models, including heat transfer, nitrogen uptake/turnover/transport as well as water uptake/transport and crop management. To represent the key landuse types grassland and forest, we selected two mechanistic plant models: The Hurley Pasture model (Thornley 1998) and a modified TREEDYN3 forest simulation model (Bossel 1996). The models simulate plant growth, water, nitrogen and carbon flows for grassland and forest stands. A mosaic approach enables Expert-N to use high resolution land use data e.g. CORINE Land Cover data (CLC, 2006) for the simulation, making it possible to simulate different land use distributions within a single grid cell. The coupling results are analyzed for plausibility and compared with the results of the default land surface model NOAH (Fei Chen and Jimy Dudhia 2010). We show differences between the mechanistic and the static model coupling, with focus on the feedback effects

  3. Evaluating Parameterizations in General Circulation Models: Climate Simulation Meets Weather Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, T J; Potter, G L; Williamson, D L; Cederwall, R T; Boyle, J S; Fiorino, M; Hnilo, J J; Olson, J G; Xie, S; Yio, J J

    2004-05-06

    To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands that the GCM parameterizations of unresolved processes, in particular, should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provided that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by a realistically initialized climate GCM, and the application of six-hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be tested in the same framework. In order to further this method for evaluating and analyzing parameterizations in climate GCMs, the U.S. Department of Energy is funding a joint venture of its Climate Change Prediction Program (CCPP) and Atmospheric Radiation Measurement (ARM) Program: the CCPP-ARM Parameterization Testbed (CAPT). This article elaborates the scientific rationale for CAPT, discusses technical aspects of its methodology, and presents examples of its implementation in a representative climate GCM.

  4. 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.

  5. Contributions of the ARM Program to Radiative Transfer Modeling for Climate and Weather Applications

    Science.gov (United States)

    Mlawer, Eli J.; Iacono, Michael J.; Pincus, Robert; Barker, Howard W.; Oreopoulos, Lazaros; Mitchell, David L.

    2016-01-01

    Accurate climate and weather simulations must account for all relevant physical processes and their complex interactions. Each of these atmospheric, ocean, and land processes must be considered on an appropriate spatial and temporal scale, which leads these simulations to require a substantial computational burden. One especially critical physical process is the flow of solar and thermal radiant energy through the atmosphere, which controls planetary heating and cooling and drives the large-scale dynamics that moves energy from the tropics toward the poles. Radiation calculations are therefore essential for climate and weather simulations, but are themselves quite complex even without considering the effects of variable and inhomogeneous clouds. Clear-sky radiative transfer calculations have to account for thousands of absorption lines due to water vapor, carbon dioxide, and other gases, which are irregularly distributed across the spectrum and have shapes dependent on pressure and temperature. The line-by-line (LBL) codes that treat these details have a far greater computational cost than can be afforded by global models. Therefore, the crucial requirement for accurate radiation calculations in climate and weather prediction models must be satisfied by fast solar and thermal radiation parameterizations with a high level of accuracy that has been demonstrated through extensive comparisons with LBL codes. See attachment for continuation.

  6. Computation of optimal unstable structures for a numerical weather prediction model

    Science.gov (United States)

    Buizza, R.; Tribbia, J.; Molteni, F.; Palmer, T.

    1993-10-01

    Numerical experiments have been performed to compute the fastest growing perturbations in a finite time interval for a complex numerical weather prediction model. The models used are the tangent forward and adjoint versions of the adiabatic primitive-equation model of the Integrated Forecasting System developed at the European Centre for Medium-Range Weather Forecasts and Météo France. These have been run with a horizontal truncation T21, with 19 vertical levels. The fastest growing perturbations are the singular vectors of the propagator of the forward tangent model with the largest singular values. An iterative Lanczos algorithm has been used for the numerical computation of the perturbations. Sensitivity of the calculations to different time intervals and to the norm used in the definition of the adjoint model have been analysed. The impact of normal mode initialization has also been studied. Two classes of fastest growing perturbations have been found; one is characterized by a maximum amplitude in the middle troposphere, while the other is confined to model layers close to the surface. It is shown that the latter is damped by the boundary layer physics in the full model. The linear evolution of the perturbations has been compared to the non-linear evolution when the perturbations are superimposed on a basic state in the T63, 19-level version of the ECMWF model.

  7. Experience Transitioning Models and Data at the NOAA Space Weather Prediction Center

    Science.gov (United States)

    Berger, Thomas

    2016-07-01

    The NOAA Space Weather Prediction Center has a long history of transitioning research data and models into operations and with the validation activities required. The first stage in this process involves demonstrating that the capability has sufficient value to customers to justify the cost needed to transition it and to run it continuously and reliably in operations. Once the overall value is demonstrated, a substantial effort is then required to develop the operational software from the research codes. The next stage is to implement and test the software and product generation on the operational computers. Finally, effort must be devoted to establishing long-term measures of performance, maintaining the software, and working with forecasters, customers, and researchers to improve over time the operational capabilities. This multi-stage process of identifying, transitioning, and improving operational space weather capabilities will be discussed using recent examples. Plans for future activities will also be described.

  8. Weather and seasonal climate prediction for South America using a multi-model superensemble

    Science.gov (United States)

    Chaves, Rosane R.; Ross, Robert S.; Krishnamurti, T. N.

    2005-11-01

    This work examines the feasibility of weather and seasonal climate predictions for South America using the multi-model synthetic superensemble approach for climate, and the multi-model conventional superensemble approach for numerical weather prediction, both developed at Florida State University (FSU). The effect on seasonal climate forecasts of the number of models used in the synthetic superensemble is investigated. It is shown that the synthetic superensemble approach for climate and the conventional superensemble approach for numerical weather prediction can reduce the errors over South America in seasonal climate prediction and numerical weather prediction.For climate prediction, a suite of 13 models is used. The forecast lead-time is 1 month for the climate forecasts, which consist of precipitation and surface temperature forecasts. The multi-model ensemble is comprised of four versions of the FSU-Coupled Ocean-Atmosphere Model, seven models from the Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction (DEMETER), a version of the Community Climate Model (CCM3), and a version of the predictive Ocean Atmosphere Model for Australia (POAMA). The results show that conditions over South America are appropriately simulated by the Florida State University Synthetic Superensemble (FSUSSE) in comparison to observations and that the skill of this approach increases with the use of additional models in the ensemble. When compared to observations, the forecasts are generally better than those from both a single climate model and the multi-model ensemble mean, for the variables tested in this study.For numerical weather prediction, the conventional Florida State University Superensemble (FSUSE) is used to predict the mass and motion fields over South America. Predictions of mean sea level pressure, 500 hPa geopotential height, and 850 hPa wind are made with a multi-model superensemble comprised of six global models for the period

  9. 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)

  10. 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.

  11. Post Processing Numerical Weather Prediction Model Rainfall Forecasts for Use in Ensemble Streamflow Forecasting in Australia

    Science.gov (United States)

    Shrestha, D. L.; Robertson, D.; Bennett, J.; Ward, P.; Wang, Q. J.

    2012-12-01

    Through the water information research and development alliance (WIRADA) project, CSIRO is conducting research to improve flood and short-term streamflow forecasting services delivered by the Australian Bureau of Meteorology. WIRADA aims to build and test systems to generate ensemble flood and short-term streamflow forecasts with lead times of up to 10 days by integrating rainfall forecasts from Numerical Weather Prediction (NWP) models and hydrological modelling. Here we present an overview of the latest progress towards developing this system. Rainfall during the forecast period is a major source of uncertainty in streamflow forecasting. Ensemble rainfall forecasts are used in streamflow forecasting to characterise the rainfall uncertainty. In Australia, NWP models provide forecasts of rainfall and other weather conditions for lead times of up to 10 days. However, rainfall forecasts from Australian NWP models are deterministic and often contain systematic errors. We use a simplified Bayesian joint probability (BJP) method to post-process rainfall forecasts from the latest generation of Australian NWP models. The BJP method generates reliable and skilful ensemble rainfall forecasts. The post-processed rainfall ensembles are then used to force a semi-distributed conceptual rainfall runoff model to produce ensemble streamflow forecasts. The performance of the ensemble streamflow forecasts is evaluated on a number of Australian catchments and the benefits of using post processed rainfall forecasts are demonstrated.

  12. Parallelization and Performance of the NIM Weather Model Running on GPUs

    Science.gov (United States)

    Govett, Mark; Middlecoff, Jacques; Henderson, Tom; Rosinski, James

    2014-05-01

    The Non-hydrostatic Icosahedral Model (NIM) is a global weather prediction model being developed to run on the GPU and MIC fine-grain architectures. The model dynamics, written in Fortran, was initially parallelized for GPUs in 2009 using the F2C-ACC compiler and demonstrated good results running on a single GPU. Subsequent efforts have focused on (1) running efficiently on multiple GPUs, (2) parallelization of NIM for Intel-MIC using openMP, (3) assessing commercial Fortran GPU compilers now available from Cray, PGI and CAPS, (4) keeping the model up to date with the latest scientific development while maintaining a single source performance portable code, and (5) parallelization of two physics packages used in the NIM: the operational Global Forecast System (GFS) used operationally, and the widely used Weather Research and Forecast (WRF) model physics. The presentation will touch on each of these efforts, but highlight improvements in parallel performance of the NIM running on the Titan GPU cluster at ORNL, the ongong parallelization of model physics, and a recent evaluation of commercial GPU compilers using the F2C-ACC compiler as the baseline.

  13. 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.

  14. Verification of GRAPES unified global and regional numerical weather prediction model dynamic core

    Institute of Scientific and Technical Information of China (English)

    YANG XueSheng; HU JiangLin; CHEN DeHui; ZHANG HongLiang; SHEN XueShun; CHEN JiaBin; JI LiRen

    2008-01-01

    During the past few years, most of the new developed numerical weather prediction models adopt the strategy of multi-scale technique. Therefore, China Meteorological Administration has devoted to de-veloping a new generation of global and regional multi-scale model since 2003. In order to validate the performance of the GRAPES (Global and Regional Assimilation and PrEdiction System) model both for its scientific design and program coding, a suite of idealized tests has been proposed and conducted, which includes the density flow test, three-dimensional mountain wave and the cross-polar flow test. The density flow experiment indicates that the dynamic core has the ability to simulate the fine scale nonlinear flow structures and its transient features. While the three-dimensional mountain wave test shows that the model can reproduce the horizontal and vertical propagation of internal gravity waves quite well. Cross-polar flow test demonstrates the rationality of both for the semi-Lagrangian departure point calculation and the discretization of the model near the poles. The real case forecasts reveal that the model has the ability to predict the large-scale weather regimes in summer such as the subtropical high, and to capture the major synoptic patterns in the mid and high latitudes.

  15. How much does weather-driven vegetation dynamics matter in land surface modelling?

    Science.gov (United States)

    Ingwersen, Joachim; Streck, Thilo

    2016-04-01

    Land surface models (LSM) are an essential part of weather and climate models as they provide the lower boundary condition for the atmospheric models. In state-of-the-art LSMs the seasonal vegetation dynamics is "frozen". The seasonal variation of vegetation state variables, such as leaf area index or green vegetation fraction, are prescribed in lookup tables. Hence, a year-by-year variation in the development of vegetation due to changing weather conditions cannot be considered. For climate simulations, this is obviously a severe drawback. The objective of the present study was to quantify the potential error in the simulation of land surface exchange processes resulting from "frozen" vegetation dynamics. For this purpose we simulated energy and water fluxes from a winter wheat stand and a maize stand in Southwest Germany. In a first set of simulations, six years (2010 to 2015) were simulated considering weather-driven vegetation dynamics. For this purpose, we coupled the generic crop growth model GECROS with the NOAH-MP model (NOAHMP-GECROS). In a second set of simulations all vegetation-related state variables of the 2010 simulation were written to an external file and were used to overwrite the vegetation-related state variables of the simulations of the years 2011-2015. The difference between both sets was taken as a measure for the potential error introduced to the LSM due to the assumption of a "frozen" vegetation dynamics. We will present first results and discuss the impact of "frozen" vegetation dynamics on climate change simulations.

  16. Modeling land-surface processes and land-atmosphere interactions in the community weather and regional climate WRF model (Invited)

    Science.gov (United States)

    Chen, F.; Barlage, M. J.

    2013-12-01

    The Weather Research and Forecasting (WRF) model has been widely used with high-resolution configuration in the weather and regional climate communities, and hence demands its land-surface models to treat not only fast-response processes, such as plant evapotranspiration that are important for numerical weather prediction but also slow-evolving processes such as snow hydrology and interactions between surface soil water and deep aquifer. Correctly representing urbanization, which has been traditionally ignored in coarse-resolution modeling, is critical for applying WRF to air quality and public health research. To meet these demands, numerous efforts have been undertaken to improve land-surface models (LSM) in WRF, including the recent implementation of the Noah-MP (Noah Multiple-Physics). Noah-MP uses multiple options for key sub-grid land-atmosphere interaction processes (Niu et al., 2011; Yang et al., 2011), and contains a separate vegetation canopy representing within- and under-canopy radiation and turbulent processes, a multilayer physically-based snow model, and a photosynthesis canopy resistance parameterization with a dynamic vegetation model. This paper will focus on the interactions between fast and slow land processes through: 1) a benchmarking of the Noah-MP performance, in comparison to five widely-used land-surface models, in simulating and diagnosing snow evolution for complex terrain forested regions, and 2) the effects of interactions between shallow and deep aquifers on regional weather and climate. Moreover, we will provide an overview of recent improvements of the integrated WRF-Urban modeling system, especially its hydrological enhancements that takes into account the effects of lawn irrigation, urban oasis, evaporation from pavements, anthropogenic moisture sources, and a green-roof parameterization.

  17. 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

  18. 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.

  19. Urban modelling for Budapest using the Weather Research and Forecasting model

    Science.gov (United States)

    Göndöcs, Júlia; Breuer, Hajnalka; Pongrácz, Rita; Bartholy, Judit

    2016-04-01

    The population of Earth is continuously growing, and due to urbanisation it is quite concentrated in metropolitan areas. Overall, cities cover almost 2% of the global surface causing several environmental and social issues. These artificial surface covers significantly modify the surface energy exchange processes through modification of naturally covered lands resulting in altered local wind and temperature patterns because of the presence of buildings. The architectures' three-dimensional extensions certainly affect the incoming radiation, the sky-view factors as well, as the 3D wind fields, resulting in specific local microclimate at each metropolitan area. The increased temperature in the central built-up areas and the cooler surrounding of the cities lead to the urban heat island phenomenon, which is widely studied both with observations and numerical models. The Weather Research and Forecasting (WRF) mesoscale model coupled to multilayer urban canopy parameterisation is used to investigate this phenomenon for Budapest and its surroundings. Before starting the simulations, the detailed surface has to be set up according to the actual conditions, for which CORINE and OpenStreetMap databases are used, both including buildings, different land use categories, and waterbodies. The new land use distribution serving as input for WRF runs distinguishes three urban categories: (i) low-intensity residential, (ii) high-intensity residential, and (iii) commercial/industrial. For the simulations the initial meteorological fields are derived from the publicly available GFS (Global Forecast System) outputs. Simulations are completed for one-week-long periods in summer and winter in 2015, for which we selected periods with the atmospheric conditions of weak wind and clear sky. In order to keep the stability of the simulations, the entire downscaling is carried out in several steps using gradually smaller domains embedded to each other. Thus, three embedded target areas have

  20. The power of weather

    OpenAIRE

    Christian Huurman; Francesco Ravazzolo; Chen Zhou

    2010-01-01

    This paper examines the predictive power of weather for electricity prices in day ahead markets in real time. We find that next-day weather forecasts improve the forecast accuracy of Scandinavian day-ahead electricity prices substantially in terms of point forecasts, suggesting that weather forecasts can price the weather premium. This improvement strengthens the confidence in the forecasting model, which results in high center-mass predictive densities. In density forecast, such a predictive...

  1. Overview of the Diagnostic Cloud Forecast Model at the Air Force Weather Agency

    Science.gov (United States)

    Hildebrand, E. P.

    2014-12-01

    The Air Force Weather Agency (AFWA) is responsible for running and maintaining the Diagnostic Cloud Forecast (DCF) model to support DoD missions and those of their external partners. The DCF model generates three-dimensional cloud forecasts for global and regional domains at various resolutions. Regional domains are chosen based on Air Force mission needs. DCF is purely a statistical model that can be appended to any numerical weather prediction (NWP) model. Operationally, AFWA runs the DCF model deterministically using GFS data from NCEP and WRF data that are created in-house. In addition, AFWA also runs an ensemble version of the DCF model using the Mesoscale Ensemble Prediction System (MEPS). The deterministic DCF uses predictor variables from the WRF or GFS models, depending on whether the domain is regional or global, and statistically relates them to observed cloud cover from the World-Wide Merged Cloud Analysis (WWMCA). The forecast process of the model uses an ordinal logistic regression to predict membership in one of 101 groups (every 1% from 0-100%). The predicted group membership then is translated into a cloud amount. This is performed on 21 pressure levels ranging from 1000 hPa to 100 hPa. Cloud amount forecasts on these 21 levels are used along with the NWP geopotential height forecasts to estimate the base and top heights of cloud layers in the vertical. DCF also includes routines to estimate the amount and type of cloud within each layer. Forecasts of total cloud amount are verified using the WWMCA, as well as independent sources of cloud data. This presentation will include an overview of the DCF model and its use at AFWA. Results will be presented to show that DCF adds value over the raw cloud forecasts from NWP models. Ideas for future work also will be addressed.

  2. Model-based screening for critical wet-weather discharges related to micropollutants from urban areas.

    Science.gov (United States)

    Mutzner, Lena; Staufer, Philipp; Ort, Christoph

    2016-11-01

    Wet-weather discharges contribute to anthropogenic micropollutant loads entering the aquatic environment. Thousands of wet-weather discharges exist in Swiss sewer systems, and we do not have the capacity to monitor them all. We consequently propose a model-based approach designed to identify critical discharge points in order to support effective monitoring. We applied a dynamic substance flow model to four substances representing different entry routes: indoor (Triclosan, Mecoprop, Copper) as well as rainfall-mobilized (Glyphosate, Mecoprop, Copper) inputs. The accumulation on different urban land-use surfaces in dry weather and subsequent substance-specific wash-off is taken into account. For evaluation, we use a conservative screening approach to detect critical discharge points. This approach considers only local dilution generated onsite from natural, unpolluted areas, i.e. excluding upstream dilution. Despite our conservative assumptions, we find that the environmental quality standards for Glyphosate and Mecoprop are not exceeded during any 10-min time interval over a representative one-year simulation period for all 2500 Swiss municipalities. In contrast, the environmental quality standard is exceeded during at least 20% of the discharge time at 83% of all modelled discharge points for Copper and at 71% for Triclosan. For Copper, this corresponds to a total median duration of approximately 19 days per year. For Triclosan, discharged only via combined sewer overflows, this means a median duration of approximately 10 days per year. In general, stormwater outlets contribute more to the calculated effect than combined sewer overflows for rainfall-mobilized substances. We further evaluate the Urban Index (Aurban,impervious/Anatural) as a proxy for critical discharge points: catchments where Triclosan and Copper exceed the corresponding environmental quality standard often have an Urban Index >0.03. A dynamic substance flow analysis allows us to identify the most

  3. Post-processing rainfall forecasts from numerical weather prediction models for short-term streamflow forecasting

    Directory of Open Access Journals (Sweden)

    D. E. Robertson

    2013-09-01

    Full Text Available Sub-daily ensemble rainfall forecasts that are bias free and reliably quantify forecast uncertainty are critical for flood and short-term ensemble streamflow forecasting. Post-processing of rainfall predictions from numerical weather prediction models is typically required to provide rainfall forecasts with these properties. In this paper, a new approach to generate ensemble rainfall forecasts by post-processing raw numerical weather prediction (NWP rainfall predictions is introduced. The approach uses a simplified version of the Bayesian joint probability modelling approach to produce forecast probability distributions for individual locations and forecast lead times. Ensemble forecasts with appropriate spatial and temporal correlations are then generated by linking samples from the forecast probability distributions using the Schaake shuffle. The new approach is evaluated by applying it to post-process predictions from the ACCESS-R numerical weather prediction model at rain gauge locations in the Ovens catchment in southern Australia. The joint distribution of NWP predicted and observed rainfall is shown to be well described by the assumed log-sinh transformed bivariate normal distribution. Ensemble forecasts produced using the approach are shown to be more skilful than the raw NWP predictions both for individual forecast lead times and for cumulative totals throughout all forecast lead times. Skill increases result from the correction of not only the mean bias, but also biases conditional on the magnitude of the NWP rainfall prediction. The post-processed forecast ensembles are demonstrated to successfully discriminate between events and non-events for both small and large rainfall occurrences, and reliably quantify the forecast uncertainty. Future work will assess the efficacy of the post-processing method for a wider range of climatic conditions and also investigate the benefits of using post-processed rainfall forecasts for flood and short

  4. 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.

  5. 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...

  6. 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.

  7. Toward Performance Portability of the FV3 Weather Model on CPU, GPU and MIC Processors

    Science.gov (United States)

    Govett, Mark; Rosinski, James; Middlecoff, Jacques; Schramm, Julie; Stringer, Lynd; Yu, Yonggang; Harrop, Chris

    2017-04-01

    The U.S. National Weather Service has selected the FV3 (Finite Volume cubed) dynamical core to become part of the its next global operational weather prediction model. While the NWS is preparing to run FV3 operationally in late 2017, NOAA's Earth System Research Laboratory is adapting the model to be capable of running on next-generation GPU and MIC processors. The FV3 model was designed in the 1990s, and while it has been extensively optimized for traditional CPU chips, some code refactoring has been required to expose sufficient parallelism needed to run on fine-grain GPU processors. The code transformations must demonstrate bit-wise reproducible results with the original CPU code, and between CPU, GPU and MIC processors. We will describe the parallelization and performance while attempting to maintain performance portability between CPU, GPU and MIC with the Fortran source code. Performance results will be shown using NOAA's new Pascal based fine-grain GPU system (800 GPUs), and for the Knights Landing processor on the National Science Foundation (NSF) Stampede-2 system.

  8. Impacts of combining reanalyses and weather station data on the accuracy of discharge modelling

    Science.gov (United States)

    Essou, Gilles R. C.; Brissette, François; Lucas-Picher, Philippe

    2017-02-01

    Reanalyses are important sources of meteorological data. Recent studies have shown that precipitation and temperature data from reanalysis present a strong potential for hydrological modelling, especially in regions with a sparse observational network. The objective of this study is to evaluate the impacts of the combination of three global atmospheric reanalyses - ERA-Interim, CFSR and MERRA - and one gridded observation dataset on the accuracy of hydrological model discharge simulations. Two combination approaches were used. The first one combined reanalyses and the observational database using a weighted average of the precipitation and temperature inputs. The second one consisted in using all meteorological inputs separately and combining the simulated hydrographs. The combinations were performed over 460 Canadian watersheds (representing regions with a low density of weather stations) and 370 US watersheds (representing regions with a higher density of weather stations). Results showed significant improvements in the simulated discharges for 68% and 92% of the Canadian watersheds for the input combinations and output combinations, respectively. Moreover, both approaches led to significant improvements in the simulated discharges for 72% of the US watersheds studied. For all watersheds where simulated discharges using observational data had a Nash Sutcliffe efficiency (NSE) lower than 0.5, the combination with reanalyses resulted in a median NSE increase of 0.3. This indicates that reanalysis can successfully compensate for deficiencies in the surface observation record and provide significantly better hydrological modelling performance.

  9. 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.

  10. Forcing the snow-cover model SNOWPACK with forecasted weather data

    Directory of Open Access Journals (Sweden)

    S. Bellaire

    2011-12-01

    Full Text Available Avalanche danger is often estimated based on snow cover stratigraphy and snow stability data. In Canada, single forecasting regions are very large (>50 000 km2 and snow cover data are often not available. To provide additional information on the snow cover and its seasonal evolution the Swiss snow cover model SNOWPACK was therefore coupled with a regional weather forecasting model GEM15. The output of GEM15 was compared to meteorological as well as snow cover data from Mt. Fidelity, British Columbia, Canada, for five winters between 2005 and 2010. Precipitation amounts are most difficult to predict for weather forecasting models. Therefore, we first assess the capability of the model chain to forecast new snow amounts and consequently snow depth. Forecasted precipitation amounts were generally over-estimated. The forecasted data were therefore filtered and used as input for the snow cover model. Comparison between the model output and manual observations showed that after pre-processing the input data the snow depth and new snow events were well modelled. In a case study two key factors of snow cover instability, i.e. surface hoar formation and crust formation were investigated at a single point. Over half of the relevant critical layers were reproduced. Overall, the model chain shows promising potential as a future forecasting tool for avalanche warning services in Canadian data sparse areas and could thus well be applied to similarly large regions elsewhere. However, a more detailed analysis of the simulated snow cover structure is still required.

  11. Modeling Weather in the Ionosphere using the Navy's Highly Integrated Thermosphere and Ionosphere Demonstration System (HITIDES)

    Science.gov (United States)

    McDonald, S. E.; Sassi, F.; Zawdie, K.; McCormack, J. P.; Coker, C.; Huba, J.; Krall, J.

    2016-12-01

    The Naval Research Laboratory (NRL) has recently developed a ground-to-space atmosphere-ionosphere prediction capability, the Highly Integrated Thermosphere and Ionosphere Demonstration System (HITIDES). HITIDES is the U.S. Navy's first coupled, physics-based, atmosphere-ionosphere model, one in which the atmosphere extends from the ground to the exobase ( 500 km altitude) and the ionosphere reaches several 10,000 km in altitude. HITIDES has been developed by coupling the extended version of the Whole Atmosphere Community Climate Model (WACCM-X) with NRL's ionospheric model, Sami3 is Another Model of the Ionosphere (SAMI3). Integrated into this model are the effects of drivers from atmospheric weather (day-to-day meteorology), the Sun, and the changing high altitude composition. To simulate specific events, HITIDES can be constrained by data analysis products or observations. We have performed simulations of the ionosphere during January-February 2010 in which lower atmospheric weather patterns have been introduced using the Navy Operational Global Atmospheric Prediction System-Advanced Level Physics High Altitude (NOGAPS-ALPHA) data assimilation products. The same time period has also been simulated using the new atmospheric forecast model, the NAVy Global Environmental Model (NAVGEM), which has replaced NOGAPS-ALPHA. The two simulations are compared with each other and with observations of the low latitude ionosphere. We will discuss the importance of including lower atmospheric meteorology in ionospheric simulations to capture day-to-day variability as well as large-scale longitudinal structure in the low-latitude ionosphere. In addition, we examine the effect of the variability on HF radio wave propagation by comparing simulated ionograms calculated from the HITIDES ionospheric specifications to ionosonde measurements.

  12. 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).

  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. 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

    The existence of vertical wind shear in the atmosphere close to the ground requires that wind resource assessment and prediction with numerical weather prediction (NWP) models use wind forecasts at levels within the full rotor span of modern large wind turbines. The performance of NWP models...... 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...

  15. Effects of Real-Time NASA Vegetation Data on Model Forecasts of Severe Weather

    Science.gov (United States)

    Case, Jonathan L.; Bell, Jordan R.; LaFontaine, Frank J.; Peters-Lidard, Christa D.

    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 started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the

  16. 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.

  17. Bayesian random effect models incorporating real-time weather and traffic data to investigate mountainous freeway hazardous factors.

    Science.gov (United States)

    Yu, Rongjie; Abdel-Aty, Mohamed; Ahmed, Mohamed

    2013-01-01

    Freeway crash occurrences are highly influenced by geometric characteristics, traffic status, weather conditions and drivers' behavior. For a mountainous freeway which suffers from adverse weather conditions, it is critical to incorporate real-time weather information and traffic data in the crash frequency study. In this paper, a Bayesian inference method was employed to model one year's crash data on I-70 in the state of Colorado. Real-time weather and traffic variables, along with geometric characteristics variables were evaluated in the models. Two scenarios were considered in this study, one seasonal and one crash type based case. For the methodology part, the Poisson model and two random effect models with a Bayesian inference method were employed and compared in this study. Deviance Information Criterion (DIC) was utilized as a comparison factor. The correlated random effect models outperformed the others. The results indicate that the weather condition variables, especially precipitation, play a key role in the crash occurrence models. The conclusions imply that different active traffic management strategies should be designed based on seasons, and single-vehicle crashes have different crash mechanism compared to multi-vehicle crashes.

