WorldWideScience

Sample records for model weather research

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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.

  7. 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

  8. 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,...

  9. 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)...

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. Japanese space weather research activities

    Science.gov (United States)

    Ishii, M.

    2017-01-01

    In this paper, we present existing and planned Japanese space weather research activities. The program consists of several core elements, including a space weather prediction system using numerical forecasts, a large-scale ground-based observation network, and the cooperative framework "Project for Solar-Terrestrial Environment Prediction (PSTEP)" based on a Grant-in Aid for Scientific Research on Innovative Areas.

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. 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.

  6. Space weather research and forecast in USA

    CERN Document Server

    Pevtsov, Alexei A

    2016-01-01

    In the United States, scientific research in space weather is funded by several Government Agencies including the National Science Foundation (NSF) and the National Aeronautics and Space Agency (NASA). For commercial purposes, space weather forecast is made by the Space Weather Prediction Center (SWPC) of the National Oceanic and Atmospheric Administration (NOAA). Observations come from the network of groundbased observatories funded via various sources, as well as from the instruments on spacecraft. Numerical models used in forecast are developed in the framework of individual research projects. Later, the most promising models are selected for additional testing at SWPC. In order to increase the application of models in research and education, NASA in collaboration with other agencies created Community Coordinated Modeling Center (CCMC). In mid-1990, US scientific community presented compelling evidence for developing the National Program on Space Weather, and in 1995, such program has been formally created...

  7. 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.

  8. 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.

  9. 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

  10. 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...

  11. 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.

  12. Space Weather Research: Indian perspective

    Science.gov (United States)

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

    2016-12-01

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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  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. CCMC: Serving research and space weather communities with unique space weather services, innovative tools and resources

    Science.gov (United States)

    Zheng, Yihua; Kuznetsova, Maria M.; Pulkkinen, Antti; Maddox, Marlo

    2015-04-01

    With the addition of Space Weather Research Center (a sub-team within CCMC) in 2010 to address NASA’s own space weather needs, CCMC has become a unique entity that not only facilitates research through providing access to the state-of-the-art space science and space weather models, but also plays a critical role in providing unique space weather services to NASA robotic missions, developing innovative tools and transitioning research to operations via user feedback. With scientists, forecasters and software developers working together within one team, through close and direct connection with space weather customers and trusted relationship with model developers, CCMC is flexible, nimble and effective to meet customer needs. In this presentation, we highlight a few unique aspects of CCMC/SWRC’s space weather services, such as addressing space weather throughout the solar system, pushing the frontier of space weather forecasting via the ensemble approach, providing direct personnel and tool support for spacecraft anomaly resolution, prompting development of multi-purpose tools and knowledge bases, and educating and engaging the next generation of space weather scientists.

  4. 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.

  5. 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.

  6. 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

  7. NASA Space Weather Research Center: Addressing the Unique Space Weather Needs of NASA Robotic Missions

    Science.gov (United States)

    Zheng, Y.; Pulkkinen, A. A.; Kuznetsova, M. M.; Maddox, M. M.; Mays, M. L.; Taktakishvili, A.; Chulaki, A.; Thompson, B. J.; Collado-Vega, Y. M.; Muglach, K.; Evans, R. M.; Wiegand, C.; MacNeice, P. J.; Rastaetter, L.

    2014-12-01

    The Space Weather Research Center (SWRC) has been providing space weather monitoring and forecasting services to NASA's robotic missions since its establishment in 2010. Embedded within the Community Coordinated Modeling Center (CCMC) (see Maddox et al. in Session IN026) and located at NASA Goddard Space Flight Center, SWRC has easy access to state-of-the-art modeling capabilities and proximity to space science and research expertise. By bridging space weather users and the research community, SWRC has been a catalyst for the efficient transition from research to operations and operations to research. In this presentation, we highlight a few unique aspects of SWRC's space weather services, such as addressing space weather throughout the solar system, pushing the frontier of space weather forecasting via the ensemble approach, providing direct personnel and tool support for spacecraft anomaly resolution, prompting development of multi-purpose tools and knowledge bases (see Wiegand et al. in the same session SM004), and educating and engaging the next generation of space weather scientists.

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. 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...

  13. Ionospheric research for space weather service support

    Science.gov (United States)

    Stanislawska, Iwona; Gulyaeva, Tamara; Dziak-Jankowska, Beata

    2016-07-01

    Knowledge of the behavior of the ionosphere is very important for space weather services. A wide variety of ground based and satellite existing and future systems (communications, radar, surveillance, intelligence gathering, satellite operation, etc) is affected by the ionosphere. There are the needs for reliable and efficient support for such systems against natural hazard and minimalization of the risk failure. The joint research Project on the 'Ionospheric Weather' of IZMIRAN and SRC PAS is aimed to provide on-line the ionospheric parameters characterizing the space weather in the ionosphere. It is devoted to science, techniques and to more application oriented areas of ionospheric investigation in order to support space weather services. The studies based on data mining philosophy increasing the knowledge of ionospheric physical properties, modelling capabilities and gain applications of various procedures in ionospheric monitoring and forecasting were concerned. In the framework of the joint Project the novel techniques for data analysis, the original system of the ionospheric disturbance indices and their implementation for the ionosphere and the ionospheric radio wave propagation are developed since 1997. Data of ionosonde measurements and results of their forecasting for the ionospheric observatories network, the regional maps and global ionospheric maps of total electron content from the navigational satellite system (GNSS) observations, the global maps of the F2 layer peak parameters (foF2, hmF2) and W-index of the ionospheric variability are provided at the web pages of SRC PAS and IZMIRAN. The data processing systems include analysis and forecast of geomagnetic indices ap and kp and new eta index applied for the ionosphere forecasting. For the first time in the world the new products of the W-index maps analysis are provided in Catalogues of the ionospheric storms and sub-storms and their association with the global geomagnetic Dst storms is

  14. 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.

  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. 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...

  17. 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.

  18. 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.

  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

    2013-02-01

    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.

  20. 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.

  1. 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.

  2. Planetary Space Weather Services for the Europlanet 2020 Research Infrastructure

    Science.gov (United States)

    André, N.; Grande, M.

    2015-10-01

    Under Horizon 2020, the Europlanet 2020 Research Infrastructure (EPN2020-RI) will include an entirely new Virtual Access Service, WP5 VA1 "Planetary Space Weather Services" (PSWS) that will extend the concepts of space weather and space situational awareness to other planets in our Solar System and in particular to spacecraft that voyage through it. VA1 will make five entirely new 'toolkits' accessible to the research community and to industrial partners planning for space missions: a general planetary space weather toolkit, as well as three toolkits dedicated to the following key planetary environments: Mars (in support ExoMars), comets (building on the expected success of the ESA Rosetta mission), and outer planets (in preparation for the ESA JUICE mission to be launched in 2022). This will give the European planetary science community new methods, interfaces, functionalities and/or plugins dedicated to planetary space weather in the tools and models available within the partner institutes. It will also create a novel event-diary toolkit aiming at predicting and detecting planetary events like meteor showers and impacts. A variety of tools (in the form of web applications, standalone software, or numerical models in various degrees of implementation) are available for tracing propagation of planetary and/or solar events through the Solar System and modelling the response of the planetary environment (surfaces, atmospheres, ionospheres, and magnetospheres) to those events. But these tools were not originally designed for planetary event prediction and space weather applications. So WP10 JRA4 "Planetary Space Weather Services" (PSWS) will provide the additional research and tailoring required to apply them for these purposes. The overall objectives of this JRA will be to review, test, improve and adapt methods and tools available within the partner institutes in order to make prototype planetary event and space weather services operational in Europe at the end of

  3. Innovative Information Technology for Space Weather Research

    Science.gov (United States)

    Wang, H.; Qu, M.; Shih, F.; Denker, C.; Gerbessiotis, A.; Lofdahl, M.; Rees, D.; Keller, C.

    2004-05-01

    Solar activity is closely related to the near earth environment -- summarized descriptively as space weather. Changes in space weather have adverse effect on many aspects of life and systems on earth and in space. Real-time, high-quality data and data processing would be a key element to forecast space weather promptly and accurately. Recently, we obtained a funding from US National Science Foundation to apply innovative information technology for space weather prediction. (1) We use the technologies of image processing and pattern recognition, such as image morphology segmentation, Support Vector Machines (SVMs), and neural networks to detect and characterize three important solar activities in real-time: filament eruptions, flares, and emerging flux regions (EFRs). Combining the real time detection with the recent statistical study on the relationship among filament eruptions, flares, EFRs, coronal mass ejections (CMEs), and geomagnetic storms, we are establishing real time report of solar events and automatic forecasting of earth directed CMEs and subsequent geomagnetic storms. (2) We combine state-of-art parallel computing techniques with phase diverse speckle imaging techniques, to yield near real-time diffraction limited images with a cadence of approximately 10 sec. We utilize the multiplicity of parallel paradigms to optimize the calculation of phase diverse speckle imaging to improve calculation speed. With such data, we can monitor flare producing active regions continuously and carry out targeted studies of the evolution and flows in flare producing active regions. (3) We are developing Web based software tools to post our processed data, events and forecasting in real time, and to be integrated with current solar activity and space weather prediction Web pages at BBSO. This will also be a part of Virtual Solar Observatory (VSO) being developed by the solar physics community. This research is supported by NSF ITR program.

  4. Selective factors in sun-weather research

    Science.gov (United States)

    Taylor, H. A., Jr.

    1986-01-01

    Research on the correlations between solar wind/IMF disturbances and subsequent winter troposphere vorticity changes (denoted SV) are reviewed to investigate sun-weather relationships. Uncertainties in the research attempting to link short-term solar variations and associated changes in the lower atmosphere are discussed, and it is noted that such analyses have generally not addressed either the choice of parameters or the selective factors involved in the physical relationships existing between parameters. It is suggested that the identification of a viable mechanism scenario would require a detailed multiparameter selective factor analysis, extending to the investigation of the atmospheric data as well as the solar wind/IMF parameters.

  5. 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.

  6. 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

  7. 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

  8. Planetary Space Weather Services for the Europlanet 2020 Research Infrastructure

    Science.gov (United States)

    André, Nicolas; Grande, Manuel

    2016-04-01

    Under Horizon 2020, the Europlanet 2020 Research Infrastructure (EPN2020-RI) will include an entirely new Virtual Access Service, WP5 VA1 "Planetary Space Weather Services" (PSWS) that will extend the concepts of space weather and space situational awareness to other planets in our Solar System and in particular to spacecraft that voyage through it. VA1 will make five entirely new 'toolkits' accessible to the research community and to industrial partners planning for space missions: a general planetary space weather toolkit, as well as three toolkits dedicated to the following key planetary environments: Mars (in support ExoMars), comets (building on the expected success of the ESA Rosetta mission), and outer planets (in preparation for the ESA JUICE mission to be launched in 2022). This will give the European planetary science community new methods, interfaces, functionalities and/or plugins dedicated to planetary space weather in the tools and models available within the partner institutes. It will also create a novel event-diary toolkit aiming at predicting and detecting planetary events like meteor showers and impacts. A variety of tools (in the form of web applications, standalone software, or numerical models in various degrees of implementation) are available for tracing propagation of planetary and/or solar events through the Solar System and modelling the response of the planetary environment (surfaces, atmospheres, ionospheres, and magnetospheres) to those events. But these tools were not originally designed for planetary event prediction and space weather applications. So WP10 JRA4 "Planetary Space Weather Services" (PSWS) will provide the additional research and tailoring required to apply them for these purposes. The overall objectives of this Joint Research Aactivities will be to review, test, improve and adapt methods and tools available within the partner institutes in order to make prototype planetary event and space weather services operational in

  9. 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.

  10. Activity of Science and Operational Research of NICT Space Weather

    Science.gov (United States)

    Ishii, Mamoru; Nagatsuma, Tsutomu; Watari, Shinichi; Shinagawa, Hiroyuki; Tsugawa, Takuya; Kubo, Yuki

    Operational space weather forecast is for contribution to social infrastructure than for academic interests. These user need will determine the target of research, e.g., the precision level, spatial and temporal resolution and/or required lead time. We, NICT, aim two target in the present mid-term strategic plan, which are (1) forecast of ionospheric disturbance influencing to satellite positioning, and (2) forecast of disturbance in radiation belt influencing to satellite operation. We have our own observation network and develop empirical and numerical models for achieving each target. However in actual situation, it is much difficult to know the user needs quantitatively. Most of space weather phenomena makes the performance of social infrastructure poor, for example disconnect of HF communication, increase of GNSS error. Most of organizations related to these operation are negative to open these information. We have personal interviews to solve this issue. In this interview, we try to collect incident information related to space weather in each field, and to retrieve which space weather information is necessary for users. In this presentation we will introduce our research and corresponding new service, in addition to our recent scientific results.

  11. Development of the GPU-based Stony-Brook University 5-class microphysics scheme in the weather research and forecasting model

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.-L.; Goldberg, Mitchell D.

    2011-11-01

    Several bulk water microphysics schemes are available within the Weather Research and Forecasting (WRF) model, with different numbers of simulated hydrometeor classes and methods for estimating their size fall speeds, distributions and densities. Stony-Brook University (SBU-YLIN) microphysics scheme is a 5-class scheme with riming intensity predicted to account for mixed-phase processes. In this paper, we develop an efficient graphics processing unit (GPU) based SBU-YLIN scheme. The GPU-based SBU-YLIN scheme will be compared to a CPU-based single-threaded counterpart. The implementation achieves 213x speedup with I/O compared to a Fortran implementation running on a CPU. Without I/O the speedup is 896x.

  12. Investigation of boundary-layer wind predictions during nocturnal low-level jet events using the Weather Research and Forecasting model

    Energy Technology Data Exchange (ETDEWEB)

    Mirocha, Jeff D.; Simpson, Matthew D.; Fast, Jerome D.; Berg, Larry K.; Baskett, R.

    2016-04-01

    Simulations of two periods featuring three consecutive low level jet (LLJ) events in the US Upper Great Plains during the autumn of 2011 were conducted to explore the impacts of various setup configurations and physical process models on simulated flow parameters within the lowest 200 m above the surface, using the Weather Research and Forecasting (WRF) model. Sensitivities of simulated flow parameters to the horizontal and vertical grid spacing, planetary boundary layer (PBL) and land surface model (LSM) physics options, were assessed. Data from a Light Detection and Ranging (lidar) system, deployed to the Weather Forecast Improvement Project (WFIP; Finley et al. 2013) were used to evaluate the accuracy of simulated wind speed and direction at 80 m above the surface, as well as their vertical distributions between 120 and 40 m, covering the typical span of contemporary tall wind turbines. All of the simulations qualitatively captured the overall diurnal cycle of wind speed and stratification, producing LLJs during each overnight period, however large discrepancies occurred at certain times for each simulation in relation to the observations. 54-member ensembles encompassing changes of the above discussed configuration parameters displayed a wide range of simulated vertical distributions of wind speed and direction, and potential temperature, reflecting highly variable representations of stratification during the weakly stable overnight conditions. Root mean square error (RMSE) statistics show that different ensemble members performed better and worse in various simulated parameters at different times, with no clearly superior configuration . Simulations using a PBL parameterization designed specifically for the stable conditions investigated herein provided superior overall simulations of wind speed at 80 m, demonstrating the efficacy of targeting improvements of physical process models in areas of known deficiencies. However, the considerable magnitudes of the

  13. A Modulated-Gradient Parametrization for the Large-Eddy Simulation of the Atmospheric Boundary Layer Using the Weather Research and Forecasting Model

    Science.gov (United States)

    Khani, Sina; Porté-Agel, Fernando

    2017-08-01

    The performance of the modulated-gradient subgrid-scale (SGS) model is investigated using large-eddy simulation (LES) of the neutral atmospheric boundary layer within the weather research and forecasting model. Since the model includes a finite-difference scheme for spatial derivatives, the discretization errors may affect the simulation results. We focus here on understanding the effects of finite-difference schemes on the momentum balance and the mean velocity distribution, and the requirement (or not) of the ad hoc canopy model. We find that, unlike the Smagorinsky and turbulent kinetic energy (TKE) models, the calculated mean velocity and vertical shear using the modulated-gradient model, are in good agreement with Monin-Obukhov similarity theory, without the need for an extra near-wall canopy model. The structure of the near-wall turbulent eddies is better resolved using the modulated-gradient model in comparison with the classical Smagorinsky and TKE models, which are too dissipative and yield unrealistic smoothing of the smallest resolved scales. Moreover, the SGS fluxes obtained from the modulated-gradient model are much smaller near the wall in comparison with those obtained from the regular Smagorinsky and TKE models. The apparent inability of the LES model in reproducing the mean streamwise component of the momentum balance using the total (resolved plus SGS) stress near the surface is probably due to the effect of the discretization errors, which can be calculated a posteriori using the Taylor-series expansion of the resolved velocity field. Overall, we demonstrate that the modulated-gradient model is less dissipative and yields more accurate results in comparison with the classical Smagorinsky model, with similar computational costs.

  14. Large-Eddy Simulations of Atmospheric Flows Over Complex Terrain Using the Immersed-Boundary Method in the Weather Research and Forecasting Model

    Science.gov (United States)

    Ma, Yulong; Liu, Heping

    2017-07-01

    Atmospheric flow over complex terrain, particularly recirculation flows, greatly influences wind-turbine siting, forest-fire behaviour, and trace-gas and pollutant dispersion. However, there is a large uncertainty in the simulation of flow over complex topography, which is attributable to the type of turbulence model, the subgrid-scale (SGS) turbulence parametrization, terrain-following coordinates, and numerical errors in finite-difference methods. Here, we upgrade the large-eddy simulation module within the Weather Research and Forecasting model by incorporating the immersed-boundary method into the module to improve simulations of the flow and recirculation over complex terrain. Simulations over the Bolund Hill indicate improved mean absolute speed-up errors with respect to previous studies, as well an improved simulation of the recirculation zone behind the escarpment of the hill. With regard to the SGS parametrization, the Lagrangian-averaged scale-dependent Smagorinsky model performs better than the classic Smagorinsky model in reproducing both velocity and turbulent kinetic energy. A finer grid resolution also improves the strength of the recirculation in flow simulations, with a higher horizontal grid resolution improving simulations just behind the escarpment, and a higher vertical grid resolution improving results on the lee side of the hill. Our modelling approach has broad applications for the simulation of atmospheric flows over complex topography.

