WorldWideScience

Sample records for severe storm forecasting

  1. Geomagnetic storm forecasting service StormFocus: 5 years online

    Science.gov (United States)

    Podladchikova, Tatiana; Petrukovich, Anatoly; Yermolaev, Yuri

    2018-04-01

    Forecasting geomagnetic storms is highly important for many space weather applications. In this study, we review performance of the geomagnetic storm forecasting service StormFocus during 2011-2016. The service was implemented in 2011 at SpaceWeather.Ru and predicts the expected strength of geomagnetic storms as measured by Dst index several hours ahead. The forecast is based on L1 solar wind and IMF measurements and is updated every hour. The solar maximum of cycle 24 is weak, so most of the statistics are on rather moderate storms. We verify quality of selection criteria, as well as reliability of real-time input data in comparison with the final values, available in archives. In real-time operation 87% of storms were correctly predicted while the reanalysis running on final OMNI data predicts successfully 97% of storms. Thus the main reasons for prediction errors are discrepancies between real-time and final data (Dst, solar wind and IMF) due to processing errors, specifics of datasets.

  2. Forecasting severe ice storms using numerical weather prediction: the March 2010 Newfoundland event

    OpenAIRE

    J. Hosek; P. Musilek; E. Lozowski; P. Pytlak

    2011-01-01

    The northeast coast of North America is frequently hit by severe ice storms. These freezing rain events can produce large ice accretions that damage structures, frequently power transmission and distribution infrastructure. For this reason, it is highly desirable to model and forecast such icing events, so that the consequent damages can be prevented or mitigated. The case study presented in this paper focuses on the March 2010 ice storm event that took place in eastern Newfoundland. We apply...

  3. Forecasting severe ice storms using numerical weather prediction: the March 2010 Newfoundland event

    Directory of Open Access Journals (Sweden)

    J. Hosek

    2011-02-01

    Full Text Available The northeast coast of North America is frequently hit by severe ice storms. These freezing rain events can produce large ice accretions that damage structures, frequently power transmission and distribution infrastructure. For this reason, it is highly desirable to model and forecast such icing events, so that the consequent damages can be prevented or mitigated. The case study presented in this paper focuses on the March 2010 ice storm event that took place in eastern Newfoundland. We apply a combination of a numerical weather prediction model and an ice accretion algorithm to simulate a forecast of this event.

    The main goals of this study are to compare the simulated meteorological variables to observations, and to assess the ability of the model to accurately predict the ice accretion load for different forecast horizons. The duration and timing of the freezing rain event that occurred between the night of 4 March and the morning of 6 March was simulated well in all model runs. The total precipitation amounts in the model, however, differed by up to a factor of two from the observations. The accuracy of the model air temperature strongly depended on the forecast horizon, but it was acceptable for all simulation runs. The simulated accretion loads were also compared to the design values for power delivery structures in the region. The results indicated that the simulated values exceeded design criteria in the areas of reported damage and power outages.

  4. Using forecast information for storm ride-through control

    DEFF Research Database (Denmark)

    Barahona Garzón, Braulio; Trombe, Pierre-Julien; Vincent, Claire Louise

    2013-01-01

    Using probabilistic forecast information in control algorithms can improve the performance of wind farms during periods of extreme winds. This work presents a wind farm supervisor control concept that uses probabilistic forecast information to ride-through a storm with softer ramps of power. Wind...... speed forecasts are generated with a statistical approach (i.e. time series models). The supervisor control is based on a set of logical rules that consider point forecasts and predictive densities to ramp-down the power of the wind farm before the storm hits. The potential of this supervisor control...

  5. Hindicast and forecast of the Parsifal storm

    Energy Technology Data Exchange (ETDEWEB)

    Bertotti, L.; Cavaleri, L. [Istituto Studio Dinamica Grandi Masse, Venice (Italy); De girolamo, P.; Magnaldi, S. [Rome, Univ. `La Sapienza` (Italy). Dip. di Idraulica, Trasporti e Strade; Franco, L. [Rome, III Univ. (Italy). Dip. di Scienze dell`Ingegneria Civile

    1998-05-01

    On 2 November 1995 a Mistral storm in the Gulf of Lions sank the 16 metre yacht Parsifal claiming six lives out of the nine member crew. The authors analyse the storm with different meteorological and wave models, verifying the results against the available buoy and satellite measurements. Then the authors consider the accuracy of the storm forecasts and the information available the days before the accident. The limitations related to the resolution of the meteorological models are explored by hind casting the storm also with the winds produced by some limited area models. Finally, the authors discuss the present situation of wind and wave hind cast and forecast in the Mediterranean Sea, and the distribution of these results to the public.

  6. Revisiting the synoptic-scale predictability of severe European winter storms using ECMWF ensemble reforecasts

    Directory of Open Access Journals (Sweden)

    F. Pantillon

    2017-10-01

    Full Text Available New insights into the synoptic-scale predictability of 25 severe European winter storms of the 1995–2015 period are obtained using the homogeneous ensemble reforecast dataset from the European Centre for Medium-Range Weather Forecasts. The predictability of the storms is assessed with different metrics including (a the track and intensity to investigate the storms' dynamics and (b the Storm Severity Index to estimate the impact of the associated wind gusts. The storms are well predicted by the whole ensemble up to 2–4 days ahead. At longer lead times, the number of members predicting the observed storms decreases and the ensemble average is not clearly defined for the track and intensity. The Extreme Forecast Index and Shift of Tails are therefore computed from the deviation of the ensemble from the model climate. Based on these indices, the model has some skill in forecasting the area covered by extreme wind gusts up to 10 days, which indicates a clear potential for early warnings. However, large variability is found between the individual storms. The poor predictability of outliers appears related to their physical characteristics such as explosive intensification or small size. Longer datasets with more cases would be needed to further substantiate these points.

  7. Two-Step Forecast of Geomagnetic Storm Using Coronal Mass Ejection and Solar Wind Condition

    Science.gov (United States)

    Kim, R.-S.; Moon, Y.-J.; Gopalswamy, N.; Park, Y.-D.; Kim, Y.-H.

    2014-01-01

    To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind criteria derived in this study (Bz = -5 nT or Ey = 3 mV/m for t = 2 h for moderate storms with minimum Dst less than -50 nT) (i.e. Magnetic Field Magnitude, B (sub z) less than or equal to -5 nanoTeslas or duskward Electrical Field, E (sub y) greater than or equal to 3 millivolts per meter for time greater than or equal to 2 hours for moderate storms with Minimum Disturbance Storm Time, Dst less than -50 nanoTeslas) and a Dst model developed by Temerin and Li (2002, 2006) (TL [i.e. Temerin Li] model). Using 55 CME-Dst pairs during 1997 to 2003, our solar wind criteria produce slightly better forecasts for 31 storm events (90 percent) than the forecasts based on the TL model (87 percent). However, the latter produces better forecasts for 24 nonstorm events (88 percent), while the former correctly forecasts only 71 percent of them. We then performed the two-step forecast. The results are as follows: (i) for 15 events that are incorrectly forecasted using CME parameters, 12 cases (80 percent) can be properly predicted based on solar wind conditions; (ii) if we forecast a storm when both CME and solar wind conditions are satisfied (n, i.e. cap operator - the intersection set that is comprised of all the elements that are common to both), the critical success index becomes higher than that from the forecast using CME parameters alone, however, only 25 storm events (81 percent) are correctly forecasted; and (iii) if we forecast a storm when either set of these conditions is satisfied (?, i.e. cup operator - the union set that is comprised of all the elements of either or both

  8. Coastal emergency managers' preferences for storm surge forecast communication.

    Science.gov (United States)

    Morrow, Betty Hearn; Lazo, Jeffrey K

    2014-01-01

    Storm surge, the most deadly hazard associated with tropical and extratropical cyclones, is the basis for most evacuation decisions by authorities. One factor believed to be associated with evacuation noncompliance is a lack of understanding of storm surge. To address this problem, federal agencies responsible for cyclone forecasts are seeking more effective ways of communicating storm surge threat. To inform this process, they are engaging various partners in the forecast and warning process.This project focuses on emergency managers. Fifty-three emergency managers (EMs) from the Gulf and lower Atlantic coasts were surveyed to elicit their experience with, sources of, and preferences for storm surge information. The emergency managers-who are well seasoned in hurricane response and generally rate the surge risk in their coastal areas above average or extremely high-listed storm surge as their major concern with respect to hurricanes. They reported a general lack of public awareness about surge. Overall they support new ways to convey the potential danger to the public, including the issuance of separate storm surge watches and warnings, and the expression of surge heights using feet above ground level. These EMs would like more maps, graphics, and visual materials for use in communicating with the public. An important concern is the timing of surge forecasts-whether they receive them early enough to be useful in their evacuation decisions.

  9. Data Assimilation within the Advanced Circulation (ADCIRC) Modeling Framework for Hurricane Storm Surge Forecasting

    KAUST Repository

    Butler, T.

    2012-07-01

    Accurate, real-time forecasting of coastal inundation due to hurricanes and tropical storms is a challenging computational problem requiring high-fidelity forward models of currents and water levels driven by hurricane-force winds. Despite best efforts in computational modeling there will always be uncertainty in storm surge forecasts. In recent years, there has been significant instrumentation located along the coastal United States for the purpose of collecting data—specifically wind, water levels, and wave heights—during these extreme events. This type of data, if available in real time, could be used in a data assimilation framework to improve hurricane storm surge forecasts. In this paper a data assimilation methodology for storm surge forecasting based on the use of ensemble Kalman filters and the advanced circulation (ADCIRC) storm surge model is described. The singular evolutive interpolated Kalman (SEIK) filter has been shown to be effective at producing accurate results for ocean models using small ensemble sizes initialized by an empirical orthogonal function analysis. The SEIK filter is applied to the ADCIRC model to improve storm surge forecasting, particularly in capturing maximum water levels (high water marks) and the timing of the surge. Two test cases of data obtained from hindcast studies of Hurricanes Ike and Katrina are presented. It is shown that a modified SEIK filter with an inflation factor improves the accuracy of coarse-resolution forecasts of storm surge resulting from hurricanes. Furthermore, the SEIK filter requires only modest computational resources to obtain more accurate forecasts of storm surge in a constrained time window where forecasters must interact with emergency responders.

  10. Trajectory Calculation as Forecasting Support Tool for Dust Storms

    Directory of Open Access Journals (Sweden)

    Sultan Al-Yahyai

    2014-01-01

    Full Text Available In arid and semiarid regions, dust storms are common during windy seasons. Strong wind can blow loose sand from the dry surface. The rising sand and dust is then transported to other places depending on the wind conditions (speed and direction at different levels of the atmosphere. Considering dust as a moving object in space and time, trajectory calculation then can be used to determine the path it will follow. Trajectory calculation is used as a forecast supporting tool for both operational and research activities. Predefined dust sources can be identified and the trajectories can be precalculated from the Numerical Weather Prediction (NWP forecast. In case of long distance transported dust, the tool should allow the operational forecaster to perform online trajectory calculation. This paper presents a case study for using trajectory calculation based on NWP models as a forecast supporting tool in Oman Meteorological Service during some dust storm events. Case study validation results showed a good agreement between the calculated trajectories and the real transport path of the dust storms and hence trajectory calculation can be used at operational centers for warning purposes.

  11. Operational aerosol and dust storm forecasting

    International Nuclear Information System (INIS)

    Westphal, D L; Curtis, C A; Liu, M; Walker, A L

    2009-01-01

    The U. S. Navy now conducts operational forecasting of aerosols and dust storms on global and regional scales. The Navy Aerosol Analysis and Prediction System (NAAPS) is run four times per day and produces 6-day forecasts of sulfate, smoke, dust and sea salt aerosol concentrations and visibility for the entire globe. The Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS (registered) ) is run twice daily for Southwest Asia and produces 3-day forecasts of dust, smoke, and visibility. The graphical output from these models is available on the Internet (www.nrlmry.navy.mil/aerosol/). The aerosol optical properties are calculated for each specie for each forecast output time and used for sea surface temperature (SST) retrieval corrections, regional electro-optical (EO) propagation assessments, and the development of satellite algorithms. NAAPS daily aerosol optical depth (AOD) values are compared with the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) AOD values. Visibility forecasts are compared quantitatively with surface synoptic reports.

  12. A dynamic system to forecast ionospheric storm disturbances based on solar wind conditions

    Directory of Open Access Journals (Sweden)

    L. R. Cander

    2005-06-01

    Full Text Available For the reliable performance of technologically advanced radio communications systems under geomagnetically disturbed conditions, the forecast and modelling of the ionospheric response during storms is a high priority. The ionospheric storm forecasting models that are currently in operation have shown a high degree of reliability during quiet conditions, but they have proved inadequate during storm events. To improve their prediction accuracy, we have to take advantage of the deeper understanding in ionospheric storm dynamics that is currently available, indicating a correlation between the Interplanetary Magnetic Field (IMF disturbances and the qualitative signature of ionospheric storm disturbances at middle latitude stations. In this paper we analyse observations of the foF2 critical frequency parameter from one mid-latitude European ionospheric station (Chilton in conjunction with observations of IMF parameters (total magnitude, Bt and Bz-IMF component from the ACE spacecraft mission for eight storm events. The determination of the time delay in the ionospheric response to the interplanetary medium disturbances leads to significant results concerning the forecast of the ionospheric storms onset and their development during the first 24 h. In this way the real-time ACE observations of the solar wind parameters may be used in the development of a real-time dynamic ionospheric storm model with adequate accuracy.

  13. Factors controlling storm impacts on coastal barriers and beaches - A preliminary basis for near real-time forecasting

    Science.gov (United States)

    Morton, R.A.

    2002-01-01

    Analysis of ground conditions and meteorological and oceanographic parameters for some of the most severe Atlantic and Gulf Coast storms in the U.S. reveals the primary factors affecting morphological storm responses of beaches and barrier islands. The principal controlling factors are storm characteristics, geographic position relative to storm path, timing of storm events, duration of wave exposure, wind stress, degree of flow confinement, antecedent topography and geologic framework, sediment textures, vegetative cover, and type and density of coastal development. A classification of commonly observed storm responses demonstrates the sequential interrelations among (1) land elevations, (2) water elevations in the ocean and adjacent lagoon (if present), and (3) stages of rising water during the storm. The predictable coastal responses, in relative order from high frequency beach erosion to low frequency barrier inundation, include: beach erosion, berm migration, dune erosion, washover terrace construction, perched fan deposition, sheetwash, washover channel incision, washout formation, and forced and unforced ebb flow. Near real-time forecasting of expected storm impacts is possible if the following information is available for the coast: a detailed morphological and topographic characterization, accurate storm-surge and wave-runup models, the real-time reporting of storm parameters, accurate forecasts of the storm position relative to a particular coastal segment, and a conceptual model of geological processes that encompasses observed morphological changes caused by extreme storms.

  14. Verification of an ensemble prediction system for storm surge forecast in the Adriatic Sea

    Science.gov (United States)

    Mel, Riccardo; Lionello, Piero

    2014-12-01

    In the Adriatic Sea, storm surges present a significant threat to Venice and to the flat coastal areas of the northern coast of the basin. Sea level forecast is of paramount importance for the management of daily activities and for operating the movable barriers that are presently being built for the protection of the city. In this paper, an EPS (ensemble prediction system) for operational forecasting of storm surge in the northern Adriatic Sea is presented and applied to a 3-month-long period (October-December 2010). The sea level EPS is based on the HYPSE (hydrostatic Padua Sea elevation) model, which is a standard single-layer nonlinear shallow water model, whose forcings (mean sea level pressure and surface wind fields) are provided by the ensemble members of the ECMWF (European Center for Medium-Range Weather Forecasts) EPS. Results are verified against observations at five tide gauges located along the Croatian and Italian coasts of the Adriatic Sea. Forecast uncertainty increases with the predicted value of the storm surge and with the forecast lead time. The EMF (ensemble mean forecast) provided by the EPS has a rms (root mean square) error lower than the DF (deterministic forecast), especially for short (up to 3 days) lead times. Uncertainty for short lead times of the forecast and for small storm surges is mainly caused by uncertainty of the initial condition of the hydrodynamical model. Uncertainty for large lead times and large storm surges is mainly caused by uncertainty in the meteorological forcings. The EPS spread increases with the rms error of the forecast. For large lead times the EPS spread and the forecast error substantially coincide. However, the EPS spread in this study, which does not account for uncertainty in the initial condition, underestimates the error during the early part of the forecast and for small storm surge values. On the contrary, it overestimates the rms error for large surge values. The PF (probability forecast) of the EPS

  15. Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities

    Science.gov (United States)

    Schemm, J. E.; Long, L.; Baxter, S.

    2013-12-01

    Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities Jae-Kyung E. Schemm, Lindsey Long and Stephen Baxter Climate Prediction Center, NCEP/NWS/NOAA Predictability of intraseasonal tropical storm (TS) activities is assessed using the 1999-2010 CFSv2 hindcast suite. Weekly TS activities in the CFSv2 45-day forecasts were determined using the TS detection and tracking method devised by Carmago and Zebiak (2002). The forecast periods are divided into weekly intervals for Week 1 through Week 6, and also the 30-day mean. The TS activities in those intervals are compared to the observed activities based on the NHC HURDAT and JTWC Best Track datasets. The CFSv2 45-day hindcast suite is made of forecast runs initialized at 00, 06, 12 and 18Z every day during the 1999 - 2010 period. For predictability evaluation, forecast TS activities are analyzed based on 20-member ensemble forecasts comprised of 45-day runs made during the most recent 5 days prior to the verification period. The forecast TS activities are evaluated in terms of the number of storms, genesis locations and storm tracks during the weekly periods. The CFSv2 forecasts are shown to have a fair level of skill in predicting the number of storms over the Atlantic Basin with the temporal correlation scores ranging from 0.73 for Week 1 forecasts to 0.63 for Week 6, and the average RMS errors ranging from 0.86 to 1.07 during the 1999-2010 hurricane season. Also, the forecast track density distribution and false alarm statistics are compiled using the hindcast analyses. In real-time applications of the intraseasonal TS activity forecasts, the climatological TS forecast statistics will be used to make the model bias corrections in terms of the storm counts, track distribution and removal of false alarms. An operational implementation of the weekly TS activity prediction is planned for early 2014 to provide an objective input for the CPC's Global Tropical Hazards

  16. Hybrid vs Adaptive Ensemble Kalman Filtering for Storm Surge Forecasting

    Science.gov (United States)

    Altaf, M. U.; Raboudi, N.; Gharamti, M. E.; Dawson, C.; McCabe, M. F.; Hoteit, I.

    2014-12-01

    Recent storm surge events due to Hurricanes in the Gulf of Mexico have motivated the efforts to accurately forecast water levels. Toward this goal, a parallel architecture has been implemented based on a high resolution storm surge model, ADCIRC. However the accuracy of the model notably depends on the quality and the recentness of the input data (mainly winds and bathymetry), model parameters (e.g. wind and bottom drag coefficients), and the resolution of the model grid. Given all these uncertainties in the system, the challenge is to build an efficient prediction system capable of providing accurate forecasts enough ahead of time for the authorities to evacuate the areas at risk. We have developed an ensemble-based data assimilation system to frequently assimilate available data into the ADCIRC model in order to improve the accuracy of the model. In this contribution we study and analyze the performances of different ensemble Kalman filter methodologies for efficient short-range storm surge forecasting, the aim being to produce the most accurate forecasts at the lowest possible computing time. Using Hurricane Ike meteorological data to force the ADCIRC model over a domain including the Gulf of Mexico coastline, we implement and compare the forecasts of the standard EnKF, the hybrid EnKF and an adaptive EnKF. The last two schemes have been introduced as efficient tools for enhancing the behavior of the EnKF when implemented with small ensembles by exploiting information from a static background covariance matrix. Covariance inflation and localization are implemented in all these filters. Our results suggest that both the hybrid and the adaptive approach provide significantly better forecasts than those resulting from the standard EnKF, even when implemented with much smaller ensembles.

  17. Improvement of Storm Forecasts Using Gridded Bayesian Linear Regression for Northeast United States

    Science.gov (United States)

    Yang, J.; Astitha, M.; Schwartz, C. S.

    2017-12-01

    Bayesian linear regression (BLR) is a post-processing technique in which regression coefficients are derived and used to correct raw forecasts based on pairs of observation-model values. This study presents the development and application of a gridded Bayesian linear regression (GBLR) as a new post-processing technique to improve numerical weather prediction (NWP) of rain and wind storm forecasts over northeast United States. Ten controlled variables produced from ten ensemble members of the National Center for Atmospheric Research (NCAR) real-time prediction system are used for a GBLR model. In the GBLR framework, leave-one-storm-out cross-validation is utilized to study the performances of the post-processing technique in a database composed of 92 storms. To estimate the regression coefficients of the GBLR, optimization procedures that minimize the systematic and random error of predicted atmospheric variables (wind speed, precipitation, etc.) are implemented for the modeled-observed pairs of training storms. The regression coefficients calculated for meteorological stations of the National Weather Service are interpolated back to the model domain. An analysis of forecast improvements based on error reductions during the storms will demonstrate the value of GBLR approach. This presentation will also illustrate how the variances are optimized for the training partition in GBLR and discuss the verification strategy for grid points where no observations are available. The new post-processing technique is successful in improving wind speed and precipitation storm forecasts using past event-based data and has the potential to be implemented in real-time.

  18. Understanding Variability in Beach Slope to Improve Forecasts of Storm-induced Water Levels

    Science.gov (United States)

    Doran, K. S.; Stockdon, H. F.; Long, J.

    2014-12-01

    The National Assessment of Hurricane-Induced Coastal Erosion Hazards combines measurements of beach morphology with storm hydrodynamics to produce forecasts of coastal change during storms for the Gulf of Mexico and Atlantic coastlines of the United States. Wave-induced water levels are estimated using modeled offshore wave height and period and measured beach slope (from dune toe to shoreline) through the empirical parameterization of Stockdon et al. (2006). Spatial and temporal variability in beach slope leads to corresponding variability in predicted wave setup and swash. Seasonal and storm-induced changes in beach slope can lead to differences on the order of a meter in wave runup elevation, making accurate specification of this parameter essential to skillful forecasts of coastal change. Spatial variation in beach slope is accounted for through alongshore averaging, but temporal variability in beach slope is not included in the final computation of the likelihood of coastal change. Additionally, input morphology may be years old and potentially very different than the conditions present during forecast storm. In order to improve our forecasts of hurricane-induced coastal erosion hazards, the temporal variability of beach slope must be included in the final uncertainty of modeled wave-induced water levels. Frequently collected field measurements of lidar-based beach morphology are examined for study sites in Duck, North Carolina, Treasure Island, Florida, Assateague Island, Virginia, and Dauphin Island, Alabama, with some records extending over a period of 15 years. Understanding the variability of slopes at these sites will help provide estimates of associated water level uncertainty which can then be applied to other areas where lidar observations are infrequent, and improve the overall skill of future forecasts of storm-induced coastal change. Stockdon, H. F., Holman, R. A., Howd, P. A., and Sallenger Jr, A. H. (2006). Empirical parameterization of setup

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

    Science.gov (United States)

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

    2018-01-01

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

  20. The Czech Hydrometeorological Institute's severe storm nowcasting system

    Science.gov (United States)

    Novak, Petr

    2007-02-01

    To satisfy requirements for operational severe weather monitoring and prediction, the Czech Hydrometeorological Institute (CHMI) has developed a severe storm nowcasting system which uses weather radar data as its primary data source. Previous CHMI studies identified two methods of radar echo prediction, which were then implemented during 2003 into the Czech weather radar network operational weather processor. The applications put into operations were the Continuity Tracking Radar Echoes by Correlation (COTREC) algorithm, and an application that predicts future radar fields using the wind field derived from the geopotential at 700 hPa calculated from a local numerical weather prediction model (ALADIN). To ensure timely delivery of the prediction products to the users, the forecasts are implemented into a web-based viewer (JSMeteoView) that has been developed by the CHMI Radar Department. At present, this viewer is used by all CHMI forecast offices for versatile visualization of radar and other meteorological data (Meteosat, lightning detection, NWP LAM output, SYNOP data) in the Internet/Intranet environment, and the viewer has detailed geographical navigation capabilities.

  1. Storm Prediction Center Forecast Products

    Science.gov (United States)

    select the go button to submit request Local forecast by "City, St" or "ZIP" City, St Archive NOAA Weather Radio Research Non-op. Products Forecast Tools Svr. Tstm. Events SPC Publications SPC services. Forecast Products Current Weather Watches This is the current graphic showing any severe

  2. A numerical storm surge forecast model with Kalman filter

    Institute of Scientific and Technical Information of China (English)

    Yu Fujiang; Zhang Zhanhai; Lin Yihua

    2001-01-01

    Kalman filter data assimilation technique is incorporated into a standard two-dimensional linear storm surge model. Imperfect model equation and imperfect meteorological forcimg are accounted for by adding noise terms to the momentum equations. The deterministic model output is corrected by using the available tidal gauge station data. The stationary Kalman filter algorithm for the model domain is calculated by an iterative procedure using specified information on the inaccuracies in the momentum equations and specified error information for the observations. An application to a real storm surge that occurred in the summer of 1956 in the East China Sea is performed by means of this data assimilation technique. The result shows that Kalman filter is useful for storm surge forecast and hindcast.

  3. Data Assimilation within the Advanced Circulation (ADCIRC) Modeling Framework for Hurricane Storm Surge Forecasting

    KAUST Repository

    Butler, T.; Altaf, Muhammad; Dawson, C.; Hoteit, Ibrahim; Luo, X.; Mayo, T.

    2012-01-01

    levels, and wave heights—during these extreme events. This type of data, if available in real time, could be used in a data assimilation framework to improve hurricane storm surge forecasts. In this paper a data assimilation methodology for storm surge

  4. AI techniques in geomagnetic storm forecasting

    Science.gov (United States)

    Lundstedt, Henrik

    This review deals with how geomagnetic storms can be predicted with the use of Artificial Intelligence (AI) techniques. Today many different Al techniques have been developed, such as symbolic systems (expert and fuzzy systems) and connectionism systems (neural networks). Even integrations of AI techniques exist, so called Intelligent Hybrid Systems (IHS). These systems are capable of learning the mathematical functions underlying the operation of non-linear dynamic systems and also to explain the knowledge they have learned. Very few such powerful systems exist at present. Two such examples are the Magnetospheric Specification Forecast Model of Rice University and the Lund Space Weather Model of Lund University. Various attempts to predict geomagnetic storms on long to short-term are reviewed in this article. Predictions of a month to days ahead most often use solar data as input. The first SOHO data are now available. Due to the high temporal and spatial resolution new solar physics have been revealed. These SOHO data might lead to a breakthrough in these predictions. Predictions hours ahead and shorter rely on real-time solar wind data. WIND gives us real-time data for only part of the day. However, with the launch of the ACE spacecraft in 1997, real-time data during 24 hours will be available. That might lead to the second breakthrough for predictions of geomagnetic storms.

  5. Extreme Wind, Rain, Storm Surge, and Flooding: Why Hurricane Impacts are Difficult to Forecast?

    Science.gov (United States)

    Chen, S. S.

    2017-12-01

    The 2017 hurricane season is estimated as one of the costliest in the U.S. history. The damage and devastation caused by Hurricane Harvey in Houston, Irma in Florida, and Maria in Puerto Rico are distinctly different in nature. The complexity of hurricane impacts from extreme wind, rain, storm surge, and flooding presents a major challenge in hurricane forecasting. A detailed comparison of the storm impacts from Harvey, Irma, and Maria will be presented using observations and state-of-the-art new generation coupled atmosphere-wave-ocean hurricane forecast model. The author will also provide an overview on what we can expect in terms of advancement in science and technology that can help improve hurricane impact forecast in the near future.

  6. Predicting Typhoon Induced Storm Surges Using the Operational Ocean Forecast System

    Directory of Open Access Journals (Sweden)

    Sung Hyup You

    2010-01-01

    Full Text Available This study was performed to compare storm surges simulated by the operational storm surges/tide forecast system (STORM : Storm surges/Tide Operational Model of the Korea Meteorological Administration (KMA with observations from 30 coastal tidal stations during nine typhoons that occurred between 2005 and 2007. The results (bias showed that for cases of overestimation (or underestimation, storm surges tended to be overestimated (as well as underestimated at all coastal stations. The maximum positive bias was approximately 6.92 cm for Typhoon Ewiniar (2006, while the maximum negative bias was approximately -12.06 cm for Typhoon Khanun (2005. The maximum and minimum root mean square errors (RMSEs were 14.61 and 6.78 cm, which occurred for Typhoons Khanun (2005 and Usagi (2007, respectively. For all nine typhoons, total averaged RMSE was approximately 10.2 cm. Large differences between modeled and observed storm surges occurred in two cases. In the first, a very weak typhoon, such as Typhoon Khanun (2005, caused low storm surges. In the other, exemplified by Typhoon Nari (2007, there were errors in the predicted typhoon strength used as input data for the storm surge model.

  7. Assimilation of ZDR Columns for Improving the Spin-Up and Forecasts of Convective Storms

    Science.gov (United States)

    Carlin, J.; Gao, J.; Snyder, J.; Ryzhkov, A.

    2017-12-01

    A primary motivation for assimilating radar reflectivity data is the reduction of spin-up time for modeled convection. To accomplish this, cloud analysis techniques seek to induce and sustain convective updrafts in storm-scale models by inserting temperature and moisture increments and hydrometeor mixing ratios into the model analysis from simple relations with reflectivity. Polarimetric radar data provide additional insight into the microphysical and dynamic structure of convection. In particular, the radar meteorology community has known for decades that convective updrafts cause, and are typically co-located with, differential reflectivity (ZDR) columns - vertical protrusions of enhanced ZDR above the environmental 0˚C level. Despite these benefits, limited work has been done thus far to assimilate dual-polarization radar data into numerical weather prediction models. In this study, we explore the utility of assimilating ZDR columns to improve storm-scale model analyses and forecasts of convection. We modify the existing Advanced Regional Prediction System's (ARPS) cloud analysis routine to adjust model temperature and moisture state variables using detected ZDR columns as proxies for convective updrafts, and compare the resultant cycled analyses and forecasts with those from the original reflectivity-based cloud analysis formulation. Results indicate qualitative and quantitative improvements from assimilating ZDR columns, including more coherent analyzed updrafts, forecast updraft helicity swaths that better match radar-derived rotation tracks, more realistic forecast reflectivity fields, and larger equitable threat scores. These findings support the use of dual-polarization radar signatures to improve storm-scale model analyses and forecasts.

  8. Use of the European Severe Weather Database to verify satllite-based storm detection or nowcasting

    OpenAIRE

    Dotzek, Nikolai; Forster, Caroline

    2008-01-01

    Severe thunderstorms constitute a major weather hazard in Europe, with an estimated total damage of € 5-8 billion each year. Yet a pan-European database of severe weather reports in a homogeneous data format has become available only recently: the European Severe Weather Database (ESWD). We demonstrate the large potential of ESWD applications for storm detection and forecast or nowcasting/warning verification purposes. The study of five warm-season severe weather days in Europe from 2007 a...

  9. Improving Short-Range Ensemble Kalman Storm Surge Forecasting Using Robust Adaptive Inflation

    KAUST Repository

    Altaf, Muhammad

    2013-08-01

    This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H∞ filter. By design, an H∞ filter is more robust than the common Kalman filter in the sense that the estimation error in the H∞ filter has, in general, a finite growth rate with respect to the uncertainties in assimilation. The computational hydrodynamical model used in this study is the Advanced Circulation (ADCIRC) model. The authors assimilate data obtained from Hurricanes Katrina and Ike as test cases. The results clearly show that the H∞-based SEIK filter provides more accurate short-range forecasts of storm surge compared to recently reported data assimilation results resulting from the standard SEIK filter.

  10. Improving Short-Range Ensemble Kalman Storm Surge Forecasting Using Robust Adaptive Inflation

    KAUST Repository

    Altaf, Muhammad; Butler, T.; Luo, X.; Dawson, C.; Mayo, T.; Hoteit, Ibrahim

    2013-01-01

    This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H∞ filter. By design, an H∞ filter is more robust than the common Kalman filter in the sense that the estimation error in the H∞ filter has, in general, a finite growth rate with respect to the uncertainties in assimilation. The computational hydrodynamical model used in this study is the Advanced Circulation (ADCIRC) model. The authors assimilate data obtained from Hurricanes Katrina and Ike as test cases. The results clearly show that the H∞-based SEIK filter provides more accurate short-range forecasts of storm surge compared to recently reported data assimilation results resulting from the standard SEIK filter.

  11. New forecasting methods of the intensity and time development of geomagnetic and ionospheric storms

    International Nuclear Information System (INIS)

    Akasofu, S.I.

    1981-01-01

    The main phase of a geomagnetic storm develops differently from one storm to another. A description is given of the solar wind quantity which controls directly the development of the main phase of geomagnetic storms. The parameters involved include the solar wind speed, the magnetic field intensity, and the polar angle of the solar wind magnetic field projected onto the dawn-dusk plane. A redefinition of geomagnetic storm and auroral activity is given. It is pointed out that geomagnetic disturbances are caused by the magnetic fields of electric currents which are generated by the solar wind-magnetosphere dynamo. Attention is given to approaches for forecasting the occurrence and intensity of geomagnetic storms and ionospheric disturbances

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

    KAUST Repository

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

    2015-01-01

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

  13. Improving short-range ensemble Kalman storm surge forecasting using robust adaptive inflation

    NARCIS (Netherlands)

    Altaf, M.U.; Butler, T.; Luo, X.; Dawson, C.; Mayo, T.; Hoteit, I.

    2013-01-01

    This paper presents a robust ensemble filtering methodology for storm surge forecasting based on the singular evolutive interpolated Kalman (SEIK) filter, which has been implemented in the framework of the H? filter. By design, an H? filter is more robust than the common Kalman filter in the sense

  14. Predicting severe winter coastal storm damage

    International Nuclear Information System (INIS)

    Hondula, David M; Dolan, Robert

    2010-01-01

    Over the past 40 years residents of, and visitors to, the North Carolina coastal barrier islands have experienced the destructive forces of several 'named' extratropical storms. These storms have caused large-scale redistributions of sand and loss of coastal structures and infrastructure. While most of the population living on the islands are familiar with the wintertime storms, the damage and scars of the 'super northeasters'-such as the Ash Wednesday storm of 7 March 1962, and the Halloween storm of 1989-are slipping away from the public's memory. In this research we compared the damage zones of the 1962 Ash Wednesday storm, as depicted on aerial photographs taken after the storm, with photos taken of the same areas in 2003. With these high-resolution aerial photos we were able to estimate the extent of new development which has taken place along the Outer Banks of North Carolina since 1962. Three damage zones were defined that extend across the islands from the ocean landward on the 1962 aerial photos: (1) the zone of almost total destruction on the seaward edge of the islands where the storm waves break; (2) the zone immediately inland where moderate structural damage occurs during severe storms; and (3) the zone of flood damage at the landward margin of the storm surge and overwash. We considered the rate of coastal erosion, the rate of development, and increases in property values as factors which may contribute to changing the financial risk for coastal communities. In comparing the values of these four factors with the 1962 damage data, we produced a predicted dollar value for storm damage should another storm of the magnitude of the 1962 Ash Wednesday storm occur in the present decade. This model also provides an opportunity to estimate the rate of increase in the potential losses through time as shoreline erosion continues to progressively reduce the buffer between the development and the edge of the sea. Our data suggest that the losses along the North

  15. Predicting severe winter coastal storm damage

    Energy Technology Data Exchange (ETDEWEB)

    Hondula, David M; Dolan, Robert, E-mail: hondula@virginia.edu [Department of Environmental Sciences, University of Virginia, PO Box 400123, Charlottesville, VA 22903 (United States)

    2010-07-15

    Over the past 40 years residents of, and visitors to, the North Carolina coastal barrier islands have experienced the destructive forces of several 'named' extratropical storms. These storms have caused large-scale redistributions of sand and loss of coastal structures and infrastructure. While most of the population living on the islands are familiar with the wintertime storms, the damage and scars of the 'super northeasters'-such as the Ash Wednesday storm of 7 March 1962, and the Halloween storm of 1989-are slipping away from the public's memory. In this research we compared the damage zones of the 1962 Ash Wednesday storm, as depicted on aerial photographs taken after the storm, with photos taken of the same areas in 2003. With these high-resolution aerial photos we were able to estimate the extent of new development which has taken place along the Outer Banks of North Carolina since 1962. Three damage zones were defined that extend across the islands from the ocean landward on the 1962 aerial photos: (1) the zone of almost total destruction on the seaward edge of the islands where the storm waves break; (2) the zone immediately inland where moderate structural damage occurs during severe storms; and (3) the zone of flood damage at the landward margin of the storm surge and overwash. We considered the rate of coastal erosion, the rate of development, and increases in property values as factors which may contribute to changing the financial risk for coastal communities. In comparing the values of these four factors with the 1962 damage data, we produced a predicted dollar value for storm damage should another storm of the magnitude of the 1962 Ash Wednesday storm occur in the present decade. This model also provides an opportunity to estimate the rate of increase in the potential losses through time as shoreline erosion continues to progressively reduce the buffer between the development and the edge of the sea. Our data suggest that the

  16. Predicting severe winter coastal storm damage

    Science.gov (United States)

    Hondula, David M.; Dolan, Robert

    2010-07-01

    Over the past 40 years residents of, and visitors to, the North Carolina coastal barrier islands have experienced the destructive forces of several 'named' extratropical storms. These storms have caused large-scale redistributions of sand and loss of coastal structures and infrastructure. While most of the population living on the islands are familiar with the wintertime storms, the damage and scars of the 'super northeasters'—such as the Ash Wednesday storm of 7 March 1962, and the Halloween storm of 1989—are slipping away from the public's memory. In this research we compared the damage zones of the 1962 Ash Wednesday storm, as depicted on aerial photographs taken after the storm, with photos taken of the same areas in 2003. With these high-resolution aerial photos we were able to estimate the extent of new development which has taken place along the Outer Banks of North Carolina since 1962. Three damage zones were defined that extend across the islands from the ocean landward on the 1962 aerial photos: (1) the zone of almost total destruction on the seaward edge of the islands where the storm waves break; (2) the zone immediately inland where moderate structural damage occurs during severe storms; and (3) the zone of flood damage at the landward margin of the storm surge and overwash. We considered the rate of coastal erosion, the rate of development, and increases in property values as factors which may contribute to changing the financial risk for coastal communities. In comparing the values of these four factors with the 1962 damage data, we produced a predicted dollar value for storm damage should another storm of the magnitude of the 1962 Ash Wednesday storm occur in the present decade. This model also provides an opportunity to estimate the rate of increase in the potential losses through time as shoreline erosion continues to progressively reduce the buffer between the development and the edge of the sea. Our data suggest that the losses along the

  17. Artificial Neural Network forecasting of storm surge water levels at major estuarine ports to supplement national tide-surge models and improve port resilience planning

    Science.gov (United States)

    French, Jon; Mawdsley, Robert; Fujiyama, Taku; Achuthan, Kamal

    2017-04-01

    Effective prediction of tidal storm surge is of considerable importance for operators of major ports, since much of their infrastructure is necessarily located close to sea level. Storm surge inundation can damage critical elements of this infrastructure and significantly disrupt port operations and downstream supply chains. The risk of surge inundation is typically approached using extreme value analysis, while short-term forecasting generally relies on coastal shelf-scale tide and surge models. However, extreme value analysis does not provide information on the duration of a surge event and can be sensitive to the assumptions made and the historic data available. Also, whilst regional tide and surge models perform well along open coasts, their fairly coarse spatial resolution means that they do not always provide accurate predictions for estuarine ports. As part of a NERC Environmental Risks to Infrastructure Innovation Programme project, we have developed a tool that is specifically designed to forecast the North Sea storm surges on major ports along the east coast of the UK. Of particular interest is the Port of Immingham, Humber estuary, which handles the largest volume of bulk cargo in the UK including major flows of coal and biomass for power generation. A tidal surge in December 2013, with an estimated return period of 760 years, partly flooded the port, damaged infrastructure and disrupted operations for several weeks. This and other recent surge events highlight the need for additional tools to supplement the national UK Storm Tide Warning Service. Port operators are also keen to have access to less computationally expensive forecasting tools for scenario planning and to improve their resilience to actual events. In this paper, we demonstrate the potential of machine learning methods based on Artificial Neural Networks (ANNs) to generate accurate short-term forecasts of extreme water levels at estuarine North Sea ports such as Immingham. An ANN is

  18. Spotter's Guide for Identifying and Reporting Severe Local Storms.

    Science.gov (United States)

    National Oceanic and Atmospheric Administration (DOC), Rockville, MD.

    This guide is designed to assist personnel working in the National Weather Service's Severe Local Storm Spotter Networks in identifying and reporting severe local storms. Provided are pictures of cloud types for severe storms including tornadoes, hail, thunder, lightning, heavy rains, and waterspouts. Instructions for key indications to watch for…

  19. Toward an integrated storm surge application: ESA Storm Surge project

    Science.gov (United States)

    Lee, Boram; Donlon, Craig; Arino, Olivier

    2010-05-01

    Storm surges and their associated coastal inundation are major coastal marine hazards, both in tropical and extra-tropical areas. As sea level rises due to climate change, the impact of storm surges and associated extreme flooding may increase in low-lying countries and harbour cities. Of the 33 world cities predicted to have at least 8 million people by 2015, at least 21 of them are coastal including 8 of the 10 largest. They are highly vulnerable to coastal hazards including storm surges. Coastal inundation forecasting and warning systems depend on the crosscutting cooperation of different scientific disciplines and user communities. An integrated approach to storm surge, wave, sea-level and flood forecasting offers an optimal strategy for building improved operational forecasts and warnings capability for coastal inundation. The Earth Observation (EO) information from satellites has demonstrated high potential to enhanced coastal hazard monitoring, analysis, and forecasting; the GOCE geoid data can help calculating accurate positions of tide gauge stations within the GLOSS network. ASAR images has demonstrated usefulness in analysing hydrological situation in coastal zones with timely manner, when hazardous events occur. Wind speed and direction, which is the key parameters for storm surge forecasting and hindcasting, can be derived by using scatterometer data. The current issue is, although great deal of useful EO information and application tools exist, that sufficient user information on EO data availability is missing and that easy access supported by user applications and documentation is highly required. Clear documentation on the user requirements in support of improved storm surge forecasting and risk assessment is also needed at the present. The paper primarily addresses the requirements for data, models/technologies, and operational skills, based on the results from the recent Scientific and Technical Symposium on Storm Surges (www

  20. Case study: An isolated severe storm with giant hail hit Slovenian capital city Ljubljana on May 25th 2009

    Science.gov (United States)

    Korosec, M.

    2009-09-01

    Introduction A quite unusual weather pattern for month of May with first and early season heat wave of year 2009 resulted in several days of active severe storms across central Europe and Alpine region. Synoptic situation On May 25th 2009, an omega block pattern with strong upper-level subtropical ridge extending over Mediterranean and Balkan Peninsula brought stable and warm conditions into Southern Europe. Elsewhere, two large-scale troughs were located over Western and Eastern Europe with very unstable environment. On the nose of the Mediterranean ridge a jet streak with moderate shear was placed while over the Southern Alpine region only weak shear was placed over Slovenia. Rich boundary layer moisture and steep lapse rates within an elevated mixed layer favored extreme amounts of CAPE. After strong diurnal heating and surface wind convergence along the local topography a few convective cells were triggered in the mountainous terrain while deep moist convection over the rest of Slovenia was trapped by the strong capping inversion. In late afternoon several cells from the mountainous terrain interfered with each other and explosive convective cell was initiated along their outflow boundaries. Increasing near surface southeasterly wind flow supported enhanced low-level shear and storm relative helicity which caused this cell to very rapidly grown into an organized supercell storm on the flat terrain in northern Slovenia. This supercell then started racing southeastwards towards Ljubljana, a capital city of Slovenia. It caused extensive hail damage with very large to giant hailstones up to 7cm in diameter falling over parts of Ljubljana and areas north and southeast of the city. Presentation of research This case study will go through a research of this very damaging hailstorm, throughout a detailed analysis of the synoptic situation including analysis of satellite, radar and surface observations. At first, forecasting models did not suggest organized convection

  1. Next-generation storm tracking for minimizing service interruption

    Energy Technology Data Exchange (ETDEWEB)

    Sznaider, R. [Meteorlogix, Minneapolis, MN (United States)

    2002-08-01

    Several technological changes have taken place in the field of weather radar since its discovery during World War II. A wide variety of industries have benefited over the years from conventional weather radar displays, providing assistance in forecasting and estimating the potential severity of storms. The characteristics of individual storm cells can now be derived from the next-generation of weather radar systems (NEXRAD). The determination of which storm cells possess distinct features such as large hail or developing tornadoes was made possible through the fusing of various pieces of information with radar pictures. To exactly determine when and where a storm will hit, this data can be combined and overlaid into a display that includes the geographical physical landmarks of a specific region. Combining Geographic Information Systems (GIS) and storm tracking provides a more complete, timely and accurate forecast, which clearly benefits the electric utilities industries. The generation and production of energy are dependent on how hot or cold it will be today and tomorrow. The author described each major feature of this next-generation weather radar system. 9 figs.

  2. Severe storm in Bavaria, the Czech Republic and Poland on 12–13 July 1984: A statistic- and model-based analysis

    Czech Academy of Sciences Publication Activity Database

    Kašpar, Marek; Müller, Miloslav; Kakos, Vilibald; Řezáčová, Daniela; Sokol, Zbyněk

    2009-01-01

    Roč. 93, 1-3 (2009), s. 99-110 ISSN 0169-8095. [European Conference on Severe Storms /4./. Miramare -Trieste, 10.09.2007-14.09.2007] R&D Projects: GA ČR GA205/07/0905; GA AV ČR KJB300420701; GA AV ČR KJB300420802 Institutional research plan: CEZ:AV0Z30420517 Keywords : convective storm * synoptic anomaly * mesoscale condition * forecast verification * gust front Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.811, year: 2009 http://www. elsevier.com/locate/atmos

  3. Constraining storm-scale forecasts of deep convective initiation with surface weather observations

    Science.gov (United States)

    Madaus, Luke

    Successfully forecasting when and where individual convective storms will form remains an elusive goal for short-term numerical weather prediction. In this dissertation, the convective initiation (CI) challenge is considered as a problem of insufficiently resolved initial conditions and dense surface weather observations are explored as a possible solution. To better quantify convective-scale surface variability in numerical simulations of discrete convective initiation, idealized ensemble simulations of a variety of environments where CI occurs in response to boundary-layer processes are examined. Coherent features 1-2 hours prior to CI are found in all surface fields examined. While some features were broadly expected, such as positive temperature anomalies and convergent winds, negative temperature anomalies due to cloud shadowing are the largest surface anomaly seen prior to CI. Based on these simulations, several hypotheses about the required characteristics of a surface observing network to constrain CI forecasts are developed. Principally, these suggest that observation spacings of less than 4---5 km would be required, based on correlation length scales. Furthermore, it is anticipated that 2-m temperature and 10-m wind observations would likely be more relevant for effectively constraining variability than surface pressure or 2-m moisture observations based on the magnitudes of observed anomalies relative to observation error. These hypotheses are tested with a series of observing system simulation experiments (OSSEs) using a single CI-capable environment. The OSSE results largely confirm the hypotheses, and with 4-km and particularly 1-km surface observation spacing, skillful forecasts of CI are possible, but only within two hours of CI time. Several facets of convective-scale assimilation, including the need for properly-calibrated localization and problems from non-Gaussian ensemble estimates of the cloud field are discussed. Finally, the characteristics

  4. An Approach to Remove the Systematic Bias from the Storm Surge forecasts in the Venice Lagoon

    Science.gov (United States)

    Canestrelli, A.

    2017-12-01

    In this work a novel approach is proposed for removing the systematic bias from the storm surge forecast computed by a two-dimensional shallow-water model. The model covers both the Adriatic and Mediterranean seas and provides the forecast at the entrance of the Venice Lagoon. The wind drag coefficient at the water-air interface is treated as a calibration parameter, with a different value for each range of wind velocities and wind directions. This sums up to a total of 16-64 parameters to be calibrated, depending on the chosen resolution. The best set of parameters is determined by means of an optimization procedure, which minimizes the RMS error between measured and modeled water level in Venice for the period 2011-2015. It is shown that a bias is present, for which the peaks of wind velocities provided by the weather forecast are largely underestimated, and that the calibration procedure removes this bias. When the calibrated model is used to reproduce events not included in the calibration dataset, the forecast error is strongly reduced, thus confirming the quality of our procedure. The proposed approach it is not site-specific and could be applied to different situations, such as storm surges caused by intense hurricanes.

  5. Storm and cloud dynamics

    CERN Document Server

    Cotton, William R

    1992-01-01

    This book focuses on the dynamics of clouds and of precipitating mesoscale meteorological systems. Clouds and precipitating mesoscale systems represent some of the most important and scientifically exciting weather systems in the world. These are the systems that produce torrential rains, severe winds including downburst and tornadoes, hail, thunder and lightning, and major snow storms. Forecasting such storms represents a major challenge since they are too small to be adequately resolved by conventional observing networks and numerical prediction models.Key Features* Key Highlight

  6. Improved Satellite Techniques for Monitoring and Forecasting the Transition of Hurricanes to Extratropical Storms

    Science.gov (United States)

    Folmer, Michael; Halverson, Jeffrey; Berndt, Emily; Dunion, Jason; Goodman, Steve; Goldberg, Mitch

    2014-01-01

    The Geostationary Operational Environmental Satellites R-Series (GOES-R) and Joint Polar Satellite System (JPSS) Satellite Proving Grounds have introduced multiple proxy and operational products into operations over the last few years. Some of these products have proven to be useful in current operations at various National Weather Service (NWS) offices and national centers as a first look at future satellite capabilities. Forecasters at the National Hurricane Center (NHC), Ocean Prediction Center (OPC), NESDIS Satellite Analysis Branch (SAB) and the NASA Hurricane and Severe Storms Sentinel (HS3) field campaign have had access to a few of these products to assist in monitoring extratropical transitions of hurricanes. The red, green, blue (RGB) Air Mass product provides forecasters with an enhanced view of various air masses in one complete image to help differentiate between possible stratospheric/tropospheric interactions, moist tropical air masses, and cool, continental/maritime air masses. As a compliment to this product, a new Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS) Ozone product was introduced in the past year to assist in diagnosing the dry air intrusions seen in the RGB Air Mass product. Finally, a lightning density product was introduced to forecasters as a precursor to the new Geostationary Lightning Mapper (GLM) that will be housed on GOES-R, to monitor the most active regions of convection, which might indicate a disruption in the tropical environment and even signal the onset of extratropical transition. This presentation will focus on a few case studies that exhibit extratropical transition and point out the usefulness of these new satellite techniques in aiding forecasters forecast these challenging events.

  7. The NASA Severe Thunderstorm Observations and Regional Modeling (NASA STORM) Project

    Science.gov (United States)

    Schultz, Christopher J.; Gatlin, Patrick N.; Lang, Timothy J.; Srikishen, Jayanthi; Case, Jonathan L.; Molthan, Andrew L.; Zavodsky, Bradley T.; Bailey, Jeffrey; Blakeslee, Richard J.; Jedlovec, Gary J.

    2016-01-01

    The NASA Severe Storm Thunderstorm Observations and Regional Modeling(NASA STORM) project enhanced NASA’s severe weather research capabilities, building upon existing Earth Science expertise at NASA Marshall Space Flight Center (MSFC). During this project, MSFC extended NASA’s ground-based lightning detection capacity to include a readily deployable lightning mapping array (LMA). NASA STORM also enabled NASA’s Short-term Prediction and Research Transition (SPoRT) to add convection allowing ensemble modeling to its portfolio of regional numerical weather prediction (NWP) capabilities. As a part of NASA STORM, MSFC developed new open-source capabilities for analyzing and displaying weather radar observations integrated from both research and operational networks. These accomplishments enabled by NASA STORM are a step towards enhancing NASA’s capabilities for studying severe weather and positions them for any future NASA related severe storm field campaigns.

  8. Rapid wave and storm surge warning system for tropical cyclones in Mexico

    Science.gov (United States)

    Appendini, C. M.; Rosengaus, M.; Meza, R.; Camacho, V.

    2015-12-01

    The National Hurricane Center (NHC) in Miami, is responsible for the forecast of tropical cyclones in the North Atlantic and Eastern North Pacific basins. As such, Mexico, Central America and Caribbean countries depend on the information issued by the NHC related to the characteristics of a particular tropical cyclone and associated watch and warning areas. Despite waves and storm surge are important hazards for marine operations and coastal dwellings, their forecast is not part of the NHC responsibilities. This work presents a rapid wave and storm surge warning system based on 3100 synthetic tropical cyclones doing landfall in Mexico. Hydrodynamic and wave models were driven by the synthetic events to create a robust database composed of maximum envelops of wind speed, significant wave height and storm surge for each event. The results were incorporated into a forecast system that uses the NHC advisory to locate the synthetic events passing inside specified radiuses for the present and forecast position of the real event. Using limited computer resources, the system displays the information meeting the search criteria, and the forecaster can select specific events to generate the desired hazard map (i.e. wind, waves, and storm surge) based on the maximum envelop maps. This system was developed in a limited time frame to be operational in 2015 by the National Hurricane and Severe Storms Unit of the Mexican National Weather Service, and represents a pilot project for other countries in the region not covered by detailed storm surge and waves forecasts.

  9. Ionospheric behaviour during storm recovery phase

    Science.gov (United States)

    Buresova, D.; Lastovicka, J.; Boska, J.; Sindelarova, T.; Chum, J.

    2012-04-01

    Intensive ionospheric research, numerous multi-instrumental observations and large-scale numerical simulations of ionospheric F region response to magnetic storm-induced disturbances during the last several decades were primarily focused on the storm main phase, in most cases covering only a few hours of the recovery phase following after storm culmination. Ionospheric behaviour during entire recovery phase still belongs to not sufficiently explored and hardly predictable features. In general, the recovery phase is characterized by an abatement of perturbations and a gradual return to the "ground state" of ionosphere. However, observations of stormy ionosphere show significant departures from the climatology also within this phase. This paper deals with the quantitative and qualitative analysis of the ionospheric behaviour during the entire recovery phase of strong-to-severe magnetic storms at middle latitudes for nowadays and future modelling and forecasting purposes.

  10. Forecasting challenges during the severe weather outbreak in Central Europe on 25 June 2008

    Science.gov (United States)

    Púčik, Tomáš; Francová, Martina; Rýva, David; Kolář, Miroslav; Ronge, Lukáš

    2011-06-01

    On 25 June 2008, severe thunderstorms caused widespread damage and two fatalities in the Czech Republic. Significant features of the storms included numerous downbursts on a squall line that exhibited a bow echo reflectivity pattern, with sustained wind gusts over 32 m/s at several reporting stations. Moreover, a tornado and several downbursts of F2 intensity occurred within the convective system, collocated with the development of mesovortices within the larger scale bow echo. The extent of the event was sufficient to call it a derecho, as the windstorm had affected Eastern Germany, Southern Poland, Slovakia, Austria and Northern Hungary as well. Ahead of the squall line, several well-organized isolated cells occurred, exhibiting supercellular characteristics, both from a radar and visual perspective. These storms produced large hail and also isolated severe wind gusts. This paper deals mostly with the forecasting challenges that were experienced by the meteorologist on duty during the evolution of this convective scenario. The main challenge of the day was to identify the region that would be most affected by severe convection, especially as the numerical weather prediction failed to anticipate the extent and the progress of the derecho-producing mesoscale convective systems (MCSs). Convective storms developed in an environment conducive to severe thunderstorms, with strong wind shear confined mostly to the lower half of the troposphere. These developments also were strongly influenced by mesoscale factors, especially a mesolow centered over Austria and its trough stretching to Eastern Bohemia. The paper demonstrates how careful mesoscale analysis could prove useful in dealing with such convective situations. Remote-sensing methods are also shown to be useful in such situations, especially when they can offer sufficient lead time to issue a warning, which is not always the case.

  11. The Framework of a Coastal Hazards Model - A Tool for Predicting the Impact of Severe Storms

    Science.gov (United States)

    Barnard, Patrick L.; O'Reilly, Bill; van Ormondt, Maarten; Elias, Edwin; Ruggiero, Peter; Erikson, Li H.; Hapke, Cheryl; Collins, Brian D.; Guza, Robert T.; Adams, Peter N.; Thomas, Julie

    2009-01-01

    The U.S. Geological Survey (USGS) Multi-Hazards Demonstration Project in Southern California (Jones and others, 2007) is a five-year project (FY2007-FY2011) integrating multiple USGS research activities with the needs of external partners, such as emergency managers and land-use planners, to produce products and information that can be used to create more disaster-resilient communities. The hazards being evaluated include earthquakes, landslides, floods, tsunamis, wildfires, and coastal hazards. For the Coastal Hazards Task of the Multi-Hazards Demonstration Project in Southern California, the USGS is leading the development of a modeling system for forecasting the impact of winter storms threatening the entire Southern California shoreline from Pt. Conception to the Mexican border. The modeling system, run in real-time or with prescribed scenarios, will incorporate atmospheric information (that is, wind and pressure fields) with a suite of state-of-the-art physical process models (that is, tide, surge, and wave) to enable detailed prediction of currents, wave height, wave runup, and total water levels. Additional research-grade predictions of coastal flooding, inundation, erosion, and cliff failure will also be performed. Initial model testing, performance evaluation, and product development will be focused on a severe winter-storm scenario developed in collaboration with the Winter Storm Working Group of the USGS Multi-Hazards Demonstration Project in Southern California. Additional offline model runs and products will include coastal-hazard hindcasts of selected historical winter storms, as well as additional severe winter-storm simulations based on statistical analyses of historical wave and water-level data. The coastal-hazards model design will also be appropriate for simulating the impact of storms under various sea level rise and climate-change scenarios. The operational capabilities of this modeling system are designed to provide emergency planners with

  12. Physical and Dynamical Linkages Between Lightning Jumps and Storm Conceptual Models

    Science.gov (United States)

    Schultz, Christopher J.; Carey, Lawrence D.; Schultz, Elise V.; Blakeslee, Richard J.; Goodman, Steven J.

    2014-01-01

    The presence and rates of total lightning are both correlated to and physically dependent upon storm updraft strength, mixed phase precipitation volume and the size of the charging zone. The updraft modulates the ingredients necessary for electrification within a thunderstorm, while the updraft also plays a critical role in the development of severe and hazardous weather. Therefore utilizing this relationship, the monitoring of lightning rates and jumps provides an additional piece of information on the evolution of a thunderstorm, more often than not, at higher temporal resolution than current operational radar systems. This correlation is the basis for the total lightning jump algorithm that has been developed in recent years. Currently, the lightning jump algorithm is being tested in two separate but important efforts. Schultz et al. (2014; this conference) is exploring the transition of the algorithm from its research based formulation to a fully objective algorithm that includes storm tracking, Geostationary Lightning Mapper (GLM) Proxy data and the lightning jump algorithm. Chronis et al. (2014) provides context for the transition to current operational forecasting using lightning mapping array based products. However, what remains is an end-to-end physical and dynamical basis for coupling total lightning flash rates to severe storm manifestation, so the forecaster has a reason beyond simple correlation to utilize the lightning jump algorithm within their severe storm conceptual models. Therefore, the physical basis for the lightning jump algorithm in relation to severe storm dynamics and microphysics is a key component that must be further explored. Many radar studies have examined flash rates and their relationship to updraft strength, updraft volume, precipitation-sized ice mass, etc.; however, their relationship specifically to lightning jumps is fragmented within the literature. Thus the goal of this study is to use multiple Doppler and polarimetric

  13. Short-Term Forecasting of Urban Storm Water Runoff in Real-Time using Extrapolated Radar Rainfall Data

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2013-01-01

    Model based short-term forecasting of urban storm water runoff can be applied in realtime control of drainage systems in order to optimize system capacity during rain and minimize combined sewer overflows, improve wastewater treatment or activate alarms if local flooding is impending. A novel onl....... The radar rainfall extrapolation (nowcast) limits the lead time of the system to two hours. In this paper, the model set-up is tested on a small urban catchment for a period of 1.5 years. The 50 largest events are presented....... online system, which forecasts flows and water levels in real-time with inputs from extrapolated radar rainfall data, has been developed. The fully distributed urban drainage model includes auto-calibration using online in-sewer measurements which is seen to improve forecast skills significantly...

  14. Problem of short-term forecasting of near-earth space state

    International Nuclear Information System (INIS)

    Eselevich, V.G.; Ashmanets, V.I.; Startsev, S.A.

    1996-01-01

    The paper deals with actual and practically important problem of investigation and forecasting of state condition during magnetic storms. The available methods of forecasting of near-earth space state are analyzed. Forecasting of magnetic storms was conducted for control of space vehicles. Quasi-determinate method of magnetic storm forecasting is suggested. 13 refs., 3 figs

  15. Assessment of storm forecast

    DEFF Research Database (Denmark)

    Cutululis, Nicolaos Antonio; Hahmann, Andrea N.; Huus Bjerge, Martin

    When wind speed exceeds a certain value, wind turbines shut-down in order to protect their structure. This leads to sudden wind plants shut down and to new challenges concerning the secure operation of the pan-European electric system with future large scale offshore wind power. This task aims...... stopped, completely or partially, producing due to extreme wind speeds. Wind speed and power measurements from those events are presented and compared to the forecast available at Energinet.dk. The analysis looked at wind speed and wind power forecast. The main conclusion of the analysis is that the wind...... to consider it an EWP) and that the available wind speed forecasts are given as a mean wind speed over a rather large area. At wind power level, the analysis shows that prediction of accurate production levels from a wind farm experiencing EWP is rather poor. This is partially because the power curve...