  18. 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...

  19. Space Weather Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Space Weather Analysis archives are model output of ionospheric, thermospheric and magnetospheric particle populations, energies and electrodynamics

  20. 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

  1. EMPOL 1.0: a new parameterization of pollen emission in numerical weather prediction models

    Directory of Open Access Journals (Sweden)

    K. Zink

    2013-05-01

    Full Text Available Simulating pollen concentrations with numerical weather prediction (NWP systems requires a parameterization for pollen emission. We have developed a parameterization that is adaptable for different plant species. Both biological and physical processes of pollen emission are taken into account by parameterizing emission as a~two-step process: (1 the release of the pollen from the flowers, and (2 their entrainment into the atmosphere. Key factors influencing emission are: temperature, relative humidity, the turbulent kinetic energy and precipitation. We have simulated the birch pollen season of 2012 using the NWP system COSMO-ART, both with a parameterization already present in the model and our new parameterization EMPOL. The statistical results show that the performance of the model can be enhanced using EMPOL.

  2. Generating extreme weather event sets from very large ensembles of regional climate models

    Science.gov (United States)

    Massey, Neil; Guillod, Benoit; Otto, Friederike; Allen, Myles; Jones, Richard; Hall, Jim

    2015-04-01

    Generating extreme weather event sets from very large ensembles of regional climate models Neil Massey, Benoit P. Guillod, Friederike E. L. Otto, Myles R. Allen, Richard Jones, Jim W. Hall Environmental Change Institute, University of Oxford, Oxford, UK Extreme events can have large impacts on societies and are therefore being increasingly studied. In particular, climate change is expected to impact the frequency and intensity of these events. However, a major limitation when investigating extreme weather events is that, by definition, only few events are present in observations. A way to overcome this issue it to use large ensembles of model simulations. Using the volunteer distributed computing (VDC) infrastructure of weather@home [1], we run a very large number (10'000s) of RCM simulations over the European domain at a resolution of 25km, with an improved land-surface scheme, nested within a free-running GCM. Using VDC allows many thousands of climate model runs to be computed. Using observations for the GCM boundary forcings we can run historical "hindcast" simulations over the past 100 to 150 years. This allows us, due to the chaotic variability of the atmosphere, to ascertain how likely an extreme event was, given the boundary forcings, and to derive synthetic event sets. The events in these sets did not actually occur in the observed record but could have occurred given the boundary forcings, with an associated probability. The event sets contain time-series of fields of meteorological variables that allow impact modellers to assess the loss the event would incur. Projections of events into the future are achieved by modelling projections of the sea-surface temperature (SST) and sea-ice boundary forcings, by combining the variability of the SST in the observed record with a range of warming signals derived from the varying responses of SSTs in the CMIP5 ensemble to elevated greenhouse gas (GHG) emissions in three RCP scenarios. Simulating the future with a

  3. Cloud detection using Meteosat imagery and numerical weather prediction model data

    CERN Document Server

    Feijt, A; Van der Veen, S

    2000-01-01

    The cloud detection algorithm of the Royal Netherlands Meteorological Institute (KNMI) Meteosat Cloud Detection and Characterization KNMI (Metclock) scheme is introduced. The algorithm analyzes the Meteosat infrared and visual channel measurements over an area from about 25 degrees W to 25 degrees E and from 35 degrees to 70 degrees N, encompassing Europe and a small part of northern Africa. The scheme utilizes surface temperatures from a numerical weather prediction model. Synoptic observations are used to adjust the model surface temperatures to represent satellite brightness temperatures for cloud-free conditions. The measured reflected sunlight is analyzed using a minimum reflectivity atlas. Comparison of cloud detection results with synoptic observations of cloud cover at about 800 synoptic stations over land and 50 over sea were made on a 3-h basis for 1997. In total, two million synoptic observations were used to evaluate the detection method. Of the reported cloud cover, Metclock detected 89% during d...

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

    Energy Technology Data Exchange (ETDEWEB)

    Driskell, W.B.; Payne, J.R. [Payne Environmental Consultants Inc., Encinitas, CA (United States); Shigenaka, G. [National Oceanic and Atmospheric Administration, Seattle, WA (United States)

    2005-07-01

    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.

  5. A PBL-radiation model for application to regional numerical weather prediction

    Science.gov (United States)

    Chang, Chia-Bo

    1989-01-01

    Often in the short-range limited-area numerical weather prediction (NWP) of extratropical weather systems the effects of planetary boundary layer (PBL) processes are considered secondarily important. However, it may not be the case for the regional NWP of mesoscale convective systems over the arid and semi-arid highlands of the southwestern and south-central United States in late spring and summer. Over these dry regions, the PBL can grow quite high up into the lower middle troposphere (600 mb) due to very effective solar heating and hence a vigorous air-land thermal interaction can occur. The interaction representing a major heat source for regional dynamical systems can not be ignored. A one-dimensional PBL-radiation model was developed. The model PBL consists of a constant-flux surface layer superposed with a well-mixed (Ekman) layer. The vertical eddy mixing coefficients for heat and momentum in the surface layer are determined according to the surface similarity theory, while their vertical profiles in the Ekman layer are specified with a cubic polynomial. Prognostic equations are used for predicting the height of the nonneutral PBL. The atmospheric radiation is parameterized to define the surface heat source/sink for the growth and decay of the PBL. A series of real-data numerical experiments has been carried out to obtain a physical understanding how the model performs under various atmospheric and surface conditions. This one-dimensional model will eventually be incorporated into a mesoscale prediction system. The ultimate goal of this research is to improve the NWP of mesoscale convective storms over land.

  6. 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.

  7. Space Weather Influence on Power Systems: Prediction, Risk Analysis, and Modeling

    Science.gov (United States)

    Yatsenko, Vitaliy

    2016-04-01

    This report concentrates on dynamic probabilistic risk analysis of optical elements for complex characterization of damages using physical model of solid state lasers and predictable level of ionizing radiation and space weather. The following main subjects will be covered by our report: (a) solid-state laser model; (b) mathematical models for dynamic probabilistic risk assessment; and (c) software for modeling and prediction of ionizing radiation. A probabilistic risk assessment method for solid-state lasers is presented with consideration of some deterministic and stochastic factors. Probabilistic risk assessment is a comprehensive, structured, and logical analysis method aimed at identifying and assessing risks in solid-state lasers for the purpose of cost-e®ectively improving their safety and performance. This method based on the Conditional Value-at-Risk measure (CVaR) and the expected loss exceeding Value-at-Risk (VaR). We propose to use a new dynamical-information approach for radiation damage risk assessment of laser elements by cosmic radiation. Our approach includes the following steps: laser modeling, modeling of ionizing radiation in°uences on laser elements, probabilistic risk assessment methods, and risk minimization. For computer simulation of damage processes at microscopic and macroscopic levels the following methods are used: () statistical; (b) dynamical; (c) optimization; (d) acceleration modeling, and (e) mathematical modeling of laser functioning. Mathematical models of space ionizing radiation in°uence on laser elements were developed for risk assessment in laser safety analysis. This is a so-called `black box' or `input-output' models, which seeks only to reproduce the behaviour of the system's output in response to changes in its inputs. The model inputs are radiation in°uences on laser systems and output parameters are dynamical characteristics of the solid laser. Algorithms and software for optimal structure and parameters of

  8. 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.

  9. Post processing rainfall forecasts from numerical weather prediction models for short term streamflow forecasting

    Directory of Open Access Journals (Sweden)

    D. E. Robertson

    2013-05-01

    Full Text Available Sub-daily ensemble rainfall forecasts that are bias free and reliably quantify forecast uncertainty are critical for flood and short-term ensemble streamflow forecasting. Post processing of rainfall predictions from numerical weather prediction models is typically required to provide rainfall forecasts with these properties. In this paper, a new approach to generate ensemble rainfall forecasts by post processing raw NWP rainfall predictions is introduced. The approach uses a simplified version of the Bayesian joint probability modelling approach to produce forecast probability distributions for individual locations and forecast periods. Ensemble forecasts with appropriate spatial and temporal correlations are then generated by linking samples from the forecast probability distributions using the Schaake shuffle. The new approach is evaluated by applying it to post process predictions from the ACCESS-R numerical weather prediction model at rain gauge locations in the Ovens catchment in southern Australia. The joint distribution of NWP predicted and observed rainfall is shown to be well described by the assumed log-sinh transformed multivariate normal distribution. Ensemble forecasts produced using the approach are shown to be more skilful than the raw NWP predictions both for individual forecast periods and for cumulative totals throughout the forecast periods. Skill increases result from the correction of not only the mean bias, but also biases conditional on the magnitude of the NWP rainfall prediction. The post processed forecast ensembles are demonstrated to successfully discriminate between events and non-events for both small and large rainfall occurrences, and reliably quantify the forecast uncertainty. Future work will assess the efficacy of the post processing method for a wider range of climatic conditions and also investigate the benefits of using post processed rainfall forecast for flood and short term streamflow forecasting.

  10. 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...

  11. Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

    CERN Document Server

    Voyant, Cyril; 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 (ALADIN). We particularly look at the Multi-Layer Perceptron. After optimizing our architecture with ALADIN 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 ANN/ARMA is 14.9% compared to 26.2% for the na\\"ive persistence predictor. Note that in the stand alone 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

  12. 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

    horizontal grid spacing inner domain centered near San Diego, California. The San Diego area contains a mixture of urban , suburban, agricultural, and...Global Forecast System (GFS) model (Environmental Modeling Center 2003). The WRE–N is envisioned to be a rapid-update cycling application of WRF–ARW...surface– hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Monthly Weather Review. 2001a

  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. Evaluating storm-scale groundwater recharge dynamics with coupled weather radar data and unsaturated zone modeling

    Science.gov (United States)

    Nasta, P.; Gates, J. B.; Lock, N.; Houston, A. L.

    2013-12-01

    Groundwater recharge rates through the unsaturated zone emerge from complex interactions within the soil-vegetation-atmosphere system that derive from nonlinear relationships amongst atmospheric boundary conditions, plant water use and soil hydraulic properties. While it is widely recognized that hydrologic models must capture soil water dynamics in order to provide reliable recharge estimates, information on episodic recharge generation remains uncommon, and links between storm-scale weather patterns and their influence on recharge is largely unexplored. In this study, the water balance of a heterogeneous one-dimensional soil domain (3 m deep) beneath a typical rainfed corn agro-ecosystem in eastern Nebraska was numerically simulated in HYDRUS-1D for 12 years (2001-2012) on hourly time steps in order to assess the relationships between weather events and episodic recharge generation. WSR-88D weather radar reflectivity data provided both rainfall forcing data (after estimating rain rates using the z/r ratio method) and a means of storm classification on a scale from convective to stratiform using storm boundary characteristics. Individual storm event importance to cumulative recharge generation was assessed through iterative scenario modeling (773 total simulations). Annual cumulative recharge had a mean value of 9.19 cm/yr (about 12 % of cumulative rainfall) with coefficient of variation of 73%. Simulated recharge generation events occurred only in late winter and spring, with a peak in May (about 35% of total annual recharge). Recharge generation is observed primarily in late spring and early summer because of the combination of high residual soil moisture following a winter replenishment period, heavy convective storms, and low to moderate potential evapotranspiration rates. During the growing season, high rates of root water uptake cause rapid soil water depletion, and the concurrent high potential evapotranspiration and low soil moisture prevented recharge

  15. New efficient optimizing techniques for Kalman filters and numerical weather prediction models

    Science.gov (United States)

    Famelis, Ioannis; Galanis, George; Liakatas, Aristotelis

    2016-06-01

    The need for accurate local environmental predictions and simulations beyond the classical meteorological forecasts are increasing the last years due to the great number of applications that are directly or not affected: renewable energy resource assessment, natural hazards early warning systems, global warming and questions on the climate change can be listed among them. Within this framework the utilization of numerical weather and wave prediction systems in conjunction with advanced statistical techniques that support the elimination of the model bias and the reduction of the error variability may successfully address the above issues. In the present work, new optimization methods are studied and tested in selected areas of Greece where the use of renewable energy sources is of critical. The added value of the proposed work is due to the solid mathematical background adopted making use of Information Geometry and Statistical techniques, new versions of Kalman filters and state of the art numerical analysis tools.

  16. On the Assimilation of Satellite Sounder Data in Cloudy Skies in Numerical Weather Prediction Models

    Institute of Scientific and Technical Information of China (English)

    李俊; 王培; 李金龙; 郑婧

    2016-01-01

    Satellite measurements are an important source of global observations in support of numerical weather prediction (NWP). The assimilation of satellite radiances under clear skies has greatly improved NWP forecast scores. However, the application of radiances in cloudy skies remains a signifi cant challenge. In order to better assimilate radiances in cloudy skies, it is very important to detect any clear fi eld-of-view (FOV) accurately and assimilate cloudy radiances appropriately. Research progress on both clear FOV detection methodologies and cloudy radiance assimilation techniques are reviewed in this paper. Overview on approaches being implemented in the operational centers and studied by the satellite data assimilation research community is presented. Challenges and future directions for satellite sounder radiance assimilation in cloudy skies in NWP models are also discussed.

  17. The importance of terrestrial weathering for climate system modelling on extended timescales: a study with the UVic ESCM

    Science.gov (United States)

    Brault, Marc-Olivier; Matthews, Damon; Mysak, Lawrence

    2016-04-01

    The chemical erosion of carbonate and silicate rocks is a key process in the global carbon cycle and, through its coupling with calcium carbonate deposition in the ocean, is the primary sink of carbon on geologic timescales. The dynamic interdependence of terrestrial weathering rates with atmospheric temperature and carbon dioxide concentrations is crucial to the regulation of Earth's climate over multi-millennial timescales. However any attempts to develop a modeling context for terrestrial weathering as part of a dynamic climate system are limited, mostly because of the difficulty in adapting the multi-millennial timescales of the implied negative feedback mechanism with those of the atmosphere and ocean. Much of the earlier work on this topic is therefore based on box-model approaches, abandoning spatial variability for the sake of computational efficiency and the possibility to investigate the impact of weathering on climate change over time frames much longer than those allowed by traditional climate system models. As a result we still have but a rudimentary understanding of the chemical weathering feedback mechanism and its effects on ocean biogeochemistry and atmospheric CO2. Here, we introduce a spatially-explicit, rock weathering model into the University of Victoria Earth System Climate Model (UVic ESCM). We use a land map which takes into account a number of different rock lithologies, changes in sea level, as well as an empirical model of the temperature and NPP dependency of weathering rates for the different rock types. We apply this new model to the last deglacial period (c. 21000BP to 13000BP) as well as a future climate change scenario (c. 1800AD to 6000AD+), comparing the results of our 2-D version of the weathering feedback mechanism to simulations using only the box-model parameterizations of Meissner et al. [2012]. These simulations reveal the importance of two-dimensional factors (i.e., changes in sea level and rock type distribution) in the

  18. Community Coordinated Modeling Center (CCMC): Using innovative tools and services to support worldwide space weather scientific communities and networks

    Science.gov (United States)

    Mendoza, A. M.; Bakshi, S.; Berrios, D.; Chulaki, A.; Evans, R. M.; Kuznetsova, M. M.; Lee, H.; MacNeice, P. J.; Maddox, M. M.; Mays, M. L.; Mullinix, R. E.; Ngwira, C. M.; Patel, K.; Pulkkinen, A.; Rastaetter, L.; Shim, J.; Taktakishvili, A.; Zheng, Y.

    2012-12-01

    Community Coordinated Modeling Center (CCMC) was established to enhance basic solar terrestrial research and to aid in the development of models for specifying and forecasting conditions in the space environment. In achieving this goal, CCMC has developed and provides a set of innovative tools varying from: Integrated Space Weather Analysis (iSWA) web -based dissemination system for space weather information, Runs-On-Request System providing access to unique collection of state-of-the-art solar and space physics models (unmatched anywhere in the world), Advanced Online Visualization and Analysis tools for more accurate interpretation of model results, Standard Data formats for Simulation Data downloads, and recently Mobile apps (iPhone/Android) to view space weather data anywhere to the scientific community. The number of runs requested and the number of resulting scientific publications and presentations from the research community has not only been an indication of the broad scientific usage of the CCMC and effective participation by space scientists and researchers, but also guarantees active collaboration and coordination amongst the space weather research community. Arising from the course of CCMC activities, CCMC also supports community-wide model validation challenges and research focus group projects for a broad range of programs such as the multi-agency National Space Weather Program, NSF's CEDAR (Coupling, Energetics and Dynamics of Atmospheric Regions), GEM (Geospace Environment Modeling) and Shine (Solar Heliospheric and INterplanetary Environment) programs. In addition to performing research and model development, CCMC also supports space science education by hosting summer students through local universities; through the provision of simulations in support of classroom programs such as Heliophysics Summer School (with student research contest) and CCMC Workshops; training next generation of junior scientists in space weather forecasting; and educating

  19. On the Improvement of Numerical Weather Prediction by Assimilation of Hub Height Wind Information in Convection-Resulted Models

    Science.gov (United States)

    Declair, Stefan; Stephan, Klaus; Potthast, Roland

    2015-04-01

    Determining the amount of weather dependent renewable energy is a demanding task for transmission system operators (TSOs). In the project EWeLiNE funded by the German government, the German Weather Service and the Fraunhofer Institute on Wind Energy and Energy System Technology strongly support the TSOs by developing innovative weather- and power forecasting models and tools for grid integration of weather dependent renewable energy. The key in the energy prediction process chain is the numerical weather prediction (NWP) system. With focus on wind energy, we face the model errors in the planetary boundary layer, which is characterized by strong spatial and temporal fluctuations in wind speed, to improve the basis of the weather dependent renewable energy prediction. Model data can be corrected by postprocessing techniques such as model output statistics and calibration using historical observational data. On the other hand, latest observations can be used in a preprocessing technique called data assimilation (DA). In DA, the model output from a previous time step is combined such with observational data, that the new model data for model integration initialization (analysis) fits best to the latest model data and the observational data as well. Therefore, model errors can be already reduced before the model integration. In this contribution, the results of an impact study are presented. A so-called OSSE (Observation Simulation System Experiment) is performed using the convective-resoluted COSMO-DE model of the German Weather Service and a 4D-DA technique, a Newtonian relaxation method also called nudging. Starting from a nature run (treated as the truth), conventional observations and artificial wind observations at hub height are generated. In a control run, the basic model setup of the nature run is slightly perturbed to drag the model away from the beforehand generated truth and a free forecast is computed based on the analysis using only conventional

  20. Interpreting Climate Model Projections of Extreme Weather Events for Decision Makers

    Science.gov (United States)

    Vavrus, S. J.; Notaro, M.

    2014-12-01

    The proliferation of output from climate model ensembles, such as CMIP3 and CMIP5, has greatly expanded access to future projections, but there is no accepted blueprint for how this data should be interpreted. Decision makers are thus faced with difficult questions when trying to utilize such information: How reliable are the multi-model mean projections? How should the changes simulated by outlier models be treated? How can raw projections of temperature and precipitation be translated into probabilities? The multi-model average is often regarded as the most accurate single estimate of future conditions, but higher-order moments representing the variance and skewness of the distribution of projections provide important information about uncertainty. We have analyzed a set of statistically downscaled climate model projections from the CMIP3 archive to conduct an assessment of extreme weather events at a level designed to be relevant for decision makers. Our analysis uses the distribution of 13 GCM projections to derive the inter-model standard deviation (and coefficient of variation, COV), skewness, and percentile ranges for simulated changes in extreme heat, cold, and precipitation during the middle and late 21st century for the A1B emissions scenario. These metrics help to establish the overall confidence level across the entire range of projections (via the inter-model COV), relative confidence in the simulated high-end versus low-end changes (via skewness), and probabilistic uncertainty bounds derived from a bootstrapping technique. Over our analysis domain centered on the United States Midwest, some primary findings include: (1) Greater confidence in projections of less extreme cold than more extreme heat and intense precipitation, (2) Greater confidence in the low-end than high-end projections of extreme heat, and (3) Higher spatial and temporal variability in the confidence of projected increases of heavy precipitation. In addition, our bootstrapping

  1. 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.

  2. Development of weather based rice yellow stem borer prediction model for the Cauvery command rice areas, Karnataka, India

    Directory of Open Access Journals (Sweden)

    N.R. Prasannakumar

    2015-12-01

    Full Text Available Relationship of weather parameters viz., maximum temperature (Tmax, °C, minimum temperature (Tmin, °C, rainfall (RF, mm, morning relative humidity (RH1, %, evening humidity (RH2, %, and sunshine hours (SSH, during seven years at Mandya (Karnataka was individually explored with peaks of rice yellow stem borer (YSB Scirpophaga incertulas (Walker light trap catches. The peaks of YSB trap catches exhibited significant correlation with Tmax of October 3rd week, Tmin of November 1st week, RF of October 2nd week, RH1 of November 4th and RH2 of November 1st week, and SSH of October 4th week. Weather-based prediction model for YSB was developed by regressing peaks of YSB light trap catches on mean values of different weather parameters of aforesaid weeks. Of the weather parameters, only Tmin, RF, and RH1 were found to be relevant through stepwise regression. The model was validated satisfactorily through 8-year independent data on weather parameters and YSB light trap catch peaks (R2 = 0.90, p < 0.0002.

  3. 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

  4. 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.

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

    Science.gov (United States)

    El-Samra, R.; Bou-Zeid, E.; Bangalath, H. K.; Stenchikov, G.; El-Fadel, M.

    2017-02-01

    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.

  6. 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)

  7. Seepage weathering impacts on erosivity of arid stream banks: A new conceptual model

    Science.gov (United States)

    Nachshon, Uri

    2016-05-01

    Field observations have indicated the formation of horizontal, pipe shape cavities, along gully and dry stream channel banks in the semi-arid region of the northern Negev Desert, Israel. Piping is a well-known phenomenon in humid regions due to subsurface water flow and seepage weathering. However, in dry environments where rain events are scarce and subsurface water flow is rare, it is proposed here that capillary flow of saline water in the vadose zone leads to similar processes. It is suggested that where saline and shallow ground water persists, capillary flow may result in salt accumulation and precipitation at the top of the capillary fringe, consequently rendering this zone to be more susceptible to erosion. A conceptual model is presented and field observations, laboratory experiments, and a physically-based model are used to prove the feasibility of the proposed conceptual model and to explain why salts accumulate at the top of the capillary fringe, even though evaporation acts all along the vertical stream channel or gully banks. It is suggested that the low evaporative flux, in comparison to the liquid water flux, disables salt accumulation along the profile to the top of the capillary fringe where the liquid water flux is minimal. The presented findings strengthen the conceptual model, but thorough field studies are needed to estimate the impact of the proposed mechanism on erosion processes on a field scale.

  8. Impact of Hybrid Intelligent Computing in Identifying Constructive Weather Parameters for Modeling Effective Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    M. Sudha

    2015-12-01

    Full Text Available Uncertain atmosphere is a prevalent factor affecting the existing prediction approaches. Rough set and fuzzy set theories as proposed by Pawlak and Zadeh have become an effective tool for handling vagueness and fuzziness in the real world scenarios. This research work describes the impact of Hybrid Intelligent System (HIS for strategic decision support in meteorology. In this research a novel exhaustive search based Rough set reduct Selection using Genetic Algorithm (RSGA is introduced to identify the significant input feature subset. The proposed model could identify the most effective weather parameters efficiently than other existing input techniques. In the model evaluation phase two adaptive techniques were constructed and investigated. The proposed Artificial Neural Network based on Back Propagation learning (ANN-BP and Adaptive Neuro Fuzzy Inference System (ANFIS was compared with existing Fuzzy Unordered Rule Induction Algorithm (FURIA, Structural Learning Algorithm on Vague Environment (SLAVE and Particle Swarm OPtimization (PSO. The proposed rainfall prediction models outperformed when trained with the input generated using RSGA. A meticulous comparison of the performance indicates ANN-BP model as a suitable HIS for effective rainfall prediction. The ANN-BP achieved 97.46% accuracy with a nominal misclassification rate of 0.0254 %.

  9. 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...

  10. Space weather circulation model of plasma clouds as background radiation medium of space environment.

    Science.gov (United States)

    Kalu, A. E.

    A model for Space Weather (SW) Circulation with Plasma Clouds as background radiation medium of Space Environment has been proposed and discussed. Major characteristics of the model are outlined and the model assumes a baroclinic Space Environment in view of observed pronounced horizontal electron temperature gradient with prevailing weak vertical temperature gradient. The primary objective of the study is to be able to monitor and realistically predict on real- or near real-time SW and Space Storms (SWS) affecting human economic systems on Earth as well as the safety and Physiologic comfort of human payload in Space Environment in relation to planned increase in human space flights especially with reference to the ISS Space Shuttle Taxi (ISST) Programme and other prolonged deep Space Missions. Although considerable discussions are now available in the literature on SW issues, routine Meteorological operational applications of SW forecast data and information for Space Environment are still yet to receive adequate attention. The paper attempts to fill this gap in the literature of SW. The paper examines the sensitivity and variability in 3-D continuum of Plasmas in response to solar radiation inputs into the magnetosphere under disturbed Sun condition. Specifically, the presence of plasma clouds in the form of Coronal Mass Ejections (CMEs) is stressed as a major source of danger to Space crews, spacecraft instrumentation and architecture charging problems as well as impacts on numerous radiation - sensitive human economic systems on Earth. Finally, the paper considers the application of model results in the form of effective monitoring of each of the two major phases of manned Spaceflights - take-off and re-entry phases where all-time assessment of spacecraft transient ambient micro-incabin and outside Space Environment is vital for all manned Spaceflights as recently evidenced by the loss of vital information during take-off of the February 1, 2003 US Columbia

  11. Tropospheric delay parameters from numerical weather models for multi-GNSS precise positioning

    Science.gov (United States)

    Lu, Cuixian; Zus, Florian; Ge, Maorong; Heinkelmann, Robert; Dick, Galina; Wickert, Jens; Schuh, Harald

    2016-12-01

    The recent dramatic development of multi-GNSS (Global Navigation Satellite System) constellations brings great opportunities and potential for more enhanced precise positioning, navigation, timing, and other applications. Significant improvement on positioning accuracy, reliability, as well as convergence time with the multi-GNSS fusion can be observed in comparison with the single-system processing like GPS (Global Positioning System). In this study, we develop a numerical weather model (NWM)-constrained precise point positioning (PPP) processing system to improve the multi-GNSS precise positioning. Tropospheric delay parameters which are derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis are applied to the multi-GNSS PPP, a combination of four systems: GPS, GLONASS, Galileo, and BeiDou. Observations from stations of the IGS (International GNSS Service) Multi-GNSS Experiments (MGEX) network are processed, with both the standard multi-GNSS PPP and the developed NWM-constrained multi-GNSS PPP processing. The high quality and accuracy of the tropospheric delay parameters derived from ECMWF are demonstrated through comparison and validation with the IGS final tropospheric delay products. Compared to the standard PPP solution, the convergence time is shortened by 20.0, 32.0, and 25.0 % for the north, east, and vertical components, respectively, with the NWM-constrained PPP solution. The positioning accuracy also benefits from the NWM-constrained PPP solution, which was improved by 2.5, 12.1, and 18.7 % for the north, east, and vertical components, respectively.

  12. Creating long-term weather data from thin air for crop simulation modeling

    NARCIS (Netherlands)

    Wart, Van Justin; Grassini, Patricio; Yang, Haishun; Claessens, Lieven; Jarvis, Andrew; Cassman, Kenneth G.

    2015-01-01

    Simulating crop yield and yield variability requires long-term, high-quality daily weather data, including solar radiation, maximum (Tmax) and minimum temperature (Tmin), and precipitation. In many regions, however, daily weather data of sufficient quality and duration are not available. To overcome

  13. Creating long-term weather data from thin air for crop simulation modeling

    NARCIS (Netherlands)

    Wart, Van Justin; Grassini, Patricio; Yang, Haishun; Claessens, Lieven; Jarvis, Andrew; Cassman, Kenneth G.