  15. Review on space weather in Latin America. 2. The research networks ready for space weather

    Science.gov (United States)

    Denardini, Clezio Marcos; Dasso, Sergio; Gonzalez-Esparza, J. Americo

    2016-11-01

    The present work is the second of a three-part review of space weather in Latin America, specifically observing its evolution in three countries (Argentina, Brazil and Mexico). This work comprises a summary of scientific challenges in space weather research that are considered to be open scientific questions and how they are being addressed in terms of instrumentation by the international community, including the Latin American groups. We also provide an inventory of the networks and collaborations being constructed in Latin America, including details on the data processing, capabilities and a basic description of the resulting variables. These instrumental networks currently used for space science research are gradually being incorporated into the space weather monitoring data pipelines as their data provides key variables for monitoring and forecasting space weather, which allow these centers to monitor space weather and issue watches, warnings and alerts.

  16. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part 2: Gas Tracer Dispersion

    Science.gov (United States)

    Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; Bieringer, Paul E.; Annunzio, Andrew; Bieberbach, George; Meech, Scott

    2016-12-01

    The Quick Urban & Industrial Complex (QUIC) atmospheric transport, and dispersion modelling, system was evaluated against the Joint Urban 2003 tracer-gas measurements. This was done using the wind and turbulence fields computed by the Weather Research and Forecasting (WRF) model. We compare the simulated and observed plume transport when using WRF-model-simulated wind fields, and local on-site wind measurements. Degradation of the WRF-model-based plume simulations was cased by errors in the simulated wind direction, and limitations in reproducing the small-scale wind-field variability. We explore two methods for importing turbulence from the WRF model simulations into the QUIC system. The first method uses parametrized turbulence profiles computed from WRF-model-computed boundary-layer similarity parameters; and the second method directly imports turbulent kinetic energy from the WRF model. Using the WRF model's Mellor-Yamada-Janjic boundary-layer scheme, the parametrized turbulence profiles and the direct import of turbulent kinetic energy were found to overpredict and underpredict the observed turbulence quantities, respectively. Near-source building effects were found to propagate several km downwind. These building effects and the temporal/spatial variations in the observed wind field were often found to have a stronger influence over the lateral and vertical plume spread than the intensity of turbulence. Correcting the WRF model wind directions using a single observational location improved the performance of the WRF-model-based simulations, but using the spatially-varying flow fields generated from multiple observation profiles generally provided the best performance.

  17. NATO Advanced Research Workshop on The Chemistry of Weathering

    CERN Document Server

    1985-01-01

    Several important developments in our understanding of the chemistry of weathering have occurred in the last few years: 1. There has been a major breakthrough in our understanding of the mechanisms controlling the kinetics of sil icate dissolution, and there have been major advances in computer modeling of weathering processes. 2. There has been a growing recognition of the importance of organic solutes in the weathering process, and hence of the inter-relationships between mineral weathering and the terrestrial ecosystem. 3. The impact of acid deposition ("acid rain") has been widely recognized. The processes by which acid deposition is neutral ized are closely related to the processes of normal chemical weathering; an understanding of the chemistry of weathering is thus essential for predicting the effects of acid deposition. 4. More high-qual ity data have become available on the chemical dynamics of smal I watersheds and large river systems, which represent the integrated effects of chemical weathering.

  18. Assessment of the Weather Research and Forecasting/Chemistry Model to Simulate Ozone Concentrations in March 2008 over Coastal Areas of the Sea of Japan

    Directory of Open Access Journals (Sweden)

    Moritomi Hiroshi

    2012-07-01

    Full Text Available The fully coupled WRF/Chem (Weather Research and Forecasting/Chemistry model is used to simulate air quality over coastal areas of the Sea of Japan. The anthropogenic surface emissions database used as input for this model was based primarily on global hourly emissions data (dust, sea salt, and biomass burning, RETRO (REanalysis of the TROpospheric chemical composition, GEIA (Global Emissions Inventory Activity, and POET (Precursors of Ozone and their Effects in the Troposphere. Climatologic concentrations of particulate matter derived from the Regional Acid Deposition Model (RADM2, chemical mechanism, and the Secondary Organic Aerosol Model (MADE/SORGAM with aqueous reactions were used to deduce the corresponding aerosol fluxes for input to the WRF/Chem model. The model was first integrated continuously over 48 hours, starting from 00:00 UTC on 14 March 2008, to evaluate ozone concentrations and other precursor pollutants. WPS meteorological data were used for the WRF/Chem model simulation in this study. Despite the low resolution of global emissions and the weak density of the local point emissions, it was found that the WRF/Chem model simulates the diurnal variation of the chemical species concentrations over the coastal areas of the Sea of Japan quite well. The Air Quality Management Division of the Ministry of the Environment in Japan selected the maximum level of the air quality standard for ozone, which is 60 ppb. In this study, the atmospheric concentrations of ozone over the coastal area of the Sea of Japan were calculated to be 30–55 ppb during the simulation period, which was lower than the Japanese air quality standard for ozone.

  19. Sensitivity of Turbine-Height Wind Speeds to Parameters in Planetary Boundary-Layer and Surface-Layer Schemes in the Weather Research and Forecasting Model

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Ben; Qian, Yun; Berg, Larry K.; Ma, Po-Lun; Wharton, Sonia; Bulaevskaya, Vera; Yan, Huiping; Hou, Zhangshuan; Shaw, William J.

    2016-07-21

    We evaluate the sensitivity of simulated turbine-height winds to 26 parameters applied in a planetary boundary layer (PBL) scheme and a surface layer scheme of the Weather Research and Forecasting (WRF) model over an area of complex terrain during the Columbia Basin Wind Energy Study. An efficient sampling algorithm and a generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of modeled turbine-height winds. The results indicate that most of the variability in the ensemble simulations is contributed by parameters related to the dissipation of the turbulence kinetic energy (TKE), Prandtl number, turbulence length scales, surface roughness, and the von Kármán constant. The relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability. The parameter associated with the TKE dissipation rate is found to be the most important one, and a larger dissipation rate can produce larger hub-height winds. A larger Prandtl number results in weaker nighttime winds. Increasing surface roughness reduces the frequencies of both extremely weak and strong winds, implying a reduction in the variability of the wind speed. All of the above parameters can significantly affect the vertical profiles of wind speed, the altitude of the low-level jet and the magnitude of the wind shear strength. The wind direction is found to be modulated by the same subset of influential parameters. Remainder of abstract is in attachment.

  20. Impact of the Assimilation of Hyperspectral Infrared Retrieved Profiles on Advanced Weather and Research Model Simulations of a Non-Convective Wind Event

    Science.gov (United States)

    Berndt, E. B.; Zavodsky, B. T.; Folmer, M. J.; Jedlovec, G. J.

    2014-01-01

    Non-convective wind events commonly occur with passing extratropical cyclones and have significant societal and economic impacts. Since non-convective winds often occur in the absence of specific phenomena such as a thunderstorm, tornado, or hurricane, the public are less likely to heed high wind warnings and continue daily activities. Thus non-convective wind events result in as many fatalities as straight line thunderstorm winds. One physical explanation for non-convective winds includes tropopause folds. Improved model representation of stratospheric air and associated non-convective wind events could improve non-convective wind forecasts and associated warnings. In recent years, satellite data assimilation has improved skill in forecasting extratropical cyclones; however errors still remain in forecasting the position and strength of extratropical cyclones as well as the tropopause folding process. The goal of this study is to determine the impact of assimilating satellite temperature and moisture retrieved profiles from hyperspectral infrared (IR) sounders (i.e. Atmospheric Infrared Sounder (AIRS), Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI)) on the model representation of the tropopause fold and an associated high wind event that impacted the Northeast United States on 09 February 2013. Model simulations using the Advanced Research Weather Research and Forecasting Model (ARW) were conducted on a 12-km grid with cycled data assimilation mimicking the operational North American Model (NAM). The results from the satellite assimilation run are compared to a control experiment (without hyperspectral IR retrievals), 32-km North American Regional Reanalysis (NARR) interpolated to a 12-km grid, and 13-km Rapid Refresh analyses.

  1. Simulations of Clouds and Sensitivity Study by Weather Research and Forecast Model for Atmospheric Radiation Measurement Case 4

    Energy Technology Data Exchange (ETDEWEB)

    Wu, J.; Zhang, M.

    2005-03-18

    One of the large errors in general circulation models (GCMs) cloud simulations is from the mid-latitude, synoptic-scale frontal cloud systems. Now, with the availability of the cloud observations from Atmospheric Radiation Measurement (ARM) 2000 cloud Intensive Operational Period (IOP) and other observational datasets, the community is able to document the model biases in comparison with the observations and make progress in development of better cloud schemes in models. Xie et al. (2004) documented the errors in midlatitude frontal cloud simulations for ARM Case 4 by single-column models (SCMs) and cloud resolving models (CRMs). According to them, the errors in the model simulated cloud field might be caused by following reasons: (1) lacking of sub-grid scale variability; (2) lacking of organized mesoscale cyclonic advection of hydrometeors behind a moving cyclone which may play important role to generate the clouds there. Mesoscale model, however, can be used to better under stand these controls on the subgrid variability of clouds. Few studies have focused on applying mesoscale models to the forecasting of cloud properties. Weaver et al. (2004) used a mesoscale model RAMS to study the frontal clouds for ARM Case 4 and documented the dynamical controls on the sub-GCM-grid-scale cloud variability.

  2. 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.

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

    Science.gov (United States)

    Spectral nudging – a scale-selective interior constraint technique – is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonst...

  4. Sensitivity of Turbine-Height Wind Speeds to Parameters in Planetary Boundary-Layer and Surface-Layer Schemes in the Weather Research and Forecasting Model

    Science.gov (United States)

    Yang, Ben; Qian, Yun; Berg, Larry K.; Ma, Po-Lun; Wharton, Sonia; Bulaevskaya, Vera; Yan, Huiping; Hou, Zhangshuan; Shaw, William J.

    2017-01-01

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

  5. Climatic effects of irrigation over the Huang-Huai-Hai Plain in China simulated by the weather research and forecasting model: Simulated Irrigation Effects in China

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Ben [CMA-NJU Joint Laboratory for Climate Prediction Studies, Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing China; Collaborative Innovation Center of Climate Change, Jiangsu Province China; Zhang, Yaocun [CMA-NJU Joint Laboratory for Climate Prediction Studies, Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing China; Collaborative Innovation Center of Climate Change, Jiangsu Province China; Qian, Yun [Pacific Northwest National Laboratory, Richland Washington USA; Tang, Jian [China Meteorological Administration, Beijing China; Liu, Dongqing [Nanjing Meteorological Bureau, Nanjing China

    2016-03-14

    In this study, we apply the Weather Research and Forecasting model coupled with an operational-like irrigation scheme to investigate the climatic effects of irrigation over the Huang-Huai-Hai plain (3HP) in China. Multiple numerical experiments with irrigation off/on during spring, summer and both spring and summer are conducted, respectively. Our results show that the warm bias in surface temperature and dry bias in soil moisture are reduced over the 3HP region during growing seasons when irrigation is turned on in the model. Air temperature during non-growing seasons is also affected by irrigation due to the persistent effects of soil moisture on land-air energy exchanges and ground heat storage. Irrigation can induce a cooler planetary boundary layer (PBL) during growing seasons, causing a wetter PBL with more low-level clouds during spring but relatively dryer PBL in summer. Further analyses indicate that the dryer summer is highly related to the changes in the East Asian summer monsoon (EASM) circulation that is modified by irrigation effect. Spring irrigation may induce a decreased land-ocean thermal contrast, leading to a possible weaker EASM. Summer irrigation, however, evidently cools the atmosphere column and forces a southward shift of the upper-level jet, which results in more precipitation in Yangtze River basin but less over southern and northern China during summer.

  6. Sensitivity of Turbine-Height Wind Speeds to Parameters in Planetary Boundary-Layer and Surface-Layer Schemes in the Weather Research and Forecasting Model

    Science.gov (United States)

    Yang, Ben; Qian, Yun; Berg, Larry K.; Ma, Po-Lun; Wharton, Sonia; Bulaevskaya, Vera; Yan, Huiping; Hou, Zhangshuan; Shaw, William J.

    2016-07-01

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

  7. Exploring Vertical Turbulence Structure in Neutrally and Stably Stratified Flows Using the Weather Research and Forecasting-Large-Eddy Simulation (WRF-LES) Model

    Science.gov (United States)

    Udina, Mireia; Sun, Jielun; Kosović, Branko; Soler, Maria Rosa

    2016-11-01

    Following Sun et al. (J Atmos Sci 69(1):338-351, 2012), vertical variations of turbulent mixing in stably stratified and neutral environments as functions of wind speed are investigated using the large-eddy simulation capability in the Weather Research and Forecasting model. The simulations with a surface cooling rate for the stable boundary layer (SBL) and a range of geostrophic winds for both stable and neutral boundary layers are compared with observations from the Cooperative Atmosphere-Surface Exchange Study 1999 (CASES-99). To avoid the uncertainty of the subgrid scheme, the investigation focuses on the vertical domain when the ratio between the subgrid and the resolved turbulence is small. The results qualitatively capture the observed dependence of turbulence intensity on wind speed under neutral conditions; however, its vertical variation is affected by the damping layer used in absorbing undesirable numerical waves at the top of the domain as a result of relatively large neutral turbulent eddies. The simulated SBL fails to capture the observed temperature variance with wind speed and the observed transition from the SBL to the near-neutral atmosphere with increasing wind speed, although the vertical temperature profile of the simulated SBL resembles the observed profile. The study suggests that molecular thermal conduction responsible for the thermal coupling between the surface and atmosphere cannot be parameterized through the Monin-Obukhov bulk relation for turbulent heat transfer by applying the surface radiation temperature, as is common practice when modelling air-surface interactions.

  8. Large Eddy Simulation of Wind Turbine Wake Dynamics in the Stable Boundary Layer Using the Weather Research and Forecasting Model

    Science.gov (United States)

    Aitken, M.; Kosovic, B.; Mirocha, J. D.; Lundquist, J. K.

    2014-12-01

    To thoroughly verify the actuator disk model recently implemented in WRF for large eddy simulation (LES) of wind turbine wakes, simulations of various types of turbines and atmospheric conditions must be compared to full-scale field measurements of the real atmosphere. Here, numerical simulations are compared to nacelle-based scanning lidar measurements taken in stable atmospheric conditions during a field campaign conducted at a wind farm in the western United States. Using several wake characteristics—such as the velocity deficit, centerline location, and wake width—as metrics for model verification, the simulations show good agreement with the observations. Notably, the average velocity deficit was seen to be quite high in both the experiment and simulation, resulting from a low average wind speed and therefore high average turbine thrust coefficient. Moreover, new features—namely rotor tilt and drag from the nacelle and tower—were added to the existing actuator disk model in WRF-LES. Compared to the rotor, the effect of the tower and nacelle on the flow is relatively small but nevertheless important for an accurate representation of the entire turbine. Adding rotor tilt to the model causes the vertical location of the wake center to shift upward. Continued advancement of the actuator disk model in WRF-LES will help lead to optimized turbine siting and controls at wind farms.

  9. Space Weather Research Towards Applications in Europe

    CERN Document Server

    Lilensten, Jean

    2007-01-01

    This book shows the state of the art in Europe on a very new discipline, Space Weather. This discipline lies at the edge between science and industry. This book reflects such a position, with theoretic papers and applicative papers as well. It is divided into 5 chapters. Each chapter starts with a short introduction, which shows the coherence of a given domain. Then, 4 to 5 contributions written by the best specialists in Europe give detailed hints of a hot topic in space weather. From the reading of this book, it becomes evident that space weather is a living discipline, full of promises and already full of amazing realizations. The strength of Europe is clear through the book, but it is also clear that this discipline is world wide.

  10. 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.