  16. Geomagnetic Dst index forecast based on IMF data only

    Directory of Open Access Journals (Sweden)

    G. Pallocchia

    2006-05-01

    Full Text Available In the past years several operational Dst forecasting algorithms, based on both IMF and solar wind plasma parameters, have been developed and used. We describe an Artificial Neural Network (ANN algorithm which calculates the Dst index on the basis of IMF data only and discuss its performance for several individual storms. Moreover, we briefly comment on the physical grounds which allow the Dst forecasting based on IMF only.

  17. Remote sensing of severe convective storms over Qinghai-Xizang Plateau

    Science.gov (United States)

    Hung, R. J.; Liu, J. M.; Tsao, D. Y.; Smith, R. E.

    1984-01-01

    The American satellite, GOES-1 was moved to the Indian Ocean at 58 deg E during the First GARP Global Experiment (FGGE). The Qinghai-Xizang Plateau significantly affects the initiation and development of heavy rainfall and severe storms in China, just as the Rocky Mountains influence the local storms in the United States. Satelite remote sensing of short-lived, meso-scale convective storms is particularly important for covering a huge area of a high elevation with a low population density, such as the Qinghai-Xizang Plateau. Results of this study show that a high growth rate of the convective clouds, followed by a rapid collapse of the cloud top, is associated with heavy rainfall in the area. The tops of the convective clouds developed over the Plateau lie between the altitudes of the two tropopauses, while the tops of convective clouds associated with severe storms in the United States usually extend much above the tropopause.

  18. Regional corrections and checking the reliability of geomagnetic forecasts

    International Nuclear Information System (INIS)

    Afanas'eva, V.I.; Shevnin, A.D.

    1978-01-01

    Regional corrections of the K index mark estimate with respect to the Moskva observatory are reviewed in order to improve the short-range forecast of the geomagnetic activity and to promote it within the aqua area. The forecasts of the storms of all categories and weak perturbations have been verified for the predominant days in the catalogue of the magnetic storms family. It is shown that the adopted methods of forecasts yield considerably good results for weak perturbations as well as for weak and moderate magnetic storms. Strong and very strong storms are less predictable

  19. Enhanced outage prediction modeling for strong extratropical storms and hurricanes in the Northeastern United States

    Science.gov (United States)

    Cerrai, D.; Anagnostou, E. N.; Wanik, D. W.; Bhuiyan, M. A. E.; Zhang, X.; Yang, J.; Astitha, M.; Frediani, M. E.; Schwartz, C. S.; Pardakhti, M.

    2016-12-01

    The overwhelming majority of human activities need reliable electric power. Severe weather events can cause power outages, resulting in substantial economic losses and a temporary worsening of living conditions. Accurate prediction of these events and the communication of forecasted impacts to the affected utilities is necessary for efficient emergency preparedness and mitigation. The University of Connecticut Outage Prediction Model (OPM) uses regression tree models, high-resolution weather reanalysis and real-time weather forecasts (WRF and NCAR ensemble), airport station data, vegetation and electric grid characteristics and historical outage data to forecast the number and spatial distribution of outages in the power distribution grid located within dense vegetation. Recent OPM improvements consist of improved storm classification and addition of new predictive weather-related variables and are demonstrated using a leave-one-storm-out cross-validation based on 130 severe extratropical storms and two hurricanes (Sandy and Irene) in the Northeast US. We show that it is possible to predict the number of trouble spots causing outages in the electric grid with a median absolute percentage error as low as 27% for some storm types, and at most around 40%, in a scale that varies between four orders of magnitude, from few outages to tens of thousands. This outage information can be communicated to the electric utility to manage allocation of crews and equipment and minimize the recovery time for an upcoming storm hazard.

  20. L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting

    Science.gov (United States)

    Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i...

  1. Storm surge model based on variational data assimilation method

    Directory of Open Access Journals (Sweden)

    Shi-li Huang

    2010-06-01

    Full Text Available By combining computation and observation information, the variational data assimilation method has the ability to eliminate errors caused by the uncertainty of parameters in practical forecasting. It was applied to a storm surge model based on unstructured grids with high spatial resolution meant for improving the forecasting accuracy of the storm surge. By controlling the wind stress drag coefficient, the variation-based model was developed and validated through data assimilation tests in an actual storm surge induced by a typhoon. In the data assimilation tests, the model accurately identified the wind stress drag coefficient and obtained results close to the true state. Then, the actual storm surge induced by Typhoon 0515 was forecast by the developed model, and the results demonstrate its efficiency in practical application.

  2. Visualizing uncertainties in a storm surge ensemble data assimilation and forecasting system

    KAUST Repository

    Hollt, Thomas

    2015-01-15

    We present a novel integrated visualization system that enables the interactive visual analysis of ensemble simulations and estimates of the sea surface height and other model variables that are used for storm surge prediction. Coastal inundation, caused by hurricanes and tropical storms, poses large risks for today\\'s societies. High-fidelity numerical models of water levels driven by hurricane-force winds are required to predict these events, posing a challenging computational problem, and even though computational models continue to improve, uncertainties in storm surge forecasts are inevitable. Today, this uncertainty is often exposed to the user by running the simulation many times with different parameters or inputs following a Monte-Carlo framework in which uncertainties are represented as stochastic quantities. This results in multidimensional, multivariate and multivalued data, so-called ensemble data. While the resulting datasets are very comprehensive, they are also huge in size and thus hard to visualize and interpret. In this paper, we tackle this problem by means of an interactive and integrated visual analysis system. By harnessing the power of modern graphics processing units for visualization as well as computation, our system allows the user to browse through the simulation ensembles in real time, view specific parameter settings or simulation models and move between different spatial and temporal regions without delay. In addition, our system provides advanced visualizations to highlight the uncertainty or show the complete distribution of the simulations at user-defined positions over the complete time series of the prediction. We highlight the benefits of our system by presenting its application in a real-world scenario using a simulation of Hurricane Ike.

  3. Use of Dual-Polarization Radar Variables to Assess Low-Level Wind Shear in Severe Thunderstorm Near-storm Environments in the Tennessee Valley

    Science.gov (United States)

    Crowe, Christina C.; Schultz, Christopher J.; Kumjian, Matthew; Carey, Lawerence D.; Petersen, Walter A.

    2011-01-01

    The upgrade of the National Weather Service (NWS) network of S ]band dual-polarization radars is currently underway, and the incorporation of polarimetric information into the real ]time forecasting process will enhance the forecaster fs ability to assess thunderstorms and their near ]storm environments. Recent research has suggested that the combination of polarimetric variables differential reflectivity (ZDR) and specific differential phase (KDP) can be useful in the assessment of low level wind shear within a thunderstorm. In an environment with strong low ]level veering of the wind, ZDR values will be largest along the right inflow edge of the thunderstorm near a large gradient in horizontal reflectivity (indicative of large raindrops falling with a relative lack of smaller drops), and take the shape of an arc. Meanwhile, KDP values, which are proportional to liquid water content and indicative of a large number of smaller drops, are maximized deeper into the forward flank precipitation shield than the ZDR arc as the smaller drops are being advected further from the updraft core by the low level winds than the larger raindrops. Using findings from previous work, three severe weather events that occurred in North Alabama were examined in order to assess the utility of these signatures in determining the potential for tornadic activity. The first case is from October 26, 2010, where a large number of storms indicated tornadic potential from a standard reflectivity and velocity analysis but very few storms actually produced tornadoes. The second event is from February 28, 2011, where tornadic storms were present early on in the event, but as the day progressed, the tornado threat transitioned to a high wind threat. The third case is from April 27, 2011, where multiple rounds of tornadic storms ransacked the Tennessee Valley. This event provides a dataset including multiple modes of tornadic development, including QLCS and supercell structures. The overarching goal

  4. A two year (2008-2009) analysis of severe convective storms in the Mediterranean basin as observed by satellite imagery

    Science.gov (United States)

    Gozzini, B.; Melani, S.; Pasi, F.; Ortolani, A.

    2010-09-01

    The increasing damages caused by natural disasters, a great part of them being direct or indirect effects of severe convective storms (SCS), seem to suggest that extreme events occur with greater frequency, also as a consequence of climate changes. A better comprehension of the genesis and evolution of SCS is then necessary to clarify if and what is changing in these extreme events. The major reason to go through the mechanisms driving such events is given by the growing need to have timely and precise predictions of severe weather events, especially in areas that show to be more and more sensitive to their occurrence. When dealing with severe weather events, either from a researcher or an operational point of view, it is necessary to know precisely the conditions under which these events take place to upgrade conceptual models or theories, and consequently to improve the quality of forecasts as well as to establish effective warning decision procedures. The Mediterranean basin is, in general terms, a sea of small areal extent, characterised by the presence of several islands; thus, a severe convection phenomenon originating over the sea, that lasts several hours, is very likely to make landfall during its lifetime. On the other hand, these storms are quasi-stationary or very slow moving so that, when convection happens close to the shoreline, it is normally very dangerous and in many cases can cause very severe weather, with flash floods or tornadoes. An example of these extreme events is one of the case study analysed in this work, regarding the flash flood occurred in Giampileri (Sicily, Italy) the evening of 1st October 2009, where 18 people died, other 79 injured and the historical centre of the village seriously damaged. Severe weather systems and strong convection occurring in the Mediterranean basin have been investigated for two years (2008-2009) using geostationary (MSG) and polar orbiting (AVHRR) satellite data, supported by ECMWF analyses and severe

  5. ENSO-based probabilistic forecasts of March-May U.S. tornado and hail activity

    Science.gov (United States)

    Lepore, Chiara; Tippett, Michael K.; Allen, John T.

    2017-09-01

    Extended logistic regression is used to predict March-May severe convective storm (SCS) activity based on the preceding December-February (DJF) El Niño-Southern Oscillation (ENSO) state. The spatially resolved probabilistic forecasts are verified against U.S. tornado counts, hail events, and two environmental indices for severe convection. The cross-validated skill is positive for roughly a quarter of the U.S. Overall, indices are predicted with more skill than are storm reports, and hail events are predicted with more skill than tornado counts. Skill is higher in the cool phase of ENSO (La Niña like) when overall SCS activity is higher. SCS forecasts based on the predicted DJF ENSO state from coupled dynamical models initialized in October of the previous year extend the lead time with only a modest reduction in skill compared to forecasts based on the observed DJF ENSO state.

  6. The Development of Storm Surge Ensemble Prediction System and Case Study of Typhoon Meranti in 2016

    Science.gov (United States)

    Tsai, Y. L.; Wu, T. R.; Terng, C. T.; Chu, C. H.

    2017-12-01

    Taiwan is under the threat of storm surge and associated inundation, which is located at a potentially severe storm generation zone. The use of ensemble prediction can help forecasters to know the characteristic of storm surge under the uncertainty of track and intensity. In addition, it can help the deterministic forecasting. In this study, the kernel of ensemble prediction system is based on COMCOT-SURGE (COrnell Multi-grid COupled Tsunami Model - Storm Surge). COMCOT-SURGE solves nonlinear shallow water equations in Open Ocean and coastal regions with the nested-grid scheme and adopts wet-dry-cell treatment to calculate potential inundation area. In order to consider tide-surge interaction, the global TPXO 7.1 tide model provides the tidal boundary conditions. After a series of validations and case studies, COMCOT-SURGE has become an official operating system of Central Weather Bureau (CWB) in Taiwan. In this study, the strongest typhoon in 2016, Typhoon Meranti, is chosen as a case study. We adopt twenty ensemble members from CWB WRF Ensemble Prediction System (CWB WEPS), which differs from parameters of microphysics, boundary layer, cumulus, and surface. From box-and-whisker results, maximum observed storm surges were located in the interval of the first and third quartile at more than 70 % gauge locations, e.g. Toucheng, Chengkung, and Jiangjyun. In conclusion, the ensemble prediction can effectively help forecasters to predict storm surge especially under the uncertainty of storm track and intensity

  7. A new deterministic Ensemble Kalman Filter with one-step-ahead smoothing for storm surge forecasting

    KAUST Repository

    Raboudi, Naila

    2016-11-01

    by performing assimilation experiments with the highly nonlinear Lorenz model and a realistic setting of the Advanced Circulation (ADCIRC) model configured for storm surge forecasting in the Gulf of Mexico during Hurricane Ike.

  8. The effect of severe storms on the ice cover of the northern Tatarskiy Strait

    Science.gov (United States)

    Martin, Seelye; Munoz, Esther; Drucker, Robert

    1992-01-01

    Passive microwave images from the Special Sensor Microwave Imager are used to study the volume of ice and sea-bottom water in the Japan Sea as affected by winds and severe storms. The data set comprises brightness temperatures gridded on a polar stereographic projection, and the processing is accomplished with a linear algorithm by Cavalieri et al. (1983) based on the vertically polarized 37-GHz channel. The expressions for calculating heat fluxes and downwelling radiation are given, and ice-cover fluctuations are correlated with severe storm events. The storms generate large transient polynya that occur simultaneously with the strongest heat fluxes, and severe storms are found to contribute about 25 percent of the annual introduction of 25 cu km of ice in the region. The ice production could lead to the renewal of enough sea-bottom water to account for the C-14 data provided, and the generation of Japan Sea bottom water is found to vary directly with storm activity.

  9. Marine Text Forecasts and Products Listing

    Science.gov (United States)

    FQPZ23KWNO West Coast 06z, 18z FQAC23KWNO Artic Alaska 06z, 18z Computer-generated extratropical storm surge Water Levels Tsunami Coastal/Lakeshore Hazard Message; Storm Surge Forecasts Satellite Orbit Predictions Update (Storm #1) As required TCUAT2 (alt) Tropical Cyclone Update (Storm #2) As required TCUAT3 (alt

  10. The women day storm

    OpenAIRE

    Parnowski, Aleksei; Polonska, Anna; Semeniv, Oleg

    2012-01-01

    On behalf of the International Women Day, the Sun gave a hot kiss to our mother Earth in a form of a full halo CME generated by the yesterday's double X-class flare. The resulting geomagnetic storm gives a good opportunity to compare the performance of space weather forecast models operating in near-real-time. We compare the forecasts of most major models and identify some common problems. We also present the results of our own near-real-time forecast models.

  11. Forecasting Winter Storms in the Sierra: A Social Science Perspective in Keeping the Public Safe without Negatively Impacting the Local Tourism Industry

    Science.gov (United States)

    Milne, R.; Wallmann, J.; Myrick, D. T.

    2010-12-01

    The National Weather Service Office in Reno is responsible for issuing Blizzard Warnings, Winter Storm Warnings, and Winter Weather Advisories for the Sierra, including the Lake Tahoe Basin and heavily traveled routes such as Interstate 80, Highway 395 and Highway 50. These forecast products prepare motorists for harsh travel conditions as well as those venturing into the backcountry, which are essential to the NWS mission of saving lives and property. During the winter season, millions of people from around the world visit the numerous world class ski resorts in the Sierra and the Lake Tahoe Basin, which is vital to the local economy. This situation creates a challenging decision for the forecasters to provide appropriate wording in winter statements to keep the public safe, without significantly impacting the local tourism-based economy. Numerous text and graphical products, including online weather briefings, are utilized by NWS Reno to highlight hazards in ensuring the public, businesses, and other government agencies are prepared for winter storms and take appropriate safety measures. The effectiveness of these product types will be explored, with past snowstorms used as examples to show how forecasters determine which type of text or graphical product is most appropriate to convey the hazardous weather threats.

  12. The Use of Pre-Storm Boundary-Layer Baroclinicity in Determining and Operationally Implementing the Atlantic Surface Cyclone Intensification Index

    Science.gov (United States)

    Cione, Joseph; Pietrafes, Leonard J.

    The lateral motion of the Gulf Stream off the eastern seaboard of the United States during the winter season can act to dramatically enhance the low-level baroclinicity within the coastal zone during periods of offshore cold advection. The ralative close proximity of the Gulf Stream current off the mid-Atlantic coast can result in the rapid and intense destabilization of the marine atmospheric boundary layer directly above and shoreward of the Gulf Stream within this region. This airmass modification period often precedes either wintertime coastal cyclogenesis or the cyclonic re-development of existing mid-latitude cyclones. A climatological study investigating the relationship between the severity of the pre-storm, cold advection period and subsequent cyclogenic intensification was undertaken by Cione et al. in 1993. Findings from this study illustrate that the thermal structure of the continental airmass as well as the position of the Gulf Stream front relative to land during the pre-storm period (i.e., 24-48 h prior to the initial cyclonic intensification) are linked to the observed rate of surface cyclonic deepening for storms that either advected into or initially developed within the Carolina-southeast Virginia offshore coastal zone. It is a major objective of this research to test the potential operational utility of this pre-storm low level baroclinic linkage to subsequent cyclogenesis in an actual National Weather Service (NWS) coastal winter storm forecast setting.The ability to produce coastal surface cyclone intensity forecasts recently became available to North Carolina State University researchers and NWS forecasters. This statistical forecast guidance utilizes regression relationships derived from a nine-season (January 1982-April 1990), 116-storm study conducted previously. During the period between February 1994 and February 1996, the Atlantic Surface Cyclone Intensification Index (ASCII) was successfully implemented in an operational setting by

  13. Verification of space weather forecasts at the UK Met Office

    Science.gov (United States)

    Bingham, S.; Sharpe, M.; Jackson, D.; Murray, S.

    2017-12-01

    The UK Met Office Space Weather Operations Centre (MOSWOC) has produced space weather guidance twice a day since its official opening in 2014. Guidance includes 4-day probabilistic forecasts of X-ray flares, geomagnetic storms, high-energy electron events and high-energy proton events. Evaluation of such forecasts is important to forecasters, stakeholders, model developers and users to understand the performance of these forecasts and also strengths and weaknesses to enable further development. Met Office terrestrial near real-time verification systems have been adapted to provide verification of X-ray flare and geomagnetic storm forecasts. Verification is updated daily to produce Relative Operating Characteristic (ROC) curves and Reliability diagrams, and rolling Ranked Probability Skill Scores (RPSSs) thus providing understanding of forecast performance and skill. Results suggest that the MOSWOC issued X-ray flare forecasts are usually not statistically significantly better than a benchmark climatological forecast (where the climatology is based on observations from the previous few months). By contrast, the issued geomagnetic storm activity forecast typically performs better against this climatological benchmark.

  14. Storm Surge and Tide Interaction: A Complete Paradigm

    Science.gov (United States)

    Horsburgh, K.

    2014-12-01

    Estimates show that in 2005, in the largest 136 coastal cities, there were 40 million people and 3,000 billion of assets exposed to 1 in 100 year coastal flood events. Mean sea level rise will increase this exposure to 150 million people and 35,000 billion of assets by 2070. Any further change in the statistics of flood frequency or severity would impact severely on economic and social systems. It is therefore crucial to understand the physical drivers of extreme storm surges, and to have confidence in datasets used for extreme sea level statistics. Much previous research has focussed on the process of tide-surge interaction, and it is now widely accepted that the physical basis of tide-surge interaction is that a phase shift of the tidal signal represents the effect of the surge on the tide. The second aspect of interaction is that shallow water momentum considerations imply that differing tidal states should modulate surge generation: wind stress should have greater surge-generating potential on lower tides. We present results from a storm surge model of the European shelf that demonstrate that tidal range does have an effect on the surges generated. The cycle-integrated effects of wind stress (i.e. the skew surge) are greater when tidal range is low. Our results contradict the absence of any such correlation in tide gauge records. This suggests that whilst the modulating effect of the tide on the skew surge (the time-independent difference between peak prediction and observations) is significant, the difference between individual storms is dominant. This implies that forecasting systems must predict salient detail of the most intense storms. A further implication is that flood forecasting models need to simulate tides with acceptable accuracy at all coastal locations. We extend our model analysis to show that the same modulation of storm surges (by tidal conditions) applies to tropical cyclones. We conduct simulations using a mature operational storm surge model

  15. On the improvement of wave and storm surge hindcasts by downscaled atmospheric forcing: application to historical storms

    Science.gov (United States)

    Bresson, Émilie; Arbogast, Philippe; Aouf, Lotfi; Paradis, Denis; Kortcheva, Anna; Bogatchev, Andrey; Galabov, Vasko; Dimitrova, Marieta; Morvan, Guillaume; Ohl, Patrick; Tsenova, Boryana; Rabier, Florence

    2018-04-01

    Winds, waves and storm surges can inflict severe damage in coastal areas. In order to improve preparedness for such events, a better understanding of storm-induced coastal flooding episodes is necessary. To this end, this paper highlights the use of atmospheric downscaling techniques in order to improve wave and storm surge hindcasts. The downscaling techniques used here are based on existing European Centre for Medium-Range Weather Forecasts reanalyses (ERA-20C, ERA-40 and ERA-Interim). The results show that the 10 km resolution data forcing provided by a downscaled atmospheric model gives a better wave and surge hindcast compared to using data directly from the reanalysis. Furthermore, the analysis of the most extreme mid-latitude cyclones indicates that a four-dimensional blending approach improves the whole process, as it assimilates more small-scale processes in the initial conditions. Our approach has been successfully applied to ERA-20C (the 20th century reanalysis).

  16. Simulation and analysis of synoptic scale dust storms over the Arabian Peninsula

    Science.gov (United States)

    Beegum, S. Naseema; Gherboudj, Imen; Chaouch, Naira; Temimi, Marouane; Ghedira, Hosni

    2018-01-01

    Dust storms are among the most severe environmental problems in arid and semi-arid regions of the world. The predictability of seven dust events, viz. D1: April 2-4, 2014; D2: February 23-24, 2015; D3: April 1-3, 2015; D4: March 26-28, 2016; D5: August 3-5, 2016; D6: March 13-14, 2017 and D7:March 19-21, 2017, are investigated over the Arabian Peninsula using a regionally adapted chemistry transport model CHIMERE coupled with the Weather Research and Forecast (WRF) model. The hourly forecast products of particulate matter concentrations (PM10) and aerosol optical depths (AOD) are compared against both satellite-based (MSG/SEVRI RGB dust, MODIS Deep Blue Aerosol Optical Depth: DB-AOD, Ozone Monitoring Instrument observed UV Aerosol Absorption Index: OMI-AI) and ground-based (AERONET AOD) remote sensing products. The spatial pattern and the time series of the simulations show good agreement with the observations in terms of the dust intensity as well as the spatiotemporal distribution. The causative mechanisms of these dust events are identified by the concurrent analyses of the meteorological data. From these seven storms, five are associated with synoptic scale meteorological processes, such as prefrontal storms (D1 and D7), postfrontal storms of short (D2), and long (D3) duration types, and a summer shamal storm (D6). However, the storms D4 and D6 are partly associated with mesoscale convective type dust episodes known as haboobs. The socio-economic impacts of the dust events have been assessed by estimating the horizontal visibility, air quality index (AQI), and the dust deposition flux (DDF) from the forecasted dust concentrations. During the extreme dust events, the horizontal visibility drops to near-zero values co-occurred withhazardous levels of AQI and extremely high dust deposition flux (250 μg cm- 2 day- 1).

  17. Hindcasting of storm waves using neural networks

    Digital Repository Service at National Institute of Oceanography (India)

    Rao, S.; Mandal, S.

    Department NN neural network net i weighted sum of the inputs of neuron i o k network output at kth output node P total number of training pattern s i output of neuron i t k target output at kth output node 1. Introduction Severe storms occur in Bay of Bengal...), forecasting of runoff (Crespo and Mora, 1993), concrete strength (Kasperkiewicz et al., 1995). The uses of neural network in the coastal the wave conditions will change from year to year, thus a proper statistical and climatological treatment requires several...

  18. Forecasting the 12-14 March 1993 superstorm

    Energy Technology Data Exchange (ETDEWEB)

    Uccellini, L.W.; Kocin, P.J.; Schneider, R.S.; Stokols, P.M.; Dorr, R.A. [National Weather Service, Camp Springs, MD (United States)]|[National Weather Service, Bohemia, NY (United States)

    1995-02-01

    This paper describes the decision-making process used by the forecasters in the National Meteorological Center`s (NMC`s) Meterolological Operations Division and in Weather Forecast Offices of the National Weather Service to provide the successful forecasts of the superstorm of 12-14 March 1993. This review illustrates (1) the difficult decisions forecasters faced when using sometimes conflicting model guidance, (2) the forecasters` success in recognizing the mesoscale aspects of the storm as it began to develop and move along the Gulf and East Coasts of the United States, and (3) their ability to produce one of the most successful heavy snow and blizzard forecasts ever for a major winter storm that affected the eastern third of the United States. The successful aspects of the forecasts include the following. (1) Cyclogenesis was predicted up to 5 days prior to its onset. (2) The unusual intensity of the storm was predicted three days in advance, allowing forecasters, government officials, and the media ample time to prepare the public, marine, and aviation interests to take precautions for the protection of life and property. (3) The excessive amounts and areal distribution of snowfall were prediceted two days in advance of its onset. (4) An extensive number of blizzard watches and warnings were issued throughout the eastern United States with unprecedented lead times. (5) The coordination of forecasts within the National Weather Service and between the National Weather Service, private forecasters, and media meteorologists was perhaps the most extensive in recent history.

  19. EMC: Air Quality Forecast Home page

    Science.gov (United States)

    Modeling with NCEP NMMB ( Z. Janjic) ECMWF GEMS Project WMO Sand and Dust Storm Warning and Advisory System Air Quality Forecast Links U.S. AQ Forecast Products Canadian AQ Forecastsp Navy Aerosol Prediction

  20. Forecasting the space weather impact

    DEFF Research Database (Denmark)

    Crosby, N. B.; Veronig, A.; Robbrecht, E.

    2012-01-01

    The FP7 COronal Mass Ejections and Solar Energetic Particles (COMESEP) project is developing tools for forecasting geomagnetic storms and solar energetic particle (SEP) radiation storms. By analysis of historical data, complemented by the extensive data coverage of solar cycle 23, the key ingredi...

  1. High-Resolution WRF Forecasts of Lightning Threat

    Science.gov (United States)

    Goodman, S. J.; McCaul, E. W., Jr.; LaCasse, K.

    2007-01-01

    Tropical Rainfall Measuring Mission (TRMM)lightning and precipitation observations have confirmed the existence of a robust relationship between lightning flash rates and the amount of large precipitating ice hydrometeors in storms. This relationship is exploited, in conjunction with the capabilities of the Weather Research and Forecast (WRF) model, to forecast the threat of lightning from convective storms using the output fields from the model forecasts. The simulated vertical flux of graupel at -15C is used in this study as a proxy for charge separation processes and their associated lightning risk. Initial experiments using 6-h simulations are conducted for a number of case studies for which three-dimensional lightning validation data from the North Alabama Lightning Mapping Array are available. The WRF has been initialized on a 2 km grid using Eta boundary conditions, Doppler radar radial velocity and reflectivity fields, and METAR and ACARS data. An array of subjective and objective statistical metrics is employed to document the utility of the WRF forecasts. The simulation results are also compared to other more traditional means of forecasting convective storms, such as those based on inspection of the convective available potential energy field.

  2. Simulating Storm Surge Impacts with a Coupled Atmosphere-Inundation Model with Varying Meteorological Forcing

    Directory of Open Access Journals (Sweden)

    Alexandra N. Ramos Valle

    2018-04-01

    Full Text Available Storm surge events have the potential to cause devastating damage to coastal communities. The magnitude of their impacts highlights the need for increased accuracy and real-time forecasting and predictability of storm surge. In this study, we assess two meteorological forcing configurations to hindcast the storm surge of Hurricane Sandy, and ultimately support the improvement of storm surge forecasts. The Weather Research and Forecasting (WRF model is coupled to the ADvanced CIRCulation Model (ADCIRC to determine water elevations. We perform four coupled simulations and compare storm surge estimates resulting from the use of a parametric vortex model and a full-physics atmospheric model. One simulation is forced with track-based meteorological data calculated from WRF, while three simulations are forced with the full wind and pressure field outputs from WRF simulations of varying resolutions. Experiments were compared to an ADCIRC simulation forced by National Hurricane Center best track data, as well as to station observations. Our results indicated that given accurate meteorological best track data, a parametric vortex model can accurately forecast maximum water elevations, improving upon the use of a full-physics coupled atmospheric-surge model. In the absence of a best track, atmospheric forcing in the form of full wind and pressure field from a high-resolution atmospheric model simulation prove reliable for storm surge forecasting.

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

    Science.gov (United States)

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

    2017-12-01

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

  4. Progress toward developing a practical societal response to severe convection (2005 EGU Sergei Soloviev Medal Lecture

    Directory of Open Access Journals (Sweden)

    C. A. Doswell III

    2005-01-01

    Full Text Available A review of severe convection in the context of geophysical hazards is given. Societal responses to geophysical hazards depend, in part, on the ability to forecast the events and the degree of certainty with which forecasts can be made. In particular, the spatio-temporal specificity and lead time of those forecasts are critical issues. However, societal responses to geophysical hazards are not only dependent on forecasting. Even perfect forecasts might not be sufficient for a meaningful societal response without the development of considerable infrastructure to allow a society to respond properly and in time to mitigate the hazard. Geophysical hazards of extreme magnitude are rare events, a fact that tends to make funding support for appropriate preparations difficult to obtain. Focusing on tornadoes as a prototypical hazard from severe convective storms, the infrastructure for dealing with them in the USA is reviewed. Worldwide implications of the experience with severe convective storms in the USA are discussed, with an emphasis on its relevance to the situation in Europe.

  5. A Photo Storm Report Mobile Application, Processing/Distribution System, and AWIPS-II Display Concept

    Science.gov (United States)

    Longmore, S. P.; Bikos, D.; Szoke, E.; Miller, S. D.; Brummer, R.; Lindsey, D. T.; Hillger, D.

    2014-12-01

    The increasing use of mobile phones equipped with digital cameras and the ability to post images and information to the Internet in real-time has significantly improved the ability to report events almost instantaneously. In the context of severe weather reports, a representative digital image conveys significantly more information than a simple text or phone relayed report to a weather forecaster issuing severe weather warnings. It also allows the forecaster to reasonably discern the validity and quality of a storm report. Posting geo-located, time stamped storm report photographs utilizing a mobile phone application to NWS social media weather forecast office pages has generated recent positive feedback from forecasters. Building upon this feedback, this discussion advances the concept, development, and implementation of a formalized Photo Storm Report (PSR) mobile application, processing and distribution system and Advanced Weather Interactive Processing System II (AWIPS-II) plug-in display software.The PSR system would be composed of three core components: i) a mobile phone application, ii) a processing and distribution software and hardware system, and iii) AWIPS-II data, exchange and visualization plug-in software. i) The mobile phone application would allow web-registered users to send geo-location, view direction, and time stamped PSRs along with severe weather type and comments to the processing and distribution servers. ii) The servers would receive PSRs, convert images and information to NWS network bandwidth manageable sizes in an AWIPS-II data format, distribute them on the NWS data communications network, and archive the original PSRs for possible future research datasets. iii) The AWIPS-II data and exchange plug-ins would archive PSRs, and the visualization plug-in would display PSR locations, times and directions by hour, similar to surface observations. Hovering on individual PSRs would reveal photo thumbnails and clicking on them would display the

  6. Short-Term fo F2 Forecast: Present Day State of Art

    Science.gov (United States)

    Mikhailov, A. V.; Depuev, V. H.; Depueva, A. H.

    An analysis of the F2-layer short-term forecast problem has been done. Both objective and methodological problems prevent us from a deliberate F2-layer forecast issuing at present. An empirical approach based on statistical methods may be recommended for practical use. A forecast method based on a new aeronomic index (a proxy) AI has been proposed and tested over selected 64 severe storm events. The method provides an acceptable prediction accuracy both for strongly disturbed and quiet conditions. The problems with the prediction of the F2-layer quiet-time disturbances as well as some other unsolved problems are discussed

  7. Hurricane feedback research may improve intensity forecasts

    Science.gov (United States)

    Schultz, Colin

    2012-06-01

    Forecasts of a hurricane's intensity are generally much less accurate than forecasts of its most likely path. Large-scale atmospheric patterns dictate where a hurricane will go and how quickly it will get there. The storm's intensity, however, depends on small-scale shifts in atmospheric stratification, upwelling rates, and other transient dynamics that are difficult to predict. Properly understanding the risk posed by an impending storm depends on having a firm grasp of all three properties: translational speed, intensity, and path. Drawing on 40 years of hurricane records representing 3090 different storms, Mei et al. propose that a hurricane's translational speed and intensity may be closely linked.

  8. Responses of two genetically superior loblolly pine clonal ideotypes to a severe ice storm

    Science.gov (United States)

    Lauren S. Pile; Christopher A. Maier; G. Geoff Wang; Dapao Yu; Tim M. Shearman

    2016-01-01

    An increase in the frequency and magnitude of extreme weather events, such as major ice storms, can have severe impacts on southern forests. We investigated the damage inflicted by a severe ice storm that occurred in February 2014 on two loblolly pine (Pinus taeda L.) ideotypes in Cross, South Carolina located in the southeastern coastal plain. The ‘‘narrow crown”...

  9. Design and skill assessment of an Operational Forecasting System for currents and sea level variability to the Santos Estuarine System - Brazil

    Science.gov (United States)

    Godoi Rezende Costa, C.; Castro, B. M.; Blumberg, A. F.; Leite, J. R. B., Sr.

    2017-12-01

    Santos City is subject to an average of 12 storm tide events per year. Such events bring coastal flooding able to threat human life and damage coastal infrastructure. Severe events have forced the interruption of ferry boat services and ship traffic through Santos Harbor, causing great impacts to Santos Port, the largest in South America, activities. Several studies have focused on the hydrodynamics of storm tide events but only a few of those studies have pursued an operational initiative to predict short term (operational forecasting system built to predict sea surface elevation and currents in the Santos Estuarine System and (ii) to evaluate model performance in simulating observed sea surface elevation. The Santos Operational Forecasting System (SOFS) hydrodynamic module is based on the Stevens Institute Estuarine and Coastal Ocean Model (sECOM). The fully automated SOFS is designed to provide up to 71 h forecast of sea surface elevations and currents every day. The system automatically collects results from global models to run the SOFS nested into another sECOM based model for the South Brazil Bight (SBB). Global forecasting results used to force both models come from Mercator Ocean, released by Copernicus Marine Service, and from the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) stablished by the Center for Weather Forecasts and Climate Studies (with Portuguese acronym CPTEC). The complete routines task take about 8 hours of run time to finish. SOFS was able to hindcast a severe storm tide event that took place in Santos on August 21-22, 2016. Comparisons with observed sea level provided skills of 0.92 and maximum root mean square errors of 25 cm. The good agreement with observed data shows the potential of the designed system to predict storm tides and to support both human and assets protection.

  10. Radar observations of a tornado-spawning storm complex in Southeast Brazil and Meso-Eta forecasts of this extreme event

    Science.gov (United States)

    Held, Gerhard; Gomes, Jorge Luis; Gomes, Ana Maria

    2014-05-01

    During the early afternoon of 22 September 2013, severe storms, accompanied by large hail, damaging winds, heavy precipitation and intense lightning activity, devastated a region in the southeast State of São Paulo. Several extremely intense storm cells moved at up to 80 km/h east-southeastwards, ahead of a strong cold front approaching through Paraná, which created extremely unstable conditions that led to deep convection and overshooting towers up to 18 km. At least one of theses cells spawned a tornado when it reached the town of Taquarituba. The tornado traversed the town from south-southwest to north-northeast and was responsible for 63 people injured and two fatalities. Based on the damage reported, it was at least an F3 according to the Fujita scale. The objective of the present study is to characterize this severe thunderstorm event, using different types of data, and to evaluate the forecasts provided by the Meso-Eta model centered over Bauru. The pre-frontal and frontal convective cells were tracked throughout their life-time by IPMet's Doppler radars, which cover the western and central regions of the State São Paulo, as well as northern Paraná State. Radar volume scans, generated every 7,5 min, were processed with the TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting) Software, yielding the following preliminary results: as the storm complex traversed the Paranapanema River, which forms the border between the two states, the cells intensified drastically and shortly before reaching the town of Taquarituba, that particular cell displayed extremely strong radial shear just above the cloud base (about -20 to +35 m/s), which led to the formation of a deep meso-cyclone, from which the tornado spawned and touched down at around 14:30 LT (LT=UT-3h). Cell properties calculated by TITAN showed a drastic increase of VIL (Vertically Integrated Liquid water content) from 13:52 LT (7,9 kg/m2) to a maximum of 61,8 kg/m2 at 14:15 LT. From 14

  11. HURRICANE AND SEVERE STORM SENTINEL (HS3) FLIGHT REPORTS V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The Hurricane and Severe Storm Sentinel (HS3) Flight Reports provide information about flights flown by the WB-57 and Global Hawk aircrafts during the Hurricane and...

  12. Winter in the Ouachitas--a severe winter storm signature in Pinus echinata in the Ouachita Mountains of Oklahoma and Arkansas, USA

    Science.gov (United States)

    Douglas J. Stevenson; Thomas B. Lynch; Pradip Saud; Robert Heineman; Randal Holeman; Dennis Wilson; Keith Anderson; Chris Cerny; James M. Guldin

    2016-01-01

    Each year severe winter storms (≈ice storms) damage trees throughout the southern USA. Arkansas and Oklahoma have a history of severe winter storms. To extend that history back beyond the reach of written records, a distinctive tree ring pattern or signature is needed. Storm-caused breakage, branch loss and bending stress provide that signature. We found a severe storm...

  13. Polarimetric signatures indicative of severe storm development - the Pentecost event 2014

    Science.gov (United States)

    Troemel, Silke; Diederich, Malte; Evaristo, Raquel; Ryzhkov, Alexander; Simmer, Clemens

    2015-04-01

    The 2014 Pentecost weekend storms in Europe were a series of severe supercell storms which followed a heatwave in early June 2014, resulting from a Spanish plume synoptic weather pattern. Outbreaks of severe weather were reported from these storm developments with the worst damages occurring over the German state of North Rhine-Westphalia on 9 June, where the storm was described as one of the most violent in decades by the German weather service (DWD). During this event six fatalities, wind gusts up to 150km/h, hail and a flash flood in Düsseldorf has been reported. Monitoring and analysis of high-impact weather using weather radars of shorter wavelength (X- and C-bands) requires special methods, i.e. anomalous high attenuation and differential attenuation due to very large raindrops originating from melting large hail has to be investigated and corrected. During the Pentecost event a record breaking ZDR bias of up to -25dB has been observed. Different strategies for reliable attenuation correction and rainfall estimation for this extreme event are explored and will be presented. A national 3D composite of polarimetric moments covering Germany with 1km horizontal, 250m vertical, and 5 minutes temporal resolution has been generated. 10 C-band radars from the DWD radar network, recently upgraded to polarimetry, have been included. Meanie3D, a 3D scale space tracking algorithm, is applied to the composite to investigate the magnitudes and temporal development of the 3 fundamental steps of a storms lifecycle: 1) high values of differential reflectivity ZDR aloft first indicate a developing cell, 2) ZDR-columns (these are vertical columns of high differential reflectivity) then indicate the updraft zone of a cell in the mature state. The vertical extent of the ZDR-column is thus a measure of the strength of the updraft and for the ensuing rainfall enhancement. 3) The very first big drops reach the surface before the most intense rain begins. This is reflected by the

  14. Dust storm events over Delhi: verification of dust AOD forecasts with satellite and surface observations

    Science.gov (United States)

    Singh, Aditi; Iyengar, Gopal R.; George, John P.

    2016-05-01

    Thar desert located in northwest part of India is considered as one of the major dust source. Dust storms originate in Thar desert during pre-monsoon season, affects large part of Indo-Gangetic plains. High dust loading causes the deterioration of the ambient air quality and degradation in visibility. Present study focuses on the identification of dust events and verification of the forecast of dust events over Delhi and western part of IG Plains, during the pre-monsoon season of 2015. Three dust events have been identified over Delhi during the study period. For all the selected days, Terra-MODIS AOD at 550 nm are found close to 1.0, while AURA-OMI AI shows high values. Dust AOD forecasts from NCMRWF Unified Model (NCUM) for the three selected dust events are verified against satellite (MODIS) and ground based observations (AERONET). Comparison of observed AODs at 550 nm from MODIS with NCUM predicted AODs reveals that NCUM is able to predict the spatial and temporal distribution of dust AOD, in these cases. Good correlation (~0.67) is obtained between the NCUM predicted dust AODs and location specific observations available from AERONET. Model under-predicted the AODs as compared to the AERONET observations. This may be mainly because the model account for only dust and no anthropogenic activities are considered. The results of the present study emphasize the requirement of more realistic representation of local dust emission in the model both of natural and anthropogenic origin, to improve the forecast of dust from NCUM during the dust events.

  15. Severe Autumn storms in future Western Europe with a warmer Atlantic Ocean

    Science.gov (United States)

    Baatsen, Michiel; Haarsma, Reindert J.; Van Delden, Aarnout J.; de Vries, Hylke

    2015-08-01

    Simulations with a very high resolution (~25 km) global climate model indicate that more severe Autumn storms will impact Europe in a warmer future climate. The observed increase is mainly attributed to storms with a tropical origin, especially in the later part of the twentyfirst century. As their genesis region expands, tropical cyclones become more intense and their chances of reaching Europe increase. This paper investigates the properties and evolution of such storms and clarifies the future changes. The studied tropical cyclones feature a typical evolution of tropical development, extratropical transition and a re-intensification. A reduction of the transit area between regions of tropical and extratropical cyclogenesis increases the probability of re-intensification. Many of the modelled storms exhibit hybrid properties in a considerable part of their life cycle during which they exhibit the hazards of both tropical and extratropical systems. In addition to tropical cyclones, other systems such as cold core extratropical storms mainly originating over the Gulf Stream region also increasingly impact Western Europe. Despite their different history, all of the studied storms have one striking similarity: they form a warm seclusion. The structure, intensity and frequency of storms in the present climate are compared to observations using the MERRA and IBTrACS datasets. Damaging winds associated with the occurrence of a sting jet are observed in a large fraction of the cyclones during their final stage. Baroclinic instability is of great importance for the (re-)intensification of the storms. Furthermore, so-called atmospheric rivers providing tropical air prove to be vital for the intensification through diabatic heating and will increase considerably in strength in the future, as will the associated flooding risks.

  16. Verification of Space Weather Forecasts using Terrestrial Weather Approaches

    Science.gov (United States)

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

    2015-12-01

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

  17. Building Adjustable Pre-storm Reservoir Flood-control Release Rules

    Science.gov (United States)

    Yang, Shun-Nien; Chang, Li-Chiu; Chang, Fi-John; Hsieh, Cheng-Daw

    2017-04-01

    Typhoons hit Taiwan several times every year, which could cause serious flood disasters. Because mountainous terrains and steep landforms can rapidly accelerate the speed of flood flow during typhoon events, rivers cannot be a stable source of water supply. Reservoirs become the most effective floodwater storage facilities for alleviating flood damages in Taiwan. The pre-storm flood-control release can significantly increase reservoir storage capacity available to store floodwaters for reducing downstream flood damage, while the uncertainties of total forecasted rainfalls are very high in different stages of an oncoming typhoon, which may cause the risk of water shortage in the future. This study proposes adjustable pre-storm reservoir flood-control release rules in three designed operating stages with various hydrological conditions in the Feitsui Reservoir, a pivot reservoir for water supply to Taipei metropolitan in Taiwan, not only to reduce the risk of reservoir flood control and downstream flooding but also to consider water supply. The three operating stages before an oncoming typhoon are defined upon the timings when: (1) typhoon news is issued (3-7days before typhoon hit); (2) the sea warning is issued (2-4 days before typhoon hit); and (3) the land warning is issued (1-2 days before typhoon hit). We simulate 95 historical typhoon events with 3000 initial water levels and build some pre-storm flood-control release rules to adjust the amount of pre-release based on the total forecasted rainfalls at different operating stages. A great number of simulations (68.4 millions) are conducted to extract their major consequences and then build the adjustable pre-storm reservoir flood-control release rules. Accordingly, given a total forecasted rainfall and a water level, reservoir decision makers can easily identify the corresponding rule to tell the amount of pre-release in any stage. The results show that the proposed adjustable pre-release rules can effectively

  18. Storms

    International Nuclear Information System (INIS)

    Kai, Keizo; Melrose, D.B.; Suzuki, S.

    1985-01-01

    At metre and decametre wavelengths long-lasting solar radio emission, consisting of thousands of short-lived spikes superimposed on a slowly varying continuum, is observed. This type of storm emission may continue for periods ranging from a few hours to several days; the long duration is one of the characteristics which distinguish storms from other types of solar radio emission. These events are called storms or noise storms by analogy with geomagnetic storms. (author)

  19. Aircraft route forecasting under adverse weather conditions

    Directory of Open Access Journals (Sweden)

    Thomas Hauf

    2017-04-01

    Full Text Available In this paper storm nowcasts in the terminal manoeuvring area (TMA of Hong Kong International Airport are used to forecast deviation routes through a field of storms for arriving and departing aircraft. Storms were observed and nowcast by the nowcast system SWIRLS from the Hong Kong Observatory. Storms were considered as no-go zones for aircraft and deviation routes were determined with the DIVSIM software package. Two days (21 and 22 May 2011 with 22 actual flown routes were investigated. Flights were simulated with a nowcast issued at the time an aircraft entered the TMA or departed from the airport. These flights were compared with a posteriori simulations, in which all storm fields were known and circumnavigated. Both types of simulated routes were then compared with the actual flown routes. The qualitative comparison of the various routes revealed generally good agreement. Larger differences were found in more complex situations with many active storms in the TMA. Route differences resulted primarily from air traffic control measures imposed such as holdings, slow-downs and shortcuts, causing the largest differences between the estimated and actual landing time. Route differences could be enhanced as aircraft might be forced to circumnavigate a storm ahead in a different sense. The use of route forecasts to assist controllers coordinating flights in a complex moving storm field is discussed. The study emphasises the important application of storm nowcasts in aviation meteorology.

  20. Severe ionosphere disturbances caused by the sudden response of evening subequatorial ionospheres to geomagnetic storms

    International Nuclear Information System (INIS)

    Tanaka, T.

    1981-01-01

    By monitoring C band beacon signals from geostationary satellites in Japan, we have observed anomalously strong ionospheric scintillations several times during three years from 1978 to 1980. These severe scinitillations occur associated with geomagnetic storms and accompany sudden and intense ionospheric perturbations in the low-latiude region. Through the analysis of these phenomena we have identified a new type of ionospheric disturbances characterized by intensifications of equatorial anomalies and successive severe ionospheric scintillations that extend to the C band range. The events occur only during a limited local time interval after the sunset, when storm time decreases of midlatitude geomagnetic fields in the same meridan take place during the same time interval. From the viewpoint of ionospheric storms, these disturbances precede the occurrence of midlatitude negative phases and storm time depressions of equatorial anomalies to indicate that the cause of the events is different from distrubed thermospheric circulations. The timing and magnitude of substorms at high-latitudes not always correlate with the events. We have concluded that the phenomena are closely related with penetrations toward low-latitudes of electric fields owing to the partial closure of asymmetrical ring currents

  1. Numerical simulation of the effects of cooling tower complexes on clouds and severe storms. Final report, September 1976-June 1979

    International Nuclear Information System (INIS)

    Orville, H.D.; Eckhoff, P.A.; Peak, J.E.; Hirsch, J.H.; Kopp, F.J.

    1979-11-01

    A two-dimensional, time-dependent model was developed which gives realistic simulations of many severe storm processes - such as heavy rains, hail, and strong winds. The model is a set of partial differential equations describing time changes of momentum, energy, and mass (air and various water substances such as water vapor, cloud liquid, cloud ice, rainwater, and hail). In addition, appropriate boundary And initial conditions (taken from weather sounding data) are imposed on a domain approximately 20 km high by 20 km wide with 200 m grid intervals to complete the model. Modifications were made to the model which allow additional water vapor and heat to be added at several lower grid points, simulating effluents from a power park. Cases were run which depict realistic severe storm situations. One atmospheric sounding has a strong middle-level inversion which tends to inhibit the first convective clouds but gives rise later to a severe storm with hail and heavy rains. One other sounding is taken from a day in which a severe storm occurred in the Miami area. A third sounding depicts atmospheric conditions in which severe storms formed in the vicinity of Huron, South Dakota. The results indicate that a power park emitting 80% latent heat and 20% sensible heat has little effect on the simulated storm. A case with 100% sensible heat emission leads to a much different solution, with the simulated storm reduced in severity and the rain and hail redistributed. A case in which water vapor is accumulated in a region and released over a broad depth results in sightly more rain from a severe storm

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

    Science.gov (United States)

    Hyde, Peter; Mahalov, Alex; Li, Jialun

    2018-03-01

    Nine dust storms in south-central Arizona were simulated with the Weather Research and Forecasting with Chemistry model (WRF-Chem) at 2 km resolution. The windblown dust emission algorithm was the Air Force Weather Agency model. In comparison with ground-based PM 10 observations, the model unevenly reproduces the dust-storm events. The model adequately estimates the location and timing of the events, but it is unable to precisely replicate the magnitude and timing of the elevated hourly concentrations of particles 10 µm and smaller ([PM 10 ]).Furthermore, the model underestimated [PM 10 ] in highly agricultural Pinal County because it underestimated surface wind speeds and because the model's erodible fractions of the land surface data were too coarse to effectively resolve the active and abandoned agricultural lands. In contrast, the model overestimated [PM 10 ] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) for which the surface-layer speeds were too strong. In Phoenix, AZ, the model's performance depended on the event, with both under- and overestimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM 10 ] highly relies on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM 10 ] in that region. Both 24-hr and 1-hr measured [PM 10 ] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as 10-fold and the latter exceeding health-based guidelines by as much as 70-fold. Monsoonal thunderstorms not only produce elevated [PM 10 ], but also cause urban flash floods and disrupt water resource deliveries. Given the severity and frequency of these dust storms, and conceding that the modeling system applied in this work did not produce the desired agreement between simulations and

  3. Moisture convergence using satellite-derived wind fields - A severe local storm case study

    Science.gov (United States)

    Negri, A. J.; Vonder Haar, T. H.

    1980-01-01

    Five-minute interval 1-km resolution SMS visible channel data were used to derive low-level wind fields by tracking small cumulus clouds on NASA's Atmospheric and Oceanographic Information Processing System. The satellite-derived wind fields were combined with surface mixing ratios to derive horizontal moisture convergence in the prestorm environment of April 24, 1975. Storms began developing in an area extending from southwest Oklahoma to eastern Tennessee 2 h subsequent to the time of the derived fields. The maximum moisture convergence was computed to be 0.0022 g/kg per sec and areas of low-level convergence of moisture were in general indicative of regions of severe storm genesis. The resultant moisture convergence fields derived from two wind sets 20 min apart were spatially consistent and reflected the mesoscale forcing of ensuing storm development. Results are discussed with regard to possible limitations in quantifying the relationship between low-level flow and between low-level flow and satellite-derived cumulus motion in an antecedent storm environment.

  4. Predicting Tropical Cyclogenesis with a Global Mesoscale Model: Preliminary Results with Very Severe Cyclonic Storm Nargis (2008)

    Science.gov (United States)

    Shen, B.; Tao, W.; Atlas, R.

    2008-12-01

    Very Severe Cyclonic Storm Nargis, the deadliest named tropical cyclone (TC) in the North Indian Ocean Basin, devastated Burma (Myanmar) in May 2008, causing tremendous damage and numerous fatalities. An increased lead time in the prediction of TC Nargis would have increased the warning time and may therefore have saved lives and reduced economic damage. Recent advances in high-resolution global models and supercomputers have shown the potential for improving TC track and intensity forecasts, presumably by improving multi-scale simulations. The key but challenging questions to be answered include: (1) if and how realistic, in terms of timing, location and TC general structure, the global mesoscale model (GMM) can simulate TC genesis and (2) under what conditions can the model extend the lead time of TC genesis forecasts. In this study, we focus on genesis prediction for TCs in the Indian Ocean with the GMM. Preliminary real-data simulations show that the initial formation and intensity variations of TC Nargis can be realistically predicted at a lead time of up to 5 days. These simulations also suggest that the accurate representations of a westerly wind burst (WWB) and an equatorial trough, associated with monsoon circulations and/or a Madden-Julian Oscillation (MJO), are important for predicting the formation of this kind of TC. In addition to the WWB and equatorial trough, other favorable environmental conditions will be examined, which include enhanced monsoonal circulation, upper-level outflow, low- and middle-level moistening, and surface fluxes.

  5. Detection of severe storm signatures in loblolly pine using seven-year periodic standardized averages and standard deviations

    Science.gov (United States)

    Stevenson Douglas; Thomas Hennessey; Thomas Lynch; Giulia Caterina; Rodolfo Mota; Robert Heineman; Randal Holeman; Dennis Wilson; Keith Anderson

    2016-01-01

    A loblolly pine plantation near Eagletown, Oklahoma was used to test standardized tree ring widths in detecting snow and ice storms. Widths of two rings immediately following suspected storms were standardized against widths of seven rings following the storm (Stan1 and Stan2). Values of Stan1 less than -0.900 predict a severe (usually ice) storm when Stan 2 is less...

  6. iFLOOD: A Real Time Flood Forecast System for Total Water Modeling in the National Capital Region

    Science.gov (United States)

    Sumi, S. J.; Ferreira, C.

    2017-12-01

    Extreme flood events are the costliest natural hazards impacting the US and frequently cause extensive damages to infrastructure, disruption to economy and loss of lives. In 2016, Hurricane Matthew brought severe damage to South Carolina and demonstrated the importance of accurate flood hazard predictions that requires the integration of riverine and coastal model forecasts for total water prediction in coastal and tidal areas. The National Weather Service (NWS) and the National Ocean Service (NOS) provide flood forecasts for almost the entire US, still there are service-gap areas in tidal regions where no official flood forecast is available. The National capital region is vulnerable to multi-flood hazards including high flows from annual inland precipitation events and surge driven coastal inundation along the tidal Potomac River. Predicting flood levels on such tidal areas in river-estuarine zone is extremely challenging. The main objective of this study is to develop the next generation of flood forecast systems capable of providing accurate and timely information to support emergency management and response in areas impacted by multi-flood hazards. This forecast system is capable of simulating flood levels in the Potomac and Anacostia River incorporating the effects of riverine flooding from the upstream basins, urban storm water and tidal oscillations from the Chesapeake Bay. Flood forecast models developed so far have been using riverine data to simulate water levels for Potomac River. Therefore, the idea is to use forecasted storm surge data from a coastal model as boundary condition of this system. Final output of this validated model will capture the water behavior in river-estuary transition zone far better than the one with riverine data only. The challenge for this iFLOOD forecast system is to understand the complex dynamics of multi-flood hazards caused by storm surges, riverine flow, tidal oscillation and urban storm water. Automated system

  7. On the use of wave parameterizations and a storm impact scaling model in National Weather Service Coastal Flood and decision support operations

    Science.gov (United States)

    Mignone, Anthony; Stockdon, H.; Willis, M.; Cannon, J.W.; Thompson, R.

    2012-01-01

    National Weather Service (NWS) Weather Forecast Offices (WFO) are responsible for issuing coastal flood watches, warnings, advisories, and local statements to alert decision makers and the general public when rising water levels may lead to coastal impacts such as inundation, erosion, and wave battery. Both extratropical and tropical cyclones can generate the prerequisite rise in water level to set the stage for a coastal impact event. Forecasters use a variety of tools including computer model guidance and local studies to help predict the potential severity of coastal flooding. However, a key missing component has been the incorporation of the effects of waves in the prediction of total water level and the associated coastal impacts. Several recent studies have demonstrated the importance of incorporating wave action into the NWS coastal flood program. To follow up on these studies, this paper looks at the potential of applying recently developed empirical parameterizations of wave setup, swash, and runup to the NWS forecast process. Additionally, the wave parameterizations are incorporated into a storm impact scaling model that compares extreme water levels to beach elevation data to determine the mode of coastal change at predetermined “hotspots” of interest. Specifically, the storm impact model compares the approximate storm-induced still water level, which includes contributions from tides, storm surge, and wave setup, to dune crest elevation to determine inundation potential. The model also compares the combined effects of tides, storm surge, and the 2 % exceedance level for vertical wave runup (including both wave setup and swash) to dune toe and crest elevations to determine if erosion and/or ocean overwash may occur. The wave parameterizations and storm impact model are applied to two cases in 2009 that led to significant coastal impacts and unique forecast challenges in North Carolina: the extratropical “Nor'Ida” event during 11-14 November and

  8. An assessment of the ECMWF tropical cyclone ensemble forecasting system and its use for insurance loss predictions

    Science.gov (United States)

    Aemisegger, F.; Martius, O.; Wüest, M.

    2010-09-01

    Tropical cyclones (TC) are amongst the most impressive and destructive weather systems of Earth's atmosphere. The costs related to such intense natural disasters have been rising in recent years and may potentially continue to increase in the near future due to changes in magnitude, timing, duration or location of tropical storms. This is a challenging situation for numerical weather prediction, which should provide a decision basis for short term protective measures through high quality medium range forecasts on the one hand. On the other hand, the insurance system bears great responsibility in elaborating proactive plans in order to face these extreme events that individuals cannot manage independently. Real-time prediction and early warning systems are needed in the insurance sector in order to face an imminent hazard and minimise losses. Early loss estimates are important in order to allocate capital and to communicate to investors. The ECMWF TC identification algorithm delivers information on the track and intensity of storms based on the ensemble forecasting system. This provides a physically based framework to assess the uncertainty in the forecast of a specific event. The performance of the ECMWF TC ensemble forecasts is evaluated in terms of cyclone intensity and location in this study and the value of such a physically-based quantification of uncertainty in the meteorological forecast for the estimation of insurance losses is assessed. An evaluation of track and intensity forecasts of hurricanes in the North Atlantic during the years 2005 to 2009 is carried out. Various effects are studied like the differences in forecasts over land or sea, as well as links between storm intensity and forecast error statistics. The value of the ECMWF TC forecasting system for the global re-insurer Swiss Re was assessed by performing insurance loss predictions using their in-house loss model for several case studies of particularly devastating events. The generally known

  9. Recent and Upcoming Changes to NOAA Marine Forecasts

    Science.gov (United States)

    of Tropical-Storm-Force Winds Graphics become operational on or around May 15, 2018 WFOs to be New Extratropical Surge and Tide Operational Forecast System for Micronesia Effective February 13 of High Seas and Storm Warning over NIST Time Frequency Broadcasts through January 20, 2018 NWS

  10. Can High-resolution WRF Simulations Be Used for Short-term Forecasting of Lightning?

    Science.gov (United States)

    Goodman, S. J.; Lapenta, W.; McCaul, E. W., Jr.; LaCasse, K.; Petersen, W.

    2006-01-01

    A number of research teams have begun to make quasi-operational forecast simulations at high resolution with models such as the Weather Research and Forecast (WRF) model. These model runs have used horizontal meshes of 2-4 km grid spacing, and thus resolved convective storms explicitly. In the light of recent global satellite-based observational studies that reveal robust relationships between total lightning flash rates and integrated amounts of precipitation-size ice hydrometeors in storms, it is natural to inquire about the capabilities of these convection-resolving models in representing the ice hydrometeor fields faithfully. If they do, this might make operational short-term forecasts of lightning activity feasible. We examine high-resolution WRF simulations from several Southeastern cases for which either NLDN or LMA lightning data were available. All the WRF runs use a standard microphysics package that depicts only three ice species, cloud ice, snow and graupel. The realism of the WRF simulations is examined by comparisons with both lightning and radar observations and with additional even higher-resolution cloud-resolving model runs. Preliminary findings are encouraging in that they suggest that WRF often makes convective storms of the proper size in approximately the right location, but they also indicate that higher resolution and better hydrometeor microphysics would be helpful in improving the realism of the updraft strengths, reflectivity and ice hydrometeor fields.

  11. Use of High-Resolution WRF Simulations to Forecast Lightning Threat

    Science.gov (United States)

    McCaul, E. W., Jr.; LaCasse, K.; Goodman, S. J.; Cecil, D. J.

    2008-01-01

    Recent observational studies have confirmed the existence of a robust statistical relationship between lightning flash rates and the amount of large precipitating ice hydrometeors aloft in storms. This relationship is exploited, in conjunction with the capabilities of cloud-resolving forecast models such as WRF, to forecast explicitly the threat of lightning from convective storms using selected output fields from the model forecasts. The simulated vertical flux of graupel at -15C and the shape of the simulated reflectivity profile are tested in this study as proxies for charge separation processes and their associated lightning risk. Our lightning forecast method differs from others in that it is entirely based on high-resolution simulation output, without reliance on any climatological data. short [6-8 h) simulations are conducted for a number of case studies for which three-dmmensional lightning validation data from the North Alabama Lightning Mapping Array are available. Experiments indicate that initialization of the WRF model on a 2 km grid using Eta boundary conditions, Doppler radar radial velocity fields, and METAR and ACARS data y&eld satisfactory simulations. __nalyses of the lightning threat fields suggests that both the graupel flux and reflectivity profile approaches, when properly calibrated, can yield reasonable lightning threat forecasts, although an ensemble approach is probably desirable in order to reduce the tendency for misplacement of modeled storms to hurt the accuracy of the forecasts. Our lightning threat forecasts are also compared to other more traditional means of forecasting thunderstorms, such as those based on inspection of the convective available potential energy field.

  12. Joint Typhoon Warning Center (JTWC) Storm Wallets

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Joint Typhoon Warning Center (JTWC) is responsible for typhoon forecasts and warnings for the Western Pacific and Indian Ocean basins. After each storm, the JTWC...

  13. Forecasting the Dst index using a swarm-optimized neural network

    Science.gov (United States)

    Lazzús, J. A.; Vega, P.; Rojas, P.; Salfate, I.