    2015-01-01

    Simulating crop yield and yield variability requires long-term, high-quality daily weather data, including solar radiation, maximum (Tmax) and minimum temperature (Tmin), and precipitation. In many regions, however, daily weather data of sufficient quality and duration are not available. To overcome

  14. Assimilation of Sentinel-1 estimates of Precipitable Water Vapor (PWV) into a Numerical Weather Model for a more accurate forecast of extreme weather events

    Science.gov (United States)

    Mateus, Pedro; Nico, Giovanni; Catalao, Joao

    2017-04-01

    In the last two decades, SAR interferometry has been used to obtain maps of Precipitable Water Vapor (PWV).This maps are characterized by their high spatial resolution when compared to the currently available PWV measurements (e.g. GNSS, radiometers or radiosondes). Several previous works have shown that assimilating PWV values, mainly derived from GNSS observations, into Numerical Weather Models (NWMs) can significantly improve rainfall predictions.It is noteworthy that the PWV-derived from GNSS observations have a high temporal resolution but a low spatialone. In addition, there are many regions without any GNSS stations, where temporal and spatial distribution of PWV areonly available through satellite measurements. The first attempt to assimilate InSAR-derived maps of PWV (InSAR-PWV) into a NWM was made by Pichelli et al. [1].They used InSAR-PWV maps obtained from ENVISAT-ASAR images and the mesoscale weather prediction model MM5 over the city of Rome, Italy. The statistical indices show that the InSAR-PWVdata assimilation improves the forecast of weak to moderateprecipitation (model over the city of Lisbon, Portugal, during a light rain event not forecast by the model.Results showed that after data assimilation, there is a bias correction of the PWV field and an improvement in the forecast of the weakto moderate rainfall up to 9 h after the assimilation time. We used, for the first time, the Weather Research and Forecast Data Assimilation (WRFDA) model, at micro-scale resolutions (3 km), over the Iberian Peninsula (focusing on the southern region of Spain) and during a convective cell associated with a local heavy rainfall event, to study the impact of assimilation PWV maps obtained from SAR interferometric phase calculated using images acquired by the Sentinel-1 satellite. It's worth noting that, in this case, the model without assimilation PWV maps fails to reproduce the amount and the region of heavy rainfall. The assimilation of InSAR-PWV maps with high

  15. The Transfer Function Model as a Tool to Study and Describe Space Weather Phenomena

    Science.gov (United States)

    Porter, Hayden S.; Mayr, Hans G.; Bhartia, P. K. (Technical Monitor)

    2001-01-01

    The Transfer Function Model (TFM) is a semi-analytical, linear model that is designed especially to describe thermospheric perturbations associated with magnetic storms and substorm. activity. It is a multi-constituent model (N2, O, He H, Ar) that accounts for wind induced diffusion, which significantly affects not only the composition and mass density but also the temperature and wind fields. Because the TFM adopts a semianalytic approach in which the geometry and temporal dependencies of the driving sources are removed through the use of height-integrated Green's functions, it provides physical insight into the essential properties of processes being considered, which are uncluttered by the accidental complexities that arise from particular source geometrie and time dependences. Extending from the ground to 700 km, the TFM eliminates spurious effects due to arbitrarily chosen boundary conditions. A database of transfer functions, computed only once, can be used to synthesize a wide range of spatial and temporal sources dependencies. The response synthesis can be performed quickly in real-time using only limited computing capabilities. These features make the TFM unique among global dynamical models. Given these desirable properties, a version of the TFM has been developed for personal computers (PC) using advanced platform-independent 3D visualization capabilities. We demonstrate the model capabilities with simulations for different auroral sources, including the response of ducted gravity waves modes that propagate around the globe. The thermospheric response is found to depend strongly on the spatial and temporal frequency spectra of the storm. Such varied behavior is difficult to describe in statistical empirical models. To improve the capability of space weather prediction, the TFM thus could be grafted naturally onto existing statistical models using data assimilation.

  16. Investigating Massive Dust Events Using a Coupled Weather-Chemistry Model

    Science.gov (United States)

    Raman, A.; Arellano, A. F.

    2012-12-01

    Prediction of local to regional scale dust events is challenging due to the complex nature of key processes driving emission, transport, and deposition of mineral dust. In particular, it is difficult to map precisely the sources of mineral dust across heterogeneous land surface properties and land-use changes. This is especially true for Arizona haboobs. These dust storm events are typically driven by thunderstorms and down-bursts over arid regions generating high atmospheric loading of dust in the order of hundreds to thousands of microgram per cubic meter. Modeling and prediction of these events are further complicated by the limitations in satellite-derived and in-situ measurements of dust and related geophysical variables. Here, we investigate the capability of a coupled weather-chemistry model in predicting Arizona haboobs. In particular, this research focuses on the simulation of July 5, 2011 Phoenix haboob using Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and Goddard Chemistry Aerosol Radiation and Transport Model (GOCART) dust scheme. We evaluate the ability of WRF-Chem in simulating the haboob using satellite retrievals of aerosol extinction properties and mass concentrations from Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) and high resolution SEVIRI false color dust product, in conjunction with in-situ PM10 and PM2.5 measurements. The study uses a nested modeling domain covering Utah, California and Arizona at a horizontal resolution of 5.4 km (outer) and 1.8 km (inner). Boundary conditions for the model are obtained from NOAA Global Forecasting System six-hourly forecast. We present results illustrating the key features of the haboobs, such as the cold pools and surface wind speeds driving the horizontal and vertical structure of the dust, as well as the patterns of dust transport and deposition. Although the spatio-temporal patterns of the haboob

  17. Can Agrometeorological Indices of Adverse Weather Conditions Help to Improve Yield Prediction by Crop Models?

    Directory of Open Access Journals (Sweden)

    Branislava Lalić

    2014-12-01

    Full Text Available The impact of adverse weather conditions (AWCs on crop production is random in both time and space and depends on factors such as severity, previous agrometeorological conditions, and plant vulnerability at a specific crop development stage. Any exclusion or improper treatment of any of these factors can cause crop models to produce significant under- or overestimates of yield. The analysis presented in this paper focuses on a range of agrometeorological indices (AMI related to AWCs that might affect real yield as well as simulated yield. For this purpose, the analysis addressed four indicators of extreme temperatures and three indicators of dry conditions during the growth period of maize and winter wheat in Austria, Croatia, Serbia, Slovakia, and Sweden. It is shown that increases in the number and intensity of AWCs cannot be unambiguously associated with increased deviations in simulated yields. The identified correlations indicate an increase in modeling uncertainty. This finding represents important information for the crop modeling community. Additionally, it opens a window of opportunity for a statistical (“event scenario” approach based on correlations between agrometeorological indices of AWCs and crop yield data series. This approach can provide scenarios for certain locations, crop types, and AWC patterns and, therefore, improve yield forecasting in the presence of AWCs.

  18. 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.

  19. 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.

  20. 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.

  1. Predictive zoning of rice stem borer damage in southern India through spatial interpolation of weather-based models.

    Science.gov (United States)

    Reji, G; Chander, Subhash; Kamble, Kalpana

    2014-09-01

    Rice stem borer is an important insect pest causing severe damage to rice crop in India. The relationship between weather parameters such as maximum (T(max)) and minimum temperature (T(min)), morning (RH1) and afternoon relative humidity (RH2) and the severity of stem borer damage (SB) were studied. Multiple linear regression analysis was used for formulating pest-weather models at three sites in southern India namely, Warangal, Coimbatore and Pattambi as SB = -66.849 + 2.102 T(max) + 0.095 RH1, SB = 156.518 - 3.509 T(min) - 0.785 RH1 and SB = 43.483 - 0.418 T(min) - 0.283 RH1 respectively. The pest damage predicted using the model at three sites did not significantly differ from the observed damage (t = 0.442; p > 0.05). The range of weather parameters favourable for stem borer damage at each site were also predicted using the models. Geospatial interpolation (kriging) of the pest-weather models were carried out to predict the zones of stem borer damage in southern India. Maps showing areas with high, medium and low risk of stem borer damage were prepared using geographical information system. The risk maps of rice stem borer would be useful in devising management strategies for the pest in the region.

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

    Science.gov (United States)

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

    2011-05-01

    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.

  3. Evaluating weather research and forecasting (WRF) model predictions of turbulent flow parameters in a dry convective boundary layer

    NARCIS (Netherlands)

    Gibbs, J.A.; Fedorovich, E.; Eijk, A.M.J. van

    2011-01-01

    Weather Research and Forecasting (WRF) model predictions using different boundary layer schemes and horizontal grid spacings were compared with observational and numerical large-eddy simulation data for conditions corresponding to a dry atmospheric convective boundary layer (CBL) over the southern

  4. Investigation of riming within mixed-phase stratiform clouds using Weather Research and Forecasting (WRF) model

    Science.gov (United States)

    Hou, Tuanjie; Lei, Hengchi; Yang, Jiefan; Hu, Zhaoxia; Feng, Qiujuan

    2016-09-01

    In this study, we investigated stratiform precipitation associated with an upper-level westerly trough and a cold front over northern China between 30 Apr. and 1 May 2009. We employed the Weather Research and Forecasting (WRF) model (version 3.4.1) to perform high-resolution numerical simulations of rainfall. We also conducted simulations with two microphysics schemes and sensitivity experiments without riming of snow and changing cloud droplet number concentrations (CDNCs) to determine the effect of snow riming on cloud structure and precipitation. Then we compared our results with CloudSat, Doppler radar and rain gauge observations. The comparison with the Doppler radar observations suggested that the WRF model was quite successful in capturing the timing and location of the stratiform precipitation region. Further comparisons with the CloudSat retrievals suggested that both microphysics schemes overestimated ice and liquid water contents. The sensitivity experiments without riming of snow suggested that the presence or absence of riming significantly influenced the precipitation distribution, but only slightly affected total accumulated precipitation. Without riming of snow, the changes of updrafts from the two microphysics schemes were different due to a different consideration of ice particle capacitance and latent heat effect of riming on deposition. While sensitivity experiments with three different CDNC values of 100, 250 and 1000 cm- 3 suggested variations in snow riming rates, changing CDNC had little impact on precipitation.

  5. Numerical weather prediction models and SAR interferometry: synergic use for meteorological and INSAR applications

    Science.gov (United States)

    Pierdicca, Nazzareno; Rocca, Fabio; Perissin, Daniele; Ferretti, Rossella; Pichelli, Emanuela; Rommen, Bjorn; Cimini, Nico

    2011-11-01

    Spaceborne Interferometric Synthetic Aperture Radar (InSAR) is a well established technique useful in many land applications, such as landslide monitoring and digital elevation model extraction. One of its major limitation is the atmospheric effect, and in particular the high water vapour spatial and temporal variability which introduces an unknown delay in the signal propagation. However, the sensitivity of SAR interferometric phase to atmospheric conditions could in principle be exploited and InSAR could become in certain conditions a tool to monitor the atmosphere, as it happens with GPS receiver networks. This paper describes a novel attempt to assimilate InSAR derived information on the atmosphere, based on the Permanent Scatterer multipass technique, into a numerical weather forecast model. The methodology is summarised and the very preliminary results regarding the forecast of a precipitation event in Central Italy are analysed. The work was done in the framework of an ESA funded project devoted to the mapping of the water vapour with the aim to mitigate its effect for InSAR applications.

  6. 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.

  7. Evaluation of numerical weather prediction model precipitation forecasts for short-term streamflow forecasting purpose

    Directory of Open Access Journals (Sweden)

    D. L. Shrestha

    2013-05-01

    Full Text Available The quality of precipitation forecasts from four Numerical Weather Prediction (NWP models is evaluated over the Ovens catchment in Southeast Australia. Precipitation forecasts are compared with observed precipitation at point and catchment scales and at different temporal resolutions. The four models evaluated are the Australian Community Climate Earth-System Simulator (ACCESS including ACCESS-G with a 80 km resolution, ACCESS-R 37.5 km, ACCESS-A 12 km, and ACCESS-VT 5 km. The skill of the NWP precipitation forecasts varies considerably between rain gauging stations. In general, high spatial resolution (ACCESS-A and ACCESS-VT and regional (ACCESS-R NWP models overestimate precipitation in dry, low elevation areas and underestimate in wet, high elevation areas. The global model (ACCESS-G consistently underestimates the precipitation at all stations and the bias increases with station elevation. The skill varies with forecast lead time and, in general, it decreases with the increasing lead time. When evaluated at finer spatial and temporal resolution (e.g. 5 km, hourly, the precipitation forecasts appear to have very little skill. There is moderate skill at short lead times when the forecasts are averaged up to daily and/or catchment scale. The precipitation forecasts fail to produce a diurnal cycle shown in observed precipitation. Significant sampling uncertainty in the skill scores suggests that more data are required to get a reliable evaluation of the forecasts. The non-smooth decay of skill with forecast lead time can be attributed to diurnal cycle in the observation and sampling uncertainty. Future work is planned to assess the benefits of using the NWP rainfall forecasts for short-term streamflow forecasting. Our findings here suggest that it is necessary to remove the systematic biases in rainfall forecasts, particularly those from low resolution models, before the rainfall forecasts can be used for streamflow forecasting.

  8. Geospatial Predictive Modelling for Climate Mapping of Selected Severe Weather Phenomena Over Poland: A Methodological Approach

    Science.gov (United States)

    Walawender, Ewelina; Walawender, Jakub P.; Ustrnul, Zbigniew

    2017-02-01

    The main purpose of the study is to introduce methods for mapping the spatial distribution of the occurrence of selected atmospheric phenomena (thunderstorms, fog, glaze and rime) over Poland from 1966 to 2010 (45 years). Limited in situ observations as well the discontinuous and location-dependent nature of these phenomena make traditional interpolation inappropriate. Spatially continuous maps were created with the use of geospatial predictive modelling techniques. For each given phenomenon, an algorithm identifying its favourable meteorological and environmental conditions was created on the basis of observations recorded at 61 weather stations in Poland. Annual frequency maps presenting the probability of a day with a thunderstorm, fog, glaze or rime were created with the use of a modelled, gridded dataset by implementing predefined algorithms. Relevant explanatory variables were derived from NCEP/NCAR reanalysis and downscaled with the use of a Regional Climate Model. The resulting maps of favourable meteorological conditions were found to be valuable and representative on the country scale but at different correlation ( r) strength against in situ data (from r = 0.84 for thunderstorms to r = 0.15 for fog). A weak correlation between gridded estimates of fog occurrence and observations data indicated the very local nature of this phenomenon. For this reason, additional environmental predictors of fog occurrence were also examined. Topographic parameters derived from the SRTM elevation model and reclassified CORINE Land Cover data were used as the external, explanatory variables for the multiple linear regression kriging used to obtain the final map. The regression model explained 89 % of annual frequency of fog variability in the study area. Regression residuals were interpolated via simple kriging.

  9. 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.

  10. Weather Conditions, Weather Information and Car Crashes

    Directory of Open Access Journals (Sweden)

    Adriaan Perrels

    2015-11-01

    Full Text Available Road traffic safety is the result of a complex interaction of factors, and causes behind road vehicle crashes require different measures to reduce their impacts. This study assesses how strongly the variation in daily winter crash rates associates with weather conditions in Finland. This is done by illustrating trends and spatiotemporal variation in the crash rates, by showing how a GIS application can evidence the association between temporary rises in regional crash rates and the occurrence of bad weather, and with a regression model on crash rate sensitivity to adverse weather conditions. The analysis indicates that a base rate of crashes depending on non-weather factors exists, and some combinations of extreme weather conditions are able to substantially push up crash rates on days with bad weather. Some spatial causation factors, such as variation of geophysical characteristics causing systematic differences in the distributions of weather variables, exist. Yet, even in winter, non-spatial factors are normally more significant. GIS data can support optimal deployment of rescue services and enhance in-depth quantitative analysis by helping to identify the most appropriate spatial and temporal resolutions. However, the supportive role of GIS should not be inferred as existence of highly significant spatial causation.

  11. An Extended Objective Evaluation of the 29-km Eta Model for Weather Support to the United States Space Program

    Science.gov (United States)

    Nutter, Paul; Manobianco, John

    1998-01-01

    This report describes the Applied Meteorology Unit's objective verification of the National Centers for Environmental Prediction 29-km eta model during separate warm and cool season periods from May 1996 through January 1998. The verification of surface and upper-air point forecasts was performed at three selected stations important for 45th Weather Squadron, Spaceflight Meteorology Group, and National Weather Service, Melbourne operational weather concerns. The statistical evaluation identified model biases that may result from inadequate parameterization of physical processes. Since model biases are relatively small compared to the random error component, most of the total model error results from day-to-day variability in the forecasts and/or observations. To some extent, these nonsystematic errors reflect the variability in point observations that sample spatial and temporal scales of atmospheric phenomena that cannot be resolved by the model. On average, Meso-Eta point forecasts provide useful guidance for predicting the evolution of the larger scale environment. A more substantial challenge facing model users in real time is the discrimination of nonsystematic errors that tend to inflate the total forecast error. It is important that model users maintain awareness of ongoing model changes. Such changes are likely to modify the basic error characteristics, particularly near the surface.

  12. 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.

  13. 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.

  14. From short-range barotropic modelling to extended-range global weather prediction: a 40-year perspective

    Science.gov (United States)

    Bengtsson, Lennart

    1999-02-01

    At the end of the 20th century, we can look back on a spectacular development of numerical weather prediction, which has, practically uninterrupted, been going on since the middle of the century. High-resolution predictions for more than a week ahead for any part of the globe are now routinely produced and anyone with an Internet connection can access many of these forecasts for anywhere in the world. Extended predictions for several seasons ahead are also being done — the latest El Niño event in 1997/1998 is an example of such a successful prediction. The great achievement is due to a number of factors including the progress in computational technology and the establishment of global observing systems, combined with a systematic research program with an overall strategy towards building comprehensive prediction systems for climate and weather. In this article, I will discuss the different evolutionary steps in this development and the way new scientific ideas have contributed to efficiently explore the computing power and in using observations from new types of observing systems. Weather prediction is not an exact science due to unavoidable errors in initial data and in the models. To quantify the reliability of a forecast is therefore essential and probably more so the longer the forecasts are. Ensemble prediction is thus a new and important concept in weather and climate prediction, which I believe will become a routine aspect of weather prediction in the future. The limit between weather and climate prediction is becoming more and more diffuse and in the final part of this article I will outline the way I think development may proceed in the future.

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

    African Journals Online (AJOL)

    drinie

    2002-07-03

    Jul 3, 2002 ... Department of Geography, Geoinformatics and Meteorology, University of Pretoria, ... weather systems are often associated with heavy rainfall and flooding ..... average 500 to 300 hPa temperatures in a tropical circulation.

  16. 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 objective of the present study was to compare the performance of seven different, widely applied crop models in predicting heat and drought stress effects. The study was part of a recent suite of model inter-comparisons initiated at European level and constitutes a component that has been...... lacking in the analysis of sources of uncertainties in crop models used to study the impacts of climate change. There was a specific focus on the sensitivity of models for winter wheat and maize to extreme weather conditions (heat and drought) during the short but critical period of 2 weeks after...... or minimum tillage. Since no comprehensive field experimental data sets were available, a relative comparison of simulated grain yields and soil moisture contents under defined weather scenarios with modified temperatures and precipitation was performed for a 2-week period after flowering. The results may...

  17. 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.

  18. A landscape in three biospheres: biological rock weathering in a model ecosystem

    Science.gov (United States)

    Presler, J. K.

    2012-12-01

    Biological rock weathering is the process by which life breaks down minerals into forms that are readily available for creation of an ecosystem. In order to test how microbes, plants and mycorrhizal communities interact with bedrock to initiate a primary ecosystem that will eventually lead to soil formation, we developed a modular experiment in the desert biome of Biosphere-2. In this presentation we present selected phases in the development of the experimental setup. Briefly, we aimed to replicate a large-scale primordial landscape in a closed, mesocosm system involving six carefully designed, identical chambers, each containing 48 experimental columns, 30cm long. The rocks used, i.e. basalt, rhyolite, granite and schist, represent four prevalent rock types in the natural landscape. The biotic communities are represented by combinations of rock microbial communities, plants and their associated mycorrhizae. Bacterial inoculum was optimized for each rock type. Each model was created to remain completely separated from outside influence. We expect that this experiment will provide crucial knowledge about primary interactions between rock and biota on Earth. Experimental Modules

  19. 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

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

    Science.gov (United States)

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

    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.

  1. Climate Impacts Mid-1800's Deforestation in New England using the Weather, Research, and Forecasting Model

    Science.gov (United States)

    Burakowski, E. A.; Chen, M.; Birkel, S. D.; Wake, C. P.; Dibb, J. E.

    2012-12-01

    When colonists arrived in the New England region of the United States (US) in the 1600's, more than 90% of land area was forested. By the mid-1800's, half of the land area was deforested having been cleared extensively for timber, pasture, and to heat homes. Today, New Hampshire is one of the most forested states in the US, yet little is known about the local climate impacts resulting from reforestation. We hypothesize that the removal of forests in 1850 had a strong impact on wintertime climate through changes in surface albedo, roughness length, and other biogeophysical surface properties. This study investigates the climate impacts of historical deforestation on New England winter climate using the Weather, Research, and Forecasting model. The WRF simulations presented here utilize a triple-nested approach, with the innermost 4-km domain centered on the New England states for two land cover scenarios, (2) an historical 1850 deforested scenario derived from the History Database of the Global Environment (HYDE3) land cover dataset and (2) present-day reforested scenario derived from MODerate Resolution Imaging Spectroradiometer (MODIS) land cover data. ERA-Interim lateral boundary conditions are used to drive the model and results are compared for an above average snowfall winter (November 2008 through April 2009) and a below-average snowfall winter (November 2001 through April 2002). Simulations are ongoing but analysis of observational data suggests that nocturnal cooling is a dominant response to deforestation compared to forested areas. The results from the WRF modeling efforts in this study will help inform future land use decisions in the future.

  2. 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.

  3. 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.

  4. Models of weather effects on noise temperature and attenuation for Ka- and X-band telemetry performance analysis

    Science.gov (United States)

    Slobin, S. D.

    1987-02-01

    Models that show the effects of weather on noise temperature and attenuation of deep space telemetry signals received by the Deep Space Network (DSN) at Ka- and X-band (32 and 8.5 GHz) are developed. These models were used to compare the performance of telemetry links at these two frequencies. The models build on an earlier 1982 model that used three months of water vapor radiometer measurements (31.4 GHz) at Goldstone, augmented with one year of radiosonde measurements made at Edwards Air Force Base. This 1986 model accounts for annual variations of rainfall and extends to a model for Canberra, Australia, and Madrid, Spain. The results show, for example, that at Ka-band, 30 degrees elevation angle, Goldstone weather adds less than 23 + or - 2 K to the system temperature 80% of the time, while Canberra or Madrid weather adds less than 32 + or - 5 K 80% of the time. At X-band, the comparable numbers are 5.1 + or - 0.2 K and 5.7 + or - 0.4 K. A simple analysis shows a substantial telemetry system signal-to-noise ratio advantage when operating at Ka-band compared to X-band.

  5. Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study

    Science.gov (United States)

    Zhu, Dehua; Echendu, Shirley; Xuan, Yunqing; Webster, Mike; Cluckie, Ian

    2016-11-01

    Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2-3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part.

  6. Atmospheric Test Models and Numerical Experiments for the Simulation of the Global Distributions of Weather Data Transponders III. Horizontal Distributions

    Energy Technology Data Exchange (ETDEWEB)

    Molenkamp, C.R.; Grossman, A.

    1999-12-20

    A network of small balloon-borne transponders which gather very high resolution wind and temperature data for use by modern numerical weather predication models has been proposed to improve the reliability of long-range weather forecasts. The global distribution of an array of such transponders is simulated using LLNL's atmospheric parcel transport model (GRANTOUR) with winds supplied by two different general circulation models. An initial study used winds from CCM3 with a horizontal resolution of about 3 degrees in latitude and longitude, and a second study used winds from NOGAPS with a 0.75 degree horizontal resolution. Results from both simulations show that reasonable global coverage can be attained by releasing balloons from an appropriate set of launch sites.

  7. Resolving the Multi-scale Behavior of Geochemical Weathering in the Critical Zone Using High Resolution Hydro-geochemical Models

    Science.gov (United States)

    Pandey, S.; Rajaram, H.

    2015-12-01

    This work investigates hydrologic and geochemical interactions in the Critical Zone (CZ) using high-resolution reactive transport modeling. Reactive transport models can be used to predict the response of geochemical weathering and solute fluxes in the CZ to changes in a dynamic environment, such as those pertaining to human activities and climate change in recent years. The scales of hydrology and geochemistry in the CZ range from days to eons in time and centimeters to kilometers in space. Here, we present results of a multi-dimensional, multi-scale hydro-geochemical model to investigate the role of subsurface heterogeneity on the formation of mineral weathering fronts in the CZ, which requires consideration of many of these spatio-temporal scales. The model is implemented using the reactive transport code PFLOTRAN, an open source subsurface flow and reactive transport code that utilizes parallelization over multiple processing nodes and provides a strong framework for simulating weathering in the CZ. The model is set up to simulate weathering dynamics in the mountainous catchments representative of the Colorado Front Range. Model parameters were constrained based on hydrologic, geochemical, and geophysical observations from the Boulder Creek Critical Zone Observatory (BcCZO). Simulations were performed in fractured rock systems and compared with systems of heterogeneous and homogeneous permeability fields. Tracer simulations revealed that the mean residence time of solutes was drastically accelerated as fracture density increased. In simulations that include mineral reactions, distinct signatures of transport limitations on weathering arose when discrete flow paths were included. This transport limitation was related to both advective and diffusive processes in the highly heterogeneous systems (i.e. fractured media and correlated random permeability fields with σlnk > 3). The well-known time-dependence of mineral weathering rates was found to be the most

  8. 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.

  9. Investigating the influence of subsurface heterogeneity on chemical weathering in the critical zone using high resolution reactive transport models

    Science.gov (United States)

    Pandey, S.; Rajaram, H.

    2014-12-01

    The critical zone (CZ) represents a major life-sustaining realm of the terrestrial surface. The processes controlling the development and transformation of the CZ are important to continued health of the planet as human influence continues to grow. The CZ encompasses the shallow subsurface, a region of reaction, unsaturated flow, and transport. Chemical weathering in the subsurface is one of the important processes involved in the formation and functioning of the CZ. We present two case studies of reactive transport modeling to investigate the influence of subsurface heterogeneity and unsaturated flow on chemical weathering processes in the CZ. The model is implemented using the reactive transport code PFLOTRAN. Heterogeneity in subsurface flow is represented using multiple realizations of conductive fracture networks in a hillslope cross-section. The first case study is motivated by observations at the Boulder Creek Critical Zone Observatory (BCCZO) including extensive hydrologic and geochemical datasets. The simulations show that fractures greatly enhance weathering as compared to a homogeneous porous medium. Simulations of north-facing slope hydrology with prolonged snowmelt pulses also increases weathering rates, showing the importance of slope aspect on weathering intensity. Recent work elucidates deteriorating water quality caused by climate change in the CZ of watersheds where acid rock drainage (ARD) occurs. The more complex reactions of ARD require a customized kinetic reaction module with PFLOTRAN. The second case study explores the mechanisms by which changes in hydrologic forcing, air and ground temperatures, and water table elevations influence ARD. For instance, unreacted pyrite exposed by a water table drop was shown to produce a 125% increase in annual pyrite oxidization rate, which provides one explanation for increased ARD.

  10. Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model

    Science.gov (United States)

    Molthan, Andrew L.; Jedlovec, Gary J.; Lapenta, William M.

    2008-01-01

    The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.

  11. 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

  12. 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).

  13. Two Way Coupling RAM-SCB to the Space Weather Modeling Framework

    Science.gov (United States)

    Welling, D. T.; Jordanova, V. K.; Zaharia, S. G.; Toth, G.