  11. 2015 Los Alamos Space Weather Summer School Research Reports

    Energy Technology Data Exchange (ETDEWEB)

    Cowee, Misa [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chen, Yuxi [Univ. of Michigan, Ann Arbor, MI (United States); Desai, Ravindra [Univ. College London, Bloomsbury (United Kingdom); Hassan, Ehab [Univ. of Texas, Austin, TX (United States); Kalmoni, Nadine [Univ. College London, Bloomsbury (United Kingdom); Lin, Dong [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Depascuale, Sebastian [Univ. of Iowa, Iowa City, IA (United States); Hughes, Randall Scott [Univ. of Southern California, Los Angeles, CA (United States); Zhou, Hong [Univ. of Colorado, Boulder, CO (United States)

    2015-11-24

    The fifth Los Alamos Space Weather Summer School was held June 1st - July 24th, 2015, at Los Alamos National Laboratory (LANL). With renewed support from the Institute of Geophysics, Planetary Physics, and Signatures (IGPPS) and additional support from the National Aeronautics and Space Administration (NASA) and the Department of Energy (DOE) Office of Science, we hosted a new class of five students from various U.S. and foreign research institutions. The summer school curriculum includes a series of structured lectures as well as mentored research and practicum opportunities. Lecture topics including general and specialized topics in the field of space weather were given by a number of researchers affiliated with LANL. Students were given the opportunity to engage in research projects through a mentored practicum experience. Each student works with one or more LANL-affiliated mentors to execute a collaborative research project, typically linked with a larger ongoing research effort at LANL and/or the student’s PhD thesis research. This model provides a valuable learning experience for the student while developing the opportunity for future collaboration. This report includes a summary of the research efforts fostered and facilitated by the Space Weather Summer School. These reports should be viewed as work-in-progress as the short session typically only offers sufficient time for preliminary results. At the close of the summer school session, students present a summary of their research efforts. Titles of the papers included in this report are as follows: Full particle-in-cell (PIC) simulation of whistler wave generation, Hybrid simulations of the right-hand ion cyclotron anisotropy instability in a sub-Alfvénic plasma flow, A statistical ensemble for solar wind measurements, Observations and models of substorm injection dispersion patterns, Heavy ion effects on Kelvin-Helmholtz instability: hybrid study, Simulating plasmaspheric electron densities with a two

  12. 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

  13. Initial phase of the Hans-Ertel Centre for Weather Research – A virtual centre at the interface of basic and applied weather and climate research

    Directory of Open Access Journals (Sweden)

    Martin Weissmann

    2014-09-01

    Full Text Available The Hans-Ertel Centre for Weather Research is a network of German universities, research institutes and the German Weather Service (Deutscher Wetterdienst, DWD. It has been established to trigger and intensify basic research and education on weather forecasting and climate monitoring. The performed research ranges from nowcasting and short-term weather forecasting to convective-scale data assimilation, the development of parameterizations for numerical weather prediction models, climate monitoring and the communication and use of forecast information. Scientific findings from the network contribute to better understanding of the life-cycle of shallow and deep convection, representation of uncertainty in ensemble systems, effects of unresolved variability, regional climate variability, perception of forecasts and vulnerability of society. Concrete developments within the research network include dual observation-microphysics composites, satellite forward operators, tools to estimate observation impact, cloud and precipitation system tracking algorithms, large-eddy-simulations, a regional reanalysis and a probabilistic forecast test product. Within three years, the network has triggered a number of activities that include the training and education of young scientists besides the centre's core objective of complementing DWD's internal research with relevant basic research at universities and research institutes. The long term goal is to develop a self-sustaining research network that continues the close collaboration with DWD and the national and international research community.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

    Gross, N. A.; Hughes, W.

    2011-12-01

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

  16. 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

  17. Multi-initial-conditions and Multi-physics Ensembles in the Weather Research and Forecasting Model to Improve Coastal Stratocumulus Forecasts for Solar Power Integration

    Science.gov (United States)

    Yang, H.

    2015-12-01

    In coastal Southern California, variation in solar energy production is predominantly due to the presence of stratocumulus clouds (Sc), as they greatly attenuate surface solar irradiance and cover most distributed photovoltaic systems on summer mornings. Correct prediction of the spatial coverage and lifetime of coastal Sc is therefore vital to the accuracy of solar energy forecasts in California. In Weather Research and Forecasting (WRF) model simulations, underprediction of Sc inherent in the initial conditions directly leads to an underprediction of Sc in the resulting forecasts. Hence, preprocessing methods were developed to create initial conditions more consistent with observational data and reduce spin-up time requirements. Mathiesen et al. (2014) previously developed a cloud data assimilation system to force WRF initial conditions to contain cloud liquid water based on CIMSS GOES Sounder cloud cover. The Well-mixed Preprocessor and Cloud Data Assimilation (WEMPPDA) package merges an initial guess of cloud liquid water content obtained from mixed-layer theory with assimilated CIMSS GOES Sounder cloud cover to more accurately represent the spatial coverage of Sc at initialization. The extent of Sc inland penetration is often constrained topographically; therefore, the low inversion base height (IBH) bias in NAM initial conditions decreases Sc inland penetration. The Inversion Base Height (IBH) package perturbs the initial IBH by the difference between model IBH and the 12Z radiosonde measurement. The performance of these multi-initial-condition configurations was evaluated over June, 2013 against SolarAnywhere satellite-derived surface irradiance data. Four configurations were run: 1) NAM initial conditions, 2) RAP initial conditions, 3) WEMPPDA applied to NAM, and 4) IBH applied to NAM. Both preprocessing methods showed significant improvement in the prediction of both spatial coverage and lifetime of coastal Sc. The best performing configuration was then

  18. Weather Research and Forecasting Model simulations of extended warm-season heavy precipitation episode over the US Southern Great Plains: data assimilation and microphysics sensitivity experiments

    Directory of Open Access Journals (Sweden)

    Zewdu T. Segele

    2013-07-01

    Full Text Available This study examines eight microphysics schemes (Lin, WSM5, Eta, WSM6, Goddard, Thompson, WDM5, WDM6 in the Advanced Research Weather Research and Forecasting Model (WRF-ARW for their reproduction of observed strong convection over the US Southern Great Plains (SGP for three heavy precipitation events of 27–31 May 2001. It also assesses how observational analysis nudging (OBNUD, three-dimensional (3DVAR and four-dimensional variational (4DVAR data assimilation (DA affect simulated cloud properties relative to simulations with no DA (CNTRL. Primary evaluation data were cloud radar reflectivity measurements by the millimetre cloud radar (MMCR at the Central Facility (CF of the SGP site of the ARM Climate Research Facility (ACRF. All WRF-ARW microphysics simulations reproduce the intensity and vertical structure of the first two major MMCR-observed storms, although the first simulated storm initiates a few hours earlier than observed. Of three organised convective events, the model best identifies the timing and vertical structure of the second storm more than 50 hours into the simulation. For this well-simulated cloud structure, simulated reflectivities are close to the observed counterparts in the mid- and upper troposphere, and only overestimate observed cloud radar reflectivity in the lower troposphere by less than 10 dBZ. Based on relative measures of skill, no single microphysics scheme excels in all aspects, although the WDM schemes show much-improved frequency bias scores (FBSs in the lower troposphere for a range of reflectivity thresholds. The WDM6 scheme has improved FBSs and high simulated-observed reflectivity correlations in the lower troposphere, likely due to its large production of liquid water immediately below the melting level. Of all the DA experiments, 3DVAR has the lowest mean errors (MEs and root mean-squared errors (RMSEs, although both the 3DVAR and 4DVAR simulations reduced noticeably the MEs for seven of eight

  19. Intercomparison of the Performance of CLM3, NOAH, RUC, and STD Land Surface Schemes in the Weather and Research Forecasting Model

    Science.gov (United States)

    Jin, J.; Miller, N.

    2007-12-01

    The Community Land Model version 3 (CLM3) developed by the National Center for Atmospheric Research (NCAR) was coupled into the Weather Research and Forecasting (WRF) Model version 2.2. The performance of WRF-CLM3 in predicting regional climate was quantitatively compared with that of WRF coupled to the soil thermal diffusion (STD), Rapid Update Cycle, and NOAH Land Surface Schemes. These land surface schemes represent a range of complexity within land-surface schemes. CLM3 is the most sophisticated model, with detailed snow and vegetation processes. The STD scheme is oversimplified, which only calculates soil temperature and neglects vegetation and snow physics. The RUC and NOAH schemes are intermediate in the detail, and the major deference between them is that RUC has a multi-layer snow scheme, and Noah has a single snow layer lumped with the topmost soil layer. WRF was driven by the National Centers for Environmental Prediction Reanalysis data II with each of these land surface schemes for one-year simulations over the period, 1 October 1995 to 30 September 1996, resulting in four one-year simulations for intercomparison. Each simulation has 30km-10km two-way nested domains. The 30 km domain includes the western U.S. and eastern Pacific, and the inner domain includes California and parts of Nevada, Oregon, and the eastern Pacific. Our analysis shows that WRF-CLM3 outperforms WRF-RUC, WRF-NOAH, and WRF-STD in simulating temperature and snow when compared with observations. The WRF-STD scheme, which does not include snow and vegetation processes resulted in the poorest results, with a dramatic overestimation of surface air temperature. However, regardless of the land surface scheme chosen, WRF reasonably well reproduces the winter precipitation, a major water resource for California, suggesting that the linkage between land surface processes and precipitation is not explicit. In general, land surface schemes play a significant role in the simulation of regional

  20. Research Environment and Information Service of the Space Weather Cloud

    Directory of Open Access Journals (Sweden)

    S Watari

    2013-04-01

    Full Text Available To optimize space weather research and information services, it is important to establish a comprehensive system that enables us to analyze observation and simulation data in an integrated manner. For this, we recently constructed a new computing environment called the "Space Weather Cloud Computing System" of the National Institute of Information and Communications Technology (NICT. Currently, the Space Weather Cloud contains a high performance computer, a distributed mass storage system using the Grid Data Farm (Gfarm technology, servers for analysis and visualization of data, a job service based on the RCM (R&D Chain Management system, servers for Solar-Terrestrial data Analysis, and the Reference System (STARS.

  1. Geodetic Space Weather Monitoring by means of Ionosphere Modelling

    Science.gov (United States)

    Schmidt, Michael

    2017-04-01

    modelling the ionosphere and detecting and forecasting its disturbances. At present a couple of nations, such as the US, UK, Japan, Canada and China, are taken the threats from extreme space weather events seriously and support the development of observing strategies and fundamental research. However, (extreme) space weather events are in all their consequences on the modern highly technologized society, causative global problems which have to be treated globally and not regionally or even nationally. Consequently, space weather monitoring must include (1) all space-geodetic observation techniques and (2) geodetic evaluation methods such as data combination, real-time modelling and forecast. In other words, geodetic space weather monitoring comprises the basic ideas of GGOS and will provide products such as forecasts of severe solar events in order to initiate necessary activities to protect the infrastructure of modern society.

  2. Growing Diversity in Space Weather and Climate Change Research

    Science.gov (United States)

    Johnson, L. P.; Ng, C.; Marchese, P.; Austin, S.; Frost, J.; Cheung, T. D.; Robbins, I.; Carlson, B. E.; Steiner, J. C.; Tremberger, G.; Paglione, T.; Damas, C.; Howard, A.; Scalzo, F.

    2013-12-01

    Space Weather and Global Climate Impacts are critical items on the present national and international science agendas. Understanding and forecasting solar activity is increasingly important for manned space flight, unmanned missions (including communications satellites, satellites that monitor the space and earth environment), and regional power grids. The ability to predict the effects of forcings and feedback mechanisms on global and local climate is critical to survival of the inhabitants of planet Earth. It is therefore important to motivate students to continue their studies via advanced degrees and pursue careers related to these areas. This CUNY-based initiative, supported by NASA and NSF, provided undergraduate research experience for more than 70 students in topics ranging from urban impacts of global climate change to magnetic rope structure, solar flares and CMEs. Other research topics included investigations of the ionosphere using a CubeSat, stratospheric aerosols in Jupiter's atmosphere, and ocean climate modeling. Mentors for the primarily summer research experiences included CUNY faculty, GISS and GSFC scientists. Students were recruited from CUNY colleges as well as other colleges including Spelman, Cornell, Rutgers and SUNY colleges. Fifty-eight percent of the undergraduate students were under-represented minorities and thirty-four percent were female. Many of the research teams included high school teachers and students as well as graduate students. Supporting workshops for students included data analysis and visualization tools, space weather, planetary energy balance and BalloonSats. The project is supported by NASA awards NNX10AE72G and NNX09AL77G, and NSF REU Site award 0851932.

  3. 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...

  4. 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...

  5. Weather conditions: a neglected factor in human salivary cortisol research?

    Science.gov (United States)

    Milas, Goran; Šupe-Domić, Daniela; Drmić-Hofman, Irena; Rumora, Lada; Klarić, Irena Martinović

    2017-09-01

    There is ample evidence that environmental stressors such as extreme weather conditions affect animal behavior and that this process is in part mediated through the elevated activity of the hypothalamic pituitary adrenal axis which results in an increase in cortisol secretion. This relationship has not been extensively researched in humans, and weather conditions have not been analyzed as a potential confounder in human studies of stress. Consequently, the goal of this paper was to assess the relationship between salivary cortisol and weather conditions in the course of everyday life and to test a possible moderating effect of two weather-related variables, the climate region and timing of exposure to outdoors conditions. The sample consisted of 903 secondary school students aged 18 to 21 years from Mediterranean and Continental regions. Cortisol from saliva was sampled in naturalistic settings at three time points over the course of a single day. We found that weather conditions are related to salivary cortisol concentration and that this relationship may be moderated by both the specific climate and the anticipation of immediate exposure to outdoors conditions. Unpleasant weather conditions are predictive for the level of salivary cortisol, but only among individuals who anticipate being exposed to it in the immediate future (e.g., in students attending school in the morning shift). We also demonstrated that isolated weather conditions or their patterns may be relevant in one climate area (e.g., Continental) while less relevant in the other (e.g., Mediterranean). Results of this study draw attention to the importance of controlling weather conditions in human salivary cortisol research.

  6. 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.

  7. 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.

  8. Integration of Weather Data into Airspace and Traffic Operations Simulation (ATOS) for Trajectory- Based Operations Research

    Science.gov (United States)

    Peters, Mark; Boisvert, Ben; Escala, Diego

    2009-01-01

    Explicit integration of aviation weather forecasts with the National Airspace System (NAS) structure is needed to improve the development and execution of operationally effective weather impact mitigation plans and has become increasingly important due to NAS congestion and associated increases in delay. This article considers several contemporary weather-air traffic management (ATM) integration applications: the use of probabilistic forecasts of visibility at San Francisco, the Route Availability Planning Tool to facilitate departures from the New York airports during thunderstorms, the estimation of en route capacity in convective weather, and the application of mixed-integer optimization techniques to air traffic management when the en route and terminal capacities are varying with time because of convective weather impacts. Our operational experience at San Francisco and New York coupled with very promising initial results of traffic flow optimizations suggests that weather-ATM integrated systems warrant significant research and development investment. However, they will need to be refined through rapid prototyping at facilities with supportive operational users We have discussed key elements of an emerging aviation weather research area: the explicit integration of aviation weather forecasts with NAS structure to improve the effectiveness and timeliness of weather impact mitigation plans. Our insights are based on operational experiences with Lincoln Laboratory-developed integrated weather sensing and processing systems, and derivative early prototypes of explicit ATM decision support tools such as the RAPT in New York City. The technical components of this effort involve improving meteorological forecast skill, tailoring the forecast outputs to the problem of estimating airspace impacts, developing models to quantify airspace impacts, and prototyping automated tools that assist in the development of objective broad-area ATM strategies, given probabilistic

  9. Evaluation of a seven-year air quality simulation using the Weather Research and Forecasting (WRF)/Community Multiscale Air Quality (CMAQ) models in the eastern United States.

    Science.gov (United States)

    Zhang, Hongliang; Chen, Gang; Hu, Jianlin; Chen, Shu-Hua; Wiedinmyer, Christine; Kleeman, Michael; Ying, Qi

    2014-03-01

    The performance of the Weather Research and Forecasting (WRF)/Community Multi-scale Air Quality (CMAQ) system in the eastern United States is analyzed based on results from a seven-year modeling study with a 4-km spatial resolution. For 2-m temperature, the monthly averaged mean bias (MB) and gross error (GE) values are generally within the recommended performance criteria, although temperature is over-predicted with MB values up to 2K. Water vapor at 2-m is well-predicted but significant biases (>2 g kg(-1)) were observed in wintertime. Predictions for wind speed are satisfactory but biased towards over-prediction with 0

  10. Space Weather Research at the National Science Foundation

    Science.gov (United States)

    Moretto, T.

    2015-12-01

    There is growing recognition that the space environment can have substantial, deleterious, impacts on society. Consequently, research enabling specification and forecasting of hazardous space effects has become of great importance and urgency. This research requires studying the entire Sun-Earth system to understand the coupling of regions all the way from the source of disturbances in the solar atmosphere to the Earth's upper atmosphere. The traditional, region-based structure of research programs in Solar and Space physics is ill suited to fully support the change in research directions that the problem of space weather dictates. On the observational side, dense, distributed networks of observations are required to capture the full large-scale dynamics of the space environment. However, the cost of implementing these is typically prohibitive, especially for measurements in space. Thus, by necessity, the implementation of such new capabilities needs to build on creative and unconventional solutions. A particularly powerful idea is the utilization of new developments in data engineering and informatics research (big data). These new technologies make it possible to build systems that can collect and process huge amounts of noisy and inaccurate data and extract from them useful information. The shift in emphasis towards system level science for geospace also necessitates the development of large-scale and multi-scale models. The development of large-scale models capable of capturing the global dynamics of the Earth's space environment requires investment in research team efforts that go beyond what can typically be funded under the traditional grants programs. This calls for effective interdisciplinary collaboration and efficient leveraging of resources both nationally and internationally. This presentation will provide an overview of current and planned initiatives, programs, and activities at the National Science Foundation pertaining to space weathe research.

  11. Current research on aviation weather (bibliography), 1979

    Science.gov (United States)

    Turkel, B. S.; Frost, W.

    1980-01-01

    The titles, managers, supporting organizations, performing organizations, investigators and objectives of 127 current research projects in advanced meteorological instruments, forecasting, icing, lightning, visibility, low level wind shear, storm hazards/severe storms, and turbulence are tabulated and cross-referenced. A list of pertinent reference material produced through the above tabulated research activities is given. The acquired information is assembled in bibliography form to provide a readily available source of information in the area of aviation meteorology.

  12. 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

  13. 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.

  14. Research from an Operatonal Space Weather Satellite

    Science.gov (United States)

    de Koning, C. A.