    2017-08-01

    A hybrid technique that combines an artificial neural network with a particle swarm optimization (ANN+PSO) was used to forecast the disturbance storm time (Dst) index from 1 to 6 h ahead. Our ANN was optimized by PSO to update ANN weights and to predict the short-term Dst index using past values as input parameters. The database used contains 233,760 hourly data from 1 January 1990 to 31 August 2016, considering storms and quiet period, grouped into three data sets: learning set (with 116,880 hourly data points), validation set (with 58,440 data points), and testing set (with 58,440 data points). Several ANN topologies were studied, and the best architecture was determined by systematically adding neurons and evaluating the root-mean-square error (RMSE) and the correlation coefficient (R) during the training process. These results show that the hybrid algorithm is a powerful technique for forecasting the Dst index a short time in advance like t + 1 to t + 3, with RMSE from 3.5 nT to 7.5 nT, and R from 0.98 to 0.90. However, t + 4 to t + 6 predictions become slightly more uncertain, with RMSE from 8.8 nT to 10.9 nT, and R from 0.86 to 0.79. Additionally, an exhaustive analysis according to geomagnetic storm magnitude was conducted. In general, the results show that our hybrid algorithm can be correctly trained to forecast the Dst index with appropriate precision and that Dst past behavior significantly affects adequate training and predicting capabilities of the implemented ANN.

  14. Natural Disasters under the Form of Severe Storms in Europe: the Cause-Effect Analysis

    Directory of Open Access Journals (Sweden)

    Virginia Câmpeanu

    2009-07-01

    Full Text Available For more than 100 years, from 1900 to 2008, there were almost 400 storms natural disasters in Europe, 40% of which occurred in the 1990s. The international prognoses for the world weather suggest a tendency toward increasing in frequency and intensity of the severe storms as the climate warms. In these circumstances, for a researcher in the field of Environmental Economics, a natural question occurs, on whether people can contribute to reducing the frequency and the magnitude of severe storms that produce disastreous social and economic effects, by acting on their causes. In researching an answer to support the public policies in the field, a cause-effect analysis applied to Europe might make a contribution to the literature in the field. This especially considering the fact that international literature regarding the factors influencing global warming contains certainties in regard to the natural factors of influence, but declared incertitudes or skepticism in regard to anthropogenic ones. Skepticism, and even tension arised during the international negotiations in Copenhagen (December 2009 in regard to the agreement for limiting global warming, with doubts being raised about the methods used by experts of the International Climate Experts Group (GIEC, and thus the results obtained, which served as a basis for the negotiations. The object of critics was in regard to the form, and at times in regard to the content. It was not about contesting the phenomenon of Global warming during the negotiations, but the methods of calculation. The methodology relies on qualitative (type top down and quantitative (type correlations bottom up cause-effect analysis of the storm disasters in Europe. Based on the instruments used, we proposed a dynamic model of association of the evolution of storm disasters in Europe with anthropogenic factors, with 3 variants. Results: The diagram cause-effect (Ishikawa or fishbone diagram and quantitative correlation of sub

  15. Severe Weather Field Experience: An Undergraduate Field Course on Career Enhancement and Severe Convective Storms

    Science.gov (United States)

    Godfrey, Christopher M.; Barrett, Bradford S.; Godfrey, Elaine S.

    2011-01-01

    Undergraduate students acquire a deeper understanding of scientific principles through first-hand experience. To enhance the learning environment for atmospheric science majors, the University of North Carolina at Asheville has developed the severe weather field experience. Participants travel to Tornado Alley in the Great Plains to forecast and…

  16. HURRICANE AND SEVERE STORM SENTINEL (HS3) HURRICANE IMAGING RADIOMETER (HIRAD) V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The Hurricane and Severe Storm Sentinel (HS3) Hurricane Imaging Radiometer (HIRAD) was collected by the Hurricane Imaging Radiometer (HIRAD), which was a multi-band...

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

    Science.gov (United States)

    Walz, Michael; Leckebusch, Gregor C.

    2016-04-01

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

  18. Conceptual design of an airborne laser Doppler velocimeter system for studying wind fields associated with severe local storms

    Science.gov (United States)

    Thomson, J. A. L.; Davies, A. R.; Sulzmann, K. G. P.

    1976-01-01

    An airborne laser Doppler velocimeter was evaluated for diagnostics of the wind field associated with an isolated severe thunderstorm. Two scanning configurations were identified, one a long-range (out to 10-20 km) roughly horizontal plane mode intended to allow probing of the velocity field around the storm at the higher altitudes (4-10 km). The other is a shorter range (out to 1-3 km) mode in which a vertical or horizontal plane is scanned for velocity (and possibly turbulence), and is intended for diagnostics of the lower altitude region below the storm and in the out-flow region. It was concluded that aircraft flight velocities are high enough and severe storm lifetimes are long enough that a single airborne Doppler system, operating at a range of less than about 20 km, can view the storm area from two or more different aspects before the storm characteristics change appreciably.

  19. Severe geomagnetic storms and Forbush decreases: interplanetary relationships reexamined

    Directory of Open Access Journals (Sweden)

    R. P. Kane

    2010-02-01

    Full Text Available Severe storms (Dst and Forbush decreases (FD during cycle 23 showed that maximum negative Dst magnitudes usually occurred almost simultaneously with the maximum negative values of the Bz component of interplanetary magnetic field B, but the maximum magnitudes of negative Dst and Bz were poorly correlated (+0.28. A parameter Bz(CP was calculated (cumulative partial Bz as sum of the hourly negative values of Bz from the time of start to the maximum negative value. The correlation of negative Dst maximum with Bz(CP was higher (+0.59 as compared to that of Dst with Bz alone (+0.28. When the product of Bz with the solar wind speed V (at the hour of negative Bz maximum was considered, the correlation of negative Dst maximum with VBz was +0.59 and with VBz(CP, 0.71. Thus, including V improved the correlations. However, ground-based Dst values have a considerable contribution from magnetopause currents (several tens of nT, even exceeding 100 nT in very severe storms. When their contribution is subtracted from Dst(nT, the residue Dst* representing true ring current effect is much better correlated with Bz and Bz(CP, but not with VBz or VBz(CP, indicating that these are unimportant parameters and the effect of V is seen only through the solar wind ram pressure causing magnetopause currents. Maximum negative Dst (or Dst* did not occur at the same hour as maximum FD. The time evolutions of Dst and FD were very different. The correlations were almost zero. Basically, negative Dst (or Dst* and FDs are uncorrelated, indicating altogether different mechanism.

  20. Coastal and Riverine Flood Forecast Model powered by ADCIRC

    Science.gov (United States)

    Khalid, A.; Ferreira, C.

    2017-12-01

    Coastal flooding is becoming a major threat to increased population in the coastal areas. To protect coastal communities from tropical storms & hurricane damages, early warning systems are being developed. These systems have the capability of real time flood forecasting to identify hazardous coastal areas and aid coastal communities in rescue operations. State of the art hydrodynamic models forced by atmospheric forcing have given modelers the ability to forecast storm surge, water levels and currents. This helps to identify the areas threatened by intense storms. Study on Chesapeake Bay area has gained national importance because of its combined riverine and coastal phenomenon, which leads to greater uncertainty in flood predictions. This study presents an automated flood forecast system developed by following Advanced Circulation (ADCIRC) Surge Guidance System (ASGS) guidelines and tailored to take in riverine and coastal boundary forcing, thus includes all the hydrodynamic processes to forecast total water in the Potomac River. As studies on tidal and riverine flow interaction are very scarce in number, our forecast system would be a scientific tool to examine such area and fill the gaps with precise prediction for Potomac River. Real-time observations from National Oceanic and Atmospheric Administration (NOAA) and field measurements have been used as model boundary feeding. The model performance has been validated by using major historical riverine and coastal flooding events. Hydrodynamic model ADCIRC produced promising predictions for flood inundation areas. As better forecasts can be achieved by using coupled models, this system is developed to take boundary conditions from Global WaveWatchIII for the research purposes. Wave and swell propagation will be fed through Global WavewatchIII model to take into account the effects of swells and currents. This automated forecast system is currently undergoing rigorous testing to include any missing parameters which

  1. New insights on geomagnetic storms from observations and modeling

    Energy Technology Data Exchange (ETDEWEB)

    Jordanova, Vania K [Los Alamos National Laboratory

    2009-01-01

    Understanding the response at Earth of the Sun's varying energy output and forecasting geomagnetic activity is of central interest to space science, since intense geomagnetic storms may cause severe damages on technological systems and affect communications. Episodes of southward (Bzstorms representative of each interplanetary condition with our kinetic ring current atmosphere interactions model (RAM), and investigate the mechanisms responsible for trapping particles and for causing their loss. We find that periods of increased magnetospheric convection coinciding with enhancements of plasma sheet density are needed for strong ring current buildup. During the HSS-driven storm the convection potential is highly variable and causes small sporadic injections into the ring current. The long period of enhanced convection during the CME-driven storm causes a continuous ring current injection penetrating to lower L shells and stronger ring current buildup.

  2. Ionospheric and satellite observations for studying the dynamic behavior of typhoons and the detection of severe storms and tsunamis

    Science.gov (United States)

    Hung, R. J.; Smith, R. E.

    1978-01-01

    Atmospheric acoustic-gravity waves associated with severe thunderstorms, tornadoes, typhoons (hurricanes) and tsunamis can be studied through the coupling between the ionosphere and the troposphere. Reverse ray tracing computations of acoustic-gravity waves observed by an ionospheric Doppler sounder array show that wave sources are in the nearby storm systems and that the waves are excited prior to the storms. Results show that ionospheric observations, together with satellite observations, can contribute to the understanding of the dynamical behavior of typhoons, severe storms and tsunamis.

  3. Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market

    Energy Technology Data Exchange (ETDEWEB)

    Mandal, Paras; Senjyu, Tomonobu [Department of Electrical and Electronics, University of the Ryukyus, 1 Senbaru, Nagakami Nishihara, Okinawa 903-0213 (Japan); Funabashi, Toshihisa [Meidensha Corporation, Tokyo 103-8515 (Japan)

    2006-09-15

    In daily power markets, forecasting electricity prices and loads are the most essential task and the basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper introduces an approach for several hour ahead (1-6h) electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of the similar days. Two different ANN models, one for one to six hour ahead load forecasting and another for one to six hour ahead price forecasting have been proposed. The MAPE (mean absolute percentage error) results show a clear increasing trend with the increase in hour ahead load and price forecasting. The sample average of MAPEs for one hour ahead price forecasts is 9.75%. This figure increases to only 20.03% for six hour ahead predictions. Similarly, the one to six hour ahead load forecast errors (MAPE) range from 0.56% to 1.30% only. MAPE results show that several hour ahead electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy. (author)

  4. Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market

    International Nuclear Information System (INIS)

    Mandal, Paras; Senjyu, Tomonobu; Funabashi, Toshihisa

    2006-01-01

    In daily power markets, forecasting electricity prices and loads are the most essential task and the basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper introduces an approach for several hour ahead (1-6 h) electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of the similar days. Two different ANN models, one for one to six hour ahead load forecasting and another for one to six hour ahead price forecasting have been proposed. The MAPE (mean absolute percentage error) results show a clear increasing trend with the increase in hour ahead load and price forecasting. The sample average of MAPEs for one hour ahead price forecasts is 9.75%. This figure increases to only 20.03% for six hour ahead predictions. Similarly, the one to six hour ahead load forecast errors (MAPE) range from 0.56% to 1.30% only. MAPE results show that several hour ahead electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy

  5. 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.

  6. A climatology of potential severe convective environments across South Africa

    Science.gov (United States)

    Blamey, R. C.; Middleton, C.; Lennard, C.; Reason, C. J. C.

    2017-09-01

    Severe thunderstorms pose a considerable risk to society and the economy of South Africa during the austral summer months (October-March). Yet, the frequency and distribution of such severe storms is poorly understood, which partly stems out of an inadequate observation network. Given the lack of observations, alternative methods have focused on the relationship between severe storms and their associated environments. One such approach is to use a combination of covariant discriminants, derived from gridded datasets, as a probabilistic proxy for the development of severe storms. These covariates describe some key ingredient for severe convective storm development, such as the presence of instability. Using a combination of convective available potential energy and deep-layer vertical shear from Climate Forecast System Reanalysis, this study establishes a climatology of potential severe convective environments across South Africa for the period 1979-2010. Results indicate that early austral summer months are most likely associated with conditions that are conducive to the development of severe storms over the interior of South Africa. The east coast of the country is a hotspot for potential severe convective environments throughout the summer months. This is likely due to the close proximity of the Agulhas Current, which produces high latent heat fluxes and acts as a key moisture source. No obvious relationship is established between the frequency of potential severe convective environments and the main large-scale modes of variability in the Southern Hemisphere, such as ENSO. This implies that several factors, possibly more localised, may modulate the spatial and temporal frequency of severe thunderstorms across the region.

  7. Wave forecasting and monitoring during very severe cyclone Phailin in the Bay of Bengal.

    Digital Repository Service at National Institute of Oceanography (India)

    Nair, T.M.B; Remya, P.G.; Harikumar, R.; Sandhya, K.G.; Sirisha, P.; Srinivas, K.; Nagaraju, C.; Nherakkol, A.; KrishnaPrasad, B.; Jeyakumar, C.; Kaviyazhahu, K.; Hithin, N.K.; Kumari, R.; SanilKumar, V.; RameshKumar, M.; Shenoi, S.S.C.; Nayak, S.

    Wave fields, both measured and forecast during the very severe cyclone Phailin, are discussed in this communication. Waves having maximum height of 13.54 m were recorded at Gopalpur, the landfall point of the cyclone. The forecast and observed...

  8. An Exploration of Wind Stress Calculation Techniques in Hurricane Storm Surge Modeling

    Directory of Open Access Journals (Sweden)

    Kyra M. Bryant

    2016-09-01

    Full Text Available As hurricanes continue to threaten coastal communities, accurate storm surge forecasting remains a global priority. Achieving a reliable storm surge prediction necessitates accurate hurricane intensity and wind field information. The wind field must be converted to wind stress, which represents the air-sea momentum flux component required in storm surge and other oceanic models. This conversion requires a multiplicative drag coefficient for the air density and wind speed to represent the air-sea momentum exchange at a given location. Air density is a known parameter and wind speed is a forecasted variable, whereas the drag coefficient is calculated using an empirical correlation. The correlation’s accuracy has brewed a controversy of its own for more than half a century. This review paper examines the lineage of drag coefficient correlations and their acceptance among scientists.

  9. ECMWF Extreme Forecast Index for water vapor transport: A forecast tool for atmospheric rivers and extreme precipitation

    Science.gov (United States)

    Lavers, David A.; Pappenberger, Florian; Richardson, David S.; Zsoter, Ervin

    2016-11-01

    In winter, heavy precipitation and floods along the west coasts of midlatitude continents are largely caused by intense water vapor transport (integrated vapor transport (IVT)) within the atmospheric river of extratropical cyclones. This study builds on previous findings that showed that forecasts of IVT have higher predictability than precipitation, by applying and evaluating the European Centre for Medium-Range Weather Forecasts Extreme Forecast Index (EFI) for IVT in ensemble forecasts during three winters across Europe. We show that the IVT EFI is more able (than the precipitation EFI) to capture extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase; conversely, the precipitation EFI is better during the negative NAO phase and at shorter leads. An IVT EFI example for storm Desmond in December 2015 highlights its potential to identify upcoming hydrometeorological extremes, which may prove useful to the user and forecasting communities.

  10. STORM3: a new flood forecast management and monitoring system in accordance with the recent Italian national directive

    Directory of Open Access Journals (Sweden)

    A. Burastero

    2005-01-01

    Full Text Available The effectiveness of alert systems for civil protection purposes, defined as the ability to minimize the level of risk in a region subjected to an imminent flood event, strongly depends on availability and exploitability of information. It also depends on technical expertise and the ability to easily manage the civil protection actions through the organization into standardized procedures. Hydro-geologic and hydraulic risk estimation, based on the combination of different technical issues (in this case meteorological, hydro-geological, hydraulic matters, but also socio-economic ones, requires the integration between quasi-static and time-varying information within the same operative platform. Beside the real-time data exchange, a Decision Support System must provide tools which enable knowledge sharing among the civil protection centres. Moreover, due to the amount and heterogeneity of information, quality procedures become necessary to handle all forecasting and monitoring routines within operative centres, according to the latest national directive. In Italy procedures on the civil protection matter have been condensed into the Prime Minister's Directive (27 February 2004. STORM3, an innovative management and monitoring System for real-time flood forecasting and warning, takes in the Directive, supporting the operator step by step within the different phases of civil protection activities.

  11. Dynamic stability analysis of caisson breakwater in lifetime considering the annual frequency of severe storm

    Science.gov (United States)

    Wang, Yu-chi; Wang, Yuan-zhan; Hong, Ning-ning

    2015-04-01

    In the dynamic stability analysis of a caisson breakwater, most of current studies pay attention to the motion characteristics of caisson breakwaters under a single periodical breaking wave excitation. And in the lifetime stability analysis of caisson breakwater, it is assumed that the caisson breakwater suffers storm wave excitation once annually in the design lifetime. However, the number of annual severe storm occurrence is a random variable. In this paper, a series of random waves are generated by the Wen Sheng-chang wave spectrum, and the histories of successive and long-term random wave forces are built up by using the improved Goda wave force model. It is assumed that the number of annual severe storm occurrence is in the Poisson distribution over the 50-year design lifetime, and the history of random wave excitation is generated for each storm by the wave spectrum. The response histories of the caisson breakwater to the random waves over 50-year design lifetime are calculated and taken as a set of samples. On the basis of the Monte Carlo simulation technique, a large number of samples can be obtained, and the probability assessment of the safety of the breakwater during the complete design lifetime is obtained by statistical analysis of a large number of samples. Finally, the procedure of probability assessment of the breakwater safety is illustrated by an example.

  12. Impact of Short Interval SMS Digital Data on Wind Vector Determination for a Severe Local Storms Area

    Science.gov (United States)

    Peslen, C. A.

    1979-01-01

    The impact of 5 minute interval SMS-2 visible digital image data in analyzing severe local storms is examined using wind vectors derived from cloud tracking on time lapsed sequence of geosynchronous satellite images. The cloud tracking areas are located in the Central Plains, where on 6 May 1975, hail-producing thunderstorms occurred ahead of a well defined dry line. The results demonstrate that satellite-derived wind vectors and their associated divergence fields complement conventional meteorological analyses in describing the conditions preceding severe local storm development.

  13. High Resolution Hurricane Storm Surge and Inundation Modeling (Invited)

    Science.gov (United States)

    Luettich, R.; Westerink, J. J.

    2010-12-01

    Coastal counties are home to nearly 60% of the U.S. population and industry that accounts for over 16 million jobs and 10% of the U.S. annual gross domestic product. However, these areas are susceptible to some of the most destructive forces in nature, including tsunamis, floods, and severe storm-related hazards. Since 1900, tropical cyclones making landfall on the US Gulf of Mexico Coast have caused more than 9,000 deaths; nearly 2,000 deaths have occurred during the past half century. Tropical cyclone-related adjusted, annualized losses in the US have risen from 1.3 billion from 1949-1989, to 10.1 billion from 1990-1995, and $35.8 billion per year for the period 2001-2005. The risk associated with living and doing business in the coastal areas that are most susceptible to tropical cyclones is exacerbated by rising sea level and changes in the characteristics of severe storms associated with global climate change. In the five years since hurricane Katrina devastated the northern Gulf of Mexico Coast, considerable progress has been made in the development and utilization of high resolution coupled storm surge and wave models. Recent progress will be presented with the ADCIRC + SWAN storm surge and wave models. These tightly coupled models use a common unstructured grid in the horizontal that is capable of covering large areas while also providing high resolution (i.e., base resolution down to 20m plus smaller subgrid scale features such as sea walls and levees) in areas that are subject to surge and inundation. Hydrodynamic friction and overland winds are adjusted to account for local land cover. The models scale extremely well on modern high performance computers allowing rapid turnaround on large numbers of compute cores. The models have been adopted for FEMA National Flood Insurance Program studies, hurricane protection system design and risk analysis, and quasi-operational forecast systems for several regions of the country. They are also being evaluated as

  14. Modelling and forecasting occupational accidents of different severity levels in Spain

    International Nuclear Information System (INIS)

    Carmen Carnero, Maria; Jose Pedregal, Diego

    2010-01-01

    The control of accidents at the work place is a critical issue all over the world. The consequences of occupational accidents in terms of costs for the company in which the accidents take place is only one minor matter, being the social impact and the loss of human life the most controversial effects of this important problem. The methods used to forecast future evolution of accidents are often limited to trend estimations and projections, being the scientific literature on this topic rather scarce. This paper aims at showing and predicting the evolution of Spanish occupational accidents of different levels of severity, allowing the evaluation of the influence that preventive actions carried out by public administrations or private companies may have over the number of occupational accidents. Though some contributions may be found on this topic for Spain, this paper is the first contribution that forecast occupational accidents for different levels of severity using Multivariate Unobserved Components models developed in a State Space framework extended to deal with the irregular sampling interval of the data. Data from 1998 to 2009 have been used to test the efficacy of the forecasting system.

  15. Storm Identification, Tracking and Forecasting Using High-Resolution Images of Short-Range X-Band Radar

    Directory of Open Access Journals (Sweden)

    Sajid Shah

    2015-05-01

    Full Text Available Rain nowcasting is an essential part of weather monitoring. It plays a vital role in human life, ranging from advanced warning systems to scheduling open air events and tourism. A nowcasting system can be divided into three fundamental steps, i.e., storm identification, tracking and nowcasting. The main contribution of this work is to propose procedures for each step of the rain nowcasting tool and to objectively evaluate the performances of every step, focusing on two-dimension data collected from short-range X-band radars installed in different parts of Italy. This work presents the solution of previously unsolved problems in storm identification: first, the selection of suitable thresholds for storm identification; second, the isolation of false merger (loosely-connected storms; and third, the identification of a high reflectivity sub-storm within a large storm. The storm tracking step of the existing tools, such as TITANand SCIT, use only up to two storm attributes, i.e., center of mass and area. It is possible to use more attributes for tracking. Furthermore, the contribution of each attribute in storm tracking is yet to be investigated. This paper presents a novel procedure called SALdEdA (structure, amplitude, location, eccentricity difference and areal difference for storm tracking. This work also presents the contribution of each component of SALdEdA in storm tracking. The second order exponential smoothing strategy is used for storm nowcasting, where the growth and decay of each variable of interest is considered to be linear. We evaluated the major steps of our method. The adopted techniques for automatic threshold calculation are assessed with a 97% goodness. False merger and sub-storms within a cluster of storms are successfully handled. Furthermore, the storm tracking procedure produced good results with an accuracy of 99.34% for convective events and 100% for stratiform events.

  16. Analysis and Forecast of a Tornadic Thunderstorm Using Multiple Doppler Radar Data, 3DVAR, and ARPS Model

    Directory of Open Access Journals (Sweden)

    Edward Natenberg

    2013-01-01

    Full Text Available A three-dimensional variational (3DVAR assimilation technique developed for a convective-scale NWP model—advanced regional prediction system (ARPS—is used to analyze the 8 May 2003, Moore/Midwest City, Oklahoma tornadic supercell thunderstorm. Previous studies on this case used only one or two radars that are very close to this storm. However, three other radars observed the upper-level part of the storm. Because these three radars are located far away from the targeted storm, they were overlooked by previous studies. High-frequency intermittent 3DVAR analyses are performed using the data from five radars that together provide a more complete picture of this storm. The analyses capture a well-defined mesocyclone in the midlevels and the wind circulation associated with a hook-shaped echo. The analyses produced through this technique are used as initial conditions for a 40-minute storm-scale forecast. The impact of multiple radars on a short-term NWP forecast is most evident when compared to forecasts using data from only one and two radars. The use of all radars provides the best forecast in which a strong low-level mesocyclone develops and tracks in close proximity to the actual tornado damage path.

  17. Increasing frequency of extremely severe cyclonic storms over the Arabian Sea

    Science.gov (United States)

    Murakami, Hiroyuki; Vecchi, Gabriel A.; Underwood, Seth

    2017-12-01

    In 2014 and 2015, post-monsoon extremely severe cyclonic storms (ESCS)—defined by the WMO as tropical storms with lifetime maximum winds greater than 46 m s-1—were first observed over the Arabian Sea (ARB), causing widespread damage. However, it is unknown to what extent this abrupt increase in post-monsoon ESCSs can be linked to anthropogenic warming, natural variability, or stochastic behaviour. Here, using a suite of high-resolution global coupled model experiments that accurately simulate the climatological distribution of ESCSs, we show that anthropogenic forcing has likely increased the probability of late-season ECSCs occurring in the ARB since the preindustrial era. However, the specific timing of observed late-season ESCSs in 2014 and 2015 was likely due to stochastic processes. It is further shown that natural variability played a minimal role in the observed increase of ESCSs. Thus, continued anthropogenic forcing will further amplify the risk of cyclones in the ARB, with corresponding socio-economic implications.

  18. Use of Remote Sensing Data to Enhance NWS Storm Damage Toolkit

    Science.gov (United States)

    Jedlove, Gary J.; Molthan, Andrew L.; White, Kris; Burks, Jason; Stellman, Keith; Smith, Mathew

    2012-01-01

    In the wake of a natural disaster such as a tornado, the National Weather Service (NWS) is required to provide a very detailed and timely storm damage assessment to local, state and federal homeland security officials. The Post ]Storm Data Acquisition (PSDA) procedure involves the acquisition and assembly of highly perishable data necessary for accurate post ]event analysis and potential integration into a geographic information system (GIS) available to its end users and associated decision makers. Information gained from the process also enables the NWS to increase its knowledge of extreme events, learn how to better use existing equipment, improve NWS warning programs, and provide accurate storm intensity and damage information to the news media and academia. To help collect and manage all of this information, forecasters in NWS Southern Region are currently developing a Storm Damage Assessment Toolkit (SDAT), which incorporates GIS ]capable phones and laptops into the PSDA process by tagging damage photography, location, and storm damage details with GPS coordinates for aggregation within the GIS database. However, this tool alone does not fully integrate radar and ground based storm damage reports nor does it help to identify undetected storm damage regions. In many cases, information on storm damage location (beginning and ending points, swath width, etc.) from ground surveys is incomplete or difficult to obtain. Geographic factors (terrain and limited roads in rural areas), manpower limitations, and other logistical constraints often prevent the gathering of a comprehensive picture of tornado or hail damage, and may allow damage regions to go undetected. Molthan et al. (2011) have shown that high resolution satellite data can provide additional valuable information on storm damage tracks to augment this database. This paper presents initial development to integrate satellitederived damage track information into the SDAT for near real ]time use by forecasters

  19. An operational integrated short-term warning solution for solar radiation storms: introducing the Forecasting Solar Particle Events and Flares (FORSPEF) system

    Science.gov (United States)

    Anastasiadis, Anastasios; Sandberg, Ingmar; Papaioannou, Athanasios; Georgoulis, Manolis; Tziotziou, Kostas; Jiggens, Piers; Hilgers, Alain

    2015-04-01

    We present a novel integrated prediction system, of both solar flares and solar energetic particle (SEP) events, which is in place to provide short-term warnings for hazardous solar radiation storms. FORSPEF system provides forecasting of solar eruptive events, such as solar flares with a projection to coronal mass ejections (CMEs) (occurrence and velocity) and the likelihood of occurrence of a SEP event. It also provides nowcasting of SEP events based on actual solar flare and CME near real-time alerts, as well as SEP characteristics (peak flux, fluence, rise time, duration) per parent solar event. The prediction of solar flares relies on a morphological method which is based on the sophisticated derivation of the effective connected magnetic field strength (Beff) of potentially flaring active-region (AR) magnetic configurations and it utilizes analysis of a large number of AR magnetograms. For the prediction of SEP events a new reductive statistical method has been implemented based on a newly constructed database of solar flares, CMEs and SEP events that covers a large time span from 1984-2013. The method is based on flare location (longitude), flare size (maximum soft X-ray intensity), and the occurrence (or not) of a CME. Warnings are issued for all > C1.0 soft X-ray flares. The warning time in the forecasting scheme extends to 24 hours with a refresh rate of 3 hours while the respective warning time for the nowcasting scheme depends on the availability of the near real-time data and falls between 15-20 minutes. We discuss the modules of the FORSPEF system, their interconnection and the operational set up. The dual approach in the development of FORPSEF (i.e. forecasting and nowcasting scheme) permits the refinement of predictions upon the availability of new data that characterize changes on the Sun and the interplanetary space, while the combined usage of solar flare and SEP forecasting methods upgrades FORSPEF to an integrated forecasting solution. This

  20. Analyis of the role of the planetary boundary layer schemes during a severe convective storm

    NARCIS (Netherlands)

    Wisse, J.S.P.; Vilà-Guerau de Arellano, J.

    2004-01-01

    The role played by planetary boundary layer (PBL) in the development and evolution of a severe convective storm is studied by means of meso-scale modeling and surface and upper air observations. The severe convective precipitation event that occurred on 14 September 1999 in the northeast of the

  1. Adaptive mesh refinement for storm surge

    KAUST Repository

    Mandli, Kyle T.; Dawson, Clint N.

    2014-01-01

    An approach to utilizing adaptive mesh refinement algorithms for storm surge modeling is proposed. Currently numerical models exist that can resolve the details of coastal regions but are often too costly to be run in an ensemble forecasting framework without significant computing resources. The application of adaptive mesh refinement algorithms substantially lowers the computational cost of a storm surge model run while retaining much of the desired coastal resolution. The approach presented is implemented in the GeoClaw framework and compared to ADCIRC for Hurricane Ike along with observed tide gauge data and the computational cost of each model run. © 2014 Elsevier Ltd.

  2. Adaptive mesh refinement for storm surge

    KAUST Repository

    Mandli, Kyle T.

    2014-03-01

    An approach to utilizing adaptive mesh refinement algorithms for storm surge modeling is proposed. Currently numerical models exist that can resolve the details of coastal regions but are often too costly to be run in an ensemble forecasting framework without significant computing resources. The application of adaptive mesh refinement algorithms substantially lowers the computational cost of a storm surge model run while retaining much of the desired coastal resolution. The approach presented is implemented in the GeoClaw framework and compared to ADCIRC for Hurricane Ike along with observed tide gauge data and the computational cost of each model run. © 2014 Elsevier Ltd.

  3. Current understanding of magnetic storms: Storm-substorm relationships

    International Nuclear Information System (INIS)

    Kamide, Y.; Gonzalez, W.D.; Baumjohann, W.; Daglis, I.A.; Grande, M.; Joselyn, J.A.; Singer, H.J.; McPherron, R.L.; Phillips, J.L.; Reeves, E.G.; Rostoker, G.; Sharma, A.S.; Tsurutani, B.T.

    1998-01-01

    storm-time ring current. An apparently new controversy regarding the relative importance of the two processes is thus created. It is important to identify the role of substorm occurrence in the large-scale enhancement of magnetospheric convection driven by solar wind electric fields. (3) Numerical schemes for predicting geomagnetic activity indices on the basis of solar/solar wind/interplanetary magnetic field parameters continue to be upgraded, ensuring reliable techniques for forecasting magnetic storms under real-time conditions. There is a need to evaluate the prediction capability of geomagnetic indices on the basis of physical processes that occur during storm time substorms. (4) It is crucial to differentiate between storms and nonstorm time substorms in terms of energy transfer/conversion processes, i.e., mechanical energy from the solar wind, electromagnetic energy in the magnetotail, and again, mechanical energy of particles in the plasma sheet, ring current, and aurora. To help answer the question of the role of substorms in energizing ring current particles, it is crucial to find efficient magnetospheric processes that heat ions up to some minimal energies so that they can have an effect on the strength of the storm time ring current. (5) The question of whether the Dst index is an accurate and effective measure of the storm time ring-current is also controversial. In particular, it is demonstrated that the dipolarization effect associated with substorm expansion

  4. Ionosphere dynamics over the Southern Hemisphere during the 31 March 2001 severe magnetic storm using multi-instrument measurement data

    Directory of Open Access Journals (Sweden)

    E. Yizengaw

    2005-03-01

    Full Text Available The effects of the 31 March 2001 severe magnetic storm on the Southern Hemisphere ionosphere have been studied using ground-based and satellite measurements. The prime goal of this comprehensive study is to track the ionospheric response from high-to-low latitude to obtain a clear understanding of storm-time ionospheric change. The study uses a combination of ionospheric Total Electron Content (TEC obtained from GPS signal group delay and phase advance measurements, ionosonde data, and data from satellite in-situ measurements, such as the Defense Metrological Satellite Program (DMSP, TOPographic EXplorer (TOPEX, and solar wind data from the Advanced Composition Explorer (ACE. A chain of Global Positioning System (GPS stations near the 150° E meridian has been used to give comprehensive latitude coverage extending from the cusp to the equatorial region. A tomographic inversion algorithm has been applied to the GPS TEC measurements to obtain maps of the latitudinal structure of the ionospheric during this severe magnetic storm period, enabling both the spatial and temporal response of the ionosphere to be studied. Analysis of data from several of the instruments indicates that a strong density enhancement occurred at mid-latitudes at 11:00 UT on 31 March 2001 and was followed by equatorward propagating large-scale Travelling Ionospheric Disturbances (TIDs. The tomographic reconstruction revealed important features in ionospheric structure, such as quasi-wave formations extending finger-like to higher altitudes. The most pronounced ionospheric effects of the storm occurred at high- and mid-latitudes, where strong positive disturbances occurred during the storm main phase, followed by a long lasting negative storm effect during the recovery phase. Relatively minor storm effects occurred in the equatorial region.

  5. Two-sample Kalman filter and system error modelling for storm surge forecasting

    NARCIS (Netherlands)

    Sumihar, J.H.

    2009-01-01

    Two directions for improving the accuracy of sea level forecast are investigated in this study. The first direction seeks to improve the forecast accuracy of astronomical tide component. Here, a method is applied to analyze and forecast the remaining periodic components of harmonic analysis

  6. Perceptions and Expected Immediate Reactions to Severe Storm Displays.

    Science.gov (United States)

    Jon, Ihnji; Huang, Shih-Kai; Lindell, Michael K

    2017-11-09

    The National Weather Service has adopted warning polygons that more specifically indicate the risk area than its previous county-wide warnings. However, these polygons are not defined in terms of numerical strike probabilities (p s ). To better understand people's interpretations of warning polygons, 167 participants were shown 23 hypothetical scenarios in one of three information conditions-polygon-only (Condition A), polygon + tornadic storm cell (Condition B), and polygon + tornadic storm cell + flanking nontornadic storm cells (Condition C). Participants judged each polygon's p s and reported the likelihood of taking nine different response actions. The polygon-only condition replicated the results of previous studies; p s was highest at the polygon's centroid and declined in all directions from there. The two conditions displaying storm cells differed from the polygon-only condition only in having p s just as high at the polygon's edge nearest the storm cell as at its centroid. Overall, p s values were positively correlated with expectations of continuing normal activities, seeking information from social sources, seeking shelter, and evacuating by car. These results indicate that participants make more appropriate p s judgments when polygons are presented in their natural context of radar displays than when they are presented in isolation. However, the fact that p s judgments had moderately positive correlations with both sheltering (a generally appropriate response) and evacuation (a generally inappropriate response) suggests that experiment participants experience the same ambivalence about these two protective actions as people threatened by actual tornadoes. © 2017 Society for Risk Analysis.

  7. Thermal response of upper layers of Bay of Bengal to forcing of a severe cyclonic storm: A case study

    Digital Repository Service at National Institute of Oceanography (India)

    Gopalakrishna, V.V.; Murty, V.S.N.; Sarma, M.S.S.; Sastry, J.S.

    Upper ocean response to forcing of a severe cyclonic storm during May 1990 in the western Bay of Bengal was studied using the XBT data sets collected (4 d after passage of storm) under Indian TOGA programme. A maximum lowering in the sea surface...

  8. Changing statistics of storms in the North Atlantic?

    International Nuclear Information System (INIS)

    Storch, H. von; Guddal, J.; Iden, K.A.; Jonsson, T.; Perlwitz, J.; Reistad, M.; Ronde, J. de; Schmidt, H.; Zorita, E.

    1993-01-01

    Problems in the present discussion about increasing storminess in the North Atlantic area are discusesd. Observational data so far available do not indicate a change in the storm statistics. Output from climate models points to an itensified storm track in the North Atlantic, but because of the limited skill of present-day climate models in simulating high-frequency variability and regional details any such 'forecast' has to be considered with caution. A downscaling procedure which relates large-scale time-mean aspects of the state of the atmosphere and ocean to the local statistics of storms is proposed to reconstruct past variations of high-frequency variability in the atmosphere (storminess) and in the sea state (wave statistics). First results are presented. (orig.)

  9. The Use of a Statistical Model of Storm Surge as a Bias Correction for Dynamical Surge Models and its Applicability along the U.S. East Coast

    Directory of Open Access Journals (Sweden)

    Haydee Salmun

    2015-02-01

    Full Text Available The present study extends the applicability of a statistical model for prediction of storm surge originally developed for The Battery, NY in two ways: I. the statistical model is used as a biascorrection for operationally produced dynamical surge forecasts, and II. the statistical model is applied to the region of the east coast of the U.S. susceptible to winter extratropical storms. The statistical prediction is based on a regression relation between the “storm maximum” storm surge and the storm composite significant wave height predicted ata nearby location. The use of the statistical surge prediction as an alternative bias correction for the National Oceanic and Atmospheric Administration (NOAA operational storm surge forecasts is shownhere to be statistically equivalent to the existing bias correctiontechnique and potentially applicable for much longer forecast lead times as well as for storm surge climate prediction. Applying the statistical model to locations along the east coast shows that the regression relation can be “trained” with data from tide gauge measurements and near-shore buoys along the coast from North Carolina to Maine, and that it provides accurate estimates of storm surge.

  10. Thromboembolic complications of thyroid storm.

    Science.gov (United States)

    Min, T; Benjamin, S; Cozma, L

    2014-01-01

    Thyroid storm is a rare but potentially life-threatening complication of hyperthyroidism. Early recognition and prompt treatment are essential. Atrial fibrillation can occur in up to 40% of patients with thyroid storm. Studies have shown that hyperthyroidism increases the risk of thromboembolic events. There is no consensus with regard to the initiation of anticoagulation for atrial fibrillation in severe thyrotoxicosis. Anticoagulation is not routinely initiated if the risk is low on a CHADS2 score; however, this should be considered in patients with thyroid storm or severe thyrotoxicosis with impending storm irrespective of the CHADS2 risk, as it appears to increase the risk of thromboembolic episodes. Herein, we describe a case of thyroid storm complicated by massive pulmonary embolism. Diagnosis of thyroid storm is based on clinical findings. Early recognition and prompt treatment could lead to a favourable outcome.Hypercoagulable state is a recognised complication of thyrotoxicosis.Atrial fibrillation is strongly associated with hyperthyroidism and thyroid storm.Anticoagulation should be considered for patients with severe thyrotoxicosis and atrial fibrillation irrespective of the CHADS2 score.Patients with severe thyrotoxicosis and clinical evidence of thrombosis should be immediately anticoagulated until hyperthyroidism is under control.

  11. Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

    Science.gov (United States)

    Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

    2013-12-01

    Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail

  12. Operational Forecasting and Warning systems for Coastal hazards in Korea

    Science.gov (United States)

    Park, Kwang-Soon; Kwon, Jae-Il; Kim, Jin-Ah; Heo, Ki-Young; Jun, Kicheon

    2017-04-01

    Coastal hazards caused by both Mother Nature and humans cost tremendous social, economic and environmental damages. To mitigate these damages many countries have been running the operational forecasting or warning systems. Since 2009 Korea Operational Oceanographic System (KOOS) has been developed by the leading of Korea Institute of Ocean Science and Technology (KIOST) in Korea and KOOS has been operated in 2012. KOOS is consists of several operational modules of numerical models and real-time observations and produces the basic forecasting variables such as winds, tides, waves, currents, temperature and salinity and so on. In practical application systems include storm surges, oil spills, and search and rescue prediction models. In particular, abnormal high waves (swell-like high-height waves) have occurred in the East coast of Korea peninsula during winter season owing to the local meteorological condition over the East Sea, causing property damages and the loss of human lives. In order to improve wave forecast accuracy even very local wave characteristics, numerical wave modeling system using SWAN is established with data assimilation module using 4D-EnKF and sensitivity test has been conducted. During the typhoon period for the prediction of sever waves and the decision making support system for evacuation of the ships, a high-resolution wave forecasting system has been established and calibrated.

  13. A Numerical Simulation of Extratropical Storm Surge and Hydrodynamic Response in the Bohai Sea

    OpenAIRE

    Ding, Yumei; Ding, Lei

    2014-01-01

    A hindcast of typical extratropical storm surge occurring in the Bohai Sea in October 2003 is performed using a three-dimensional (3D) Finite Volume Coastal Ocean Model (FVCOM). The storm surge model is forced by 10 m winds obtained from the Weather Research Forecasting (WRF) model simulation. It is shown that the simulated storm surge and tides agree well with the observations. The nonlinear interaction between the surge and astronomical tides, the spatial distribution of the max...

  14. Detection and Prediction of Hail Storms in Satellite Imagery using Deep Learning

    Science.gov (United States)

    Pullman, M.; Gurung, I.; Ramachandran, R.; Maskey, M.

    2017-12-01

    Natural hazards, such as damaging hail storms, dramatically disrupt both industry and agriculture, having significant socio-economic impacts in the United States. In 2016, hail was responsible for 3.5 billion and 23 million dollars in damage to property and crops, respectively, making it the second costliest 2016 weather phenomenon in the United States. The destructive nature and high cost of hail storms has driven research into the development of more accurate hail-prediction algorithms in an effort to mitigate societal impacts. Recently, weather forecasting efforts have turned to deep learning neural networks because neural networks can more effectively model complex, nonlinear, dynamical phenomenon that exist in large datasets through multiple stages of transformation and representation. In an effort to improve hail-prediction techniques, we propose a deep learning technique that leverages satellite imagery to detect and predict the occurrence of hail storms. The technique is applied to satellite imagery from 2006 to 2016 for the contiguous United States and incorporates hail reports obtained from the National Center for Environmental Information Storm Events Database for training and validation purposes. In this presentation, we describe a novel approach to predicting hail via a neural network model that creates a large labeled dataset of hail storms, the accuracy and results of the model, and its applications for improving hail forecasting.

  15. Space weather and dangerous phenomena on the Earth: principles of great geomagnetic storms forcasting by online cosmic ray data

    Directory of Open Access Journals (Sweden)

    L. I. Dorman

    2005-11-01

    Full Text Available According to NOAA space weather scales, geomagnetic storms of scales G5 (3-h index of geomagnetic activity Kp=9, G4 (Kp=8 and G3 (Kp=7 are dangerous for satellites, aircrafts, and even for technology on the ground (influence on power systems, on spacecraft operations, on HF radio-communications and others. We show on the basis of statistical data, that these geomagnetic storms, mostly accompanied by cosmic ray (CR Forbush-decreases, are also dangerous for people's health on spacecraft and on the ground (increasing the rate of myocardial infarctions, brain strokes and car accident road traumas. To prevent these serious damages it is very important to forecast dangerous geomagnetic storms. Here we consider the principles of using CR measurements for this aim: to forecast at least 10-15h before the sudden commencement of great geomagnetic storms accompanied by Forbush-decreases, by using neutron monitor muon telescope worldwide network online hourly data. We show that for this forecast one may use the following features of CR intensity variations connected with geomagnetic storms accompanied by Forbush-decreases: 1 CR pre-increase, 2 CR pre-decrease, 3 CR fluctuations, 4 change in the 3-D CR anisotropy.

  16. Developing empirical lightning cessation forecast guidance for the Kennedy Space Center

    Science.gov (United States)

    Stano, Geoffrey T.

    The Kennedy Space Center in east Central Florida is one of the few locations in the country that issues lightning advisories. These forecasts are vital to the daily operations of the Space Center and take on even greater significance during launch operations. The U.S. Air Force's 45th Weather Squadron (45WS), who provides forecasts for the Space Center, has a good record of forecasting the initiation of lightning near their locations of special concern. However, the remaining problem is knowing when to cancel a lightning advisory. Without specific scientific guidelines detailing cessation activity, the Weather Squadron must keep advisories in place longer than necessary to ensure the safety of personnel and equipment. This unnecessary advisory time costs the Space Center millions of dollars in lost manpower each year. This research presents storm and environmental characteristics associated with lightning cessation that then are utilized to create lightning cessation guidelines for isolated thunderstorms for use by the 45WS during the warm season months of May through September. The research uses data from the Lightning Detection and Ranging (LDAR) network at the Kennedy Space Center, which can observe intra-cloud and portions of cloud-to-ground lightning strikes. Supporting data from the Cloud-to-Ground Lightning Surveillance System (CGLSS), radar observations from the Melbourne WSR-88D, and Cape Canaveral morning radiosonde launches also are included. Characteristics of 116 thunderstorms comprising our dataset are presented. Most of these characteristics are based on LDAR-derived spark and flash data and have not been described previously. In particular, the first lightning activity is quantified as either cloud-to-ground (CG) or intra-cloud (IC). Only 10% of the storms in this research are found to initiate with a CG strike. Conversely, only 16% of the storms end with a CG strike. Another characteristic is the average horizontal extent of all the flashes

  17. High resolution modelling of wind fields for optimization of empirical storm flood predictions

    Science.gov (United States)

    Brecht, B.; Frank, H.

    2014-05-01

    High resolution wind fields are necessary to predict the occurrence of storm flood events and their magnitude. Deutscher Wetterdienst (DWD) created a catalogue of detailed wind fields of 39 historical storms at the German North Sea coast from the years 1962 to 2011. The catalogue is used by the Niedersächsisches Landesamt für Wasser-, Küsten- und Naturschutz (NLWKN) coastal research center to improve their flood alert service. The computation of wind fields and other meteorological parameters is based on the model chain of the DWD going from the global model GME via the limited-area model COSMO with 7 km mesh size down to a COSMO model with 2.2 km. To obtain an improved analysis COSMO runs are nudged against observations for the historical storms. The global model GME is initialised from the ERA reanalysis data of the European Centre for Medium-Range Weather Forecasts (ECMWF). As expected, we got better congruency with observations of the model for the nudging runs than the normal forecast runs for most storms. We also found during the verification process that different land use data sets could influence the results considerably.

  18. Storm Surge Modeling of Typhoon Haiyan at the Naval Oceanographic Office Using Delft3D

    Science.gov (United States)

    Gilligan, M. J.; Lovering, J. L.

    2016-02-01

    The Naval Oceanographic Office provides estimates of the rise in sea level along the coast due to storm surge associated with tropical cyclones, typhoons, and hurricanes. Storm surge modeling and prediction helps the US Navy by providing a threat assessment tool to help protect Navy assets and provide support for humanitarian assistance/disaster relief efforts. Recent advancements in our modeling capabilities include the use of the Delft3D modeling suite as part of a Naval Research Laboratory (NRL) developed Coastal Surge Inundation Prediction System (CSIPS). Model simulations were performed on Typhoon Haiyan, which made landfall in the Philippines in November 2013. Comparisons of model simulations using forecast and hindcast track data highlight the importance of accurate storm track information for storm surge predictions. Model runs using the forecast track prediction and hindcast track information give maximum storm surge elevations of 4 meters and 6.1 meters, respectively. Model results for the hindcast simulation were compared with data published by the JSCE-PICE Joint survey for locations in San Pedro Bay (SPB) and on the Eastern Samar Peninsula (ESP). In SPB, where wind-induced set-up predominates, the model run using the forecast track predicted surge within 2 meters in 38% of survey locations and within 3 meters in 59% of the locations. When the hindcast track was used, the model predicted within 2 meters in 77% of the locations and within 3 meters in 95% of the locations. The model was unable to predict the high surge reported along the ESP produced by infragravity wave-induced set-up, which is not simulated in the model. Additional modeling capabilities incorporating infragravity waves are required to predict storm surge accurately along open coasts with steep bathymetric slopes, such as those seen in island arcs.

  19. Revisiting the latent heat nudging scheme for the rainfall assimilation of a simulated convective storm

    Science.gov (United States)

    Leuenberger, D.; Rossa, A.

    2007-12-01

    Next-generation, operational, high-resolution numerical weather prediction models require economical assimilation schemes for radar data. In the present study we evaluate and characterise the latent heat nudging (LHN) rainfall assimilation scheme within a meso-γ scale NWP model in the framework of identical twin simulations of an idealised supercell storm. Consideration is given to the model’s dynamical response to the forcing as well as to the sensitivity of the LHN scheme to uncertainty in the observations and the environment. The results indicate that the LHN scheme is well able to capture the dynamical structure and the right rainfall amount of the storm in a perfect environment. This holds true even in degraded environments but a number of important issues arise. In particular, changes in the low-level humidity field are found to affect mainly the precipitation amplitude during the assimilation with a fast adaptation of the storm to the system dynamics determined by the environment during the free forecast. A constant bias in the environmental wind field, on the other hand, has the potential to render a successful assimilation with the LHN scheme difficult, as the velocity of the forcing is not consistent with the system propagation speed determined by the wind. If the rainfall forcing moves too fast, the system propagation is supported and the assimilated storm and forecasts initialised therefrom develop properly. A too slow forcing, on the other hand, can decelerate the system and eventually disturb the system dynamics by decoupling the low-level moisture inflow from the main updrafts during the assimilation. This distortion is sustained in the free forecast. It has further been found that a sufficient temporal resolution of the rainfall input is crucial for the successful assimilation of a fast moving, coherent convective storm and that the LHN scheme, when applied to a convective storm, appears to necessitate a careful tuning.

  20. Perceptions of severe storms, climate change, ecological structures and resiliency three years post-hurricane Sandy in New Jersey.

    Science.gov (United States)

    Burger, Joanna; Gochfeld, Michael

    2017-12-01

    Global warming is leading to increased frequency and severity of storms that are associated with flooding, increasing the risk to urban, coastal populations. This study examined perceptions of the relationship between severe storms, sea level rise, climate change and ecological barriers by a vulnerable environmental justice population in New Jersey. Patients using New Jersey's Federally Qualified Health Centers were interviewed after Hurricane [Superstorm] Sandy because it is essential to understand the perceptions of uninsured, underinsured, and economically challenged people to better develop a resiliency strategy for the most vulnerable people. Patients ( N = 355) using 6 centers were interviewed using a structured interview form. Patients were interviewed in the order they entered the reception area, in either English or Spanish. Respondents were asked to rate their agreement with environmental statements. Respondents 1) agreed with experts that "severe storms were due to climate change", "storms will come more often", and that "flooding was due to sea level rise", 2) did not agree as strongly that "climate change was due to human activity", 3) were neutral for statements that " Sandy damages were due to loss of dunes or salt marshes". 4) did not differ as a function of ethnic/racial categories, and 5) showed few gender differences. It is imperative that the public understand that climate change and sea level rise are occurring so that they support community programs (and funding) to prepare for increased frequency of storms and coastal flooding. The lack of high ratings for the role of dunes and marshes in preventing flooding indicates a lack of understanding that ecological structures protect coasts, and suggests a lack of support for management actions to restore dunes as part of a coastal preparedness strategy. Perceptions that do not support a public policy of coastal zone management to protect coastlines can lead to increased flooding, extensive property

  1. Predictability of tropical cyclone events on intraseasonal timescales with the ECMWF monthly forecast model

    Science.gov (United States)

    Elsberry, Russell L.; Jordan, Mary S.; Vitart, Frederic

    2010-05-01

    The objective of this study is to provide evidence of predictability on intraseasonal time scales (10-30 days) for western North Pacific tropical cyclone formation and subsequent tracks using the 51-member ECMWF 32-day forecasts made once a week from 5 June through 25 December 2008. Ensemble storms are defined by grouping ensemble member vortices whose positions are within a specified separation distance that is equal to 180 n mi at the initial forecast time t and increases linearly to 420 n mi at Day 14 and then is constant. The 12-h track segments are calculated with a Weighted-Mean Vector Motion technique in which the weighting factor is inversely proportional to the distance from the endpoint of the previous 12-h motion vector. Seventy-six percent of the ensemble storms had five or fewer member vortices. On average, the ensemble storms begin 2.5 days before the first entry of the Joint Typhoon Warning Center (JTWC) best-track file, tend to translate too slowly in the deep tropics, and persist for longer periods over land. A strict objective matching technique with the JTWC storms is combined with a second subjective procedure that is then applied to identify nearby ensemble storms that would indicate a greater likelihood of a tropical cyclone developing in that region with that track orientation. The ensemble storms identified in the ECMWF 32-day forecasts provided guidance on intraseasonal timescales of the formations and tracks of the three strongest typhoons and two other typhoons, but not for two early season typhoons and the late season Dolphin. Four strong tropical storms were predicted consistently over Week-1 through Week-4, as was one weak tropical storm. Two other weak tropical storms, three tropical cyclones that developed from precursor baroclinic systems, and three other tropical depressions were not predicted on intraseasonal timescales. At least for the strongest tropical cyclones during the peak season, the ECMWF 32-day ensemble provides

  2. Lightning Sensors for Observing, Tracking and Nowcasting Severe Weather

    Directory of Open Access Journals (Sweden)

    Colin Price

    2008-01-01

    Full Text Available Severe and extreme weather is a major natural hazard all over the world, oftenresulting in major natural disasters such as hail storms, tornados, wind storms, flash floods,forest fires and lightning damages. While precipitation, wind, hail, tornados, turbulence,etc. can only be observed at close distances, lightning activity in these damaging stormscan be monitored at all spatial scales, from local (using very high frequency [VHF]sensors, to regional (using very low frequency [VLF] sensors, and even global scales(using extremely low frequency [ELF] sensors. Using sensors that detect the radio wavesemitted by each lightning discharge, it is now possible to observe and track continuouslydistant thunderstorms using ground networks of sensors. In addition to the number oflightning discharges, these sensors can also provide information on lightningcharacteristics such as the ratio between intra-cloud and cloud-to-ground lightning, thepolarity of the lightning discharge, peak currents, charge removal, etc. It has been shownthat changes in some of these lightning characteristics during thunderstorms are oftenrelated to changes in the severity of the storms. In this paper different lightning observingsystems are described, and a few examples are provided showing how lightning may beused to monitor storm hazards around the globe, while also providing the possibility ofsupplying short term forecasts, called nowcasting.

  3. Impact of storms on coastlines: preparing for the future without forgetting the past? Examples from European coastlines using a Storm Impact Database

    Science.gov (United States)

    Ciavola, Paolo; Garnier, Emmanuel; Ferreira, Oscar; Spencer, Thomas; Armaroli, Clara

    2017-04-01

    Severe storms have historically affected many European coastlines but the impact of each storm has been evaluated in different ways in different countries, often using local socio-economic impact criteria (e.g. loss of lives and damage to properties). Although the Xynthia (2010) storm, Atlantic coast of France, was the largest coastal disaster of the last 50 years, similar events have previously impacted Europe. The 1953 storm surge in the southern North Sea, resulted in over 2000 deaths and extensive flooding and was the catalyst for post WWII improvements in flood defences and storm early warning systems. On a longer timescale, the very extreme storm of 1634 AD re-configured Wadden Sea coastlines, accompanied by thousands of deaths. Establishing patterns of coastal risk and vulnerability is greatly helped by the use of historical sources, as these allow the development of more complete time series of storm events and their impacts. The work to be presented was supported by the EU RISC-KIT (Resilience-Increasing Strategies for Coasts - toolKIT) Project. RISC-KIT (http://www.risckit.eu/np4/home.html) is a EU FP7 Collaborative project that has developed methods, tools and management approaches to reduce risk and increase resilience to low frequency, high-impact hydro-meteorological events in the coastal zone. These products will enhance forecasting, prediction and early warning capabilities, improve the assessment of long-term coastal risk and optimize the mix of prevention, mitigation and preparedness measures. We analyse historical large-scale events occurred from The Middle Ages to the 1960s at the case study sites of North Norfolk Coast (UK), the Charente-Maritime and Vendée coast (France), the Cinque Terre-Liguria (Italy), the Emilia-Romagna coast (Italy), and the Ria Formosa coast (Portugal). The work presented here uses a database of events built by the project, examining records for the last 300 years, including the characteristics of the storms as well as

  4. Sudden post-midnight decrease in equatorial F-region electron densities associated with severe magnetic storms

    Directory of Open Access Journals (Sweden)

    D. R. Lakshmi

    1997-03-01

    Full Text Available A detailed analysis of the responses of the equatorial ionosphere to a large number of severe magnetic storms shows the rapid and remarkable collapse of F-region ionisation during post-midnight hours; this is at variance with the presently accepted general behaviour of the low-latitude ionosphere during magnetic storms. This paper discusses such responses as seen in the ionosonde data at Kodaikanal (Geomagn. Lat. 0.6 N. It is also observed that during magnetic storm periods the usual increase seen in the h'F at Kodaikanal during sunset hours is considerably suppressed and these periods are also characterised by increased foF2 values. It is suggested that the primary process responsible for these dramatic pre- and post-midnight changes in foF2 during magnetic storms could be due to changes in the magnitude as well as in the direction of usual equatorial electric fields. During the post-midnight periods the change in electric-field direction from westward to eastward for a short period causes an upward E × B plasma drift resulting in increased h'F and decreased electron densities in the equatorial region. In addition, it is also suggested that the enhanced storm-induced meridional winds in the thermosphere, from the poles towards the equator, may also cause the decreases in electron density seen during post-midnight hours by spatially transporting the F-region ionisation southwards away from Kodaikanal. The paper also includes a discussion on the effects of such decreases in ionisation on low-latitude HF communications.

  5. HURRICANE AND SEVERE STORM SENTINEL (HS3) GLOBAL HAWK HIGH ALTITUDE MMIC SOUNDING RADIOMETER (HAMSR) V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The Hurricane and Severe Storm Sentinel (HS3) Global Hawk High Altitude MMIC Sounding Radiometer (HAMSR) datasets include measurements gathered by the HAMSR...

  6. Improvements of Storm Surge Modelling in the Gulf of Venice with Satellite Data: The ESA Due Esurge-Venice Project

    Science.gov (United States)

    De Biasio, F.; Bajo, M.; Vignudelli, S.; Papa, A.; della Valle, A.; Umgiesser, G.; Donlon, C.; Zecchetto, S.

    2016-08-01

    Among the most detrimental natural phenomena, storm surges heavily endanger the environment, the economy and the everyday life of sea-side countries and coastal zones. Considering that 120.000.000 people live in the Mediterranean area, with additional 200.000.000 presences in Summer for tourism purposes, the correct prediction of storm surges is crucial to avoid fatalities and economic losses. Earth Observation (EO) can play an important role in operational storm surge forecasting, yet it is not widely diffused in the storm surge community. In 2011 the European Space Agency (ESA), through its Data User Element (DUE) programme, financed two projects aimed at encouraging the uptake of EO data in this sector: eSurge and eSurge-Venice (eSV). The former was intended to address the issues of a wider users' community, while the latter was focused on a restricted geographical area: the northern Adriatic Sea and the Gulf of Venice. Among the objectives of the two projects there were a number of storm surge hindcast experiments using satellite data, to demonstrate the improvements on the surge forecast brought by EO. We report here the results of the hindcast experiments of the eSV project. They were aimed to test the sensitivity of a storm surge model to a forcing wind field modified with scatterometer data in order to reduce the bias between simulated and observed winds. Hindcast experiments were also performed to test the response of the storm surge model to the assimilation, with a dual 4D-Var system, of satellite altimetry observations as model errors of the initial state of the sea surface level. Remarkable improvements on the storm surge forecast have been obtained for what concerns the modified model wind forcing. Encouraging results have been obtained also in the assimilation experiments.

  7. A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

    KAUST Repository

    Altaf, Muhammad

    2014-08-01

    This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

  8. A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

    KAUST Repository

    Altaf, Muhammad; Butler, T.; Mayo, T.; Luo, X.; Dawson, C.; Heemink, A. W.; Hoteit, Ibrahim

    2014-01-01

    This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

  9. Assimilating InSAR Maps of Water Vapor to Improve Heavy Rainfall Forecasts: A Case Study With Two Successive Storms

    Science.gov (United States)

    Mateus, Pedro; Miranda, Pedro M. A.; Nico, Giovanni; Catalão, João.; Pinto, Paulo; Tomé, Ricardo

    2018-04-01

    Very high resolution precipitable water vapor maps obtained by the Sentinel-1 A synthetic aperture radar (SAR), using the SAR interferometry (InSAR) technique, are here shown to have a positive impact on the performance of severe weather forecasts. A case study of deep convection which affected the city of Adra, Spain, on 6-7 September 2015, is successfully forecasted by the Weather Research and Forecasting model initialized with InSAR data assimilated by the three-dimensional variational technique, with improved space and time distributions of precipitation, as observed by the local weather radar and rain gauge. This case study is exceptional because it consisted of two severe events 12 hr apart, with a timing that allows for the assimilation of both the ascending and descending satellite images, each for the initialization of each event. The same methodology applied to the network of Global Navigation Satellite System observations in Iberia, at the same times, failed to reproduce observed precipitation, although it also improved, in a more modest way, the forecast skill. The impact of precipitable water vapor data is shown to result from a direct increment of convective available potential energy, associated with important adjustments in the low-level wind field, favoring its release in deep convection. It is suggested that InSAR images, complemented by dense Global Navigation Satellite System data, may provide a new source of water vapor data for weather forecasting, since their sampling frequency could reach the subdaily scale by merging different SAR platforms, or when future geosynchronous radar missions become operational.

  10. Convective Mode and Mesoscale Heavy Rainfall Forecast Challenges during a High-Impact Weather Period along the Gulf Coast and Florida from 17-20 May 2016

    Science.gov (United States)

    Bosart, L. F.; Wallace, B. C.