    2010-12-01

    The Ring current Atmosphere interaction Model with Self-Consistently calculated 3D Magnetic field (RAM-SCB) has been used to successfully study inner magnetosphere dynamics during different solar wind and magnetosphere conditions. Recently, one way coupling of RAM-SCB with the Space Weather Modeling Framework (SWMF) has been achieved to replace all data or empirical inputs with those obtained through first-principles-based codes: magnetic field and plasma flux outer boundary conditions are provided by the Block Adaptive Tree Solar wind Roe-type Upwind Scheme (BATS-R-US) MHD code, convection electric field is provided by the Ridley Ionosphere Model (RIM), and ion composition is provided by the Polar Wind Outflow Model (PWOM) combined with a multi-species MHD approach. These advances, though creating a powerful inner magnetosphere virtual laboratory, neglect the important mechanisms through which the ring current feeds back into the whole system, primarily the stretching of the magnetic field lines and shielding of the convection electric field through strong region two Field Aligned Currents (FACs). In turn, changing the magnetosphere in this way changes the evolution of the ring current. To address this shortcoming, the coupling has been expanded to include feedback from RAM-SCB to the other coupled codes: region two FACs are returned to the RIM while total plasma pressure is used to nudge the MHD solution towards the RAM-SCB values. The impacts of the two way coupling are evaluated on three levels: the global magnetospheric level, focusing on the impact on the ionosphere and the shape of the magnetosphere, the regional level, examining the impact on the development of the ring current in terms of energy density, anisotropy, and plasma distribution, and the local level to compare the new results to in-situ measurements of magnetic and electric field and plasma. The results will also be compared to past simulations using the one way coupling and no coupling

  14. Design and Evaluation of a Dynamic Programming Flight Routing Algorithm Using the Convective Weather Avoidance Model

    Science.gov (United States)

    Ng, Hok K.; Grabbe, Shon; Mukherjee, Avijit

    2010-01-01

    The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.

  15. Slope stability assessment of weathered clay by using field data and computer modelling: a case study from Budapest

    Directory of Open Access Journals (Sweden)

    P. Görög

    2007-06-01

    Full Text Available A future development site of a housing estate, an abandoned-brick yard with clayey slopes was studied in details to assess slope stability and to calculate the factor of safety. The Oligocene clay, the former raw material, is divided into two different geotechnical units in the clay pit. The lower one consists of grey impermeable clays while the upper unit is characterised by yellowish weathered clay having a limited permeability. At some localities the topmost weathered clay layers are covered by loess, and slope debris. Parts of the former pit were also used as a landfill site. The slope stability analyses were performed based on borehole information and laboratory analyses in order to provide necessary engineering geological data for further site development and urban planning. Two geotechnical codes Plaxis and Geo4 were used to model the slope failures and assess the slope stability. The aim of using two different approaches was to compare them since Plaxis uses finite elements modelling while Geo4 uses conventional calculation methods to obtain circular and polygonal slip surfaces. According to model calculations and field data, the main trigger mechanisms of landslides seem to be high pore pressure due to rainwater and small slope debris covered springs. The slip surface is located at the boundary zone of yellow weathered and grey unaltered clay. Two computer models gave very similar results; although Plaxis provides combined safety factor which is slightly more pessimistic when compared to the safety factor obtained by using Geo4.

  16. 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…

  17. 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…

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

    Directory of Open Access Journals (Sweden)

    L. Rontu

    2017-07-01

    Full Text Available 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

  19. 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

  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. 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.

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

    OpenAIRE

    Khandakar Md Habib Al Razi, Moritomi Hiroshi

    2013-01-01

    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 u...

  3. 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

  4. Modeling spatial patterns of wildfire susceptibility in southern California: Applications of MODIS remote sensing data and mesoscale numerical weather models

    Science.gov (United States)

    Schneider, Philipp

    This dissertation investigates the potential of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and mesoscale numerical weather models for mapping wildfire susceptibility in general and for improving the Fire Potential Index (FPI) in southern California in particular. The dissertation explores the use of the Visible Atmospherically Resistant Index (VARI) from MODIS data for mapping relative greenness (RG) of vegetation and subsequently for computing the FPI. VARI-based RG was validated against in situ observations of live fuel moisture. The results indicate that VARI is superior to the previously used Normalized Difference Vegetation Index (NDVI) for computing RG. FPI computed using VARI-based RG was found to outperform the traditional FPI when validated against historical fire detections using logistic regression. The study further investigates the potential of using Multiple Endmember Spectral Mixture Analysis (MESMA) on MODIS data for estimating live and dead fractions of vegetation. MESMA fractions were compared against in situ measurements and fractions derived from data of a high-resolution, hyperspectral sensor. The results show that live and dead fractions obtained from MODIS using MESMA are well correlated with the reference data. Further, FPI computed using MESMA-based green vegetation fraction in lieu of RG was validated against historical fire occurrence data. MESMA-based FPI performs at a comparable level to the traditional NDVI-based FPI, but can do so using a single MODIS image rather than an extensive remote sensing time series as required for the RG approach. Finally this dissertation explores the potential of integrating gridded wind speed data obtained from the MM5 mesoscale numerical weather model in the FPI. A new fire susceptibility index, the Wind-Adjusted Fire Potential Index (WAFPI), was introduced. It modifies the FPI algorithm by integrating normalized wind speed. Validating WAFPI against historical wildfire events using

  5. 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.

  6. Crop weather models of corn and soybeans for Agrophysical Units (APU's) in Iowa using monthly meteorological predictors

    Science.gov (United States)

    Leduc, S. (Principal Investigator)

    1982-01-01

    Models based on multiple regression were developed to estimate corn and soybean yield from weather data for agrophysical units (APU) in Iowa. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for crop reporting districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU's were selected to be more homogeneous with respect crop to production than the CRDs. The APU models are quite similar to the CRD models, similar explained variation and number of predictor variables. The APU models are to be independently evaluated and compared to the previously evaluated CRD models. That comparison should indicate the preferred model area for this application, i.e., APU or CRD.

  7. Domain-Level Assessment of the Weather Running Estimate-Nowcast (WREN) Model

    Science.gov (United States)

    2016-11-01

    Yes No No Obs-nudge rad 90,45,20 No Yes No Obs-nudge rad 120,60,20 No No Yes MYJ– PBL Scheme (modified) Yes Yes Yes WRF, sgl-moment, 5-class mp Yes...Environmental Prediction NOFDDA “no FDDA” NWP Numerical Weather Prediction PBL planetary boundary layer RH relative humidity RMSE root-mean

  8. Free Space Optical Channel Characterization and Modeling with Focus on Algeria Weather Conditions

    Directory of Open Access Journals (Sweden)

    Mehdi ROUISSAT

    2012-04-01

    Full Text Available Free-Space Optics (FSO is a wireless optical technology that enables optical transmission of data, voice and video communications through the air, up to 10 Gbps of data, based on the use of the free space (the atmosphere as transmission medium and low power lasers as light sources.Quality and performance of FSO links are generally affected by link distance and weather conditions like environmental temperature and light, sun, fog, snow, smoke, haze and rain. In this paper we study the effects of weather conditions on the performance of FSO links, taking the climate of Algeria as an example, and since there is no known analysis on the effects of weather conditions in this country, this paper offers an attempt to analyze and identify the challenges related to the deployment of FSO links under Algeria’s weather. We also present a Graphic User Interface “GUI” to provide an approximate availability estimate of an atmospheric optical link in term of probability of connection.

  9. 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...

  10. 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.

  11. Separation of convective and stratiform precipitation for a precipitation analysis of the local model of the German Weather Service

    Directory of Open Access Journals (Sweden)

    E. Reimer

    2007-04-01

    Full Text Available An improved independent precipitation data set with the horizontal resolution of 7×7 km grid over central Europe was generated (Free University of Berlin (FUB-precipitation analysis. For scale dependent evaluation of the Local model (LM of the German Weather service, the precipitation data were separated into convective and stratiform fractions. To analyse precipitation amounts an interpolation scheme is used which contains the data set of "present weather" (ww, rain gauges and cloud types from the WMO-network in hourly resolution from the year 1992 until 2004 together with satellite cloud types derived from Meteosat-7 data. The structural analyses of cloud classes from satellite data as well as clouds from the synoptic observations were used to develop a statistical interpolation procedure to build up an independent precipitation analysis in resolution corresponding to the LM grid.

  12. Urban pluvial flood prediction: a case study evaluating radar rainfall nowcasts and numerical weather prediction models as model inputs.

    Science.gov (United States)

    Thorndahl, Søren; Nielsen, Jesper Ellerbæk; Jensen, David Getreuer

    2016-12-01

    Flooding produced by high-intensive local rainfall and drainage system capacity exceedance can have severe impacts in cities. In order to prepare cities for these types of flood events - especially in the future climate - it is valuable to be able to simulate these events numerically, both historically and in real-time. There is a rather untested potential in real-time prediction of urban floods. In this paper, radar data observations with different spatial and temporal resolution, radar nowcasts of 0-2 h leadtime, and numerical weather models with leadtimes up to 24 h are used as inputs to an integrated flood and drainage systems model in order to investigate the relative difference between different inputs in predicting future floods. The system is tested on the small town of Lystrup in Denmark, which was flooded in 2012 and 2014. Results show it is possible to generate detailed flood maps in real-time with high resolution radar rainfall data, but rather limited forecast performance in predicting floods with leadtimes more than half an hour.

  13. 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

  14. 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.

  15. The DACCIWA model evaluation project: representation of the meteorology of southern West Africa in state-of-the-art weather, seasonal and climate prediction models

    Science.gov (United States)

    Kniffka, Anke; Benedetti, Angela; Knippertz, Peter; Stanelle, Tanja; Brooks, Malcolm; Deetz, Konrad; Maranan, Marlon; Rosenberg, Philip; Pante, Gregor; Allan, Richard; Hill, Peter; Adler, Bianca; Fink, Andreas; Kalthoff, Norbert; Chiu, Christine; Vogel, Bernhard; Field, Paul; Marsham, John

    2017-04-01

    DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) is an EU-funded project that aims to determine the influence of anthropogenic and natural emissions on the atmospheric composition, air quality, weather and climate over southern West Africa. DACCIWA organised a major international field campaign in June-July 2016 and involves a wide range of modelling activities. Here we report about the coordinated model evaluation performed in the framework of DACCIWA focusing on meteorological fields. This activity consists of two elements: (a) the quality of numerical weather prediction during the field campaign, (b) the ability of seasonal and climate models to represent the mean state and its variability. For the first element, the extensive observations from the main field campaign in West Africa in June-July 2016 (ground supersites, radiosondes, aircraft measurements) will be combined with conventional data (synoptic stations, satellites data from various sensors) to evaluate models against. The forecasts include operational products from centres such as the ECMWF, UK MetOffice and the German Weather Service and runs specifically conducted for the planning and the post-analysis of the field campaign using higher resolutions (e.g., WRF, COSMO). The forecast and the observations are analysed in a concerted way to assess the ability of the models to represent the southern West African weather systems and secondly to provide a comprehensive synoptic overview of the state of the atmosphere. In a second step the process will be extended to long-term modelling periods. This includes both seasonal and climate models, respectively. In this case, the observational dataset contains long-term satellite observations and station data, some of which were digitised from written records in the framework of DACCIWA. Parameter choice and spatial averaging will build directly on the weather forecasting evaluation to allow an assessment of the impact of short-term errors on

  16. Mirador - Weather

    Data.gov (United States)

    National Aeronautics and Space Administration — Earth Science data access made simple. Our weather system includes the dynamics of the atmosphere and its interaction with the oceans and land. The improvement of...

  17. 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.

  18. Realized heritability analysis of resistance to imidacloprid and cross-resistance to insecticides in Bemisia tabaci Middle-East-Asia-Minor 1 (MEAM1) in Xinjiang%新疆MEAM1烟粉虱隐种对吡虫啉的抗性遗传力分析及交互抗性测定

    Institute of Scientific and Technical Information of China (English)

    李国志; 曹骞; 段晓东; 张鑫; 马德英

    2013-01-01

    采用Tabashnik的域性状指标分析了新疆MEAM1(Middle-East-Asia-Minor l)烟粉虱隐种对吡虫啉的抗性现实遗传力(h2)和不同致死率下的抗性发展速率,同时测定了抗性种群对不同类型杀虫剂的交互抗性.结果表明,在30%~ 50%较低的选择压力下,新疆MEAM1烟粉虱隐种连续汰选8代后,对吡虫啉的抗性上升28.01倍,抗性现实遗传力h2为0.429 7.假设田间种群现实遗传力为实验室筛选估算值的1/2,即h2=0.214 9,对新疆MEAM1烟粉虱隐种对吡虫啉的抗性发展速率估算结果表明:在药剂选择压力为50%~ 60%下,若使其对吡虫啉的抗性增长10倍,则需要生长10 ~8代;而在药剂选择压力为70%~ 90%下,若使其抗性增长10倍,则仅需要生长6~4代.表明新疆MEAM1烟粉虱隐种对吡虫啉产生抗性的风险很大.交互抗性测定结果显示:抗性种群对同类型的杀虫剂吡虫清和噻虫嗪分别产生了10.78倍和4.75倍的中等至低水平交互抗性;对多杀菌素、毒死蜱、吡丙醚和高效氯氰菊酯的敏感性有所降低;对阿维菌素、氟啶虫胺腈和乙基多杀菌素等杀虫剂则无交互抗性.%The method of threshold trait analysis described by Tabashnik was used to estimate realized heritability (h2) of resistance to imidacloprid and the development rate of resistance in Bemisia tabaci Middle-East-Asia-Minor 1 (MEAM1) cryptic species in Xinjiang, and the cross-resistance of resistant population to different insecticides was detected. The results showed that under the ordinary selection pressure 30% -50% , compared with the original unselected populations, the resistance of MEAM1 to imidacloprid was developed 28. 01 times higher after 8 generations by uninterrupted selection, also, the realized heritability (h2) was 0. 429 7. Given that h2 of field population was half of those value at 0. 214 9, the risk predicting of resistance of MEAMI to imidacloprid for field population showed that

  19. Evaluation of Thompson-type trend and monthly weather data models for corn yields in Iowa, Illinois, and Indiana

    Science.gov (United States)

    French, V. (Principal Investigator)

    1982-01-01

    An evaluation was made of Thompson-Type models which use trend terms (as a surrogate for technology), meteorological variables based on monthly average temperature, and total precipitation to forecast and estimate corn yields in Iowa, Illinois, and Indiana. Pooled and unpooled Thompson-type models were compared. Neither was found to be consistently superior to the other. Yield reliability indicators show that the models are of limited use for large area yield estimation. The models are objective and consistent with scientific knowledge. Timely yield forecasts and estimates can be made during the growing season by using normals or long range weather forecasts. The models are not costly to operate and are easy to use and understand. The model standard errors of prediction do not provide a useful current measure of modeled yield reliability.

  20. Impact of horizontal resolution on prediction of tropical cyclones over Bay of Bengal using a regional weather prediction model

    Indian Academy of Sciences (India)

    M Mandal; U C Mohanty; K V J Potty; A Sarkar

    2003-03-01

    The present study is carried out to examine the performance of a regional atmospheric model in forecasting tropical cyclones over the Bay of Bengal and its sensitivity to horizontal resolution. Two cyclones, which formed over the Bay of Bengal during the years 1995 and 1997, are simulated using a regional weather prediction model with two horizontal resolutions of 165km and 55 km. The model is found to perform reasonably well towards simulation of the storms. The structure, intensity and track of the cyclones are found to be better simulated by finer resolution of the model as compared to the coarse resolution. Rainfall amount and its distribution are also found to be sensitive to the model horizontal resolution. Other important fields, viz., vertical velocity, horizontal divergence and horizontal moisture flux are also found to be sensitive to model horizontal resolution and are better simulated by the model with finer horizontal grids.

  1. 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.; Zhao, J.; Stein, R.; Duvall, T.; Fan, Y.

    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

  2. A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

    Science.gov (United States)

    Duveiller, G.; Donatelli, M.; Fumagalli, D.; Zucchini, A.; Nelson, R.; Baruth, B.

    2017-02-01

    Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure

  3. 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).

  4. Space Weather Services of Korea

    Science.gov (United States)

    Yoon, KiChang; Kim, Jae-Hun; Kim, Young Yun; Kwon, Yongki; Wi, Gwan-sik

    2016-07-01

    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).

  5. Modeling Uranium Transport in Koongarra, Australia: The Effect of a Moving Weathering Zone

    OpenAIRE

    2001-01-01

    Natural analogues are an important source of long-term data and may be viewed as naturally occurring experiments that often include processes, phenomena, and scenarios that are important to nuclear waste disposal safety assessment studies. The Koongarra uranium deposit in the Alligator Rivers region of Australia is one of the best-studied natural analogue sites. The deposit has been subjected to chemical weathering over several million years, during which many climatological, hydrological, an...

  6. Improvements of Satellite-derived High Impact Weather Rainfall over Global Oceans and Implications for NWP models

    Science.gov (United States)

    Klepp, C.; Bakan, S.; Graßl, H.

    2003-04-01

    High impact weather precipitation fields of cyclone case studies over global ocean precipitation centers are presented using the technology of the HOAPS-II (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data) data base. All case studies are compared to the Global Precipitation Climatology Project (GPCP) data set and to ECMWF numerical weather prediction output. A detailed in situ rainfall validation is presented using voluntary observing ships (VOS). Results show that only the HOAPS data base recognizes the development of frequently occurring mesoscale cyclones and gales over the North Atlantic and North Pacific ocean as observed by VOS data. In case of landfall these events cause high socio-economic impact to the society. GPCP and the ECMWF model are frequently missing these mesoscale storms. For example, the gale Lothar known as the `Christmas Storm', could have been nowcasted using the HOAPS data base. HOAPS probably allows to give high impact weather warning in the near future on a near real time basis.

  7. 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.

  8. Tracking the weathering of basalts on Mars using lithium isotope fractionation models

    Science.gov (United States)

    Fairén, Alberto G.; Losa-Adams, Elisabeth; Gil-Lozano, Carolina; Gago-Duport, Luis; Uceda, Esther R.; Squyres, Steven W.; Rodríguez, J. Alexis P.; Davila, Alfonso F.; McKay, Christopher P.

    2015-04-01

    Lithium (Li), the lightest of the alkali elements, has geochemical properties that include high aqueous solubility (Li is the most fluid mobile element) and high relative abundance in basalt-forming minerals (values ranking between 0.2 and 12 ppm). Li isotopes are particularly subject to fractionation because the two stable isotopes of lithium—7Li and 6Li—have a large relative mass difference (˜15%) that results in significant fractionation between water and solid phases. The extent of Li isotope fractionation during aqueous alteration of basalt depends on the dissolution rate of primary minerals—the source of Li—and on the precipitation kinetics, leading to formation of secondary phases. Consequently, a detailed analysis of Li isotopic ratios in both solution and secondary mineral lattices could provide clues about past Martian weathering conditions, including weathering extent, temperature, pH, supersaturation, and evaporation rate of the initial solutions in contact with basalt rocks. In this paper, we discuss ways in which Martian aqueous processes could have lead to Li isotope fractionation. We show that Li isotopic data obtained by future exploration of Mars could be relevant to highlighting different processes of Li isotopic fractionation in the past, and therefore to understanding basalt weathering and environmental conditions early in the planet's history.

  9. 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.

  10. Modeling the Zeeman effect in high altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

    Directory of Open Access Journals (Sweden)

    R. Larsson

    2015-10-01

    Full Text Available We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high altitude Special Sensor Microwave Imager/Sounder channels 19–22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively and the expected profile errors at the affected altitudes (estimated to be around 5 K. For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Same channel, there is 1.2 K in average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Same channel, there is 1.3 K in average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K and smaller standard deviations (at below 0.4 K when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies causing up to ± 7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better

  11. Analysis of the mid-latitude weather regimes in the 200-year control integration of the SINTEX model

    Directory of Open Access Journals (Sweden)

    A. Navarra

    2003-06-01

    Full Text Available Recent results indicate that climate predictions require models which can simulate accurately natural circulation regimes and their associated variability. The main purpose of this study is to investigate whether (and how a coupled model can simulate the real world weather regimes. A 200-year control integration of a coupled GCM (the «SINTEX model» is considered. The output analysed consists of monthly mean values of Northern Hemisphere extended winter (November to April 500-hPa geopotential heights. An Empirical Orthogonal Function (EOF analysis is first applied in order to define a reduced phase space based on the leading modes of variability. Therefore the principal component PDF in the reduced phase space spanned by two leading EOFs is computed. Based on a PDF analysis in the phase space spanned by the leading EOF1 and REOF2, substantial evidence of the nongaussian regime structure of the SINTEX northern winter circulation is found. The model Probability Density Function (PDF exhibits three maxima. The 500-hPa height geographical patterns of these density maxima are strongly reminiscent of well-documented Northern Hemisphere weather regimes. This result indicates that the SINTEX model can not only simulate the non-gaussian structure of the climatic attractor, but is also able to reproduce the natural modes of variability of the system.

  12. US NOAA HRRR/RAP Model/Assimilation System 2016-17 Improvements for Aviation Weather Applications

    Science.gov (United States)

    Benjamin, Stan; Alexander, Curtis; Weygandt, Stephen; Hu, Ming; Smirnova, Tanya; Olson, Joseph; Brown, John; Kenyon, Jaymes; James, Eric; Jankov, Isidora; Ladwig, Terra

    2017-04-01

    To improve US short-range forecast guidance for aviation (and severe weather and energy applications), an operational upgrade of the Rapid Refresh (RAP, 13km) and High-Resolution Rapid Refresh (HRRR, 3km) model systems at NOAA's NCEP occurred in August 2016. This coordinated upgrade (RAP version 3 and HRRR version 2, RAPv3/HRRRv2) includes enhancements to the data assimilation, model, and post-processing formulations that result in significant improvements to aviation forecasts for upper-air, surface, cloud and precipitation, and thunderstorms. Key changes will be described toward the next NCEP operational implementation (RAPv4/HRRRv3), planned for early 2018. Additional work is focused testing and refinement in related areas, including a real-time prototype High Resolution Rapid Refresh Ensemble (HRRRE), a post-processing-based HRRR-time-lagged ensemble (HRRR-TLE), and a HRRR domain covering Alaska (HRRR-AK). In this presentation, a recap of the RAPv3/HRRRv2 upgrade and forecast improvements will be provided, followed by a description of the planned improvements for RAPv4/HRRRv3 and impacts for aviation guidance for winds (turbulence), clouds (ceiling and visibility) and near-surface (terminal) forecasts. ESRL is now showing strong further improvements from model and assimilation improvements from the new RAPv4/HRRRv3 including further enhancements to the model physics components (aerosol-aware Thompson microphysics, MYNN PBL scheme, Smirnova land-surface model), and testing of a new vertical coordinate). The interaction of the various physics modules has been a particular research focus area, with modifications in place that further reduce various physics-related model biases. HRRRv3/RAPv4 data assimilation enhancements include improved radar and cloud assimilation, addition of data from TAMDAR aircraft, radar radial velocity data, and GOES cloud-top cooling rate data). HRRR time-lagged ensemble products are now being produced in real-time for many variables

  13. Enhancing Cloud Radiative Processes and Radiation Efficiency in the Advanced Research Weather Research and Forecasting (WRF) Model

    Energy Technology Data Exchange (ETDEWEB)

    Iacono, Michael J. [Atmospheric and Environmental Research, Lexington, MA (United States)

    2015-03-09

    The objective of this research has been to evaluate and implement enhancements to the computational performance of the RRTMG radiative transfer option in the Advanced Research version of the Weather Research and Forecasting (WRF) model. Efficiency is as essential as accuracy for effective numerical weather prediction, and radiative transfer is a relatively time-consuming component of dynamical models, taking up to 30-50 percent of the total model simulation time. To address this concern, this research has implemented and tested a version of RRTMG that utilizes graphics processing unit (GPU) technology (hereinafter RRTMGPU) to greatly improve its computational performance; thereby permitting either more frequent simulation of radiative effects or other model enhancements. During the early stages of this project the development of RRTMGPU was completed at AER under separate NASA funding to accelerate the code for use in the Goddard Space Flight Center (GSFC) Goddard Earth Observing System GEOS-5 global model. It should be noted that this final report describes results related to the funded portion of the originally proposed work concerning the acceleration of RRTMG with GPUs in WRF. As a k-distribution model, RRTMG is especially well suited to this modification due to its relatively large internal pseudo-spectral (g-point) dimension that, when combined with the horizontal grid vector in the dynamical model, can take great advantage of the GPU capability. Thorough testing under several model configurations has been performed to ensure that RRTMGPU improves WRF model run time while having no significant impact on calculated radiative fluxes and heating rates or on dynamical model fields relative to the RRTMG radiation. The RRTMGPU codes have been provided to NCAR for possible application to the next public release of the WRF forecast model.

  14. Architecture vision and technologies for post-NPOESS weather prediction system: two-way interactive observing and modeling

    Science.gov (United States)

    Kalb, Michael W.; Higgins, Glenn J.; Mahoney, Robert L.; Lutz, Robert; Mauk, Robin; Seablom, Michael; Talabac, Stephen J.

    2005-01-01

    A recently completed two-year NASA-sponsored study on Advanced Weather Forecasting Technologies envisions that given the opportunity to realize key technological advances over the next quarter century, and with judicious infrastructure and technology investments, it may be possible to significantly extend the skill range of model based weather forecasting via real-time two-way feedbacks between computer forecast models and highly networked, intelligent observing systems (Sensor Webs). Through this linkage, the observing system will have access to information about the present and evolving state of the atmosphere and, most importantly, have the intelligence to act on information about the future states of the atmosphere derived from the forecast model. An ultimate aim is full dynamic situation-driven observing system reconfigurability. The system is conceived to enable operational expression of optimized targeted observing. Ideas are presented on how the entire system might be designed and operated from the perspectives of the underlying science, technology evolution, and system engineering in order to provide the needed coordination between and among space- and ground-based observing and forecast model operations. The greatest challenges lay with the development of the large scale deep infrastructure on which the more advanced proposed forecast system functionality depends.

  15. Estimation of the mean depth of boreal lakes for use in numerical weather prediction and climate modelling

    Directory of Open Access Journals (Sweden)

    Margarita Choulga

    2014-03-01

    Full Text Available Lakes influence the structure of the atmospheric boundary layer and, consequently, the local weather and local climate. Their influence should be taken into account in the numerical weather prediction (NWP and climate models through parameterisation. For parameterisation, data on lake characteristics external to the model are also needed. The most important parameter is the lake depth. Global database of lake depth GLDB (Global Lake Database is developed to parameterise lakes in NWP and climate modelling. The main purpose of the study is to upgrade GLDB by use of indirect estimates of the mean depth for lakes in boreal zone, depending on their geological origin. For this, Tectonic Plates Map, geological, geomorphologic maps and the map of Quaternary deposits were used. Data from maps were processed by an innovative algorithm, resulting in 141 geological regions where lakes were considered to be of kindred origin. To obtain a typical mean lake depth for each of the selected regions, statistics from GLDB were gained and analysed. The main result of the study is a new version of GLDB with estimations of the typical mean lake depth included. Potential users of the product are NWP and climate models.

  16. Cascading model uncertainty from medium range weather forecasts (10 days) through a rainfall-runoff model to flood inundation predictions within the European Flood Forecasting System (EFFS)

    OpenAIRE

    Pappenberger, F.; K. J. Beven; N. M. Hunter; Bates, P. D.; B. T. Gouweleeuw; Thielen, J.; A. P. J. De De Roo

    2005-01-01

    International audience; The political pressure on the scientific community to provide medium to long term flood forecasts has increased in the light of recent flooding events in Europe. Such demands can be met by a system consisting of three different model components (weather forecast, rainfall-runoff forecast and flood inundation forecast) which are all liable to considerable uncertainty in the input, output and model parameters. Thus, an understanding of cascaded uncertainties is a necessa...

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

    DEFF Research Database (Denmark)

    Lovring, M. M.; Löwe, Roland; Courdent, Vianney Augustin Thomas

    (NWP) with assimilation of radar and cloud data (RA3), and Ensemble NWP with 25 members (S05) is conducted by comparing against rain gauge measurements and flood extent. Despite lower spatial and temporal resolution, the ensemble product seems promising for forecasting extreme events. A combination......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...... of the three forecast products is expected to yield the optimal input for flood warning....