    2015-12-01

    STEREO real-time white-light images, or beacon images, are heavily compressed, 256x256 pixel images. And yet, they show the same transient features that are in the STEREO science images, which are up to 2048x2048 pixels. Based on our experience with STEREO beacon images, we demonstrate that operational images can be used to do good quality science. We also discuss the limitations of operational data for scientific research. Finally, we discuss ways in which a predominantly operational mission could be combined with science mission, to further enhance research.

  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. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Recent Applications of Space Weather Research to NASA Space Missions

    Science.gov (United States)

    Willis, Emily M.; Howard, James W., Jr.; Miller, J. Scott; Minow, Joseph I.; NeergardParker, L.; Suggs, Robert M.

    2013-01-01

    Marshall Space Flight Center s Space Environments Team is committed to applying the latest research in space weather to NASA programs. We analyze data from an extensive set of space weather satellites in order to define the space environments for some of NASA s highest profile programs. Our goal is to ensure that spacecraft are designed to be successful in all environments encountered during their missions. We also collaborate with universities, industry, and other federal agencies to provide analysis of anomalies and operational impacts to current missions. This presentation is a summary of some of our most recent applications of space weather data, including the definition of the space environments for the initial phases of the Space Launch System (SLS), acquisition of International Space Station (ISS) frame potential variations during geomagnetic storms, and Nascap-2K charging analyses.

  2. 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.

  3. 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.

  4. 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

  5. The impact of Sun-weather research on forecasting

    Science.gov (United States)

    Larsen, M. F.

    1979-01-01

    The possible impact of Sun-weather research on forecasting is examined. The type of knowledge of the effect is evaluated to determine if it is in a form that can be used for forecasting purposes. It is concluded that the present understanding of the effect does not lend itself readily to applications for forecast purposes. The limits of present predictive skill are examined and it is found that skill is most lacking for prediction of the smallest scales of atmospheric motion. However, it is not expected that Sun-weather research will have any significant impact on forecasting the smaller scales since predictability at these scales is limited by the finite grid size resolution and the time scales of turbulent diffusion. The predictability limits for the largest scales are on the order of several weeks although presently only a one week forecast is achievable.

  6. 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...

  7. 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.

  8. Development research for wind power weather insurance index through analysis of weather elements and new renewable energy

    Science.gov (United States)

    Park, Ki-Jun; jung, jihoon

    2014-05-01

    Recently, social interests and concerns regarding weather risk are gradually growing with increase in frequency of unusual phenomena. Actually, the threat to many vulnerable industries (sensitive to climate conditions) such as agriculture, architecture, logistics, transportation, clothing, home appliance, and food is increasing. According to climate change scenario reports published by National Institute of Meteorological Research (NIMR) in 2012, temperature and precipitation are expected to increase by 4.8% and 13.2% respectively with current status of CO2 emissions (RCP 8.5) at the end of the 21st century. Furthermore, most of areas in Korea except some mountainous areas are also expected to shift from temperate climate to subtropical climate. In the context of climate change, the intensity of severe weathers such as heavy rainfalls and droughts is enhanced, which, in turn, increases the necessity and importance of weather insurance. However, most insurance market is small and limited to policy insurance like crop disaster insurance, and natural disaster insurance in Korea. The reason for poor and small weather insurance market could result from the lack of recognition of weather risk management even though all economic components (firms, governments, and households) are significantly influenced by weather. However, fortunately, new renewable energy and leisure industry which are vulnerable to weather risk are in a long term uptrend and the interest of weather risk is also getting larger and larger in Korea. So, in the long run, growth potential of weather insurance market in Korea might be higher than ever. Therefore, in this study, the capacity of power generation per hour and hourly wind speed are analyzed to develop and test weather insurance index for wind power, and then the effectiveness of weather insurance index are investigated and the guidance will be derived to objectively calculate the weather insurance index.

  9. 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

  10. 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.

  11. 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.

  12. 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...

  13. Planetary Space Weather Service: Part of the the Europlanet 2020 Research Infrastructure

    Science.gov (United States)

    Grande, Manuel; Andre, Nicolas

    2016-07-01

    Over the next four years the Europlanet 2020 Research Infrastructure will set up an entirely new European Planetary Space Weather service (PSWS). Europlanet RI is a part of of Horizon 2020 (EPN2020-RI, http://www.europlanet-2020-ri.eu). The Virtual Access Service, WP5 VA1 "Planetary Space Weather Services" will extend the concepts of space weather and space situational awareness to other planets in our Solar System and in particular to spacecraft that voyage through it. VA1 will make five entirely new 'toolkits' accessible to the research community and to industrial partners planning for space missions: a general planetary space weather toolkit, as well as three toolkits dedicated to the following key planetary environments: Mars (in support ExoMars), comets (building on the expected success of the ESA Rosetta mission), and outer planets (in preparation for the ESA JUICE mission to be launched in 2022). This will give the European planetary science community new methods, interfaces, functionalities and/or plugins dedicated to planetary space weather in the tools and models available within the partner institutes. It will also create a novel event-diary toolkit aiming at predicting and detecting planetary events like meteor showers and impacts. A variety of tools (in the form of web applications, standalone software, or numerical models in various degrees of implementation) are available for tracing propagation of planetary and/or solar events through the Solar System and modelling the response of the planetary environment (surfaces, atmospheres, ionospheres, and magnetospheres) to those events. But these tools were not originally designed for planetary event prediction and space weather applications. So WP10 JRA4 "Planetary Space Weather Services" (PSWS) will provide the additional research and tailoring required to apply them for these purposes. The overall objectives of this Joint Research Aactivities will be to review, test, improve and adapt methods and tools

  14. 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.

  15. Synopsis of the Review on Space Weather in Latin America: Space Science, Research Networks and Space Weather Center

    Science.gov (United States)

    Denardini, Clezio Marcos; Dasso, Sergio; Gonzalez-Esparza, Americo

    2016-07-01

    The present work is a synopsis of a three-part review on space weather in Latin America. The first paper (part 1) comprises the evolution of several Latin American institutions investing in space science since the 1960's, focusing on the solar-terrestrial interactions, which today is commonly called space weather. Despite recognizing advances in space research in all of Latin America, this part 1 is restricted to the development observed in three countries in particular (Argentina, Brazil and Mexico), due to the fact that these countries have recently developed operational centers for monitoring space weather. The review starts with a brief summary of the first groups to start working with space science in Latin America. This first part of the review closes with the current status and the research interests of these groups, which are described in relation to the most significant works and challenges of the next decade in order to aid in the solving of space weather open issues. The second paper (part 2) comprises a summary of scientific challenges in space weather research that are considered to be open scientific questions and how they are being addressed in terms of instrumentation by the international community, including the Latin American groups. We also provide an inventory of the networks and collaborations being constructed in Latin America, including details on the data processing, capabilities and a basic description of the resulting variables. These instrumental networks currently used for space science research are gradually being incorporated into the space weather monitoring data pipelines as their data provides key variables for monitoring and forecasting space weather, which allow these centers to monitor space weather and issue warnings and alerts. The third paper (part 3) presents the decision process for the spinning off of space weather prediction centers from space science groups with our interpretation of the reason/opportunities that leads to

  16. An outline of the review on space weather in Latin America: space science, research networks and space weather center

    Science.gov (United States)

    De Nardin, C. M.; Dasso, S.; Gonzalez-Esparza, A.

    2016-12-01

    The present work is an outline of a three-part review on space weather in Latin America. The first paper (part 1) comprises the evolution of several Latin American institutions investing in space science since the 1960's, focusing on the solar-terrestrial interactions, which today is commonly called space weather. Despite recognizing advances in space research in all of Latin America, this part 1 is restricted to the development observed in three countries in particular (Argentina, Brazil and Mexico), due to the fact that these countries have recently developed operational centers for monitoring space weather. The review starts with a brief summary of the first groups to start working with space science in Latin America. This first part of the review closes with the current status and the research interests of these groups, which are described in relation to the most significant works and challenges of the next decade in order to aid in the solving of space weather open issues. The second paper (part 2) comprises a summary of scientific challenges in space weather research that are considered to be open scientific questions and how they are being addressed in terms of instrumentation by the international community, including the Latin American groups. We also provide an inventory of the networks and collaborations being constructed in Latin America, including details on the data processing, capabilities and a basic description of the resulting variables. These instrumental networks currently used for space science research are gradually being incorporated into the space weather monitoring data pipelines as their data provides key variables for monitoring and forecasting space weather, which allow these centers to monitor space weather and issue warnings and alerts. The third paper (part 3) presents the decision process for the spinning off of space weather prediction centers from space science groups with our interpretation of the reason/opportunities that leads to

  17. 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.

  18. Early Japanese contributions to space weather research (1945–1960

    Directory of Open Access Journals (Sweden)

    A. Nishida

    2010-04-01

    Full Text Available Major contributions by Japanese scientists in the period of 1945 to 1960 are reviewed. This was the period when the foundation of the space weather research was laid by ground-based observations and theoretical research. Important contributions were made on such subjects as equatorial ionosphere in quiet times, tidal wind system in the ionosphere, formation of the F2 layer, VLF propagation above the ionosphere, and precursory phenomena (type IV radio outburst and polar cap absorption to storms. At the IGY (1957, 1958, research efforts were intensified and new programs in space and Antarctica were initiated. Japanese scientists in this discipline held a tight network for communication and collaboration that has been kept to this day.

  19. 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...

  20. 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 ...

  1. An overview on the Space Weather in Latin America: from Space Research to Space Weather and its Forecast

    Science.gov (United States)

    De Nardin, C. M.; Gonzalez-Esparza, A.; Dasso, S.

    2015-12-01

    We present an overview on the Space Weather in Latin America, highlighting the main findings from our review the recent advances in the space science investigations in Latin America focusing in the solar-terrestrial interactions, modernly named space weather, which leaded to the creation of forecast centers. Despite recognizing advances in the space research over the whole Latin America, this review is restricted to the evolution observed in three countries (Argentina, Brazil and Mexico) only, due to the fact that these countries have recently developed operational center for monitoring the space weather. The work starts with briefly mentioning the first groups that started the space science in Latin America. The current status and research interest of such groups are then described together with the most referenced works and the challenges for the next decade to solve space weather puzzles. A small inventory of the networks and collaborations being built is also described. Finally, the decision process for spinning off the space weather prediction centers from the space science groups is reported with an interpretation of the reason/opportunities that lead to it. Lastly, the constraints for the progress in the space weather monitoring, research, and forecast are listed with recommendations to overcome them.

  2. A strategy for representing the effects of convective momentum transport in multiscale models: Evaluation using a new superparameterized version of the Weather Research and Forecast model (SP-WRF)

    Science.gov (United States)

    Tulich, S. N.

    2015-06-01

    This paper describes a general method for the treatment of convective momentum transport (CMT) in large-scale dynamical solvers that use a cyclic, two-dimensional (2-D) cloud-resolving model (CRM) as a "superparameterization" of convective-system-scale processes. The approach is similar in concept to traditional parameterizations of CMT, but with the distinction that both the scalar transport and diagnostic pressure gradient force are calculated using information provided by the 2-D CRM. No assumptions are therefore made concerning the role of convection-induced pressure gradient forces in producing up or down-gradient CMT. The proposed method is evaluated using a new superparameterized version of the Weather Research and Forecast model (SP-WRF) that is described herein for the first time. Results show that the net effect of the formulation is to modestly reduce the overall strength of the large-scale circulation, via "cumulus friction." This statement holds true for idealized simulations of two types of mesoscale convective systems, a squall line, and a tropical cyclone, in addition to real-world global simulations of seasonal (1 June to 31 August) climate. In the case of the latter, inclusion of the formulation is found to improve the depiction of key synoptic modes of tropical wave variability, in addition to some aspects of the simulated time-mean climate. The choice of CRM orientation is also found to importantly affect the simulated time-mean climate, apparently due to changes in the explicit representation of wide-spread shallow convective regions.

  3. The STEREO Mission: A New Approach to Space Weather Research

    Science.gov (United States)

    Kaiser, michael L.

    2006-01-01

    With the launch of the twin STEREO spacecraft in July 2006, a new capability will exist for both real-time space weather predictions and for advances in space weather research. Whereas previous spacecraft monitors of the sun such as ACE and SOH0 have been essentially on the sun-Earth line, the STEREO spacecraft will be in 1 AU orbits around the sun on either side of Earth and will be viewing the solar activity from distinctly different vantage points. As seen from the sun, the two spacecraft will separate at a rate of 45 degrees per year, with Earth bisecting the angle. The instrument complement on the two spacecraft will consist of a package of optical instruments capable of imaging the sun in the visible and ultraviolet from essentially the surface to 1 AU and beyond, a radio burst receiver capable of tracking solar eruptive events from an altitude of 2-3 Rs to 1 AU, and a comprehensive set of fields and particles instruments capable of measuring in situ solar events such as interplanetary magnetic clouds. In addition to normal daily recorded data transmissions, each spacecraft is equipped with a real-time beacon that will provide 1 to 5 minute snapshots or averages of the data from the various instruments. This beacon data will be received by NOAA and NASA tracking stations and then relayed to the STEREO Science Center located at Goddard Space Flight Center in Maryland where the data will be processed and made available within a goal of 5 minutes of receipt on the ground. With STEREO's instrumentation and unique view geometry, we believe considerable improvement can be made in space weather prediction capability as well as improved understanding of the three dimensional structure of solar transient events.

  4. Coupled Stochastic Time-Inverted Lagrangian Transport/Weather Forecast and Research/Vegetation Photosynthesis and Respiration Model. Part II; Simulations of Tower-Based and Airborne CO2 Measurements

    Science.gov (United States)

    Eluszkiewicz, Janusz; Nehrkorn, Thomas; Wofsy, Steven C.; Matross, Daniel; Gerbig, Christoph; Lin, John C.; Freitas, Saulo; Longo, Marcos; Andrews, Arlyn E.; Peters, Wouter

    2007-01-01

    This paper evaluates simulations of atmospheric CO2 measured in 2004 at continental surface and airborne receptors, intended to test the capability to use data with high temporal and spatial resolution for analyses of carbon sources and sinks at regional and continental scales. The simulations were performed using the Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by the Weather Forecast and Research (WRF) model, and linked to surface fluxes from the satellite-driven Vegetation Photosynthesis and Respiration Model (VPRM). The simulations provide detailed representations of hourly CO2 tower data and reproduce the shapes of airborne vertical profiles with high fidelity. WRF meteorology gives superior model performance compared with standard meteorological products, and the impact of including WRF convective mass fluxes in the STILT trajectory calculations is significant in individual cases. Important biases in the simulation are associated with the nighttime CO2 build-up and subsequent morning transition to convective conditions, and with errors in the advected lateral boundary condition. Comparison of STILT simulations driven by the WRF model against those driven by the Brazilian variant of the Regional Atmospheric Modeling System (BRAMS) shows that model-to-model differences are smaller than between an individual transport model and observations, pointing to systematic errors in the simulated transport. Future developments in the WRF model s data assimilation capabilities, basic research into the fundamental aspects of trajectory calculations, and intercomparison studies involving other transport models, are possible venues for reducing these errors. Overall, the STILT/WRF/VPRM offers a powerful tool for continental and regional scale carbon flux estimates.

  5. 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...

  6. Lightning: Nature's Probe of Severe Weather for Research and Operations

    Science.gov (United States)

    Blakeslee, R.J.

    2007-01-01

    Lightning, the energetic and broadband electrical discharge produced by thunderstorms, provides a natural remote sensing signal for the study of severe storms and related phenomena on global, regional and local scales. Using this strong signal- one of nature's own probes of severe weather -lightning measurements prove to be straightforward and take advantage of a variety of measurement techniques that have advanced considerably in recent years. We briefly review some of the leading lightning detection systems including satellite-based optical detectors such as the Lightning Imaging Sensor, and ground-based radio frequency systems such as Vaisala's National Lightning Detection Network (NLDN), long range lightning detection systems, and the Lightning Mapping Array (LMA) networks. In addition, we examine some of the exciting new research results and operational capabilities (e.g., shortened tornado warning lead times) derived from these observations. Finally we look forward to the next measurement advance - lightning observations from geostationary orbit.

  7. Projected Applications of a "Weather in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

    Science.gov (United States)

    Jedlovec, Gary J.; Molthan, Andrew; Zavodsky, Bradley T.; Case, Jonathan L.; LaFontaine, Frank J.; Srikishen, Jayanthi

    2010-01-01

    The NASA Short-term Prediction Research and Transition Center (SPoRT)'s new "Weather in a Box" resources will provide weather research and forecast modeling capabilities for real-time application. Model output will provide additional forecast guidance and research into the impacts of new NASA satellite data sets and software capabilities. By combining several research tools and satellite products, SPoRT can generate model guidance that is strongly influenced by unique NASA contributions.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. Intel Xeon Phi accelerated Weather Research and Forecasting (WRF Goddard microphysics scheme

    Directory of Open Access Journals (Sweden)

    J. Mielikainen

    2014-12-01

    Full Text Available The Weather Research and Forecasting (WRF model is a numerical weather prediction system designed to serve both atmospheric research and operational forecasting needs. The WRF development is a done in collaboration around the globe. Furthermore, the WRF is used by academic atmospheric scientists, weather forecasters at the operational centers and so on. The WRF contains several physics components. The most time consuming one is the microphysics. One microphysics scheme is the Goddard cloud microphysics scheme. It is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF model. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the Goddard scheme code. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU does. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is one familiar to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discussed in this paper. The results show that the optimizations improved performance of Goddard microphysics scheme on Xeon Phi 7120P by a factor of 4.7×. In addition, the optimizations reduced the Goddard microphysics scheme's share of the total WRF processing time from 20.0 to 7.5%. Furthermore, the same

  16. 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.

  17. 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.