    2017-12-01

    Two high-impact convective storm forecast challenges occurred between 17-20 May 2016 during NOAA's Hazardous Weather Testbed Spring Forecast Experiment (SFE) at the Storm Prediction Center. The first forecast challenge was 286 mm of unexpected record-breaking rain that fell on Vero Beach (VRB), Florida, between 1500 UTC 17 May and 0600 UTC 18 May, more than doubling the previous May daily rainfall record. The record rains in VRB occurred subsequent to the formation of a massive MCS over the central Gulf of Mexico between 0900-1000 UTC 17 May. This MCS, linked to the earlier convection associated with an anomalously strong subtropical jet (STJ) over the Gulf of Mexico, moved east-northeastward toward Florida. The second forecast challenge was a large MCS that formed over the Mexican mountains near the Texas-Mexican border, moved eastward and grew upscale prior to 1200 UTC 19 May. This MCS further strengthened offshore after 1800 UTC 19 May beneath the STJ. SPC SFE participants expected this MCS to move east-northeastward and bring heavy rain due to training echoes along the Gulf coast as far eastward as the Florida panhandle. Instead, this MCS transitioned into a bowing MCS that resembled a low-end derecho and produced a 4-6 hPa cold pool with widespread surface wind gusts between 35-50 kt. Both MCS events occurred in a large-scale baroclinic environment along the northern Gulf coast. Both MCS events responded to antecedent convection within this favorable large-scale environment. Rainfall amounts with the first heavy rain-producing MCS were severely underestimated by models and forecasters alike. The second MCS produced the greatest forecaster angst because rainfall totals were forecast too high (MCS propagated too fast) and severe wind reports were much more widespread than anticipated (because of cold pool formation). This presentation will attempt to untangle what happened and why it happened.

  11. Dust Storm Feature Identification and Tracking from 4D Simulation Data

    Science.gov (United States)

    Yu, M.; Yang, C. P.

    2016-12-01

    Dust storms cause significant damage to health, property and the environment worldwide every year. To help mitigate the damage, dust forecasting models simulate and predict upcoming dust events, providing valuable information to scientists, decision makers, and the public. Normally, the model simulations are conducted in four-dimensions (i.e., latitude, longitude, elevation and time) and represent three-dimensional (3D), spatial heterogeneous features of the storm and its evolution over space and time. This research investigates and proposes an automatic multi-threshold, region-growing based identification algorithm to identify critical dust storm features, and track the evolution process of dust storm events through space and time. In addition, a spatiotemporal data model is proposed, which can support the characterization and representation of dust storm events and their dynamic patterns. Quantitative and qualitative evaluations for the algorithm are conducted to test the sensitivity, and capability of identify and track dust storm events. This study has the potential to assist a better early warning system for decision-makers and the public, thus making hazard mitigation plans more effective.

  12. Probabilistic evaluation of decadal prediction skill regarding Northern Hemisphere winter storms

    Directory of Open Access Journals (Sweden)

    Tim Kruschke

    2016-12-01

    Full Text Available Winter wind storms related to intense extra-tropical cyclones are meteorological extreme events, often with major impacts on economy and human life, especially for Europe and the mid-latitudes. Hence, skillful decadal predictions regarding the frequency of their occurrence would be of great socio-economic value. The present paper extends the study of Kruschke et al. (2014 in several aspects. First, this study is situated in a more impact oriented context by analyzing the frequency of potentially damaging wind storm events instead of targeting at cyclones as general meteorological features which was done by Kruschke et al. (2014. Second, this study incorporates more data sets by analyzing five decadal hindcast experiments – 41 annual (1961–2001 initializations integrated for ten years each – set up with different initialization strategies. However, all experiments are based on the Max-Planck-Institute Earth System Model in a low-resolution configuration (MPI-ESM-LR. Differing combinations of these five experiments allow for more robust estimates of predictive skill (due to considerably larger ensemble size and systematic comparisons of the underlying initialization strategies. Third, the hindcast experiments are corrected for model bias and potential drifts over lead time by means of a novel parametric approach, accounting for non-stationary model drifts. We analyze whether skillful probabilistic three-category forecasts (enhanced, normal or decreased can be provided regarding winter (ONDJFM wind storm frequencies over the Northern Hemisphere (NH. Skill is assessed by using climatological probabilities and uninitialized transient simulations as reference forecasts. It is shown that forecasts of average winter wind storm frequencies for winters 2–5 and winters 2–9 are skillful over large parts of the NH. However, most of this skill is associated with external forcing from transient greenhouse gas and aerosol concentrations

  13. An Extensive Study on Dynamical aspects of Dust Storm over the United Arab Emirates during 18-20 March 2012

    Science.gov (United States)

    Basha, Ghouse; Phanikumar, Devulapalli V.; Ouarda, Taha B. M. J.

    2015-04-01

    On 18 March 2012, a super dust storm event occurred over Middle East (ME) and lasted for several hours. Following to this, another dust storm occurred on early morning of 20 March 2012 with almost higher intensity. Both these storms reduced the horizontal visibility to few hundreds of meters and represented as one of the most intense and long duration dust storms over United Arab Emirates (UAE) in recent times. These storms also reduced the air quality in most parts of the ME implying the shutdown of Airports, schools and hundreds of people were hospitalized with respirational problems. In the context of the above, we have made a detailed study on the dynamical processes leading to triggering of dust storm over UAE and neighboring regions. We have also analyzed its impact on surface, and vertical profiles of background parameters and aerosols during the dust storm period by using ground-based, space borne, dust forecasting model, and reanalysis data sets. The synoptic and dynamic conditions responsible for the occurrence of the dust storm are discussed extensively by using European Centre for Medium-Range Weather Forecasts (ECMWF) ERA interim reanalysis data sets. The Impact of dust storm on surface and upper air radiosonde measurements and aerosol optical properties are also investigated before, during and after the dust storm event. During the dust storm, surface temperature decreased by 15oC when compared to before and after the event. PM10 values significantly increased maximum of about 1600µg/m3. Spatial variation of Aerosol Optical Depth (AOD) from Moderate-resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) aerosol index (AI) exhibited very high values during the event and source region can be identified of dust transport to our region with this figure. The total attenuated backscatter at 550nm from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite shows the vertical extent of dust up to 8km. The dynamics of this event is

  14. Electrical storm in patients with implantable cardioverter-defibrillators: can it be forecast?

    Science.gov (United States)

    Emkanjoo, Zahra; Alihasani, Narges; Alizadeh, Abolfath; Tayyebi, Mohammad; Bonakdar, Hamid; Barakpour, Hamid; Sadr-Ameli, Mohammad Ali

    2009-01-01

    The aim of this retrospective study was to determine the prevalence and predictors of electrical storm in 227 patients who had received implantable cardioverter-defibrillators (ICDs) and had been monitored for 31.7 +/- 15.6 months. Of these, 174 (77%) were men. The mean age was 55.8 +/- 15.5 years (range, 20-85 yr), and the mean left ventricular ejection fraction (LVEF) was 0.30 +/- 0.14. One hundred forty-six of the patients (64%) had underlying coronary artery disease. Cardioverter-defibrillators were implanted for secondary (80%) and primary (20%) prevention. Of the 227 patients, 117 (52%) experienced events that required ICD therapy. Thirty patients (mean age, 57.26 +/- 14.3 yr) had > or = 3 episodes requiring ICD therapy in a 24-hour period and were considered to have electrical storm. The mean number of events was 12.75 +/- 15 per patient. Arrhythmia-clustering occurred an average of 6.1 +/- 6.7 months after ICD implantation. Clinical variables with the most significant association with electrical storm were low LVEF (P = 0.04; hazard ratio of 0.261, and 95% confidence interval of 0.08-0.86) and higher use of class IA antiarrhythmic drugs (P = 0.018, hazard ratio of 3.84, and 95% confidence interval of 1.47-10.05). Amiodarone treatment and use of beta-blockers were not significant predictors when subjected to multivariate analysis. We conclude that electrical storm is most likely to occur in patients with lower LVEF and that the use of Class IA antiarrhythmic drugs is a risk factor.

  15. Ionospheric Data Assimilation and Targeted Observation Strategies: Proof of Concept Analysis in a Geomagnetic Storm Event

    Science.gov (United States)

    Kostelich, Eric; Durazo, Juan; Mahalov, Alex

    2017-11-01

    The dynamics of the ionosphere involve complex interactions between the atmosphere, solar wind, cosmic radiation, and Earth's magnetic field. Geomagnetic storms arising from solar activity can perturb these dynamics sufficiently to disrupt radio and satellite communications. Efforts to predict ``space weather,'' including ionospheric dynamics, require the development of a data assimilation system that combines observing systems with appropriate forecast models. This talk will outline a proof-of-concept targeted observation strategy, consisting of the Local Ensemble Transform Kalman Filter, coupled with the Thermosphere Ionosphere Electrodynamics Global Circulation Model, to select optimal locations where additional observations can be made to improve short-term ionospheric forecasts. Initial results using data and forecasts from the geomagnetic storm of 26-27 September 2011 will be described. Work supported by the Air Force Office of Scientific Research (Grant Number FA9550-15-1-0096) and by the National Science Foundation (Grant Number DMS-0940314).

  16. The impact of dust storms on the Arabian Peninsula and the Red Sea

    KAUST Repository

    Jish Prakash, P.

    2015-01-12

    Located in the dust belt, the Arabian Peninsula is a major source of atmospheric dust. Frequent dust outbreaks and some 15 to 20 dust storms per year have profound effects on all aspects of human activity and natural processes in this region. To quantify the effect of severe dust events on radiation fluxes and regional climate characteristics, we simulated the storm that occurred from 18 to 20 March 2012 using a regional weather research forecast model fully coupled with the chemistry/aerosol module (WRF–Chem). This storm swept over a remarkably large area affecting the entire Middle East, northeastern Africa, Afghanistan, and Pakistan. It was caused by a southward propagating cold front, and the associated winds activated the dust production in river valleys of the lower Tigris and Euphrates in Iraq; the coastal areas in Kuwait, Iran, and the United Arab Emirates; the Rub al Khali, An Nafud, and Ad Dahna deserts; and along the Red Sea coast on the west side of the Arabian Peninsula. Our simulation results compare well with available ground-based and satellite observations. We estimate the total amount of dust generated by the storm to have reached 94 Mt. Approximately 78% of this dust was deposited within the calculation domain. The Arabian Sea and Persian Gulf received 5.3 Mt and the Red Sea 1.2 Mt of dust. Dust particles bring nutrients to marine ecosystems, which is especially important for the oligotrophic Northern Red Sea. However, their contribution to the nutrient balance in the Red Sea remains largely unknown. By scaling the effect of one storm to the number of dust storms observed annually over the Red Sea, we estimate the annual dust deposition to the Red Sea, associated with major dust storms, to be 6 Mt.

  17. The impact of dust storms on the Arabian Peninsula and the Red Sea

    KAUST Repository

    Jish Prakash, P.; Stenchikov, Georgiy L.; Kalenderski, Stoitchko; Osipov, Sergey; Bangalath, Hamza Kunhu

    2015-01-01

    Located in the dust belt, the Arabian Peninsula is a major source of atmospheric dust. Frequent dust outbreaks and some 15 to 20 dust storms per year have profound effects on all aspects of human activity and natural processes in this region. To quantify the effect of severe dust events on radiation fluxes and regional climate characteristics, we simulated the storm that occurred from 18 to 20 March 2012 using a regional weather research forecast model fully coupled with the chemistry/aerosol module (WRF–Chem). This storm swept over a remarkably large area affecting the entire Middle East, northeastern Africa, Afghanistan, and Pakistan. It was caused by a southward propagating cold front, and the associated winds activated the dust production in river valleys of the lower Tigris and Euphrates in Iraq; the coastal areas in Kuwait, Iran, and the United Arab Emirates; the Rub al Khali, An Nafud, and Ad Dahna deserts; and along the Red Sea coast on the west side of the Arabian Peninsula. Our simulation results compare well with available ground-based and satellite observations. We estimate the total amount of dust generated by the storm to have reached 94 Mt. Approximately 78% of this dust was deposited within the calculation domain. The Arabian Sea and Persian Gulf received 5.3 Mt and the Red Sea 1.2 Mt of dust. Dust particles bring nutrients to marine ecosystems, which is especially important for the oligotrophic Northern Red Sea. However, their contribution to the nutrient balance in the Red Sea remains largely unknown. By scaling the effect of one storm to the number of dust storms observed annually over the Red Sea, we estimate the annual dust deposition to the Red Sea, associated with major dust storms, to be 6 Mt.

  18. Forecasting Lightning Threat using Cloud-resolving Model Simulations

    Science.gov (United States)

    McCaul, E. W., Jr.; Goodman, S. J.; LaCasse, K. M.; Cecil, D. J.

    2009-01-01

    As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\\dgc\\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating

  19. 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.

  20. Modelling the economic losses of historic and present-day high-impact winter storms in Switzerland

    Science.gov (United States)

    Welker, Christoph; Stucki, Peter; Bresch, David; Dierer, Silke; Martius, Olivia; Brönnimann, Stefan

    2014-05-01

    Severe winter storms such as "Vivian" in February 1990 and "Lothar" in December 1999 are among the most destructive meteorological hazards in Switzerland. Disaster severity resulting from such windstorms is attributable, on the one hand, to hazardous weather conditions such as high wind gust speeds; and on the other hand to socio-economic factors such as population density, distribution of values at risk, and damage susceptibility. For present-day winter storms, the data basis is generally good to describe the meteorological development and wind forces as well as the associated socio-economic impacts. In contrast, the information on historic windstorms is overall sparse and the available historic weather and loss reports mostly do not provide quantitative information. This study illustrates a promising technique to simulate the economic impacts of both historic and present winter storms in Switzerland since end of the 19th century. Our approach makes use of the novel Twentieth Century Reanalysis (20CR) spanning 1871-present. The 2-degree spatial resolution of the global 20CR dataset is relatively coarse. Thus, the complex orography of Switzerland is not realistically represented, which has considerable ramifications for the representation of wind systems that are strongly influenced by the local orography, such as Föhn winds. Therefore, a dynamical downscaling of the 20CR to 3 km resolution using the Weather Research and Forecasting (WRF) model was performed, for in total 40 high-impact winter storms in Switzerland since 1871. Based on the downscaled wind gust speeds and the climada loss model, the estimated economic losses were calculated at municipality level for current economic and social conditions. With this approach, we find an answer to the question what would be the economic losses of e.g. a hazardous Föhn storm - which occurred in northern Switzerland in February 1925 - today, i.e. under current socio-economic conditions. Encouragingly, the pattern of

  1. 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.

  2. An analysis of simulated and observed storm characteristics

    Science.gov (United States)

    Benestad, R. E.

    2010-09-01

    A calculus-based cyclone identification (CCI) method has been applied to the most recent re-analysis (ERAINT) from the European Centre for Medium-range Weather Forecasts and results from regional climate model (RCM) simulations. The storm frequency for events with central pressure below a threshold value of 960-990hPa were examined, and the gradient wind from the simulated storm systems were compared with corresponding estimates from the re-analysis. The analysis also yielded estimates for the spatial extent of the storm systems, which was also included in the regional climate model cyclone evaluation. A comparison is presented between a number of RCMs and the ERAINT re-analysis in terms of their description of the gradient winds, number of cyclones, and spatial extent. Furthermore, a comparison between geostrophic wind estimated though triangules of interpolated or station measurements of SLP is presented. Wind still represents one of the more challenging variables to model realistically.

  3. Dust modelling and forecasting in the Barcelona Supercomputing Center: Activities and developments

    Energy Technology Data Exchange (ETDEWEB)

    Perez, C; Baldasano, J M; Jimenez-Guerrero, P; Jorba, O; Haustein, K; Basart, S [Earth Sciences Department. Barcelona Supercomputing Center. Barcelona (Spain); Cuevas, E [Izanaa Atmospheric Research Center. Agencia Estatal de Meteorologia, Tenerife (Spain); Nickovic, S [Atmospheric Research and Environment Branch, World Meteorological Organization, Geneva (Switzerland)], E-mail: carlos.perez@bsc.es

    2009-03-01

    The Barcelona Supercomputing Center (BSC) is the National Supercomputer Facility in Spain, hosting MareNostrum, one of the most powerful Supercomputers in Europe. The Earth Sciences Department of BSC operates daily regional dust and air quality forecasts and conducts intensive modelling research for short-term operational prediction. This contribution summarizes the latest developments and current activities in the field of sand and dust storm modelling and forecasting.

  4. Dust modelling and forecasting in the Barcelona Supercomputing Center: Activities and developments

    International Nuclear Information System (INIS)

    Perez, C; Baldasano, J M; Jimenez-Guerrero, P; Jorba, O; Haustein, K; Basart, S; Cuevas, E; Nickovic, S

    2009-01-01

    The Barcelona Supercomputing Center (BSC) is the National Supercomputer Facility in Spain, hosting MareNostrum, one of the most powerful Supercomputers in Europe. The Earth Sciences Department of BSC operates daily regional dust and air quality forecasts and conducts intensive modelling research for short-term operational prediction. This contribution summarizes the latest developments and current activities in the field of sand and dust storm modelling and forecasting.

  5. Coupling between the lower and middle atmosphere observed during a very severe cyclonic storm 'Madi'

    Science.gov (United States)

    Hima Bindu, H.; Venkat Ratnam, M.; Yesubabu, V.; Narayana Rao, T.; Eswariah, S.; Naidu, C. V.; Vijaya Bhaskara Rao, S.

    2018-04-01

    Synoptic-scale systems like cyclones can generate broad spectrum of waves, which propagate from its source to the middle atmosphere. Coupling between the lower and middle atmosphere over Tirupati (13.6°N, 79.4°E) is studied during a very severe cyclonic storm 'Madi' (06-13 December 2013) using Weather Research and Forecast (WRF) model assimilated fields and simultaneous meteor radar observations. Since high temporal and spatial measurements are difficult to obtain during these disturbances, WRF model simulations are obtained by assimilating conventional and satellite observations using 3DVAR technique. The obtained outputs are validated for their consistency in predicting cyclone track and vertical structure by comparing them with independent observations. The good agreement between the assimilated outputs and independent observations prompted us to use the model outputs to investigate the gravity waves (GWs) and tides over Tirupati. GWs with the periods 1-5 h are observed with clear downward phase propagation in the lower stratosphere. These upward propagating waves obtained from the model are also noticed in the meteor radar horizontal wind observations in the MLT region (70-110 km). Interestingly, enhancement in the tidal activity in both the zonal and meridional winds in the mesosphere and lower thermosphere (MLT) region is noticed during the peak cyclonic activity except the suppression of semi-diurnal tide in meridional wind. A very good agreement in the tidal activity is also observed in the horizontal winds in the troposphere and lower stratosphere from the WRF model outputs and ERA5. These results thus provide evidence on the vertical coupling of lower and middle atmosphere induced by the tropical cyclone.

  6. A European precipitation index for extreme rain-storm and flash flood early warning

    OpenAIRE

    ALFIERI LORENZO; THIELEN DEL POZO Jutta

    2012-01-01

    Extreme rain-storms are known for triggering devastating flash floods in various regions of Europe and particularly along the Mediterranean coasts. Despite recent notable advances in weather forecasting, most operational early warning systems for extreme rainstorms and flash floods are based on rainfall estimation, rather than on forecasts. As a result, warning lead times are bounded to few hours and warnings are usually issued when the event is already taking place. This work proposes a n...

  7. Development of High-Resolution Dynamic Dust Source Function - A Case Study with a Strong Dust Storm in a Regional Model

    Science.gov (United States)

    Kim, Dongchul; Chin, Mian; Kemp, Eric M.; Tao, Zhining; Peters-Lidard, Christa D.; Ginoux, Paul

    2017-01-01

    A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 0203 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events.

  8. Development of High-Resolution Dynamic Dust Source Function -A Case Study with a Strong Dust Storm in a Regional Model.

    Science.gov (United States)

    Kim, Dongchul; Chin, Mian; Kemp, Eric M; Tao, Zhining; Peters-Lidard, Christa D; Ginoux, Paul

    2017-06-01

    A high-resolution dynamic dust source has been developed in the NASA Unified-Weather Research and Forecasting (NU-WRF) model to improve the existing coarse static dust source. In the new dust source map, topographic depression is in 1-km resolution and surface bareness is derived using the Normalized Difference Vegetation Index (NDVI) data from Moderate Resolution Imaging Spectroradiometer (MODIS). The new dust source better resolves the complex topographic distribution over the Western United States where its magnitude is higher than the existing, coarser resolution static source. A case study is conducted with an extreme dust storm that occurred in Phoenix, Arizona in 02-03 UTC July 6, 2011. The NU-WRF model with the new high-resolution dynamic dust source is able to successfully capture the dust storm, which was not achieved with the old source identification. However the case study also reveals several challenges in reproducing the time evolution of the short-lived, extreme dust storm events.

  9. HURRICANE AND SEVERE STORM SENTINEL (HS3) GLOBAL HAWK ADVANCED VERTICAL ATMOSPHERIC PROFILING SYSTEM (AVAPS) DROPSONDE SYSTEM V2

    Data.gov (United States)

    National Aeronautics and Space Administration — The Hurricane and Severe Storm Sentinel (HS3) Global Hawk Advanced Vertical Atmospheric Profiling System (AVAPS) Dropsonde System dataset was collected by the...

  10. Ionospheric Storm Effects and Equatorial Plasma Irregularities During the 17-18 March 2015 Event

    Science.gov (United States)

    Zhou, Yun-Liang; Luhr, Hermann; Xiong, Chao; Pfaff, Robert F.

    2016-01-01

    The intense magnetic storm on 17-18 March 2015 caused large disturbances of the ionosphere. Based on the plasma density (Ni) observations performed by the Swarm fleet of satellites, the Gravity Recovery and Climate Experiment mission, and the Communications/Navigation Outage Forecasting System satellite, we characterize the storm-related perturbations at low latitudes. All these satellites sampled the ionosphere in morning and evening time sectors where large modifications occurred. Modifications of plasma density are closely related to changes of the solar wind merging electric field (E (sub m)). We consider two mechanisms, prompt penetration electric field (PPEF) and disturbance dynamo electric field (DDEF), as the main cause for the Ni redistribution, but effects of meridional wind are also taken into account. At the start of the storm main phase, the PPEF is enhancing plasma density on the dayside and reducing it on the nightside. Later, DDEF takes over and causes the opposite reaction. Unexpectedly, there appears during the recovery phase a strong density enhancement in the morning/pre-noon sector and a severe Ni reduction in the afternoon/evening sector, and we suggest a combined effect of vertical plasma drift, and meridional wind is responsible for these ionospheric storm effects. Different from earlier studies about this storm, we also investigate the influence of storm dynamics on the initiation of equatorial plasma irregularities (EPIs). Shortly after the start of the storm main phase, EPIs appear in the post-sunset sector. As a response to a short-lived decline of E (sub m), EPI activity appears in the early morning sector. Following the second start of the main phase, EPIs are generated for a few hours in the late evening sector. However, for the rest of the storm main phase, no more EPIs are initiated for more than 12 hours. Only after the onset of recovery phase does EPI activity start again in the post-midnight sector, lasting more than 7 hours

  11. WRF-Chem Model Simulations of Arizona Dust Storms

    Science.gov (United States)

    Mohebbi, A.; Chang, H. I.; Hondula, D.

    2017-12-01

    The online Weather Research and Forecasting model with coupled chemistry module (WRF-Chem) is applied to simulate the transport, deposition and emission of the dust aerosols in an intense dust outbreak event that took place on July 5th, 2011 over Arizona. Goddard Chemistry Aerosol Radiation and Transport (GOCART), Air Force Weather Agency (AFWA), and University of Cologne (UoC) parameterization schemes for dust emission were evaluated. The model was found to simulate well the synoptic meteorological conditions also widely documented in previous studies. The chemistry module performance in reproducing the atmospheric desert dust load was evaluated using the horizontal field of the Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectro (MODIS) radiometer Terra/Aqua and Aerosol Robotic Network (AERONET) satellites employing standard Dark Target (DT) and Deep Blue (DB) algorithms. To assess the temporal variability of the dust storm, Particulate Matter mass concentration data (PM10 and PM2.5) from Arizona Department of Environmental Quality (AZDEQ) ground-based air quality stations were used. The promising performance of WRF-Chem indicate that the model is capable of simulating the right timing and loading of a dust event in the planetary-boundary-layer (PBL) which can be used to forecast approaching severe dust events and to communicate an effective early warning.

  12. Coupled atmosphere-ocean-wave simulations of a storm event over the Gulf of Lion and Balearic Sea

    Science.gov (United States)

    Renault, Lionel; Chiggiato, Jacopo; Warner, John C.; Gomez, Marta; Vizoso, Guillermo; Tintore, Joaquin

    2012-01-01

    The coastal areas of the North-Western Mediterranean Sea are one of the most challenging places for ocean forecasting. This region is exposed to severe storms events that are of short duration. During these events, significant air-sea interactions, strong winds and large sea-state can have catastrophic consequences in the coastal areas. To investigate these air-sea interactions and the oceanic response to such events, we implemented the Coupled Ocean-Atmosphere-Wave-Sediment Transport Modeling System simulating a severe storm in the Mediterranean Sea that occurred in May 2010. During this event, wind speed reached up to 25 m.s-1 inducing significant sea surface cooling (up to 2°C) over the Gulf of Lion (GoL) and along the storm track, and generating surface waves with a significant height of 6 m. It is shown that the event, associated with a cyclogenesis between the Balearic Islands and the GoL, is relatively well reproduced by the coupled system. A surface heat budget analysis showed that ocean vertical mixing was a major contributor to the cooling tendency along the storm track and in the GoL where turbulent heat fluxes also played an important role. Sensitivity experiments on the ocean-atmosphere coupling suggested that the coupled system is sensitive to the momentum flux parameterization as well as air-sea and air-wave coupling. Comparisons with available atmospheric and oceanic observations showed that the use of the fully coupled system provides the most skillful simulation, illustrating the benefit of using a fully coupled ocean-atmosphere-wave model for the assessment of these storm events.

  13. On the impact of wind on the development of wave field during storm Britta

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Du, Jianting; Bolaños, Rodolfo

    2017-01-01

    The observation of extreme waves at FINO 1 during storm Britta on the 1st November 2006 has initiated a series of research studies regarding the mechanisms behind. The roles of stability and the presence of the open cell structures have been previously investigated but not conclusive. To improve...... our understanding of these processes, which are essential for a good forecast of similarly important events offshore, this study revisits the development of storm Britta using an atmospheric and wave coupled modeling system, wind and wave measurements from ten stations across the North Sea, cloud...... images and Synthetic Aperture Radar (SAR) data. It is found here that a standard state-of-the-art model is capable of capturing the important characteristics of a major storm like Britta, including the storm path, storm peak wind speed, the open cells, and peak significant wave height (H s ) for open sea...

  14. Rapidly updated hyperspectral sounding and imaging data for severe storm prediction

    Science.gov (United States)

    Bingham, Gail; Jensen, Scott; Elwell, John; Cardon, Joel; Crain, David; Huang, Hung-Lung (Allen); Smith, William L.; Revercomb, Hank E.; Huppi, Ronald J.

    2013-09-01

    Several studies have shown that a geostationary hyperspectral imager/sounder can provide the most significant value increase in short term, regional numerical prediction weather models over a range of other options. In 1998, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) proposal was selected by NASA as the New Millennium Earth Observation 3 program over several other geostationary instrument development proposals. After the EO3 GIFTS flight demonstration program was changed to an Engineering Development Unit (EDU) due to funding limitations by one of the partners, the EDU was subjected to flight-like thermal vacuum calibration and testing and successfully validated the breakthrough technologies needed to make a successful observatory. After several government stops and starts, only EUMETSAT's Meteosat Third Generation (MTG-S) sounder is in operational development. Recently, a commercial partnership has been formed to fill the significant data gap. AsiaSat has partnered with GeoMetWatch (GMW)1 to fund the development and launch of the Sounding and Tracking Observatory for Regional Meteorology (STORMTM) sensor, a derivative of the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) EDU that was designed, built, and tested by Utah State University (USU). STORMTM combines advanced technologies to observe surface thermal properties, atmospheric weather, and chemistry variables in four dimensions to provide high vertical resolution temperature and moisture sounding information, with the fourth dimension (time) provided by the geosynchronous satellite platform ability to measure a location as often as desired. STORMTM will enhance the polar orbiting imaging and sounding measurements by providing: (1) a direct measure of moisture flux and altitude-resolved water vapor and cloud tracer winds throughout the troposphere, (2) an observation of the time varying atmospheric thermodynamics associated with storm system development, and (3) the

  15. Cyclone track forecasting based on satellite images using artificial neural networks

    OpenAIRE

    Kovordanyi, Rita; Roy, Chandan

    2009-01-01

    Many places around the world are exposed to tropical cyclones and associated storm surges. In spite of massive efforts, a great number of people die each year as a result of cyclone events. To mitigate this damage, improved forecasting techniques must be developed. The technique presented here uses artificial neural networks to interpret NOAA-AVHRR satellite images. A multi-layer neural network, resembling the human visual system, was trained to forecast the movement of cyclones based on sate...

  16. Ensemble Sensitivity Analysis of a Severe Downslope Windstorm in Complex Terrain: Implications for Forecast Predictability Scales and Targeted Observing Networks

    Science.gov (United States)

    2013-09-01

    observations, linear regression finds the straight line that explains the linear relationship of the sample. This line is given by the equation y = mx + b...SENSITIVITY ANALYSIS OF A SEVERE DOWNSLOPE WINDSTORM IN COMPLEX TERRAIN: IMPLICATIONS FOR FORECAST PREDICTABILITY SCALES AND TARGETED OBSERVING...SENSITIVITY ANALYSIS OF A SEVERE DOWNSLOPE WINDSTORM IN COMPLEX TERRAIN: IMPLICATIONS FOR FORECAST PREDICTABILITY SCALES AND TARGETED OBSERVING NETWORKS

  17. Mid-latitude thermospheric wind changes during the St. Patrick's Day storm of 2015 observed by two Fabry-Perot interferometers in China

    Science.gov (United States)

    Huang, Cong; Xu, Ji-Yao; Zhang, Xiao-Xin; Liu, Dan-Dan; Yuan, Wei; Jiang, Guo-Ying

    2018-04-01

    In this work, we utilize thermospheric wind observations by the Fabry-Perot interferometers (FPI) from the Kelan (KL) station (38.7°N, 111.6°E, Magnetic Latitude: 28.9°N) and the Xinglong (XL) station (40.2°N, 117.4°E, Magnetic Latitude: 30.5°N) in central China during the St. Patrick's Day storm (from Mar. 17 to Mar. 19) of 2015 to analyze thermospheric wind disturbances and compare observations with the Horizontal Wind Model 2007 (HWM07). The results reveal that the wind measurements at KL show very similar trends to those at XL. Large enhancements are seen in both the westward and equatorward winds after the severe geomagnetic storm occurred. The westward wind speed increased to a peak value of 75 m/s and the equatorward wind enhanced to a peak value of over 100 m/s. There also exist obvious poleward disturbances in the meridional winds during Mar. 17 to Mar. 19. According to the comparison with HWM07, there exist evident wind speed and temporal differences between FPI-winds and the model outputs in this severe geomagnetic storm. The discrepancies between the observations and HWM07 imply that the empirical model should be used carefully in wind disturbance forecast during large geomagnetic storms and more investigations between measurements and numerical models are necessary in future studies.

  18. Simultaneous Radar and Satellite Data Storm-Scale Assimilation Using an Ensemble Kalman Filter Approach for 24 May 2011

    Science.gov (United States)

    Jones, Thomas A.; Stensrud, David; Wicker, Louis; Minnis, Patrick; Palikonda, Rabindra

    2015-01-01

    Assimilating high-resolution radar reflectivity and radial velocity into convection-permitting numerical weather prediction models has proven to be an important tool for improving forecast skill of convection. The use of satellite data for the application is much less well understood, only recently receiving significant attention. Since both radar and satellite data provide independent information, combing these two sources of data in a robust manner potentially represents the future of high-resolution data assimilation. This research combines Geostationary Operational Environmental Satellite 13 (GOES-13) cloud water path (CWP) retrievals with Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity and radial velocity to examine the impacts of assimilating each for a severe weather event occurring in Oklahoma on 24 May 2011. Data are assimilated into a 3-km model using an ensemble adjustment Kalman filter approach with 36 members over a 2-h assimilation window between 1800 and 2000 UTC. Forecasts are then generated for 90 min at 5-min intervals starting at 1930 and 2000 UTC. Results show that both satellite and radar data are able to initiate convection, but that assimilating both spins up a storm much faster. Assimilating CWP also performs well at suppressing spurious precipitation and cloud cover in the model as well as capturing the anvil characteristics of developed storms. Radar data are most effective at resolving the 3D characteristics of the core convection. Assimilating both satellite and radar data generally resulted in the best model analysis and most skillful forecast for this event.

  19. A Synoptic- and Planetary-Scale Analysis of Widespread North American Ice Storms

    Science.gov (United States)

    McCray, C.; Gyakum, J. R.; Atallah, E.

    2017-12-01

    Freezing rain can have devastating impacts, particularly when it persists for many hours. Predicting the precise temperature stratification necessary for long duration freezing rain events remains an important forecast challenge. To better elucidate the conditions responsible for the most severe events, we concentrate on surface observations of long-duration (6 or more hours) freezing rain events over North America from 1979-2016. Furthermore, we analyze cases in which multiple stations observe long-duration events simultaneously. Following these cases over successive days allows us to generate maps of freezing rain "tracks." We then categorize recurring geographic patterns to examine the meteorological conditions leading to these events. While freezing rain is most frequently observed in the northeastern United States and southeastern Canada, long-duration events have affected areas as far south as the Gulf Coast. Notably, a disproportionately large number of very long duration (18 or more hours) events have occurred in the Southern Plains states relative to the climatological annual frequency of freezing rain there. Classification of individual cases shows that most of these very long duration events are associated with a recurring pattern which produces freezing rain along a southwest-northeast swath from Texas/Oklahoma into the northeastern U.S. and eastern Canada. Storms classified within this pattern include the January 1998 and December 2013 ice storms. While this pattern is the most widespread, additional spatially extensive patterns occur. One of these areas extends from the Southern Plains eastward along the Gulf Coast to Georgia and the Carolinas. A third category of events extends from the Upper Midwest into the northeastern U.S. and southeastern Canada. The expansive areal extent and long duration of these events make them especially problematic. An analysis of the planetary- to synoptic-scale settings responsible for these cases and the differences

  20. The 2015 Summer Solstice Storm: One of the Major Geomagnetic Storms of Solar Cycle 24 Observed at Ground Level

    Science.gov (United States)

    Augusto, C. R. A.; Navia, C. E.; de Oliveira, M. N.; Nepomuceno, A. A.; Raulin, J. P.; Tueros, E.; de Mendonça, R. R. S.; Fauth, A. C.; Vieira de Souza, H.; Kopenkin, V.; Sinzi, T.

    2018-05-01

    We report on the 22 - 23 June 2015 geomagnetic storm that occurred at the summer solstice. There have been fewer intense geomagnetic storms during the current solar cycle, Solar Cycle 24, than in the previous cycle. This situation changed after mid-June 2015, when one of the largest solar active regions (AR 12371) of Solar Cycle 24 that was located close to the central meridian, produced several coronal mass ejections (CMEs) associated with M-class flares. The impact of these CMEs on the Earth's magnetosphere resulted in a moderate to severe G4-class geomagnetic storm on 22 - 23 June 2015 and a G2 (moderate) geomagnetic storm on 24 June. The G4 solstice storm was the second largest (so far) geomagnetic storm of Cycle 24. We highlight the ground-level observations made with the New-Tupi, Muonca, and the CARPET El Leoncito cosmic-ray detectors that are located within the South Atlantic Anomaly (SAA) region. These observations are studied in correlation with data obtained by space-borne detectors (ACE, GOES, SDO, and SOHO) and other ground-based experiments. The CME designations are taken from the Computer Aided CME Tracking (CACTus) automated catalog. As expected, Forbush decreases (FD) associated with the passing CMEs were recorded by these detectors. We note a peculiar feature linked to a severe geomagnetic storm event. The 21 June 2015 CME 0091 (CACTus CME catalog number) was likely associated with the 22 June summer solstice FD event. The angular width of CME 0091 was very narrow and measured {˜} 56° degrees seen from Earth. In most cases, only CME halos and partial halos lead to severe geomagnetic storms. We perform a cross-check analysis of the FD events detected during the rise phase of Solar Cycle 24, the geomagnetic parameters, and the CACTus CME catalog. Our study suggests that narrow angular-width CMEs that erupt in a westward direction from the Sun-Earth line can lead to moderate and severe geomagnetic storms. We also report on the strong solar proton

  1. Advances in electric power and energy systems load and price forecasting

    CERN Document Server

    2017-01-01

    A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally. Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world’s foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial ar nas. Short-run forecasting of electricity prices has become nece...

  2. Short-term wind power combined forecasting based on error forecast correction

    International Nuclear Information System (INIS)

    Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

    2016-01-01

    Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

  3. Solar Storm GIC Forecasting: Solar Shield Extension Development of the End-User Forecasting System Requirements

    Science.gov (United States)

    Pulkkinen, A.; Mahmood, S.; Ngwira, C.; Balch, C.; Lordan, R.; Fugate, D.; Jacobs, W.; Honkonen, I.

    2015-01-01

    A NASA Goddard Space Flight Center Heliophysics Science Division-led team that includes NOAA Space Weather Prediction Center, the Catholic University of America, Electric Power Research Institute (EPRI), and Electric Research and Management, Inc., recently partnered with the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) to better understand the impact of Geomagnetically Induced Currents (GIC) on the electric power industry. This effort builds on a previous NASA-sponsored Applied Sciences Program for predicting GIC, known as Solar Shield. The focus of the new DHS S&T funded effort is to revise and extend the existing Solar Shield system to enhance its forecasting capability and provide tailored, timely, actionable information for electric utility decision makers. To enhance the forecasting capabilities of the new Solar Shield, a key undertaking is to extend the prediction system coverage across Contiguous United States (CONUS), as the previous version was only applicable to high latitudes. The team also leverages the latest enhancements in space weather modeling capacity residing at Community Coordinated Modeling Center to increase the Technological Readiness Level, or Applications Readiness Level of the system http://www.nasa.gov/sites/default/files/files/ExpandedARLDefinitions4813.pdf.

  4. Depth-area-duration characteristics of storm rainfall in Texas using Multi-Sensor Precipitation Estimates

    Science.gov (United States)

    McEnery, J. A.; Jitkajornwanich, K.

    2012-12-01

    This presentation will describe the methodology and overall system development by which a benchmark dataset of precipitation information has been used to characterize the depth-area-duration relations in heavy rain storms occurring over regions of Texas. Over the past two years project investigators along with the National Weather Service (NWS) West Gulf River Forecast Center (WGRFC) have developed and operated a gateway data system to ingest, store, and disseminate NWS multi-sensor precipitation estimates (MPE). As a pilot project of the Integrated Water Resources Science and Services (IWRSS) initiative, this testbed uses a Standard Query Language (SQL) server to maintain a full archive of current and historic MPE values within the WGRFC service area. These time series values are made available for public access as web services in the standard WaterML format. Having this volume of information maintained in a comprehensive database now allows the use of relational analysis capabilities within SQL to leverage these multi-sensor precipitation values and produce a valuable derivative product. The area of focus for this study is North Texas and will utilize values that originated from the West Gulf River Forecast Center (WGRFC); one of three River Forecast Centers currently represented in the holdings of this data system. Over the past two decades, NEXRAD radar has dramatically improved the ability to record rainfall. The resulting hourly MPE values, distributed over an approximate 4 km by 4 km grid, are considered by the NWS to be the "best estimate" of rainfall. The data server provides an accepted standard interface for internet access to the largest time-series dataset of NEXRAD based MPE values ever assembled. An automated script has been written to search and extract storms over the 18 year period of record from the contents of this massive historical precipitation database. Not only can it extract site-specific storms, but also duration-specific storms and

  5. Enhancing national Daily Landslide Hazard Assessments through inter-agency collaboration; lessons learned from storm Desmond (UK)/Synne (Norway), Dec 2015.

    Science.gov (United States)

    Boje, Søren; Devoli, Graziella; Sund, Monica; Freeborough, Katy; Dijkstra, Tom; Reeves, Helen; Banks, Vanessa

    2016-04-01

    th December. Synne triggered at least 23 landslides, 5 slush flows and 8 snow avalanches. The storm caused also significant floods in the southern sector of the west coast of Norway. In the UK, the DLHA warning level was elevated to yellow on Friday 4th and maintained the following days. Desmond resulted circa 25 landslides that were reported in the media. In both countries, many events were recorded close to transport infrastructure, but the actual number of events is much greater than reported during the storm. The severe consequences of extensive, simultaneous flooding provided a focus for most media reports. Following the events a picture emerged of the wider landscape response through anecdotal photographic evidence and social media. Data gathering therefore continues to date. Even though the issuing of landslide warnings has seen a high rate of success, there are important lessons to be learned regarding the magnitude of landscape response to particular events. This study shows how extreme events can strike several countries at approximately the same time raising landslide forecasting beyond the local environment. Significant gains can be made through inter-agency, international collaboration in order to improve the quality of daily landslide hazard assessments and risk mitigation strategies.

  6. Modeling and Forecasting the Onset and Duration of Severe Radiation Fog under Frost Conditions

    NARCIS (Netherlands)

    Velde, van der I.R.; Steeneveld, G.J.; Wichers Schreur, B.G.J.; Holtslag, A.A.M.

    2010-01-01

    A case of a severe radiation fog during frost conditions is analyzed as a benchmark for the development of a very high resolution NWP model. Results by the Weather Research and Forecasting model (WRF) and the High resolution limited area model (HIRLAM) are evaluated against detailed observations to

  7. Developing an early warning system for storm surge inundation in the Philippines

    Science.gov (United States)

    Tablazon, J.; Caro, C. V.; Lagmay, A. M. F.; Briones, J. B. L.; Dasallas, L.; Lapidez, J. P.; Santiago, J.; Suarez, J. K.; Ladiero, C.; Gonzalo, L. A.; Mungcal, M. T. F.; Malano, V.

    2014-10-01

    A storm surge is the sudden rise of sea water generated by an approaching storm, over and above the astronomical tides. This event imposes a major threat in the Philippine coastal areas, as manifested by Typhoon Haiyan on 8 November 2013 where more than 6000 people lost their lives. It has become evident that the need to develop an early warning system for storm surges is of utmost importance. To provide forecasts of the possible storm surge heights of an approaching typhoon, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. Bathymetric data, storm track, central atmospheric pressure, and maximum wind speed were used as parameters for the Japan Meteorological Agency Storm Surge Model. The researchers calculated the frequency distribution of maximum storm surge heights of all typhoons under a specific Public Storm Warning Signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of probable area inundation and flood levels of storm surges along coastal areas for a specific PSWS using the results of the frequency distribution. These maps were developed from the time series data of the storm tide at 10 min intervals of all observation points in the Philippines. This information will be beneficial in developing early warnings systems, static maps, disaster mitigation and preparedness plans, vulnerability assessments, risk-sensitive land use plans, shoreline defense efforts, and coastal protection measures. Moreover, these will support the local government units' mandate to raise public awareness, disseminate information about storm surge hazards, and implement appropriate counter

  8. The Southern Hemisphere and equatorial region ionization response for a 22 September 1999 severe magnetic storm

    Directory of Open Access Journals (Sweden)

    E. Yizengaw

    2004-09-01

    Full Text Available The ionospheric storm evolution process was monitored during the 22 September 1999 magnetic storm over the Australian eastern region, through measurements of the ionospheric Total Electron Content (TEC from seven Global Positioning Systems (GPS stations. The spatial and temporal variations of the ionosphere were analysed as a time series of TEC maps. Results of our analysis show that the main ionospheric effect of the storm under consideration are: the long lasting negative storm effect during a magnetic storm at mid-latitude regions; the strong, positive disturbances during the storm's main phase at auroral latitude regions; the effects of storm-induced equatorward directed wind causing a positive disturbance at high and mid-latitude stations with appropriate time shift between higher and lower latitudes; daytime poleward movement of depleted plasma that causes temporary suppression of the equatorial anomaly during the start of the storm recovery phase; and prompt penetration of eastward electric fields to ionospheric altitudes and the production of nearly simultaneous TEC enhancement at all latitudes. In general, we found dominant negative disturbance over mid and high latitudes and positive disturbance at low latitudes. A comparison of storm-time behaviour of TEC determined from GPS satellites, and foF2 derived from ionosondes at a range of latitudes, showed reasonable agreement between the two independent measurements.

  9. Modeling and Forecasting the Onset and Duration of Severe Radiation Fog under Frost Conditions

    NARCIS (Netherlands)

    van der Velde, I. R.; Steeneveld, G. J.; Schreur, B. G. J. Wichers; Holtslag, A. A. M.

    2010-01-01

    A case of a severe radiation fog during frost conditions is analyzed as a benchmark for the development of a very high-resolution NWP model Results by the Weather Research and Forecasting model (WRF) and the High Resolution Limited Area Model (H I RLAM) are evaluated against detailed observations to

  10. Global lightning and severe storm monitoring from GPS orbit

    Energy Technology Data Exchange (ETDEWEB)

    Suszcynsky, D. M. (David M.); Jacobson, A. R.; Linford, J (Justin); Pongratz, M. B. (Morris B.); Light, T. (Tracy E.); Shao, X. (Xuan-Min)

    2004-01-01

    Over the last few decades, there has been a growing interest to develop and deploy an automated and continuously operating satellite-based global lightning mapper [e.g. Christian et al., 1989; Weber et al., 1998; Suszcynsky et al., 2000]. Lightning is a direct consequence of the electrification and breakdown processes that take place during the convective stages of thunderstorm development. Satellite-based lightning mappers are designed to exploit this relationship by using lightning detection as a proxy for remotely identifying, locating and characterizing strong convective activity on a global basis. Global lightning and convection mapping promises to provide users with (1) an enhanced global severe weather monitoring and early warning capability [e.g. Weber et al., 1998] (2) improved ability to optimize aviation flight paths around convective cells, particularly over oceanic and remote regions that are not sufficiently serviced by existing weather radar [e.g. Weber et al., 1998], and (3) access to regional and global proxy data sets that can be used for scientific studies and as input into meteorological forecast and global climatology models. The physical foundation for satellite-based remote sensing of convection by way of lightning detection is provided by the basic interplay between the electrical and convective states of a thundercloud. It is widely believed that convection is a driving mechanism behind the hydrometeor charging and transport that produces charge separation and lightning discharges within thunderclouds [e.g. see chapter 3 in MacGorman and Rust, 1998]. Although cloud electrification and discharge processes are a complex function of the convective dynamics and microphysics of the cloud, the fundamental relationship between convection and electrification is easy to observe. For example, studies have shown that the strength of the convective process within a thundercell can be loosely parameterized (with large variance) by the intensity of the

  11. Severe rainfall prediction systems for civil protection purposes

    Science.gov (United States)

    Comellas, A.; Llasat, M. C.; Molini, L.; Parodi, A.; Siccardi, F.

    2010-09-01

    One of the most common natural hazards impending on Mediterranean regions is the occurrence of severe weather structures able to produce heavy rainfall. Floods have killed about 1000 people across all Europe in last 10 years. With the aim of mitigating this kind of risk, quantitative precipitation forecasts (QPF) and rain probability forecasts are two tools nowadays available for national meteorological services and institutions responsible for weather forecasting in order to and predict rainfall, by using either the deterministic or the probabilistic approach. This study provides an insight of the different approaches used by Italian (DPC) and Catalonian (SMC) Civil Protection and the results they achieved with their peculiar issuing-system for early warnings. For the former, the analysis considers the period between 2006-2009 in which the predictive ability of the forecasting system, based on the numerical weather prediction model COSMO-I7, has been put into comparison with ground based observations (composed by more than 2000 raingauge stations, Molini et al., 2009). Italian system is mainly focused on regional-scale warnings providing forecasts for periods never shorter than 18 hours and very often have a 36-hour maximum duration . The information contained in severe weather bulletins is not quantitative and usually is referred to a specific meteorological phenomena (thunderstorms, wind gales et c.). Updates and refining have a usual refresh time of 24 hours. SMC operates within the Catalonian boundaries and uses a warning system that mixes both quantitative and probabilistic information. For each administrative region ("comarca") Catalonia is divided into, forecasters give an approximate value of the average predicted rainfall and the probability of overcoming that threshold. Usually warnings are re-issued every 6 hours and their duration depends on the predicted time extent of the storm. In order to provide a comprehensive QPF verification, the rainfall

  12. The Southern Hemisphere and equatorial region ionization response for a 22 September 1999 severe magnetic storm

    OpenAIRE

    Yizengaw, Endawoke

    2004-01-01

    The ionospheric storm evolution process was monitored during the 22 September 1999 magnetic storm over the Australian eastern region, through measurements of the ionospheric Total Electron Content (TEC) from seven Global Positioning Systems (GPS) stations. The spatial and temporal variations of the ionosphere were analysed as a time series of TEC maps. Results of our analysis show that the main ionospheric effect of the storm under consideration are: the long lasting negative storm effect dur...

  13. Operational hydrological forecasting in Bavaria. Part I: Forecast uncertainty

    Science.gov (United States)

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

    2009-04-01

    In Bavaria, operational flood forecasting has been established since the disastrous flood of 1999. Nowadays, forecasts based on rainfall information from about 700 raingauges and 600 rivergauges are calculated and issued for nearly 100 rivergauges. With the added experience of the 2002 and 2005 floods, awareness grew that the standard deterministic forecast, neglecting the uncertainty associated with each forecast is misleading, creating a false feeling of unambiguousness. As a consequence, a system to identify, quantify and communicate the sources and magnitude of forecast uncertainty has been developed, which will be presented in part I of this study. In this system, the use of ensemble meteorological forecasts plays a key role which will be presented in part II. Developing the system, several constraints stemming from the range of hydrological regimes and operational requirements had to be met: Firstly, operational time constraints obviate the variation of all components of the modeling chain as would be done in a full Monte Carlo simulation. Therefore, an approach was chosen where only the most relevant sources of uncertainty were dynamically considered while the others were jointly accounted for by static error distributions from offline analysis. Secondly, the dominant sources of uncertainty vary over the wide range of forecasted catchments: In alpine headwater catchments, typically of a few hundred square kilometers in size, rainfall forecast uncertainty is the key factor for forecast uncertainty, with a magnitude dynamically changing with the prevailing predictability of the atmosphere. In lowland catchments encompassing several thousands of square kilometers, forecast uncertainty in the desired range (usually up to two days) is mainly dependent on upstream gauge observation quality, routing and unpredictable human impact such as reservoir operation. The determination of forecast uncertainty comprised the following steps: a) From comparison of gauge

  14. Evaluation of Deep Learning Representations of Spatial Storm Data

    Science.gov (United States)

    Gagne, D. J., II; Haupt, S. E.; Nychka, D. W.

    2017-12-01

    The spatial structure of a severe thunderstorm and its surrounding environment provide useful information about the potential for severe weather hazards, including tornadoes, hail, and high winds. Statistics computed over the area of a storm or from the pre-storm environment can provide descriptive information but fail to capture structural information. Because the storm environment is a complex, high-dimensional space, identifying methods to encode important spatial storm information in a low-dimensional form should aid analysis and prediction of storms by statistical and machine learning models. Principal component analysis (PCA), a more traditional approach, transforms high-dimensional data into a set of linearly uncorrelated, orthogonal components ordered by the amount of variance explained by each component. The burgeoning field of deep learning offers two potential approaches to this problem. Convolutional Neural Networks are a supervised learning method for transforming spatial data into a hierarchical set of feature maps that correspond with relevant combinations of spatial structures in the data. Generative Adversarial Networks (GANs) are an unsupervised deep learning model that uses two neural networks trained against each other to produce encoded representations of spatial data. These different spatial encoding methods were evaluated on the prediction of severe hail for a large set of storm patches extracted from the NCAR convection-allowing ensemble. Each storm patch contains information about storm structure and the near-storm environment. Logistic regression and random forest models were trained using the PCA and GAN encodings of the storm data and were compared against the predictions from a convolutional neural network. All methods showed skill over climatology at predicting the probability of severe hail. However, the verification scores among the methods were very similar and the predictions were highly correlated. Further evaluations are being

  15. The structure of the big magnetic storms

    International Nuclear Information System (INIS)

    Mihajlivich, J. Spomenko; Chop, Rudi; Palangio, Paolo

    2010-01-01

    The records of geomagnetic activity during Solar Cycles 22 and 23 (which occurred from 1986 to 2006) indicate several extremely intensive A-class geomagnetic storms. These were storms classified in the category of the Big Magnetic Storms. In a year of maximum solar activity during Solar Cycle 23, or more precisely, during a phase designated as a post-maximum phase in solar activity (PPM - Phase Post maximum), near the autumn equinox, on 29, October 2003, an extremely strong and intensive magnetic storm was recorded. In the first half of November 2004 (7, November 2004) an intensive magnetic storm was recorded (the Class Big Magnetic Storm). The level of geomagnetic field variations which were recorded for the selected Big Magnetic Storms, was ΔD st=350 nT. For the Big Magnetic Storms the indicated three-hour interval indices geomagnetic activity was Kp = 9. This study presents the spectral composition of the Di - variations which were recorded during magnetic storms in October 2003 and November 2004. (Author)

  16. Evaluation of Lightning Jumps as a Predictor of Severe Weather in the Northeastern United States

    Science.gov (United States)

    Eck, Pamela

    Severe weather events in the northeastern United States can be challenging to forecast, given how the evolution of deep convection can be influenced by complex terrain and the lack of quality observations in complex terrain. To supplement existing observations, this study explores using lightning to forecast severe convection in areas of complex terrain in the northeastern United States. A sudden increase in lightning flash rate by two standard deviations (2sigma), also known as a lightning jump, may be indicative of a strengthening updraft and an increased probability of severe weather. This study assesses the value of using lightning jumps to forecast severe weather during July 2015 in the northeastern United States. Total lightning data from the National Lightning Detection Network (NLDN) is used to calculate lightning jumps using a 2sigma lightning jump algorithm with a minimum threshold of 5 flashes min-1. Lightning jumps are used to predict the occurrence of severe weather, as given by whether a Storm Prediction Center (SPC) severe weather report occurred 45 min after a lightning jump in the same cell. Results indicate a high probability of detection (POD; 85%) and a high false alarm rate (FAR; 89%), suggesting that lightning jumps occur in sub-severe storms. The interaction between convection and complex terrain results in a locally enhanced updraft and an increased probability of severe weather. Thus, it is hypothesized that conditioning on an upslope variable may reduce the FAR. A random forest is introduced to objectively combine upslope flow, calculated using data from the High Resolution Rapid Refresh (HRRR), flash rate (FR), and flash rate changes with time (DFRDT). The random forest, a machine-learning algorithm, uses pattern recognition to predict a severe or non-severe classification based on the predictors. In addition to upslope flow, FR, and DFRDT, Next-Generation Radar (NEXRAD) Level III radar data was also included as a predictor to compare its

  17. Severe Weather Environments in Atmospheric Reanalyses

    Science.gov (United States)

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

    2017-12-01

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

  18. Storm water permitting for oil and gas facilities

    International Nuclear Information System (INIS)

    de Blanc, P.C.

    1991-01-01

    After several false starts, the US Environmental Protection Agency (EPA) published new federal storm water regulations in the November 16, 1990 Federal Register. These regulations identify facilities which must apply for a storm water permit and detail permit application requirements. The regulations appear at 40 CFR 122 Subpart B and became effective December 17, 1990. An outline of these regulations and their applicability to oil and gas facilities is presented. They are: facilities which require a storm water permit; types of storm water permits; permit application deadlines; permit application forms; facilities with existing storm water permits; storm water permit application data requirements; storm water sampling and analysis requirements; and EPA contacts for additional information

  19. Extreme Geomagnetic Storms – 1868–2010

    DEFF Research Database (Denmark)

    Vennerstrøm, Susanne; Lefèvre, L.; Dumbović, M.

    2016-01-01

    presents our investigation of the corresponding solar eventsand their characteristics. The storms were selected based on their intensity in the aa index,which constitutes the longest existing continuous series of geomagnetic activity. They areanalyzed statistically in the context of more well...... occurring in May 1921 and the Quebec storm from March 1989. We identifykey characteristics of the storms by combining several different available data sources, listsof storm sudden commencements (SSCs) signifying occurrence of interplanetary shocks,solar wind in-situ measurements, neutron monitor data...... %), Forbushdecreases (100 %), and energetic solar proton events (70 %). A quantitative comparison ofthese associations relative to less intense storms is also presented. Most notably, we findthat most often the extreme storms are characterized by a complexity that is associated with multiple, often interacting, solar...

  20. Lightning Evolution In Two North Central Florida Summer Multicell Storms and Three Winter/Spring Frontal Storms

    Science.gov (United States)

    Caicedo, J. A.; Uman, M. A.; Pilkey, J. T.

    2018-01-01

    We present the first lightning evolution studies, via the Lightning Mapping Array (LMA) and radar, performed in North Central Florida. Parts of three winter/spring frontal storms (cold season) and two complete summer (warm season) multicell storms are studied. Storm parameters measured are as follows: total number of flashes, flash-type classification, first flashes, flash initiation altitude, flash initiation power, flash rate (flashes per minute), charge structure, altitude and temperature ranges of the inferred charge regions, atmospheric isotherm altitude, radar base reflectivity (dBZ), and radar echo tops (EET). Several differences were found between summer multicell and winter/spring frontal storms in North Central Florida: (1) in winter/spring storms, the range of altitudes that all charge regions occupy is up to 1 km lower in altitude than in summer storms, as are the 0°C, -10°C, and -20°C isotherms; (2) lightning activity in summer storms is highly correlated with changes in radar signatures, in particular, echo tops; and (3) the LMA average initiation power of all flash types in winter/frontal storms is about an order of magnitude larger than that for summer storms. In relation to storms in other geographical locations, North Central Florida seasonal storms were found to have similarities in most parameters studied with a few differences, examples in Florida being (1) colder initiation altitudes for intracloud flashes, (2) charge regions occupying larger ranges of atmospheric temperatures, and (3) winter/spring frontal storms not having much lightning activity in the stratiform region.

  1. Diagnosis and Modeling of the Explosive Development of Winter Storms: Sensitivity to PBL Schemes

    Science.gov (United States)

    Liberato, Margarida L. R.; Pradhan, Prabodha K.

    2014-05-01

    The correct representation of extreme windstorms in regional models is of great importance for impact studies of climate change. The Iberian Peninsula has recently witnessed major damage from winter extratropical intense cyclones like Klaus (January 2009), Xynthia (February 2010) and Gong (January 2013) which formed over the mid-Atlantic, experienced explosive intensification while travelling eastwards at lower latitudes than usual [Liberato et al. 2011; 2013]. In this paper the explosive development of these storms is simulated by the advanced mesoscale Weather Research and Forecasting Model (WRF v 3.4.1), initialized with NCEP Final Analysis (FNL) data as initial and lateral boundary conditions (boundary conditions updated in every 3 hours intervals). The simulation experiments are conducted with two domains, a coarser (25km) and nested (8.333km), covering the entire North Atlantic and Iberian Peninsula region. The characteristics of these storms (e.g. wind speed, precipitation) are studied from WRF model and compared with multiple observations. In this context simulations with different Planetary Boundary Layer (PBL) schemes are performed. This approach aims at understanding which mechanisms favor the explosive intensification of these storms at a lower than usual latitudes, thus improving the knowledge of atmospheric dynamics (including small-scale processes) on controlling the life cycle of midlatitude extreme storms and contributing to the improvement in predictability and in our ability to forecast storms' impacts over Iberian Peninsula. Acknowledgments: This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa Operacional Factores de Competitividade) and by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project STORMEx FCOMP-01-0124-FEDER- 019524 (PTDC/AAC-CLI/121339/2010). References: Liberato M.L.R., J.G. Pinto, I.F. Trigo, R.M. Trigo (2011) Klaus - an

  2. High-resolution refinement of a storm loss model and estimation of return periods of loss-intensive storms over Germany

    Directory of Open Access Journals (Sweden)

    M. G. Donat

    2011-10-01

    Full Text Available A refined model for the calculation of storm losses is presented, making use of high-resolution insurance loss records for Germany and allowing loss estimates on a spatial level of administrative districts and for single storm events. Storm losses are calculated on the basis of wind speeds from both ERA-Interim and NCEP reanalyses. The loss model reproduces the spatial distribution of observed losses well by taking specific regional loss characteristics into account. This also permits high-accuracy estimates of total cumulated losses, though slightly underestimating the country-wide loss sums for storm "Kyrill", the most severe event in the insurance loss records from 1997 to 2007. A larger deviation, which is assigned to the relatively coarse resolution of the NCEP reanalysis, is only found for one specific rather small-scale event, not adequately captured by this dataset.

    The loss model is subsequently applied to the complete reanalysis period to extend the storm event catalogue to cover years when no systematic insurance records are available. This allows the consideration of loss-intensive storm events back to 1948, enlarging the event catalogue to cover the recent 60+ years, and to investigate the statistical characteristics of severe storm loss events in Germany based on a larger sample than provided by the insurance records only. Extreme value analysis is applied to the loss data to estimate the return periods of loss-intensive storms, yielding a return period for storm "Kyrill", for example, of approximately 15 to 21 years.

  3. Living with storm damage to forests

    NARCIS (Netherlands)

    Gardiner, B.; Schuck, A.; Schelhaas, M.J.; Orazio, C.; Blennow, K.; Nicoll, B.