  19. Severe weather during the North American monsoon and its response to rapid urbanization and a changing global climate within the context of high resolution regional atmospheric modeling

    Science.gov (United States)

    Luong, Thang Manh

    The North American monsoon (NAM) is the principal driver of summer severe weather in the Southwest U.S. With sufficient atmospheric instability and moisture, monsoon convection initiates during daytime in the mountains and later may organize, principally into mesoscale convective systems (MCSs). Most monsoon-related severe weather occurs in association with organized convection, including microbursts, dust storms, flash flooding and lightning. The overarching theme of this dissertation research is to investigate simulation of monsoon severe weather due to organized convection within the use of regional atmospheric modeling. A commonly used cumulus parameterization scheme has been modified to better account for dynamic pressure effects, resulting in an improved representation of a simulated MCS during the North American monsoon experiment and the climatology of warm season precipitation in a long-term regional climate model simulation. The effect of urbanization on organized convection occurring in Phoenix is evaluated in model sensitivity experiments using an urban canopy model (UCM) and urban land cover compared to pre-settlement natural desert land cover. The presence of vegetation and irrigation makes Phoenix a "heat sink" in comparison to its surrounding desert, and as a result the modeled precipitation in response to urbanization decreases within the Phoenix urban area and increase on its periphery. Finally, analysis of how monsoon severe weather is changing in association with observed global climate change is considered within the context of a series of retrospectively simulated severe weather events during the period 1948-2010 in a numerical weather prediction paradigm. The individual severe weather events are identified by favorable thermodynamic conditions of instability and atmospheric moisture (precipitable water). Changes in precipitation extremes are evaluated with extreme value statistics. During the last several decades, there has been

  20. Effective roughness calculated from satellite-derived land cover maps and hedge-information used in a weather forecasting model

    DEFF Research Database (Denmark)

    Hasager, C.B.; Nielsen, N.,W.; Jensen, N.O.

    2003-01-01

    In numerical weather prediction, climate and hydrological modelling, the grid cell size is typically larger than the horizontal length scales of variations in aerodynamic roughness, surface temperature and surface humidity. These local land cover variations give rise to sub-grid scale surface flux...... to be well-described in any large-scale model. A method of aggregating the roughness step changes in arbitrary real terrain has been applied in flat terrain (Denmark) where sub-grid scale vegetation-driven roughness variations are a dominant characteristic of the landscape. The aggregation model...... is a physical two-dimensional atmospheric flow model in the horizontal domain based on a linearized version of the Navier Stoke equation. The equations are solved by the Fast Fourier Transformation technique, hence the code is very fast. The new effective roughness maps have been used in the HIgh Resolution...

  1. 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.

  2. Software Engineering Practices in the Development of NASA Unified Weather Research and Forecasting (NU-WRF) Model

    Science.gov (United States)

    Burns, R.; Zhou, S.; Syed, R.

    2010-12-01

    The NASA Unified Weather Research and Forecasting (NU-WRF) Model is an effort to unify several WRF variants developed at NASA and bring together NASA's existing earth science models and assimilation systems that simulate the interaction among clouds, aerosols, atmospheric gases, precipitation, and land surfaces. By developing NU-WRF, the NASA modeling community expects to: (1) facilitate better use of WRF for scientific research, (2) reduce redundancy in major WRF development, (3) prolong the serviceable life span of WRF, and (4) allow better use of NASA high-resolution satellite data for short term climate and weather research. This project involves multiple teams from different organizations and the research goals are still evolving. As a result, software engineering best practices are needed for software life-cycle management and testing, and to ensure reliability of the data being generated. NASA software engineers and scientists have worked together to develop software requirements, scientific use cases, automated regression tests, software release plans, and a revision control system. Nightly automated regression tests are being used on scaled-down versions of the use cases to test if any code changes have unintentionally changed the science results or made the software unstable. Revision control management is needed to track software changes that are made by the many developers involved in the project. The release planning helps to guide the release of NU-WRF versions to the NASA community and allows for making strategic changes in delivery dates and software features as needed. The team of software engineers and scientists have also worked on optimizing, generalizing, and testing existing model preprocessing codes and run scripts for the various models. Finally, the team developed model coupling tools to link WRF with NASA earth science models. NU-WRF 1.0 was based on WRF3.1.1 and was released to the NASA community in July 2010, providing the researchers

  3. The Effects of Terrain Slope and Orientation on Different Weather Processes in China under Different Model Resolutions

    Institute of Scientific and Technical Information of China (English)

    HUANG Danqing; QIAN Yongfu

    2009-01-01

    Currently, short wave radiation at the ground surface (GSW) is calculated under the assumption of a horizontal surface. This method of estimating the GSW may lead to considerable errors when the model resolution becomes higher and the model terrain becomes steeper. In this paper, to improve the short wave solar radiation simulations, a terrain slope and orientation parameterization has been implemented into the non-hydrostatic mesoscale model GRAPES (Global/Regional Assimilation and Prediction System). The effects of the terrain slope and orientation on different short range weather processes in China under differentmodel resolutions are simulated and discussed. In the simulations, topography height is taken from NCEP (National Centers for Environmental Prediction) with a resolution of 1 kin, and the slope and orientation of terrain are calculated using different staggering schemes and under different weather conditions. The results show that when the model resolution is low (30 and 60 kin) and the slope of terrain is not large, the influence of the slope and orientation of terrain on the GSW is not evident; otherwise, however, it is not negligible.Under high model resolutions (3 and 6 kin), the increase (decrease) of simulated precipitation corresponds to the decrease (increase) of the GSW induced by the slope effect, and the variations of precipitation are usually ranged between -5 and 5 mm. Under the high resolution, the surface temperature and heat fluxes are strongly correlated to each other and the high correlation exists mostly in the complex terrain regions. The changes of the GSW, precipitation, surface temperature, and heat fluxes induced by the effects of the terrain slope and orientation are more obvious in mountainous regions, due to the alternations in the atmospheric circulation. It is found as well that under the weather condition of less cloud and less precipitation, the effects of the terrain slope and orientation can be more realistically seen

  4. Assimilation of microwave, infrared, and radio occultation satellite observations with a weather research and forecasting model for heavy rainfall forecasting

    Science.gov (United States)

    Boonyuen, Pakornpop; Wu, Falin; Phunthirawuth, Parwapath; Zhao, Yan

    2016-10-01

    In this research, satellite observation data were assimilated into Weather Research and Forecasting Model (WRF) by using Three-dimensional Variational Data Assimilation System (3DVAR) to analyze its impacts on heavy rainfall forecasts. The weather case for this research was during 13-18 September 2015. Tropical cyclone VAMCO, forming in South China Sea near with Vietnam, moved on west direction to the Northeast of Thailand. After passed through Vietnam, the tropical cyclone was become to depression and there was heavy rainfall throughout the area of Thailand. Observation data, used in this research, included microwave radiance observations from the Advanced Microwave Sounding Unit-A (AMSU-A), infrared radiance observations from Infrared Atmospheric Sounding Interferometer (IASI), and GPS radio occultation (RO) from the COSMIC and CHAMP missions. The experiments were designed in five cases, namely, 1) without data assimilation (CTRL); 2) with only RO data (RO); 3) with only AMSU-A data (AMSUA); 4) with only IASI data (IASI); and 5) with all of RO, AMSU-A and IASI data assimilation (ALL). Then all experiment results would be compared with both NCEP FNL (Final) Operational Global Analysis and the observation data from Thai Meteorological Department weather stations. The experiments result demonstrated that with microwave (AMSU-A), infrared (IASI) and GPS radio occultation (RO) data assimilation can produce the positive impact on analyses and forecast. All of satellite data assimilations have corresponding positive effects in term of temperature and humidity forecasting, and the GPS-RO assimilation produces the best of temperature and humidity forecast biases. The satellite data assimilation has a good impact on temperature and humidity in lower troposphere and vertical distribution that very helpful for heavy rainfall forecast improvement.

  5. ESA radiation and micro-meteoroid models applied to Space Weathering of atmosphere-less bodies: icy moons and asteroids

    Science.gov (United States)

    Vallat, Claire; Altobelli, Nicolas; Cornet, Thomas; Schmidt, Jürgen; Navarro, Sara; Erd, Christian; Witasse, Olivier; Rodmann, Jens; Mints, Alexey

    2016-10-01

    The Galilean moons reveal large albedo variations on their surfaces, in particular between their leading and trailing hemispheres. The differences observed are likely the results of a balance between various weathering processes of the surface, determined by the moons' local environment. Chemical and physical alterations occur at the surface, triggered by multiple exogenic energy deposit processes (radiolysis, plasma sputtering, micro-meteoroids impacts, …).The observed variations are probably due to anisotropy in the energy fluxes received on each hemisphere and due to to a different relative contribution of the weathering agents (plasma, dust…) as function of the distance to Jupiter. We will be testing this hypothesis by estimating quantitatively the kinetic energy flux impacting different part of the surfaces of the Galilean moons. This work is essential in the context of the future missions to the Jovian moons, such as the JUICE ESA mission, as a proper understanding of the moons' surface history can be achieved only if one is able to constrain the balance between exogenic and endogenic alteration processes.Impacts of dust particles coming from the Galilean moons and evolving dynamically in the Jovian system will be simulated using the Jovian Micrometeoroid Environment Model (JMEM) [1]. Direct interplanetary dust impacts are simulated using the prediction of the Interplanetary Micrometeoroid Environment Model (IMEM) [2] computed at Jupiter's Hill radius, taking into account gravitational focusing by the planet. Finally, electron and ion fluxes interacting with different parts of the moons' surfaces can be estimated using the Jovian Specification Environment model (JOSE) [3].In parallel, signature of surface weathering will be assessed using reflectance maps based on the Galileo imaging data.Those models will also be applied, for comparison, to other atmosphere-less bodies of the solar system such as the asteroids Ceres, Vesta and Pallas.References[1] Liu et

  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. 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.

  8. The Role of Model and Initial Condition Error in Numerical Weather Forecasting Investigated with an Observing System Simulation Experiment

    Science.gov (United States)

    Prive, Nikki C.; Errico, Ronald M.

    2013-01-01

    A series of experiments that explore the roles of model and initial condition error in numerical weather prediction are performed using an observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO). The use of an OSSE allows the analysis and forecast errors to be explicitly calculated, and different hypothetical observing networks can be tested with ease. In these experiments, both a full global OSSE framework and an 'identical twin' OSSE setup are utilized to compare the behavior of the data assimilation system and evolution of forecast skill with and without model error. The initial condition error is manipulated by varying the distribution and quality of the observing network and the magnitude of observation errors. The results show that model error has a strong impact on both the quality of the analysis field and the evolution of forecast skill, including both systematic and unsystematic model error components. With a realistic observing network, the analysis state retains a significant quantity of error due to systematic model error. If errors of the analysis state are minimized, model error acts to rapidly degrade forecast skill during the first 24-48 hours of forward integration. In the presence of model error, the impact of observation errors on forecast skill is small, but in the absence of model error, observation errors cause a substantial degradation of the skill of medium range forecasts.

  9. Climate-dependent sediment production: numerical modeling and field observations of variable grain size distributions from heterogeneous hillslope weathering of fractured basalt flows, Kohala Peninsula, Hawaii

    Science.gov (United States)

    Murphy, B. P.; Johnson, J. P.

    2012-12-01

    We present a numerical model for hillslope sediment production that includes climate-dependent chemical weathering rates and bedrock fracture spacings, and predicts how grain size distributions vary with climate and hillslope erosion rate. Understanding sediment preparation, or the in situ reduction of fractured bedrock to coarse sediment by heterogeneous weathering on hillslopes, is critical to understanding the evolution of mountainous landscapes, as sediment supply rates and size distributions can strongly influence river incision rates. The majority of soil production models assume a homogenous substrate and uniform weathering front, and therefore do not track the size of rock fragments and corestones, which become the sediment supplied to channels by hillslope erosion. Our model is inspired by the Kohala Peninsula on the big island of Hawaii, which has a gradient of mean annual precipitation (MAP) spanning over an order of magnitude that has been shown to influence the weathering rates of the basalt. Previous geochemical studies have constrained climate-dependent weathering rates for local soil production. Using these inputs, we developed a kinetics-based numerical model for the chemical weathering of initially fractured basalt into soil and coarse sediment over 150ky. Following first-order reaction kinetics, chemical weathering in the model decreases exponentially with both depth below the surface and time. The model starts with a column of repeating basalt flows (typically 1 m thick), each with fracture spacing distributions consistent with thermal-mechanical cooling characteristics. Each individual fracture-bound block is assumed to weather from the surface inwards, similar in form to a weathering rind. Since the model is constructed of discrete blocks, larger blocks remain as unweathered corestones (the "sediment"), surrounded by weathered material. In addition to a MAP-dependent initial surface weathering rate and rate constant, climate is also reflected

  10. 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.

  11. A Subgrid Parameterization for Wind Turbines in Weather Prediction Models with an Application to Wind Resource Limits

    Directory of Open Access Journals (Sweden)

    B. H. Fiedler

    2014-01-01

    Full Text Available A subgrid parameterization is offered for representing wind turbines in weather prediction models. The parameterization models the drag and mixing the turbines cause in the atmosphere, as well as the electrical power production the wind causes in the wind turbines. The documentation of the parameterization is complete; it does not require knowledge of proprietary data of wind turbine characteristics. The parameterization is applied to a study of wind resource limits in a hypothetical giant wind farm. The simulated production density was found not to exceed 1 W m−2, peaking at a deployed capacity density of 5 W m−2 and decreasing slightly as capacity density increased to 20 W m−2.

  12. Chemical weathering rates in deep-sea sediments: Comparison of multicomponent reactive transport models and estimates based on 234U

    Science.gov (United States)

    Maher, K.; Steefel, C. I.; Depaolo, D. J.

    2004-12-01

    Chemical weathering rates in natural systems are typically much slower than expected based on experiments and theory. There are several possible explanations. However, because it has been difficult to determine what effects in particular reduce the rates in specific settings, natural rates remain difficult to predict. Silicate-rich deep-sea sediments provide an ideal in-situ laboratory for investigating weathering rates because certain potentially important factors, such as advective transport through heterogeneous media, limitations on the availability of reactive surface area due to low porosity and/or cementation, unsaturated flow conditions, and seasonal variations in fluid flux and temperature, do not occur in this setting. Geochemical profiles from Site 984 in the North Atlantic are modeled using a multi-component reactive transport model (CRUNCH) to determine in-situ rates of plagioclase dissolution and other diagenetic processes, including sulfate reduction and anaerobic methane oxidation. Various possible processes which might contribute to slower rates in the field are considered, including the effect of mineral saturation state, secondary precipitation of clays, inhibition by dissolved aluminum, and the availability of reactive surface area. The reactive transport model includes an isotopic solid-solution formulation that tracks the isotopic composition of precipitating (calcite) and dissolving (plagioclase and calcite) phases, thus allowing the determination of plagioclase dissolution rates. The rate constants for plagioclase determined by geochemical transport modeling of major element profiles are within the same range determined from U-series calculations and suggest that natural weathering rates for this system are on the order of 10-17.5 to 10-17.7 mol/m2/sec assuming estimates of reactive surface area are correct, several orders of magnitude slower than laboratory-derived rates. The slow plagioclase rates are most likely due to the fact that

  13. Stormy Weather

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    Inspired by the deep abyss of the unknown; a constant source for investigation and discovery, heating and destruction, all simultaneously. Beneath the deep darkness, millions of species vibrantly thrive in another universe wholly untouched by human hands, though affected by their choices. The weathered pieces and people associated with seaside villages, the deep wrinkles that tell a story of one's life and experiences like

  14. 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.

  15. 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; 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. PMID:24511292

  16. 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.

  17. A Global Analysis of the ZWD/PW Conversion Methods using Radiosonde Observations and Numerical Weather Models

    Science.gov (United States)

    Rozsa, S.

    2014-12-01

    Water vapor plays an important role as a basic climate variable in the thermodynamics and dynamics of the storm systems at the atmosphere and in hydrological cycles of local, regional and global scales. Moreover, the distribution of atmospheric water vapor is difficult to determine because of its rapid change in spatial and temporal scales. Atmospheric water vapor can be estimated by the zenith delay derived from ground-based GNSS data. Ground-based GNSS receivers are a valuable source for determining total zenith delay (ZTD) and precipitable water vapor (PW) data for meteorology since they are portable, economic and provide measurements that are not affected by weather conditions. They cannot provide a humidity profile as radiosondes can, however they have the advantage of producing automated continuous data as opposed to operational radiosondes usually providing two measurements in a day. Therefore, tropospheric delay modeling methods for estimating precipitable water vapor using GNSS signals are being developed frequently. Wet and hydrostatic zenith delays can be computed by applying the mapping functions which are mathematical equations using elevation angles. The observed tropospheric delays can be used for monitoring the water vapor content of the troposphere. In several regions of the world GNSS derived products are already used on a routine basis for numerical weather prediction. In this study, PW values obtained from radiosonde profiles and the ones derived from ground-based GNSS data are processed both with BERNESE v5.0 using Niell mapping function and GAMIT/GLOBK using empirical model GPT (Global Pressure and Temperature) are compared with the values computed from radiosonde analysis algorithm under severe storm conditions. In order to convert the ZWD to PW new, locally fitted models are derived using local radiosonde observations and ECMWF model data.

  18. 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.

  19. Performance of a coupled lagged ensemble weather and river runoff prediction model system for the Alpine Ammer River catchment

    Science.gov (United States)

    Smiatek, G.; Kunstmann, H.; Werhahn, J.

    2012-04-01

    The Ammer River catchment located in the Bavarian Ammergau Alps and alpine forelands, Germany, represents with elevations reaching 2185 m and annual mean precipitation between1100 and 2000 mm a very demanding test ground for a river runoff prediction system. Large flooding events in 1999 and 2005 motivated the development of a physically based prediction tool in this area. Such a tool is the coupled high resolution numerical weather and river runoff forecasting system AM-POE that is being studied in several configurations in various experiments starting from the year 2005. Corner stones of the coupled system are the hydrological water balance model WaSiM-ETH run at 100 m grid resolution, the numerical weather prediction model (NWP) MM5 driven at 3.5 km grid cell resolution and the Perl Object Environment (POE) framework. POE implements the input data download from various sources, the input data provision via SOAP based WEB services as well as the runs of the hydrology model both with observed and with NWP predicted meteorology input. The one way coupled system utilizes a lagged ensemble prediction system (EPS) taking into account combination of recent and previous NWP forecasts. Results obtained in the years 2005-2011 reveal that river runoff simulations depict high correlation with observed runoff when driven with monitored observations in hindcast experiments. The ability to runoff forecasts is depending on lead times in the lagged ensemble prediction and shows still limitations resulting from errors in timing and total amount of the predicted precipitation in the complex mountainous area. The presentation describes the system implementation, and demonstrates the application of the POE framework in networking, distributed computing and in the setup of various experiments as well as long term results of the system application in the years 2005 - 2011.

  20. 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.

  1. Characterization of downwelling radiance measured from a ground-based microwave radiometer using numerical weather prediction model data

    Science.gov (United States)

    Ahn, M.-H.; Won, H. Y.; Han, D.; Kim, Y.-H.; Ha, J.-C.

    2016-01-01

    The ground-based microwave sounding radiometers installed at nine weather stations of Korea Meteorological Administration alongside with the wind profilers have been operating for more than 4 years. Here we apply a process to assess the characteristics of the observation data by comparing the measured brightness temperature (Tb) with reference data. For the current study, the reference data are prepared by the radiative transfer simulation with the temperature and humidity profiles from the numerical weather prediction model instead of the conventional radiosonde data. Based on the 3 years of data, from 2010 to 2012, we were able to characterize the effects of the absolute calibration on the quality of the measured Tb. We also showed that when clouds are present the comparison with the model has a high variability due to presence of cloud liquid water therefore making cloudy data not suitable for assessment of the radiometer's performance. Finally we showed that differences between modeled and measured brightness temperatures are unlikely due to a shift in the selection of the center frequency but more likely due to spectroscopy issues in the wings of the 60 GHz absorption band. With a proper consideration of data affected by these two effects, it is shown that there is an excellent agreement between the measured and simulated Tb. The regression coefficients are better than 0.97 along with the bias value of better than 1.0 K except for the 52.28 GHz channel which shows a rather large bias and variability of -2.6 and 1.8 K, respectively.

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

    Directory of Open Access Journals (Sweden)

    Khandakar Md Habib Al Razi, Moritomi Hiroshi

    2013-01-01

    Full Text Available 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.

  3. Sensitivity of high-temperature weather to initial soil moisture: a case study using the WRF model

    Science.gov (United States)

    Zeng, X.-M.; Wang, B.; Zhang, Y.; Song, S.; Huang, X.; Zheng, Y.; Chen, C.; Wang, G.

    2014-09-01

    Using a succession of 24 h Weather Research and Forecasting model (WRF) simulations, we investigate the sensitivity to initial soil moisture of a short-range high-temperature weather event that occurred in late July 2003 in East China. The initial soil moisture (SMOIS) in the Noah land surface scheme is adjusted (relative to the control run, CTL) for four groups of simulations: DRY25 (-25%), DRY50 (-50%), WET25 (+25%) and WET50 (+50%). Ten 24 h integrations are performed in each group. We focus on 2 m surface air temperature (SAT) greater than 35 °C (the threshold of "high-temperature" events in China) at 06:00 UTC (roughly 14:00 LT in the study domain) to analyse the occurrence of the high-temperature event. The 10-day mean results show that the 06:00 UTC SAT (SAT06) is sensitive to the SMOIS change; specifically, SAT06 exhibits an apparent increase with the SMOIS decrease (e.g. compared with CTL, DRY25 generally results in a 1 °C SAT06 increase over the land surface of East China), areas with 35 °C or higher SAT06 are the most affected, and the simulations are more sensitive to the SMOIS decrease than to the SMOIS increase, which suggests that hot weather can be amplified under low soil moisture conditions. Regarding the mechanism underlying the extremely high SAT06, sensible heat flux has been shown to directly heat the lower atmosphere, and latent heat flux has been found to be more sensitive to the SMOIS change, resulting in an overall increase in surface net radiation due to the increased greenhouse effect (e.g. with the SMOIS increase from DRY25 to CTL, the 10-day mean net radiation increases by 5 W m-2). Additionally, due to the unique and dynamic nature of the western Pacific subtropical high, negative feedback occurs between the regional atmospheric circulation and the air temperature in the lower atmosphere while positive feedback occurs in the mid-troposphere. Using a method based on an analogous temperature relationship, a detailed analysis of the

  4. Sensitivity of high-temperature weather to initial soil moisture: a case study with the WRF model

    Science.gov (United States)

    Zeng, X.-M.; Wang, B.; Zhang, Y.; Song, S.; Huang, X.; Zheng, Y.; Chen, C.; Wang, G.

    2014-05-01

    Using the Weather Research and Forecasting model (WRF), we investigate the sensitivity of simulated short-range high-temperature weather to initial soil moisture for the East China extremely hot event in late July 2003 via a succession of 24 h simulations. The initial soil moisture (SMOIS) in the Noah land surface scheme is prescribed for five groups of designed simulations, i.e., relative to the control run (CTL), SMOIS is changed by -25, -50, +25 and +50% in the DRY25, DRY50, WET25 and WET50 groups, respectively, with ten 24 h-long integrations performed in each group. We focus on above-35 °C (standard of so-called "high-temperature" event in China) 2 m surface air temperature (SAT) at 06:00 UTC (roughly 12:00 LT in the study domain) to analyze the occurrence of the high-temperature event. Ten-day mean results show that the 06:00 UTC SAT (SAT06) is sensitive to the SMOIS change, i.e., SAT06 exhibits an apparent rising with the SMOIS decrease (e.g., compared with CTL, DRY25 results in a 1 °C SAT06 rising in general over land surface of East China), areas with above-35 °C SAT06 are most affected, and the simulations are found to be more sensitive to the SMOIS decrease than to the SMOIS increase, suggesting that hot weather can be amplified under low soil moisture conditions. With regard to the mechanism of influencing the extreme high SAT06, sensible heat flux shows to directly heat the lower atmosphere, latent heat flux is found to be more sensitive to the SMOIS change and results in the overall increase of surface net radiation due to the increased greenhouse effect (e.g., with the SMOIS increase of 25% from DRY25 to CTL, the ten-day mean net radiation is increased by 5 W m-2), and a negative (positive) feedback is found between regional atmospheric circulation and air temperature in the lower atmosphere (mid-troposphere) due to the unique dynamic nature of the western Pacific subtropical high. Using a method based on an analogous temperature relationship, a

  5. Climate indices over the last three decades in Tunisia using Weather Research and Forecasting Model:WRF

    Science.gov (United States)

    Deli, Meriem; Mkhinini, Nadia; Sadok Guellouz, Mohamed; Benjabrallah, Sadok

    2016-04-01

    Tunisia is a country situated in the south of the mediterannen basin. This region undergoes direct and indirect effects of climate change. Actually, we notice that summer temperatures have risen during the last decades. Nevertheless research on the tunisian climate are not well developed and are mainly based on observations; short and mid term forecast are not available for the tunisian case. In this context we have studied the climate properties of Tunisia over the last 30 years using Weather Research and Forecasting model WRF. Afterwards we compared our results to the observations that we have obteined on behalf of the National Institute of Meteorology. Results were then used to calculate different climate indices related to the air temperature such as extreme values during a specific period exceeding specific limits (Percentile), warm and cold spell duration and growing season length. We admit that we have created a reliable database for the Tunisian climate.

  6. 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.

  7. A grid-based distributed flood forecasting model for use with weather radar data: Part 2. Case studies

    Science.gov (United States)

    Bell, V. A.; Moore, R. J.

    A simple distributed rainfall-runoff model, configured on a square grid to make best use of weather radar data, was developed in Part 1 (Bell and Moore, 1998). The simple form of the basic model, referred to as the Simple Grid Model or SGM, allows a number of model variants to be introduced, including probability-distributed storage and topographic index representations of runoff production and formulations which use soil survey and land use data. These models are evaluated here on three catchments in the UK: the Rhondda in south Wales, the Wyre in north-west England and the Mole in the Thames Basin near London. Assessment is initially carried out in simulation mode to focus on the conversion of rainfall to runoff as influenced by (i) use of radar or raingauge input, (ii) choice of model variant, and (iii) use of a lumped or distributed model formulation. Weather radar data, in grid square and catchment average form, and raingauge data are used as alternative estimates of rainfall input to the model. Results show that when radar data are of good quality, significant model improvement may be obtained by replacing data from a single raingauge by 2 km grid square radar data. The performance of the Simple Grid Model with optimised isochrones is only marginally improved through the use of different model variants and is generally preferred on account of its simplicity. A more traditional lumped rainfall-runoff model, the Probability-Distributed Moisture model or PDM, is used as a benchmark against which to assess the performance of the distributed models. This proves hard to better, although the distributed formulation of the Grid model proves more reliable for some storm and catchment combinations where spatial effects on runoff response are evident. Assessment is then carried out in updating mode to emulate a real-time forecasting environment. First, a state updating form of the Grid Model is developed and then assessed against an ARMA error-prediction technique. Both

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

    Energy Technology Data Exchange (ETDEWEB)

    Morrison, PI Hugh

    2012-09-21

    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 advisor).

  9. Tropospheric Profiles of Total Refractivity Based on Numerical Weather Prediction Model and GNSS Data Using the Collocation Software COMEDIE

    Science.gov (United States)

    Wilgan, K. I.; Rohm, W.; Bosy, J.; Geiger, A.; Hurter, F.