  18. Impact Analysis of Climate Change on Snow over a Complex Mountainous Region Using Weather Research and Forecast Model (WRF Simulation and Moderate Resolution Imaging Spectroradiometer Data (MODIS-Terra Fractional Snow Cover Products

    Directory of Open Access Journals (Sweden)

    Xiaoduo Pan

    2017-07-01

    Full Text Available Climate change has a complex effect on snow at the regional scale. The change in snow patterns under climate change remains unknown for certain regions. Here, we used high spatiotemporal resolution snow-related variables simulated by a weather research and forecast model (WRF including snowfall, snow water equivalent and snow depth along with fractional snow cover (FSC data extracted from Moderate Resolution Imaging Spectroradiometer Data (MODIS-Terra to evaluate the effects of climate change on snow over the Heihe River Basin (HRB, a typical inland river basin in arid northwestern China from 2000 to 2013. We utilized Empirical Orthogonal Function (EOF analysis and Mann-Kendall/Theil-Sen trend analysis to evaluate the results. The results are as follows: (1 FSC, snow water equivalent, and snow depth across the entire HRB region decreased, especially at elevations over 4500 m; however, snowfall increased at mid-altitude ranges in the upstream area of the HRB. (2 Total snowfall also increased in the upstream area of the HRB; however, the number of snowfall days decreased. Therefore, the number of extreme snow events in the upstream area of the HRB may have increased. (3 Snowfall over the downstream area of the HRB decreased. Thus, ground stations, WRF simulations and remote sensing products can be used to effectively explore the effect of climate change on snow at the watershed scale.

  19. National programme for weather, climate and atmosphere research. Annual report 1984/85

    CSIR Research Space (South Africa)

    Louw, CW

    1984-12-01

    Full Text Available This report reviews the activities of the National Programme for Weather, Climate and Atmosphere Research (NPWCAR) for 1984/85, highlights the findings and also discusses future developments and general needs regarding research within the framework...

  20. 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.

  1. Forecast Issues in the Urban Zone: Report of the 10th Prospectus Development Team of the U.S. Weather Research Program.

    Science.gov (United States)

    Dabberdt, Walter F.; Hales, Jeremy; Zubrick, Steven; Crook, Andrew; Krajewski, Witold; Doran, J. Christopher; Mueller, Cynthia; King, Clark; Keener, Ronald N.; Bornstein, Robert; Rodenhuis, David; Kocin, Paul; Rossetti, Michael A.; Sharrocks, Fred; Stanley, Ellis M., Sr.

    2000-09-01

    The 10th Prospectus Development Team (PDT-10) of the U.S. Weather Research Program was charged with identifying research needs and opportunities related to the short-term prediction of weather and air quality in urban forecast zones. Weather has special and significant impacts on large numbers of the U.S. population who live in major urban areas. It is recognized that urban users have different weather information needs than do their rural counterparts. Further, large urban areas can impact local weather and hydrologic processes in various ways. The recommendations of the team emphasize that human life and well-being in urban areas can be protected and enjoyed to a significantly greater degree. In particular, PDT-10 supports the need for 1) improved access to real-time weather information, 2) improved tailoring of weather data to the specific needs of individual user groups, and 3) more user-specific forecasts of weather and air quality. Specific recommendations fall within nine thematic areas: 1) development of a user-oriented weather database; 2) focused research on the impacts of visibility and icing on transportation; 3) improved understanding and forecasting of winter storms; 4) improved understanding and forecasting of convective storms; 5) improved forecasting of intense/severe lightning; 6) further research into the impacts of large urban areas on the location and intensity of urban convection; 7) focused research on the application of mesoscale forecasting in support of emergency response and air quality; 8) quantification and reduction of uncertainty in hydrological, meteorological, and air quality modeling; and 9) the need for improved observing systems. An overarching recommendation of PDT-10 is that research into understanding and predicting weather impacts in urban areas should receive increased emphasis by the atmospheric science community at large, and that urban weather should be a focal point of the U.S. Weather Research Program.

  2. 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

    based on several case studies. This research can be seen as a first step towards the operational use of InSAR data in state-of-the-art weather models and can be a driver for the design and development for new SAR missions, such as NISAR. References: [1] Hanssen, R. F., Weckwerth, T. M., Zebker, H. A., & Klees, R. (1999). High-resolution water vapor mapping from interferometric radar measurements.Science, 283(5406), 1297-1299. [2] P. Mateus, R. Tomé, G. Nico and J. Catalão, "Three-Dimensional Variational Assimilation of InSAR PWV Using the WRFDA Model," in IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 12, pp. 7323-7330, Dec. 2016. [3] Navascués, B., Calvo, J., Morales, G., Santos, C., Callado, A., Cansado, A., ... & García-Colombo, O. (2013). Long-term verification of HIRLAM and ECMWF forecasts over southern europe: History and perspectives of numerical weather prediction at AEMET. Atmospheric Research, 125, 20-33. [4] Seity, Y., P. Brousseau, S. Malardel, G. Hello, P. Bénard, F. Bouttier, C. Lac, and V. Masson, 2011: The AROME-France Convective-Scale Operational Model. Mon. Wea. Rev., 139, 976-991. [5] Lorenc, A. C. and Rawlins, F. (2005), Why does 4D-Var beat 3D-Var?. Q.J.R. Meteorol. Soc., 131: 3247-3257.

  3. 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.

  4. 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.

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    Hans Schermeyer

    2015-12-01

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

  7. Mission to the Sun-Earth L5 Lagrangian Point: An Optimal Platform for Space Weather Research

    Science.gov (United States)

    Vourlidas, Angelos

    2015-04-01

    The Sun-Earth Lagrangian L5 point is a uniquely advantageous location for space weather research and monitoring. It covers the "birth-to-impact" travel of solar transients; it enables imaging of solar activity at least 3 days prior to a terrestrial viewpoint and measures the solar wind conditions 4-5 days ahead of Earth impact. These observations, especially behind east limb magnetograms, will be a boon for background solar wind models, which are essential for coronal mass ejection (CME) and shock propagation forecasting. From an operational perspective, the L5 orbit is the space weather equivalent to the geosynchronous orbit for weather satellites. Optimal for both research and monitoring, an L5 mission is ideal for developing a Research-to-Operations capability in Heliophysics.

  8. 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.

  9. 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.

  10. 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.

  11. From Predicting Solar Activity to Forecasting Space Weather: Practical Examples of Research-to-Operations and Operations-to-Research

    CERN Document Server

    Steenburgh, R A; Millward, G H; 10.1007/s11207-013-0308-6

    2013-01-01

    The successful transition of research to operations (R2O) and operations to research (O2R) requires, above all, interaction between the two communities. We explore the role that close interaction and ongoing communication played in the successful fielding of three separate developments: an observation platform, a numerical model, and a visualization and specification tool. Additionally, we will examine how these three pieces came together to revolutionize interplanetary coronal mass ejection (ICME) arrival forecasts. A discussion of the importance of education and training in ensuring a positive outcome from R2O activity follows. We describe efforts by the meteorological community to make research results more accessible to forecasters and the applicability of these efforts to the transfer of space-weather research.We end with a forecaster "wish list" for R2O transitions. Ongoing, two-way communication between the research and operations communities is the thread connecting it all.

  12. 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

  13. 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

  14. 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.

  15. 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 ...

  16. The USWRP Workshop on the Weather Research Needs of the Private Sector.

    Science.gov (United States)

    Pielke, Roger A., Jr.; Abraham, Jim; Abrams, Elliot; Block, Jim; Carbone, Richard; Chang, David; Droegemeier, Kelvin; Emanuel, Kerry; Friday, Elbert W. Joe, Jr.; Gall, Robert; Gaynor, John; Getz, Rodger R.; Glickman, Todd; Hoggatt, Bradley; Hooke, William H.; Johnson, Edward R.; Kalnay, Eugenia; Kimpel, James Jeff; Kocin, Paul; Marler, Byron; Morss, Rebecca; Nathan, Ravi; Nelson, Steve; Pielke, Roger, Sr.; Pirone, Maria; Prater, Erwin; Qualley, Warren; Simmons, Kevin; Smith, Michael; Thomson, John; Wilson, Greg

    2003-07-01

    Private sector meteorology is a rapidly growing enterprise. It has been estimated that the provision of weather information has, by some estimates, a global market totaling in the billions of dollars. Further, the decisions based on such information could easily total trillions of dollars in the U.S. economy alone. The private sector clearly plays an important, and growing, role at the interface of weather research and the weather information needs of society. To date, little information has been paid to the connections of the meteorological research community and the scientific needs of the private sector. Thus, the time is ripe to stimulate a more active dialogue between what is generally considered the "basic" research community of physical and social scientists and those individuals and businesses that provide weather information to myriad customers across the U.S. economy. In December 2000, the U.S. Weather Research Program (supported by NSF, NOAA, NASA, and the U.S. Navy) sponsored a workshop in Palm Springs, California, to bring together weather researchers and representatives of private sector meteorology to discuss needs, wants, opportunities, and challenges and how to enhance the linkages between the two relatively detached communities. The workshop focused on developing a better understanding of the relations of research and private sector meteorology, which ultimately means a better understanding of one of the important connections of research and societal needs.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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

    modelers on the meteorology team. Some of the Olympic venues were located in the mountains to the west of Torino, while the rest were located on the relatively flat plain in and around the cities of Pinerolo and Torino to the east. DTRA partners at Pennsylvania State University (PSU) and the U.S. National Center for Atmospheric Research (NCAR) established data collection and assimilation, and forecast modeling processes that used special weather station observations provided by the Area Previsione e Monitoraggio Ambientale of Italy's ARPA Piemonte. At PSU a version of the MM5 was especially prepared to use observation data to forecast weather in a four-nest configuration. Two other DTRA partners provided independent weather forecast models against which the PSU model data were compared. The U.S. Air Force Weather Agency provided its MM5 forecast model data and the U.S. National Oceanic and Atmospheric Administration's National Centers for Environmental Prediction provided data from a special version of their WRF model. The project produced many opportunities to improve the modeling and forecasting capability at DTRA. DTRA and its partners plan to expand upon this experience during upcoming field tests, and to further improve and expand the capability to provide accurate high-resolution weather forecast information to hazard and consequence assessment operations.

  2. Operational Planetary Space Weather Services for the Europlanet 2020 Research Infrastructure

    Science.gov (United States)

    André, Nicolas; Grande, Manuel

    2017-04-01

    Under Horizon 2020, the Europlanet 2020 Research Infrastructure (EPN2020-RI, http://www.europlanet-2020-ri.eu) includes an entirely new Virtual Access Service, "Planetary Space Weather Services" (PSWS) that will extend the concepts of space weather and space situational awareness to other planets in our Solar System and in particular to spacecraft that voyage through it. PSWS will provide at the end of 2017 12 services distributed over 4 different service domains - 1) Prediction, 2) Detection, 3) Modelling, 4) Alerts. These services include 1.1) A 1D MHD solar wind prediction tool, 1.2) Extensions of a Propagation Tool, 1.3) A meteor showers prediction tool, 1.4) A cometary tail crossing prediction tool, 2.1) Detection of lunar impacts, 2.2) Detection of giant planet fireballs, 2.3) Detection of cometary tail events, 3.1) A Transplanet model of magnetosphere-ionosphere coupling, 3.2) A model of the Mars radiation environment, 3.3.) A model of giant planet magnetodisc, 3.4) A model of Jupiter's thermosphere, 4) A VO-event based alert system. We will detail in the present paper some of these services with a particular emphasis on those already operational at the time of the presentation (1.1, 1.2, 1.3, 2.2, 3.1, 4). The proposed Planetary Space Weather Services will be accessible to the research community, amateur astronomers as well as to industrial partners planning for space missions dedicated in particular to the following key planetary environments: Mars, in support of ESA's ExoMars missions; comets, building on the success of the ESA Rosetta mission; and outer planets, in preparation for the ESA JUpiter ICy moon Explorer (JUICE). These services will also be augmented by the future Solar Orbiter and BepiColombo observations. This new facility will not only have an impact on planetary space missions but will also allow the hardness of spacecraft and their components to be evaluated under variety of known conditions, particularly radiation conditions, extending

  3. 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...

  4. 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.

  5. 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.

  6. 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.

  7. Review on space weather in Latin America. 1. The beginning from space science research

    Science.gov (United States)

    Denardini, Clezio Marcos; Dasso, Sergio; Gonzalez-Esparza, J. Americo

    2016-11-01

    The present work is the first of a three-part review on space weather in Latin America. It comprises the evolution of several Latin American institutions investing in space science since the 1960s, focusing on the solar-terrestrial interactions, which today is commonly called space weather. Despite recognizing advances in space research in all of Latin America, this review is restricted to the development observed in three countries in particular (Argentina, Brazil and Mexico), due to the fact that these countries have recently developed operational centers for monitoring space weather. The review starts with a brief summary of the first groups to start working with space science in Latin America. This first part of the review closes with the current status and the research interests of these groups, which are described in relation to the most significant works and challenges of the next decade in order to aid in the solving of space weather open issues.

  8. 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.

  9. Performance tuning Weather Research and Forecasting (WRF) Goddard longwave radiative transfer scheme on Intel Xeon Phi

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

    2015-10-01

    Next-generation mesoscale numerical weather prediction system, the Weather Research and Forecasting (WRF) model, is a designed for dual use for forecasting and research. WRF offers multiple physics options that can be combined in any way. One of the physics options is radiance computation. The major source for energy for the earth's climate is solar radiation. Thus, it is imperative to accurately model horizontal and vertical distribution of the heating. Goddard solar radiative transfer model includes the absorption duo to water vapor,ozone, ozygen, carbon dioxide, clouds and aerosols. The model computes the interactions among the absorption and scattering by clouds, aerosols, molecules and surface. Finally, fluxes are integrated over the entire longwave spectrum.In this paper, we present our results of optimizing the Goddard longwave radiative transfer scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The coprocessor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discusses in this paper. The optimizations improved the performance of the original Goddard longwave radiative transfer scheme on Xeon Phi 7120P by a factor of 2.2x. Furthermore, the same optimizations improved the performance of the Goddard longwave radiative transfer scheme on a dual socket configuration of eight core Intel Xeon E5-2670 CPUs by a factor of 2.1x compared to the original Goddard longwave radiative transfer scheme code.

  10. 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).

  11. 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.

  12. 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

  13. Engaging Undergraduate Students in Space Weather Research at a 2- Year College

    Science.gov (United States)

    Damas, M. C.

    2017-07-01

    The Queensborough Community College (QCC) of the City University of New York (CUNY), a Hispanic and minority-serving institution, has been very successful at engaging undergraduate students in space weather research for the past ten years. Recently, it received two awards to support student research and education in solar and atmospheric physics under the umbrella discipline of space weather. Through these awards, students receive stipends during the academic year and summer to engage in scientific research. Students also have the opportunity to complete a summer internship at NASA and at other partner institutions. Funding also supports the development of course materials and tools in space weather. Educational materials development and the challenges of engaging students in research as early as their first year will be discussed. Once funding is over, how is the program sustained? Sustaining such a program, as well as how to implement it at other universities will also be discussed.

  14. 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...

  15. 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.

  16. 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.

  17. 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

  18. 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).

  19. 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).

  20. Increasing Diversity in Global Climate Change, Space Weather and Space Technology Research and Education

    Science.gov (United States)

    Johnson, L. P.; Austin, S. A.; Howard, A. M.; Boxe, C.; Jiang, M.; Tulsee, T.; Chow, Y. W.; Zavala-Gutierrez, R.; Barley, R.; Filin, B.; Brathwaite, K.

    2015-12-01

    This presentation describes projects at Medgar Evers College of the City University of New York that contribute to the preparation of a diverse workforce in the areas of ocean modeling, planetary atmospheres, space weather and space technology. Specific projects incorporating both undergraduate and high school students include Assessing Parameterizations of Energy Input to Internal Ocean Mixing, Reaction Rate Uncertainty on Mars Atmospheric Ozone, Remote Sensing of Solar Active Regions and Intelligent Software for Nano-satellites. These projects are accompanied by a newly developed Computational Earth and Space Science course to provide additional background on methodologies and tools for scientific data analysis. This program is supported by NSF award AGS-1359293 REU Site: CUNY/GISS Center for Global Climate Research and the NASA New York State Space Grant Consortium.

  1. 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.

  2. 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.)

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. Space Weather Research at IAA/NOA: Solar Energetic Particle Investigations

    Science.gov (United States)

    Malandraki, O.; Tylka, A. J.; Ng, C. K.; Marsden, R. G.; Tranquille, C.; Klein, K. L.; Patterson, J. D.; Armstrong, T. P.; Lanzerotti, L. J.; Papaioannou, A.; Marhavilas, P. K.; Tziotziou, K.; Crosby, N.; Vainio, R.

    2012-01-01

    applied. 'SEPServer' will enhance our understanding of the source, acceleration and transport of SEPs which is directly related to space weather research progress. 'COMESEP' sets out to develop tools for forecasting SEP radiation storms and geomagnetic storms based on scientific data analysis and extensive modeling. It is foreseen that these forecasting tools will be incorporated into an automated operational European Space Weather Alert system, which is the 'COMESEP' primary goal. Basic research activities on Space Weather carried out at IAA/NOA within the framework of these two projects will be presented including the analysis of SEPs and the associated electromagnetic emissions for selected case studies, the detailed study of the so-called 'reservoir effect' in the heliosphere as well as the impact of the large-scale structure of the IMF on the SEP profiles and its space weather implications. These project-related activities will provide the basis for future solar missions such as Solar Orbiter - in which IAA/NOA participates as a Co-Investigator (EPD instrument).

  9. Space Weather Monitoring for the IHY: Involving Students Worldwide in the Research Process

    Science.gov (United States)

    Scherrer, D.; Burress, B.; Ross, K.