    2013-01-01

    Windstorms are a major disturbance factor for European forests. In the past six decades wind storms have damaged standing forest volume, which on a yearly average equals about the size of Poland's annual fellings. The evedence also indicates that the actual severity of storms in the wake of climatic

  4. Substorms during different storm phases

    Directory of Open Access Journals (Sweden)

    N. Partamies

    2011-11-01

    Full Text Available After the deep solar minimum at the end of the solar cycle 23, a small magnetic storm occurred on 20–26 January 2010. The Dst (disturbance storm time index reached the minimum of −38 nT on 20 January and the prolonged recovery that followed the main phase that lasted for about 6 days. In this study, we concentrate on three substorms that took place (1 just prior to the storm, (2 during the main phase of the storm, and (3 at the end of the recovery of the storm. We analyse the solar wind conditions from the solar wind monitoring spacecraft, the duration and intensity of the substorm events as well as the behaviour of the electrojet currents from the ground magnetometer measurements. We compare the precipitation characteristics of the three substorms. The results show that the F-region electron density enhancements and dominant green and red auroral emission of the substorm activity during the storm recovery resembles average isolated substorm precipitation. However, the energy dissipated, even at the very end of a prolonged storm recovery, is very large compared to the typical energy content of isolated substorms. In the case studied here, the dissipation of the excess energy is observed over a 3-h long period of several consecutive substorm intensifications. Our findings suggest that the substorm energy dissipation varies between the storm phases.

  5. An impact analysis of forecasting methods and forecasting parameters on bullwhip effect

    Science.gov (United States)

    Silitonga, R. Y. H.; Jelly, N.

    2018-04-01

    Bullwhip effect is an increase of variance of demand fluctuation from downstream to upstream of supply chain. Forecasting methods and forecasting parameters were recognized as some factors that affect bullwhip phenomena. To study these factors, we can develop simulations. There are several ways to simulate bullwhip effect in previous studies, such as mathematical equation modelling, information control modelling, computer program, and many more. In this study a spreadsheet program named Bullwhip Explorer was used to simulate bullwhip effect. Several scenarios were developed to show the change in bullwhip effect ratio because of the difference in forecasting methods and forecasting parameters. Forecasting methods used were mean demand, moving average, exponential smoothing, demand signalling, and minimum expected mean squared error. Forecasting parameters were moving average period, smoothing parameter, signalling factor, and safety stock factor. It showed that decreasing moving average period, increasing smoothing parameter, increasing signalling factor can create bigger bullwhip effect ratio. Meanwhile, safety stock factor had no impact to bullwhip effect.

  6. Atmospheric Motion Vectors from INSAT-3D: Initial quality assessment and its impact on track forecast of cyclonic storm NANAUK

    Science.gov (United States)

    Deb, S. K.; Kishtawal, C. M.; Kumar, Prashant; Kiran Kumar, A. S.; Pal, P. K.; Kaushik, Nitesh; Sangar, Ghansham

    2016-03-01

    The advanced Indian meteorological geostationary satellite INSAT-3D was launched on 26 July 2013 with an improved imager and an infrared sounder and is placed at 82°E over the Indian Ocean region. With the advancement in retrieval techniques of different atmospheric parameters and with improved imager data have enhanced the scope for better understanding of the different tropical atmospheric processes over this region. The retrieval techniques and accuracy of one such parameter, Atmospheric Motion Vectors (AMV) has improved significantly with the availability of improved spatial resolution data along with more options of spectral channels in the INSAT-3D imager. The present work is mainly focused on providing brief descriptions of INSAT-3D data and AMV derivation processes using these data. It also discussed the initial quality assessment of INSAT-3D AMVs for a period of six months starting from 01 February 2014 to 31 July 2014 with other independent observations: i) Meteosat-7 AMVs available over this region, ii) in-situ radiosonde wind measurements, iii) cloud tracked winds from Multi-angle Imaging Spectro-Radiometer (MISR) and iv) numerical model analysis. It is observed from this study that the qualities of newly derived INSAT-3D AMVs are comparable with existing two versions of Meteosat-7 AMVs over this region. To demonstrate its initial application, INSAT-3D AMVs are assimilated in the Weather Research and Forecasting (WRF) model and it is found that the assimilation of newly derived AMVs has helped in reduction of track forecast errors of the recent cyclonic storm NANAUK over the Arabian Sea. Though, the present study is limited to its application to one case study, however, it will provide some guidance to the operational agencies for implementation of this new AMV dataset for future applications in the Numerical Weather Prediction (NWP) over the south Asia region.

  7. Application of Artificial Neural Network into the Water Level Modeling and Forecast

    Directory of Open Access Journals (Sweden)

    Marzenna Sztobryn

    2013-06-01

    Full Text Available The dangerous sea and river water level increase does not only destroy the human lives, but also generate the severe flooding in coastal areas. The rapidly changes in the direction and velocity of wind and associated with them sea level changes could be the severe threat for navigation, especially on the fairways of small fishery harbors located in the river mouth. There is the area of activity of two external forcing: storm surges and flood wave. The aim of the work was the description of an application of Artificial Neural Network (ANN methodology into the water level forecast in the case study field in Swibno harbor located is located at 938.7 km of the Wisla River and at a distance of about 3 km up the mouth (Gulf of Gdansk - Baltic Sea.

  8. Risk Analysis and Forecast Service for Geomagnetically Induced Currents in Europe

    Science.gov (United States)

    Wik, Magnus; Pirjola, Risto; Viljanen, Ari; Lundstedt, Henrik

    Geomagnetically induced currents (GIC), occurring during magnetic storms, pose a widespread natural disaster risk to the reliable operation of electric power transmission grids, oil and gas pipelines, telecommunication cables and railway systems. The solar magnetic activity is the cause of GIC. Solar coronal holes can cause recurrent inter-vals of raised geomagnetic activity, and coronal mass ejections (CME) at the Sun, sometimes producing very high speed plasma clouds with enhanced magnetic fields and particle densities, can cause the strongest geomagnetic storms. When the solar wind interacts with the geomag-netic field, energy is transferred to the magnetosphere, driving strong currents in the ionosphere. When these currents change in time a geoelectric field is induced at the surface of the Earth and in the ground. Finally, this field drives GIC in the ground and in any technological conductor systems. The worst consequence of a severe magnetic storm within a power grid is a complete blackout, as happened in the province of Québec, Canada, in March 1989, and in the city of Malmü, Sweden, in October 2003. Gas and oil pipelines are not regarded as vulnerable to the immediate impact of GIC, but the corrosion rate of buried steel pipes can increase due to GIC, which may thus shorten the lifetime of a pipe. European Risk from Geomagnetically Induced Currents (EURISGIC) is an EU project, that, if approved, will produce the first European-wide real-time prototype forecast service of GIC in power systems, based on in-situ solar wind observations and comprehensive simulations of the Earth's magnetosphere. This project focuses on high-voltage power transmission networks, which are probably currently the most susceptible to GIC effects. Geomagnetic storms cover large geographical regions, at times the whole globe. Consequently, power networks are rightly described as being European critical infrastructures whose disruption or destruction could have a significant impact

  9. Thyroid Storm Precipitated by Duodenal Ulcer Perforation

    Directory of Open Access Journals (Sweden)

    Shoko Natsuda

    2015-01-01

    Full Text Available Thyroid storm is a rare and life-threatening complication of thyrotoxicosis that requires prompt treatment. Thyroid storm is also known to be associated with precipitating events. The simultaneous treatment of thyroid storm and its precipitant, when they are recognized, in a patient is recommended; otherwise such disorders, including thyroid storm, can exacerbate each other. Here we report the case of a thyroid storm patient (a 55-year-old Japanese male complicated with a perforated duodenal ulcer. The patient was successfully treated with intensive treatment for thyroid storm and a prompt operation. Although it is believed that peptic ulcer rarely coexists with hyperthyroidism, among patients with thyroid storm, perforation of a peptic ulcer has been reported as one of the causes of fatal outcome. We determined that surgical intervention was required in this patient, reported despite ongoing severe thyrotoxicosis, and reported herein a successful outcome.

  10. Thyroid storm precipitated by duodenal ulcer perforation.

    Science.gov (United States)

    Natsuda, Shoko; Nakashima, Yomi; Horie, Ichiro; Ando, Takao; Kawakami, Atsushi

    2015-01-01

    Thyroid storm is a rare and life-threatening complication of thyrotoxicosis that requires prompt treatment. Thyroid storm is also known to be associated with precipitating events. The simultaneous treatment of thyroid storm and its precipitant, when they are recognized, in a patient is recommended; otherwise such disorders, including thyroid storm, can exacerbate each other. Here we report the case of a thyroid storm patient (a 55-year-old Japanese male) complicated with a perforated duodenal ulcer. The patient was successfully treated with intensive treatment for thyroid storm and a prompt operation. Although it is believed that peptic ulcer rarely coexists with hyperthyroidism, among patients with thyroid storm, perforation of a peptic ulcer has been reported as one of the causes of fatal outcome. We determined that surgical intervention was required in this patient, reported despite ongoing severe thyrotoxicosis, and reported herein a successful outcome.

  11. Patterns of Storm Injury and Tree Response

    Science.gov (United States)

    Kevin Smith; Walter Shortle; Kenneth Dudzik

    2001-01-01

    The ice storm of January 1998 in the northeastern United States and adjacent Canada was an extreme example of severe weather that injures trees every year. Broken branches, split branch forks, and snapped stems are all examples of storm injury.

  12. Seasonal timing of first rain storms affects rare plant population dynamics

    Science.gov (United States)

    Levine, J.M.; McEachern, A.K.; Cowan, C.

    2011-01-01

    A major challenge in forecasting the ecological consequences of climate change is understanding the relative importance of changes to mean conditions vs. changes to discrete climatic events, such as storms, frosts, or droughts. Here we show that the first major storm of the growing season strongly influences the population dynamics of three rare and endangered annual plant species in a coastal California (USA) ecosystem. In a field experiment we used moisture barriers and water addition to manipulate the timing and temperature associated with first major rains of the season. The three focal species showed two- to fivefold variation in per capita population growth rates between the different storm treatments, comparable to variation found in a prior experiment imposing eightfold differences in season-long precipitation. Variation in germination was a major demographic driver of how two of three species responded to the first rains. For one of these species, the timing of the storm was the most critical determinant of its germination, while the other showed enhanced germination with colder storm temperatures. The role of temperature was further supported by laboratory trials showing enhanced germination in cooler treatments. Our work suggests that, because of species-specific cues for demographic transitions such as germination, changes to discrete climate events may be as, if not more, important than changes to season-long variables.

  13. Effects of an assimilation of radar and satellite data on a very-short range forecast of heavy convective rainfalls

    Czech Academy of Sciences Publication Activity Database

    Sokol, Zbyněk

    2009-01-01

    Roč. 93, 1-3 (2009), s. 188-206 ISSN 0169-8095. [European Conference on Severe Storms /4./. Miramare -Trieste, 10.09.2007-14.09.2007] R&D Projects: GA ČR GA205/07/0905; GA MŠk OC 112; GA MŠk 1P05ME748 Institutional research plan: CEZ:AV0Z30420517 Keywords : Precipitation forecast * NWP model * Assimilation of radar and satellite data * Local convective precipitation Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.811, year: 2009 http://www.sciencedirect.com/science/journal/01698095

  14. Storm surge climatology report

    OpenAIRE

    Horsburgh, Kevin; Williams, Joanne; Cussack, Caroline

    2017-01-01

    Any increase in flood frequency or severity due to sea level rise or changes in storminess would adversely impact society. It is crucial to understand the physical drivers of extreme storm surges to have confidence in the datasets used for extreme sea level statistics. We will refine and improve methods to the estimation of extreme sea levels around Europe and more widely. We will do so by developing a comprehensive world picture of storm surge distribution (including extremes) for both tropi...

  15. Development of a Severe Sand-dust Storm Model and its Application to Northwest China

    International Nuclear Information System (INIS)

    Zhang Xiaoling; Cheng, Linsheng; Chung, Yong-Seung

    2003-01-01

    A very strong sand-dust storm occurred on 5 May, 1993 in Northwest China. In order to give a detailed description of the evolution of a mesoscale system along with the heavy sand-dust storm, a complex model including improved physical processes and a radiation parameterization scheme was developed based on a simulation model. The improved model introduced a sand-dust transport equation as well as a lifting transport model, sand-dust aerosols and radiation parameterization scheme.Using this model, the super sand-dust storm case on 5 May was simulated. Results indicated that the coupled mesoscale model successfully simulated the mesoscale vortex, its strong upward movement and the warm core structure of PBL. The generation and development of these structures were consistent with that of the sand-dust storm and dry squall-line (which was different with normal squall-line). Simulated sand-dust concentration and its radiative effect corresponded with observation data. The radiative effect of sand-dust aerosols caused the air to heat on the top of aerosol layer with a heating rate amounting to 2 K hr -1 . As a result, solar radiation flux that reached the surface, net radiation flux and surface temperature all suddenly went down. The temperature gradient across the cold front became obviously larger. Therefore, enhancing the development of the mesoscale system. The simulation generally reflected features during the squall-line passage of this strong sand-dust storm

  16. Modeling North Atlantic Nor'easters With Modern Wave Forecast Models

    Science.gov (United States)

    Perrie, Will; Toulany, Bechara; Roland, Aron; Dutour-Sikiric, Mathieu; Chen, Changsheng; Beardsley, Robert C.; Qi, Jianhua; Hu, Yongcun; Casey, Michael P.; Shen, Hui

    2018-01-01

    Three state-of-the-art operational wave forecast model systems are implemented on fine-resolution grids for the Northwest Atlantic. These models are: (1) a composite model system consisting of SWAN implemented within WAVEWATCHIII® (the latter is hereafter, WW3) on a nested system of traditional structured grids, (2) an unstructured grid finite-volume wave model denoted "SWAVE," using SWAN physics, and (3) an unstructured grid finite element wind wave model denoted as "WWM" (for "wind wave model") which uses WW3 physics. Models are implemented on grid systems that include relatively large domains to capture the wave energy generated by the storms, as well as including fine-resolution nearshore regions of the southern Gulf of Maine with resolution on the scale of 25 m to simulate areas where inundation and coastal damage have occurred, due to the storms. Storm cases include three intense midlatitude cases: a spring Nor'easter storm in May 2005, the Patriot's Day storm in 2007, and the Boxing Day storm in 2010. Although these wave model systems have comparable overall properties in terms of their performance and skill, it is found that there are differences. Models that use more advanced physics, as presented in recent versions of WW3, tuned to regional characteristics, as in the Gulf of Maine and the Northwest Atlantic, can give enhanced results.

  17. On the Representation of an Early Modern Dutch Storm in Two Poems

    Directory of Open Access Journals (Sweden)

    Katrin Pfeifer

    2015-10-01

    Full Text Available On 19th December 1660, a severe storm raged over the Dutch isle of Texel, causing severe damage. It proceeded to destroy parts of the city of Amsterdam. Both the sailor and merchant Gerrit Jansz Kooch and the priest Joannes Vollenhove wrote a poem about this natural disaster, presumably independently of each other. The poets perceived the storm differently: Kooch, an eyewitness of the storm, matter-of-factly portrays the calamity and details a feud between his son-in-law and a colleague to commemorate the day of the disaster. In contrast, Vollenhove personifies the winter storm and struggles to understand it. Their poems are valuable sources for a cultural historical analysis. After a brief review of historical severe storm research, I will analyse these poems from a cultural historical point of view. I will shed light on how this severe storm was represented poetically in the Early Modern Period.

  18. Probabilistic Forecasting of Coastal Morphodynamic Storm Response at Fire Island, New York

    Science.gov (United States)

    Wilson, K.; Adams, P. N.; Hapke, C. J.; Lentz, E. E.; Brenner, O.

    2013-12-01

    Site-specific probabilistic models of shoreline change are useful because they are derived from direct observations so that local factors, which greatly influence coastal response, are inherently considered by the model. Fire Island, a 50-km barrier island off Long Island, New York, is periodically subject to large storms, whose waves and storm surge dramatically alter beach morphology. Nor'Ida, which impacted the Fire Island coast in 2009, was one of the larger storms to occur in the early 2000s. In this study, we improve upon a Bayesian Network (BN) model informed with historical data to predict shoreline change from Nor'Ida. We present two BN models, referred to as 'original' model (BNo) and 'revised' model (BNr), designed to predict the most probable magnitude of net shoreline movement (NSM), as measured at 934 cross-shore transects, spanning 46 km. Both are informed with observational data (wave impact hours, shoreline and dune toe change rates, pre-storm beach width, and measured NSM) organized within five nodes, but the revised model contains a sixth node to represent the distribution of material added during an April 2009 nourishment project. We evaluate model success by examining the percentage of transects on which the model chooses the correct (observed) bin value of NSM. Comparisons of observed to model-predicted NSM show BNr has slightly higher predictive success over the total study area and significantly higher success at nourished locations. The BNo, which neglects anthropogenic modification history, correctly predicted the most probable NSM in 66.6% of transects, with ambiguous prediction at 12.7% of the locations. BNr, which incorporates anthropogenic modification history, resulted in 69.4% predictive accuracy and 13.9% ambiguity. However, across nourished transects, BNr reported 72.9% predictive success, while BNo reported 61.5% success. Further, at nourished transects, BNr reported higher ambiguity of 23.5% compared to 9.9% in BNo. These results

  19. New technology and tool prepared for communication against storm surges.

    Science.gov (United States)

    Letkiewicz, Beata

    2010-05-01

    The aim of the presentation is description of the new technology and tool prepared for communication, information and issue of warnings against storm surges. The Maritime Branch of the Institute of Meteorology and Water Management is responsible for preparing the forecast as warning, where the end users are Government Officials and Public. The Maritime Branch carry out the project "Strengthening the administrative capacity in order to improve the management of Polish coastal zone environment" (supported by a grant from Norway through the Norwegian Financial Mechanism). The expected final result of the project is web site www.baltyk.pogodynka.pl. One of the activities of the project is - set up of information website www.baltyk.pogodynka.pl, giving public access to the complied data. Information on web site: - meta data - marine data (on-line measurement: sea level, water temperature, salinity, oxygen concentration); - data bases of mathematical model outputs - forecast data (sea level, currents); - ice conditions of the Baltic Sea, - instructions, information materials with information of polish coastal zone. The aim of set up of the portal is development of communication between users of the system, exchange of the knowledge of marine environment and natural hazards such as storm surges, improving the ability of the region in the scope of the data management about the sea environment and the coastal zone.

  20. Modeling ionospheric foF 2 response during geomagnetic storms using neural network and linear regression techniques

    Science.gov (United States)

    Tshisaphungo, Mpho; Habarulema, John Bosco; McKinnell, Lee-Anne

    2018-06-01

    In this paper, the modeling of the ionospheric foF 2 changes during geomagnetic storms by means of neural network (NN) and linear regression (LR) techniques is presented. The results will lead to a valuable tool to model the complex ionospheric changes during disturbed days in an operational space weather monitoring and forecasting environment. The storm-time foF 2 data during 1996-2014 from Grahamstown (33.3°S, 26.5°E), South Africa ionosonde station was used in modeling. In this paper, six storms were reserved to validate the models and hence not used in the modeling process. We found that the performance of both NN and LR models is comparable during selected storms which fell within the data period (1996-2014) used in modeling. However, when validated on storm periods beyond 1996-2014, the NN model gives a better performance (R = 0.62) compared to LR model (R = 0.56) for a storm that reached a minimum Dst index of -155 nT during 19-23 December 2015. We also found that both NN and LR models are capable of capturing the ionospheric foF 2 responses during two great geomagnetic storms (28 October-1 November 2003 and 6-12 November 2004) which have been demonstrated to be difficult storms to model in previous studies.

  1. Short-range quantitative precipitation forecasting using Deep Learning approaches

    Science.gov (United States)

    Akbari Asanjan, A.; Yang, T.; Gao, X.; Hsu, K. L.; Sorooshian, S.

    2017-12-01

    Predicting short-range quantitative precipitation is very important for flood forecasting, early flood warning and other hydrometeorological purposes. This study aims to improve the precipitation forecasting skills using a recently developed and advanced machine learning technique named Long Short-Term Memory (LSTM). The proposed LSTM learns the changing patterns of clouds from Cloud-Top Brightness Temperature (CTBT) images, retrieved from the infrared channel of Geostationary Operational Environmental Satellite (GOES), using a sophisticated and effective learning method. After learning the dynamics of clouds, the LSTM model predicts the upcoming rainy CTBT events. The proposed model is then merged with a precipitation estimation algorithm termed Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) to provide precipitation forecasts. The results of merged LSTM with PERSIANN are compared to the results of an Elman-type Recurrent Neural Network (RNN) merged with PERSIANN and Final Analysis of Global Forecast System model over the states of Oklahoma, Florida and Oregon. The performance of each model is investigated during 3 storm events each located over one of the study regions. The results indicate the outperformance of merged LSTM forecasts comparing to the numerical and statistical baselines in terms of Probability of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), RMSE and correlation coefficient especially in convective systems. The proposed method shows superior capabilities in short-term forecasting over compared methods.

  2. Flood forecasting and uncertainty of precipitation forecasts

    International Nuclear Information System (INIS)

    Kobold, Mira; Suselj, Kay

    2004-01-01

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

  3. Radioiodine-induced thyroid storm. Case report and literature review

    Energy Technology Data Exchange (ETDEWEB)

    McDermott, M.T.; Kidd, G.S.; Dodson, L.E. Jr.; Hofeldt, F.D.

    1983-08-01

    Thyroid storm developed following radioiodine therapy in a 43-year-old man with Graves' disease, weight loss, myopathy, severe thyrotoxic hypercalcemia, and a pituitary adenoma. The hypercalcemia may have been a significant, and previously unreported, predisposing factor for the radioiodine-associated thyroid storm. This case and 15 other well-documented cases of radioiodine-associated storm found in the literature are reviewed, as are several other cases of less severe exacerbations of thyrotoxicosis associated with radioiodine therapy. Although not often seen, these complications are often fatal. High-risk patients, such as the elderly, those with severe thyrotoxicosis, and those with significant underlying diseases, may benefit from preventive measures such as the judicious use of thyrostatic medications during the periods before and after isotope administration.

  4. Radioiodine-induced thyroid storm. Case report and literature review

    International Nuclear Information System (INIS)

    McDermott, M.T.; Kidd, G.S.; Dodson, L.E. Jr.; Hofeldt, F.D.

    1983-01-01

    Thyroid storm developed following radioiodine therapy in a 43-year-old man with Graves' disease, weight loss, myopathy, severe thyrotoxic hypercalcemia, and a pituitary adenoma. The hypercalcemia may have been a significant, and previously unreported, predisposing factor for the radioiodine-associated thyroid storm. This case and 15 other well-documented cases of radioiodine-associated storm found in the literature are reviewed, as are several other cases of less severe exacerbations of thyrotoxicosis associated with radioiodine therapy. Although not often seen, these complications are often fatal. High-risk patients, such as the elderly, those with severe thyrotoxicosis, and those with significant underlying diseases, may benefit from preventive measures such as the judicious use of thyrostatic medications during the periods before and after isotope administration

  5. [Thyroid Storm and Myxedema Coma].

    Science.gov (United States)

    Milkau, Malte; Sayk, Friedhelm

    2018-03-01

    Thyroid storm and myxedema coma are the most severe clinical forms of thyroid dysfunction. While both hyper- and hypothyroidsm are common diseases, thyroid storm and myxedema coma are rare. Due to their unspecific signs and symptoms they are often difficult to diagnose. Both disorders are medical emergencies, which still show a significant mortality. The following article summarizes diagnostic tools and treatment options for these disorders. © Georg Thieme Verlag KG Stuttgart · New York.

  6. Reconnaissance level study Mississippi storm surge barrier

    NARCIS (Netherlands)

    Van Ledden, M.; Lansen, A.J.; De Ridder, H.A.J.; Edge, B.

    2012-01-01

    This paper reports a reconnaissance level study of a storm surge barrier in the Mississippi River. Historical hurricanes have shown storm surge of several meters along the Mississippi River levees up to and upstream of New Orleans. Future changes due to sea level rise and subsidence will further

  7. A parabolic model of drag coefficient for storm surge simulation in the South China Sea

    Science.gov (United States)

    Peng, Shiqiu; Li, Yineng

    2015-01-01

    Drag coefficient (Cd) is an essential metric in the calculation of momentum exchange over the air-sea interface and thus has large impacts on the simulation or forecast of the upper ocean state associated with sea surface winds such as storm surges. Generally, Cd is a function of wind speed. However, the exact relationship between Cd and wind speed is still in dispute, and the widely-used formula that is a linear function of wind speed in an ocean model could lead to large bias at high wind speed. Here we establish a parabolic model of Cd based on storm surge observations and simulation in the South China Sea (SCS) through a number of tropical cyclone cases. Simulation of storm surges for independent Tropical cyclones (TCs) cases indicates that the new parabolic model of Cd outperforms traditional linear models. PMID:26499262

  8. A parabolic model of drag coefficient for storm surge simulation in the South China Sea

    Science.gov (United States)

    Peng, Shiqiu; Li, Yineng

    2015-10-01

    Drag coefficient (Cd) is an essential metric in the calculation of momentum exchange over the air-sea interface and thus has large impacts on the simulation or forecast of the upper ocean state associated with sea surface winds such as storm surges. Generally, Cd is a function of wind speed. However, the exact relationship between Cd and wind speed is still in dispute, and the widely-used formula that is a linear function of wind speed in an ocean model could lead to large bias at high wind speed. Here we establish a parabolic model of Cd based on storm surge observations and simulation in the South China Sea (SCS) through a number of tropical cyclone cases. Simulation of storm surges for independent Tropical cyclones (TCs) cases indicates that the new parabolic model of Cd outperforms traditional linear models.

  9. Acute and long term outcomes of catheter ablation using remote magnetic navigation for the treatment of electrical storm in patients with severe ischemic heart failure

    DEFF Research Database (Denmark)

    Jin, Qi; Jacobsen, Peter Karl; Pehrson, Steen

    2015-01-01

    BACKGROUND: Catheter ablation with remote magnetic navigation (RMN) can offer some advantages compared to manual techniques. However, the relevant clinical evidence for how RMN-guided ablation affects electrical storm (ES) due to ventricular tachycardia (VT) in patients with severe ischemic heart......-guided catheter ablation can prevent VT recurrence and significantly reduce ICD shocks, suggesting that this strategy can be used as an alternative therapy for VT storm in SIHF patients with ICDs....

  10. PAI-OFF: A new proposal for online flood forecasting in flash flood prone catchments

    Science.gov (United States)

    Schmitz, G. H.; Cullmann, J.

    2008-10-01

    SummaryThe Process Modelling and Artificial Intelligence for Online Flood Forecasting (PAI-OFF) methodology combines the reliability of physically based, hydrologic/hydraulic modelling with the operational advantages of artificial intelligence. These operational advantages are extremely low computation times and straightforward operation. The basic principle of the methodology is to portray process models by means of ANN. We propose to train ANN flood forecasting models with synthetic data that reflects the possible range of storm events. To this end, establishing PAI-OFF requires first setting up a physically based hydrologic model of the considered catchment and - optionally, if backwater effects have a significant impact on the flow regime - a hydrodynamic flood routing model of the river reach in question. Both models are subsequently used for simulating all meaningful and flood relevant storm scenarios which are obtained from a catchment specific meteorological data analysis. This provides a database of corresponding input/output vectors which is then completed by generally available hydrological and meteorological data for characterizing the catchment state prior to each storm event. This database subsequently serves for training both a polynomial neural network (PoNN) - portraying the rainfall-runoff process - and a multilayer neural network (MLFN), which mirrors the hydrodynamic flood wave propagation in the river. These two ANN models replace the hydrological and hydrodynamic model in the operational mode. After presenting the theory, we apply PAI-OFF - essentially consisting of the coupled "hydrologic" PoNN and "hydrodynamic" MLFN - to the Freiberger Mulde catchment in the Erzgebirge (Ore-mountains) in East Germany (3000 km 2). Both the demonstrated computational efficiency and the prediction reliability underline the potential of the new PAI-OFF methodology for online flood forecasting.

  11. Use of Vertically Integrated Ice in WRF-Based Forecasts of Lightning Threat

    Science.gov (United States)

    McCaul, E. W., jr.; Goodman, S. J.

    2008-01-01

    Previously reported methods of forecasting lightning threat using fields of graupel flux from WRF simulations are extended to include the simulated field of vertically integrated ice within storms. Although the ice integral shows less temporal variability than graupel flux, it provides more areal coverage, and can thus be used to create a lightning forecast that better matches the areal coverage of the lightning threat found in observations of flash extent density. A blended lightning forecast threat can be constructed that retains much of the desirable temporal sensitivity of the graupel flux method, while also incorporating the coverage benefits of the ice integral method. The graupel flux and ice integral fields contributing to the blended forecast are calibrated against observed lightning flash origin density data, based on Lightning Mapping Array observations from a series of case studies chosen to cover a wide range of flash rate conditions. Linear curve fits that pass through the origin are found to be statistically robust for the calibration procedures.

  12. What does the magnetic storm development depend on?

    International Nuclear Information System (INIS)

    Wodnicka, E.B.

    1991-01-01

    Adiabatic drift model applied to the magnetic storm development simulation reveals the significance of initial energy, initial pitch angle and the site of ions injection for the intensity, growth time and growth rate of a storm produced by two ion species - H + and O + . The most severe storms are caused by the ring current intensified by low initial pitch angle ions injected at low radial distance in the postmidnight local time region. (author)

  13. Short-interval SMS wind vector determinations for a severe local storms area

    Science.gov (United States)

    Peslen, C. A.

    1980-01-01

    Short-interval SMS-2 visible digital image data are used to derive wind vectors from cloud tracking on time-lapsed sequences of geosynchronous satellite images. The cloud tracking areas are located in the Central Plains, where on May 6, 1975 hail-producing thunderstorms occurred ahead of a well defined dry line. Cloud tracking is performed on the Goddard Space Flight Center Atmospheric and Oceanographic Information Processing System. Lower tropospheric cumulus tracers are selected with the assistance of a cloud-top height algorithm. Divergence is derived from the cloud motions using a modified Cressman (1959) objective analysis technique which is designed to organize irregularly spaced wind vectors into uniformly gridded wind fields. The results demonstrate the feasibility of using satellite-derived wind vectors and their associated divergence fields in describing the conditions preceding severe local storm development. For this case, an area of convergence appeared ahead of the dry line and coincided with the developing area of severe weather. The magnitude of the maximum convergence varied between -10 to the -5th and -10 to the -14th per sec. The number of satellite-derived wind vectors which were required to describe conditions of the low-level atmosphere was adequate before numerous cumulonimbus cells formed. This technique is limited in areas of advanced convection.

  14. Development of the Coastal Storm Modeling System (CoSMoS) for predicting the impact of storms on high-energy, active-margin coasts

    Science.gov (United States)

    Barnard, Patrick; Maarten van Ormondt,; Erikson, Li H.; Jodi Eshleman,; Hapke, Cheryl J.; Peter Ruggiero,; Peter Adams,; Foxgrover, Amy C.

    2014-01-01

    The Coastal Storm Modeling System (CoSMoS) applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers). CoSMoS was developed for hindcast studies, operational applications (i.e., nowcasts and multiday forecasts), and future climate scenarios (i.e., sea-level rise + storms) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. The prototype system, developed for the California coast, uses the global WAVEWATCH III wave model, the TOPEX/Poseidon satellite altimetry-based global tide model, and atmospheric-forcing data from either the US National Weather Service (operational mode) or Global Climate Models (future climate mode), to determine regional wave and water-level boundary conditions. These physical processes are dynamically downscaled using a series of nested Delft3D-WAVE (SWAN) and Delft3D-FLOW (FLOW) models and linked at the coast to tightly spaced XBeach (eXtreme Beach) cross-shore profile models and a Bayesian probabilistic cliff failure model. Hindcast testing demonstrates that, despite uncertainties in preexisting beach morphology over the ~500 km alongshore extent of the pilot study area, CoSMoS effectively identifies discrete sections of the coast (100s of meters) that are vulnerable to coastal hazards under a range of current and future oceanographic forcing conditions, and is therefore an effective tool for operational and future climate scenario planning.

  15. Assessing the Effectiveness of the Cone of Probability as a Visual Means of Communicating Scientific Forecasts

    Science.gov (United States)

    Orlove, B. S.; Broad, K.; Meyer, R.

    2010-12-01

    We review the evolution, communication, and differing interpretations of the National Hurricane Center (NHC)'s "cone of uncertainty" hurricane forecast graphic, drawing on several related disciplines—cognitive psychology, visual anthropology, and risk communication theory. We examine the 2004 hurricane season, two specific hurricanes (Katrina 2005 and Ike 2008) and the 2010 hurricane season, still in progress. During the 2004 hurricane season, five named storms struck Florida. Our analysis of that season draws upon interviews with key government officials and media figures, archival research of Florida newspapers, analysis of public comments on the NHC cone of uncertainty graphic and a multiagency study of 2004 hurricane behavior. At that time, the hurricane forecast graphic was subject to misinterpretation by many members of the public. We identify several characteristics of this graphic that contributed to public misinterpretation. Residents overemphasized the specific track of the eye, failed to grasp the width of hurricanes, and generally did not recognize the timing of the passage of the hurricane. Little training was provided to emergency response managers in the interpretation of forecasts. In the following year, Katrina became a national scandal, further demonstrating the limitations of the cone as a means of leading to appropriate responses to forecasts. In the second half of the first decade of the 21st century, three major changes occurred in hurricane forecast communication: the forecasts themselves improved in terms of accuracy and lead time, the NHC made minor changes in the graphics and expanded the explanatory material that accompanies the graphics, and some efforts were made to reach out to emergency response planners and municipal officials to enhance their understanding of the forecasts and graphics. There were some improvements in the responses to Ike, though a number of deaths were due to inadequate evacuations, and property damage probably

  16. Short-term Forecasting Tools for Agricultural Nutrient Management.

    Science.gov (United States)

    Easton, Zachary M; Kleinman, Peter J A; Buda, Anthony R; Goering, Dustin; Emberston, Nichole; Reed, Seann; Drohan, Patrick J; Walter, M Todd; Guinan, Pat; Lory, John A; Sommerlot, Andrew R; Sharpley, Andrew

    2017-11-01

    The advent of real-time, short-term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high-performance computing and hydrologic or climate modeling have enabled rapid dissemination of real-time information that can assist landowners and conservation personnel with short-term management planning. This paper reviews short-term decision support tools for agriculture that are under various stages of development and implementation in the United States: (i) Wisconsin's Runoff Risk Advisory Forecast (RRAF) System, (ii) New York's Hydrologically Sensitive Area Prediction Tool, (iii) Virginia's Saturated Area Forecast Model, (iv) Pennsylvania's Fertilizer Forecaster, (v) Washington's Application Risk Management (ARM) System, and (vi) Missouri's Design Storm Notification System. Although these decision support tools differ in their underlying model structure, the resolution at which they are applied, and the hydroclimates to which they are relevant, all provide forecasts (range 24-120 h) of runoff risk or soil moisture saturation derived from National Weather Service Forecast models. Although this review highlights the need for further development of robust and well-supported short-term nutrient management tools, their potential for adoption and ultimate utility requires an understanding of the appropriate context of application, the strategic and operational needs of managers, access to weather forecasts, scales of application (e.g., regional vs. field level), data requirements, and outreach communication structure. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  17. Simulation of a severe convective storm using a numerical model with explicitly incorporated aerosols

    Science.gov (United States)

    Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje

    2017-09-01

    Despite an important role the aerosols play in all stages of cloud lifecycle, their representation in numerical weather prediction models is often rather crude. This paper investigates the effects the explicit versus implicit inclusion of aerosols in a microphysics parameterization scheme in Weather Research and Forecasting (WRF) - Advanced Research WRF (WRF-ARW) model has on cloud dynamics and microphysics. The testbed selected for this study is a severe mesoscale convective system with supercells that struck west and central parts of Serbia in the afternoon of July 21, 2014. Numerical products of two model runs, i.e. one with aerosols explicitly (WRF-AE) included and another with aerosols implicitly (WRF-AI) assumed, are compared against precipitation measurements from surface network of rain gauges, as well as against radar and satellite observations. The WRF-AE model accurately captured the transportation of dust from the north Africa over the Mediterranean and to the Balkan region. On smaller scales, both models displaced the locations of clouds situated above west and central Serbia towards southeast and under-predicted the maximum values of composite radar reflectivity. Similar to satellite images, WRF-AE shows the mesoscale convective system as a merged cluster of cumulonimbus clouds. Both models over-predicted the precipitation amounts; WRF-AE over-predictions are particularly pronounced in the zones of light rain, while WRF-AI gave larger outliers. Unlike WRF-AI, the WRF-AE approach enables the modelling of time evolution and influx of aerosols into the cloud which could be of practical importance in weather forecasting and weather modification. Several likely causes for discrepancies between models and observations are discussed and prospects for further research in this field are outlined.

  18. Evaluation of the performance of DIAS ionospheric forecasting models

    Directory of Open Access Journals (Sweden)

    Tsagouri Ioanna

    2011-08-01

    Full Text Available Nowcasting and forecasting ionospheric products and services for the European region are regularly provided since August 2006 through the European Digital upper Atmosphere Server (DIAS, http://dias.space.noa.gr. Currently, DIAS ionospheric forecasts are based on the online implementation of two models: (i the solar wind driven autoregression model for ionospheric short-term forecast (SWIF, which combines historical and real-time ionospheric observations with solar-wind parameters obtained in real time at the L1 point from NASA ACE spacecraft, and (ii the geomagnetically correlated autoregression model (GCAM, which is a time series forecasting method driven by a synthetic geomagnetic index. In this paper we investigate the operational ability and the accuracy of both DIAS models carrying out a metrics-based evaluation of their performance under all possible conditions. The analysis was established on the systematic comparison between models’ predictions with actual observations obtained over almost one solar cycle (1998–2007 at four European ionospheric locations (Athens, Chilton, Juliusruh and Rome and on the comparison of the models’ performance against two simple prediction strategies, the median- and the persistence-based predictions during storm conditions. The results verify operational validity for both models and quantify their prediction accuracy under all possible conditions in support of operational applications but also of comparative studies in assessing or expanding the current ionospheric forecasting capabilities.

  19. Solar wind-magnetosphere coupling during intense magnetic storms (1978-1979)

    Science.gov (United States)

    Gonzalez, Walter D.; Gonzalez, Alicia L. C.; Tsurutani, Bruce T.; Smith, Edward J.; Tang, Frances

    1989-01-01

    The solar wind-magnetosphere coupling problem during intense magnetic storms was investigated for ten intense magnetic storm events occurring between August 16, 1978 to December 28, 1979. Particular attention was given to the dependence of the ring current energization on the ISEE-measured solar-wind parameters and the evolution of the ring current during the main phase of the intense storms. Several coupling functions were tested as energy input, and several sets of the ring current decay time-constant were searched for the best correlation with the Dst response. Results indicate that a large-scale magnetopause reconnection operates during an intense storm event and that the solar wind ram pressure plays an important role in the energization of the ring current.

  20. Three-dimensional variational assimilation of MODIS aerosol optical depth: Implementation and application to a dust storm over East Asia

    Science.gov (United States)

    Liu, Zhiquan; Liu, Quanhua; Lin, Hui-Chuan; Schwartz, Craig S.; Lee, Yen-Huei; Wang, Tijian

    2011-12-01

    Assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) total aerosol optical depth (AOD) retrieval products (at 550 nm wavelength) from both Terra and Aqua satellites have been developed within the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) three-dimensional variational (3DVAR) data assimilation system. This newly developed algorithm allows, in a one-step procedure, the analysis of 3-D mass concentration of 14 aerosol variables from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module. The Community Radiative Transfer Model (CRTM) was extended to calculate AOD using GOCART aerosol variables as input. Both the AOD forward model and corresponding Jacobian model were developed within the CRTM and used in the 3DVAR minimization algorithm to compute the AOD cost function and its gradient with respect to 3-D aerosol mass concentration. The impact of MODIS AOD data assimilation was demonstrated by application to a dust storm from 17 to 24 March 2010 over East Asia. The aerosol analyses initialized Weather Research and Forecasting/Chemistry (WRF/Chem) model forecasts. Results indicate that assimilating MODIS AOD substantially improves aerosol analyses and subsequent forecasts when compared to MODIS AOD, independent AOD observations from the Aerosol Robotic Network (AERONET) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, and surface PM10 (particulate matter with diameters less than 10 μm) observations. The newly developed AOD data assimilation system can serve as a tool to improve simulations of dust storms and general air quality analyses and forecasts.

  1. High resolution modelling results of the wind flow over Canary Islands during the meteorological situation of the extratropical storm Delta (28–30 November 2005

    Directory of Open Access Journals (Sweden)

    J. M. Baldasano

    2008-05-01

    Full Text Available On 28–29 November 2005 an extratropical storm affected the Canary Islands causing significant damage related to high average wind speeds and intense gusts over some islands of the archipelago. Delta was the twenty-sixth tropical or subtropical storm of the 2005 Atlantic hurricane season. It represents an unusual meteorological phenomenon for that region, and its impacts were underestimated by the different operational meteorological forecasts during the previous days of the arrival of the low near Canary Islands. The aim of this study is to reproduce the local effects of the flow that were observed over the Canary Islands during the travel of the Delta storm near the region using high-resolution mesoscale meteorological simulations. The Advanced Research Weather Research & Forecasting Model (WRF-ARW is applied at 9, 3 and 1 km horizontal resolution using ECMWF forecasts as initial and boundary conditions. The high-resolution simulation will outline the main features that contributed to the high wind speeds observed in the archipelago. Variations in vertical static stability, vertical windshear and the intense synoptic winds of the southwestern part of Delta with a warm core at 850 hPa were the main characteristics that contributed to the development and amplification of intense gravity waves while the large-scale flow interacted with the complex topography of the islands.

  2. Storm surge modeling of Superstorm Sandy in the New York City Metropolitan area

    Science.gov (United States)

    Benimoff, A. I.; Blanton, B. O.; Dzedzits, E.; Fritz, W. J.; Kress, M.; Muzio, P.; Sela, L.

    2013-12-01

    Even though the New York/New Jersey area does not lie within the typical 'hurricane belt', recent events and the historical record indicate that large infrequent tropical storms have had direct hits on the region, with impacts being amplified due to the nearly right angle bend in the coastline. The recent plan unveiled by New York City's Mayor Bloomberg lays out mitigation strategies to protect the region's communities, infrastructure, and assets from future storms, and numerical simulation of storm surge and wave hazards driven by potential hurricanes plays a central role in developing and evaluating these strategies. To assist in local planning, recovery, and decision-making, we have used the tide, storm surge, and wind wave model ADCIRC+SWAN to simulate storm surge in one of the most populated areas of the United States: the New York City (NYC) metropolitan area. We have generated a new high-resolution triangular finite-element model grid for the region from recent USGS data as well as recent city topographic maps at 2-foot (0.6m) contour intervals, nautical charts, and details of shipping channels. Our hindcast simulations are compared against Superstorm Sandy. We used the City University of New York High Performance Computing Center's Cray XE6tm at the College of Staten Island for these simulations. Hindcasting and analysis of the Superstorm Sandy storm surge and waves indicates that our simulations produce a reasonable representation of actual events. The grid will be used in an ADCIRC-based forecasting system implementation for the region.

  3. Tropical cyclone induced asymmetry of sea level surge and fall and its presentation in a storm surge model with parametric wind fields

    Science.gov (United States)

    Peng, Machuan; Xie, Lian; Pietrafesa, Leonard J.

    The asymmetry of tropical cyclone induced maximum coastal sea level rise (positive surge) and fall (negative surge) is studied using a three-dimensional storm surge model. It is found that the negative surge induced by offshore winds is more sensitive to wind speed and direction changes than the positive surge by onshore winds. As a result, negative surge is inherently more difficult to forecast than positive surge since there is uncertainty in tropical storm wind forecasts. The asymmetry of negative and positive surge under parametric wind forcing is more apparent in shallow water regions. For tropical cyclones with fixed central pressure, the surge asymmetry increases with decreasing storm translation speed. For those with the same translation speed, a weaker tropical cyclone is expected to gain a higher AI (asymmetry index) value though its induced maximum surge and fall are smaller. With fixed RMW (radius of maximum wind), the relationship between central pressure and AI is heterogeneous and depends on the value of RMW. Tropical cyclone's wind inflow angle can also affect surge asymmetry. A set of idealized cases as well as two historic tropical cyclones are used to illustrate the surge asymmetry.

  4. Assessments of Total Lightning Data Utility in Weather Forecasting

    Science.gov (United States)

    Buechler, Dennis E.; Goodman, Steve; LaCasse, Katherine; Blakeslee, Richard; Darden, Chris

    2005-01-01

    National Weather Service forecasters in Huntsville, Alabama have had access to total lightning data from the North Alabama Lightning Mapping Array (LMA) since 2003. Forecasters can monitor real-time total lightning observations on their AWIPS (Advanced Weather Interactive Processing System (AWIPS) workstations. The lightning data is used to supplement other observations such as radar and satellite data. The lightning data is updated every 2 min, providing more timely evidence of storm growth or decay than is available from 5 min radar scans. Total lightning observations have been used to positively impact warning decisions in a number of instances. A number of approaches are being pursued to assess the usefulness of total lightning measurements to the operational forecasting community in the warning decision process. These approaches, which include both qualitative and quantitative assessment methods, will be discussed. submitted to the American Meteorological Society (AMS) Conference on Meteorological Applications of Lightning Data to be held in San Diego, CA January 9-13,2005. This will be a presentation and an extended abstract will be published on a CD available from the AMS.

  5. Solar noise storms

    CERN Document Server

    Elgaroy, E O

    2013-01-01

    Solar Noise Storms examines the properties and features of solar noise storm phenomenon. The book also presents some theories that can be used to gain a better understanding of the phenomenon. The coverage of the text includes topics that cover the features and behavior of noise storms, such as the observable features of noise storms; the relationship between noise storms and the observable features on the sun; and ordered behavior of storm bursts in the time-frequency plane. The book also covers the spectrum, polarization, and directivity of noise storms. The text will be of great use to astr

  6. Empirical STORM-E Model. [I. Theoretical and Observational Basis

    Science.gov (United States)

    Mertens, Christopher J.; Xu, Xiaojing; Bilitza, Dieter; Mlynczak, Martin G.; Russell, James M., III

    2013-01-01

    Auroral nighttime infrared emission observed by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument onboard the Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics (TIMED) satellite is used to develop an empirical model of geomagnetic storm enhancements to E-region peak electron densities. The empirical model is called STORM-E and will be incorporated into the 2012 release of the International Reference Ionosphere (IRI). The proxy for characterizing the E-region response to geomagnetic forcing is NO+(v) volume emission rates (VER) derived from the TIMED/SABER 4.3 lm channel limb radiance measurements. The storm-time response of the NO+(v) 4.3 lm VER is sensitive to auroral particle precipitation. A statistical database of storm-time to climatological quiet-time ratios of SABER-observed NO+(v) 4.3 lm VER are fit to widely available geomagnetic indices using the theoretical framework of linear impulse-response theory. The STORM-E model provides a dynamic storm-time correction factor to adjust a known quiescent E-region electron density peak concentration for geomagnetic enhancements due to auroral particle precipitation. Part II of this series describes the explicit development of the empirical storm-time correction factor for E-region peak electron densities, and shows comparisons of E-region electron densities between STORM-E predictions and incoherent scatter radar measurements. In this paper, Part I of the series, the efficacy of using SABER-derived NO+(v) VER as a proxy for the E-region response to solar-geomagnetic disturbances is presented. Furthermore, a detailed description of the algorithms and methodologies used to derive NO+(v) VER from SABER 4.3 lm limb emission measurements is given. Finally, an assessment of key uncertainties in retrieving NO+(v) VER is presented

  7. Simulating storm surge inundation and damage potential within complex port facilities

    Science.gov (United States)

    Mawdsley, Robert; French, Jon; Fujiyama, Taku; Achutan, Kamalasudhan

    2017-04-01

    Storm surge inundation of port facilities can cause damage to critical elements of infrastructure, significantly disrupt port operations and cause downstream impacts on vital supply chains. A tidal surge in December 2013 in the North Sea partly flooded the Port of Immingham, which handles the largest volume of bulk cargo in the UK including major flows of coal and biomass for power generation. This flooding caused damage to port and rail transport infrastructure and disrupted operations for several weeks. This research aims to improve resilience to storm surges using hydrodynamic modelling coupled to an agent-based model of port operations. Using the December 2013 event to validate flood extent, depth and duration, we ran a high resolution hydrodynamic simulation using the open source Telemac 2D finite element code. The underlying Digital Elevation Model (DEM) was derived from Environment Agency LiDAR data, with ground truthing of the flood defences along the port frontage. Major infrastructure and buildings are explicitly resolved with varying degrees of permeability. Telemac2D simulations are run in parallel and take only minutes on a single 16 cpu compute node. Inundation characteristics predicted using Telemac 2D differ from a simple Geographical Information System 'bath-tub' analysis of the DEM based upon horizontal application of the maximum water level across the port topography. The hydrodynamic simulation predicts less extensive flooding and more closely matches observed flood extent. It also provides more precise depth and duration curves. Detailed spatial flood depth and duration maps were generated for a range of tide and surge scenarios coupled to mean sea-level rise projections. These inundation scenarios can then be integrated with critical asset databases and an agent-based model of port operation (MARS) that is capable of simulating storm surge disruption along wider supply chains. Port operators are able to act on information from a particular

  8. Effective Feature Preprocessing for Time Series Forecasting

    DEFF Research Database (Denmark)

    Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

    2006-01-01

    Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

  9. Long-Range Lightning Products for Short Term Forecasting of Tropical Cyclogenesis

    Science.gov (United States)

    Businger, S.; Pessi, A.; Robinson, T.; Stolz, D.

    2010-12-01

    This paper will describe innovative graphical products derived in real time from long-range lightning data. The products have been designed to aid in short-term forecasting of tropical cyclone development for the Tropical Cyclone Structure Experiment 2010 (TCS10) held over the western Pacific Ocean from 17 August to 17 October 2010 and are available online at http://www.soest.hawaii.edu/cgi-bin/pacnet/tcs10.pl. The long-range lightning data are from Vaisala’s Global Lightning Data 360 (GLD360) network and include time, location, current strength, polarity, and data quality indication. The products currently provided in real time include i. Infrared satellite imagery overlaid with lighting flash locations, with color indication of current strength and polarity (shades of blue for negative to ground and red for positive to ground). ii. A 15x15 degree storm-centered tile of IR imagery overlaid with lightning data as in i). iii. A pseudo reflectivity product showing estimates of radar reflectivity based on lightning rate - rain rate conversion derived from TRMM and PacNet data. iv. A lightning history product that plots each hour of lightning flash locations in a different color for a 12-hour period. v. Graphs of lightning counts within 50 or 300 km radius, respectively, of the storm center vs storm central sea-level pressure. vi. A 2-D graphic showing storm core lightning density along the storm track. The first three products above can be looped to gain a better understanding of the evolution of the lightning and storm structure. Examples of the graphics and their utility will be demonstrated and discussed. Histogram of lightning counts within 50 km of the storm center and graph of storm central pressure as a function of time.

  10. Reproducing Electric Field Observations during Magnetic Storms by means of Rigorous 3-D Modelling and Distortion Matrix Co-estimation

    Science.gov (United States)

    Püthe, Christoph; Manoj, Chandrasekharan; Kuvshinov, Alexey

    2015-04-01

    Electric fields induced in the conducting Earth during magnetic storms drive currents in power transmission grids, telecommunication lines or buried pipelines. These geomagnetically induced currents (GIC) can cause severe service disruptions. The prediction of GIC is thus of great importance for public and industry. A key step in the prediction of the hazard to technological systems during magnetic storms is the calculation of the geoelectric field. To address this issue for mid-latitude regions, we developed a method that involves 3-D modelling of induction processes in a heterogeneous Earth and the construction of a model of the magnetospheric source. The latter is described by low-degree spherical harmonics; its temporal evolution is derived from observatory magnetic data. Time series of the electric field can be computed for every location on Earth's surface. The actual electric field however is known to be perturbed by galvanic effects, arising from very local near-surface heterogeneities or topography, which cannot be included in the conductivity model. Galvanic effects are commonly accounted for with a real-valued time-independent distortion matrix, which linearly relates measured and computed electric fields. Using data of various magnetic storms that occurred between 2000 and 2003, we estimated distortion matrices for observatory sites onshore and on the ocean bottom. Strong correlations between modellings and measurements validate our method. The distortion matrix estimates prove to be reliable, as they are accurately reproduced for different magnetic storms. We further show that 3-D modelling is crucial for a correct separation of galvanic and inductive effects and a precise prediction of electric field time series during magnetic storms. Since the required computational resources are negligible, our approach is suitable for a real-time prediction of GIC. For this purpose, a reliable forecast of the source field, e.g. based on data from satellites

  11. Local TEC Modelling and Forecasting using Neural Networks

    Science.gov (United States)

    Tebabal, A.; Radicella, S. M.; Nigussie, M.; Damtie, B.; Nava, B.; Yizengaw, E.

    2017-12-01

    Abstract Modelling the Earth's ionospheric characteristics is the focal task for the ionospheric community to mitigate its effect on the radio communication, satellite navigation and technologies. However, several aspects of modelling are still challenging, for example, the storm time characteristics. This paper presents modelling efforts of TEC taking into account solar and geomagnetic activity, time of the day and day of the year using neural networks (NNs) modelling technique. The NNs have been designed with GPS-TEC measured data from low and mid-latitude GPS stations. The training was conducted using the data obtained for the period from 2011 to 2014. The model prediction accuracy was evaluated using data of year 2015. The model results show that diurnal and seasonal trend of the GPS-TEC is well reproduced by the model for the two stations. The seasonal characteristics of GPS-TEC is compared with NN and NeQuick 2 models prediction when the latter one is driven by the monthly average value of solar flux. It is found that NN model performs better than the corresponding NeQuick 2 model for low latitude region. For the mid-latitude both NN and NeQuick 2 models reproduce the average characteristics of TEC variability quite successfully. An attempt of one day ahead forecast of TEC at the two locations has been made by introducing as driver previous day solar flux and geomagnetic index values. The results show that a reasonable day ahead forecast of local TEC can be achieved.

  12. Ionospheric storms at geophysically-equivalent sites – Part 1: Storm-time patterns for sub-auroral ionospheres

    Directory of Open Access Journals (Sweden)

    M. Mendillo

    2009-04-01

    Full Text Available The systematic study of ionospheric storms has been conducted primarily with groundbased data from the Northern Hemisphere. Significant progress has been made in defining typical morphology patterns at all latitudes; mechanisms have been identified and tested via modeling. At higher mid-latitudes (sites that are typically sub-auroral during non-storm conditions, the processes that change significantly during storms can be of comparable magnitudes, but with different time constants. These include ionospheric plasma dynamics from the penetration of magnetospheric electric fields, enhancements to thermospheric winds due to auroral and Joule heating inputs, disturbance dynamo electrodynamics driven by such winds, and thermospheric composition changes due to the changed circulation patterns. The ~12° tilt of the geomagnetic field axis causes significant longitude effects in all of these processes in the Northern Hemisphere. A complementary series of longitude effects would be expected to occur in the Southern Hemisphere. In this paper we begin a series of studies to investigate the longitudinal-hemispheric similarities and differences in the response of the ionosphere's peak electron density to geomagnetic storms. The ionosonde stations at Wallops Island (VA and Hobart (Tasmania have comparable geographic and geomagnetic latitudes for sub-auroral locations, are situated at longitudes close to that of the dipole tilt, and thus serve as our candidate station-pair choice for studies of ionospheric storms at geophysically-comparable locations. They have an excellent record of observations of the ionospheric penetration frequency (foF2 spanning several solar cycles, and thus are suitable for long-term studies. During solar cycle #20 (1964–1976, 206 geomagnetic storms occurred that had Ap≥30 or Kp≥5 for at least one day of the storm. Our analysis of average storm-time perturbations (percent deviations from the monthly means showed a remarkable

  13. Seasat microwave wind and rain observations in severe tropical and midlatitude marine storms

    Science.gov (United States)

    Black, P. G.; Hawkins, J. D.; Gentry, R. C.; Cardone, V. J.

    1985-01-01

    Initial results of studies concerning Seasat measurements in and around tropical and severe midlatitude cyclones over the open ocean are presented, together with an assessment of their accuracy and usefulness. Complementary measurements of surface wind speed and direction, rainfall rate, and the sea surface temperature obtained with the Seasat-A Satellite Scatterometer (SASS), the Scanning Multichannel Microwave Radiometer (SMMR), and the Seasat SAR are analyzed. The Seasat data for the Hurrricanes Fico, Ella, and Greta and the QE II storm are compared with data obtained from aircraft, buoys, and ships. It is shown that the SASS-derived wind speeds are accurate to within 10 percent, and the directions are accurate to within 20 percent. In general, the SASS estimates tend to measure light winds too high and intense winds too low. The errors of the SMMR-derived measurements of the winds in hurricanes tend to be higher than those of the SASS-derived measurements.

  14. Impact of a Diagnostic Pressure Equation Constraint on Tornadic Supercell Thunderstorm Forecasts Initialized Using 3DVAR Radar Data Assimilation

    Directory of Open Access Journals (Sweden)

    Guoqing Ge

    2013-01-01

    Full Text Available A diagnostic pressure equation constraint has been incorporated into a storm-scale three-dimensional variational (3DVAR data assimilation system. This diagnostic pressure equation constraint (DPEC is aimed to improve dynamic consistency among different model variables so as to produce better data assimilation results and improve the subsequent forecasts. Ge et al. (2012 described the development of DPEC and testing of it with idealized experiments. DPEC was also applied to a real supercell case, but only radial velocity was assimilated. In this paper, DPEC is further applied to two real tornadic supercell thunderstorm cases, where both radial velocity and radar reflectivity data are assimilated. The impact of DPEC on radar data assimilation is examined mainly based on the storm forecasts. It is found that the experiments using DPEC generally predict higher low-level vertical vorticity than the experiments not using DPEC near the time of observed tornadoes. Therefore, it is concluded that the use of DPEC improves the forecast of mesocyclone rotation within supercell thunderstorms. The experiments using different weighting coefficients generate similar results. This suggests that DPEC is not very sensitive to the weighting coefficients.

  15. A novel ice storm manipulation experiment in a northern hardwood forest

    Science.gov (United States)

    Lindsey E. Rustad; John L. Campbell

    2012-01-01

    Ice storms are an important natural disturbance within forest ecosystems of the northeastern United States. Current models suggest that the frequency and severity of ice storms may increase in the coming decades in response to changes in climate. Because of the stochastic nature of ice storms and difficulties in predicting their occurrence, most past investigations of...

  16. Uncertainty Forecasts Improve Weather-Related Decisions and Attenuate the Effects of Forecast Error

    Science.gov (United States)

    Joslyn, Susan L.; LeClerc, Jared E.

    2012-01-01

    Although uncertainty is inherent in weather forecasts, explicit numeric uncertainty estimates are rarely included in public forecasts for fear that they will be misunderstood. Of particular concern are situations in which precautionary action is required at low probabilities, often the case with severe events. At present, a categorical weather…

  17. Clustering of European winter storms: A multi-model perspective

    Science.gov (United States)

    Renggli, Dominik; Buettner, Annemarie; Scherb, Anke; Straub, Daniel; Zimmerli, Peter

    2016-04-01

    The storm series over Europe in 1990 (Daria, Vivian, Wiebke, Herta) and 1999 (Anatol, Lothar, Martin) are very well known. Such clusters of severe events strongly affect the seasonally accumulated damage statistics. The (re)insurance industry has quantified clustering by using distribution assumptions deduced from the historical storm activity of the last 30 to 40 years. The use of storm series simulated by climate models has only started recently. Climate model runs can potentially represent 100s to 1000s of years, allowing a more detailed quantification of clustering than the history of the last few decades. However, it is unknown how sensitive the representation of clustering is to systematic biases. Using a multi-model ensemble allows quantifying that uncertainty. This work uses CMIP5 decadal ensemble hindcasts to study clustering of European winter storms from a multi-model perspective. An objective identification algorithm extracts winter storms (September to April) in the gridded 6-hourly wind data. Since the skill of European storm predictions is very limited on the decadal scale, the different hindcast runs are interpreted as independent realizations. As a consequence, the available hindcast ensemble represents several 1000 simulated storm seasons. The seasonal clustering of winter storms is quantified using the dispersion coefficient. The benchmark for the decadal prediction models is the 20th Century Reanalysis. The decadal prediction models are able to reproduce typical features of the clustering characteristics observed in the reanalysis data. Clustering occurs in all analyzed models over the North Atlantic and European region, in particular over Great Britain and Scandinavia as well as over Iberia (i.e. the exit regions of the North Atlantic storm track). Clustering is generally weaker in the models compared to reanalysis, although the differences between different models are substantial. In contrast to existing studies, clustering is driven by weak

  18. Solid low-level waste forecasting guide

    International Nuclear Information System (INIS)

    Templeton, K.J.; Dirks, L.L.

    1995-03-01

    Guidance for forecasting solid low-level waste (LLW) on a site-wide basis is described in this document. Forecasting is defined as an approach for collecting information about future waste receipts. The forecasting approach discussed in this document is based solely on hanford's experience within the last six years. Hanford's forecasting technique is not a statistical forecast based upon past receipts. Due to waste generator mission changes, startup of new facilities, and waste generator uncertainties, statistical methods have proven to be inadequate for the site. It is recommended that an approach similar to Hanford's annual forecasting strategy be implemented at each US Department of Energy (DOE) installation to ensure that forecast data are collected in a consistent manner across the DOE complex. Hanford's forecasting strategy consists of a forecast cycle that can take 12 to 30 months to complete. The duration of the cycle depends on the number of LLW generators and staff experience; however, the duration has been reduced with each new cycle. Several uncertainties are associated with collecting data about future waste receipts. Volume, shipping schedule, and characterization data are often reported as estimates with some level of uncertainty. At Hanford, several methods have been implemented to capture the level of uncertainty. Collection of a maximum and minimum volume range has been implemented as well as questionnaires to assess the relative certainty in the requested data

  19. Modeling the Effects of Storm Surge from Hurricane Jeanne on Saltwater Intrusion into the Surficial Aquifer, East-Central Florida (USA)

    Science.gov (United States)

    Xiao, H.; Wang, D.; Hagen, S. C.; Medeiros, S. C.; Hall, C. R.