    2015-12-01

    The GNSS (Global Navigation Satellite Systems) signal propagation delay in neutral atmosphere can be described in terms of total refractivity which depends on the atmospheric parameters: air pressure, temperature and water vapor partial pressure. In this study we have reconstructed the total refractivity profiles over Poland using the least-squares collocation software COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays). Profiles were calculated from different combinations of data sets from following sources: meteorological parameters from Numerical Weather Prediction Model WRF (Weather Research and Forecasting) or EUREF Permanent Network (EPN) stations and zenith total delay (ZTD) from ground-based GNSS products on ASG-EUPOS stations. The combinations of data sets included into this study are: 'WRF only', 'WRF/GNSS', 'WRF/GNSS/EPN' and 'GNSS only'. To find the data set with the best accuracy, profiles were compared with the reference radiosonde observations. The data set with the best accuracy is the combined 'WRF/GNSS' with mean bias close to 0 and standard deviation of 3 ppm. The data set 'WRF/GNSS/EPN' shows very similar accuracy so, there is no need to include the additional ground-based meteorological information from EPN stations. The data set 'GNSS only' shows much worse accuracy with the discrepancies at lower altitudes even at the level of -30 ppm. The data set 'WRF only' shows as good agreement with reference data as 'WRF/GNSS' in term of total refractivity, but when we calculated ZTD from all sets, we found that standard deviations from residuals are almost two times larger for the 'WRF only' dataset. We continue advancing the collocation algorithms, so the ZTD from the model can be useful as a priori troposphere information for example in PPP (Precise Point Positioning) technique.

  10. 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

  11. Temporal variation of chemical and mechanical weathering in NE Iceland: Evaluation of a steady-state model of erosion

    Science.gov (United States)

    Eiriksdottir, E. S.; Louvat, P.; Gislason, S. R.; Óskarsson, N.; Hardardóttir, J.

    2008-07-01

    This study critically assesses the temporal sensitivity of the steady-state model of erosion that has been applied to chemical and mechanical weathering studies of volcanic islands and the continents, using only one sample from each catchment. The model assumes a geochemical mass balance between the initially unweathered rock of a drainage basin and the dissolved and solid loads of the river. Chemical composition of 178 samples of suspended and dissolved inorganic river constituents, collected in 1998-2002, were studied from five basaltic river catchments in NE Iceland. The Hydrological Service in Iceland has monitored the discharge and the total suspended inorganic matter concentration (SIM) of the glacial rivers for ~ four decades, making it possible to compare modelled and measured SIM fluxes. Concentration of SIM and grain size increased with discharge. As proportion of clay size particles in the SIM samples increased, concentrations of insoluble elements increased and of soluble decreased. The highest proportion of altered basaltic glass was in the clay size particles. The concentration ratio of insoluble elements in the SIM was used along with data on chemical composition of unweathered rocks (high-Mg basalts, tholeiites, rhyolites) to calculate the pristine composition of the original catchment rocks. The calculated rhyolite proportions compare nicely with area-weighted average proportions, from geological maps of these catchments. The calculated composition of the unweathered bedrock was used in the steady-state model, together with the chemical composition of the suspended and dissolved constituents of the river. Seasonal changes in dissolved constituent concentrations resulted in too low modelled concentrations of SIM mod at high discharge (and too high SIM mod at low discharge). Samples collected at annual average river dissolved load yielded SIM mod concentrations close to the measured ones. According to the model, the studied rivers had specific

  12. Use of weather research and forecasting model outputs to obtain near-surface refractive index structure constant over the ocean.

    Science.gov (United States)

    Qing, Chun; Wu, Xiaoqing; Li, Xuebin; Zhu, Wenyue; Qiao, Chunhong; Rao, Ruizhong; Mei, Haipin

    2016-06-13

    The methods to obtain atmospheric refractive index structure constant (Cn2) by instrument measurement are limited spatially and temporally and they are more difficult and expensive over the ocean. It is useful to forecast Cn2 effectively from Weather Research and Forecasting Model (WRF) outputs. This paper introduces a method that WRF Model is used to forecast the routine meteorological parameters firstly, and then Cn2 is calculated based on these parameters by the Bulk model from the Monin-Obukhov similarity theory (MOST) over the ocean near-surface. The corresponding Cn2 values measured by the micro-thermometer which is placed on the ship are compared with the ones forecasted by WRF model to determine how this method performs. The result shows that the forecasted Cn2 is consistent with the measured Cn2 in trend and the order of magnitude as a whole, as well as the correlation coefficient is up to 77.57%. This method can forecast some essential aspects of Cn2 and almost always captures the correct magnitude of Cn2, which experiences fluctuations of two orders of magnitude. Thus, it seems to be a feasible and meaningful method that using WRF model to forecast near-surface Cn2 value over the ocean.

  13. EMPOL 1.0: a new parameterization of pollen emission in numerical weather prediction models

    Directory of Open Access Journals (Sweden)

    K. Zink

    2013-11-01

    Gases, both with a parameterization already present in the model and with our new parameterization EMPOL. The statistical results show that the performance of the model can be enhanced by using EMPOL.

  14. 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

  15. Evaluation of weather research and forecasting model parameterizations under sea-breeze conditions in a North Sea coastal environment

    Science.gov (United States)

    Salvador, Nadir; Reis, Neyval Costa; Santos, Jane Meri; Albuquerque, Taciana Toledo de Almeida; Loriato, Ayres Geraldo; Delbarre, Hervé; Augustin, Patrick; Sokolov, Anton; Moreira, Davidson Martins

    2016-12-01

    Three atmospheric boundary layer (ABL) schemes and two land surface models that are used in the Weather Research and Forecasting (WRF) model, version 3.4.1, were evaluated with numerical simulations by using data from the north coast of France (Dunkerque). The ABL schemes YSU (Yonsei University), ACM2 (Asymmetric Convective Model version 2), and MYJ (Mellor-Yamada-Janjic) were combined with two land surface models, Noah and RUC (Rapid Update Cycle), in order to determine the performances under sea-breeze conditions. Particular attention is given in the determination of the thermal internal boundary layer (TIBL), which is very important in air pollution scenarios. The other physics parameterizations used in the model were consistent for all simulations. The predictions of the sea-breeze dynamics output from the WRF model were compared with observations taken from sonic detection and ranging, light detection and ranging systems and a meteorological surface station to verify that the model had reasonable accuracy in predicting the behavior of local circulations. The temporal comparisons of the vertical and horizontal wind speeds and wind directions predicted by the WRF model showed that all runs detected the passage of the sea-breeze front. However, except for the combination of MYJ and Noah, all runs had a time delay compared with the frontal passage measured by the instruments. The proposed study shows that the synoptic wind attenuated the intensity and penetration of the sea breeze. This provided changes in the vertical mixing in a short period of time and on soil temperature that could not be detected by the WRF model simulations with the computational grid used. Additionally, among the tested schemes, the combination of the localclosure MYJ scheme with the land surface Noah scheme was able to produce the most accurate ABL height compared with observations, and it was also able to capture the TIBL.

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. Evaluation of medium-range weather forecasts about Korea Institute of Atmospheric Prediction Systems (KIAPS) Integrated Model System (KIM)

    Science.gov (United States)

    Lee, J.; Seol, K. H.

    2015-12-01

    The Korea Institute of Atmospheric Prediction Systems (KIAPS) is a government funded non-profit research and development institute located in Seoul, South Korea. KIAPS was established in 2011 by the Korea Meteorological Administration, KIAPS' primary sponsor. KIAPS is developing the KIAPS Integrated Model System (KIM), a backbone for the next-generation operational global numerical weather prediction (NWP) system. The KIM will be a unified model that can be used for global modeling as well as local areas, particularly optimized to topographic and meteorological features of the Korean Peninsula. We have been completed developing major model components based on KIAPS own research and release the KIAPS beta version model on September 2014. We evaluated the results of KIM by using verification system developed KIAPS, it is composed of standard verification score based on WMO report. The system consists of four parts: verification against analysis, observations, vertical verification and quantitative precipitation forecasts. The results of verification against analysis, we found that increase of error for temperature under 700 hPa. In case of MSLP, poor performance except for tropical region is represented, and the increase of error for geopotential height is shown in tropical region. For verification against observations, positive bias is represented for upper level geopotential height, for low level wind speed in tropical region in summer, for all level wind speed in Northern Hemisphere in winter, and for specific humidity in Northern Hemisphere in summer. As previously stated about the result against analysis, cold bias for low level temperature is shown in Northern Hemisphere in summer. In case of verification for rain about KIM, the model value is underestimated in heavy rain category in summer, on the contrary, that is overestimated in heavy rain category in winter. Overall, there is overestimation in ocean for all models. Our findings indicate that continuing

  1. Compilation of 3D global conductivity model of the Earth for space weather applications

    Science.gov (United States)

    Alekseev, Dmitry; Kuvshinov, Alexey; Palshin, Nikolay

    2015-07-01

    We have compiled a global three-dimensional (3D) conductivity model of the Earth with an ultimate goal to be used for realistic simulation of geomagnetically induced currents (GIC), posing a potential threat to man-made electric systems. Bearing in mind the intrinsic frequency range of the most intense disturbances (magnetospheric substorms) with typical periods ranging from a few minutes to a few hours, the compiled 3D model represents the structure in depth range of 0-100 km, including seawater, sediments, earth crust, and partly the lithosphere/asthenosphere. More explicitly, the model consists of a series of spherical layers, whose vertical and lateral boundaries are established based on available data. To compile a model, global maps of bathymetry, sediment thickness, and upper and lower crust thicknesses as well as lithosphere thickness are utilized. All maps are re-interpolated on a common grid of 0.25×0.25 degree lateral spacing. Once the geometry of different structures is specified, each element of the structure is assigned either a certain conductivity value or conductivity versus depth distribution, according to available laboratory data and conversion laws. A numerical formalism developed for compilation of the model, allows for its further refinement by incorporation of regional 3D conductivity distributions inferred from the real electromagnetic data. So far we included into our model four regional conductivity models, available from recent publications, namely, surface conductance model of Russia, and 3D conductivity models of Fennoscandia, Australia, and northwest of the United States.

  2. 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

  3. Adopting the Test-Driven Development to Developing Numerical Weather Prediction Model by Using the pFUnit

    Science.gov (United States)

    Jun, S. Y.; Kim, J.; Song, I. S.

    2014-12-01

    Modern Numerical Weather Prediction (NWP) model is a complex software that consists of scientific and computational components over multiple software layers. Development of NWP model is complicated process bringing many risks arise from the software complexity and long-term developing period. The software engineering suggests that software testing is a requisite for developing the complex software because it can improve software quality and reduce risk. In particular, the Test-Driven Development (TDD) is known to the useful way in software testing enable to develop more productive software with writing more unit-tests. We utilize the pFUnit, which is the unit testing framework for Fortran with MPI extensions under the NASA open source license, for adopting TDD to developing the KIAPS-GM (Korea Institute of Atmospheric Prediction Systems-Global Model) framework. It is known that the pFUnit offers a convenient, lightweight mechanism for Fortran developers to create and run software tests that specify the desired behavior for a given piece of code. Our implementation of TDD with the pFUnit will be presented with test suite and unit-tests for infrastructure of the KIAPS-GM framework.

  4. IPW and ZTD from numerical weather prediction model in the context of GNSS tropospheric products

    Science.gov (United States)

    Kruczyk, M.; Liwosz, T.; Mazur, A.

    2012-04-01

    Paper describes extensive experiences in dealing with operational numerical prediction models treated as a source of IPW and ZTD needed for GNSS tropospheric products quality assessment. Authors use operational numerical prediction model COSMO-LM (maintained by Polish Institute of Meteorology and Water Management) in two different resolution versions: 14 km and 2.8 km and global model GFS (operated by NCEP). Both input fields and first prognosis steps of operational numerical prediction model were processed as IPW source for comparisons and analyses. We discuss diversity of questions concerning precise derivation of IPW and ZTD from model grid e. g.: interpolation of data in space, numerical integration in zenith direction, correction for model topography, physical equations chosen for humidity parameters conversions etc. Results from NWP model are neatly collated with various GNSS tropospheric solutions: WUT EPN LAC solutions, EPN combined product and IGS solutions. Also meteorological water vapour data sources (radiosoundings and sun photometer CIMEL-318) were utilized for independent verification. Presented results of many comparisons lead to some clues about key factors in such calculations. We get also valuable information about GNSS tropospheric solutions quality.

  5. Implementation Weather-Type Models of Capacitated Arc Routing Problem via Heuristics

    Directory of Open Access Journals (Sweden)

    Zuhaimy Ismail

    2011-01-01

    Full Text Available Problem statement: In this study, we introduced a new and real-life condition of Capacitated Arc Routing Problem (CARP, a model that represents vehicles operation in waste collection. In general, we studied the element of rain drops that affected the collected waste weight in total by imposed a new variable namely rainy weight age. In rainy days, the household refusals did not increase in volumes, but in weights due to rain drops. Consequently, this matter thus burdened vehicles capacity and prolonged its operation time. This dynamic variable thus changes the initial CARP model where the existing model did not consider other external elements that have effected onto the model. Approach: Then we developed and enhanced CARP by integrating stochastic demand and time windows to suit the models with our specific case. Results: Objectively, CARP with stochastic demand (CARPSD and CARP with time windows (CARPTW were designed to minimize the total routing cost and number of trips for a vehicle. Our approach is to design CARP models in almost likely to road layout in residential area and graphically this model is called mesh network. We also developed a constructive heuristic that is called nearest procedure based on highest demand/cost (NPHDC and work in conjunction with switching rules to search the feasible solution. Conclusion: Our preliminary results show a higher cost and more trips are needed when the vehicle operates in rainy day compared to normal day operation.

  6. Updating prediction models by dynamical relaxation - An examination of the technique. [for numerical weather forecasting

    Science.gov (United States)

    Davies, H. C.; Turner, R. E.

    1977-01-01

    A dynamical relaxation technique for updating prediction models is analyzed with the help of the linear and nonlinear barotropic primitive equations. It is assumed that a complete four-dimensional time history of some prescribed subset of the meteorological variables is known. The rate of adaptation of the flow variables toward the true state is determined for a linearized f-model, and for mid-latitude and equatorial beta-plane models. The results of the analysis are corroborated by numerical experiments with the nonlinear shallow-water equations.

  7. Clouds, weather, climate, and modeling for K-12 and public audiences from the Center for Multi-scale Modeling of Atmospheric Processes

    Science.gov (United States)

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

    2010-12-01

    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 fifth year, the National Science Foundation-funded Center for Multi-scale Modeling of Atmospheric Processes (CMMAP) at Colorado State University (CSU) 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. This is accomplished through collaborations in resource development and dissemination between CMMAP scientists, CSU’s Little Shop of Physics (LSOP) program, and the Windows to the Universe (W2U) program at University Corporation for Atmospheric Research (UCAR). Little Shop of Physics develops new hands on science activities demonstrating basic science concepts fundamental to understanding atmospheric characteristics, weather, and climate. Videos capture demonstrations of children completing these activities which are broadcast to school districts and public television programs. CMMAP and LSOP educators and scientists partner in teaching a summer professional development workshops for teachers at CSU with a semester's worth of college-level content on the basic physics of the atmosphere, weather, climate, climate modeling, and climate change, as well as dozens of LSOP inquiry-based activities suitable for use in classrooms. The W2U project complements these efforts by developing and broadly disseminating new CMMAP-related online content pages, animations, interactives, image galleries, scientists’ biographies, and LSOP videos to K-12 and public audiences. Reaching nearly 20 million users annually, W2U is highly valued as a curriculum enhancement

  8. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Brownsville, Texas Weather Forecast Office (WFO)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

  9. NOAA Office for Coastal Management Coastal Inundation Digital Elevation Model: Corpus Christi Weather Forecast Office (WFO)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This digital elevation model (DEM) is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea...

  10. Implementation Weather-Type Models of Capacitated Arc Routing Problem via Heuristics

    National Research Council Canada - National Science Library

    Zuhaimy Ismail; Mohammad F. Ramli

    2011-01-01

    ...), a model that represents vehicles operation in waste collection. In general, we studied the element of rain drops that affected the collected waste weight in total by imposed a new variable namely rainy weight age...

  11. A quantitative evaluation of the high resolution HARMONIE model for critical weather phenomena

    Science.gov (United States)

    van der Plas, E. V.; Wichers Schreur, B.; Kok, K.

    2012-07-01

    The high resolution non-hydrostatic Harmonie model (Seity et al., 2012) seems capable of delivering high quality precipitation forecasts. The quality with respect to the European radar composite is assessed using the Model Evaluation Tool, as distributed by the NCAR DTC (Developmental Testbed Center, 2012), and compared to that of the reference run of Hirlam (Unden et al., 2002), the current operational NWP model at KNMI. Both neighbourhood and object-based verification methods are compared for a week with several high intensity precipitation events in July 2010. It is found that Hirlam scores very well in most metrics, and that in spite of the higher resolution the added value of the Harmonie model is sometimes hard to quantify. However, higher precipitation intensities are better represented in the Harmonie model with its higher resolution. Object-based methods do not yet yield a sharp distinction between the different models, as it proves difficult to construct a meaningful and distinguishing metric with a solid physical basis for the many settings that can be varied.

  12. Modelling surface drifting of buoys during a rapidly-moving weather front in the Gulf of Finland, Baltic Sea

    Science.gov (United States)

    Gästgifvars, Maria; Lauri, Hannu; Sarkanen, Annakaisa; Myrberg, Kai; Andrejev, Oleg; Ambjörn, Cecilia

    2006-12-01

    The Gulf of Finland is an elongated estuary located in the north-eastern extremity of the Baltic Sea. This semi-enclosed sea-area is subject to heavy sea traffic, and is one of the main risk areas for oil accidents in the Baltic. The continuous development and validation of operational particle drift and oil-spill forecasting systems is thus seen to be essential for this sea-area. Here, the results of a three-day drift experiment in May 2003 are discussed. The field studies were performed using GPS-positioned surface floating buoys. The aim of this paper is to evaluate how well models can reproduce the drift of these buoys. Model simulations, both in forecast and hindcast modes, were carried out by three different 3D hydrodynamic models, the results of which are evaluated by comparing the calculated drifts with observations. These models were forced by HIRLAM (High Resolution Limited Area Model) and ECMWF (European Centre for Medium-Range Weather Forecasts) meteorological forecast fields. The simulated drift of the buoys showed a good agreement with observations even when, during the study period, a rapidly-changing wind situation was observed to affect the investigation area; in this situation the winds turned about 100 degrees in half an hour. In such a case it is a very complicated task to forecast the drifters' routes: there is a need to regularly update the meteorological forcing fields and to use these regularly-updated fields throughout the simulations. It is furthermore recommended that forecasts should be made using several circulation models and several meteorological forecasts, in order to get an overview of the accuracy of the forecasted drifts and related differences in between the forecasts.

  13. Satellite Cloud Assimilation in the Weather Research & Forecasting (WRF) Model and its Impact on Air Quality Simulations

    Science.gov (United States)

    Pour Biazar, Arastoo; White, Andrew; McNider, Richard; Khan, Maudood; Dornblaser, Bright; Wu, Yuling

    2017-04-01

    Clouds have a significant role in air quality simulations as they modulate biogenic hydrocarbon emissions and photolysis rates, impact boundary-layer development, lead to deep vertical mixing of pollutants and precursors, and induce aqueous phase chemistry. Unfortunately, numerical meteorological models still have difficulty in creating clouds in the right place and time compared to observed clouds. This is especially the case when synoptic-scale forcing is weak, as often is the case during air pollution episodes in the Southeast United States. Thus, poor representation of clouds impacts the photochemical model's ability in simulating the air quality. However, since satellites provide the best observational platform for defining the formation and location of clouds, satellite observations can be of great value in retrospective simulations. Here, we present results from a recent activity in which the Geostationary Operational Environmental Satellite (GOES) derived cloud fields are assimilated within Weather Research and Forecasting (WRF) model to improve simulated clouds. The assimilation technique dynamically support cloud formation/dissipation within WRF based on GOES observations. The technique uses observations to identify model cloud errors, estimates a target vertical velocity and moisture to create/remove clouds, and adjust the flow field accordingly. The technique was implemented and tested in WRF for a month-long simulation during August 2006, and was tested in an air quality simulation over the period of August-September 2013 (NASA's Discover-AQ field campaign). The cloud assimilation on the average improved model cloud simulation by 15%. The cloud correction not only improved the spatial and temporal distribution of clouds, it also improved boundary layer temperature, humidity, and wind speed. These improvements in meteorological fields directly impacted the air quality simulations and altered trace gas concentrations. For air quality simulations, WRF

  14. A grid-based distributed flood forecasting model for use with weather radar data: Part 1. Formulation

    Science.gov (United States)

    Bell, V. A.; Moore, R. J.

    A practical methodology for distributed rainfall-runoff modelling using grid square weather radar data is developed for use in real-time flood forecasting. The model, called the Grid Model, is configured so as to share the same grid as used by the weather radar, thereby exploiting the distributed rainfall estimates to the full. Each grid square in the catchment is conceptualised as a storage which receives water as precipitation and generates water by overflow and drainage. This water is routed across the catchment using isochrone pathways. These are derived from a digital terrain model assuming two fixed velocities of travel for land and river pathways which are regarded as model parameters to be optimised. Translation of water between isochrones is achieved using a discrete kinematic routing procedure, parameterised through a single dimensionless wave speed parameter, which advects the water and incorporates diffusion effects through the discrete space-time formulation. The basic model routes overflow and drainage separately through a parallel system of kinematic routing reaches, characterised by different wave speeds but using the same isochrone-based space discretisation; these represent fast and slow pathways to the basin outlet, respectively. A variant allows the slow pathway to have separate isochrones calculated using Darcy velocities controlled by the hydraulic gradient as estimated by the local gradient of the terrain. Runoff production within a grid square is controlled by its absorption capacity which is parameterised through a simple linkage function to the mean gradient in the square, as calculated from digital terrain data. This allows absorption capacity to be specified differently for every grid square in the catchment through the use of only two regional parameters and a DTM measurement of mean gradient for each square. An extension of this basic idea to consider the distribution of gradient within the square leads analytically to a Pareto

  15. A grid-based distributed flood forecasting model for use with weather radar data: Part 1. Formulation

    Directory of Open Access Journals (Sweden)

    V. A. Bell

    1998-01-01

    Full Text Available A practical methodology for distributed rainfall-runoff modelling using grid square weather radar data is developed for use in real-time flood forecasting. The model, called the Grid Model, is configured so as to share the same grid as used by the weather radar, thereby exploiting the distributed rainfall estimates to the full. Each grid square in the catchment is conceptualised as a storage which receives water as precipitation and generates water by overflow and drainage. This water is routed across the catchment using isochrone pathways. These are derived from a digital terrain model assuming two fixed velocities of travel for land and river pathways which are regarded as model parameters to be optimised. Translation of water between isochrones is achieved using a discrete kinematic routing procedure, parameterised through a single dimensionless wave speed parameter, which advects the water and incorporates diffusion effects through the discrete space-time formulation. The basic model routes overflow and drainage separately through a parallel system of kinematic routing reaches, characterised by different wave speeds but using the same isochrone-based space discretisation; these represent fast and slow pathways to the basin outlet, respectively. A variant allows the slow pathway to have separate isochrones calculated using Darcy velocities controlled by the hydraulic gradient as estimated by the local gradient of the terrain. Runoff production within a grid square is controlled by its absorption capacity which is parameterised through a simple linkage function to the mean gradient in the square, as calculated from digital terrain data. This allows absorption capacity to be specified differently for every grid square in the catchment through the use of only two regional parameters and a DTM measurement of mean gradient for each square. An extension of this basic idea to consider the distribution of gradient within the square leads analytically

  16. 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.

  17. 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 cou

  18. 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 cou

  19. Detection of Weather Radar Clutter

    DEFF Research Database (Denmark)

    Bøvith, Thomas

    2008-01-01

    Weather radars provide valuable information on precipitation in the atmosphere but due to the way radars work, not only precipitation is observed by the weather radar. Weather radar clutter, echoes from non-precipitating targets, occur frequently in the data, resulting in lowered data quality....... Especially in the application of weather radar data in quantitative precipitation estimation and forecasting a high data quality is important. Clutter detection is one of the key components in achieving this goal. This thesis presents three methods for detection of clutter. The methods use supervised...... and precipitating and non-precipitating clouds. Another method uses the difference in the motion field of clutter and precipitation measured between two radar images. Furthermore, the direction of the wind field extracted from a weather model is used. The third method uses information about the refractive index...

  20. 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 the maxi......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......-model in second-order 1-D SST models in the future. A significant part of the thesis was dedicated to the development of a CFD model of a circular conical SST with the open source OpenFOAM CFD toolbox. The focus was mainly on identifying the settling and rheology submodels using data obtained from laboratory...

  1. The impact of the atmospheric model and of the space weather data on the dynamics of clouds of space debris

    Science.gov (United States)

    Petit, Alexis; Lemaitre, Anne

    2016-06-01

    New tools are necessary to deal with more than hundred thousands of space debris, thus our aim is to develop software able to propagate numerous trajectories and manage collisions or fragmentations. Specifically in low orbits Earth, gravity and atmospheric drag are the two main forces that affect the dynamics of the artificial satellites or space debris. NIMASTEP, the local orbit propagator, initially designed for high altitudes, has been adapted to low altitude orbits. To study the future debris environment, we propose a suitable model of space weather and we compare three different atmospheric density models (Jacchia-Bowman 2008, DTM-2013, and TD-88) able to propagate with accuracy and efficiency a large population of space debris on long time scales. We compare the results in different altitudes and during the reentry regime; we show, with a ballistic coefficient constant, a trend to underestimate or overestimate the decrease of the semi-major axis, specifically during the periods of high solar activity. We parallelize our software and use the calculation power of a computing cluster, we propagate a huge cloud of debris and we show that its global evolution is in agreement with the observations on several years.

  2. On the contribution of lakes in predicting near-surface temperature in a global weather forecasting model

    Directory of Open Access Journals (Sweden)

    T. Stockdale

    2012-02-01

    Full Text Available The impact of lakes in numerical weather prediction is investigated in a set of global simulations performed with the ECMWF Integrated Forecasting System (IFS. A Fresh shallow-water Lake model (FLake is introduced allowing the coupling of both resolved and subgrid lakes (those that occupy less than 50% of a grid-box to the IFS atmospheric model. Global fields for the lake ancillary conditions (namely lake cover and lake depth, as well as initial conditions for the lake physical state, have been derived to initialise the forecast experiments. The procedure for initialising the lake variables is described and verified with particular emphasis on the importance of surface water temperature and freezing conditions. The response of short-range near surface temperature to the representation of lakes is examined in a set of forecast experiments covering one full year. It is shown that the impact of subgrid lakes is beneficial, reducing forecast error over the Northern territories of Canada and over Scandinavia particularly in spring and summer seasons. This is mainly attributed to the lake thermal effect, which delays the temperature response to seasonal radiation forcing.

  3. Generalized Wind Turbine Actuator Disk Parameterization in the Weather Research and Forecasting (WRF) Model for Real-World Simulations

    Science.gov (United States)

    Marjanovic, N.; Mirocha, J. D.; Chow, F. K.

    2013-12-01

    In this work, we examine the performance of a generalized actuator disk (GAD) model embedded within the Weather Research and Forecasting (WRF) atmospheric model to study wake effects on successive rows of turbines at a North American wind farm. These wake effects are of interest as they can drastically reduce down-wind energy extraction and increase turbulence intensity. The GAD, which is designed for turbulence-resolving simulations, is used within downscaled large-eddy simulations (LES) forced with mesoscale simulations and WRF's grid nesting capability. The GAD represents the effects of thrust and torque created by a wind turbine on the atmosphere within a disk representing the rotor swept area. The lift and drag forces acting on the turbine blades are parameterized using blade-element theory and the aerodynamic properties of the blades. Our implementation permits simulation of turbine wake effects and turbine/airflow interactions within a realistic atmospheric boundary layer flow field, including resolved turbulence, time-evolving mesoscale forcing, and real topography. The GAD includes real-time yaw and pitch control to respond realistically to changing flow conditions. Simulation results are compared to SODAR data from operating wind turbines and an already existing WRF mesoscale turbine drag parameterization to validate the GAD parameterization.