    2008-06-01

    Our project explores how new methods of space weather data collection and networks of instruments can lead to innovative and exciting ways of involving audiences in the research process. We describe our space weather monitors, being distributed to high school students and universities worldwide for the International Heliophysical Year. The project includes a centralized data collection site, accessible to anyone with or without a monitor. Classroom materials, developed in conjunction with the Chabot Space & Science Center in California, are designed to introduce teachers and students to the Sun, space weather, the Earth's ionosphere, and how to use monitor data to encourage students to undertake "hands-on" research and gain experience with real scientific data. For more information, see \\url{http://sid-stanford.edu}.

  10. WWOSC 2014: research needs for better health resilience to weather hazards.

    Science.gov (United States)

    Jancloes, Michel; Anderson, Vidya; Gosselin, Pierre; Mee, Carol; Chong, Nicholas J

    2015-03-05

    The first World Weather Open Science Conference (WWOSC, held from 17-21 August 2014 in Montreal, Québec), provided an open forum where the experience and perspective of a variety of weather information providers and users was combined with the latest application advances in social sciences. A special session devoted to health focused on how best the most recent weather information and communication technologies (ICT) could improve the health emergency responses to disasters resulting from natural hazards. Speakers from a plenary presentation and its corresponding panel shared lessons learnt from different international multidisciplinary initiatives against weather-related epidemics, such as malaria, leptospirosis and meningitis and from public health responses to floods and heat waves such as in Ontario and Quebec, Canada. Participants could bear witness to recent progress made in the use of forecasting tools and in the application of increased spatiotemporal resolutions in the management of weather related health risks through anticipative interventions, early alert and warning and early responses especially by vulnerable groups. There was an agreement that resilience to weather hazards is best developed based on evidence of their health impact and when, at local level, there is a close interaction between health care providers, epidemiologists, climate services, public health authorities and communities. Using near real time health data (such as hospital admission, disease incidence monitoring…) combined with weather information has been recommended to appraise the relevance of decisions and the effectiveness of interventions and to make adjustments when needed. It also helps appraising how people may be more or less vulnerable to a particular hazard depending on the resilience infrastructures and services. This session was mainly attended by climate, environment and social scientists from North American and European countries. Producing a commentary appears

  11. 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

  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. 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.

  14. 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

  15. 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...

  16. 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...

  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. 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.

  19. 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.

  20. The Main Pillar: Assessment of Space Weather Observational Asset Performance Supporting Nowcasting, Forecasting and Research to Operations

    Science.gov (United States)

    Posner, Arik; Hesse, Michael; SaintCyr, Chris

    2014-01-01

    Space weather forecasting critically depends upon availability of timely and reliable observational data. It is therefore particularly important to understand how existing and newly planned observational assets perform during periods of severe space weather. Extreme space weather creates challenging conditions under which instrumentation and spacecraft may be impeded or in which parameters reach values that are outside the nominal observational range. This paper analyzes existing and upcoming observational capabilities for forecasting, and discusses how the findings may impact space weather research and its transition to operations. A single limitation to the assessment is lack of information provided to us on radiation monitor performance, which caused us not to fully assess (i.e., not assess short term) radiation storm forecasting. The assessment finds that at least two widely spaced coronagraphs including L4 would provide reliability for Earth-bound CMEs. Furthermore, all magnetic field measurements assessed fully meet requirements. However, with current or even with near term new assets in place, in the worst-case scenario there could be a near-complete lack of key near-real-time solar wind plasma data of severe disturbances heading toward and impacting Earth's magnetosphere. Models that attempt to simulate the effects of these disturbances in near real time or with archival data require solar wind plasma observations as input. Moreover, the study finds that near-future observational assets will be less capable of advancing the understanding of extreme geomagnetic disturbances at Earth, which might make the resulting space weather models unsuitable for transition to operations.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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.

  7. Vehicular-networking- and road-weather-related research in Sodankylä

    Science.gov (United States)

    Sukuvaara, Timo; Mäenpää, Kari; Ylitalo, Riika

    2016-10-01

    Vehicular-networking- and especially safety-related wireless vehicular services have been under intensive research for almost a decade now. Only in recent years has road weather information also been acknowledged to play an important role when aiming to reduce traffic accidents and fatalities via intelligent transport systems (ITSs). Part of the progress can be seen as a result of the Finnish Meteorological Institute's (FMI) long-term research work in Sodankylä within the topic, originally started in 2006. Within multiple research projects, the FMI Arctic Research Centre has been developing wireless vehicular networking and road weather services, in co-operation with the FMI meteorological services team in Helsinki. At the beginning the wireless communication was conducted with traditional Wi-Fi type local area networking, but during the development the system has evolved into a hybrid communication system of a combined vehicular ad hoc networking (VANET) system with special IEEE 802.11p protocol and supporting cellular networking based on a commercial 3G network, not forgetting support for Wi-Fi-based devices also. For piloting purposes and further research, we have established a special combined road weather station (RWS) and roadside unit (RSU), to interact with vehicles as a service hotspot. In the RWS-RSU we have chosen to build support to all major approaches, IEEE 802.11, traditional Wi-Fi and cellular 3G. We employ road weather systems of FMI, along with RWS and vehicle data gathered from vehicles, in the up-to-date localized weather data delivered in real time. IEEE 802.11p vehicular networking is supported with Wi-Fi and 3G communications. This paper briefly introduces the research work related to vehicular networking and road weather services conducted in Sodankylä, as well as the research project involved in this work. The current status of instrumentation, available services and capabilities are presented in order to formulate a clear general view of

  8. Four top tier challenges for Space Weather Research for the next decade

    Science.gov (United States)

    Spann, James

    2017-04-01

    The science of space weather is that which (1) develops the knowledge and understanding to predict conditions in space that impact life and society, and (2) leads to operational solutions that protect assets and systems to the benefit of society. Advances over the past decades in this area of research have yielded amazing discoveries and significant strides toward fulfilling the promise of an operational solution to space weather, and have facilitated the enterprise to make its way into the realm of national and international policy. Even if the resources, technologies, and political will were available to take advantage of this progress, our current lack of understanding of space weather would prevent the implementation of a fully operational system. This talk will highlight four distinct areas of research that, if fully understood, could enable operational solutions to space weather impacts, given sufficient resources and political will. These areas are (a) trigger of solar variability, (b) acceleration of mass and energy in interplanetary space, (c) geoeffectiveness of solar wind, and (d) ionospheric variability. A brief description, technical challenges, and possible pathways to resolution will be offered for each of these areas.

  9. Research Data Alliance's Interest Group on "Weather, Climate and Air Quality"

    Science.gov (United States)

    Bretonnière, Pierre-Antoine; Benincasa, Francesco

    2016-04-01

    Research Data Alliance's Interest Group on "Weather, Climate and Air Quality" More than ever in the history of Earth sciences, scientists are confronted with the problem of dealing with huge amounts of data that grow continuously at a rate that becomes a challenge to process and analyse them using conventional methods. Data come from many different and widely distributed sources, ranging from satellite platforms and in-situ sensors to model simulations, and with different degrees of openness. How can Earth scientists deal with this diversity and big volume and extract useful information to understand and predict the relevant processes? The Research Data Alliance (RDA, https://rd-alliance.org/), an organization that promotes and develops new data policies, data standards and focuses on the development of new technical solutions applicable in many distinct areas of sciences, recently entered in its third phase. In this framework, an Interest Group (IG) comprised of community experts that are committed to directly or indirectly enable and facilitate data sharing, exchange, or interoperability in the fields of weather, climate and air quality has been created recently. Its aim is to explore and discuss the challenges for the use and efficient analysis of large and diverse datasets of relevance for these fields taking advantage of the knowledge generated and exchanged in RDA. At the same time, this IG intends to be a meeting point between members of the aforementioned communities to share experiences and propose new solutions to overcome the forthcoming challenges. Based on the collaboration between several research meteorological and European climate institutes, but also taking into account the input from the private (from the renewable energies, satellites and agriculture sectors for example) and public sectors, this IG will suggest practical and applicable solutions for Big Data issues, both at technological and policy level, encountered by these communities. We

  10. 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.

  11. 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

  12. Engaging Undergraduate Students in Space Weather Research at a 2-Year College

    Science.gov (United States)

    Chantale Damas, M.

    2016-07-01

    The Queensborough Community College (QCC) of the City University of New York (CUNY), a Hispanic and minority-serving institution, has been very successful at engaging undergraduate students in space weather research for the past ten years. Recently, it received two awards* to support student research and education in solar and atmospheric physics under the umbrella discipline of space weather. Through these awards, students receive stipends during the academic year and summer to engage in research. Students also have the opportunity to complete a summer internship at NASA and other partner institutions. Funding also supports the development of course materials and tools in space weather. Educational materials development and the challenges of engaging students in research as early as their first year will be discussed. Once funding is over, how is the program sustained? Sustaining such a program, as well as how to implement it at other universities will also be discussed. *This project is supported by the National Science Foundation Geosciences Directorate under NSF Award Number DES-1446704 and the NASA MUREP Community College Curriculum Improvement (MC3I) Grant/Cooperative Agreement Number NNX15AV96A.

  13. 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

  14. 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.

  15. 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.

  16. Science Coordination in Support of the US Weather Research Program Office of the Lead Scientist (OLS) and for Coordination with the World Weather Research (WMO) Program

    Science.gov (United States)

    Gall, Robert

    2005-01-01

    This document is the final report of the work of the Office of the Lead Scientist (OLS) of the U.S. Weather Research Program (USWRP) and for Coordination of the World Weather Research Program (WWRP). The proposal was for a continuation of the duties and responsibilities described in the proposal of 7 October, 1993 to NSF and NOAA associated with the USWRP Lead Scientist then referred to as the Chief Scientist. The activities of the Office of the Lead Scientist (OLS) ended on January 31, 2005 and this report describes the activities undertaken by the OLS from February 1, 2004 until January 3 1, 2005. The OLS activities were under the cosponsorship of the agencies that are members of the Interagency Working Group (IWG) of the US WRP currently: NOAA, NSF, NASA, and DOD. The scope of the work described includes activities that were necessary to develop, facilitate and implement the research objectives of the USWRP consistent with the overall program goals and specific agency objectives. It included liaison with and promotion of WMO/WWW activities that were consistent with and beneficial to the USWRP programs and objectives. Funds covered several broad categories of activity including meetings convened by the Lead Scientist, OLS travel, partial salary and benefits support, publications, hard-copy dissemination of reports and program announcements and the development and maintenance of the USWRP website. In addition to funding covered by this grant, NCAR program funds provided co-sponsorship of half the salary and benefits resources of the USWRP Lead Scientist (.25 FTE) and the WWRP Chairman/Liaison (.167 FTE). Also covered by the grant were partial salaries for the Science Coordinator for the hurricane portion of the program and partial salary for a THORPEX coordinator.

  17. 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

  18. 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...

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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 ...

  11. 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.

  12. 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 %.

  13. Roundhouse (RND) Mountain Top Research Site: Measurements and Uncertainties for Winter Alpine Weather Conditions

    Science.gov (United States)

    Gultepe, I.; Isaac, G. A.; Joe, P.; Kucera, P. A.; Theriault, J. M.; Fisico, T.

    2014-01-01

    The objective of this work is to better understand and summarize the mountain meteorological observations collected during the Science of Nowcasting Winter Weather for the Vancouver 2010 Olympics and Paralympics (SNOW-V10) project that was supported by the Fog Remote Sensing and Modeling (FRAM) project. The Roundhouse (RND) meteorological station was located 1,856 m above sea level that is subject to the winter extreme weather conditions. Below this site, there were three additional observation sites at 1,640, 1,320, and 774 m. These four stations provided some or all the following measurements at 1 min resolution: precipitation rate (PR) and amount, cloud/fog microphysics, 3D wind speed (horizontal wind speed, U h; vertical air velocity, w a), visibility (Vis), infrared (IR) and shortwave (SW) radiative fluxes, temperature ( T) and relative humidity with respect to water (RHw), and aerosol observations. In this work, comparisons are made to assess the uncertainties and variability for the measurements of Vis, RHw, T, PR, and wind for various winter weather conditions. The ground-based cloud imaging probe (GCIP) measurements of snow particles using a profiling microwave radiometer (PMWR) data have also been shown to assess the icing conditions. Overall, the conclusions suggest that uncertainties in the measurements of Vis, PR, T, and RH can be as large as 50, >60, 50, and >20 %, respectively, and these numbers may increase depending on U h, T, Vis, and PR magnitude. Variability of observations along the Whistler Mountain slope (~500 m) suggested that to verify the models, model space resolution should be better than 100 m and time scales better than 1 min. It is also concluded that differences between observed and model based parameters are strongly related to a model's capability of accurate prediction of liquid water content (LWC), PR, and RHw over complex topography.

  14. Activities of the Japanese space weather forecast center at Communications Research Laboratory.

    Science.gov (United States)

    Watari, Shinichi; Tomita, Fumihiko

    2002-12-01

    The International Space Environment Service (ISES) is an international organization for space weather forecasts and belongs to the International Union of Radio Science (URSI). There are eleven ISES forecast centers in the world, and Communications Research Laboratory (CRL) runs the Japanese one. We make forecasts on the space environment and deliver them over the phones and through the Internet. Our forecasts could be useful for human activities in space. Currently solar activity is near maximum phase of the solar cycle 23. We report the several large disturbances of space environment occurred in 2001, during which low-latitude auroras were observed several times in Japan.

  15. 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

  16. 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).

  17. The Sydney 2000 World Weather Research Programme Forecast Demonstration Project: Overview and Current Status.

    Science.gov (United States)

    Keenan, T.; Joe, P.; Wilson, J.; Collier, C.; Golding, B.; Burgess, D.; May, P.; Pierce, C.; Bally, J.; Crook, A.; Seed, A.; Sills, D.; Berry, L.; Potts, R.; Bell, I.; Fox, N.; Ebert, E.; Eilts, M.;  O'Loughlin, K.;  Webb, R.;  Carbone, R.;  Browning, K.;  Roberts, R.;  Mueller, C.

    2003-08-01

    The first World Weather Research Programme (WWRP) Forecast Demonstration Project (FDP), with a focus on nowcasting, was conducted in Sydney, Australia, from 4 September to 21 November 2000 during a period associated with the Sydney 2000 Olympic Games. Through international collaboration, nine nowcasting systems from the United States, United Kingdom, Canada, and Australia were deployed at the Sydney Office of the Bureau of Meteorology (BOM) to demonstrate the capability of modern forecast systems and to quantify the associated benefits in the delivery of a real-time nowcast service. On-going verification and impact studies supported by international committees assisted by the WWRP formed an integral part of this project. A description is given of the project, including component systems, the weather, and initial outcomes. Initial results show that the nowcasting systems tested were transferable and able to provide valuable information enhancing BOM nowcasts. The project provided for unprecedented interchange of concepts and ideas between forecasters, researchers, and end users in an operational framework where they all faced common issues relevant to real time nowcast decision making. A training workshop sponsored by the World Meteorological Organization (WMO) was also held in conjunction with the project so that other member nations could benefit from the FDP.

  18. 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

  19. 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...

  20. 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

  1. 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.

  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. 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...

  4. 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.

  5. Research Project Entitled "The Dynamics and Physical Processes in The Weather and Climate System" --Part Ⅰ: A Brief Introduction

    Institute of Scientific and Technical Information of China (English)

    罗云峰; 郑文静; 周小刚

    2004-01-01

    In the beginning of the 21st century, the Tenth Five-Year Priority Research Projects of the Earth Sciences of the National Natural Science Foundation of China (NSFC) were initiated. After nearly a two-year long process to prepare, the first version of six Priority Research Projects of Earth Sciences was published in October 2001 by NSFC, viz., Local Response to Global Changes, Life Process and Environment,Dynamics and Physical Processes in the Weather and Climate System, Continental Dynamics, Regional Sustainable Development, Solar-Terrestrial Environment and Space Weather. The process involved more than 200 renowned Chinese scientists and many departments and agencies in China. The six Priority Research Projects guide the research effort of the earth sciences for the NSFC from year 2001 to 2005.This paper provides a brief introduction to the Third Priority Research Project of the Department of Earth Sciences of NSFC-Dynamics and Physical Processes in the Weather and Climate System (DPWOS).

  6. 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

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

    Science.gov (United States)

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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. Nimble@ITCEcnoGrid: A Grid in Research Domain for Weather Forecasting

    CERN Document Server

    Dhir, Vijay; Dutta, Maitreyee; 10.5121/ijgca.2011.2404

    2012-01-01

    Computer Technology has Revolutionized Science. This has motivated scientists to develop mathematical model to simulate salient features of Physical universe. These models can approximate reality at many levels of scale such as atomic nucleus, Earth's biosphere & weather/climate assessment. If the computer power is greater, the greater will be the accuracy in approximation i.e. close will be the approximation to the reality. The speed of the computer required for solution of such problems require computers with processing power of teraflops to Pets flops speed.. The way to speed up the computation is to "parallelize" it. One of the approach is to use multimillion dollar Supercomputer or use Computational Grid (which is also called poor man's supercomputer) having geographically distributed resources e.g. SETI@home (Used to detect radio waves emitted by intelligent civilizations outside earth) has 4.6 million participants computers. There are many alternatives tools available to achieve this goal like Glob...

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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...

  2. 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.

  3. 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.

  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. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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....

  11. 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

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. 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...

  4. 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.

  5. Influence of bulk microphysics schemes upon Weather Research and Forecasting (WRF) version 3.6.1 nor'easter simulations

    Science.gov (United States)

    Nicholls, Stephen D.; Decker, Steven G.; Tao, Wei-Kuo; Lang, Stephen E.; Shi, Jainn J.; Mohr, Karen I.