    2017-12-01

    Saltwater intrusion (SWI) that has been widely recognized as a detrimental issue causing the deterioration of coastal aquifer water quality and degradation of coastal ecosystems. While it is widely recognized that SWI is exacerbated worldwide due to global sea-level rise, we show that increased SWI from tropical cyclones under climate change is also a concern. In the Cape Canaveral Barrier Island Complex (CCBIC) located in east-central Florida, the salinity level of the surficial aquifer is of great importance to maintain a bio-diverse ecosystem and to support the survival of various vegetation species. Climate change induced SWI into the surficial aquifer can lead to reduction of freshwater storage and alteration of the distribution and productivity of vegetation communities. In this study, a three-dimensional variable-density SEAWAT model is developed and calibrated to investigate the spatial and temporal variation of salinity level in the surficial aquifer of CCBIC. We link the SEAWAT model to surge model data to examine the effects of storm surge from Hurricane Jeanne. Simulation results indicate that the surficial aquifer salinity level increases significantly right after the occurrence of storm surge because of high aquifer permeability and rapid infiltration and diffusion of the overtopping saltwater, while the surficial aquifer salinity level begins to decrease after the fresh groundwater recharge from the storm's rainfall. The tropical storm precipitation generates an effective hydraulic barrier further impeding SWI and providing seaward freshwater discharge for saltwater dilution and flushing. To counteract the catastrophic effects of storm surge, this natural remediation process may take at least 15-20 years or even several decades. These simulation results contribute to ongoing research focusing on forecasting regional vegetation community responses to climate change, and are expected to provide a useful reference for climate change adaptation planning

  20. Applications of Earth Remote Sensing for Identifying Tornado and Severe Weather Damage

    Science.gov (United States)

    Schultz, Lori; Molthan, Andrew; Burks, Jason E.; Bell, Jordan; McGrath, Kevin; Cole, Tony

    2016-01-01

    NASA SPoRT (Short-term Prediction Research and Transition Center) provided MODIS (Moderate Resolution Imaging Spectrometer) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) imagery to WFOs (Weather Forecast Offices) in Alabama to support April 27th, 2011 damage assessments across the state. SPoRT was awarded a NASA Applied Science: Disasters Feasibility award to investigate the applicability of including remote sensing imagery and derived products into the NOAA/NWS (National Oceanic and Atmospheric Administration/National Weather System) Damage Assessment Toolkit (DAT). Proposal team was awarded the 3-year proposal to implement a web mapping service and associate data feeds from the USGS (U.S. Geological Survey) to provide satellite imagery and derived products directly to the NWS thru the DAT. In the United States, NOAA/NWS is charged with performing damage assessments when storm or tornado damage is suspected after a severe weather event. This has led to the development of the Damage Assessment Toolkit (DAT), an application for smartphones, tablets and web browsers that allows for the collection, geo-location, and aggregation of various damage indicators collected during storm surveys.

  1. Comparison of two recent storm surge events based on results of field surveys

    Science.gov (United States)

    Nakamura, Ryota; Shibayama, Tomoya; Mikami, Takahito; Esteban, Miguel; Takagi, Hiroshi; Maell, Martin; Iwamoto, Takumu

    2017-10-01

    This paper compares two different types of storm surge disaster based on field surveys. Two cases: a severe storm surge flood with its height of over 5 m due to Typhoon Haiyan (2013) in Philippine, and inundation of storm surge around Nemuro city in Hokkaido of Japan with its maximum surge height of 2.8 m caused by extra-tropical cyclone are taken as examples. For the case of the Typhoon Haiyan, buildings located in coastal region were severely affected due to a rapidly increase in ocean surface. The non-engineering buildings were partially or completely destroyed due to their debris transported to an inner bay region. In fact, several previous reports indicated two unique features, bore-like wave and remarkably high speed currents. These characteristics of the storm surge may contribute to a wide-spread corruption for the buildings around the affected region. Furthermore, in the region where the surge height was nearly 3 m, the wooden houses were completely or partially destroyed. On the other hand, in Nemuro city, a degree of suffering in human and facility caused by the storm surge is minor. There was almost no partially destroyed residential houses even though the height of storm surge reached nearly 2.8 m. An observation in the tide station in Nemuro indicated that this was a usual type of storm surge, which showed a gradual increase of sea level height in several hours without possessing the unique characteristics like Typhoon Haiyan. As a result, not only the height of storm surge but also the robustness of the buildings and characteristics of storm surge, such as bore like wave and strong currents, determined the existent of devastation in coastal regions.

  2. Ensemble forecasting using sequential aggregation for photovoltaic power applications

    International Nuclear Information System (INIS)

    Thorey, Jean

    2017-01-01

    Our main objective is to improve the quality of photovoltaic power forecasts deriving from weather forecasts. Such forecasts are imperfect due to meteorological uncertainties and statistical modeling inaccuracies in the conversion of weather forecasts to power forecasts. First we gather several weather forecasts, secondly we generate multiple photovoltaic power forecasts, and finally we build linear combinations of the power forecasts. The minimization of the Continuous Ranked Probability Score (CRPS) allows to statistically calibrate the combination of these forecasts, and provides probabilistic forecasts under the form of a weighted empirical distribution function. We investigate the CRPS bias in this context and several properties of scoring rules which can be seen as a sum of quantile-weighted losses or a sum of threshold-weighted losses. The minimization procedure is achieved with online learning techniques. Such techniques come with theoretical guarantees of robustness on the predictive power of the combination of the forecasts. Essentially no assumptions are needed for the theoretical guarantees to hold. The proposed methods are applied to the forecast of solar radiation using satellite data, and the forecast of photovoltaic power based on high-resolution weather forecasts and standard ensembles of forecasts. (author) [fr

  3. Predicting Power Outages Using Multi-Model Ensemble Forecasts

    Science.gov (United States)

    Cerrai, D.; Anagnostou, E. N.; Yang, J.; Astitha, M.

    2017-12-01

    Power outages affect every year millions of people in the United States, affecting the economy and conditioning the everyday life. An Outage Prediction Model (OPM) has been developed at the University of Connecticut for helping utilities to quickly restore outages and to limit their adverse consequences on the population. The OPM, operational since 2015, combines several non-parametric machine learning (ML) models that use historical weather storm simulations and high-resolution weather forecasts, satellite remote sensing data, and infrastructure and land cover data to predict the number and spatial distribution of power outages. A new methodology, developed for improving the outage model performances by combining weather- and soil-related variables using three different weather models (WRF 3.7, WRF 3.8 and RAMS/ICLAMS), will be presented in this study. First, we will present a performance evaluation of each model variable, by comparing historical weather analyses with station data or reanalysis over the entire storm data set. Hence, each variable of the new outage model version is extracted from the best performing weather model for that variable, and sensitivity tests are performed for investigating the most efficient variable combination for outage prediction purposes. Despite that the final variables combination is extracted from different weather models, this ensemble based on multi-weather forcing and multi-statistical model power outage prediction outperforms the currently operational OPM version that is based on a single weather forcing variable (WRF 3.7), because each model component is the closest to the actual atmospheric state.

  4. Learning Storm

    CERN Document Server

    Jain, Ankit

    2014-01-01

    If you are a Java developer who wants to enter into the world of real-time stream processing applications using Apache Storm, then this book is for you. No previous experience in Storm is required as this book starts from the basics. After finishing this book, you will be able to develop not-so-complex Storm applications.

  5. Validation of the CME Geomagnetic forecast alerts under COMESEP alert system

    Science.gov (United States)

    Dumbovic, Mateja; Srivastava, Nandita; Khodia, Yamini; Vršnak, Bojan; Devos, Andy; Rodriguez, Luciano

    2017-04-01

    An automated space weather alert system has been developed under the EU FP7 project COMESEP (COronal Mass Ejections and Solar Energetic Particles: http://comesep.aeronomy.be) to forecast solar energetic particles (SEP) and coronal mass ejection (CME) risk levels at Earth. COMESEP alert system uses automated detection tool CACTus to detect potentially threatening CMEs, drag-based model (DBM) to predict their arrival and CME geo-effectiveness tool (CGFT) to predict their geomagnetic impact. Whenever CACTus detects a halo or partial halo CME and issues an alert, DBM calculates its arrival time at Earth and CGFT calculates its geomagnetic risk level. Geomagnetic risk level is calculated based on an estimation of the CME arrival probability and its likely geo-effectiveness, as well as an estimate of the geomagnetic-storm duration. We present the evaluation of the CME risk level forecast with COMESEP alert system based on a study of geo-effective CMEs observed during 2014. The validation of the forecast tool is done by comparing the forecasts with observations. In addition, we test the success rate of the automatic forecasts (without human intervention) against the forecasts with human intervention using advanced versions of DBM and CGFT (self standing tools available at Hvar Observatory website: http://oh.geof.unizg.hr). The results implicate that the success rate of the forecast is higher with human intervention and using more advanced tools. This work has received funding from the European Commission FP7 Project COMESEP (263252). We acknowledge the support of Croatian Science Foundation under the project 6212 „Solar and Stellar Variability".

  6. Verification of high-speed solar wind stream forecasts using operational solar wind models

    DEFF Research Database (Denmark)

    Reiss, Martin A.; Temmer, Manuela; Veronig, Astrid M.

    2016-01-01

    and the background solar wind conditions. We found that both solar wind models are capable of predicting the large-scale features of the observed solar wind speed (root-mean-square error, RMSE ≈100 km/s) but tend to either overestimate (ESWF) or underestimate (WSA) the number of high-speed solar wind streams (threat......High-speed solar wind streams emanating from coronal holes are frequently impinging on the Earth's magnetosphere causing recurrent, medium-level geomagnetic storm activity. Modeling high-speed solar wind streams is thus an essential element of successful space weather forecasting. Here we evaluate...... high-speed stream forecasts made by the empirical solar wind forecast (ESWF) and the semiempirical Wang-Sheeley-Arge (WSA) model based on the in situ plasma measurements from the Advanced Composition Explorer (ACE) spacecraft for the years 2011 to 2014. While the ESWF makes use of an empirical relation...

  7. The development of the Australian Space Forecast Centre (ASFC)

    Science.gov (United States)

    Wilkinson, Phil; Kennewell, John A.; Cole, David

    2018-05-01

    The Ionospheric Prediction Service (IPS) was formed in 1947 to provide monthly prediction services for high frequency (HF) radio, in particular to support HF communications with the United Kingdom. It was quickly recognized that to be effective such a service also had to provide advice when ionospheric storms prevented HF communications from taking place. With the advent of the International Geophysical Year (IGY), short-term forecasts were also required for research programmes and the task of supplying the Australian input to these was given to Frank Cook, of the IPS, while Jack Turner, also of the IPS, supervised the generation of ionospheric maps to support high latitude HF communications. These two important IGY activities formed the platform on which all future IPS services would be built. This paper reviews the development of the Australian Space Forecast Centre (ASFC), which arose from these early origins.

  8. Ensemble Kalman Filter data assimilation and storm surge experiments of tropical cyclone Nargis

    Directory of Open Access Journals (Sweden)

    Le Duc

    2015-07-01

    Full Text Available Data assimilation experiments on Myanmar tropical cyclone (TC, Nargis, using the Local Ensemble Transform Kalman Filter (LETKF method and the Japan Meteorological Agency (JMA non-hydrostatic model (NHM were performed to examine the impact of LETKF on analysis performance in real cases. Although the LETKF control experiment using NHM as its driving model (NHM–LETKF produced a weak vortex, the subsequent 3-day forecast predicted Nargis’ track and intensity better than downscaling from JMA's global analysis. Some strategies to further improve the final analysis were considered. They were sea surface temperature (SST perturbations and assimilation of TC advisories. To address SST uncertainty, SST analyses issued by operational forecast centres were used in the assimilation window. The use of a fixed source of SST analysis for each ensemble member was more effective in practice. SST perturbations were found to have slightly positive impact on the track forecasts. Assimilation of TC advisories could have a positive impact with a reasonable choice of its free parameters. However, the TC track forecasts exhibited northward displacements, when the observation error of intensities was underestimated in assimilation of TC advisories. The use of assimilation of TC advisories was considered in the final NHM–LETKF by choosing an appropriate set of free parameters. The extended forecast based on the final analysis provided meteorological forcings for a storm surge simulation using the Princeton Ocean Model. Probabilistic forecasts of the water levels at Irrawaddy and Yangon significantly improved the results in the previous studies.

  9. Hindcast of extreme sea states in North Atlantic extratropical storms

    Science.gov (United States)

    Ponce de León, Sonia; Guedes Soares, Carlos

    2015-02-01

    This study examines the variability of freak wave parameters around the eye of northern hemisphere extratropical cyclones. The data was obtained from a hindcast performed with the WAve Model (WAM) model forced by the wind fields of the Climate Forecast System Reanalysis (CFSR). The hindcast results were validated against the wave buoys and satellite altimetry data showing a good correlation. The variability of different wave parameters was assessed by applying the empirical orthogonal functions (EOF) technique on the hindcast data. From the EOF analysis, it can be concluded that the first empirical orthogonal function (V1) accounts for greater share of variability of significant wave height (Hs), peak period (Tp), directional spreading (SPR) and Benjamin-Feir index (BFI). The share of variance in V1 varies for cyclone and variable: for the 2nd storm and Hs V1 contains 96 % of variance while for the 3rd storm and BFI V1 accounts only for 26 % of variance. The spatial patterns of V1 show that the variables are distributed around the cyclones centres mainly in a lobular fashion.

  10. Using HPC within an operational forecasting configuration

    Science.gov (United States)

    Jagers, H. R. A.; Genseberger, M.; van den Broek, M. A. F. H.

    2012-04-01

    Various natural disasters are caused by high-intensity events, for example: extreme rainfall can in a short time cause major damage in river catchments, storms can cause havoc in coastal areas. To assist emergency response teams in operational decisions, it's important to have reliable information and predictions as soon as possible. This starts before the event by providing early warnings about imminent risks and estimated probabilities of possible scenarios. In the context of various applications worldwide, Deltares has developed an open and highly configurable forecasting and early warning system: Delft-FEWS. Finding the right balance between simulation time (and hence prediction lead time) and simulation accuracy and detail is challenging. Model resolution may be crucial to capture certain critical physical processes. Uncertainty in forcing conditions may require running large ensembles of models; data assimilation techniques may require additional ensembles and repeated simulations. The computational demand is steadily increasing and data streams become bigger. Using HPC resources is a logical step; in different settings Delft-FEWS has been configured to take advantage of distributed computational resources available to improve and accelerate the forecasting process (e.g. Montanari et al, 2006). We will illustrate the system by means of a couple of practical applications including the real-time dynamic forecasting of wind driven waves, flow of water, and wave overtopping at dikes of Lake IJssel and neighboring lakes in the center of The Netherlands. Montanari et al., 2006. Development of an ensemble flood forecasting system for the Po river basin, First MAP D-PHASE Scientific Meeting, 6-8 November 2006, Vienna, Austria.

  11. Uncertainty in the area-related QPF for heavy convective precipitation

    Czech Academy of Sciences Publication Activity Database

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

    2009-01-01

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

  12. The extreme solar storm of May 1921: observations and a complex topological model

    Directory of Open Access Journals (Sweden)

    H. Lundstedt

    2015-01-01

    Full Text Available A complex solid torus model was developed in order to be able to study an extreme solar storm, the so-called "Great Storm" or "New York Railroad Storm" of May 1921, when neither high spatial and time resolution magnetic field measurements, solar flare nor coronal mass ejection observations were available. We suggest that a topological change happened in connection with the occurrence of the extreme solar storm. The solar storm caused one of the most severe space weather effects ever.

  13. Magnetogram Forecast: An All-Clear Space Weather Forecasting System

    Science.gov (United States)

    Barghouty, Nasser; Falconer, David

    2015-01-01

    Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

  14. MiKlip-PRODEF: Probabilistic Decadal Forecast for Central and Western Europe

    Science.gov (United States)

    Reyers, Mark; Haas, Rabea; Ludwig, Patrick; Pinto, Joaquim

    2013-04-01

    The demand for skilful climate predictions on time-scales of several years to decades has increased in recent years, in particular for economic, societal and political terms. Within the BMBF MiKlip consortium, a decadal prediction system on the global to local scale is currently being developed. The subproject PRODEF is part of the MiKlip-Module C, which aims at the regionalisation of decadal predictability for Central and Western Europe. In PRODEF, a combined statistical-dynamical downscaling (SDD) and a probabilistic forecast tool are developed and applied to the new Earth system model of the Max-Planck Institute Hamburg (MPI-ESM), which is part of the CMIP5 experiment. Focus is given on the decadal predictability of windstorms, related wind gusts as well as wind energy potentials. SDD combines the benefits of both high resolution dynamical downscaling and purely statistical downscaling of GCM output. Hence, the SDD approach is used to obtain a very large ensemble of highly resolved decadal forecasts. With respect to the focal points of PRODEF, a clustering of temporal evolving atmospheric fields, a circulation weather type (CWT) analysis, and a storm damage indices analysis is applied to the full ensemble of the decadal hindcast experiments of the MPI-ESM in its lower resolution (MPI-ESM-LR). The ensemble consists of up to ten realisations per yearly initialised decadal hindcast experiments for the period 1960-2010 (altogether 287 realisations). Representatives of CWTs / clusters and single storm episodes are dynamical downscaled with the regional climate model COSMO-CLM with a horizontal resolution of 0.22°. For each model grid point, the distributions of the local climate parameters (e.g. surface wind gusts) are determined for different periods (e.g. each decades) by recombining dynamical downscaled episodes weighted with the respective weather type frequencies. The applicability of the SDD approach is illustrated with examples of decadal forecasts of the MPI

  15. Recent Atlantic Hurricanes, Pacific Super Typhoons, and Tropical Storm Awareness in Underdeveloped Island and Coastal Regions

    Science.gov (United States)

    Plondke, D. L.

    2017-12-01

    about the urgency of climate change mitigation. Lacking in most of the island and coastal environments where major storms occur and are likely to occur more frequently in the future are educational opportunities and public dissemination of information about climate change forecasts, storm impact mitigation, and emergency preparedness.

  16. Solar particle radiation storms forecasting and analysis the HESPERIA HORIZON 2020 project and beyond

    CERN Document Server

    Crosby, Norma

    2018-01-01

    Solar energetic particles (SEPs) emitted from the Sun are a major space weather hazard motivating the development of predictive capabilities. This book presents the results and findings of the HESPERIA (High Energy Solar Particle Events forecasting and Analysis) project of the EU HORIZON 2020 programme. It discusses the forecasting operational tools developed within the project, and presents progress to SEP research contributed by HESPERIA both from the observational as well as the SEP modelling perspective. Using multi-frequency observational data and simulations HESPERIA investigated the chain of processes from particle acceleration in the corona, particle transport in the magnetically complex corona and interplanetary space, to the detection near 1 AU. The book also elaborates on the unique software that has been constructed for inverting observations of relativistic SEPs to physical parameters that can be compared with spac e-borne measurements at lower energies. Introductory and pedagogical material incl...

  17. A Basis Function Approach to Simulate Storm Surge Events for Coastal Flood Risk Assessment

    Science.gov (United States)

    Wu, Wenyan; Westra, Seth; Leonard, Michael

    2017-04-01

    Storm surge is a significant contributor to flooding in coastal and estuarine regions, especially when it coincides with other flood producing mechanisms, such as extreme rainfall. Therefore, storm surge has always been a research focus in coastal flood risk assessment. Often numerical models have been developed to understand storm surge events for risk assessment (Kumagai et al. 2016; Li et al. 2016; Zhang et al. 2016) (Bastidas et al. 2016; Bilskie et al. 2016; Dalledonne and Mayerle 2016; Haigh et al. 2014; Kodaira et al. 2016; Lapetina and Sheng 2015), and assess how these events may change or evolve in the future (Izuru et al. 2015; Oey and Chou 2016). However, numeric models often require a lot of input information and difficulties arise when there are not sufficient data available (Madsen et al. 2015). Alternative, statistical methods have been used to forecast storm surge based on historical data (Hashemi et al. 2016; Kim et al. 2016) or to examine the long term trend in the change of storm surge events, especially under climate change (Balaguru et al. 2016; Oh et al. 2016; Rueda et al. 2016). In these studies, often the peak of surge events is used, which result in the loss of dynamic information within a tidal cycle or surge event (i.e. a time series of storm surge values). In this study, we propose an alternative basis function (BF) based approach to examine the different attributes (e.g. peak and durations) of storm surge events using historical data. Two simple two-parameter BFs were used: the exponential function and the triangular function. High quality hourly storm surge record from 15 tide gauges around Australia were examined. It was found that there are significantly location and seasonal variability in the peak and duration of storm surge events, which provides additional insights in coastal flood risk. In addition, the simple form of these BFs allows fast simulation of storm surge events and minimises the complexity of joint probability

  18. Maximum wind radius estimated by the 50 kt radius: improvement of storm surge forecasting over the western North Pacific

    Science.gov (United States)

    Takagi, Hiroshi; Wu, Wenjie

    2016-03-01

    Even though the maximum wind radius (Rmax) is an important parameter in determining the intensity and size of tropical cyclones, it has been overlooked in previous storm surge studies. This study reviews the existing estimation methods for Rmax based on central pressure or maximum wind speed. These over- or underestimate Rmax because of substantial variations in the data, although an average radius can be estimated with moderate accuracy. As an alternative, we propose an Rmax estimation method based on the radius of the 50 kt wind (R50). Data obtained by a meteorological station network in the Japanese archipelago during the passage of strong typhoons, together with the JMA typhoon best track data for 1990-2013, enabled us to derive the following simple equation, Rmax = 0.23 R50. Application to a recent strong typhoon, the 2015 Typhoon Goni, confirms that the equation provides a good estimation of Rmax, particularly when the central pressure became considerably low. Although this new method substantially improves the estimation of Rmax compared to the existing models, estimation errors are unavoidable because of fundamental uncertainties regarding the typhoon's structure or insufficient number of available typhoon data. In fact, a numerical simulation for the 2013 Typhoon Haiyan as well as 2015 Typhoon Goni demonstrates a substantial difference in the storm surge height for different Rmax. Therefore, the variability of Rmax should be taken into account in storm surge simulations (e.g., Rmax = 0.15 R50-0.35 R50), independently of the model used, to minimize the risk of over- or underestimating storm surges. The proposed method is expected to increase the predictability of major storm surges and to contribute to disaster risk management, particularly in the western North Pacific, including countries such as Japan, China, Taiwan, the Philippines, and Vietnam.

  19. Forecasting Costa Rican Quarterly Growth with Mixed-frequency Models

    Directory of Open Access Journals (Sweden)

    Adolfo Rodríguez Vargas

    2014-11-01

    Full Text Available We assess the utility of mixed-frequency models to forecast the quarterly growth rate of Costa Rican real GDP: we estimate bridge and MiDaS models with several lag lengths using information of the IMAE and compute forecasts (horizons of 0-4 quarters which are compared between themselves, with those of ARIMA models and with those resulting from forecast combinations. Combining the most accurate forecasts is most useful when forecasting in real time, whereas MiDaS forecasts are the best-performing overall: as the forecasting horizon increases, their precisionis affected relatively little; their success rates in predicting the direction of changes in the growth rate are stable, and several forecastsremain unbiased. In particular, forecasts computed from simple MiDaS with 9 and 12 lags are unbiased at all horizons and information sets assessed, and show the highest number of significant differences in forecasting ability in comparison with all other models.

  20. Coastal Storm Surge Analysis: Storm Forcing. Report 3. Intermediate Submission No. 1.3

    Science.gov (United States)

    2013-07-01

    The storm surge study considers both tropical storms and extratropical cyclones for determination of return period storm surge elevations. The...Appendix B: Extratropical Cyclone Selection in Support of FEMA Region III Storm Surge Modeling...stations applied in the storm selection process. ............................................. 56  Table B2. Extratropical cyclones selected from the

  1. Space weather: Modeling and forecasting ionospheric

    International Nuclear Information System (INIS)

    Calzadilla Mendez, A.

    2008-01-01

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

  2. On the robustness of aerosol effects on an idealized supercell storm simulated with a cloud system-resolving model

    Directory of Open Access Journals (Sweden)

    H. Morrison

    2012-08-01

    Full Text Available A cloud system-resolving model (the Weather Research and Forecasting model with 1 km horizontal grid spacing is used to investigate the response of an idealized supercell storm to increased cloud droplet concentrations associated with polluted conditions. The primary focus is on exploring robustness of simulated aerosol effects in the face of complex process interactions and feedbacks between the cloud microphysics and dynamics. Simulations are run using sixteen different model configurations with various microphysical or thermodynamic processes modified or turned off. Robustness of the storm response to polluted conditions is also explored for each configuration by performing additional simulations with small perturbations to the initial conditions. Differences in the domain-mean accumulated surface precipitation and convective mass flux between polluted and pristine conditions are small for almost all model configurations, with relative differences in each quantity generally less than 15%. Configurations that produce a decrease (increase in cold pool strength in polluted conditions also tend to simulate a decrease (increase in surface precipitation and convective mass flux. Combined with an analysis of the dynamical and thermodynamic fields, these results indicate the importance of interactions between microphysics, cold pool evolution, and dynamics along outflow boundaries in explaining the system response. Several model configurations, including the baseline, produce an overall similar storm response (weakening in polluted conditions despite having different microphysical or thermodynamic processes turned off. With hail initiation turned off or the hail fallspeed-size relation set to that of snow, the model produces an invigoration instead of weakening of the storm in polluted conditions. These results highlight the difficulty of foreseeing impacts of changes to model parameterizations and isolating process interactions that drive the system

  3. The New Era in Operational Forecasting

    Science.gov (United States)

    Tobiska, W.; Schunk, R. W.; Sojka, J. J.; Carlson, H. C.; Gardner, L. C.; Scherliess, L.; Zhu, L.; Eccles, J. V.; Rice, D. D.; Bouwer, D.; Bailey, J. J.; Knipp, D. J.; Blake, J. B.; Rex, J.; Fuschino, R.; Mertens, C. J.; Gersey, B.; Wilkins, R.; Atwell, W.

    2012-12-01

    Space weather's effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun's photons, particles, and fields. Of the space environment domains that are affected by space weather, the ionosphere, thermosphere, and even troposphere are key regions that are affected. The Utah State University (USU) Space Weather Center (SWC) and Space Environment Technologies (SET) are developing and producing commercial space weather applications. Key systems for providing timely information about the effects of space weather are SWC's Global Assimilation of Ionospheric Measurements (GAIM) system, SET's Magnetosphere Alert and Prediction System (MAPS), and SET's Automated Radiation Measurements for Aviation Safety (ARMAS) system. GAIM, operated by SWC, improves real-time communication and navigation systems by continuously ingesting up to 10,000 slant TEC measurements every 15-minutes from approximately 500 stations. Ionosonde data from several dozen global stations is ingested every 15 minutes to improve the vertical profiles within GAIM. These operational runs enable the reporting of global radio high frequency (HF) signal strengths and near vertical incidence skywave (NVIS) maps used by amateur radio operators and emergency responders via the http://q-upnow.com website. MAPS provides a forecast Dst index out to 6 days through the data-driven Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. ARMAS is demonstrating a prototype flight of microdosimeters on aircraft to capture the "weather" of the radiation environment for air-crew and passenger safety. It assimilates real-time radiation dose and dose rate data into the global NAIRAS radiation system to correct the global climatology for more accurate radiation fields along flight tracks. This team

  4. Solar Particle Radiation Storms Forecasting and Analysis within the Framework of the `HESPERIA' HORIZON 2020 Project

    Science.gov (United States)

    Posner, A.; Malandraki, O.; Nunez, M.; Heber, B.; Labrenz, J.; Kühl, P.; Milas, N.; Tsiropoula, G.; Pavlos, E.

    2017-12-01

    Two prediction tools that have been developed in the framework of HESPERIA based upon the proven concepts UMASEP and REleASE. Near-relativistic (NR) electrons traveling faster than ions (30 MeV protons have 0.25c) are used to forecast the arrival of protons of Solar Energetic Particle (SEP) events with real-time measurements of NR electrons. The faster electrons arrive at L1 30 to 90 minutes before the slower protons. REleASE (Relativistic Electron Alert System for Exploration, Posner, 2007) uses this effect to predict the proton flux by utilizing actual electron fluxes and their most recent increases. Through HESPERIA, a clone of REleASE was built in open source programming language. The same forecasting principle was adapted to real-time data from ACE/EPAM. It is shown that HESPERIA REleASE forecasting works with any NR electron flux measurements. >500 MeV solar protons are so energetic that they usually have effects on the ground, producing Ground Level Enhancement (GLE) events. Within HESPERIA, a predictor of >500 SEP proton events near earth (geostationary orbit) has been developed. In order to predict these events, UMASEP (Núñez, 2011, 2015) has been used. UMASEP makes a lag-correlation of solar electromagnetic (EM) flux with the particle flux near earth. If the correlation is high, the model infers that there is a magnetic connection through which particles are arriving. If, additionally, the intensity of the flux of the associated solar event is also high, then UMASEP issues a SEP prediction. In the case of the prediction of >500 MeV SEP events, the implemented system, called HESPERIA UMASEP-500, correlates X-ray flux with differential proton fluxes by GOES, and with fluxes collected by neutron monitor stations around the world. When the correlation estimation and flare surpasses thresholds, a >500 MeV SEP forecast is issued. These findings suggest that a synthesis of the various approaches may improve over the status quo. Both forecasting tools are

  5. Oil spill monitoring and forecasting on the Prestige-Nassau accident

    Energy Technology Data Exchange (ETDEWEB)

    Montero, P.; Blanco, J.; Cabanas, J.M.; Maneiro, J.; Pazos, Y.; Morono, A. [Unidade de Observacion Proxima CPAM, Vilaxoan, Pontevedra (Spain); Balseiro, C.F.; Carracedo, P.; Gomez, B.; Penabad, E.; Perez-Munuzuri, V. [MeteoGalicia CMA, Santiago de Compostela (Spain); Braunschweig, F.; Fernandes, R.; Leitao, P.C.; Neves, R. [MARETEC IST, Lisbon (Portugal)

    2003-07-01

    The Prestige-Nassau tanker ship spilled about 10,000 tons of oil off the coast of Spain on November 13, 2002 during a severe storm. On November 19, the ship split in half and sank 133 nautical miles from the Galician coast to a depth of 3,500 metres, spilling another 20,000 tons of oil. The Galician government set up an Office of Nearshore Surveillance and recruited people from the Galician Regional Meteorological Service and the Spanish Institute of Oceanography to monitor the slick and forecast its trajectory. The main spill arrived at Galicia on November 30, damaging most of the coast. A variety of models that combined surface wind drift and ocean currents were used to forecast the movement of the spill. These included the Mothy from MeteoFrance, and DERIVA from the Portuguese Hydrographic Institute. Two models were also developed by MeteoGalicia and MAETEC. The path followed by the oil spill was classified in three parts. The first spill of 10,000 tons took place from November 13 until the ship split in two. The second spill of around 20,000 tons of oil occurred when the ship sank on November 19. The last spill includes oil that continued to leak from the sunken tanker at a rate of 125 tons per day. The trajectory predictions were found to be in good agreement with aerial observations. 24 refs., 10 figs.

  6. Effects of wave-current interaction on storm surge in the Taiwan Strait: Insights from Typhoon Morakot

    Science.gov (United States)

    Yu, Xiaolong; Pan, Weiran; Zheng, Xiangjing; Zhou, Shenjie; Tao, Xiaoqin

    2017-08-01

    The effects of wave-current interaction on storm surge are investigated by a two-dimensional wave-current coupling model through simulations of Typhoon Morakot in the Taiwan Strait. The results show that wind wave and slope of sea floor govern wave setup modulations within the nearshore surf zone. Wave setup during Morakot can contribute up to 24% of the total storm surge with a maximum value of 0.28 m. The large wave setup commonly coincides with enhanced radiation stress gradient, which is itself associated with transfer of wave momentum flux. Water levels are to leading order in modulating significant wave height inside the estuary. High water levels due to tidal change and storm surge stabilize the wind wave and decay wave breaking. Outside of the estuary, waves are mainly affected by the current-induced modification of wind energy input to the wave generation. By comparing the observed significant wave height and water level with the results from uncoupled and coupled simulations, the latter shows a better agreement with the observations. It suggests that wave-current interaction plays an important role in determining the extreme storm surge and wave height in the study area and should not be neglected in a typhoon forecast.

  7. Forecasting metal prices: Do forecasters herd?

    DEFF Research Database (Denmark)

    Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

    2013-01-01

    We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

  8. Thyrotoxicosis and Choledocholithiasis Masquerading as Thyroid Storm

    Directory of Open Access Journals (Sweden)

    Christian L. Horn

    2017-01-01

    Full Text Available A 26-year-old female, thirteen months postpartum, presented to the emergency department for four weeks of epigastric abdominal pain, pruritus, new onset jaundice, and 11.3 kgs (25 lbs unintentional weight loss. On examination, she was afebrile, tachycardic, alert, and oriented and had jaundice with scleral icterus. Labs were significant for undetectable TSH, FT4 that was too high to measure, and elevated total bilirubin, direct bilirubin, alkaline phosphatase, and transaminases. Abdominal ultrasound revealed cholelithiasis without biliary ductal dilation. Treatment for presumed thyroid storm was initiated. Further work-up with magnetic resonance cholangiopancreatography (MRCP revealed an obstructing cholelith within the distal common bile duct. With the presence of choledocholithiasis explaining the jaundice and abdominal pain, plus the absence of CNS alterations, the diagnosis of thyroid storm was revised to thyrotoxicosis complicated by choledocholithiasis. Endoscopic retrograde cholangiopancreatogram (ERCP with sphincterotomy was performed to alleviate the biliary obstruction, with prompt symptomatic improvement. Thyroid storm is a rare manifestation of hyperthyroidism with a high rate of morbidity and mortality. The diagnosis of thyroid storm is based on clinical examination, and abnormal thyroid function tests do not correlate with disease severity. Knowledge of the many manifestations of thyroid storm will facilitate a quick and accurate diagnosis and treatment.

  9. Tornadic storm avoidance behavior in breeding songbirds

    Science.gov (United States)

    Streby, Henry M.; Kramer, Gunnar R.; Peterson, Sean M.; Lehman, Justin A.; Buehler, David A.; Andersen, David E.

    2015-01-01

    Migration is a common behavior used by animals of many taxa to occupy different habitats during different periods. Migrant birds are categorized as either facultative (i.e., those that are forced to migrate by some proximal cue, often weather) or obligate (i.e., those that migrate on a regular cycle). During migration, obligate migrants can curtail or delay flights in response to inclement weather or until favorable winds prevail, and they can temporarily reorient or reverse direction when ecological or meteorological obstacles are encountered. However, it is not known whether obligate migrants undertake facultative migrations and make large-scale movements in response to proximal cues outside of their regular migration periods. Here, we present the first documentation of obligate long-distance migrant birds undertaking a facultative migration, wherein breeding golden-winged warblers (Vermivora chrysoptera) carrying light-level geolocators performed a >1,500 km 5-day circumvention of a severe tornadic storm. The birds evacuated their breeding territories >24 hr before the arrival of the storm and atmospheric variation associated with it. The probable cue, radiating >1,000 km from tornadic storms, perceived by birds and influencing bird behavior and movements, is infrasound (i.e., sound below the range of human hearing). With the predicted increase in severity and frequency of similar storms as anthropogenic climate change progresses, understanding large-scale behavioral responses of animals to such events will be an important objective of future research.

  10. The development of a probabilistic approach to forecast coastal change

    Science.gov (United States)

    Lentz, Erika E.; Hapke, Cheryl J.; Rosati, Julie D.; Wang, Ping; Roberts, Tiffany M.

    2011-01-01

    This study demonstrates the applicability of a Bayesian probabilistic model as an effective tool in predicting post-storm beach changes along sandy coastlines. Volume change and net shoreline movement are modeled for two study sites at Fire Island, New York in response to two extratropical storms in 2007 and 2009. Both study areas include modified areas adjacent to unmodified areas in morphologically different segments of coast. Predicted outcomes are evaluated against observed changes to test model accuracy and uncertainty along 163 cross-shore transects. Results show strong agreement in the cross validation of predictions vs. observations, with 70-82% accuracies reported. Although no consistent spatial pattern in inaccurate predictions could be determined, the highest prediction uncertainties appeared in locations that had been recently replenished. Further testing and model refinement are needed; however, these initial results show that Bayesian networks have the potential to serve as important decision-support tools in forecasting coastal change.

  11. Operational Impact of Data Collected from the Global Hawk Unmanned Aircraft During SHOUT

    Science.gov (United States)

    Wick, G. A.; Dunion, J. P.; Sippel, J.; Cucurull, L.; Aksoy, A.; Kren, A.; Christophersen, H.; Black, P.

    2017-12-01

    The primary scientific goal of the Sensing Hazards with Operational Unmanned Technology (SHOUT) Project was to determine the potential utility of observations from high-altitude, long-endurance unmanned aircraft systems such as the Global Hawk (GH) aircraft to improve operational forecasts of high-impact weather events or mitigate potential degradation of forecasts in the event of a future gap in satellite coverage. Hurricanes and tropical cyclones are among the most potentially destructive high-impact weather events and pose a major forecasting challenge to NOAA. Major winter storms over the Pacific Ocean, including atmospheric river events, which make landfall and bring strong winds and extreme precipitation to the West Coast and Alaska are also important to forecast accurately because of their societal impact in those parts of the country. In response, the SHOUT project supported three field campaigns with the GH aircraft and dedicated data impact studies exploring the potential for the real-time data from the aircraft to improve the forecasting of both tropical cyclones and landfalling Pacific storms. Dropsonde observations from the GH aircraft were assimilated into the operational Hurricane Weather Research and Forecasting (HWRF) and Global Forecast System (GFS) models. The results from several diverse but complementary studies consistently demonstrated significant positive forecast benefits spanning the regional and global models. Forecast skill improvements within HWRF reached up to about 9% for track and 14% for intensity. Within GFS, track skill improvements for multi-storm averages exceeded 10% and improvements for individual storms reached over 20% depending on forecast lead time. Forecasted precipitation was also improved. Impacts for Pacific winter storms were smaller but still positive. The results are highly encouraging and support the potential for operational utilization of data from a platform like the GH. This presentation summarizes the

  12. Utilizing NASA Earth Observations to Monitor, Map, and Forecast Mangrove Extent and Deforestation in Myanmar for Enhanced Conservation

    Science.gov (United States)

    Ferraro, C. P.; Jensen, D.; Disla, C.

    2013-12-01

    Mangrove ecosystems offer several significant services including providing habitat and spawning grounds for a diverse range of species, protecting coastal communities from storms and other natural disasters, and contributing resources and income for local residents. Currently, Myanmar is undergoing a period of rapid economic development which has led to increased pressure on the extensive mangrove habitat in the Ayeyarwady River Delta in southern Myanmar. In this study, we partnered with the Smithsonian Conservation Biology Institute to examine changes to mangrove extent between 1989 and 2013 using Landsat 4, 7, and 8 imagery in combination with a Digital Elevation Model (DEM) generated from ASTER stereoscopic imagery. Classification was performed using a Random Forests model and accuracy was assessed using higher resolution ASTER imagery and local expertise on mangrove distribution. Results show a large and consistent decline in mangrove cover during the study period. The data provided by this assessment was subsequently used to forecast potential vulnerability and changes to mangrove habitat up to 2030. A multi-layered perceptron was used to model transition potentials for vulnerability forecasting. Forest managers in Myanmar will be able to use the mangrove change maps and forecasts to evaluate current policies and focus future ones to maximize effectiveness. Data and methodology resulting from this project will be useful for future mangrove and land-cover mapping projects in this region.

  13. Geomagnetic storms, super-storms, and their impacts on GPS-based navigation systems

    Science.gov (United States)

    Astafyeva, E.; Yasyukevich, Yu.; Maksikov, A.; Zhivetiev, I.

    2014-07-01

    Using data of GPS receivers located worldwide, we analyze the quality of GPS performance during four geomagnetic storms of different intensity: two super-storms and two intense storms. We show that during super-storms the density of GPS Losses-of-Lock (LoL) increases up to 0.25% at L1 frequency and up to 3% at L2 frequency, and up to 0.15% (at L1) and 1% (at L2) during less intense storms. Also, depending on the intensity of the storm time ionospheric disturbances, the total number of total electron content (TEC) slips can exceed from 4 to 40 times the quiet time level. Both GPS LoL and TEC slips occur during abrupt changes of SYM-H index of geomagnetic activity, i.e., during the main phase of geomagnetic storms and during development of ionospheric storms. The main contribution in the total number of GPS LoL was found to be done by GPS sites located at low and high latitudes, whereas the area of numerous TEC slips seemed to mostly correspond to the boundary of the auroral oval, i.e., region with intensive ionospheric irregularities. Our global maps of TEC slips show where the regions with intense irregularities of electron density occur during geomagnetic storms and will let us in future predict appearance of GPS errors for geomagnetically disturbed conditions.

  14. Comprehensive Condition Survey and Storm Waves, Circulation, and Sediment Study, Dana Point Harbor, California

    Science.gov (United States)

    2014-12-01

    waters; 3) west to northwest local sea; 4) prefrontal local sea; 5) tropical storm swell; and 6) extratropical cyclone in the southern hemisphere...14-13 58 Prefrontal local sea The coastal zone within the south Orange County area is vulnerable under extratropical winter storm conditions (a...wave characteristics for severe extratropical storms during the 39 yr time period (1970–2008) are comparable to peak storm wave heights that were

  15. "Storms of crustal stress" and AE earthquake precursors

    Directory of Open Access Journals (Sweden)

    G. P. Gregori

    2010-02-01

    Full Text Available Acoustic emission (AE displays violent paroxysms preceding strong earthquakes, observed within some large area (several hundred kilometres wide around the epicentre. We call them "storms of crustal stress" or, briefly "crustal storms". A few case histories are discussed, all dealing with the Italian peninsula, and with the different behaviour shown by the AE records in the Cephalonia island (Greece, which is characterized by a different tectonic setting.

    AE is an effective tool for diagnosing the state of some wide slab of the Earth's crust, and for monitoring its evolution, by means of AE of different frequencies. The same effect ought to be detected being time-delayed, when referring to progressively lower frequencies. This results to be an effective check for validating the physical interpretation.

    Unlike a seismic event, which involves a much limited focal volume and therefore affects a restricted area on the Earth's surface, a "crustal storm" typically involves some large slab of lithosphere and crust. In general, it cannot be easily reckoned to any specific seismic event. An earthquake responds to strictly local rheological features of the crust, which are eventually activated, and become crucial, on the occasion of a "crustal storm". A "crustal storm" lasts typically few years, eventually involving several destructive earthquakes that hit at different times, at different sites, within that given lithospheric slab.

    Concerning the case histories that are here discussed, the lithospheric slab is identified with the Italian peninsula. During 1996–1997 a "crustal storm" was on, maybe elapsing until 2002 (we lack information for the period 1998–2001. Then, a quiet period occurred from 2002 until 26 May 2008, when a new "crustal storm" started, and by the end of 2009 it is still on. During the 1996–1997 "storm" two strong earthquakes occurred (Potenza and

  16. Proxy records of Holocene storm events in coastal barrier systems: Storm-wave induced markers

    Science.gov (United States)

    Goslin, Jérôme; Clemmensen, Lars B.

    2017-10-01

    Extreme storm events in the coastal zone are one of the main forcing agents of short-term coastal system behavior. As such, storms represent a major threat to human activities concentrated along the coasts worldwide. In order to better understand the frequency of extreme events like storms, climate science must rely on longer-time records than the century-scale records of instrumental weather data. Proxy records of storm-wave or storm-wind induced activity in coastal barrier systems deposits have been widely used worldwide in recent years to document past storm events during the last millennia. This review provides a detailed state-of-the-art compilation of the proxies available from coastal barrier systems to reconstruct Holocene storm chronologies (paleotempestology). The present paper aims (I) to describe the erosional and depositional processes caused by storm-wave action in barrier and back-barrier systems (i.e. beach ridges, storm scarps and washover deposits), (ii) to understand how storm records can be extracted from barrier and back-barrier sedimentary bodies using stratigraphical, sedimentological, micro-paleontological and geochemical proxies and (iii) to show how to obtain chronological control on past storm events recorded in the sedimentary successions. The challenges that paleotempestology studies still face in the reconstruction of representative and reliable storm-chronologies using these various proxies are discussed, and future research prospects are outlined.

  17. Climatological properties of summertime extra-tropical storm tracks in the Northern Hemisphere

    OpenAIRE

    Dos Santos Mesquita, Michel; Kvamstø, Nils Gunnar; Sorteberg, Asgeir; Atkinson, David E.

    2008-01-01

    This paper presents climatological properties of Northern Hemisphere summer extratropical storm tracks using data extracted from an existing, relative-vorticity-based storm database. This database was constructed using the NCEPNCAR ‘Reanalysis I’ data set from 1948 to 2002. Results contrasting summer and winter patterns for several storm parameters indicated general similarity at the largest scales, including the prominent track corridors of the middle latitude ocean regions and the mid-conti...

  18. Thyroid Echography-induced Thyroid Storm and Exacerbation of Acute Heart Failure.

    Science.gov (United States)

    Nakabayashi, Keisuke; Nakazawa, Naomi; Suzuki, Toshiaki; Asano, Ryotaro; Saito, Hideki; Nomura, Hidekimi; Isomura, Daichi; Okada, Hisayuki; Sugiura, Ryo; Oka, Toshiaki

    2016-01-01

    Hyperthyroidism and thyroid storm affect cardiac circulation in some conditions. Several factors including trauma can induce thyroid storms. We herein describe the case of a 57-year-old woman who experienced a thyroid storm and exacerbation of acute heart failure on thyroid echography. She initially demonstrated a good clinical course after medical rate control for atrial fibrillation; however, thyroid echography for evaluating hyperthyroidism led to a thyroid storm and she collapsed. A multidisciplinary approach stabilized her thyroid hormone levels and hemodynamics. Thus, the medical staff should be prepared for a deterioration in the patient's condition during thyroid echography in heart failure patients with hyperthyroidism.

  19. Storm-tracks interannual variability and large-scale climate modes

    Science.gov (United States)

    Liberato, Margarida L. R.; Trigo, Isabel F.; Trigo, Ricardo M.

    2013-04-01

    In this study we focus on the interannual variability and observed changes in northern hemisphere mid-latitude storm-tracks and relate them to large scale atmospheric circulation variability modes. Extratropical storminess, cyclones dominant paths, frequency and intensity have long been the object of climatological studies. The analysis of storm characteristics and historical trends presented here is based on the cyclone detecting and tracking algorithm first developed for the Mediterranean region (Trigo et al. 1999) and recently extended to a larger Euro-Atlantic region (Trigo 2006). The objective methodology, which identifies and follows individual lows as minima in SLP fields, fulfilling a set of conditions regarding the central pressure and the pressure gradient, is applied to the northern hemisphere 6-hourly geopotential data at 1000 hPa from the 20th Century Reanalyses (20CRv2) project and from reanalyses datasets provided by the European Centre for Medium-Range Weather Forecasts (ECMWF): ERA-40 and ERA Interim reanalyses. First, we assess the interannual variability and cyclone frequency trends for each of the datasets, for the 20th century and for the period between 1958 and 2002 using the highest spatial resolution available (1.125° x 1.125°) from the ERA-40 data. Results show that winter variability of storm paths, cyclone frequency and travel times is in agreement with the reported variability in a number of large-scale climate patterns (including the North Atlantic Oscillation, the East Atlantic Pattern and the Scandinavian Pattern). In addition, three storm-track databases are built spanning the common available extended winter seasons from October 1979 to March 2002. Although relatively short, this common period allows a comparison of systems represented in reanalyses datasets with distinct horizontal resolutions. This exercise is mostly focused on the key areas of cyclogenesis and cyclolysis and main cyclone characteristics over the northern

  20. Thyroid storm complicated by fulminant hepatic failure: case report and literature review.

    Science.gov (United States)

    Hambleton, Catherine; Buell, Joseph; Saggi, Bob; Balart, Luis; Shores, Nathan J; Kandil, Emad

    2013-11-01

    Thyroid storm is a presentation of severe thyrotoxicosis that has a mortality rate of up to 20% to 30%. Fulminant hepatic failure (FHF) entails encephalopathy with severe coagulopathy in the setting of liver disease. It carries a high mortality rate, with an approximately 60% rate of overall survival for patients who undergo orthotopic liver transplantation (OLT). Fulminant hepatic failure is a rare but serious complication of thyroid storm. There have been only 6 previously reported cases of FHF with thyroid storm. We present a patient from our institution with thyroid storm and FHF. A literature review was performed to analyze the outcomes of the 6 additional cases of concomitant thyroid storm and FHF. Our patient underwent thyroidectomy followed by OLT. Her serum levels of thyroid-stimulating hormone, triiodothyronine, thyroxine, and transaminase normalized, and she was ready for discharge within 10 days of surgery. She has survived without complication. There is a 40% mortality rate for the reported patients treated medically with these conditions. Of the 7 total cases of reported FHF and thyroid storm, 2 patients died. Only 2 of the 7 patients underwent thyroidectomy and OLT--both at our institution. Both patients survived without complications. Thyroid storm and FHF each independently carry high mortality rates, and managing patients with both conditions simultaneously is an extraordinary challenge. These cases should compel clinicians to investigate liver function in hyperthyroid patients and to be wary of its rapid decline in patients who present in thyroid storm with symptoms of liver dysfunction. Patients with rapidly progressing thyroid storm and FHF should be considered for total thyroidectomy and OLT.

  1. Directional analysis of the storm surge from Hurricane Sandy 2012, with applications to Charleston, New Orleans, and the Philippines.

    Science.gov (United States)

    Drews, Carl; Galarneau, Thomas J

    2015-01-01

    Hurricane Sandy in late October 2012 drove before it a storm surge that rose to 4.28 meters above mean lower low water at The Battery in lower Manhattan, and flooded the Hugh L. Carey automobile tunnel between Brooklyn and The Battery. This study examines the surge event in New York Harbor using the Weather Research and Forecasting (WRF) atmospheric model and the Coupled-Ocean-Atmosphere-Wave- Sediment Transport/Regional Ocean Modeling System (COAWST/ROMS). We present a new technique using directional analysis to calculate and display maps of a coastline's potential for storm surge; these maps are constructed from wind fields blowing from eight fixed compass directions. This analysis approximates the surge observed during Hurricane Sandy. The directional analysis is then applied to surge events at Charleston, South Carolina, New Orleans, Louisiana, and Tacloban City, the Philippines. Emergency managers could use these directional maps to prepare their cities for an approaching storm, on planning horizons from days to years.

  2. Spatiotemporal drought forecasting using nonlinear models

    Science.gov (United States)

    Vasiliades, Lampros; Loukas, Athanasios

    2010-05-01

    Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

  3. Curcumin suppression of cytokine release and cytokine storm. A potential therapy for patients with Ebola and other severe viral infections.

    Science.gov (United States)

    Sordillo, Peter P; Helson, Lawrence

    2015-01-01

    The terminal stage of Ebola and other viral diseases is often the onset of a cytokine storm, the massive overproduction of cytokines by the body's immune system. The actions of curcumin in suppressing cytokine release and cytokine storm are discussed. Curcumin blocks cytokine release, most importantly the key pro-inflammatory cytokines, interleukin-1, interleukin-6 and tumor necrosis factor-α. The suppression of cytokine release by curcumin correlates with clinical improvement in experimental models of disease conditions where a cytokine storm plays a significant role in mortality. The use of curcumin should be investigated in patients with Ebola and cytokine storm. Intravenous formulations may allow achievement of therapeutic blood levels of curcumin. Copyright © 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  4. A-Train Observations of Deep Convective Storm Tops

    Science.gov (United States)

    Setvak, Martin; Bedka, Kristopher; Lindsey, Daniel T.; Sokol, Alois; Charvat, Zdenek; Stastka, Jindrich; Wang, Pao K.

    2013-01-01

    The paper highlights simultaneous observations of tops of deep convective clouds from several space-borne instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS) of the Aqua satellite, Cloud Profiling Radar (CPR) of the CloudSat satellite, and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) flown on the CALIPSO satellite. These satellites share very close orbits, thus together with several other satellites they are referred to as the "A-Train" constellation. Though the primary responsibility of these satellites and their instrumentation is much broader than observations of fine-scale processes atop convective storms, in this study we document how data from the A-Train can contribute to a better understanding and interpretation of various storm-top features, such as overshooting tops, cold-U/V and cold ring features with their coupled embedded warm areas, above anvil ice plumes and jumping cirrus. The relationships between MODIS multi-spectral brightness temperature difference (BTD) fields and cloud top signatures observed by the CPR and CALIOP are also examined in detail to highlight the variability in BTD signals across convective storm events.

  5. Morphology of geomagnetic storms, recorded at Hurbanovo, and its relation to solar activity

    International Nuclear Information System (INIS)

    Ochabova, P.; Psenakova, M.

    1977-01-01

    The morphological structure of geomagnetic storms was investigated using the data on 414 storms, recorded in the years 1949 to 1968 at the Geomagnetic Observatory of Hurbanovo (phi=47.9 deg N, lambda=18.2 deg E). These data also formed a suitable basis for investigating the effect of the solar activity on the characteristic features of storms. The storm-time variation of the geomagnetic field was considered after the Sq-variation had been eliminated. The sets of storms, i.e. 263 storms recorded at a time of high sunspot activity and 151 storms recorded at a time of low activity, were divided into 7 groups, depending on the duration of their initial phase. In 92% of the investigated storms the increase in the horizontal component lasted from 0 to 15 hrs. The effect of the solar activity was markedly reflected in the occurrence of very severe storms, as well as in the maximum decrease in the H-component in the main phase. This can also be seen in the rate at which the storms recover. (author)

  6. Visualizing Coastal Erosion, Overwash and Coastal Flooding in New England

    Science.gov (United States)

    Young Morse, R.; Shyka, T.

    2017-12-01

    Powerful East Coast storms and their associated storm tides and large, battering waves can lead to severe coastal change through erosion and re-deposition of beach sediment. The United States Geological Survey (USGS) has modeled such potential for geological response using a storm-impact scale that compares predicted elevations of hurricane-induced water levels and associated wave action to known elevations of coastal topography. The resulting storm surge and wave run-up hindcasts calculate dynamic surf zone collisions with dune structures using discrete regime categories of; "collision" (dune erosion), "overwash" and "inundation". The National Weather Service (NWS) recently began prototyping this empirical technique under the auspices of the North Atlantic Regional Team (NART). Real-time erosion and inundation forecasts were expanded to include both tropical and extra-tropical cyclones along vulnerable beaches (hotspots) on the New England coast. Preliminary results showed successful predictions of impact during hurricane Sandy and several intense Nor'easters. The forecasts were verified using observational datasets, including "ground truth" reports from Emergency Managers and storm-based, dune profile measurements organized through a Maine Sea Grant partnership. In an effort to produce real-time visualizations of this forecast output, the Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS) and the Gulf of Maine Research Institute (GMRI) partnered with NART to create graphical products of wave run-up levels for each New England "hotspot". The resulting prototype system updates the forecasts twice daily and allows users the ability to adjust atmospheric and sea state input into the calculations to account for model errors and forecast uncertainty. This talk will provide an overview of the empirical wave run-up calculations, the system used to produce forecast output and a demonstration of the new web based tool.

  7. A new deterministic Ensemble Kalman Filter with one-step-ahead smoothing for storm surge forecasting

    KAUST Repository

    Raboudi, Naila

    2016-01-01

    KF-OSA exploits the observation twice. The incoming observation is first used to smooth the ensemble at the previous time step. The resulting smoothed ensemble is then integrated forward to compute a "pseudo forecast" ensemble, which is again updated with the same

  8. A multi-scale ensemble-based framework for forecasting compound coastal-riverine flooding: The Hackensack-Passaic watershed and Newark Bay

    Science.gov (United States)

    Saleh, F.; Ramaswamy, V.; Wang, Y.; Georgas, N.; Blumberg, A.; Pullen, J.

    2017-12-01

    Estuarine regions can experience compound impacts from coastal storm surge and riverine flooding. The challenges in forecasting flooding in such areas are multi-faceted due to uncertainties associated with meteorological drivers and interactions between hydrological and coastal processes. The objective of this work is to evaluate how uncertainties from meteorological predictions propagate through an ensemble-based flood prediction framework and translate into uncertainties in simulated inundation extents. A multi-scale framework, consisting of hydrologic, coastal and hydrodynamic models, was used to simulate two extreme flood events at the confluence of the Passaic and Hackensack rivers and Newark Bay. The events were Hurricane Irene (2011), a combination of inland flooding and coastal storm surge, and Hurricane Sandy (2012) where coastal storm surge was the dominant component. The hydrodynamic component of the framework was first forced with measured streamflow and ocean water level data to establish baseline inundation extents with the best available forcing data. The coastal and hydrologic models were then forced with meteorological predictions from 21 ensemble members of the Global Ensemble Forecast System (GEFS) to retrospectively represent potential future conditions up to 96 hours prior to the events. Inundation extents produced by the hydrodynamic model, forced with the 95th percentile of the ensemble-based coastal and hydrologic boundary conditions, were in good agreement with baseline conditions for both events. The USGS reanalysis of Hurricane Sandy inundation extents was encapsulated between the 50th and 95th percentile of the forecasted inundation extents, and that of Hurricane Irene was similar but with caveats associated with data availability and reliability. This work highlights the importance of accounting for meteorological uncertainty to represent a range of possible future inundation extents at high resolution (∼m).

  9. How uncertain are day-ahead wind forecasts?

    Energy Technology Data Exchange (ETDEWEB)

    Grimit, E. [3TIER Environmental Forecast Group, Seattle, WA (United States)

    2006-07-01

    Recent advances in the combination of weather forecast ensembles with Bayesian statistical techniques have helped to address uncertainties in wind forecasting. Weather forecast ensembles are a collection of numerical weather predictions. The combination of several equally-skilled forecasts typically results in a consensus forecast with greater accuracy. The distribution of forecasts also provides an estimate of forecast inaccuracy. However, weather forecast ensembles tend to be under-dispersive, and not all forecast uncertainties can be taken into account. In order to address these issues, a multi-variate linear regression approach was used to correct the forecast bias for each ensemble member separately. Bayesian model averaging was used to provide a predictive probability density function to allow for multi-modal probability distributions. A test location in eastern Canada was used to demonstrate the approach. Results of the test showed that the method improved wind forecasts and generated reliable prediction intervals. Prediction intervals were much shorter than comparable intervals based on a single forecast or on historical observations alone. It was concluded that the approach will provide economic benefits to both wind energy developers and investors. refs., tabs., figs.

  10. Analysis of synoptic situation for dust storms in Iraq

    Energy Technology Data Exchange (ETDEWEB)

    Al-Jumaily, Kais J.; Ibrahim, Morwa K. [Department of Atmospheric Sciences, College of Science, Al-Mustansiriyah University, Baghdad (Iraq)

    2013-07-01

    Dust storms are considered major natural disasters that cause many damages to society and environment in Iraq and surrounded deserted regions. The aim of this research is to analyze and study the synoptic patterns leading to the formation of dust storms in Iraq. Analysis are based on satellite images, aerosols index and synoptic weather maps. Two severe dust storms occurred over Iraq on February 22, 2010, and on December 10, 2011 were analyzed. The results showed that dust storms form when a low-pressure system forms over Iran causing Shamal winds blow; they carry cool air from that region towards warmer regions like eastern Syria and Iraq. In some cases, this low-pressure system is followed by a high-pressure system brining more cold air to the region and pushing dust toward south. Dust storms are initiated from source regions near Iraq-Syria borders by the existence of negative vertical velocity, which causes dust particles to be lifted upwards, and the strong westerly wind drives dust to travel eastward.

  11. Solar radio continuum storms and a breathing magnetic field model. Final report

    International Nuclear Information System (INIS)

    1975-01-01

    Radio noise continuum emissions observed in metric and decametric wave frequencies are, in general, associated with actively varying sunspot groups accompanied by the S-component of microwave radio emissions. These continuum emission sources, often called type I storm sources, are often associated with type III burst storm activity from metric to hectometric wave frequencies. This storm activity is, therefore, closely connected with the development of these continuum emission sources. It is shown that the S-component emission in microwave frequencies generally precedes, by several days, the emission of these noise continuum storms of lower frequencies. In order for these storms to develop, the growth of sunspot groups into complex types is very important in addition to the increase of the average magnetic field intensity and area of these groups. After giving a review on the theory of these noise continuum storm emissions, a model is briefly considered to explain the relation of the emissions to the storms

  12. Storm tide monitoring during the blizzard of January 26-28, 2015, in eastern Massachusetts

    Science.gov (United States)

    Massey, Andrew J.; Verdi, Richard J.

    2015-01-01

    The U.S. Geological Survey (USGS) deployed a temporary monitoring network of six storm surge sensors and four barometric pressure sensors along the Atlantic coast in eastern Massachusetts, from Plymouth to Newburyport, before the blizzard of January 26–28, 2015 (Blizzard of January 2015), to record the timing and magnitude of storm tide at select locations where forecasters had predicted the potential for coastal flooding. Additionally, water-level data were recorded and transmitted in near real-time from four permanent USGS tidal stations—three on Cape Cod and one near the mouth of the Merrimack River in Newburyport. The storm surge sensors were deployed at previously established fixed sites outfitted with presurveyed mounting brackets. The mounting brackets were installed in 2014 as part of the USGS Surge, Wave, and Tide Hydrodynamic (SWaTH) Network (https://water.usgs.gov/floods/STN/), which was funded through congressional supplemental appropriations for the U.S. Department of the Interior after the devastating landfall of Hurricane Sandy on October 29, 2012 (Simmons and others, 2014). The USGS received this funding to enable better understanding of coastal flooding hazards in the region, to improve preparedness for future coastal storms, and to increase the resilience of coastal cities, infrastructure, and natural systems in the region (Buxton and others, 2013). The USGS established 163 monitoring locations along the New England coast for the SWaTH Network, including 70 sites in Massachusetts.