  4. Weather Modification: Finding Common Ground.

    Science.gov (United States)

    Garstang, Michael; Bruintjes, Roelof; Serafin, Robert; Orville, Harold; Boe, Bruce; Cotton, William; Warburton, Joseph

    2005-05-01

    Research and operational approaches to weather modification expressed in the National Research Council's 2003 report on “Critical Issues in Weather Modification Research” and in the Weather Modification Association's response to that report form the basis for this discussion. There is agreement that advances in the past few decades over a broad front of understanding physical processes and in technology have not been comprehensively applied to weather modification. Such advances need to be capitalized upon in the form of a concerted and sustained national effort to carry out basic and applied research in weather modification. The need for credible scientific evidence and the pressure for action should be resolved. Differences in the perception of current knowledge, the utility of numerical models, and the specific needs of research and operations in weather modification must be addressed. The increasing demand for water and the cost to society inflicted by severe weather require that the intellectual, technical, and administrative resources of the nation be combined to resolve whether and to what degree humans can influence the weather.The National Center for Atmospheric Research is sponsored by the National Science Foundation

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

    Science.gov (United States)

    López L, D.

    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.

  6. QUANTITATIVE ULTRAVIOLET SPECTROSCOPY IN WEATHERING OF A MODEL POLYESTER-URETHANE COATING. (R828081E01)

    Science.gov (United States)

    Spectroscopy was used to quantify the effects of ultraviolet light on a model polyester–urethane coating as it degraded in an accelerated exposure chamber. An explorative calculation of the effective dosage absorbed by the coatings was made and, depending on the quantum...

  7. Validation of Crop Weather Models for'Crop Assessment arid Yield ...

    African Journals Online (AJOL)

    over predict grain yields of maize, sorghum and wheat, a fact that could be attributed to the inadequacy of the model .... Of particular interest in this category is the cesses (Hanks and Hill, 1980). ... ter and basic infiltration rate for soii data. The.

  8. Performance assessment of the COAMPS numerical weather prediction model in precise GPS positioning: EUPOS network case study

    Science.gov (United States)

    Wielgosz, Pawel; Paziewski, Jacek; Krankowski, Andrzej; Kroszczynski, Krzyszfof; Figurski, Mariusz

    2010-05-01

    The Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®) represents a complete three-dimensional data assimilation system comprised of data quality control, analysis, initialization, and forecast model components. COAMPS has been developed by the Marine Meteorology Division (MMD) of the Naval Research Laboratory (NRL). The U.S. Navy uses the system for short-term numerical weather predictions for various regions of the world. Currently COAMPS ver.3.1 is also operated and tested at the Department of Civil Engineering and Geodesy of the Military University of Technology, Warsaw, Poland (MUT). It is primarily used for military applications, but also a new module has been developed to provide tropospheric zenith total delays (ZTD) for stations of the Polish part of the European Position Determination System (EUPOS). ZTDs can be obtained in both near-real time and several hours ahead. In the highest-precision GPS applications tropospheric delays are usually estimated from satellite observables. When processing long baselines the common practice is to derive the hydrostatic component from any troposphere model and use it as a priori information. The non-hydrostatic part is estimated in the adjustment along with station coordinates. The change of satellite geometry during the observational session allows overcome high correlation between the tropospheric delays and the station height components. However, when processing very short sessions and medium baselines, this change is too small and does not allow estimating reliable ZTDs. Hence, ZTD are derived from troposphere models and used for correction of GPS data in the processing. This contribution presents the application of COAMPS-derived ZTDs in precise GPS positioning when using short data spans (1-5 minutes) and processing medium baselines (50-80 km). The presented tests were performed in two areas: Wielkopolska Lowland (all stations located at similar heights), and Carpathian Mountains (where station

  9. Comprehensive Solar-Terrestrial Environment Model (COSTEM) for Space Weather Predictions

    Science.gov (United States)

    2007-07-01

    predictions. Cluster spacecraft was in the dayside magnetosphere, Polar was magnetically connected Too/ to the high latitude region, GOES-]0 was...driven simulations of a Workshop on Astrophysical Particle Acceleration 3D solar wind powered by WKB Alfven waves in Geospace and Beyond, Chattanooga...October Decay of Moderate Storms at Solar Maximum: 2001. Page 23 of 32 MURI F49620-01-1-0359 FINAL REPORT PI: TAMAS GOMBOSI Global Modeling Using

  10. Multi-output ANN Model for Prediction of Seven Meteorological Parameters in a Weather Station

    Science.gov (United States)

    Raza, Khalid; Jothiprakash, V.

    2014-12-01

    The meteorological parameters plays a vital role for determining various water demand in the water resource systems, planning, management and operation. Thus, accurate prediction of meteorological variables at different spatial and temporal intervals is the key requirement. Artificial Neural Network (ANN) is one of the most widely used data driven modelling techniques with lots of good features like, easy applications, high accuracy in prediction and to predict the multi-output complex non-linear relationships. In this paper, a Multi-input Multi-output (MIMO) ANN model has been developed and applied to predict seven important meteorological parameters, such as maximum temperature, minimum temperature, relative humidity, wind speed, sunshine hours, dew point temperature and evaporation concurrently. Several types of ANN, such as multilayer perceptron, generalized feedforward neural network, radial basis function and recurrent neural network with multi hidden layer and varying number of neurons at the hidden layer, has been developed, trained, validated and tested. From the results, it is found that the recurrent MIMO-ANN having 28 neurons in a single hidden layer, trained using hyperbolic tangent transfer function with a learning rate of 0.3 and momentum factor of 0.7 performed well over the other types of MIMO-ANN models. The MIMO ANN model performed well for all parameters with higher correlation and other performance indicators except for sunshine hours. Due to erratic nature, the importance of each of the input over the output through sensitivity analysis indicated that relative humidity has highest influence while others have equal influence over the output.

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

    Science.gov (United States)

    Larbi, John Aseidu; Lawer, Eric Adjei

    2017-01-01

    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. PMID:28255497

  12. Detection of Digital Elevation Model Errors Using X-band Weather Radar

    Science.gov (United States)

    Young, Steven D.; deHaag, Maatren Uijt

    2007-01-01

    Flight in Instrument Meteorological Conditions requires pilots to manipulate flight controls while referring to a Primary Flight Display. The Primary Flight Display indicates aircraft attitude along with, in some cases, many other state variables such as altitude, speed, and guidance cues. Synthetic Vision Systems have been proposed that overlay the traditional information provided on Primary Flight Displays onto a scene depicting the location of terrain and other geo-spatial features.Terrain models used by these displays must have sufficient quality to avoid providing misleading information. This paper describes how X-band radar measurements can be used as part of a monitor, and/or maintenance system, to quantify the integrity of terrain models that are used by systems such as Synthetic Vision. Terrain shadowing effects, as seen by the radar, are compared in a statistical manner against estimated shadow feature elements extracted from the stored terrain model from the perspective of the airborne observer. A test statistic is defined that enables detection of errors as small as the range resolution of the radar. Experimental results obtained from two aircraft platforms hosting certified commercial-off-the-shelf X-band radars test the premise and illustrate its potential.

  13. Validation of Multi-Scale Simulations of the Flow over Big Southern Butte Using Weather Research and Forecasting Model

    Science.gov (United States)

    Kosovic, B.; Jimenez, P. A.

    2015-12-01

    Advances in high performance computational resources and frameworks now make possible the use of Numerical Weather Predication (NWP) models for high-resolution simulations of atmospheric flows. In order to develop best practices, standards, and procedures for multi-scale simulations, we need to carry out extensive validation of NWP models across unprecedented range of scales from hundreds of kilometers to tens of meters. However, there are limited observational data available for evaluating high-resolution models. Recently, Nunalee et al (2015) validated large-eddy simulations (LES) using WRF for flow and dispersion based on the Cinder Cone Butte experiment carried out in Idaho in 1982. This study involved moderately complex terrain. We now extend the study to a significantly more complex terrain based on a more recent field study in Idaho. This field study include two experiments: the first one carried out in 2010 and centered on the Big Southern Butte (BSB) and the second in 2011 centered on the Salmon River Canyon both in Idaho (Butler et al., 2015). As a first step, here we focus on using the observations from the BSB experiment to validate multi-scale simulations using the WRF model. We carry out both mesoscale simulations and large-eddy simulations (LES). Nested mesoscale simulations are carried out using the innermost nest with grid cell size of 300m while nested WRF-LES are carried with grid cell size of ~50m. We analyze the performance of PBL scheme in mesoscale simulations and the resulting interplay between subgrid parameterization and numerical advection scheme in LES. The results of this analysis are used to assess performance of PBL schemes in complex terrain where the assumption of horizontal homogeneity on which these schemes are based are violated and to suggest the modifications to PBL scheme to account for the effect of heterogeneity.

  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. 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...

  16. Impact of a Revised Convective Triggering Mechanism on CAM2 Model Simulations: Results from Short-Range Weather Forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Xie, S; Boyle, J S; Cederwall, R T; Potter, G L; Zhang, M; Lin, W

    2004-02-19

    This study implements a revised convective triggering condition in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM2) model to reduce its excessive warm season daytime precipitation over land. The new triggering mechanism introduces a simple dynamic constraint on the initiation of convection that emulates the collective effects of lower level moistening and upward motion of the large-scale circulation. It requires a positive contribution from the large-scale advection of temperature and moisture to the existing positive Convective Available Potential Energy (CAPE) for model convection to start. In contrast, the original convection triggering function in CAM2 assumes that convection is triggered whenever there is positive CAPE, which results in too frequent warm season convection over land arising from strong diurnal variation of solar radiation. We examine the impact of the new trigger on CAM2 simulations by running the climate model in Numerical Weather Prediction (NWP) mode so that more available observations and high-frequency NWP analysis data can be used to evaluate model performance. We show that the modified triggering mechanism has led to considerable improvements in the simulation of precipitation, temperature, moisture, clouds, radiations, surface temperature, and surface sensible and latent heat fluxes when compared to the data collected from the Atmospheric Radiation Measurement (ARM) program at its South Great Plains (SGP) site. Similar improvements are also seen over other parts of the globe. In particular, the surface precipitation simulation has been significantly improved over both the continental United States and around the globe; the overestimation of high clouds in the equatorial tropics has been substantially reduced; and the temperature, moisture, and zonal wind are more realistically simulated. Results from this study also show that some systematic errors in the CAM2 climate simulations can be detected in

  17. An online trajectory module (version 1.0 for the non-hydrostatic numerical weather prediction model COSMO

    Directory of Open Access Journals (Sweden)

    A. K. Miltenberger

    2013-02-01

    Full Text Available A module to calculate online trajectories has been implemented into the non-hydrostatic limited-area weather prediction and climate model COSMO. Whereas offline trajectories are calculated with wind fields from model output, which is typically available every one to six hours, online trajectories use the simulated wind field at every model time step (typically less than a minute to solve the trajectory equation. As a consequence, online trajectories much better capture the short-term temporal fluctuations of the wind field, which is particularly important for mesoscale flows near topography and convective clouds, and they do not suffer from temporal interpolation errors between model output times. The numerical implementation of online trajectories in the COSMO model is based upon an established offline trajectory tool and takes full account of the horizontal domain decomposition that is used for parallelization of the COSMO model. Although a perfect workload balance cannot be achieved for the trajectory module (due to the fact that trajectory positions are not necessarily equally distributed over the model domain, the additional computational costs are fairly small for high-resolution simulations. Various options have been implemented to initialize online trajectories at different locations and times during the model simulation. As a first application of the new COSMO module an Alpine North Föhn event in summer 1987 has been simulated with horizontal resolutions of 2.2 km, 7 km, and 14 km. It is shown that low-tropospheric trajectories calculated offline with one- to six-hourly wind fields can significantly deviate from trajectories calculated online. Deviations increase with decreasing model grid spacing and are particularly large in regions of deep convection and strong orographic flow distortion. On average, for this particular case study, horizontal and vertical positions between online and offline trajectories differed by 50–190 km and

  18. The Los Alamos dynamic radiation environment assimilation model (DREAM) for space weather specification and forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Reeves, Geoffrey D [Los Alamos National Laboratory; Friedel, Reiner H W [Los Alamos National Laboratory; Chen, Yue [Los Alamos National Laboratory; Koller, Josef [Los Alamos National Laboratory; Henderson, Michael G [Los Alamos National Laboratory

    2008-01-01

    The Dynamic Radiation Environment Assimilation Model (DREAM) was developed at Los Alamos National Laboratory to assess, quantify, and predict the hazards from the natural space environment and the anthropogenic environment produced by high altitude nuclear explosions (HANE). DREAM was initially developed as a basic research activity to understand and predict the dynamics of the Earth's Van Allen radiation belts. It uses Kalman filter techniques to assimilate data from space environment instruments with a physics-based model of the radiation belts. DREAM can assimilate data from a variety of types of instruments and data with various levels of resolution and fidelity by assigning appropriate uncertainties to the observations. Data from any spacecraft orbit can be assimilated but DREAM was designed to function with as few as two spacecraft inputs: one from geosynchronous orbit and one from GPS orbit. With those inputs, DREAM can be used to predict the environment at any satellite in any orbit whether space environment data are available in those orbits or not. Even with very limited data input and relatively simple physics models, DREAM specifies the space environment in the radiation belts to a high level of accuracy. DREAM has been extensively tested and evaluated as we transition from research to operations. We report here on one set of test results in which we predict the environment in a highly-elliptical polar orbit. We also discuss long-duration reanalysis for spacecraft design, using DREAM for real-time operations, and prospects for 1-week forecasts of the radiation belt environment.

  19. 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...... for vector field estimation already known from short-term weather radar nowcasting. However, instead of forecasting the weather radar rainfall, the proposed interpolation method exploits the advection of the rainfall in the interpolation. The interpolated rainfall fields are validated by measurements...... at ground level from laser disdrometers. The proposed interpolation method performs better when compared to traditional interpolation of weather radar rainfall where the radar observation is considered constant in time between measurements. It is demonstrated that the advection-based interpolation method...

  20. 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.

  1. 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

    2011-12-01

    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.

  2. MODELING OF WEATHER DATA FOR THE EAST ANATOLIA REGION OF TURKEY

    Directory of Open Access Journals (Sweden)

    S. Akpinar

    2010-01-01

    Full Text Available Monthly average daily data of climatic conditions over the period 1994-2003 of cities in the east Anatolia region of Turkey is presented. Regression methods are used to fit polynomial and trigonometric functions to the monthly averages for nine parameters. The parameters namely temperature, maximum-minimum temperature, relative humidity, pressure, wind speed, rainfall, solar radiation and sunshine duration are useful for renewable energy applications. The functions presented for the parameters should enable determination of specific parameter values and prediction of missing values. They also provide some insight into the variation of these parameters. The models developed can be used in any study related to climatic and its effect on the environment and energy.

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    S. L. Gong

    2012-04-01

    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. 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.

  6. New developments in geostrophic turbulence and its implications for climate modeling and weather predictability

    Science.gov (United States)

    Tribbia, Joseph

    2012-10-01

    One of the many areas in geophysical fluid dynamics that impacts how we model dissipation in the climate system is the theory of two-dimensional and quasi geostrophic turbulence and its impact on atmospheric flow. Upscale energy and and down scale enstrophy cascades have been observed in the atmosphere along with the -3 power law predicted in two-dimensional turbulence theory put forward by Batchelor and Kraichnan in the late 1960s. A consequence of this observational finding is the fact that, unlike three-dimensional turbulence in which the eddy turnover time decreases with eddy length scale, in two dimensional and quasi-geostrophic turbulence the eddy turnover time is constant independent of eddy length scale in the enstrophy cascading range. A further consequence of this is that the Rossby number is constant through the enstrophy cascade. This implies that instabilities which depend on ageostrophic processes are restricted because the scaling laws which imply balanced, quasi-geostrophic dynamics are valid at all length scales. Recent results show, however, even given that all of the above statements are true and maintained in the dynamics, there is a mechanism through which quasi-geostrophic turbulence becomes inconsistent and develops the seeds of its own destruction at small scales.

  7. Operational Space Weather Activities in the US

    Science.gov (United States)

    Berger, Thomas; Singer, Howard; Onsager, Terrance; Viereck, Rodney; Murtagh, William; Rutledge, Robert

    2016-07-01

    We review the current activities in the civil operational space weather forecasting enterprise of the United States. The NOAA/Space Weather Prediction Center is the nation's official source of space weather watches, warnings, and alerts, working with partners in the Air Force as well as international operational forecast services to provide predictions, data, and products on a large variety of space weather phenomena and impacts. In October 2015, the White House Office of Science and Technology Policy released the National Space Weather Strategy (NSWS) and associated Space Weather Action Plan (SWAP) that define how the nation will better forecast, mitigate, and respond to an extreme space weather event. The SWAP defines actions involving multiple federal agencies and mandates coordination and collaboration with academia, the private sector, and international bodies to, among other things, develop and sustain an operational space weather observing system; develop and deploy new models of space weather impacts to critical infrastructure systems; define new mechanisms for the transition of research models to operations and to ensure that the research community is supported for, and has access to, operational model upgrade paths; and to enhance fundamental understanding of space weather through support of research models and observations. The SWAP will guide significant aspects of space weather operational and research activities for the next decade, with opportunities to revisit the strategy in the coming years through the auspices of the National Science and Technology Council.

  8. Optimization of numerical weather/wave prediction models based on information geometry and computational techniques

    Science.gov (United States)

    Galanis, George; Famelis, Ioannis; Kalogeri, Christina

    2014-10-01

    The last years a new highly demanding framework has been set for environmental sciences and applied mathematics as a result of the needs posed by issues that are of interest not only of the scientific community but of today's society in general: global warming, renewable resources of energy, natural hazards can be listed among them. Two are the main directions that the research community follows today in order to address the above problems: The utilization of environmental observations obtained from in situ or remote sensing sources and the meteorological-oceanographic simulations based on physical-mathematical models. In particular, trying to reach credible local forecasts the two previous data sources are combined by algorithms that are essentially based on optimization processes. The conventional approaches in this framework usually neglect the topological-geometrical properties of the space of the data under study by adopting least square methods based on classical Euclidean geometry tools. In the present work new optimization techniques are discussed making use of methodologies from a rapidly advancing branch of applied Mathematics, the Information Geometry. The latter prove that the distributions of data sets are elements of non-Euclidean structures in which the underlying geometry may differ significantly from the classical one. Geometrical entities like Riemannian metrics, distances, curvature and affine connections are utilized in order to define the optimum distributions fitting to the environmental data at specific areas and to form differential systems that describes the optimization procedures. The methodology proposed is clarified by an application for wind speed forecasts in the Kefaloniaisland, Greece.

  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. Validation of Optical Turbulence Simulations from a Numerical Weather Prediction Model in Support of Adaptive Optics Design

    Science.gov (United States)

    Alliss, R.; Felton, B.

    Optical turbulence (OT) acts to distort light in the atmosphere, degrading imagery from large astronomical telescopes and possibly reducing data quality of air to air laser communication links. Some of the degradation due to turbulence can be corrected by adaptive optics. However, the severity of optical turbulence, and thus the amount of correction required, is largely dependent upon the turbulence at the location of interest. Therefore, it is vital to understand the climatology of optical turbulence at such locations. In many cases, it is impractical and expensive to setup instrumentation to characterize the climatology of OT, so simulations become a less expensive and convenient alternative. The strength of OT is characterized by the refractive index structure function Cn2, which in turn is used to calculate atmospheric seeing parameters. While attempts have been made to characterize Cn2 using empirical models, Cn2 can be calculated more directly from Numerical Weather Prediction (NWP) simulations using pressure, temperature, thermal stability, vertical wind shear, turbulent Prandtl number, and turbulence kinetic energy (TKE). In this work we use the Weather Research and Forecast (WRF) NWP model to generate Cn2 climatologies in the planetary boundary layer and free atmosphere, allowing for both point-to-point and ground-to-space seeing estimates of the Fried Coherence length (ro) and other seeing parameters. Simulations are performed using the Maui High Performance Computing Centers Jaws cluster. The WRF model is configured to run at 1km horizontal resolution over a domain covering the islands of Maui and the Big Island. The vertical resolution varies from 25 meters in the boundary layer to 500 meters in the stratosphere. The model top is 20 km. We are interested in the variations in Cn2 and the Fried Coherence Length (ro) between the summits of Haleakala and Mauna Loa. Over six months of simulations have been performed over this area. Simulations indicate that

  11. Inverse modeling of soil water content to estimate the hydraulic properties of a shallow soil and the associated weathered bedrock

    Science.gov (United States)

    Le Bourgeois, O.; Bouvier, C.; Brunet, P.; Ayral, P.-A.

    2016-10-01

    Modeling soil water flow requires the knowledge of numerous parameters associated to the water content and the soil hydraulic properties. Direct estimations of those parameters in laboratory require expensive equipment and the obtained parameters are generally not representative at the field scale because of the limitation of core sample size. Indirect methods such as inverse modeling are known to get efficient estimations and are easier to set up and process for large-scale studies. In this study, we investigated the capacity of an inverse modeling procedure to estimate the soil and the bedrock hydrodynamic properties only from in situ soil water content measurements at multiple depths under natural conditions. Multi-objective parameter optimization was performed using the HYDRUS-1D software and an external optimization procedure based on the NSGA-II algorithm. In a midslope shallow soil, water content was monitored at 3 depths, 20, 40, and 60 cm during 12 intense rainfall events, whose amounts ranged between 50 and 250 mm and duration between 1 and 5 days. The vertical profile was considered as 2 layers of soils above a third layer representing the weathered schist rock. This deep layer acted as a deep boundary condition, which features the bedrock permeability and water storage. Each layer was described trough the 6 parameters of the Mualem-van Genuchten formulation. The calibrated parameters appeared to have very low uncertainty while allowing a good modelisation of the observed water content variations. The calibrated saturated water content was close to the laboratory porosity measurements while the saturated hydraulic conductivity showed that the soil was highly permeable, as measured in the field. The inverse modeling approach allowed an estimation of the hydraulic properties of the bedrock layer where no measurement was available. The bedrock layer was found to have a low saturated hydraulic conductivity (model failed sometimes to reproduce the saturation

  12. 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.

  13. INTRAVAL phase 2, test case 8, Alligator Rivers Natural Analogue: Modelling of uranium transport in the weathered zone at Koongarra (Australia)

    Energy Technology Data Exchange (ETDEWEB)

    Van de Weerd, H.; Leijnse, A.; Hassanizadeh, S.M.; Richardson-van der Poel, M.A.

    1994-04-01

    The purpose of this study is to test the simulation package METROPOL, developed at RIVM to simulate transport of radionuclides over large time scales. At the Koongarra site secondary uranium mineralization and dispersed uranium is present from the surface down to the base of weathering. Field data are analyzed to choose a modelling approach, to estimate model inputs and to test model results. Field data show that three layers can be distinguished in the Koongarra area: (1) a top layer which is fully weathered, (2) an intermediate layer which is partially weathered (the transition zone) and (3) a lower layer which is unweathered. The groundwater velocities are largest in the transition zone which has been moving downward as the weathering process proceeds. The finite element code METROPOL has been adapted to account for the movement of the transition zone and to describe the dissolution of uranium in the orebody by a non-equilibrium relation. In simulations taking into account the downward movement of the transition zone, the dispersion patterns at all depths are simulated. These simulations result in a pseudo steady state situation. Despite the fact that the model results presented are not fully in agreement with the dispersion patterns, it is expected that the present situation may be obtained by changing some of the model parameters. In this study it was shown that over large timescales geologic processes may have an impact on the transport of radionuclides, and the movement of the transition zone will have an impact on the uranium concentration distribution. The simulation results are influenced by the parameters values, which are difficult to estimate for a period of some million years. The largest uncertainties are associated with the boundary conditions. Continuation of natural analogue studies in the framework of nuclear waste disposal research is highly recommended. 24 figs., 13 tabs., 2 appendices, 39 refs.

  14. Two-dimensional gas chromatography/mass spectrometry, physical property modeling and automated production of component maps to assess the weathering of pollutants.

    Science.gov (United States)

    Antle, Patrick M; Zeigler, Christian D; Livitz, Dimitri G; Robbat, Albert

    2014-10-17

    Local conditions influence how pollutants will weather in subsurface environments and sediment, and many of the processes that comprise environmental weathering are dependent upon these substances' physical and chemical properties. For example, the effects of dissolution, evaporation, and organic phase partitioning can be related to the aqueous solubility (SW), vapor pressure (VP), and octanol-water partition coefficient (KOW), respectively. This study outlines a novel approach for estimating these physical properties from comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC/MS) retention index-based polyparameter linear free energy relationships (LFERs). Key to robust correlation between GC measurements and physical properties is the accurate and precise generation of retention indices. Our model, which employs isovolatility curves to calculate retention indices, provides improved retention measurement accuracy for families of homologous compounds and leads to better estimates of their physical properties. Results indicate that the physical property estimates produced from this approach have the same error on a logarithmic-linear scale as previous researchers' log-log estimates, yielding a markedly improved model. The model was embedded into a new software program, allowing for automated determination of these properties from a single GC×GC analysis with minimal model training and parameter input. This process produces component maps that can be used to discern the mechanism and progression of how a particular site weathers due to dissolution, organic phase partitioning, and evaporation into the surrounding environment.

  15. Effect of horizontal and vertical resolution for wind resource assessment in Metro Manila, Philippines using Weather Research and Forecasting (WRF) model

    Science.gov (United States)

    Tolentino, Jerome T.; Rejuso, Ma. Victoria; Inocencio, Loureal Camille; Ang, Ma. Rosario Concepcion; Bagtasa, Gerry

    2016-10-01

    Wind energy is one of the best options for renewable energy such that, many researchers work on wind resource assessment, specifically using numerical weather prediction (NWP) model to forecast atmospheric behavior on a given domain. In addition, every combination of parameterization configuration influences wind assessment. At the same time, choosing the optimum vertical and horizontal resolution may affect its output and processing time. Regardless of available researches, most of them focuses on mid-latitude area but not in tropical areas like the Philippines. In the study, sensitivity analysis of Weather Research and Forecasting (WRF) model version 3.6.1 with 4 configurations was performed. The duration of the simulation was from January 1, 2014 00:00 to December 31, 2014 23:00. The parameters involved were horizontal resolution and vertical levels. Also, meteorological input data from NCEP Final Analysis with 1 degree resolution every 6 hours was used. For validation, wind speed measurements at 10 m height from NOAA Integrated Surface Database (ISD) were utilized, of which, the 3 weather stations are located in Manila, Science Garden and Ninoy Aquino International Airport (NAIA). The results show that increasing horizontal resolution from 4 km to 1 km have no significant increase to wind speed accuracy. In majority, higher vertical levels tend to increase its accuracy. Moreover, the model has higher accuracy during the rainy season and months of April and May. Overall, the model overestimated the observed wind speed but the diurnal cycle of wind speed follows all the simulation.

  16. Weather in Your Life.

    Science.gov (United States)

    Kannegieter, Sandy; Wirkler, Linda

    Facts and activities related to weather and meteorology are presented in this unit. Separate sections cover the following topics: (1) the water cycle; (2) clouds; (3) the Beaufort Scale for rating the speed and force of wind; (4) the barometer; (5) weather prediction; (6) fall weather in Iowa (sleet, frost, and fog); (7) winter weather in Iowa…

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

    Directory of Open Access Journals (Sweden)

    J. W. Kaminski

    2007-10-01

    Full Text Available Tropospheric chemistry and air quality processes were implemented on-line in the Global Environmental Multiscale model. The integrated model, GEM-AQ, has been developed as a platform to investigate chemical weather at scales from global to urban. The model was exercised for five years (2001–2005 to evaluate its ability to simulate seasonal variations and regional distributions of trace gases such as ozone, nitrogen dioxide and carbon monoxide on the global scale. The model results presented are compared with observations from satellites, aircraft measurement campaigns and balloon sondes.