    2017-03-01

    This study evaluated the impact of five single- or double-moment bulk microphysics schemes (BMPSs) on Weather Research and Forecasting model (WRF) simulations of seven intense wintertime cyclones impacting the mid-Atlantic United States; 5-day long WRF simulations were initialized roughly 24 h prior to the onset of coastal cyclogenesis off the North Carolina coastline. In all, 35 model simulations (five BMPSs and seven cases) were run and their associated microphysics-related storm properties (hydrometer mixing ratios, precipitation, and radar reflectivity) were evaluated against model analysis and available gridded radar and ground-based precipitation products. Inter-BMPS comparisons of column-integrated mixing ratios and mixing ratio profiles reveal little variability in non-frozen hydrometeor species due to their shared programming heritage, yet their assumptions concerning snow and graupel intercepts, ice supersaturation, snow and graupel density maps, and terminal velocities led to considerable variability in both simulated frozen hydrometeor species and radar reflectivity. WRF-simulated precipitation fields exhibit minor spatiotemporal variability amongst BMPSs, yet their spatial extent is largely conserved. Compared to ground-based precipitation data, WRF simulations demonstrate low-to-moderate (0.217-0.414) threat scores and a rainfall distribution shifted toward higher values. Finally, an analysis of WRF and gridded radar reflectivity data via contoured frequency with altitude diagrams (CFADs) reveals notable variability amongst BMPSs, where better performing schemes favored lower graupel mixing ratios and better underlying aggregation assumptions.

  6. 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...

  7. 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...

  8. 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.

  9. 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...

  10. 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

  11. Meeting summary - Coastal meteorology and oceanography: Report of the third prospectus development team of the U.S. Weather Research Program to NOAA and NSF

    Science.gov (United States)

    Rotunno, R.; Pietrafesa, L.J.; Allen, J.S.; Colman, B.R.; Dorman, C.M.; Kreitzberg, C.W.; Lord, S.J.; McPhee, M.G.; Mellor, G.L.; Mooers, C.N.K.; Niiler, P.P.; Pielke, R.A.; Powell, M.D.; Rogers, D.P.; Smith, J.D.; Xie, Lingtian; Carbone, R.

    1996-01-01

    U.S. Weather Research Program (USWRP) prospectus development teams (PDTs) are small groups of scientists that are convened by the USWRP lead scientist on a one-time basis to discuss critical issues and to provide advice related to future directions of the program. PDTs are a principal source of information for the Science Advisory Committee, which is a standing committee charged with the duty of making recommendations to the Program Office based upon overall program objectives. PDT-1 focused on theoretical issues, and PDT-2 on observational issues; PDT-3 is the first of several to focus on more specialized topics. PDT-3 was convened to identify forecasting problems related to U.S. coastal weather and oceanic conditions, and to suggest likely solution strategies. There were several overriding themes that emerged from the discussion. First, the lack of data in and over critical regions of the ocean, particularly in the atmospheric boundary layer, and the upper-ocean mixed layer were identified as major impediments to coastal weather prediction. Strategies for data collection and dissemination, as well as new instrument implementation, were discussed. Second, fundamental knowledge of air-sea fluxes and boundary layer structure in situations where there is significant mesoscale variability in the atmosphere and ocean is needed. Companion field studies and numerical prediction experiments were discussed. Third, research prognostic models suggest that future operational forecast models pertaining to coastal weather will be high resolution and site specific, and will properly treat effects of local coastal geography, orography, and ocean state. The view was expressed that the exploration of coupled air-sea models of the coastal zone would be a particularly fruitful area of research. PDT-3 felt that forecasts of land-impacting tropical cyclones, Great Lakes-affected weather, and coastal cyclogenesis, in particular, would benefit from such coordinated modeling and field

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

    Science.gov (United States)

    2012-09-01

    difficulty of making accurate fallout predictions. 2.2.1 Fireball In the first few instants following a nuclear explosion, fireball temperatures can...exceed 107 K, and the resulting gradient between the atmospheric and the fireball temperatures will cause the fireball to rise [2]. The temperature...will decrease initially through radiative cooling, but as toroidal motion of the fireball begins to dominate, entrainment of cold air will result in

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. Promoting equal opportunity within the transregional Collabortive Research Center "Waves to Weather" (W2W)

    Science.gov (United States)

    Laurian, Audine; Craig, George

    2017-04-01

    The promotion of equal opportunity (EO) is a central commitment of the transregional Collaborative Research Center "Waves to Weather" (W2W) funded by the DFG. Intense efforts are made to promote EO measures and to support female scientists and parents of young children throughout their career within the consortium. Since the start of W2W in July 2015, the following actions have been undertaken: - an EO committee has been created, which consists of parents of young children and a PhD student from the main partner institutions in Munich, in Mainz and in Karlsruhe. The EO committee has agreed on a list of EO measures to be offered within the consortium and a flyer advertising these measures has been designed, produced and distributed - childcare has been organized during the meetings organized by W2W - outreach events addressed to school girls and promoting the study of physics and mathematics at the university (e.g. Girls' Day) has been organized in Munich, in Mainz and in Karlsruhe - student helpers have been hired to reduce the workload of female principal investigators with young children - efforts are made to invite female keynote speakers to the annual meetings of W2W - regular meetings with the Women's Officer for the Faculty of Physics at the LMU are taking place, e..g to setup a parent-child office. These measures have received very positive feedback from the W2W community and from the partner institutions. Discussions and exchanges of experience with colleagues from other research programs and institutions regarding EO measures would be greatly beneficial to promote EO further.

  1. Nimble@ITCEcnoGrid: A Grid in Research Domain for Weather Forecasting

    Directory of Open Access Journals (Sweden)

    Vijay Dhir

    2012-01-01

    Full Text Available Computer Technology has Revolutionized Science. This has motivated scientists to develop mathematicalmodel to simulate salient features of Physical universe .These models can approximate reality at manylevels of scale such as atomic nucleus, Earth’s biosphere & weather/climate assessment. To solve these type of complex problems in usable time frame , there is a need of high performance powerful computer mechanism which can do the calculations in a time bound with high precision. If the computer power isgreater, the greater will be the accuracy in approximation i.e. close will be the approximation to thereality. The speed of the computer required for solution of such problems require computers with processing power of teraflops to Pets flops speed.. The way to speed up the computation is to “parallelize” it i.e. divide the work into modules that can be worked on by separate processors at the same time. Thus we can solve the problems that are Non-Polynomial form in polynomial time. One of the approach is to use multimillion dollar Supercomputer or use Computational Grid ( Which is also called poor man’s supercomputer having geographically distributed resources e.g. SETI@home(Used to detect radio waves emitted by intelligent civilizations outside earth has 4.6 million participants computers. There are many alternatives tools available to achieve this goal like Globus Toolkit, Entropia, Legion, BOINC etc but they are mainly based on Linux platform. As majority of the computers available are windows based, so it will be easy to develop a larger network of computers which will use the freecycles of the computer to solve the complex problem at window platform. Nimble@ITCEcnoGrid has been developed. It includes the feature of Inter Thread Communication which is missing in any of the toolkits available. Nimble@ITCEcnoGrid Framework (A Fast Grid with Inter-thread communication with Economic Based Policy was tested for computation of ‘PI’ up to

  2. Space Weather Around the World: Using Educational Technology to Engage Teachers and Students in Science Research

    Science.gov (United States)

    Lewis, E.; Cline, T.; Thieman, J.

    2007-12-01

    The Space Weather Around the World Program uses NASA satellite data and education technology to provide a framework for students and teachers to study the effects of solar storms on the Earth and then report their results at their own school and to others around the world. Teachers and students are trained to create Space Weather Action Centers by building their own equipment to take data or using real satellite and/or ground-based data available through the internet to study and track the effects of solar storms. They can then predict "space weather" for our planet and what the effects might be on aurora, Earth-orbiting satellites, humans in space, etc. The results are presented via proven education technology techniques including weather broadcasts using green screen technology, podcasts, webcasts and distance learning events. Any one of these techniques can capture the attention of the audience, engage them in the science and spark an interest that will encourage continued participation. Space Weather Around the World uses all of these techniques to engage millions. We will share the techniques that can be applied to any subject area and will increase participation and interest in that content. The Space Weather program provides students and teachers with unique and compelling teaching and learning experiences that will help to improve science literacy, spark an interest in careers in Science, Technology, Engineeering, and Mathematics (STEM), and engage children and adults in shaping and sharing the experience of discovery and exploration.

  3. 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)

  4. Progresses of Researches on Numerical Weather Prediction in China:1999-2002

    Institute of Scientific and Technical Information of China (English)

    薛纪善

    2004-01-01

    The recent progresses in the research and development of (NWP) in China are reviewed in this paper. The most impressive achievements are the development of direct assimilation of satellite irradiances with a 3DVAR (three-dimentional variational) data assimilation system and a non-hydrostatic model with a semi-Lagrangian semi-implicit scheme. Progresses have also been made in model physics and model application to precipitation and environmental forecasts. Some scientific issues of great importance for further development are discussed.

  5. 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.

  6. 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.

  7. 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.

  8. Learning to become a member of a community of scientists: An ethnographic study of student participation in weather research in two middle school classes

    Science.gov (United States)

    Brown, Candice Michelle

    2000-11-01

    This research project involves the investigation of the opportunities to learn science and about science through an extended year-long weather project in two middle school science classrooms. The theoretical framework draws together two compatible but as yet unconnected bodies of literature. From studies of scientific practices, the importance of the ways science is learned through practice in authentic settings are considered. Studies of situated cognition are examined as well to discern how students learn in context-specific ways. This empirical research is unique in three important ways. First, the research took place in two different middle school classrooms and utilized extensive participant observation over the course of the entire academic year and focus group interviews with students. One of the classes was mostly Hispanic students of lower socioeconomic status. The other class was primarily Caucasian students of middle socioeconomic status. Second, the teachers in the study participated in a multi-year service program coordinated by the local university. The teachers worked with their students to complete a year-long weather project that involves data collection, representation, analysis, and interpretation. Third, the project involves long-term study of weather data. As a result, students participating in the research over the year began to challenge the claims of their peers. Few classroom studies of earth science have been conducted and published and even fewer involved student managed school science research projects. The findings from this study can be used as a model for how long-term research projects in science can be incorporated into middle school science classes. This project is thus very important in the field of science education for understanding ways to make science accessible and appealing to a variety of students.

  9. THE RESEARCH ON RELATIONSHIP BETWEEN OUTER CIRCULATION OF TROPICAL CYCLONES AND HIGH TEMPERATURE WEATHER IN GUANGZHOU

    Institute of Scientific and Technical Information of China (English)

    LU Shan; YE Meng

    2007-01-01

    Using historical synoptic data, the surface observation data of Guangzhou, the data in the Yearbook on Tropical Cyclones of P. R. China, and NCEP/NCAR reanalysis data of geopotential height,vertical velocity from June to September over the years 1983 to 2004, and defining three days or more in succession with daily maximum temperature over 35℃as a process of high temperature weather, this work analyzes the relationship between the activity of tropical cyclones and the disastrous high temperature weather in Guangzhou. The result shows that disastrous high temperature weather in Guangzhou is closely related to the outer circulation of tropical cyclones, and high temperatures weather over 37℃ occur mainly when tropical cyclones move in the range from 400 to 1600 km southeast or east to Guangzhou. Furthermore,rapid temperature increase with descending motion resulting from tropical cyclones is the major factor that induces disastrous high temperature weather in Guangzhou when the city is controlled by the subtropical high.

  10. 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...

  11. Using Arduinos and 3D-printers to Build Research-grade Weather Stations and Environmental Sensors

    Science.gov (United States)

    Ham, J. M.

    2013-12-01

    Many plant, soil, and surface-boundary-layer processes in the geosphere are governed by the microclimate at the land-air interface. Environmental monitoring is needed at smaller scales and higher frequencies than provided by existing weather monitoring networks. The objective of this project was to design, prototype, and test a research-grade weather station that is based on open-source hardware/software and off-the-shelf components. The idea is that anyone could make these systems with only elementary skills in fabrication and electronics. The first prototypes included measurements of air temperature, humidity, pressure, global irradiance, wind speed, and wind direction. The best approach for measuring precipitation is still being investigated. The data acquisition system was deigned around the Arduino microcontroller and included an LCD-based user interface, SD card data storage, and solar power. Sensors were sampled at 5 s intervals and means, standard deviations, and maximum/minimums were stored at user-defined intervals (5, 30, or 60 min). Several of the sensor components were printed in plastic using a hobby-grade 3D printer (e.g., RepRap Project). Both passive and aspirated radiation shields for measuring air temperature were printed in white Acrylonitrile Butadiene Styrene (ABS). A housing for measuring solar irradiance using a photodiode-based pyranometer was printed in opaque ABS. The prototype weather station was co-deployed with commercial research-grade instruments at an agriculture research unit near Fort Collins, Colorado, USA. Excellent agreement was found between Arduino-based system and commercial weather instruments. The technology was also used to support air quality research and automated air sampling. The next step is to incorporate remote access and station-to-station networking using Wi-Fi, cellular phone, and radio communications (e.g., Xbee).

  12. Ionosphere Waves Service (IWS) – a problem-oriented tool in ionosphere and Space Weather research produced by POPDAT project

    OpenAIRE

    Ferencz Csaba; Lizunov Georgii; Crespon François; Price Ivan; Bankov Ludmil; Przepiórka Dorota; Brieß Klaus; Dudkin Denis; Girenko Andrey; Korepanov Valery; Kuzmych Andrii; Skorokhod Tetiana; Marinov Pencho; Piankova Olena; Rothkaehl Hanna

    2014-01-01

    In the frame of the FP7 POPDAT project the Ionosphere Waves Service (IWS) has been developed and opened for public access by ionosphere experts. IWS is forming a database, derived from archived ionospheric wave records to assist the ionosphere and Space Weather research, and to answer the following questions: How can the data of earlier ionospheric missions be reprocessed with current algorithms to gain more profitable results? How could the scientific community be provided with a new insight...

  13. 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.

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Use of Atmospheric Infrared Sounder clear-sky and cloud-cleared radiances in the Weather Research and Forecasting 3DVAR assimilation system for mesoscale weather predictions over the Indian region

    Science.gov (United States)

    Singh, Randhir; Kishtawal, C. M.; Pal, P. K.

    2011-11-01

    A set of assimilation experiments is conducted with the Three-Dimensional Variational (3DVAR) data assimilation system associated with the Weather Research and Forecasting (WRF) model. The purpose of the investigation is to assess the impact on forecast skill in response to assimilation of the Atmospheric Infrared Sounder (AIRS) clear-sky and cloud-cleared radiances over the Indian region. This is the first study that makes use of cloud-cleared radiances in the WRF system. Two sets of thirty-one 72 h forecasts are performed, all initialized at 00:00 UTC each day throughout the month of July 2010, to compare the model performance consequent to assimilation of clear-sky versus cloud-cleared radiances. A rigorous validation is produced against National Centers for Environmental Prediction analyzed wind, temperature, and moisture. In addition, the precipitation forecast skill is assessed against Tropical Rainfall Measuring Mission observations. The results show improvement in forecast skill consequent to the assimilation of cloud-cleared radiances (CCR). The implications of using CCR for operational weather forecasting appear to be significant. Since only a small fraction of AIRS channels are cloud-free, information obtained in cloudy regions, which is meteorologically very significant, is lost when assimilating only clear-sky radiances (CSR). On the contrary, assimilation of CCR allows a larger yield, which leads to improved model performance. The assimilation of CCR resulted in significantly improved rainfall prediction compared to that obtained from the use of CSR. The finding of this study clearly shows the advantage of CCR available from clear-sky as well as from partly cloudy regions as compared to CSR, which are available only in clear-sky regions.

  6. 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.

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

    Science.gov (United States)

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

    2012-01-01

    The NASA GSFC Space Weather Center (http://swc.gsfc.nasa.gov) is committed to providing forecasts, alerts, research, and educational support to address NASA's space weather needs - in addition to the needs of the general space weather community. We provide a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, custom space weather alerts and products, weekly summaries and reports, and most recently - video casts. There are many challenges in providing accurate descriptions of past, present, and expected space weather events - and the Space Weather Center at NASA GSFC employs several innovative solutions to provide access to a comprehensive collection of both observational data, as well as space weather model/simulation data. We'll describe the challenges we've faced with managing hundreds of data streams, running models in real-time, data storage, and data dissemination. We'll also highlight several systems and tools that are utilized by the Space Weather Center in our daily operations, all of which are available to the general community as well. These systems and services include a web-based application called the Integrated Space Weather Analysis System (iSWA http://iswa.gsfc.nasa.gov), two mobile space weather applications for both IOS and Android devices, an external API for web-service style access to data, google earth compatible data products, and a downloadable client-based visualization tool.

  8. 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.

  9. Research on Trends in Extreme Weather Events and their Effects on Grapevine in Romanian Viticulture

    OpenAIRE

    Georgeta Mihaela Bucur; Anca Cristina Babes

    2016-01-01

    The aim of this work was to investigate the frequency and intensity of extreme weather events in various centers from Romania’s viticultural regions: winter frost, extreme temperatures during the growing season and summer droughts. Winter frost damaging the vine is a significant risk to grape production, mainly in the plains and lowlands to the foothills. The frequency of winter frost damaging the vine has increased during the last decades, in the context of climate change. Also, there has be...

  10. 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

  11. Weathering the Storm: Developing a Spatial Data Infrastructure and Online Research Platform for Oil Spill Preparedness

    Science.gov (United States)

    Bauer, J. R.; Rose, K.; Romeo, L.; Barkhurst, A.; Nelson, J.; Duran-Sesin, R.; Vielma, J.