  13. Space weather effects on radio propagation: study of the CEDAR, GEM and ISTP storm events

    Directory of Open Access Journals (Sweden)

    D. V. Blagoveshchensky

    2008-06-01

    Full Text Available The impact of 14 geomagnetic storms from a list of CEDAR, GEM and ISTP storms, that occurred during 1997–1999, on radio propagation conditions has been investigated. The propagation conditions were estimated through variations of the MOF and LOF (the maximum and lowest operation frequencies on three high-latitude HF radio paths in north-west Russia. Geophysical data of Dst, Bz, AE as well as some riometer data from Sodankyla observatory, Finland, were used for the analysis. It was shown that the storm impact on the ionosphere and radio propagation for each storm has an individual character. Nevertheless, there are common patterns in variation of the propagation parameters for all storms. Thus, the frequency range Δ=MOF−LOF increases several hours before a storm, then it narrows sharply during the storm, and expands again several hours after the end of the storm. This regular behaviour should be useful for the HF radio propagation predictions and frequency management at high latitudes. On the trans-auroral radio path, the time interval when the signal is lost through a storm (tdes depends on the local time. For the day-time storms an average value tdes is 6 h, but for night storms tdes is only 2 h. The ionization increase in the F2 layer before storm onset is 3.5 h during the day-time and 2.4 h at night. Mechanisms to explain the observed variations are discussed including some novel possibilities involving energy input through the cusp.

  14. Analysis of the positive ionospheric response to a moderate geomagnetic storm using a global numerical model

    Directory of Open Access Journals (Sweden)

    A. A. Namgaladze

    2000-04-01

    disturbances both at middle and low latitudes. Minor contributions arise from the general density enhancement of all constituents during geomagnetic storms, which favours ion production processes above ion losses at fixed height under day-light conditions.Key words: Atmospheric composition and structure (thermosphere · composition and chemistry · Ionosphere (ionosphere · atmosphere interactions; modelling and forecasting

  15. Analysis of the positive ionospheric response to a moderate geomagnetic storm using a global numerical model

    Directory of Open Access Journals (Sweden)

    A. A. Namgaladze

    to create the positive ionospheric disturbances both at middle and low latitudes. Minor contributions arise from the general density enhancement of all constituents during geomagnetic storms, which favours ion production processes above ion losses at fixed height under day-light conditions.

    Key words: Atmospheric composition and structure (thermosphere · composition and chemistry · Ionosphere (ionosphere · atmosphere interactions; modelling and forecasting

  16. Impacts on coralligenous outcrop biodiversity of a dramatic coastal storm.

    Directory of Open Access Journals (Sweden)

    Núria Teixidó

    Full Text Available Extreme events are rare, stochastic perturbations that can cause abrupt and dramatic ecological change within a short period of time relative to the lifespan of organisms. Studies over time provide exceptional opportunities to detect the effects of extreme climatic events and to measure their impacts by quantifying rates of change at population and community levels. In this study, we show how an extreme storm event affected the dynamics of benthic coralligenous outcrops in the NW Mediterranean Sea using data acquired before (2006-2008 and after the impact (2009-2010 at four different sites. Storms of comparable severity have been documented to occur occasionally within periods of 50 years in the Mediterranean Sea. We assessed the effects derived from the storm comparing changes in benthic community composition at sites exposed to and sheltered from this extreme event. The sites analyzed showed different damage from severe to negligible. The most exposed and impacted site experienced a major shift immediately after the storm, represented by changes in the species richness and beta diversity of benthic species. This site also showed higher compositional variability immediately after the storm and over the following year. The loss of cover of benthic species resulted between 22% and 58%. The damage across these species (e.g. calcareous algae, sponges, anthozoans, bryozoans, tunicates was uneven, and those with fragile forms were the most impacted, showing cover losses up to 50 to 100%. Interestingly, small patches survived after the storm and began to grow slightly during the following year. In contrast, sheltered sites showed no significant changes in all the studied parameters, indicating no variations due to the storm. This study provides new insights into the responses to large and rare extreme events of Mediterranean communities with low dynamics and long-lived species, which are among the most threatened by the effects of global change.

  17. Healthcare4VideoStorm: Making Smart Decisions Based on Storm Metrics.

    Science.gov (United States)

    Zhang, Weishan; Duan, Pengcheng; Chen, Xiufeng; Lu, Qinghua

    2016-04-23

    Storm-based stream processing is widely used for real-time large-scale distributed processing. Knowing the run-time status and ensuring performance is critical to providing expected dependability for some applications, e.g., continuous video processing for security surveillance. The existing scheduling strategies' granularity is too coarse to have good performance, and mainly considers network resources without computing resources while scheduling. In this paper, we propose Healthcare4Storm, a framework that finds Storm insights based on Storm metrics to gain knowledge from the health status of an application, finally ending up with smart scheduling decisions. It takes into account both network and computing resources and conducts scheduling at a fine-grained level using tuples instead of topologies. The comprehensive evaluation shows that the proposed framework has good performance and can improve the dependability of the Storm-based applications.

  18. Development of VLF noise storm and its relation to dynamics of magnetosphere during geomagnetic storms

    International Nuclear Information System (INIS)

    Fedyakina, N.I.; Khorosheva, O.V.

    1989-01-01

    Dependence between the development of geomagnetic storm and VLF noise storm is studied. Two conditions should be met for the development of noise storm in VLF-hiss (f ≅ 0.5-10 kHz): a) threshold intensity of electron fluxes with E e > 40 keV in plasma layers; b) the presence of substorms resulting to widening of electron belt and its collision with cold plasma of plasmasphere. The noise storm at the fixed longitude begins about midnight independently of the phase of magnetic storm; Noise storm duration is connected with geomagnetic storm intensity by direct linear relationship

  19. Dynamic interactions between coastal storms and salt marshes: A review

    Science.gov (United States)

    Leonardi, Nicoletta; Carnacina, Iacopo; Donatelli, Carmine; Ganju, Neil K.; Plater, Andrew James; Schuerch, Mark; Temmerman, Stijn

    2018-01-01

    detrimental effect for marsh boundaries even during calm weather. On the other hand, when a violent storm causes substantial erosion but sediments are redistributed across nearby areas, the long term impact might not be as severe as if sediments were permanently lost from the system, and the salt marsh could easily recover to the initial state.

  20. Dynamic interactions between coastal storms and salt marshes: A review

    Science.gov (United States)

    Leonardi, Nicoletta; Carnacina, Iacopo; Donatelli, Carmine; Ganju, Neil Kamal; Plater, Andrew James; Schuerch, Mark; Temmerman, Stijn

    2018-01-01

    effect for marsh boundaries even during calm weather. On the other hand, when a violent storm causes substantial erosion but sediments are redistributed across nearby areas, the long term impact might not be as severe as if sediments were permanently lost from the system, and the salt marsh could easily recover to the initial state.

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

    Science.gov (United States)

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

    2018-01-01

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

  2. Geomagnetic Storm Sudden Commencements

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Storm Sudden Commencements (ssc) 1868 to present: STORM1 and STORM2 Lists: (Some text here is taken from the International Association of Geomagnetism and Aeronomy...

  3. Verification of short lead time forecast models: applied to Kp and Dst forecasting

    Science.gov (United States)

    Wintoft, Peter; Wik, Magnus

    2016-04-01

    In the ongoing EU/H2020 project PROGRESS models that predicts Kp, Dst, and AE from L1 solar wind data will be used as inputs to radiation belt models. The possible lead times from L1 measurements are shorter (10s of minutes to hours) than the typical duration of the physical phenomena that should be forecast. Under these circumstances several metrics fail to single out trivial cases, such as persistence. In this work we explore metrics and approaches for short lead time forecasts. We apply these to current Kp and Dst forecast models. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637302.

  4. Evidence for Gravity Wave Seeding of Convective Ionosphere Storms Initiated by Deep Troposphere Convection

    Science.gov (United States)

    Kelley, M. C.; Pfaff, R. F., Jr.; Dao, E. V.; Holzworth, R. H., II

    2014-12-01

    With the increase in solar activity, the Communications/Outage Forecast System satellite (C/NOFS) now goes below the F peak. As such, we now can study the development of Convective Ionospheric Storms (CIS) and, most importantly, large-scale seeding of the low growth-rate Rayleigh-Taylor (R-T) instability. Two mechanisms have been suggested for such seeding: the Collisional Kelvin-Helmholtz Instability (CKHI) and internal atmospheric gravity waves. A number of observations have shown that the spectrum of fully developed topside structures peaks at 600 km and extends to over 1000 km. These structures are exceedingly difficult to explain by CKHI. Here we show that sinusoidal plasma oscillations on the bottomside during daytime develop classical R-T structures on the nightside with the background 600 km structure still apparent. In two case studies, thunderstorm activity was observed east of the sinusoidal features in the two hours preceding the C/NOFS passes. Thus, we argue that convective tropospheric storms are a likely source of these sinusoidal features.

  5. Shoreline resilience to individual storms and storm clusters on a meso-macrotidal barred beach

    NARCIS (Netherlands)

    Angnuureng, Donatus Bapentire; Almar, Rafael; Senechal, Nadia; Castelle, Bruno; Addo, Kwasi Appeaning; Marieu, Vincent; Ranasinghe, Roshanka

    2017-01-01

    This study investigates the impact of individual storms and storm clusters on shoreline recovery for the meso-to macrotidal, barred Biscarrosse beach in SW France, using 6 years of daily video observations. While the study area experienced 60 storms during the 6-year study period, only 36 storms

  6. The effects of storms and storm-generated currents on sand beaches in Southern Maine, USA

    Science.gov (United States)

    Hill, H.W.; Kelley, J.T.; Belknap, D.F.; Dickson, S.M.

    2004-01-01

    Storms are one of the most important controls on the cycle of erosion and accretion on beaches. Current meters placed in shoreface locations of Saco Bay and Wells Embayment, ME, recorded bottom currents during the winter months of 2000 and 2001, while teams of volunteers profiled the topography of nearby beaches. Coupling offshore meteorological and beach profile data made it possible to determine the response of nine beaches in southern Maine to various oceanographic and meteorological conditions. The beaches selected for profiling ranged from pristine to completely developed and permitted further examination of the role of seawalls on the response of beaches to storms. Current meters documented three unique types of storms: frontal passages, southwest storms, and northeast storms. In general, the current meter results indicate that frontal passages and southwest storms were responsible for bringing sediment towards the shore, while northeast storms resulted in a net movement of sediment away from the beach. During the 1999-2000 winter, there were a greater percentage of frontal passages and southwest storms, while during the 2000-2001 winter, there were more northeast storms. The sediment that was transported landward during the 1999-2000 winter was reworked into the berm along moderately and highly developed beaches during the next summer. A northeast storm on March 5-6, 2001, resulted in currents in excess of 1 m s-1 and wave heights that reached six meters. The storm persisted over 10 high tides and caused coastal flooding and property damage. Topographic profiles made before and after the storm demonstrate that developed beaches experienced a loss of sediment volume during the storm, while sediment was redistributed along the profile on moderately developed and undeveloped beaches. Two months after the storm, the profiles along the developed beaches had not reached their pre-storm elevation. In comparison, the moderately developed and undeveloped beaches

  7. Advanced inflow forecasting for a hydropower plant in an Alpine hydropower regulated catchment - coupling of operational and hydrological forecasts

    Science.gov (United States)

    Tilg, Anna-Maria; Schöber, Johannes; Huttenlau, Matthias; Messner, Jakob; Achleitner, Stefan

    2017-04-01

    Hydropower is a renewable energy source which can help to stabilize fluctuations in the volatile energy market. Especially pumped-storage infrastructures in the European Alps play an important role within the European energy grid system. Today, the runoff of rivers in the Alps is often influenced by cascades of hydropower infrastructures where the operational procedures are triggered by energy market demands, water deliveries and flood control aspects rather than by hydro-meteorological variables. An example for such a highly hydropower regulated river is the catchment of the river Inn in the Eastern European Alps, originating in the Engadin (Switzerland). A new hydropower plant is going to be built as transboundary project at the boarder of Switzerland and Austria using the water of the Inn River. For the operation, a runoff forecast to the plant is required. The challenge in this case is that a high proportion of runoff is turbine water from an upstream situated hydropower cascade. The newly developed physically based hydrological forecasting system is mainly capable to cover natural hydrological runoff processes caused by storms and snow melt but can model only a small degree of human impact. These discontinuous parts of the runoff downstream of the pumped storage are described by means of an additional statistical model which has been developed. The main goal of the statistical model is to forecast the turbine water up to five days in advance. The lead time of the data driven model exceeds the lead time of the used energy production forecast. Additionally, the amount of turbine water is linked to the need of electricity production and the electricity price. It has been shown that especially the parameters day-ahead prognosis of the energy production and turbine inflow of the previous week are good predictors and are therefore used as input parameters for the model. As the data is restricted due to technical conditions, so-called Tobit models have been used to

  8. Electrical storm after CRT implantation treated by AV delay optimization.

    Science.gov (United States)

    Combes, Nicolas; Marijon, Eloi; Boveda, Serge; Albenque, Jean-Paul

    2010-02-01

    We present a case of symptomatic ischemic heart failure with an indication for cardiac resynchronization and implantable cardiac defibrillator therapy in primary prevention. After implantation, the patient developed a severe electrical storm with multiple shocks. Hemodynamic improvement based only on AV delay, guided by echocardiography and ECG, brought about a dramatic improvement in the situation. We discuss the pathophysiology of electrical storm occurring immediately after LV pacing.

  9. Lightning Initiation Forecasting: An Operational Dual-Polarimetric Radar Technique

    Science.gov (United States)

    Woodard, Crystal J.; Carey, L. D.; Petersen, W. A.; Roeder, W. P.

    2011-01-01

    The objective of this NASA MSFC and NOAA CSTAR funded study is to develop and test operational forecast algorithms for the prediction of lightning initiation utilizing the C-band dual-polarimetric radar, UAHuntsville's Advanced Radar for Meteorological and Operational Research (ARMOR). Although there is a rich research history of radar signatures associated with lightning initiation, few studies have utilized dual-polarimetric radar signatures (e.g., Z(sub dr) columns) and capabilities (e.g., fuzzy-logic particle identification [PID] of precipitation ice) in an operational algorithm for first flash forecasting. The specific goal of this study is to develop and test polarimetric techniques that enhance the performance of current operational radar reflectivity based first flash algorithms. Improving lightning watch and warning performance will positively impact personnel safety in both work and leisure environments. Advanced warnings can provide space shuttle launch managers time to respond appropriately to secure equipment and personnel, while they can also provide appropriate warnings for spectators and players of leisure sporting events to seek safe shelter. Through the analysis of eight case dates, consisting of 35 pulse-type thunderstorms and 20 non-thunderstorm case studies, lightning initiation forecast techniques were developed and tested. The hypothesis is that the additional dual-polarimetric information could potentially reduce false alarms while maintaining high probability of detection and increasing lead-time for the prediction of the first lightning flash relative to reflectivity-only based techniques. To test the hypothesis, various physically-based techniques using polarimetric variables and/or PID categories, which are strongly correlated to initial storm electrification (e.g., large precipitation ice production via drop freezing), were benchmarked against the operational reflectivity-only based approaches to find the best compromise between

  10. Creating a comprehensive quality-controlled dataset of severe weather occurrence in Europe

    Science.gov (United States)

    Groenemeijer, P.; Kühne, T.; Liang, Z.; Holzer, A.; Feuerstein, B.; Dotzek, N.

    2010-09-01

    database's web-interface has been translated into 14 European languages. At the time of writing, a nowcast-mode to the web interface, which renders the ESWD a convenient tool for meteorologists in forecast centres, is being developed. In the near future, within the EWENT project, an extension of the data set with several other isolated but extreme events including avalanches, landslides, heavy snowfall and extremely powerful lightning flashes, is foreseen. The resulting ESWD dataset, that grows at a rate of 4000-5000 events per year, is used for wide range of purposes including the validation of remote-sensing techniques, forecast verification studies, projections of the future severe storm climate, and risk assessments. Its users include scientists working for EUMETSAT, NASA, NSSL, DLR, and several reinsurance companies.

  11. Improved stratospheric atmosphere forecasts in the general circulation model through a methane oxidation parametrization

    Science.gov (United States)

    Wang, S.; Jun, Z.

    2017-12-01

    Climatic characteristics of tropical stratospheric methane have been well researched using various satellite data, and numerical simulations have furtherly conducted using chemical climatic models, while the impact of stratospheric methane oxidation on distribution of water vapor is not paid enough attention in general circulation models. Simulated values of water vapour in the tropical upper stratosphere, and throughout much of the extratropical stratosphere, were too low. Something must be done to remedy this deficiency in order to producing realistic stratospheric water vapor using a general circulation model including the whole stratosphere. Introduction of a simple parametrization of the upper-stratospheric moisture source due to methane oxidation and a sink due to photolysis in the mesosphere was conducted. Numerical simulations and analysis of the influence of stratospheric methane on the prediction of tropical stratospheric moisture and temperature fields were carried out. This study presents the advantages of methane oxidation parametrization in producing a realistic distribution of water vapour in the tropical stratosphere and analyzes the impact of methane chemical process on the general circulation model using two storm cases including a heavy rain in South China and a typhoon caused tropical storm.It is obvious that general circulation model with methane oxidation parametrization succeeds in simulating the water vapor and temperature in stratosphere. The simulating rain center value of contrast experiment is increased up to 10% than that of the control experiment. Introduction of methane oxidation parametrization has modified the distribution of water vapour and then producing a broadly realistic distribution of temperature. Objective weather forecast verifications have been performed using simulating results of one month, which demonstrate somewhat positive effects on the model skill. There is a certain extent impact of methane oxidation

  12. Space weather effects on radio propagation: study of the CEDAR, GEM and ISTP storm events

    Directory of Open Access Journals (Sweden)

    D. V. Blagoveshchensky

    2008-06-01

    Full Text Available The impact of 14 geomagnetic storms from a list of CEDAR, GEM and ISTP storms, that occurred during 1997–1999, on radio propagation conditions has been investigated. The propagation conditions were estimated through variations of the MOF and LOF (the maximum and lowest operation frequencies on three high-latitude HF radio paths in north-west Russia. Geophysical data of Dst, Bz, AE as well as some riometer data from Sodankyla observatory, Finland, were used for the analysis. It was shown that the storm impact on the ionosphere and radio propagation for each storm has an individual character. Nevertheless, there are common patterns in variation of the propagation parameters for all storms. Thus, the frequency range Δ=MOF−LOF increases several hours before a storm, then it narrows sharply during the storm, and expands again several hours after the end of the storm. This regular behaviour should be useful for the HF radio propagation predictions and frequency management at high latitudes. On the trans-auroral radio path, the time interval when the signal is lost through a storm (tdes depends on the local time. For the day-time storms an average value tdes is 6 h, but for night storms tdes is only 2 h. The ionization increase in the F2 layer before storm onset is 3.5 h during the day-time and 2.4 h at night. Mechanisms to explain the observed variations are discussed including some novel possibilities involving energy input through the cusp.

  13. Estimating Reservoir Inflow Using RADAR Forecasted Precipitation and Adaptive Neuro Fuzzy Inference System

    Science.gov (United States)

    Yi, J.; Choi, C.

    2014-12-01

    Rainfall observation and forecasting using remote sensing such as RADAR(Radio Detection and Ranging) and satellite images are widely used to delineate the increased damage by rapid weather changeslike regional storm and flash flood. The flood runoff was calculated by using adaptive neuro-fuzzy inference system, the data driven models and MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as the input variables.The result of flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated by comparing it with the actual data.The Adaptive Neuro Fuzzy method was applied to the Chungju Reservoir basin in Korea. The six rainfall events during the flood seasons in 2010 and 2011 were used for the input data.The reservoir inflow estimation results were comparedaccording to the rainfall data used for training, checking and testing data in the model setup process. The results of the 15 models with the combination of the input variables were compared and analyzed. Using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation in this study.The model using the MAPLE forecasted precipitation data showed better result for inflow estimation in the Chungju Reservoir.

  14. Thyroid Storm Triggered by Strangulation in a Patient with Undiagnosed Graves’ Disease

    Directory of Open Access Journals (Sweden)

    Jorge I. Conte

    2018-01-01

    Full Text Available Thyroid storm is the life-threatening end-organ manifestation of severe thyrotoxicosis. If left untreated, thyroid storm may cause acute heart failure, multiorgan dysfunction, and death. A high degree of suspicion is necessary to make the diagnosis and start antithyroid medications to decrease mortality. Thyroid storm is generally seen in patients with Graves’ disease but should also be suspected in patients with fever, tachycardia, altered mental status, and risk factors including local trauma to the neck, such as strangulation. Based on our review, we report the first case of thyroid storm after strangulation as the presentation of previously undiagnosed Graves’ disease.

  15. [Electrical storm].

    Science.gov (United States)

    Barnay, C; Taieb, J; Morice, R

    2007-11-01

    Electrical storm is defined as repeated occurrence of severe ventricular arrhythmias requiring multiple cardioversions, two or more or three or more following different studies. The clinical aspect can sometimes be made of multiple, self aggravating, life threatening accesses. There are three main clinical circumstances of occurrence: in patients equipped with intracardiac defibrillators, during the acute phase of myocardial infarction and in Brugada syndrome. 10 to 15% of patients with cardiac defibrillators are subject to electrical storms in a period of two years. The causative arrhythmia is most often ventricular tachycardia than ventricular fibrillation, especially in secondary prevention and if the initial arrhythmias justifying the device was a ventricular tachycardia. Precipitaing factors are present in one third of cases, mainly acute heart failure, ionic disorders and arrhythmogenic drugs. Predictive factors are age, left ventricular ejection fractionelectrical shock in 50% of cases, antitachycardi stimulation in 30% and in 20% by association of the two. Treatment, after elimination of inappropriate shocks, is mainly based on beta-blockers and amiodarone, class I antiarrhythmics, lidocaïne or bretylium in some cases, and sedation pushed to general anesthesia in some cases. Radio-frequency ablation and even heart transplantation have been proposed in extreme cases. Quinidine has been proved efficient in cases of Brugada syndrome.

  16. In the Eye of the Storm: A Participatory Course on Coastal Storms

    Science.gov (United States)

    Curtis, Scott

    2013-01-01

    Storm disasters are amplified in the coastal environment due to population pressures and the power of the sea. The upper-division/graduate university course "Coastal Storms" was designed to equip future practitioners with the skills necessary to understand, respond to, and mitigate for these natural disasters. To accomplish this, "Coastal Storms"…

  17. Measuring and building resilience after big storms: Lessons learned from Super-Storm Sandy for the Harvey, Irma, Jose, and Maria coasts

    Science.gov (United States)

    Murdoch, P. S.; Penn, K. M.; Taylor, S. M.; Subramanian, B.; Bennett, R.

    2017-12-01

    As we recover from recent large storms, we need information to support increased environmental and socio-economic resilience of the Nation's coasts. Defining baseline conditions, tracking effects of mitigation actions, and measuring the uncertainty of resilience to future disturbance are essential so that the best management practices can be determined. The US Dept. of the Interior invested over $787 million dollars in 2013 to understand and mitigate coastal storm vulnerabilities and enhance resilience of the Northeast coast following Super-Storm Sandy. Several lessons-learned from that investment have direct application to mitigation and restoration needs following Hurricanes Harvey, Irma, Jose and Maria. New models of inundation, overwash, and erosion, developed during the Sandy projects have already been applied to coastlines before and after these recent storms. Results from wetland, beach, back-bay, estuary, and built-environment projects improved models of inundation and erosion from surge and waves. Tests of nature-based infrastructure for mitigating coastal disturbance yielded new concepts for best-practices. Ecological and socio-economic measurements established for detecting disturbance and tracking recovery provide baseline data critical to early detection of vulnerabilities. The Sandy lessons and preliminary applications on the recent storms could help define best-resilience practices before more costly mitigation or restoration efforts are required.

  18. Empirical forecast of the quiet time Ionosphere over Europe: a comparative model investigation

    Science.gov (United States)

    Badeke, R.; Borries, C.; Hoque, M. M.; Minkwitz, D.

    2016-12-01

    The purpose of this work is to find the best empirical model for a reliable 24 hour forecast of the ionospheric Total Electron Content (TEC) over Europe under geomagnetically quiet conditions. It will be used as an improved reference for the description of storm-induced perturbations in the ionosphere. The observational TEC-data were obtained from the International GNSS Service (IGS). Four different forecast model approaches were validated with observational IGS TEC-data: a 27 day median model (27d), a Fourier Analysis (FA) approach, the Neustrelitz TEC global model (NTCM-GL) and NeQuick 2. Two years were investigated depending on the solar activity: 2015 (high activity) and 2008 (low avtivity) The time periods of magnetic storms, which were identified with the Dst index, were excluded from the validation. For both years the two models 27d and FA show better results than NTCM-GL and NeQuick 2. For example for the year 2015 and 15° E / 50° N the difference between the IGS data and the predicted 27d model shows a mean value of 0.413 TEC units (TECU), a standard deviation of 3.307 TECU and a correlation coefficient of 0.921, while NTCM-GL and NeQuick 2 have mean differences of around 2-3 TECU, standard deviations of 4.5-5 TECU and correlation coefficients below 0.85. Since 27d and FA predictions strongly depend on observational data, the results confirm that data driven forecasts perform better than the climatological models NTCM-GL and NeQuick 2. However, the benefits of NTCM-GL and NeQuick 2 are actually the lower data dependency, i.e. they do not lack on precision when observational IGS TEC data are unavailable. Hence a combination of the different models is recommended reacting accordingly to the different data availabilities.

  19. Impacts of storm chronology on the morphological changes of the Formby beach and dune system, UK

    Science.gov (United States)

    Dissanayake, P.; Brown, J.; Karunarathna, H.

    2015-07-01

    Impacts of storm chronology within a storm cluster on beach/dune erosion are investigated by applying the state-of-the-art numerical model XBeach to the Sefton coast, northwest England. Six temporal storm clusters of different storm chronologies were formulated using three storms observed during the 2013/2014 winter. The storm power values of these three events nearly halve from the first to second event and from the second to third event. Cross-shore profile evolution was simulated in response to the tide, surge and wave forcing during these storms. The model was first calibrated against the available post-storm survey profiles. Cumulative impacts of beach/dune erosion during each storm cluster were simulated by using the post-storm profile of an event as the pre-storm profile for each subsequent event. For the largest event the water levels caused noticeable retreat of the dune toe due to the high water elevation. For the other events the greatest evolution occurs over the bar formations (erosion) and within the corresponding troughs (deposition) of the upper-beach profile. The sequence of events impacting the size of this ridge-runnel feature is important as it consequently changes the resilience of the system to the most extreme event that causes dune retreat. The highest erosion during each single storm event was always observed when that storm initialised the storm cluster. The most severe storm always resulted in the most erosion during each cluster, no matter when it occurred within the chronology, although the erosion volume due to this storm was reduced when it was not the primary event. The greatest cumulative cluster erosion occurred with increasing storm severity; however, the variability in cumulative cluster impact over a beach/dune cross section due to storm chronology is minimal. Initial storm impact can act to enhance or reduce the system resilience to subsequent impact, but overall the cumulative impact is controlled by the magnitude and number

  20. Validation of Storm Water Management Model Storm Control Measures Modules

    Science.gov (United States)

    Simon, M. A.; Platz, M. C.

    2017-12-01

    EPA's Storm Water Management Model (SWMM) is a computational code heavily relied upon by industry for the simulation of wastewater and stormwater infrastructure performance. Many municipalities are relying on SWMM results to design multi-billion-dollar, multi-decade infrastructure upgrades. Since the 1970's, EPA and others have developed five major releases, the most recent ones containing storm control measures modules for green infrastructure. The main objective of this study was to quantify the accuracy with which SWMM v5.1.10 simulates the hydrologic activity of previously monitored low impact developments. Model performance was evaluated with a mathematical comparison of outflow hydrographs and total outflow volumes, using empirical data and a multi-event, multi-objective calibration method. The calibration methodology utilized PEST++ Version 3, a parameter estimation tool, which aided in the selection of unmeasured hydrologic parameters. From the validation study and sensitivity analysis, several model improvements were identified to advance SWMM LID Module performance for permeable pavements, infiltration units and green roofs, and these were performed and reported herein. Overall, it was determined that SWMM can successfully simulate low impact development controls given accurate model confirmation, parameter measurement, and model calibration.

  1. Nippon Storm Study design

    Directory of Open Access Journals (Sweden)

    Takashi Kurita

    2012-10-01

    Full Text Available An understanding of the clinical aspects of electrical storm (E-storms in patients with implantable cardiac shock devices (ICSDs: ICDs or cardiac resynchronization therapy with defibrillator [CRT-D] may provide important information for clinical management of patients with ICSDs. The Nippon Storm Study was organized by the Japanese Heart Rhythm Society (JHRS and Japanese Society of Electrocardiology and was designed to prospectively collect a variety of data from patients with ICSDs, with a focus on the incidence of E-storms and clinical conditions for the occurrence of an E-storm. Forty main ICSD centers in Japan are participating in the present study. From 2002, the JHRS began to collect ICSD patient data using website registration (termed Japanese cardiac defibrillator therapy registration, or JCDTR. This investigation aims to collect data on and investigate the general parameters of patients with ICSDs, such as clinical backgrounds of the patients, purposes of implantation, complications during the implantation procedure, and incidence of appropriate and inappropriate therapies from the ICSD. The Nippon Storm Study was planned as a sub-study of the JCDTR with focus on E-storms. We aim to achieve registration of more than 1000 ICSD patients and complete follow-up data collection, with the assumption of a 5–10% incidence of E-storms during the 2-year follow-up.

  2. [Thyrotoxic storm and myxedema coma].

    Science.gov (United States)

    Takasu, N

    1999-08-01

    Thyrotoxic or hyperthyroid storm is a grave, life-threatening, but relatively infrequent medical emergency. Immediate causes of death in this emergency are severe hyperpyrexia and pulmonary edema associated with arrhythmias, shock, and coma. This emergency is found in Graves' patients most frequently. Myxedema coma is an emergency clinical state caused by severe deficiency of thyroid hormones. This crisis represents the extreme expression of hypothyroidism. While it is quite useful to elicit a history of previous hypothyroidism, thyroid surgery, or radioactive iodine treatment, it is not obtainable.

  3. Response of Amazon Fires to the 2015/2016 El Niño and Evaluation of a Seasonal Fire Season Severity Forecast

    Science.gov (United States)

    Randerson, J. T.

    2016-12-01

    Recent work has established that year-to-year variability in drought and fire within the Amazon responds to a dual forcing from ocean-atmosphere interactions in the tropical Pacific and North Atlantic. Teleconnections between the Pacific and the Amazon are strongest between October and March, when El Niño contributes to below-average precipitation during the wet season. A reduced build-up of soil moisture during the wet season, in turn, may limit water availability and transpiration in tropical forests during the following dry season, lowering surface humidity, drying fuels, and allowing fires to spread more easily through the understory. The delayed influence of soil moisture through this land - atmosphere coupling provides a means to predict fire season severity 3-6 months before the onset of the dry season. With the aim of creating new opportunities for forest conservation, we have developed an experimental seasonal fire forecasting system for the Amazon. The 2016 fire season severity forecast, released in June by UCI and NASA, predicts unusually high risk across eastern Peru, northern Bolivia, and Brazil. Several surface and satellite data streams confirm that El Niño teleconnections had a significant impact on wet season hydrology within the Amazon. Rainfall observations from the Global Precipitation Climatology Centre provided evidence that cumulative precipitation deficits during August-April were 1 to 2 standard deviations below the long-term mean for most of the basin. These observations were corroborated by strong negative terrestrial water storage anomalies measured by the Gravity Recovery and Climate Experiment, and by fluorescence and vegetation index observations from other sensors that indicated elevated canopy stress. By August 3rd, satellite observations showed above average fire activity in most, but not all, forecast regions. Using additional satellite observations that become available later this year, we plan to describe the full spatial and

  4. Navigating the storm: report and recommendations from the Atlantic Storm exercise.

    Science.gov (United States)

    Smith, Bradley T; Inglesby, Thomas V; Brimmer, Esther; Borio, Luciana; Franco, Crystal; Gronvall, Gigi Kwik; Kramer, Bradley; Maldin, Beth; Nuzzo, Jennifer B; Schuler, Ari; Stern, Scott; Henderson, Donald A; Larsen, Randall J; Hamilton, Daniel S; O'Toole, Tara

    2005-01-01

    Atlantic Storm was a tabletop exercise simulating a series of bioterrorism attacks on the transatlantic community. The exercise occurred on January 14, 2005, in Washington, DC, and was organized and convened by the Center for Biosecurity of UPMC, the Center for Transatlantic Relations of Johns Hopkins University, and the Transatlantic Biosecurity Network. Atlantic Storm portrayed a summit meeting of presidents, prime ministers, and other international leaders from both sides of the Atlantic Ocean in which they responded to a campaign of bioterrorist attacks in several countries. The summit principals, who were all current or former senior government leaders, were challenged to address issues such as attaining situational awareness in the wake of a bioattack, coping with scarcity of critical medical resources such as vaccine, deciding how to manage the movement of people across borders, and communicating with their publics. Atlantic Storm illustrated that much might be done in advance to minimize the illness and death, as well as the social, economic, and political disruption, that could be caused by an international epidemic, be it natural or the result of a bioterrorist attack. These lessons are especially timely given the growing concerns over the possibility of an avian influenza pandemic that would require an international response. However, international leaders cannot create the necessary response systems in the midst of a crisis. Medical, public health, and diplomatic response systems and critical medical resources (e.g., medicines and vaccines) must be in place before a bioattack occurs or a pandemic emerges.

  5. Deep depletions of total electron content associated with severe mid-latitude gigahertz scintillations during geomagnetic storms

    International Nuclear Information System (INIS)

    Ogawa, T.; Kumagai, H.

    1985-01-01

    Using 136-MHz Faraday rotation data obtained at three closely spaced stations, we present evidence that severe nightime gigahertz scintillations, which appear rarely at mid-latitudes around Japan only during geomagnetic storm conditions, are closely associated with deep depletions of total electron content (TEC). The TEC depletions amount to 2--8 x 10 16 el/m 2 (10--30% of the background TEC), and their durations range from 10 min to 1 hour. These depletions move northeastward or eastward with velocities between 60 and 260 m/s. The depletions are probably not counterparts of the equatorial bubbles but seem to be formed in localized regions around Japan under complicated and peculiar ionospheric conditions. There is an indication that the oscillation of the F region caused by large-scale TID's propagating from north to south (approx.600 m/s) may initiate the generation of the depletion

  6. Modelling economic losses of historic and present-day high-impact winter storms in Switzerland

    Science.gov (United States)

    Welker, Christoph; Martius, Olivia; Stucki, Peter; Bresch, David; Dierer, Silke; Brönnimann, Stefan

    2015-04-01

    simulate the wind field and related economic impact of both historic and present-day high-impact winter storms in Switzerland since end of the 19th century. Our technique involves the dynamical downscaling of the 20CR to 3 km horizontal resolution using the numerical Weather Research and Forecasting model and the subsequent loss simulation using an open-source impact model. This impact model estimates, for modern economic and social conditions, storm-related economic losses at municipality level, and thus allows a numerical simulation of the impact from both historic and present-day severe winter storms in Switzerland on a relatively fine spatial scale. In this study, we apply the modelling chain to a storm sample of almost 90 high-impact winter storms in Switzerland since 1871, and we are thus able to make a statement of the typical wind and loss patterns of hazardous windstorms in Switzerland. To evaluate our modelling chain, we compare simulated storm losses with insurance loss data for the present-day windstorms "Lothar" and "Joachim" in December 1999 and December 2011, respectively. Our study further includes a range of sensitivity experiments and a discussion of the main sources of uncertainty.

  7. Storm-surge flooding on the Yukon-Kuskokwim Delta, Alaska

    Science.gov (United States)

    Terenzi, John; Ely, Craig R.; Jorgenson, M. Torre

    2014-01-01

    Coastal regions of Alaska are regularly affected by intense storms of ocean origin, the frequency and intensity of which are expected to increase as a result of global climate change. The Yukon-Kuskokwim Delta (YKD), situated in western Alaska on the eastern edge of the Bering Sea, is one of the largest deltaic systems in North America. Its low relief makes it especially susceptible to storm-driven flood tides and increases in sea level. Little information exists on the extent of flooding caused by storm surges in western Alaska and its effects on salinization, shoreline erosion, permafrost thaw, vegetation, wildlife, and the subsistence-based economy. In this paper, we summarize storm flooding events in the Bering Sea region of western Alaska during 1913 – 2011 and map both the extent of inland flooding caused by autumn storms on the central YKD, using Radarsat-1 and MODIS satellite imagery, and the drift lines, using high-resolution IKONOS satellite imagery and field surveys. The largest storm surges occurred in autumn and were associated with high tides and strong (> 65 km hr-1) southwest winds. Maximum inland extent of flooding from storm surges was 30.3 km in 2005, 27.4 km in 2006, and 32.3 km in 2011, with total flood area covering 47.1%, 32.5%, and 39.4% of the 6730 km2 study area, respectively. Peak stages for the 2005 and 2011 storms were 3.1 m and 3.3 m above mean sea level, respectively—almost as high as the 3.5 m amsl elevation estimated for the largest storm observed (in November 1974). Several historically abandoned village sites lie within the area of inundation of the largest flood events. With projected sea level rise, large storms are expected to become more frequent and cover larger areas, with deleterious effects on freshwater ponds, non-saline habitats, permafrost, and landscapes used by nesting birds and local people.

  8. Empirical forecast of quiet time ionospheric Total Electron Content maps over Europe

    Science.gov (United States)

    Badeke, Ronny; Borries, Claudia; Hoque, Mainul M.; Minkwitz, David

    2018-06-01

    An accurate forecast of the atmospheric Total Electron Content (TEC) is helpful to investigate space weather influences on the ionosphere and technical applications like satellite-receiver radio links. The purpose of this work is to compare four empirical methods for a 24-h forecast of vertical TEC maps over Europe under geomagnetically quiet conditions. TEC map data are obtained from the Space Weather Application Center Ionosphere (SWACI) and the Universitat Politècnica de Catalunya (UPC). The time-series methods Standard Persistence Model (SPM), a 27 day median model (MediMod) and a Fourier Series Expansion are compared to maps for the entire year of 2015. As a representative of the climatological coefficient models the forecast performance of the Global Neustrelitz TEC model (NTCM-GL) is also investigated. Time periods of magnetic storms, which are identified with the Dst index, are excluded from the validation. By calculating the TEC values with the most recent maps, the time-series methods perform slightly better than the coefficient model NTCM-GL. The benefit of NTCM-GL is its independence on observational TEC data. Amongst the time-series methods mentioned, MediMod delivers the best overall performance regarding accuracy and data gap handling. Quiet-time SWACI maps can be forecasted accurately and in real-time by the MediMod time-series approach.

  9. Winter storm intensity, hazards, and property losses in the New York tristate area.

    Science.gov (United States)

    Shimkus, Cari E; Ting, Mingfang; Booth, James F; Adamo, Susana B; Madajewicz, Malgosia; Kushnir, Yochanan; Rieder, Harald E

    2017-07-01

    Winter storms pose numerous hazards to the Northeast United States, including rain, snow, strong wind, and flooding. These hazards can cause millions of dollars in damages from one storm alone. This study investigates meteorological intensity and impacts of winter storms from 2001 to 2014 on coastal counties in Connecticut, New Jersey, and New York and underscores the consequences of winter storms. The study selected 70 winter storms on the basis of station observations of surface wind strength, heavy precipitation, high storm tide, and snow extremes. Storm rankings differed between measures, suggesting that intensity is not easily defined with a single metric. Several storms fell into two or more categories (multiple-category storms). Following storm selection, property damages were examined to determine which types lead to high losses. The analysis of hazards (or events) and associated damages using the Storm Events Database of the National Centers for Environmental Information indicates that multiple-category storms were responsible for a greater portion of the damage. Flooding was responsible for the highest losses, but no discernible connection exists between the number of storms that afflict a county and the damage it faces. These results imply that losses may rely more on the incidence of specific hazards, infrastructure types, and property values, which vary throughout the region. © 2017 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of The New York Academy of Sciences.

  10. Forecasting of Currency Crises in East Asia

    Directory of Open Access Journals (Sweden)

    Chi-Young Song

    2005-06-01

    Full Text Available In this paper, we have developed a forecasting system for currency crisis in East Asia based on a signaling approach. Our system uses 15 monthly indicators of five East Asian countries including Indonesia, Korea, Malaysia, the Philippines and Thailand that were severely hit by the currency crisis in 1997. We investigate the performance of the system through deploying out-of-sample forecasting for the periods both before and after the 1997 East Asian currency crisis. Unlike the existing research based on the signaling approach, our out-of-sample forecasting does not fix the in-sample period. The out-of-sample forecasting between July 1995 and June 1997 shows that prior to breakout of the crisis, several indicators including real exchange rates and exports sent frequent warnings to all crisis-hit East Asian countries except the Philippines. This may indicate that a signaling-based early warning system for currency crisis could have been an useful method of forecasting the East Asian crisis. On the other hand, we also find that our forecasting system often generates warning signals during the out-of-sample period between July 1999 and June 2001. Since we have not observed any currency crisis in this region after 1998, these are all false alarms, indicating that our system may be seriously exposed to the type II error. We can, however, mitigate this problem if we adjust the optimal critical values of indicators depending on the preferences of forecasting system manager.

  11. Biological effects of geomagnetic storms

    International Nuclear Information System (INIS)

    Chibisov, S.M.; Breus, T.K.; Levitin, A.E.; Drogova, G.M.; AN SSSR, Moscow; AN SSSR, Moscow

    1995-01-01

    Six physiological parameters of cardio-vascular system of rabbits and ultrastructure of cardiomyocytes were investigated during two planetary geomagnetic storms. At the initial and main phase of the storm the normal circadian structure in each cardiovascular parameter was lost. The disynchronozis was growing together with the storm and abrupt drop of cardia activity was observed during the main phase of storm. The main phase of storm followed by the destruction and degradation of cardiomyocytes. Parameters of cardia activity became substantially synchronized and characterized by circadian rhythm structure while the amplitude of deviations was still significant at the recovery stage of geomagnetic storm. 3 refs.; 7 figs

  12. Sensitivity study of surface wind flow of a limited area model simulating the extratropical storm Delta affecting the Canary Islands

    OpenAIRE

    Marrero, C.; Jorba, O.; Cuevas, E.; Baldasano, J. M.

    2009-01-01

    In November 2005 an extratropical storm named Delta affected the Canary Islands (Spain). The high sustained wind and intense gusts experienced caused significant damage. A numerical sensitivity study of Delta was conducted using the Weather Research & Forecasting Model (WRF-ARW). A total of 27 simulations were performed. Non-hydrostatic and hydrostatic experiments were designed taking into account physical parameterizations and geometrical factors (size and position of the outer domain, d...

  13. Solar wind-magnetosphere coupling during intense magnetic storms (1978--1979)

    International Nuclear Information System (INIS)

    Gonzalez, W.D.; Tsurutani, B.T.; Gonzalez, A.L.C.; Smith, E.J.; Tang, F.; Akasofu, S.

    1989-01-01

    The solar wind-magnetosphere coupling problem is investigated for the ten intense magnetic storms (Dst <-100 nT) that occurred during the 500 days (August 16, 1978 to December 28, 1979) studied by Gonzalez and Tsurutani [1987]. This investigation concentrates on the ring current energization in terms of solar wind parameters, in order to explain the | -Dst | growth observed during these storms. Thus several coupling functions are tested as energy input and several sets of the ring current decay time-constant τ are searched to find best correlations with the Dst response. From the fairly large correlation coefficients found in this study, there is strong evidence that large scale magnetopause reconnection operates during such intense storm events and that the solar wind ram pressure plays an important role in the ring current energization. Thus a ram pressure correction factor is suggested for expressions concerning the reconnection power during time intervals with large ram pressure variations

  14. Coping with EPA's new petroleum industry storm water permits

    International Nuclear Information System (INIS)

    Veal, S.C.; Whitescarver, J.P.

    1994-01-01

    The United States Environmental Protection Agency has just released for public comment its so-called multi-sector industry specific storm water permit. This permit -- developed in response to the 730 group storm water permit applications submitted in 1992 to EPA -- proposes the establishment of specific runoff sampling and facility design requirements for at least two petroleum industry sectors. This proposed permit establishes specific conditions for the oil and gas extraction section (SIC group 13) and for lubricant manufacturers (SIC 2992). Permit conditions are also established for allied industrial sectors such as the chemical, transportation and asphalt materials industries. By most standards, the proposed permit is much tougher than EPA's baseline general permit for storm water discharges which was released in September of 1992. For example, under the proposal, most industries are required to perform periodic storm water sampling. EPA has also established storm water effluent and performance standards for several industrial categories. This paper will discuss the petroleum industry specific conditions of the new permit. The paper will also discuss the results of the industry-wide storm water sampling efforts undertaken by more than 300 oil patch facilities across the country. In particular, sampling results will be discussed in the context to the permit conditions proposed by EPA. The paper will also discuss strategies for dealing with the new permits

  15. A review of forecasting models for new products

    Directory of Open Access Journals (Sweden)

    Marta Mas-Machuca

    2014-02-01

    Full Text Available Purpose. The main objective of this article is to present an up-to-date review of new product forecasting techniques. Design/methodology/approach: A systematic review of forecasting journals was carried out using the ISI-Web of Knowledge database. Several articles were retrieved and examined, and forecasting techniques relevant to this study were selected and assessed. Findings: The strengths, weaknesses and applications of the main forecasting models are discussed to examine trends and set future challenges. Research limitations/implications: A theoretical reference framework for forecasting techniques classified into judgmental, consumer/market research, cause-effect and artificial intelligence is proposed. Future research can assess these models qualitatively. Practical implications: Companies are currently motivated to launch new products and thus attract new customers to expand their market share.  In order to reduce uncertainty and risk, many companies go to extra lengths to forecast sales accurately using several techniques. Originality/value: This article outlines new lines of research on the improvement of new product performance which will aid managers in decision making and allow companies to sustain their competitive advantages in this challenging world.

  16. Forecasting in an integrated surface water-ground water system: The Big Cypress Basin, South Florida

    Science.gov (United States)

    Butts, M. B.; Feng, K.; Klinting, A.; Stewart, K.; Nath, A.; Manning, P.; Hazlett, T.; Jacobsen, T.

    2009-04-01

    The South Florida Water Management District (SFWMD) manages and protects the state's water resources on behalf of 7.5 million South Floridians and is the lead agency in restoring America's Everglades - the largest environmental restoration project in US history. Many of the projects to restore and protect the Everglades ecosystem are part of the Comprehensive Everglades Restoration Plan (CERP). The region has a unique hydrological regime, with close connection between surface water and groundwater, and a complex managed drainage network with many structures. Added to the physical complexity are the conflicting needs of the ecosystem for protection and restoration, versus the substantial urban development with the accompanying water supply, water quality and flood control issues. In this paper a novel forecasting and real-time modelling system is presented for the Big Cypress Basin. The Big Cypress Basin includes 272 km of primary canals and 46 water control structures throughout the area that provide limited levels of flood protection, as well as water supply and environmental quality management. This system is linked to the South Florida Water Management District's extensive real-time (SCADA) data monitoring and collection system. Novel aspects of this system include the use of a fully distributed and integrated modeling approach and a new filter-based updating approach for accurately forecasting river levels. Because of the interaction between surface- and groundwater a fully integrated forecast modeling approach is required. Indeed, results for the Tropical Storm Fay in 2008, the groundwater levels show an extremely rapid response to heavy rainfall. Analysis of this storm also shows that updating levels in the river system can have a direct impact on groundwater levels.

  17. The new IEA Wind Task 36 on Wind Power Forecasting

    DEFF Research Database (Denmark)

    Giebel, Gregor; Cline, Joel; Frank, Helmut

    Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Forecasting for Wind E...... forecasts, including probabilistic forecasts. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions....

  18. Multivariate Hybrid Modelling of Future Wave-Storms at the Northwestern Black Sea

    Directory of Open Access Journals (Sweden)

    Jue Lin-Ye

    2018-02-01

    Full Text Available The characterization of future wave-storms and their relationship to large-scale climate can provide useful information for environmental or urban planning at coastal areas. A hybrid methodology (process-based and statistical was used to characterize the extreme wave-climate at the northwestern Black Sea. The Simulating WAve Nearshore spectral wave-model was employed to produce wave-climate projections, forced with wind-fields projections for two climate change scenarios: Representative Concentration Pathways (RCPs 4.5 and 8.5. A non-stationary multivariate statistical model was built, considering significant wave-height and peak-wave-period at the peak of the wave-storm, as well as storm total energy and storm-duration. The climate indices of the North Atlantic Oscillation, East Atlantic Pattern, and Scandinavian Pattern have been used as covariates to link to storminess, wave-storm threshold, and wave-storm components in the statistical model. The results show that, first, under both RCP scenarios, the mean values of significant wave-height and peak-wave-period at the peak of the wave-storm remain fairly constant over the 21st century. Second, the mean value of storm total energy is more markedly increasing in the RCP4.5 scenario than in the RCP8.5 scenario. Third, the mean value of storm-duration is increasing in the RCP4.5 scenario, as opposed to the constant trend in the RCP8.5 scenario. The variance of each wave-storm component increases when the corresponding mean value increases under both RCP scenarios. During the 21st century, the East Atlantic Pattern and changes in its pattern have a special influence on wave-storm conditions. Apart from the individual characteristics of each wave-storm component, wave-storms with both extreme energy and duration can be expected in the 21st century. The dependence between all the wave-storm components is moderate, but grows with time and, in general, the severe emission scenario of RCP8.5 presents

  19. A New Approach to Forecasting Exchange Rates

    OpenAIRE

    Kenneth W Clements; Yihui Lan

    2006-01-01

    Building on purchasing power parity theory, this paper proposes a new approach to forecasting exchange rates using the Big Mac data from The Economist magazine. Our approach is attractive in three aspects. Firstly, it uses easily-available Big Mac prices as input. These prices avoid several serious problems associated with broad price indexes, such as the CPI, that are used in conventional PPP studies. Secondly, this approach provides real-time exchange-rate forecasts at any forecast horizon....

  20. Thyroid storm and warm autoimmune hemolytic anemia.

    Science.gov (United States)

    Moore, Joseph A; Gliga, Louise; Nagalla, Srikanth

    2017-08-01

    Graves' disease is often associated with other autoimmune disorders, including rare associations with autoimmune hemolytic anemia (AIHA). We describe a unique presentation of thyroid storm and warm AIHA diagnosed concurrently in a young female with hyperthyroidism. The patient presented with nausea, vomiting, diarrhea and altered mental status. Laboratory studies revealed hemoglobin 3.9g/dL, platelets 171×10 9 L -1 , haptoglobin storm and warm AIHA. She was started on glucocorticoids to treat both warm AIHA and thyroid storm, as well as antithyroid medications, propranolol and folic acid. Due to profound anemia and hemodynamic instability, the patient was transfused two units of uncrossmatched packed red blood cells slowly and tolerated this well. She was discharged on methimazole as well as a prolonged prednisone taper, and achieved complete resolution of the thyrotoxicosis and anemia at one month. Hyperthyroidism can affect all three blood cell lineages of the hematopoietic system. Anemia can be seen in 10-20% of patients with thyrotoxicosis. Several autoimmune processes can lead to anemia in Graves' disease, including pernicious anemia, celiac disease, and warm AIHA. This case illustrates a rarely described presentation of a patient with Graves' disease presenting with concurrent thyroid storm and warm AIHA. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Environmentally-driven ensemble forecasts of dengue fever

    Science.gov (United States)

    Yamana, T. K.; Shaman, J. L.

    2017-12-01

    Dengue fever is a mosquito-borne viral disease prevalent in the tropics and subtropics, with an estimated 2.5 billion people at risk of transmission. In many areas where dengue is found, disease transmission is seasonal but prone to high inter-annual variability with occasional severe epidemics. Predicting and preparing for periods of higher than average transmission remains a significant public health challenge. Recently, we developed a framework for forecasting dengue incidence using an dynamical model of disease transmission coupled with observational data of dengue cases using data-assimilation methods. Here, we investigate the use of environmental data to drive the disease transmission model. We produce retrospective forecasts of the timing and severity of dengue outbreaks, and quantify forecast predictive accuracy.

  2. Dynamic neural network modeling of HF radar current maps for forecasting oil spill trajectories

    International Nuclear Information System (INIS)

    Tissot, P.; Perez, J.; Kelly, F.J.; Bonner, J.; Michaud, P.

    2001-01-01

    This paper examined the concept of dynamic neural network (NN) modeling for short-term forecasts of coastal high-frequency (HF) radar current maps offshore of Galveston Texas. HF radar technology is emerging as a viable and affordable way to measure surface currents in real time and the number of users applying the technology is increasing. A 25 megahertz, two site, Seasonde HF radar system was used to map ocean and bay surface currents along the coast of Texas where wind and river discharge create complex and rapidly changing current patters that override the weaker tidal flow component. The HF radar system is particularly useful in this type of setting because its mobility makes it a good marine spill response tool that could provide hourly current maps. This capability helps improve deployment of response resources. In addition, the NN model recently developed by the Conrad Blucher Institute can be used to forecast water levels during storm events. Forecasted currents are based on time series of current vectors from HF radar plus wind speed, wind direction, and water levels, as well as tidal forecasts. The dynamic NN model was tested to evaluate its performance and the results were compared with a baseline model which assumes the currents do not change from the time of the forecast up to the forecasted time. The NN model showed improvements over the baseline model for forecasting time equal or greater than 3 hours, but the difference was relatively small. The test demonstrated the ability of the dynamic NN model to link meteorological forcing functions with HF radar current maps. Development of the dynamic NN modeling is still ongoing. 18 refs., 1 tab., 5 figs

  3. New Employment Forecasts. Hotel and Catering Industry 1988-1993.

    Science.gov (United States)

    Measurement for Management Decision, Ltd., London (England).

    Econometric forecasting models were used to forecast employment levels in the hotel and catering industry in Great Britain through 1993 under several different forecasting scenarios. The growth in employment in the hotel and catering industry over the next 5 years is likely to be broadly based, both across income levels of domestic consumers,…

  4. Wave modelling to assess the storm conditions in the Black Sea

    Science.gov (United States)

    Rusu, Liliana; Raileanu, Alina

    2014-05-01

    The work proposed herewith presents the results of a ten-year wave hindcast performed in the Black Sea and focused on the storm conditions. A wave modelling system, SWAN based, was implemented in the basin of the Black Sea. Validations have been performed both against in situ and remotely sensed data for the entire ten-year period considered (1999-2008). The wind field provided by NCEP-CFSR (United States National Centers for Environmental Prediction, Climate Forecast System Reanalysis) with a spatial resolution of 0.312ºx0.312º and a temporal resolution of 3 hours was considered for forcing the wave model. In statistical terms, the results are in general in line with those provided by similar wave prediction systems implemented in enclosed or semi-enclosed seas, the most important factors in increasing the general system reliability being the accuracy and resolution of the wind fields considered. As regards the physical processes, the calibration tests performed show that whitecapping still represents the weak link in deep water wave modelling. The most relevant storm conditions encountered in this ten-year period considered were further analysed. This analysis was performed from the point of view of the intensity, location of occurrence, duration and propagation in the geographical space of the storms. Following the results of the work, the western side of the sea is more energetic and almost each year storms with significant wave heights of about eight meters are encountered in this part of the Black Sea, while in the case of the extreme storms significant wave heights even greater than eleven meters may occur. From this perspective, it can be concluded that the present work provides valuable information about the characteristics of the storm conditions and on their dynamics in the Black Sea. Moreover, this marine environment is currently subjected to high navigation traffic and to offshore operations and the strong storms that systematically occur may produce

  5. Ice storm '98: The electricity industry's great challenge

    International Nuclear Information System (INIS)

    Anon.

    1998-01-01

    The biggest and most costly natural disaster to hit Canada in over a century, the ice storms of 1998, that transformed Eastern Canada into a virtual glacier, was discussed. Trees, wires, poles, transmission towers, transformers succumbed to the immense weight of the ice, countless transmission and distribution lines were destroyed, leaving millions in the dark and cold, many for several weeks. The unprecedented show of solidarity within the electricity industry, as hundreds of crews from utilities across Canada and the U.S., the many thousands of private individuals and some 16,000 members of the Canadian Forces that came to the assistance of those in the affected areas, working 16-hour days, braving falling trees and sub-zero temperatures, was truly astonishing, and clearly the stuff of which legends are made. The storm has humbled Canadian public authorities and especially the Canadian electricity industry. Besides honoring those that weathered the storm, and paying tribute to the utilities and private companies that reached out to assist in the relief efforts, this review also discusses the need for government agencies and utility companies to review their emergency preparedness plans. The objective is to improve them by incorporating the most important lessons learned from this experience, in an effort to forestall their future recurrence. It is generally accepted that the Ice Storm of '98 was a unique natural disaster that no amount of planning could have foreseen, much less prevented. Nevertheless, by examining the lessons learned, it might be possible to reduce the severity should a similar disaster occur again

  6. A methodology for Electric Power Load Forecasting

    Directory of Open Access Journals (Sweden)

    Eisa Almeshaiei

    2011-06-01

    Full Text Available Electricity demand forecasting is a central and integral process for planning periodical operations and facility expansion in the electricity sector. Demand pattern is almost very complex due to the deregulation of energy markets. Therefore, finding an appropriate forecasting model for a specific electricity network is not an easy task. Although many forecasting methods were developed, none can be generalized for all demand patterns. Therefore, this paper presents a pragmatic methodology that can be used as a guide to construct Electric Power Load Forecasting models. This methodology is mainly based on decomposition and segmentation of the load time series. Several statistical analyses are involved to study the load features and forecasting precision such as moving average and probability plots of load noise. Real daily load data from Kuwaiti electric network are used as a case study. Some results are reported to guide forecasting future needs of this network.

  7. [Thyroid emergencies : Thyroid storm and myxedema coma].

    Science.gov (United States)

    Spitzweg, C; Reincke, M; Gärtner, R

    2017-10-01

    Thyroid emergencies are rare life-threatening endocrine conditions resulting from either decompensated thyrotoxicosis (thyroid storm) or severe thyroid hormone deficiency (myxedema coma). Both conditions develop out of a long-standing undiagnosed or untreated hyper- or hypothyroidism, respectively, precipitated by an acute stress-associated event, such as infection, trauma, or surgery. Cardinal features of thyroid storm are myasthenia, cardiovascular symptoms, in particular tachycardia, as well as hyperthermia and central nervous system dysfunction. The diagnosis is made based on clinical criteria only as thyroid hormone measurements do not differentiate between thyroid storm and uncomplicated hyperthyroidism. In addition to critical care measures therapy focusses on inhibition of thyroid hormone synthesis and secretion (antithyroid drugs, perchlorate, Lugol's solution, cholestyramine, thyroidectomy) as well as inhibition of thyroid hormone effects in the periphery (β-blocker, glucocorticoids).Cardinal symptoms of myxedema coma are hypothermia, decreased mental status, and hypoventilation with risk of pneumonia and hyponatremia. The diagnosis is also purely based on clinical criteria as measurements of thyroid hormone levels do not differ between uncomplicated severe hypothyroidism and myxedema coma. In addition to substitution of thyroid hormones and glucocorticoids, therapy focusses on critical care measures to treat hypoventilation and hypercapnia, correction of hyponatremia and hypothermia.Survival of both thyroid emergencies can only be optimized by early diagnosis based on clinical criteria and prompt initiation of multimodal therapy including supportive measures and treatment of the precipitating event.

  8. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Ruelke

    2013-01-01

    We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from) t......) the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time....

  9. Case studies of extended model-based flood forecasting: prediction of dike strength and flood impacts

    Science.gov (United States)

    Stuparu, Dana; Bachmann, Daniel; Bogaard, Tom; Twigt, Daniel; Verkade, Jan; de Bruijn, Karin; de Leeuw, Annemargreet

    2017-04-01

    to local forecasting. The third case explores the use of global models for local flood forecasting in Manila Bay (Philippines). The forecasting chain combines global forecasted data on storm surges, a local hydrodynamic model of the bay and the hinterland and a quantitative impact model. All three study-cases prove the added value of extended flood impact forecasting systems: timely identification of the weak spots in the flood defence lines, expected flood spread and extent as well as expected impacts and consequences of a flood event.

  10. Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

    Science.gov (United States)

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

    2009-04-01

    In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

  11. Shifting Pacific storm tracks as stressors to ecosystems of western North America.

    Science.gov (United States)

    Dannenberg, Matthew P; Wise, Erika K

    2017-11-01

    Much of the precipitation delivered to western North America arrives during the cool season via midlatitude Pacific storm tracks, which may experience future shifts in response to climate change. Here, we assess the sensitivity of the hydroclimate and ecosystems of western North America to the latitudinal position of cool-season Pacific storm tracks. We calculated correlations between storm track variability and three hydroclimatic variables: gridded cool-season standardized precipitation-evapotranspiration index, April snow water equivalent, and water year streamflow from a network of USGS stream gauges. To assess how historical storm track variability affected ecosystem processes, we derived forest growth estimates from a large network of tree-ring widths and land surface phenology and wildfire estimates from remote sensing. From 1980 to 2014, cool-season storm tracks entered western North America between approximately 41°N and 53°N. Cool-season moisture supply and snowpack responded strongly to storm track position, with positive correlations to storm track latitude in eastern Alaska and northwestern Canada but negative correlations in the northwestern U.S. Ecosystems of the western United States were greener and more productive following winters with south-shifted storm tracks, while Canadian ecosystems were greener in years when the cool-season storm track was shifted to the north. On average, larger areas of the northwestern United States were burned by moderate to high severity wildfires when storm tracks were displaced north, and the average burn area per fire also tended to be higher in years with north-shifted storm tracks. These results suggest that projected shifts of Pacific storm tracks over the 21st century would likely alter hydroclimatic and ecological regimes in western North America, particularly in the northwestern United States, where moisture supply and ecosystem processes are highly sensitive to the position of cool-season storm tracks.