  18. The chemistry CATT–BRAMS model (CCATT–BRAMS 4.5: a regional atmospheric model system for integrated air quality and weather forecasting and research

    Directory of Open Access Journals (Sweden)

    K. M. Longo

    2013-02-01

    Full Text Available The Coupled Chemistry Aerosol-Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CCATT–BRAMS, version 4.5 is an online regional chemical transport model designed for local and regional studies of atmospheric chemistry from surface to the lower stratosphere suitable both for operational and research purposes. It includes gaseous/aqueous chemistry, photochemistry, scavenging and dry deposition. The CCATT–BRAMS model takes advantages of the BRAMS specific development for the tropics/subtropics and of the recent availability of preprocessing tools for chemical mechanisms and of fast codes for photolysis rates. BRAMS includes state-of-the-art physical parameterizations and dynamic formulations to simulate atmospheric circulations of scales down to meters. The online coupling between meteorology and chemistry allows the system to be used for simultaneous atmospheric weather and chemical composition forecasts as well as potential feedbacks between them. The entire system comprises three preprocessing software tools for chemical mechanism (which are user defined, aerosol and trace gases emission fields and atmospheric and chemistry fields for initial and boundary conditions. In this paper, the model description is provided along evaluations performed using observational data obtained from ground-based stations, instruments aboard of aircrafts and retrieval from space remote sensing. The evaluation takes into account model application on different scales from megacities and Amazon Basin up to intercontinental region of the Southern Hemisphere.

  19. The Chemistry CATT-BRAMS model (CCATT-BRAMS 4.5: a regional atmospheric model system for integrated air quality and weather forecasting and research

    Directory of Open Access Journals (Sweden)

    K. M. Longo

    2013-09-01

    Full Text Available Coupled Chemistry Aerosol-Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CCATT-BRAMS, version 4.5 is an on-line regional chemical transport model designed for local and regional studies of atmospheric chemistry from the surface to the lower stratosphere suitable both for operational and research purposes. It includes gaseous/aqueous chemistry, photochemistry, scavenging and dry deposition. The CCATT-BRAMS model takes advantage of BRAMS-specific development for the tropics/subtropics as well as the recent availability of preprocessing tools for chemical mechanisms and fast codes for photolysis rates. BRAMS includes state-of-the-art physical parameterizations and dynamic formulations to simulate atmospheric circulations down to the meter. This on-line coupling of meteorology and chemistry allows the system to be used for simultaneous weather and chemical composition forecasts as well as potential feedback between the two. The entire system is made of three preprocessing software tools for user-defined chemical mechanisms, aerosol and trace gas emissions fields and the interpolation of initial and boundary conditions for meteorology and chemistry. In this paper, the model description is provided along with the evaluations performed by using observational data obtained from ground-based stations, instruments aboard aircrafts and retrieval from space remote sensing. The evaluation accounts for model applications at different scales from megacities and the Amazon Basin up to the intercontinental region of the Southern Hemisphere.

  20. Impact of aerosols on the forecast accuracy of solar irradiance calculated by a numerical weather prediction model

    Science.gov (United States)

    Shimose, Ken-ichi; Ohtake, Hideaki; Fonseca, Joao Gari da Silva; Takashima, Takumi; Oozeki, Takashi; Yamada, Yoshinori

    2014-10-01

    The impact of aerosols on the forecast accuracy of solar irradiance calculated by a fine-scale, one day-ahead, and operational numerical weather prediction model (NWP) is investigated in this study. In order to investigate the impact of aerosols only, the clear sky period is chosen, which is defined as when there are no clouds in the observation data and in the forecast data at the same time. The evaluation of the forecast accuracy of the solar irradiance is done at a single observation point that is sometimes affected by aerosol events. The analysis period is one year from April 2010 to March 2011. During the clear sky period, the root mean square errors (RMSE) of the global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance (DHI) are 40.0 W m-2, 84.0 Wm-2, and 47.9 W m-2, respectively. During one extreme event, the RMSEs of the GHI, DNI, and DHI are 70.1 W m-2, 211.6 W m-2, and 141.7 W m-2, respectively. It is revealed that the extreme events were caused by aerosols such as dust or haze. In order to investigate the impact of the aerosols, the sensitivity experiments of the aerosol optical depth (AOD) for the extreme events are executed. The best result is obtained by changing the AOD to 2.5 times the original AOD. This changed AOD is consistent with the satellite observation. Thus, it is our conclusion that an accurate aerosol forecast is important for the forecast accuracy of the solar irradiance.

  1. 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.

    2016-07-01

    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.

  2. 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.

  3. 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

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

    Science.gov (United States)

    Pineda, Luis E.; Willems, Patrick

    2017-04-01

    Weather and climatic characterization of rainfall extremes is both of scientific and societal value for hydrometeorogical risk management, yet discrimination of local and large-scale forcing remains challenging in data-scarce and complex terrain environments. Here, we present an analysis framework that separate weather (seasonal) regimes and climate (inter-annual) influences using data-driven process identification. The approach is based on signal-to-noise separation methods and extreme value (EV) modeling of multisite rainfall extremes. The EV models use a semi-automatic parameter learning [1] for model identification across temporal scales. At weather scale, the EV models are combined with a state-based hidden Markov model [2] to represent the spatio-temporal structure of rainfall as persistent weather states. At climatic scale, the EV models are used to decode the drivers leading to the shift of weather patterns. The decoding is performed into a climate-to-weather signal subspace, built via dimension reduction of climate model proxies (e.g. sea surface temperature and atmospheric circulation) We apply the framework to the Western Andean Ridge (WAR) in Ecuador and Peru (0-6°S) using ground data from the second half of the 20th century. We find that the meridional component of winds is what matters for the in-year and inter-annual variability of high rainfall intensities alongside the northern WAR (0-2.5°S). There, low-level southerly winds are found as advection drivers for oceanic moist of the normal-rainy season and weak/moderate the El Niño (EN) type; but, the strong EN type and its unique moisture surplus is locally advected at lowlands in the central WAR. Moreover, the coastal ridges, south of 3°S dampen meridional airflows, leaving local hygrothermal gradients to control the in-year distribution of rainfall extremes and their anomalies. Overall, we show that the framework, which does not make any prior assumption on the explanatory power of the weather

  5. 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

  6. The Chemistry CATT-BRAMS model : a regional atmospheric model system for integrated air quality and weather forecasting and research

    National Research Council Canada - National Science Library

    Longo, K. M; Freitas, S. R; Pirre, M; Marécal, V; Rodrigues, L. F; Panetta, J; Alonso, M. F; Rosário, N. E; Moreira, D. S; Gácita, M. S; Arteta, J; Fonseca, R; Stockler, R; Katsurayama, D. M; Fazenda, A; Bela, M

    2013-01-01

    ... (CCATT-BRAMS, version 4.5) is an on-line regional chemical transport model designed for local and regional studies of atmospheric chemistry from the surface to the lower stratosphere suitable both for operational and research purposes...

  7. On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model

    Energy Technology Data Exchange (ETDEWEB)

    Grell, Georg; Fast, Jerome D.; Gustafson, William I.; Peckham, Steven E.; McKeen, Stuart A.; Salzmann, Marc; Freitas, Saulo

    2010-01-01

    This is a conference proceeding that is now being put together as a book. This is chapter 2 of the book: "INTEGRATED SYSTEMS OF MESO-METEOROLOGICAL AND CHEMICAL TRANSPORT MODELS" published by Springer. The chapter title is "On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model." The original conference was the COST-728/NetFAM workshop on Integrated systems of meso-meteorological and chemical transport models, Danish Meteorological Institute, Copenhagen, May 21-23, 2007.

  8. 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

  9. Cascading model uncertainty from medium range weather forecasts (10 days through a rainfall-runoff model to flood inundation predictions within the European Flood Forecasting System (EFFS

    Directory of Open Access Journals (Sweden)

    F. Pappenberger

    2005-01-01

    Full Text Available The political pressure on the scientific community to provide medium to long term flood forecasts has increased in the light of recent flooding events in Europe. Such demands can be met by a system consisting of three different model components (weather forecast, rainfall-runoff forecast and flood inundation forecast which are all liable to considerable uncertainty in the input, output and model parameters. Thus, an understanding of cascaded uncertainties is a necessary requirement to provide robust predictions. In this paper, 10-day ahead rainfall forecasts, consisting of one deterministic, one control and 50 ensemble forecasts, are fed into a rainfall-runoff model (LisFlood for which parameter uncertainty is represented by six different parameter sets identified through a Generalised Likelihood Uncertainty Estimation (GLUE analysis and functional hydrograph classification. The runoff of these 52 * 6 realisations form the input to a flood inundation model (LisFlood-FP which acknowledges uncertainty by utilising ten different sets of roughness coefficients identified using the same GLUE methodology. Likelihood measures for each parameter set computed on historical data are used to give uncertain predictions of flow hydrographs as well as spatial inundation extent. This analysis demonstrates that a full uncertainty analysis of such an integrated system is limited mainly by computer power as well as by how well the rainfall predictions represent potential future conditions. However, these restrictions may be overcome or lessened in the future and this paper establishes a computationally feasible methodological approach to the uncertainty cascade problem.

  10. 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.

  11. INTRAVAL phase 2, test case 8. Alligator Rivers Natural Analogue. Modelling of uranium transport in the weathered zone at Koongarra, Australia

    Energy Technology Data Exchange (ETDEWEB)

    Hassanizadeh, S.M.; Van de Weerd, H.; Richardson-Van der Poel, M.A. [National Inst. of Public Health and Environmental Protection RIVM, Bilthoven (Netherlands)

    1993-01-01

    Preliminary results of modelling of the dispersion of uranium in the weathered and transition zones are given. In the course of the Alligator Rivers Analogue Project (ARAP) more insight was gained about the formation of the dispersion fan and about the hydrology at Koongarra. The here applied transport modelling strategy takes into account those results. First, a general explanation of Natural Analogue is given, next to a brief description of the ARAP test case, carried out within the INTRAVAL phase 2. INTRAVAL is an international project concerned with the use of mathematical models for predicting the potential transport of radioactive solutes in the geosphere. Following is the analysis of chemical data, necessary for the choice of the modelling approach, for estimation of model inputs and for testing model results. Subsequently, the modelling strategy is expounded and a description is given of METROPOL, the transport code, used for modelling. 11 figs., 2 tabs., 1 appendix, 17 refs.

  12. A stochastic ensemble-based model to predict crop water requirements from numerical weather forecasts and VIS-NIR high resolution satellite images in Southern Italy

    Science.gov (United States)

    Pelosi, Anna; Falanga Bolognesi, Salvatore; De Michele, Carlo; Medina Gonzalez, Hanoi; Villani, Paolo; D'Urso, Guido; Battista Chirico, Giovanni

    2015-04-01

    Irrigation agriculture is one the biggest consumer of water in Europe, especially in southern regions, where it accounts for up to 70% of the total water consumption. The EU Common Agricultural Policy, combined with the Water Framework Directive, imposes to farmers and irrigation managers a substantial increase of the efficiency in the use of water in agriculture for the next decade. Ensemble numerical weather predictions can be valuable data for developing operational advisory irrigation services. We propose a stochastic ensemble-based model providing spatial and temporal estimates of crop water requirements, implemented within an advisory service offering detailed maps of irrigation water requirements and crop water consumption estimates, to be used by water irrigation managers and farmers. The stochastic model combines estimates of crop potential evapotranspiration retrieved from ensemble numerical weather forecasts (COSMO-LEPS, 16 members, 7 km resolution) and canopy parameters (LAI, albedo, fractional vegetation cover) derived from high resolution satellite images in the visible and near infrared wavelengths. The service provides users with daily estimates of crop water requirements for lead times up to five days. The temporal evolution of the crop potential evapotranspiration is simulated with autoregressive models. An ensemble Kalman filter is employed for updating model states by assimilating both ground based meteorological variables (where available) and numerical weather forecasts. The model has been applied in Campania region (Southern Italy), where a satellite assisted irrigation advisory service has been operating since 2006. This work presents the results of the system performance for one year of experimental service. The results suggest that the proposed model can be an effective support for a sustainable use and management of irrigation water, under conditions of water scarcity and drought. Since the evapotranspiration term represents a staple

  13. Linking Satellite-Derived Fire Counts to Satellite-Derived Weather Data in Fire Prediction Models to Forecast Extreme Fires in Siberia

    Science.gov (United States)

    Westberg, D. J.; Soja, A. J.; Stackhouse, P. W.

    2009-12-01

    Fire is the dominant disturbance that precipitates ecosystem change in boreal regions, and fire is largely under the control of weather and climate. Fire frequency, fire severity, area burned and fire season length are predicted to increase in boreal regions under climate change scenarios. Therefore to predict fire weather and ecosystem change, we must understand the factors that influence fire regimes and at what scale these are viable. The Canadian Fire Weather Index (FWI), developed by the Canadian Forestry Service, is used for this comparison, and it is calculated using local noon surface-level air temperature, relative humidity, wind speed, and daily (noon-noon) rainfall. The FWI assesses daily forest fire burning potential. Large-scale FWI are calculated at the NASA Langley Research Center (LaRC) using NASA Goddard Earth Observing System version 4 (GEOS-4) large-scale reanalysis and NASA Global Precipitation Climatology Project (GPCP) data. The GEOS-4 reanalysis weather data are 3-hourly interpolated to 1-hourly data at a 1ox1o resolution and the GPCP precipitation data are also at 1ox1o resolution. In previous work focusing on the fire season in Siberia in 1999 and 2002, we have shown the combination of GEOS-4 weather data and Global Precipitation Climatology Project (GPCP) precipitation data compares well to ground-based weather data when used as inputs for FWI calculation. The density and accuracy of Siberian surface station data can be limited, which leads to results that are not representative of the spatial reality. GEOS-4/GPCP-dervied FWI can serve to spatially enhance current and historic FWI, because these data are spatially and temporally consistency. The surface station and model reanalysis derived fire weather indices compared well spatially, temporally and quantitatively, and increased fire activity compares well with increasing FWI ratings. To continue our previous work, we statistically compare satellite-derived fire counts to FWI categories at

  14. Preliminary Results of a U.S. Deep South Modeling Experiment Using NASA SPoRT Initialization Datasets for Operational National Weather Service Local Model Runs

    Science.gov (United States)

    Wood, Lance; Medlin, Jeffrey M.; Case, Jon

    2012-01-01

    A joint collaborative modeling effort among the NWS offices in Mobile, AL, and Houston, TX, and NASA Short-term Prediction Research and Transition (SPoRT) Center began during the 2011-2012 cold season, and continued into the 2012 warm season. The focus was on two frequent U.S. Deep South forecast challenges: the initiation of deep convection during the warm season; and heavy precipitation during the cold season. We wanted to examine the impact of certain NASA produced products on the Weather Research and Forecasting Environmental Modeling System in improving the model representation of mesoscale boundaries such as the local sea-, bay- and land-breezes (which often leads to warm season convective initiation); and improving the model representation of slow moving, or quasi-stationary frontal boundaries (which focus cold season storm cell training and heavy precipitation). The NASA products were: the 4-km Land Information System, a 1-km sea surface temperature analysis, and a 4-km greenness vegetation fraction analysis. Similar domains were established over the southeast Texas and Alabama coastlines, each with an outer grid with a 9 km spacing and an inner nest with a 3 km grid spacing. The model was run at each NWS office once per day out to 24 hours from 0600 UTC, using the NCEP Global Forecast System for initial and boundary conditions. Control runs without the NASA products were made at the NASA SPoRT Center. The NCAR Model Evaluation Tools verification package was used to evaluate both the positive and negative impacts of the NASA products on the model forecasts. Select case studies will be presented to highlight the influence of the products.

  15. 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

  16. 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...

  17. Project Weather and Water.

    Science.gov (United States)

    Hansen, Pal J. Kirkeby

    2000-01-01

    Introduces Project Weather and Water with the goal of developing and testing ideas of how to implement weather topics and water physics in an integrated way. Discusses teacher preparation, implementation, and evaluation of this project. (ASK)

  18. 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...

  19. 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...

  20. 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...

  1. Surface Weather Observing Manuals

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Manuals and instructions for taking weather observations. Includes the annual Weather Bureau 'Instructions for Preparing Meteorological Forms...' and early airways...

  2. 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...

  3. 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. ...

  4. 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...

  5. 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...

  6. 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...

  7. Evaluating sensitivity of silicate mineral dissolution rates to physical weathering using a soil evolution model (SoilGen2.25)

    Science.gov (United States)

    Opolot, E.; Finke, P. A.

    2015-11-01

    Silicate mineral dissolution rates depend on the interaction of a number of factors categorized either as intrinsic (e.g. mineral surface area, mineral composition) or extrinsic (e.g. climate, hydrology, biological factors, physical weathering). Estimating the integrated effect of these factors on the silicate mineral dissolution rates therefore necessitates the use of fully mechanistic soil evolution models. This study applies a mechanistic soil evolution model (SoilGen) to explore the sensitivity of silicate mineral dissolution rates to the integrated effect of other soil-forming processes and factors. The SoilGen soil evolution model is a 1-D model developed to simulate the time-depth evolution of soil properties as a function of various soil-forming processes (e.g. water, heat and solute transport, chemical and physical weathering, clay migration, nutrient cycling, and bioturbation) driven by soil-forming factors (i.e., climate, organisms, relief, parent material). Results from this study show that although soil solution chemistry (pH) plays a dominant role in determining the silicate mineral dissolution rates, all processes that directly or indirectly influence the soil solution composition play an equally important role in driving silicate mineral dissolution rates. Model results demonstrated a decrease of silicate mineral dissolution rates with time, an obvious effect of texture and an indirect but substantial effect of physical weathering on silicate mineral dissolution rates. Results further indicated that clay migration and plant nutrient recycling processes influence the pH and thus the silicate mineral dissolution rates. Our silicate mineral dissolution rates results fall between field and laboratory rates but were rather high and more close to the laboratory rates possibly due to the assumption of far from equilibrium reaction used in our dissolution rate mechanism. There is therefore a need to include secondary mineral precipitation mechanism in our

  8. 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.

  9. Weather Fundamentals: Meteorology. [Videotape].

    Science.gov (United States)

    1998

    The videos in this educational series, for grades 4-7, help students understand the science behind weather phenomena through dramatic live-action footage, vivid animated graphics, detailed weather maps, and hands-on experiments. This episode (23 minutes) looks at how meteorologists gather and interpret current weather data collected from sources…

  10. Cold-Weather Sports

    Science.gov (United States)

    ... Surgery? A Week of Healthy Breakfasts Shyness Cold-Weather Sports KidsHealth > For Teens > Cold-Weather Sports A A A What's in this article? ... Equipment Ahh, winter! Shorter days. Frigid temperatures. Foul weather. What better time to be outdoors? Winter sports ...

  11. Convective Weather Avoidance with Uncertain Weather Forecasts

    Science.gov (United States)

    Karahan, Sinan; Windhorst, Robert D.

    2009-01-01

    Convective weather events have a disruptive impact on air traffic both in terminal area and in en-route airspaces. In order to make sure that the national air transportation system is safe and efficient, it is essential to respond to convective weather events effectively. Traffic flow control initiatives in response to convective weather include ground delay, airborne delay, miles-in-trail restrictions as well as tactical and strategic rerouting. The rerouting initiatives can potentially increase traffic density and complexity in regions neighboring the convective weather activity. There is a need to perform rerouting in an intelligent and efficient way such that the disruptive effects of rerouting are minimized. An important area of research is to study the interaction of in-flight rerouting with traffic congestion or complexity and developing methods that quantitatively measure this interaction. Furthermore, it is necessary to find rerouting solutions that account for uncertainties in weather forecasts. These are important steps toward managing complexity during rerouting operations, and the paper is motivated by these research questions. An automated system is developed for rerouting air traffic in order to avoid convective weather regions during the 20- minute - 2-hour time horizon. Such a system is envisioned to work in concert with separation assurance (0 - 20-minute time horizon), and longer term air traffic management (2-hours and beyond) to provide a more comprehensive solution to complexity and safety management. In this study, weather is dynamic and uncertain; it is represented as regions of airspace that pilots are likely to avoid. Algorithms are implemented in an air traffic simulation environment to support the research study. The algorithms used are deterministic but periodically revise reroutes to account for weather forecast updates. In contrast to previous studies, in this study convective weather is represented as regions of airspace that pilots

  12. Simulating the meteorology and PM10 concentrations in Arizona dust storms with the Weather Research and Forecasting model with Chemistry (Wrf-Chem).

    Science.gov (United States)

    Hyde, Peter; Mahalov, Alex; Li, Jialun

    2017-07-24

    Nine dust storms in south-central Arizona, USA 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 PM10 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 microns and smaller ([PM10]).Furthermore, the model under-estimated [PM10] in highly agricultural Pinal County because it under-estimated 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 over-estimated [PM10] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) whose surface-layer speeds were too strong. In Phoenix the model's performance depended on the event, with both under- and over-estimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM10] highly rely on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM10] in that region. Both 24-hr and 1-hr measured [PM10] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as tenfold and the latter exceeding health-based guidelines by as much as seventy-fold. Monsoonal thunderstorms not only produce elevated [PM10], but also cause 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 observations, additional

  13. Prediction Techniques in Operational Space Weather Forecasting

    Science.gov (United States)

    Zhukov, Andrei

    2016-07-01

    The importance of forecasting space weather conditions is steadily increasing as our society is becoming more and more dependent on advanced technologies that may be affected by disturbed space weather. Operational space weather forecasting is still a difficult task that requires the real-time availability of input data and specific prediction techniques that are reviewed in this presentation, with an emphasis on solar and interplanetary weather. Key observations that are essential for operational space weather forecasting are listed. Predictions made on the base of empirical and statistical methods, as well as physical models, are described. Their validation, accuracy, and limitations are discussed in the context of operational forecasting. Several important problems in the scientific basis of predicting space weather are described, and possible ways to overcome them are discussed, including novel space-borne observations that could be available in future.

  14. Hands-on, online, and workshop-based K-12 weather and climate education resources from the Center for Multi-scale Modeling of Atmospheric Processes

    Science.gov (United States)

    Foster, S. Q.; Johnson, R. M.; Randall, D. A.; Denning, A.; Burt, M. A.; Gardiner, L.; Genyuk, J.; Hatheway, B.; Jones, B.; La Grave, M. L.; Russell, R. M.

    2009-12-01

    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 fourth year, the National Science Foundation-funded Center for Multi-scale Modeling of Atmospheric Processes (CMMAP) at Colorado State University (CSU) 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. This is accomplished through collaborations in resource development and dissemination between CMMAP scientists, CSU’s Little Shop of Physics (LSOP) program, and the Windows to the Universe (W2U) program at University Corporation for Atmospheric Research (UCAR). Little Shop of Physics develops new hands on science activities demonstrating basic science concepts fundamental to understanding atmospheric characteristics, weather, and climate. Videos capture demonstrations of children completing these activities which are broadcast to school districts and public television programs. CMMAP and LSOP educators and scientists partner in teaching a summer professional development workshops for teachers at CSU with a semester's worth of college-level content on the basic physics of the atmosphere, weather, climate, climate modeling, and climate change, as well as dozens of LSOP inquiry-based activities suitable for use in classrooms. The W2U project complements these efforts by developing and broadly disseminating new CMMAP-related online content pages, animations, interactives, image galleries, scientists’ biographies, and LSOP videos to K-12 and public audiences. Reaching nearly 20 million users annually, W2U is highly valued as a curriculum enhancement

  15. 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...... 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...

  16. 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.

  17. The impact of a thermodynamic sea-ice module in the COSMO numerical weather prediction model on simulations for the Laptev Sea, Siberian Arctic

    Directory of Open Access Journals (Sweden)

    David Schröder

    2011-05-01

    Full Text Available Previous versions of the Consortium for Small-scale Modelling (COSMO numerical weather prediction model have used a constant sea-ice surface temperature, but observations show a high degree of variability on sub-daily timescales. To account for this, we have implemented a thermodynamic sea-ice module in COSMO and performed simulations at a resolution of 15 km and 5 km for the Laptev Sea area in April 2008. Temporal and spatial variability of surface and 2-m air temperature are verified by four automatic weather stations deployed along the edge of the western New Siberian polynya during the Transdrift XIII-2 expedition and by surface temperature charts derived from Moderate Resolution Imaging Spectroradiometer (MODIS satellite data. A remarkable agreement between the new model results and these observations demonstrates that the implemented sea-ice module can be applied for short-range simulations. Prescribing the polynya areas daily, our COSMO simulations provide a high-resolution and high-quality atmospheric data set for the Laptev Sea for the period 14–30 April 2008. Based on this data set, we derive a mean total sea-ice production rate of 0.53 km3/day for all Laptev Sea polynyas under the assumption that the polynyas are ice-free and a rate of 0.30 km3/day if a 10-cm-thin ice layer is assumed. Our results indicate that ice production in Laptev Sea polynyas has been overestimated in previous studies.

  18. Medium-range fire weather forecasts

    Science.gov (United States)

    J.O. Roads; K. Ueyoshi; S.C. Chen; J. Alpert; F. Fujioka

    1991-01-01

    The forecast skill of theNational Meteorological Center's medium range forecast (MRF) numerical forecasts of fire weather variables is assessed for the period June 1,1988 to May 31,1990. Near-surface virtual temperature, relative humidity, wind speed and a derived fire weather index (FWI) are forecast well by the MRF model. However, forecast relative humidity has...

  19. Weathering of ordinary chondrites from Oman: Correlation of weathering parameters with 14C terrestrial ages and a refined weathering scale

    Science.gov (United States)

    Zurfluh, Florian J.; Hofmann, Beda A.; Gnos, Edwin; Eggenberger, Urs; Jull, A. J. Timothy

    2016-09-01

    We have investigated 128 14C-dated ordinary chondrites from Oman for macroscopically visible weathering parameters, for thin section-based weathering degrees, and for chemical weathering parameters as analyzed with handheld X-ray fluorescence. These 128 14C-dated meteorites show an abundance maximum of terrestrial age at 19.9 ka, with a mean of 21.0 ka and a pronounced lack of samples between 0 and 10 ka. The weathering degree is evaluated in thin section using a refined weathering scale based on the current W0 to W6 classification of Wlotzka (1993), with five newly included intermediate steps resulting in a total of nine (formerly six) steps. We find significant correlations between terrestrial ages and several macroscopic weathering parameters. The correlation of various chemical parameters including Sr and Ba with terrestrial age is not very pronounced. The microscopic weathering degree of metal and sulfides with newly added intermediate steps shows the best correlation with 14C terrestrial ages, demonstrating the significance of the newly defined weathering steps. We demonstrate that the observed 14C terrestrial age distribution can be modeled from the abundance of meteorites with different weathering degrees, allowing the evaluation of an age-frequency distribution for the whole meteorite population.

  20. 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

  1. 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

  2. Evidence for biological mediation of K and P weathering inferred from a new process-based soil evolution model and soil chronosequences from Hawaii

    Science.gov (United States)

    Johnson, M.; Gloor, E.

    2012-12-01

    The productivity of many tropical forests is limited by the availability of nutrients such as phosphorus (P). Nutrient limitation thus has consequences for the global climate because it alters the response of vegetation productivity to changing CO2 concentrations. The amount of mineral derived nutrients available to vegetation depends upon a number of factors such as the age of the soil, the weatherability of rock minerals, the mechanism of nutrient uptake by the vegetation and the leaching intensity of the soils. An understanding of the interactions between pedogenetic processes and nutrient cycling can therefore enhance our understanding of ecosystem dynamics. Studies examining the interactions between soil processes and nutrient availability are limited, mainly because of the long timescales over which many of these processes operate and of the difficulty in isolating individual soil processes. Data from soil climate-sequences and chronosequences can potentially shed light on these interactions when combined with a model which includes soil forming processes over pedogenic timescales. We have developed a process-based soil evolution model which can be evaluated with measurements of soil properties in order to understand such biogeochemical cycles. The mechanistic, soil evolution model presented includes the major processes of soil formation including i) mineral weathering, ii) percolation of rainfall, iii) leaching of solutes, iv) surface erosion, v) bioturbation and vi) vegetation-soil interactions. The specific properties the model simulates over timescales of tens to hundreds of thousand years are, soil depth, vertical profiles of elemental composition, soil solution pH and organic carbon distribution. Modelled soil properties are compared with measured soil properties from basaltic soil chronosequences in Hawaii. The model generally agrees well with the soil chronosequences. Here we focus on one particularly interesting result regarding the role of the

  3. Weather pattern climatology of the United States