    2016-12-01

    Efforts to prepare for and reduce the risk of hazards, from both natural and anthropogenic sources, which threaten our oceans and coasts requires an understanding of the dynamics and interactions between the physical, ecological, and socio-economic systems. Understanding these coupled dynamics are essential as offshore oil & gas exploration and production continues to push into harsher, more extreme environments where risks and uncertainty increase. However, working with these large, complex data from various sources and scales to assess risks and potential impacts associated with offshore energy exploration and production poses several challenges to research. In order to address these challenges, an integrated assessment model (IAM) was developed at the Department of Energy's (DOE) National Energy Technology Laboratory (NETL) that combines spatial data infrastructure and an online research platform to manage, process, analyze, and share these large, multidimensional datasets, research products, and the tools and models used to evaluate risk and reduce uncertainty for the entire offshore system, from the subsurface, through the water column, to coastal ecosystems and communities. Here, we will discuss the spatial data infrastructure and online research platform, NETL's Energy Data eXchange (EDX), that underpin the offshore IAM, providing information on how the framework combines multidimensional spatial data and spatio-temporal tools to evaluate risks to the complex matrix of potential environmental, social, and economic impacts stemming from modeled offshore hazard scenarios, such as oil spills or hurricanes. In addition, we will discuss the online analytics, tools, and visualization methods integrated into this framework that support availability and access to data, as well as allow for the rapid analysis and effective communication of analytical results to aid a range of decision-making needs.

  12. 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

  13. 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.

  14. 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

  15. 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...

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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...

  3. 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

  4. Mathematical modeling in psychological researches

    Directory of Open Access Journals (Sweden)

    Aleksandra Zyolko

    2013-04-01

    Full Text Available The author considers the nature of mathematical modeling and its significance in psychological researches. The author distinguishes the types of mathematical models: deterministic, stochastic models and synergetic models. The system approach is proposed as an instrument of implementation of mathematical modelling in psychological research.

  5. 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.

  6. 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

  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. 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.

  9. 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

  10. 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

  11. 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

  12. 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.

  13. Ionosphere Waves Service (IWS) - a problem-oriented tool in ionosphere and Space Weather research produced by POPDAT project

    Science.gov (United States)

    Ferencz, Csaba; Lizunov, Georgii; Crespon, François; Price, Ivan; Bankov, Ludmil; Przepiórka, Dorota; Brieß, Klaus; Dudkin, Denis; Girenko, Andrey; Korepanov, Valery; Kuzmych, Andrii; Skorokhod, Tetiana; Marinov, Pencho; Piankova, Olena; Rothkaehl, Hanna; Shtus, Tetyana; Steinbach, Péter; Lichtenberger, János; Sterenharz, Arnold; Vassileva, Any

    2014-05-01

    In the frame of the FP7 POPDAT project the Ionosphere Waves Service (IWS) has been developed and opened for public access by ionosphere experts. IWS is forming a database, derived from archived ionospheric wave records to assist the ionosphere and Space Weather research, and to answer the following questions: How can the data of earlier ionospheric missions be reprocessed with current algorithms to gain more profitable results? How could the scientific community be provided with a new insight on wave processes that take place in the ionosphere? The answer is a specific and unique data mining service accessing a collection of topical catalogs that characterize a huge number of recorded occurrences of Whistler-like Electromagnetic Wave Phenomena, Atmosphere Gravity Waves, and Traveling Ionosphere Disturbances. IWS online service (http://popdat.cbk.waw.pl) offers end users to query optional set of predefined wave phenomena, their detailed characteristics. These were collected by target specific event detection algorithms in selected satellite records during database buildup phase. Result of performed wave processing thus represents useful information on statistical or comparative investigations of wave types, listed in a detailed catalog of ionospheric wave phenomena. The IWS provides wave event characteristics, extracted by specific software systems from data records of the selected satellite missions. The end-user can access targets by making specific searches and use statistical modules within the service in their field of interest. Therefore the IWS opens a new way in ionosphere and Space Weather research. The scientific applications covered by IWS concern beyond Space Weather also other fields like earthquake precursors, ionosphere climatology, geomagnetic storms, troposphere-ionosphere energy transfer, and trans-ionosphere link perturbations.

  14. Ionosphere Waves Service (IWS – a problem-oriented tool in ionosphere and Space Weather research produced by POPDAT project

    Directory of Open Access Journals (Sweden)

    Ferencz Csaba

    2014-05-01

    Full Text Available In the frame of the FP7 POPDAT project the Ionosphere Waves Service (IWS has been developed and opened for public access by ionosphere experts. IWS is forming a database, derived from archived ionospheric wave records to assist the ionosphere and Space Weather research, and to answer the following questions: How can the data of earlier ionospheric missions be reprocessed with current algorithms to gain more profitable results? How could the scientific community be provided with a new insight on wave processes that take place in the ionosphere? The answer is a specific and unique data mining service accessing a collection of topical catalogs that characterize a huge number of recorded occurrences of Whistler-like Electromagnetic Wave Phenomena, Atmosphere Gravity Waves, and Traveling Ionosphere Disturbances. IWS online service (http://popdat.cbk.waw.pl offers end users to query optional set of predefined wave phenomena, their detailed characteristics. These were collected by target specific event detection algorithms in selected satellite records during database buildup phase. Result of performed wave processing thus represents useful information on statistical or comparative investigations of wave types, listed in a detailed catalog of ionospheric wave phenomena. The IWS provides wave event characteristics, extracted by specific software systems from data records of the selected satellite missions. The end-user can access targets by making specific searches and use statistical modules within the service in their field of interest. Therefore the IWS opens a new way in ionosphere and Space Weather research. The scientific applications covered by IWS concern beyond Space Weather also other fields like earthquake precursors, ionosphere climatology, geomagnetic storms, troposphere-ionosphere energy transfer, and trans-ionosphere link perturbations.

  15. 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.

  16. 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

  17. 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

  18. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-10-01

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

  20. 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.

  1. 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...

  2. 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

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. Highlights of Space Weather Services/Capabilities at NASA/GSFC Space Weather Center

    Science.gov (United States)

    Fok, Mei-Ching; Zheng, Yihua; Hesse, Michael; Kuznetsova, Maria; Pulkkinen, Antti; Taktakishvili, Aleksandre; Mays, Leila; Chulaki, Anna; Lee, Hyesook

    2012-01-01

    The importance of space weather has been recognized world-wide. Our society depends increasingly on technological infrastructure, including the power grid as well as satellites used for communication and navigation. Such technologies, however, are vulnerable to space weather effects caused by the Sun's variability. NASA GSFC's Space Weather Center (SWC) (http://science.gsfc.nasa.gov//674/swx services/swx services.html) has developed space weather products/capabilities/services that not only respond to NASA's needs but also address broader interests by leveraging the latest scientific research results and state-of-the-art models hosted at the Community Coordinated Modeling Center (CCMC: http://ccmc.gsfc.nasa.gov). By combining forefront space weather science and models, employing an innovative and configurable dissemination system (iSWA.gsfc.nasa.gov), taking advantage of scientific expertise both in-house and from the broader community as well as fostering and actively participating in multilateral collaborations both nationally and internationally, NASA/GSFC space weather Center, as a sibling organization to CCMC, is poised to address NASA's space weather needs (and needs of various partners) and to help enhancing space weather forecasting capabilities collaboratively. With a large number of state-of-the-art physics-based models running in real-time covering the whole space weather domain, it offers predictive capabilities and a comprehensive view of space weather events throughout the solar system. In this paper, we will provide some highlights of our service products/capabilities. In particular, we will take the 23 January and the 27 January space weather events as examples to illustrate how we can use the iSWA system to track them in the interplanetary space and forecast their impacts.

  11. 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.

  12. Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program.

    Science.gov (United States)

    Droegemeier, K. K.; Smith, J. D.; Businger, S.; Doswell, C., III; Doyle, J.; Duffy, C.; Foufoula-Georgiou, E.; Graziano, T.; James, L. D.; Krajewski, V.; Lemone, M.; Lettenmaier, D.; Mass, C.; Pielke, R., Sr.; Ray, P.; Rutledge, S.; Schaake, J.; Zipser, E.

    2000-11-01

    Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists-in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems-to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research

  13. Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program

    Science.gov (United States)

    Droegemeier, K.K.; Smith, J.D.; Businger, S.; Doswell, C.; Doyle, J.; Duffy, C.; Foufoula-Georgiou, E.; Graziano, T.; James, L.D.; Krajewski, V.; LeMone, M.; Lettenmaier, D.; Mass, C.; Pielke, R.; Ray, P.; Rutledge, S.; Schaake, J.; Zipser, E.

    2000-01-01

    Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists - in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems - to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research

  14. Space weather monitoring by ground-based means carried out in Polar Geophysical Center at Arctic and Antarctic Research Institute

    Science.gov (United States)

    Janzhura, Alexander

    A real-time information on geophysical processes in polar regions is very important for goals of Space Weather monitoring by the ground-based means. The modern communication systems and computer technology makes it possible to collect and process the data from remote sites without significant delays. A new acquisition equipment based on microprocessor modules and reliable in hush climatic conditions was deployed at the Roshydromet networks of geophysical observations in Arctic and is deployed at observatories in Antarctic. A contemporary system for on-line collecting and transmitting the geophysical data from the Arctic and Antarctic stations to AARI has been realized and the Polar Geophysical Center (PGC) arranged at AARI ensures the near-real time processing and analyzing the geophysical information from 11 stations in Arctic and 5 stations in Antarctic. The space weather monitoring by the ground based means is one of the main tasks standing before the Polar Geophysical Center. As studies by Troshichev and Janzhura, [2012] showed, the PC index characterizing the polar cap magnetic activity appeared to be an adequate indicator of the solar wind energy that entered into the magnetosphere and the energy that is accumulating in the magnetosphere. A great advantage of the PC index application over other methods based on satellite data is a permanent on-line availability of information about magnetic activity in both northern and southern polar caps. A special procedure agreed between Arctic and Antarctic Research Institute (AARI) and Space Institute of the Danish Technical University (DTUSpace) ensures calculation of the unified PC index in quasi-real time by magnetic data from the Thule and Vostok stations (see public site: http://pc-index.org). The method for estimation of AL and Dst indices (as indicators of state of the disturbed magnetosphere) based on data on foregoing PC indices has been elaborated and testified in the Polar Geophysical Center. It is

  15. Overview of Space Weather Impacts and NASA Space Weather Center Services and Products

    Science.gov (United States)

    Zheng, Y.

    2012-01-01

    The presentation is divided into two major components. First, I will give an overview of space weather phenomenon and their associated impacts. Then I will describe the comprehensive list of products and tools that NASA Space Weather Center has developed by leveraging more than a decade long modeling experience enabled by the Community Coordinated Modeling Center (CCMC) and latest scientific research results from the broad science community. In addition, a summary of the space weather activities we have been engaged in and our operational experience will be provided.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Research on Trends in Extreme Weather Events and their Effects on Grapevine in Romanian Viticulture

    Directory of Open Access Journals (Sweden)

    Georgeta Mihaela Bucur

    2016-11-01

    Full Text Available The aim of this work was to investigate the frequency and intensity of extreme weather events in various centers from Romania’s viticultural regions: winter frost, extreme temperatures during the growing season and summer droughts. Winter frost damaging the vine is a significant risk to grape production, mainly in the plains and lowlands to the foothills. The frequency of winter frost damaging the vine has increased during the last decades, in the context of climate change. Also, there has been found a significant increase in the number of hot days (Tmax > 30°C and very hot days (Tmax > 35°C. The evolution of these extreme events was followed in Craiova, Constanta, Bucharest, Timisoara, Cluj-Napoca, Oradea and Iasi, between 1977 and 2015. The long term study (18 years conducted in the experimental plantation of the University of Agronomic Sciences and Veterinary Medicine Bucharest revealed their influence on vine. During the last two decades, there has been registered a trend of increasing the frequency and intensity of winter frost, damaging vine (Tmin 30°C and > 35°C and droughts that adversely affect viticulture, production and quality of grapes and wine. The highest warming trends were observed for northern viticultural regions (Transylvania and Moldavia and for the seaside. Although the intensification of heat waves increases sugar accumulation in the berries, they trigger a significant reduction in grape production and in titrable acidity, requiring corrections and resulting in unbalanced wines. Meanwhile, droughts trigger production decrease. To avoid negative effects on vine, it is necessary to take measures, both on a short, medium and long term.

  5. 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.

  6. 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...

  7. 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

  8. 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

  9. 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.

  10. Operational Space Weather in USAF Education

    Science.gov (United States)

    Smithtro, C.; Quigley, S.

    2006-12-01

    Most education programs offering space weather courses are understandably and traditionally heavily weighted with theoretical space physics that is the basis for most of what is researched and modeled. While understanding the theory is a good and necessary grounding for anyone working the field of space weather, few military or commercial jobs employ such theory in real-time operations. The operations sites/centers are much more geared toward use of applied theory-resultant models, tools and products. To ensure its operations centers personnel, commanders, real-time system operators and other customers affected by the space environment are educated on available and soon-to-be operational space weather models and products, the USAF has developed applicable course/lecture material taught at various institutions to include the Air Force Institute of Technology (AFIT) and the Joint Weather Training Complex (335th/TRS/OUA). Less frequent training of operational space weather is available via other venues that will be discussed, and associated course material is also being developed for potential use at the National Security Space Institute (NSSI). This presentation provides an overview of the programs, locations, courses and material developed and/or taught by or for USAF personnel dealing with operational space weather. It also provides general information on student research project results that may be used in operational support, along with observations regarding logistical and professional benefits of teaching such non-theoretical/non-traditional material.

  11. 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.

  12. 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.

  13. Postprocessing of simulated precipitation for impact research in West Africa. Part II: A weather generator for daily data

    Science.gov (United States)

    Paeth, Heiko; Diederich, Malte

    2011-04-01

    Data from global and regional climate models refer to grid cells and, hence, are basically different from station data. This particularly holds for variables with enhanced spatio-temporal variability like precipitation. On the other hand, many applications like for instance hydrological models require atmospheric data with the statistical characteristics of station data. Here, we present a dynamical-statistical tool to construct virtual station data based on regional climate model output for tropical West Africa. This weather generator (WEGE) incorporates daily gridded rainfall from the model, an orographic term and a stochastic term, accounting for the chaotic spatial distribution of local rain events within a model grid box. In addition, the simulated probability density function of daily precipitation is adjusted to available station data in Benin. It is also assured that the generated data are still consistent with other model parameters like cloudiness and atmospheric circulation. The resulting virtual station data are in excellent agreement with various observed characteristics which are not explicitly addressed by the WEGE algorithm. This holds for the mean daily rainfall intensity and variability, the relative number of rainless days and the scaling of precipitation in time. The data set has already been used successfully for various climate impact studies in Benin.

  14. 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.

  15. 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

  16. Weather and emotional state

    Science.gov (United States)

    Spasova, Z.

    2010-09-01

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

  17. An Automated Weather Research and Forecasting (WRF)-Based Nowcasting System: Software Description

    Science.gov (United States)

    2013-10-01

    native features of HTML. WRFEE is based on the model-view-controller ( MVC ) paradigm whereby the model controls program flow (see figure 1), the view is...modifications are outlined later in this report. 3 3. Background WRFEE is based on the MVC paradigm whereby the model handles data and the business logic...Wrfendtoend Java Bean The WRFEE bean represents the “model” portion of the MVC system, as it steps through each of the requisite processes

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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

  3. 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).

  4. 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

  5. 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

  6. Research Spotlight: Improved model reproduces the 2003 European heat wave

    Science.gov (United States)

    Schultz, Colin

    2011-04-01

    In August 2003, record-breaking temperatures raged across much of Europe. In France, maximum temperatures of 37°C (99°F) persisted for 9 days straight, the longest such stretch since 1873. About 40,000 deaths (14,000 in France alone) were attributed to the extreme heat and low humidity. Various climate conditions must come into alignment to produce extreme weather like the 2003 heat wave, and despite a concerted effort, forecasting models have so far been unable to accurately reproduce the event—including the modern European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble modeling system for seasonal forecasts, which went into operation in 2007. (Geophysical Research Letters, doi:10.1029/2010GL046455, 2011)

  7. 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.

  8. 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.

  9. 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…

  10. 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…

  11. 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

  12. 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

  13. 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.

  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. 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.

  16. 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

    In 2011 the Swiss national consortium C2SM providednew climate change scenarios were released in Switzerland that came with a comprehensive data set of temperature and precipitation changes under climate change conditions for every a large network of meteorological stations, and for aggregated as well as regions in across Switzerland. These climate change signals were generated for three emission scenarios and three different future time-periods and designed to be used asbased on a delta change factors approach. This data set proved to be very successful in Switzerland as many different users, researchers, private companies, and societal users were able to use and interpret the climate data set. Thus, a range of applications that are all based on the same climate data set enabled a comparable view on climate change impact in several disciplines. The main limitation and criticism to this data set was the usage of the delta change approach for downscaling as it comes with severe limitations such as underestimatinges changes in extreme values and neglecting changes in variability and changes in temporal sequencesneglecting changes in variability, be it year-to-year or day-to-day, and changes in temporal sequences . lacks a change in the day-to-day-variability. One way to overcome this the latter limitation is the usage of stochastic weather generators in a downscaling context. Weather generators are known to be one suitable downscaling technique, but A common limitation of most weather generators is the absence of spatial consistency rrelation in the generated daily time-series, resulting in an underestimation of areal means over several stations that are often low-biased. refer to one point scale (single-site) and lacks the spatial representation of weather. The latter A realistic representation of the inter-station correlation in the downscaled time-series This is of high particular importance in some impact studies, especially infor any hydrological impact studiesy

  17. 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

  18. 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.

  19. 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.

  20. Seafloor Weathering As a Long-Term Climate Regulation Mechanism

    Scie