  12. IRI STORM validation over Europe

    Science.gov (United States)

    Haralambous, Haris; Vryonides, Photos; Demetrescu, Crişan; Dobrică, Venera; Maris, Georgeta; Ionescu, Diana

    2014-05-01

    The International Reference Ionosphere (IRI) model includes an empirical Storm-Time Ionospheric Correction Model (STORM) extension to account for storm-time changes of the F layer peak electron density (NmF2) during increased geomagnetic activity. This model extension is driven by past history values of the geomagnetic index ap (The magnetic index applied is the integral of ap over the previous 33 hours with a weighting function deduced from physically based modeling) and it adjusts the quiet-time F layer peak electron density (NmF2) to account for storm-time changes in the ionosphere. In this investigation manually scaled hourly values of NmF2 measured during the main and recovery phases of selected storms for the maximum solar activity period of the current solar cycle are compared with the predicted IRI-2012 NmF2 over European ionospheric stations using the STORM model option. Based on the comparison a subsequent performance evaluation of the STORM option during this period is quantified.

  13. Should we use seasonnal meteorological ensemble forecasts for hydrological forecasting? A case study for nordic watersheds in Canada.

    Science.gov (United States)

    Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert; Guay, Catherine

    2017-04-01

    reliability diagram. This study covers 10 nordic watersheds. We show that forecast performance according to the CRPS varies with lead-time but also with the period of the year. The raw forecasts from the ECMWF System4 display important biases for both temperature and precipitation, which need to be corrected. The linear scaling method is used for this purpose and is found effective. Bias correction improves forecasts performance, especially during the summer when the precipitations are over-estimated. According to the CRPS, bias corrected forecasts from System4 show performances comparable to those of the ESP system. However, the Ignorance score, which penalizes the lack of calibration (under-dispersive forecasts in this case) more severely than the CRPS, provides a different outlook for the comparison of the two systems. In fact, according to the Ignorance score, the ESP system outperforms forecasts based on System4 in most cases. This illustrates that the joint use of several metrics is crucial to assess the quality of a forecasts system thoroughly. Globally, ESP provide reliable forecasts which can be over-dispersed whereas bias corrected ECMWF System4 forecasts are sharper but at the risk of missing events.

  14. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    Directory of Open Access Journals (Sweden)

    Christian Pierdzioch

    2012-11-01

    Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

  15. Dynamics of a longitudinal current during a magnetic storm

    International Nuclear Information System (INIS)

    Dolginov, S.Sh.; Zhuzgov, L.N.; Kosacheva, V.P.; Strunnikova, L.N.; Tyurmina, L.O.; Sharova, V.A.; Shkol'nikova, S.I.

    1984-01-01

    Results, investigating a spatial distribution and the structure of longitudinal currents during a magnetic storm at 18-19.09.81, are presented. It is shown that during the main phase of the storm the large-scale current system expands to the equator, and current density increases. Inside the current layer and to the pole of it there appears intensive small scale longitudinal l currents. During magnetic storm restopation phase the current system segregates into several pairs of opposite directed currents. During further decreasing of geomagnetic activity the large-scale current system is restored+ and its center is shifted to the pole, longitudinal current density being decreased. The invariant width of longitudinal currents is decreased, while the magnitude, Dsub(st), being increased, that is connected to the displacement of an auroral oval to the equator

  16. Air-sea interactions during strong winter extratropical storms

    Science.gov (United States)

    Nelson, Jill; He, Ruoying; Warner, John C.; Bane, John

    2014-01-01

    A high-resolution, regional coupled atmosphere–ocean model is used to investigate strong air–sea interactions during a rapidly developing extratropical cyclone (ETC) off the east coast of the USA. In this two-way coupled system, surface momentum and heat fluxes derived from the Weather Research and Forecasting model and sea surface temperature (SST) from the Regional Ocean Modeling System are exchanged via the Model Coupling Toolkit. Comparisons are made between the modeled and observed wind velocity, sea level pressure, 10 m air temperature, and sea surface temperature time series, as well as a comparison between the model and one glider transect. Vertical profiles of modeled air temperature and winds in the marine atmospheric boundary layer and temperature variations in the upper ocean during a 3-day storm period are examined at various cross-shelf transects along the eastern seaboard. It is found that the air–sea interactions near the Gulf Stream are important for generating and sustaining the ETC. In particular, locally enhanced winds over a warm sea (relative to the land temperature) induce large surface heat fluxes which cool the upper ocean by up to 2 °C, mainly during the cold air outbreak period after the storm passage. Detailed heat budget analyses show the ocean-to-atmosphere heat flux dominates the upper ocean heat content variations. Results clearly show that dynamic air–sea interactions affecting momentum and buoyancy flux exchanges in ETCs need to be resolved accurately in a coupled atmosphere–ocean modeling framework.

  17. Flood forecasting within urban drainage systems using NARX neural network.

    Science.gov (United States)

    Abou Rjeily, Yves; Abbas, Oras; Sadek, Marwan; Shahrour, Isam; Hage Chehade, Fadi

    2017-11-01

    Urbanization activity and climate change increase the runoff volumes, and consequently the surcharge of the urban drainage systems (UDS). In addition, age and structural failures of these utilities limit their capacities, and thus generate hydraulic operation shortages, leading to flooding events. The large increase in floods within urban areas requires rapid actions from the UDS operators. The proactivity in taking the appropriate actions is a key element in applying efficient management and flood mitigation. Therefore, this work focuses on developing a flooding forecast system (FFS), able to alert in advance the UDS managers for possible flooding. For a forecasted storm event, a quick estimation of the water depth variation within critical manholes allows a reliable evaluation of the flood risk. The Nonlinear Auto Regressive with eXogenous inputs (NARX) neural network was chosen to develop the FFS as due to its calculation nature it is capable of relating water depth variation in manholes to rainfall intensities. The campus of the University of Lille is used as an experimental site to test and evaluate the FFS proposed in this paper.

  18. Ionospheric forecasting model using fuzzy logic-based gradient descent method

    Directory of Open Access Journals (Sweden)

    D. Venkata Ratnam

    2017-09-01

    Full Text Available Space weather phenomena cause satellite to ground or satellite to aircraft transmission outages over the VHF to L-band frequency range, particularly in the low latitude region. Global Positioning System (GPS is primarily susceptible to this form of space weather. Faulty GPS signals are attributed to ionospheric error, which is a function of Total Electron Content (TEC. Importantly, precise forecasts of space weather conditions and appropriate hazard observant cautions required for ionospheric space weather observations are limited. In this paper, a fuzzy logic-based gradient descent method has been proposed to forecast the ionospheric TEC values. In this technique, membership functions have been tuned based on the gradient descent estimated values. The proposed algorithm has been tested with the TEC data of two geomagnetic storms in the low latitude station of KL University, Guntur, India (16.44°N, 80.62°E. It has been found that the gradient descent method performs well and the predicted TEC values are close to the original TEC measurements.

  19. A study of the effect of geomagnetic storms on low latitude whistlers

    International Nuclear Information System (INIS)

    Rao, Manoranjan; Somayajulu, V.V.; Dikshit, S.K.

    1974-01-01

    This paper presents the results of a detailed study of the influence of geomagnetic storms on low latitude whistlers recorded on ground. Studied in detail is the effect of the geomagnetic storm of March 6-10, 1970 on whistlers recorded at Gulmarg (Geomagnetic coordinates: 24 0 10'N; 147 0 24'E); results of analysis for the earlier storm of January 13-15, 1967 are included for comparison. Some of the important results of the present study are: (i) Both the whistler occurrence rate and dispersion increase simultaneously with Kp, (ii) During the decaying phase of the storm, changes in occurrence rate and in dispersion lag behind those in Kp, (iii) There is an indication of the existence of a cross-over latitude where tube contents may not change appreciably during storm periods, (iv) Multipath whistlers are observed only during disturbed conditions, (v) Duct life ranges between several hours to few days and (vi) Maximum number of ducts is observed during the main and recovery phases of the storm. (auth.)

  20. Forecasting daily patient volumes in the emergency department.

    Science.gov (United States)

    Jones, Spencer S; Thomas, Alun; Evans, R Scott; Welch, Shari J; Haug, Peter J; Snow, Gregory L

    2008-02-01

    Shifts in the supply of and demand for emergency department (ED) resources make the efficient allocation of ED resources increasingly important. Forecasting is a vital activity that guides decision-making in many areas of economic, industrial, and scientific planning, but has gained little traction in the health care industry. There are few studies that explore the use of forecasting methods to predict patient volumes in the ED. The goals of this study are to explore and evaluate the use of several statistical forecasting methods to predict daily ED patient volumes at three diverse hospital EDs and to compare the accuracy of these methods to the accuracy of a previously proposed forecasting method. Daily patient arrivals at three hospital EDs were collected for the period January 1, 2005, through March 31, 2007. The authors evaluated the use of seasonal autoregressive integrated moving average, time series regression, exponential smoothing, and artificial neural network models to forecast daily patient volumes at each facility. Forecasts were made for horizons ranging from 1 to 30 days in advance. The forecast accuracy achieved by the various forecasting methods was compared to the forecast accuracy achieved when using a benchmark forecasting method already available in the emergency medicine literature. All time series methods considered in this analysis provided improved in-sample model goodness of fit. However, post-sample analysis revealed that time series regression models that augment linear regression models by accounting for serial autocorrelation offered only small improvements in terms of post-sample forecast accuracy, relative to multiple linear regression models, while seasonal autoregressive integrated moving average, exponential smoothing, and artificial neural network forecasting models did not provide consistently accurate forecasts of daily ED volumes. This study confirms the widely held belief that daily demand for ED services is characterized by

  1. Evolutionary Forecast Engines for Solar Meteorology

    Science.gov (United States)

    Coimbra, C. F.

    2012-12-01

    A detailed comparison of non-stationary regression and stochastic learning methods based on k-Nearest Neighbor (kNN), Artificial Neural Networks (ANN) and Genetic Algorithm (GA) approaches is carried out in order to develop high-fidelity solar forecast engines for several time horizons of interest. A hybrid GA/ANN method emerges as the most robust stochastic learning candidate. The GA/ANN approach In general the following decisions need to be made when creating an ANN-based solar forecast model: the ANN architecture: number of layers, numbers of neurons per layer; the preprocessing scheme; the fraction and distribution between training and testing data, and the meteorological and radiometric inputs. ANNs are very well suited to handle multivariate forecasting models due to their overall flexibility and nonlinear pattern recognition abilities. However, the forecasting skill of ANNs depends on a new set of parameters to be optimized within the context of the forecast model, which is the selection of input variables that most directly impact the fidelity of the forecasts. In a data rich scenario where irradiation, meteorological, and cloud cover data are available, it is not always evident which variables to include in the model a priori. New variables can also arise from data preprocessing such as smoothing or spectral decomposition. One way to avoid time-consuming trial-and-error approaches that have limited chance to result in optimal ANN topology and input selection is to couple the ANN with some optimization algorithm that scans the solution space and "evolves" the ANN structure. Genetic Algorithms (GAs) are well suited for this task. Results and Discussion The models built upon the historical data of 2009 and 2010 are applied to the 2011 data without modifications or retraining. We consider 3 solar variability seasons or periods, which are subsets of the total error evaluation data set. The 3 periods are defined based on the solar variability study as: - a high

  2. Data-based Modeling of the Dynamical Inner Magnetosphere During Strong Geomagnetic Storms

    Science.gov (United States)

    Tsyganenko, N.; Sitnov, M.

    2004-12-01

    , with the peak values as large as 5--8 MA for the symmetric ring current and region 1 field-aligned current. At the peak of the main phase, the total partial ring current can largely exceed the symmetric one, reaching ˜10 MA and even more, but it quickly subsides as the external solar wind driving disappears, with the relaxation time ≤2 hours. The tail current dramatically increases during the main phase and shifts earthward, so that the peak current concentrates at unusually close distances ˜4-6RE. This is accompanied by a significant thinning of the current sheet and enormous tailward stretching of the inner geomagnetic field lines. As an independent consistency test, we calculated the expected Dst-variation based on the model output at Earth's surface and compared it with the actual observed Dst. A good agreement (cumulative correlation coefficient R=0.92) was found, in spite of that ˜90% of the spacecraft data used in the fitting were taken at synchronous orbit and beyond, while only 3.7% of those data came from distances 2.5≤ R≤4 RE. The obtained results demonstrate the possibility to develop a dynamical model of the magnetic field, based on magnetospheric and interplanetary data and allowing one to reproduce and forecast the entire process of a geomagnetic storm, as it unfolds in time and space. Reference: N. A. Tsyganenko, H. J. Singer, J. C. Kasper, Storm-time distortion of the inner magnetosphere: How severe can it get ? J. Geophys. Res., v. 108(A5), 1209, 2003.

  3. Integrating a Storage Factor into R-NARX Neural Networks for Flood Forecasts

    Science.gov (United States)

    Chou, Po-Kai; Chang, Li-Chiu; Chang, Fi-John; Shih, Ban-Jwu

    2017-04-01

    Because mountainous terrains and steep landforms rapidly accelerate the speed of flood flow in Taiwan island, accurate multi-step-ahead inflow forecasts during typhoon events for providing reliable information benefiting the decision-makings of reservoir pre-storm release and flood-control operation are considered crucial and challenging. Various types of artificial neural networks (ANNs) have been successfully applied in hydrological fields. This study proposes a recurrent configuration of the nonlinear autoregressive with exogenous inputs (NARX) network, called R-NARX, with various effective inputs to forecast the inflows of the Feitsui Reservoir, a pivot reservoir for water supply to Taipei metropolitan in Taiwan, during typhoon periods. The proposed R-NARX is constructed based on the recurrent neural network (RNN), which is commonly used for modelling nonlinear dynamical systems. A large number of hourly rainfall and inflow data sets collected from 95 historical typhoon events in the last thirty years are used to train, validate and test the models. The potential input variables, including rainfall in previous time steps (one to six hours), cumulative rainfall, the storage factor and the storage function, are assessed, and various models are constructed with their reliability and accuracy being tested. We find that the previous (t-2) rainfall and cumulative rainfall are crucial inputs and the storage factor and the storage function would also improve the forecast accuracy of the models. We demonstrate that the R-NARX model not only can accurately forecast the inflows but also effectively catch the peak flow without adopting observed inflow data during the entire typhoon period. Besides, the model with the storage factor is superior to the model with the storage function, where its improvement can reach 24%. This approach can well model the rainfall-runoff process for the entire flood forecasting period without the use of observed inflow data and can provide

  4. Forecasting with nonlinear time series models

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Teräsvirta, Timo

    In this paper, nonlinear models are restricted to mean nonlinear parametric models. Several such models popular in time series econo- metrics are presented and some of their properties discussed. This in- cludes two models based on universal approximators: the Kolmogorov- Gabor polynomial model...... applied to economic fore- casting problems, is briefly highlighted. A number of large published studies comparing macroeconomic forecasts obtained using different time series models are discussed, and the paper also contains a small simulation study comparing recursive and direct forecasts in a partic...... and two versions of a simple artificial neural network model. Techniques for generating multi-period forecasts from nonlinear models recursively are considered, and the direct (non-recursive) method for this purpose is mentioned as well. Forecasting with com- plex dynamic systems, albeit less frequently...

  5. [Diagnosis and treatment of thyroid storm].

    Science.gov (United States)

    Akamizu, Takashi

    2012-11-01

    Thyrotoxic storm is a life-threatening condition requiring emergency treatment. Neither its epidemiological data nor diagnostic criteria have been fully established. We clarified the clinical and epidemiological characteristics of thyroid storm using nationwide surveys and then formulate diagnostic criteria for thyroid storm. To perform the nationwide survey on thyroid storm, we first developed tentative diagnostic criteria for thyroid storm, mainly based upon the literature (the first edition). We analyzed the relationship of the major features of thyroid storm to mortality and to certain other features. Finally, based upon the findings of these surveys, we revised the diagnostic criteria. Thyrotoxic storm is still a life-threatening disorder with over 10% mortality in Japan.

  6. Exceptional winter storms affecting Western Iberia and extremes: diagnosis, modelling and multi-model ensemble projection

    Science.gov (United States)

    Liberato, M. L. R.; Pinto, J. G.; Gil, V.; Ramos, A. M.; Trigo, R. M.

    2017-12-01

    Extratropical cyclones dominate autumn and winter weather over Western Europe and particularly over the Iberian Peninsula. Intense, high-impact storms are one of the major weather risks in the region, mostly due to the simultaneous occurrence of high winds and extreme precipitation events. These intense extratropical cyclones may result in windstorm damage, flooding and coastal storm surges, with large societal impacts. In Portugal, due to the extensive human use of coastal areas, the natural and built coastal environments have been amongst the most affected. In this work several historical winter storms that adversely affected the Western Iberian Peninsula are studied in detail in order to contribute to an improved assessment of the characteristics of these events. The diagnosis has been performed based on instrumental daily precipitation and wind records, on satellite images, on reanalysis data and through model simulations. For several examples the synoptic evolution and upper-level dynamics analysis of physical processes controlling the life cycle of extratropical storms associated with the triggering of the considered extreme events has also been accomplished. Furthermore, the space-time variability of the exceptionally severe storms affecting Western Iberia over the last century and under three climate scenarios (the historical simulation, the RCP4.5 and RCP8.5 scenarios) is presented. These studies contribute to improving the knowledge of atmospheric dynamics controlling the life cycle of midlatitude storms associated to severe weather (precipitation and wind) in the Iberian Peninsula. AcknowledgementsThis work is supported by the Portuguese Foundation for Science and Technology (FCT), Portugal, through project UID/GEO/50019/2013 - Instituto Dom Luiz. A. M. Ramos is also supported by a FCT postdoctoral grant (FCT/DFRH/SFRH/BPD/84328/2012).

  7. Observations and global numerical modelling of the St. Patrick's Day 2015 geomagnetic storm event

    Science.gov (United States)

    Foerster, M.; Prokhorov, B. E.; Doornbos, E.; Astafieva, E.; Zakharenkova, I.

    2017-12-01

    With a sudden storm commencement (SSC) at 04:45 UT on St. Patrick's day 2015 started the most severe geomagnetic storm in solar cycle 24. It appeared as a two-stage geomagnetic storm with a minimum SYM-H value of -233 nT. In the response to the storm commencement in the first activation, a short-term positive effect in the ionospheric vertical electron content (VTEC) occurred at low- and mid-latitudes on the dayside. The second phase commencing around 12:30 UT lasted longer and caused significant and complex storm-time changes around the globe with hemispherical different ionospheric storm reactions in different longitudinal ranges. Swarm-C observations of the neutral mass density variation along the orbital path as well as Langmuir probe plasma and magnetometer measurements of all three Swarm satellites and global TEC records are used for physical interpretations and modelling of the positive/negative storm scenario. These observations pose a challenge for the global numerical modelling of thermosphere-ionosphere storm processes as the storm, which occurred around spring equinox, obviously signify the existence of other impact factors than seasonal dependence for hemispheric asymmetries to occur. Numerical simulation trials using the Potsdam version of the Upper Atmosphere Model (UAM-P) are presented to explain these peculiar M-I-T storm processes.

  8. The Development of High-speed Full-function Storm Surge Model and the Case Study of 2013 Typhoon Haiyan

    Science.gov (United States)

    Tsai, Y. L.; Wu, T. R.; Lin, C. Y.; Chuang, M. H.; Lin, C. W.

    2016-02-01

    An ideal storm surge operational model should feature as: 1. Large computational domain which covers the complete typhoon life cycle. 2. Supporting both parametric and atmospheric models. 3. Capable of calculating inundation area for risk assessment. 4. Tides are included for accurate inundation simulation. Literature review shows that not many operational models reach the goals for the fast calculation, and most of the models have limited functions. In this paper, a well-developed COMCOT (COrnell Multi-grid Coupled of Tsunami Model) tsunami model is chosen as the kernel to establish a storm surge model which solves the nonlinear shallow water equations on both spherical and Cartesian coordinates directly. The complete evolution of storm surge including large-scale propagation and small-scale offshore run-up can be simulated by nested-grid scheme. The global tide model TPXO 7.2 established by Oregon State University is coupled to provide astronomical boundary conditions. The atmospheric model named WRF (Weather Research and Forecasting Model) is also coupled to provide metrological fields. The high-efficiency thin-film method is adopted to evaluate the storm surge inundation. Our in-house model has been optimized by OpenMp (Open Multi-Processing) with the performance which is 10 times faster than the original version and makes it an early-warning storm surge model. In this study, the thorough simulation of 2013 Typhoon Haiyan is performed. The detailed results will be presented in Oceanic Science Meeting of 2016 in terms of surge propagation and high-resolution inundation areas.

  9. Environment, behavior and physiology: do birds use barometric pressure to predict storms?

    Science.gov (United States)

    Breuner, Creagh W; Sprague, Rachel S; Patterson, Stephen H; Woods, H Arthur

    2013-06-01

    Severe storms can pose a grave challenge to the temperature and energy homeostasis of small endothermic vertebrates. Storms are accompanied by lower temperatures and wind, increasing metabolic expenditure, and can inhibit foraging, thereby limiting energy intake. To avoid these potential problems, most endotherms have mechanisms for offsetting the energetic risks posed by storms. One possibility is to use cues to predict oncoming storms and to alter physiology and behavior in ways that make survival more likely. Barometric pressure declines predictably before inclement weather, and several lines of evidence indicate that animals alter behavior based on changes in ambient pressure. Here we examined the effects of declining barometric pressure on physiology and behavior in the white-crowned sparrow, Zonotrichia leucophrys. Using field data from a long-term study, we first evaluated the relationship between barometric pressure, storms and stress physiology in free-living white-crowned sparrows. We then manipulated barometric pressure experimentally in the laboratory and determined how it affects activity, food intake, metabolic rates and stress physiology. The field data showed declining barometric pressure in the 12-24 h preceding snowstorms, but we found no relationship between barometric pressure and stress physiology. The laboratory study showed that declining barometric pressure stimulated food intake, but had no effect on metabolic rate or stress physiology. These data suggest that white-crowned sparrows can sense and respond to declining barometric pressure, and we propose that such an ability may be common in wild vertebrates, especially small ones for whom individual storms can be life-threatening events.

  10. Vulnerability assessment of storm surges in the coastal area of Guangdong Province

    Directory of Open Access Journals (Sweden)

    K. Li

    2011-07-01

    Full Text Available Being bordered by the South China Sea and with long coastline, the coastal zone of Guangdong Province is often under severe risk of storm surges, as one of a few regions in China which is seriously threatened by storm surges. This article systematically analyzes the vulnerability factors of storm surges in the coastal area of Guangdong (from Yangjing to Shanwei. Five vulnerability assessment indicators of hazard-bearing bodies are proposed, which are social economic index, land use index, eco-environmental index, coastal construction index, and disaster-bearing capability index. Then storm surge vulnerability assessment index system in the coastal area of Guangdong is established. Additionally, the international general mode about coastal vulnerability assessment is improved, and the vulnerability evolution model of storm surges in the coastal area of Guangdong is constructed. Using ArcGIS, the vulnerability zoning map of storm surges in the study region is drawn. Results show that there is the highest degree of storm surge vulnerability in Zhuhai, Panyu, and Taishan; second in Zhongshan, Dongguan, Huiyang, and Haifeng; third in Jiangmen, Shanwei, Yangjiang, and Yangdong; fourth in Baoan, Kaiping, and Enping; and lowest in Guangzhou, Shunde, Shenzhen, and Longgang. This study on the risk of storm surges in these coastal cities can guide the land use of coastal cities in the future, and provide scientific advice for the government to prevent and mitigate the storm surge disasters. It has important theoretical and practical significance.

  11. Communicating uncertainty in hydrological forecasts: mission impossible?

    Science.gov (United States)

    Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

    2010-05-01

    Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted

  12. Analysis and simulation of propagule dispersal and salinity intrusion from storm surge on the movement of a marsh–mangrove ecotone in South Florida

    Science.gov (United States)

    Jiang, Jiang; DeAngelis, Donald L.; Anderson, Gordon H.; Smith, Thomas J.

    2014-01-01

    Coastal mangrove–freshwater marsh ecotones of the Everglades represent transitions between marine salt-tolerant halophytic and freshwater salt-intolerant glycophytic communities. It is hypothesized here that a self-reinforcing feedback, termed a “vegetation switch,” between vegetation and soil salinity, helps maintain the sharp mangrove–marsh ecotone. A general theoretical implication of the switch mechanism is that the ecotone will be stable to small disturbances but vulnerable to rapid regime shifts from large disturbances, such as storm surges, which could cause large spatial displacements of the ecotone. We develop a simulation model to describe the vegetation switch mechanism. The model couples vegetation dynamics and hydrologic processes. The key factors in the model are the amount of salt-water intrusion into the freshwater wetland and the passive transport of mangrove (e.g., Rhizophora mangle) viviparous seeds or propagules. Results from the model simulations indicate that a regime shift from freshwater marsh to mangroves is sensitive to the duration of soil salinization through storm surge overwash and to the density of mangrove propagules or seedlings transported into the marsh. We parameterized our model with empirical hydrologic data collected from the period 2000–2010 at one mangrove–marsh ecotone location in southwestern Florida to forecast possible long-term effects of Hurricane Wilma (24 October 2005). The model indicated that the effects of that storm surge were too weak to trigger a regime shift at the sites we studied, 50 km south of the Hurricane Wilma eyewall, but simulations with more severe artificial disturbances were capable of causing substantial regime shifts.

  13. Influence of storm characteristics on soil erosion and storm runoff

    Science.gov (United States)

    Johnny M. III Grace

    2008-01-01

    Unpaved forest roads can be major sources of sediment from forested watersheds. Storm runoff from forest roads are a concern due to their potential delivery of sediments and nutrients to stream systems resulting in degraded water quality. The volume and sediment concentrations of stormwater runoff emanating from forest roads can be greatly influenced by storm...

  14. Thermospheric storms and related ionospheric effects

    International Nuclear Information System (INIS)

    Chandra, S.; Spencer, N.W.

    1976-01-01

    A comparative study of thermospheric storms for the equinox and winter conditions is presented based on the neutral composition measurements from the Aeros-A Nate (Neutral Atmosphere Temperature Experiment) experiment. The main features of the two storms as inferred from the changes in N 2 , Ar, He, and O are described, and their implications to current theories of thermospheric storms are discussed. On the basis of the study of the F region critical frequency measured from a chain of ground-based ionospheric stations during the two storm periods, the general characteristics of the ionospheric storms and the traveling ionospheric disturbances are described. It is suggested that the positive and negative phases of ionospheric storms are the various manifestations of thermospheric storms

  15. Overview of the ARkStorm scenario

    Science.gov (United States)

    Porter, Keith; Wein, Anne; Alpers, Charles N.; Baez, Allan; Barnard, Patrick L.; Carter, James; Corsi, Alessandra; Costner, James; Cox, Dale; Das, Tapash; Dettinger, Mike; Done, James; Eadie, Charles; Eymann, Marcia; Ferris, Justin; Gunturi, Prasad; Hughes, Mimi; Jarrett, Robert; Johnson, Laurie; Le-Griffin, Hanh Dam; Mitchell, David; Morman, Suzette; Neiman, Paul; Olsen, Anna; Perry, Suzanne; Plumlee, Geoffrey; Ralph, Martin; Reynolds, David; Rose, Adam; Schaefer, Kathleen; Serakos, Julie; Siembieda, William; Stock, Jonathan; Strong, David; Wing, Ian Sue; Tang, Alex; Thomas, Pete; Topping, Ken; Wills, Chris; Jones, Lucile

    2011-01-01

    coastal communities. Windspeeds in some places reach 125 miles per hour, hurricane-force winds. Across wider areas of the state, winds reach 60 miles per hour. Hundreds of landslides damage roads, highways, and homes. Property damage exceeds $300 billion, most from flooding. Demand surge (an increase in labor rates and other repair costs after major natural disasters) could increase property losses by 20 percent. Agricultural losses and other costs to repair lifelines, dewater (drain) flooded islands, and repair damage from landslides, brings the total direct property loss to nearly $400 billion, of which $20 to $30 billion would be recoverable through public and commercial insurance. Power, water, sewer, and other lifelines experience damage that takes weeks or months to restore. Flooding evacuation could involve 1.5 million residents in the inland region and delta counties. Business interruption costs reach $325 billion in addition to the $400 property repair costs, meaning that an ARkStorm could cost on the order of $725 billion, which is nearly 3 times the loss deemed to be realistic by the ShakeOut authors for a severe southern California earthquake, an event with roughly the same annual occurrence probability. The ARkStorm has several public policy implications: (1) An ARkStorm raises serious questions about the ability of existing federal, state, and local disaster planning to handle a disaster of this magnitude. (2) A core policy issue raised is whether to pay now to mitigate, or pay a lot more later for recovery. (3) Innovative financing solutions are likely to be needed to avoid fiscal crisis and adequately fund response and recovery costs from a similar, real, disaster. (4) Responders and government managers at all levels could be encouraged to conduct risk assessments, and devise the full spectrum of exercises, to exercise ability of their plans to address a similar event. (5) ARkStorm can be a reference point for application of Federal Emergency Ma

  16. VT Ice Damage Assessment from the 1998 Ice Storm

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) This dataset (ICEDAMAG98) depicts the extent and severity of tree damage caused by the 1998 ice storm, which resulted in extensive tree damage in...

  17. Water demand forecasting: review of soft computing methods.

    Science.gov (United States)

    Ghalehkhondabi, Iman; Ardjmand, Ehsan; Young, William A; Weckman, Gary R

    2017-07-01

    Demand forecasting plays a vital role in resource management for governments and private companies. Considering the scarcity of water and its inherent constraints, demand management and forecasting in this domain are critically important. Several soft computing techniques have been developed over the last few decades for water demand forecasting. This study focuses on soft computing methods of water consumption forecasting published between 2005 and 2015. These methods include artificial neural networks (ANNs), fuzzy and neuro-fuzzy models, support vector machines, metaheuristics, and system dynamics. Furthermore, it was discussed that while in short-term forecasting, ANNs have been superior in many cases, but it is still very difficult to pick a single method as the overall best. According to the literature, various methods and their hybrids are applied to water demand forecasting. However, it seems soft computing has a lot more to contribute to water demand forecasting. These contribution areas include, but are not limited, to various ANN architectures, unsupervised methods, deep learning, various metaheuristics, and ensemble methods. Moreover, it is found that soft computing methods are mainly used for short-term demand forecasting.

  18. Solar cycle effect on geomagnetic storms caused by interplanetary magnetic clouds

    Directory of Open Access Journals (Sweden)

    C.-C. Wu

    2006-12-01

    Full Text Available We investigated geomagnetic activity which was induced by interplanetary magnetic clouds during the past four solar cycles, 1965–1998. We have found that the intensity of such geomagnetic storms is more severe in solar maximum than in solar minimum. In addition, we affirm that the average solar wind speed of magnetic clouds is faster in solar maximum than in solar minimum. In this study, we find that solar activity level plays a major role on the intensity of geomagnetic storms. In particular, some new statistical results are found and listed as follows. (1 The intensity of a geomagnetic storm in a solar active period is stronger than in a solar quiet period. (2 The magnitude of negative Bzmin is larger in a solar active period than in a quiet period. (3 Solar wind speed in an active period is faster than in a quiet period. (4 VBsmax in an active period is much larger than in a quiet period. (5 Solar wind parameters, Bzmin, Vmax and VBsmax are correlated well with geomagnetic storm intensity, Dstmin during a solar active period. (6 Solar wind parameters, Bzmin, and VBsmax are not correlated well (very poorly for Vmax with geomagnetic storm intensity during a solar quiet period. (7 The speed of the solar wind plays a key role in the correlation of solar wind parameters vs. the intensity of a geomagnetic storm. (8 More severe storms with Dstmin≤−100 nT caused by MCs occurred in the solar active period than in the solar quiet period.

  19. Short-term electric load forecasting using computational intelligence methods

    OpenAIRE

    Jurado, Sergio; Peralta, J.; Nebot, Àngela; Mugica, Francisco; Cortez, Paulo

    2013-01-01

    Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce several methods for short-term electric load forecasting. All the presented methods stem from computational intelligence techniques: Random Forest, Nonlinear Autoregressive Neural Networks, Evolutionary Support Vector Machines and Fuzzy Inductive Reasoning. The performance of the suggested methods is experimentally justified with several experiments carried out...

  20. Journal of Earth System Science | Indian Academy of Sciences

    Indian Academy of Sciences (India)

    The accuracy of TC landfall forecast has been analysed with respect to basin of formation (Bay of Bengal, Arabian Sea, and NIO as a whole), specific regions of landfall, season of formation (pre-monsoon and post-monsoon seasons), intensity of TCs (cyclonic storm (CS), and severe cyclonic storm (SCS) or higher ...

  1. Livestock Production in the UK in the 21st Century: A Perfect Storm Averted?

    Directory of Open Access Journals (Sweden)

    Madeleine L. Campbell

    2013-06-01

    Full Text Available There is a school of thought that future demand for meat and other farm animal products is unsustainable for several reasons, including greenhouse gas emissions, especially from ruminants; standards of farm animal health and welfare, especially when farm animals are kept intensively; efficiency of conversion by livestock of solar energy into (human food, particularly by pigs and poultry; water availability and usage for all types of agricultural production, including livestock; and human health and consumption of meat, eggs and milk. Demand for meat is forecast to rise as a result of global population growth and increasing affluence. These issues buttress an impending perfect storm of food shortages, scarce water and insufficient energy, which is likely to coincide with global population reaching about 9 billion people in 2030 (pace Beddington. This paper examines global demand for animal products, the narrative of ‘sustainable intensification’ and the implications of each for the future of farm animal welfare. In the UK, we suggest that, though non-ruminant farming may become unsustainable, ruminant agriculture will continue to prosper because cows, sheep and goats utilize grass and other herbage that cannot be consumed directly by humans, especially on land that is unsuitable for other purposes. However, the demand for meat and other livestock-based food is often for pork, eggs and chicken from grain-fed pigs and poultry. The consequences of such a perfect storm are beginning to be incorporated in long-term business planning by retailers and others. Nevertheless, marketing sustainable animal produce will require considerable innovation and flair in public and private policies if marketing messages are to be optimized and consumer behaviour modified.

  2. Vulnerability Assessment of Dust Storms in the United States under a Changing Climate Scenario

    Science.gov (United States)

    Severe weather events, such as flooding, drought, forest fires, and dust storms can have a serious impact on human health. Dust storm events are not well predicted in the United States, however they are expected to become more frequent as global climate warms through the 21st cen...

  3. Impacts of Storm Surge Mitigation Strategies on Aboveground Storage Tank Chemical Spill Transport

    Science.gov (United States)

    Do, C.; Bass, B. J.; Bernier, C.; Samii, A.; Dawson, C.; Bedient, P. B.

    2017-12-01

    The Houston Ship Channel (HSC), located in the hurricane-prone Houston-Galveston region of the upper Texas Coast, is one of the busiest waterways in the United States and is home to one of the largest petrochemical complexes in the world. Due to the proximity of the HSC to Galveston Bay and the Gulf of Mexico, chemical spills resulting from storm surge damage to aboveground storage tanks (ASTs) pose serious threats to the environment, residential communities, and national/international markets whose activities in the HSC generate billions of dollars annually. In an effort to develop a comprehensive storm surge mitigation strategy for Galveston Bay and its constituents, Rice University's Severe Storm Prediction, Education, and Evacuation from Disasters Center proposed two structural storm surge mitigation concepts, the Mid Bay Structure (MBS) and the Lower Bay Structure (LBS) as components of the Houston-Galveston Area Protection System (H-GAPS) project. The MBS consists of levees along the HSC and a navigational gate across the channel, and the LBS consists of a navigation gate and environmental gates across Bolivar Road. The impacts of these two barrier systems on the fate of AST chemical spills in the HSC have previously been unknown. This study applies the coupled 2D SWAN+ADCIRC model to simulate hurricane storm surge circulation within the Gulf of Mexico and Galveston Bay due to a synthetic storm which results in approximately 250-year surge levels in Galveston Bay. The SWAN+ADCIRC model is run using high-resolution computational meshes that incorporate the MBS and LBS scenarios, separately. The resulting wind and water velocities are then fed into a Lagrangian particle transport model to simulate the spill trajectories of the ASTs most likely to fail during the 250-year proxy storm. Results from this study illustrate how each storm surge mitigation strategy impacts the transport of chemical spills (modeled as Lagrangian particles) during storm surge as

  4. The dual effect of vegetation green-up date and strong wind on the return period of spring dust storms.

    Science.gov (United States)

    Feng, Jieling; Li, Ning; Zhang, Zhengtao; Chen, Xi

    2017-08-15

    Vegetation phenology changes have been widely applied in the disaster risk assessments of the spring dust storms, and vegetation green-up date shifts have a strong influence on dust storms. However, the effect of earlier vegetation green-up dates due to climate warming on the evaluation of dust storms return periods remains an important, but poorly understood issue. In this study, we evaluate the spring dust storm return period (February to June) in Inner Mongolia, Northern China, using 165 observations of severe spring dust storm events from 16 weather stations, and regional vegetation green-up dates as an integrated factor from NDVI (Normalized Difference Vegetation Index), covering a period from 1982 to 2007, by building the bivariate Copula model. We found that the joint return period showed better fitting results than without considering the integrated factor when the actual dust storm return period is longer than 2years. Also, for extremely severe dust storm events, the gap between simulation result and actual return period can be narrowed up to 0.4888years by using integrated factor. Furthermore, the risk map based on the return period results shows that the Mandula, Zhurihe, Sunitezuoqi, Narenbaolige stations are identified as high risk areas. In this study area, land surface is extensively covered by grasses and shrubs, vegetation green-up date can play a significant role in restraining spring dust storm outbreaks. Therefore, we suggest that Copula method can become a useful tool for joint return period evaluation and risk analysis of severe dust storms. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Physics-based Space Weather Forecasting in the Project for Solar-Terrestrial Environment Prediction (PSTEP) in Japan

    Science.gov (United States)

    Kusano, K.

    2016-12-01

    Project for Solar-Terrestrial Environment Prediction (PSTEP) is a Japanese nation-wide research collaboration, which was recently launched. PSTEP aims to develop a synergistic interaction between predictive and scientific studies of the solar-terrestrial environment and to establish the basis for next-generation space weather forecasting using the state-of-the-art observation systems and the physics-based models. For this project, we coordinate the four research groups, which develop (1) the integration of space weather forecast system, (2) the physics-based solar storm prediction, (3) the predictive models of magnetosphere and ionosphere dynamics, and (4) the model of solar cycle activity and its impact on climate, respectively. In this project, we will build the coordinated physics-based model to answer the fundamental questions concerning the onset of solar eruptions and the mechanism for radiation belt dynamics in the Earth's magnetosphere. In this paper, we will show the strategy of PSTEP, and discuss about the role and prospect of the physics-based space weather forecasting system being developed by PSTEP.

  6. Assimilation of extrapolated radar reflectivity into a NWP model and its impact on a precipitation forecast at high resolution

    Czech Academy of Sciences Publication Activity Database

    Sokol, Zbyněk

    2011-01-01

    Roč. 100, 2-3 (2011), s. 201-212 ISSN 0169-8095 R&D Projects: GA ČR GA205/07/0905; GA MŠk ME09033 Institutional research plan: CEZ:AV0Z30420517 Keywords : Precipitation forecast * Nowcasting * Assimilation of radar reflectivity * Numerical weather prediction * Convective storms Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.911, year: 2011 http://www.sciencedirect.com/science/article/pii/S0169809510002462

  7. Perfect storm: Therapeutic plasma exchange for a patient with thyroid storm.

    Science.gov (United States)

    McGonigle, Andrea M; Tobian, Aaron A R; Zink, Jennifer L; King, Karen E

    2018-02-01

    Thyroid storm is a potentially lethal complication of hyperthyroidism with increased thyroid hormones and exaggerated symptoms of thyrotoxicosis. First-line therapy includes methimazole (MMI) or propylthiouracil (PTU) to block production of thyroid hormones as a bridge toward definitive surgical treatment. Untreated thyroid storm has a mortality rate of up to 30%; this is particularly alarming when patients cannot tolerate or fail pharmacotherapy, especially if they cannot undergo thyroidectomy. Therapeutic plasma exchange (TPE) is an ASFA category III indication for thyroid storm, meaning the optimum role of this therapy is not established, and there are a limited number of cases in the literature. Yet TPE can remove T3 and T4 bound to albumin, autoantibodies, catecholamines and cytokines and is likely beneficial for these patients. We report a patient with thyroid storm who could not tolerate PTU, subsequently failed therapy with MMI, and was not appropriate for thyroidectomy. TPE was therefore performed daily for 4 days (1.0 plasma volume with 5% albumin replacement and 2 U of plasma). Over the treatment course, the patient's thyroid hormones normalized and symptoms of thyroid storm largely resolved; his T3 decreased from 2.27 to 0.81 ng/mL (normal 0.8-2.0), T4 decreased from 4.8 to 1.7 ng/mL (0.8-1.8), heart rate normalized, altered mental status improved, and he converted to normal sinus rhythm. He was ultimately discharged in euthyroid state. He experienced no side effects from his TPE procedures. TPE is a safe and effective treatment for thyroid storm when conventional treatments are not successful or appropriate. © 2017 Wiley Periodicals, Inc.

  8. Magnetic Storms at Mars and Earth

    DEFF Research Database (Denmark)

    Vennerstrøm, Susanne; Falkenberg, Thea Vilstrup

    In analogy with magnetic storms at the Earth, periods of significantly enhanced global magnetic activity also exist at Mars. The extensive database of magnetic measurements from Mars Global Surveyor (MGS), covering almost an entire solar cycle, is used in combination with geomagnetic activity...... indices at Earth to compare the occurrence of magnetic storms at Mars and Earth. Based on superposed epochs analysis the time-development of typical magnetic storms at Mars and Earth is described. In contradiction to storms at Earth, most magnetic storms at Mars are found to be associated...... with heliospheric current sheet crossings, where the IMF changes polarity. While most storms at the Earth occur due to significant southward excursions of the IMF associated with CMEs, at Mars most storms seem to be associated with the density enhancement of the heliospheric current sheet. Density enhancements...

  9. Wind forecasting for grid code compliance

    Energy Technology Data Exchange (ETDEWEB)

    Vanitha, V.; Kishore, S.R.N. [Amrita Vishwa Vidyapeetham Univ.. Dept. of Electrical and Electronics Engineering, Coimbatore (India)

    2012-07-01

    This work explores Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to forecast the average hourly wind speed. To determine the characteristics of ANFIS that best suited the target wind speed forecasting system, several ANFIS models were trained, tested and compared. Different types and number of inputs, training and checking sizes, type and number of membership functions and techniques to generate the initial (FIS) were analyzed. Comparisons with other forecasting methods were analyzed the models were given wind speed, direction and air pressure as inputs having the best forecasting accuracy. SCADA system is utilized to obtain the wind speed to the forecasting system in the host computer where ANFIS is present. The SCADA is located in the central room, the substation of the wind farm, or even at a remote off site point. The data obtained from the site is plotted at every instant and the predicted wind speed is displayed and also exported to the excel sheet which will be sent/e-mailed in the form of Graphs and excel sheets to the operator, State load dispatch centre (SLDC) and to the customer. (Author)

  10. Modeling and forecasting petroleum futures volatility

    International Nuclear Information System (INIS)

    Sadorsky, Perry

    2006-01-01

    Forecasts of oil price volatility are important inputs into macroeconometric models, financial market risk assessment calculations like value at risk, and option pricing formulas for futures contracts. This paper uses several different univariate and multivariate statistical models to estimate forecasts of daily volatility in petroleum futures price returns. The out-of-sample forecasts are evaluated using forecast accuracy tests and market timing tests. The TGARCH model fits well for heating oil and natural gas volatility and the GARCH model fits well for crude oil and unleaded gasoline volatility. Simple moving average models seem to fit well in some cases provided the correct order is chosen. Despite the increased complexity, models like state space, vector autoregression and bivariate GARCH do not perform as well as the single equation GARCH model. Most models out perform a random walk and there is evidence of market timing. Parametric and non-parametric value at risk measures are calculated and compared. Non-parametric models outperform the parametric models in terms of number of exceedences in backtests. These results are useful for anyone needing forecasts of petroleum futures volatility. (author)

  11. Multidecadal Scale Detection Time for Potentially Increasing Atlantic Storm Surges in a Warming Climate

    Science.gov (United States)

    Lee, Benjamin Seiyon; Haran, Murali; Keller, Klaus

    2017-10-01

    Storm surges are key drivers of coastal flooding, which generate considerable risks. Strategies to manage these risks can hinge on the ability to (i) project the return periods of extreme storm surges and (ii) detect potential changes in their statistical properties. There are several lines of evidence linking rising global average temperatures and increasingly frequent extreme storm surges. This conclusion is, however, subject to considerable structural uncertainty. This leads to two main questions: What are projections under various plausible statistical models? How long would it take to distinguish among these plausible statistical models? We address these questions by analyzing observed and simulated storm surge data. We find that (1) there is a positive correlation between global mean temperature rise and increasing frequencies of extreme storm surges; (2) there is considerable uncertainty underlying the strength of this relationship; and (3) if the frequency of storm surges is increasing, this increase can be detected within a multidecadal timescale (≈20 years from now).

  12. Objective Lightning Probability Forecasts for East-Central Florida Airports

    Science.gov (United States)

    Crawford, Winfred C.

    2013-01-01

    The forecasters at the National Weather Service in Melbourne, FL, (NWS MLB) identified a need to make more accurate lightning forecasts to help alleviate delays due to thunderstorms in the vicinity of several commercial airports in central Florida at which they are responsible for issuing terminal aerodrome forecasts. Such forecasts would also provide safer ground operations around terminals, and would be of value to Center Weather Service Units serving air traffic controllers in Florida. To improve the forecast, the AMU was tasked to develop an objective lightning probability forecast tool for the airports using data from the National Lightning Detection Network (NLDN). The resulting forecast tool is similar to that developed by the AMU to support space launch operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) for use by the 45th Weather Squadron (45 WS) in previous tasks (Lambert and Wheeler 2005, Lambert 2007). The lightning probability forecasts are valid for the time periods and areas needed by the NWS MLB forecasters in the warm season months, defined in this task as May-September.

  13. Forecast Combinations

    OpenAIRE

    Timmermann, Allan G

    2005-01-01

    Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex-ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal combination weights. In this paper we analyse theoretically the factors that determine the advantages from combining forecasts (for example, the d...

  14. Forecaster Behaviour and Bias in Macroeconomic Forecasts

    OpenAIRE

    Roy Batchelor

    2007-01-01

    This paper documents the presence of systematic bias in the real GDP and inflation forecasts of private sector forecasters in the G7 economies in the years 1990–2005. The data come from the monthly Consensus Economics forecasting service, and bias is measured and tested for significance using parametric fixed effect panel regressions and nonparametric tests on accuracy ranks. We examine patterns across countries and forecasters to establish whether the bias reflects the inefficient use of i...

  15. European extra-tropical storm damage risk from a multi-model ensemble of dynamically-downscaled global climate models

    Science.gov (United States)

    Haylock, M. R.

    2011-10-01

    Uncertainty in the return levels of insured loss from European wind storms was quantified using storms derived from twenty-two 25 km regional climate model runs driven by either the ERA40 reanalyses or one of four coupled atmosphere-ocean global climate models. Storms were identified using a model-dependent storm severity index based on daily maximum 10 m wind speed. The wind speed from each model was calibrated to a set of 7 km historical storm wind fields using the 70 storms with the highest severity index in the period 1961-2000, employing a two stage calibration methodology. First, the 25 km daily maximum wind speed was downscaled to the 7 km historical model grid using the 7 km surface roughness length and orography, also adopting an empirical gust parameterisation. Secondly, downscaled wind gusts were statistically scaled to the historical storms to match the geographically-dependent cumulative distribution function of wind gust speed. The calibrated wind fields were run through an operational catastrophe reinsurance risk model to determine the return level of loss to a European population density-derived property portfolio. The risk model produced a 50-yr return level of loss of between 0.025% and 0.056% of the total insured value of the portfolio.

  16. European extra-tropical storm damage risk from a multi-model ensemble of dynamically-downscaled global climate models

    Directory of Open Access Journals (Sweden)

    M. R. Haylock

    2011-10-01

    Full Text Available Uncertainty in the return levels of insured loss from European wind storms was quantified using storms derived from twenty-two 25 km regional climate model runs driven by either the ERA40 reanalyses or one of four coupled atmosphere-ocean global climate models. Storms were identified using a model-dependent storm severity index based on daily maximum 10 m wind speed. The wind speed from each model was calibrated to a set of 7 km historical storm wind fields using the 70 storms with the highest severity index in the period 1961–2000, employing a two stage calibration methodology. First, the 25 km daily maximum wind speed was downscaled to the 7 km historical model grid using the 7 km surface roughness length and orography, also adopting an empirical gust parameterisation. Secondly, downscaled wind gusts were statistically scaled to the historical storms to match the geographically-dependent cumulative distribution function of wind gust speed.

    The calibrated wind fields were run through an operational catastrophe reinsurance risk model to determine the return level of loss to a European population density-derived property portfolio. The risk model produced a 50-yr return level of loss of between 0.025% and 0.056% of the total insured value of the portfolio.

  17. Martian dust storms as a possible sink of atmospheric methane

    Science.gov (United States)

    Farrell, W. M.; Delory, G. T.; Atreya, S. K.

    2006-11-01

    Recent laboratory tests, analog studies and numerical simulations all suggest that Martian dust devils and larger dusty convective storms generate and maintain large-scale electric fields. Such expected E-fields will have the capability to create significant electron drift motion in the collisional gas and to form an extended high energy (u $\\gg$ kT) electron tail in the distribution. We demonstrate herein that these energetic electrons are capable of dissociating any trace CH4 in the ambient atmosphere thereby acting as an atmospheric sink of this important gas. We demonstrate that the methane destruction rate increases by a factor of 1012 as the dust storm E-fields, E, increase from 5 to 25 kV/m, resulting in an apparent decrease in methane stability from ~ 1010 sec to a value of ~1000 seconds. While destruction in dust storms is severe, the overall methane lifetime is expected to decrease only moderately due to recycling of products, heterogeneous effects from localized sinks, etc. We show further evidence that the electrical activity anticipated in Martian dust storms creates a new harsh electro-chemical environment.

  18. Lightning mapping and dual-polarization radar observations of electrified storms at Langmuir Laboratory

    Science.gov (United States)

    Krehbiel, P. R.; Hyland, P. T.; Edens, H. E.; Rison, W.

    2013-12-01

    Observations being made at Langmuir Laboratory with the NM Tech Lightning Mapping Array (LMA) and the University of Oklahoma ARRC PX-1000 dual polarization X-band radar strongly confirm and expand upon the normal polarity tripolar electrical structure of central New Mexico storms. This is in sharp contrast with the anomalously electrified storm structures observed in northern Colorado during and subsequent to the 2012 DC3 field campaign, as seen with North Colorado LMA and CSU CHILL dual-polarization radar observations. In this presentation we focus on the New Mexico observations, and several modes in which the tripolar structure appears initially to develop and evolve with time. Central New Mexico storms are often prolific producers of negative cloud-to-ground (CG) flashes, but rarely produce positive CGs. By contrast, many or most north Colorado storms are CG-deficient, with the relatively few CG discharges being of predominantly positive polarity. In addition, NM storms commonly produce bolt-from-the-blue (BFB) negative CGs, whereas anomalously electrified Colorado storms produce none. The occurrence of BFBs is indicative of a relatively weak lower positive charge region, while the occurrence of normal downward -CGs is indicative of a somewhat stronger lower positive charge. The lack of -CGs in Colorado storms results from lower positive charge being a dominant storm charge that is elevated in altitude. These and other basic features of the electrically activity of storms, coupled with dual polarization and Doppler radar observations of hydrometeor types and motions, are leading to a better understanding of the storm electrification processes.

  19. Relationship between substorms and storms

    International Nuclear Information System (INIS)

    Kamide, Y.

    1980-01-01

    In an attempt to deduce a plausible working model of the relationship between magnetospheric substorms and storms, recent relevant studies of various processes occurring during disturbed periods are integrated along with some theoretical suggestions. It has been shown that the main phase of geomagnetic storms is associated with the successive occurrence of intense substorms and with the sustained southward component of the interplanetary magnetic field (IMF). However, these relations are only qualitatively understood, and thus basic questions remain unanswered involving the hypothesis whether a magnetic storm is a non-linear (or linear) superposition of intense substorms, each of which constitutes an elementary storm, or the main phase of magnetic storms occurs as a result of the intense southward IMF which enhances magnetospheric convection and increases occurrence probability of substorms. (Auth.)

  20. Forecast combinations

    OpenAIRE

    Aiolfi, Marco; Capistrán, Carlos; Timmermann, Allan

    2010-01-01

    We consider combinations of subjective survey forecasts and model-based forecasts from linear and non-linear univariate specifications as well as multivariate factor-augmented models. Empirical results suggest that a simple equal-weighted average of survey forecasts outperform the best model-based forecasts for a majority of macroeconomic variables and forecast horizons. Additional improvements can in some cases be gained by using a simple equal-weighted average of survey and model-based fore...

  1. In Brief: Forecasting meningitis threats

    Science.gov (United States)

    Showstack, Randy

    2008-12-01

    The University Corporation for Atmospheric Research (UCAR), in conjunction with a team of health and weather organizations, has launched a project to provide weather forecasts to medical officials in Africa to help reduce outbreaks of meningitis. The forecasts will enable local health care providers to target vaccination programs more effectively. In 2009, meteorologists with the National Center for Atmospheric Research, which is managed by UCAR, will begin issuing 14-day forecasts of atmospheric conditions in Ghana. Later, UCAR plans to work closely with health experts from several African countries to design and test a decision support system to provide health officials with useful meteorological information. ``By targeting forecasts in regions where meningitis is a threat, we may be able to help vulnerable populations. Ultimately, we hope to build on this project and provide information to public health programs battling weather-related diseases in other parts of the world,'' said Rajul Pandya, director of UCAR's Community Building Program. Funding for the project comes from a $900,000 grant from Google.org, the philanthropic arm of the Internet search company.

  2. Vulnerability of Amazon forests to storm-driven tree mortality

    Science.gov (United States)

    Negrón-Juárez, Robinson I.; Holm, Jennifer A.; Magnabosco Marra, Daniel; Rifai, Sami W.; Riley, William J.; Chambers, Jeffrey Q.; Koven, Charles D.; Knox, Ryan G.; McGroddy, Megan E.; Di Vittorio, Alan V.; Urquiza-Muñoz, Jose; Tello-Espinoza, Rodil; Alegria Muñoz, Waldemar; Ribeiro, Gabriel H. P. M.; Higuchi, Niro

    2018-05-01

    Tree mortality is a key driver of forest community composition and carbon dynamics. Strong winds associated with severe convective storms are dominant natural drivers of tree mortality in the Amazon. Why forests vary with respect to their vulnerability to wind events and how the predicted increase in storm events might affect forest ecosystems within the Amazon are not well understood. We found that windthrows are common in the Amazon region extending from northwest (Peru, Colombia, Venezuela, and west Brazil) to central Brazil, with the highest occurrence of windthrows in the northwest Amazon. More frequent winds, produced by more frequent severe convective systems, in combination with well-known processes that limit the anchoring of trees in the soil, help to explain the higher vulnerability of the northwest Amazon forests to winds. Projected increases in the frequency and intensity of convective storms in the Amazon have the potential to increase wind-related tree mortality. A forest demographic model calibrated for the northwestern and the central Amazon showed that northwestern forests are more resilient to increased wind-related tree mortality than forests in the central Amazon. Our study emphasizes the importance of including wind-related tree mortality in model simulations for reliable predictions of the future of tropical forests and their effects on the Earth’ system.

  3. Probabilistic storm surge inundation maps for Metro Manila based on Philippine public storm warning signals

    Science.gov (United States)

    Tablazon, J.; Caro, C. V.; Lagmay, A. M. F.; Briones, J. B. L.; Dasallas, L.; Lapidez, J. P.; Santiago, J.; Suarez, J. K.; Ladiero, C.; Gonzalo, L. A.; Mungcal, M. T. F.; Malano, V.

    2015-03-01

    A storm surge is the sudden rise of sea water over the astronomical tides, generated by an approaching storm. This event poses a major threat to the Philippine coastal areas, as manifested by Typhoon Haiyan on 8 November 2013. This hydro-meteorological hazard is one of the main reasons for the high number of casualties due to the typhoon, with 6300 deaths. It became evident that the need to develop a storm surge inundation map is of utmost importance. To develop these maps, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. The Japan Meteorological Agency storm surge model was used to simulate storm surge heights. The frequency distribution of the maximum storm surge heights was calculated using simulation results of tropical cyclones under a specific public storm warning signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of inundation for a specific PSWS using the probability of exceedance derived from the frequency distribution. Buildings and other structures were assigned a probability of exceedance depending on their occupancy category, i.e., 1% probability of exceedance for critical facilities, 10% probability of exceedance for special occupancy structures, and 25% for standard occupancy and miscellaneous structures. The maps produced show the storm-surge-vulnerable areas in Metro Manila, illustrated by the flood depth of up to 4 m and extent of up to 6.5 km from the coastline. This information can help local government units in developing early warning systems, disaster preparedness and mitigation plans, vulnerability assessments, risk-sensitive land use plans, shoreline

  4. NCDC Storm Events Database

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Storm Data is provided by the National Weather Service (NWS) and contain statistics on personal injuries and damage estimates. Storm Data covers the United States of...

  5. Wind field measurement in the nonprecipitous regions surrounding storms by an airborne pulsed Doppler lidar system, appendix A

    Science.gov (United States)

    Bilbro, J. W.; Vaughan, W. W.

    1980-01-01

    Coherent Doppler lidar appears to hold great promise in contributing to the basic store of knowledge concerning flow field characteristics in the nonprecipitous regions surrounding severe storms. The Doppler lidar, through its ability to measure clear air returns, augments the conventional Doppler radar system, which is most useful in the precipitous regions of the storm. A brief description of the Doppler lidar severe storm measurement system is provided along with the technique to be used in performing the flow field measurements. The application of the lidar is addressed, and the planned measurement program is outlined.

  6. Do probabilistic forecasts lead to better decisions?

    Directory of Open Access Journals (Sweden)

    M. H. Ramos

    2013-06-01

    Full Text Available The last decade has seen growing research in producing probabilistic hydro-meteorological forecasts and increasing their reliability. This followed the promise that, supplied with information about uncertainty, people would take better risk-based decisions. In recent years, therefore, research and operational developments have also started focusing attention on ways of communicating the probabilistic forecasts to decision-makers. Communicating probabilistic forecasts includes preparing tools and products for visualisation, but also requires understanding how decision-makers perceive and use uncertainty information in real time. At the EGU General Assembly 2012, we conducted a laboratory-style experiment in which several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision-makers. Answers were collected and analysed. In this paper, we present the results of this exercise and discuss if we indeed make better decisions on the basis of probabilistic forecasts.

  7. Effects of storm waves on rapid deposition of sediment in the Yangtze Estuary channel

    Directory of Open Access Journals (Sweden)

    Xu Fumin

    2008-03-01

    Full Text Available Recent research on short-term topographic change in the Yangtze Estuary channel under storm surge conditions is briefly summarized. The mild-slope, Boussinesq and action balance equations are compared and analyzed. The action balance equation, SWAN, was used as a wave numerical model to forecast strong storm waves in the Yangtze Estuary. The spherical coordinate system and source terms used in the equation are described in this paper. The significant wave height and the wave orbital motion velocity near the bottom of the channel during 20 m/s winds in the EES direction were simulated, and the model was calibrated with observation data of winds and waves generated by Tropical Cyclone 9912. The distribution of critical velocity for incipient motion along the bottom was computed according to the threshold velocity formula for bottom sediment. The mechanism of rapid deposition is analyzed based on the difference between the root-mean-square value of the near-bottom wave orbital motion velocity and the bottom critical tractive velocity. The results show that a large amount of bottom sediments from Hengsha Shoal and Jiuduan Shoal are lifted into the water body when 20 m/s wind is blowing in the EES direction. Some of the sediments may enter the channel with the cross-channel current, causing serious rapid deposition. Finally, the tendency of the storm to induce rapid deposition in the Yangtze Estuary channel zone is analyzed.

  8. Action-based flood forecasting for triggering humanitarian action

    Science.gov (United States)

    Coughlan de Perez, Erin; van den Hurk, Bart; van Aalst, Maarten K.; Amuron, Irene; Bamanya, Deus; Hauser, Tristan; Jongma, Brenden; Lopez, Ana; Mason, Simon; Mendler de Suarez, Janot; Pappenberger, Florian; Rueth, Alexandra; Stephens, Elisabeth; Suarez, Pablo; Wagemaker, Jurjen; Zsoter, Ervin

    2016-09-01

    Too often, credible scientific early warning information of increased disaster risk does not result in humanitarian action. With financial resources tilted heavily towards response after a disaster, disaster managers have limited incentive and ability to process complex scientific data, including uncertainties. These incentives are beginning to change, with the advent of several new forecast-based financing systems that provide funding based on a forecast of an extreme event. Given the changing landscape, here we demonstrate a method to select and use appropriate forecasts for specific humanitarian disaster prevention actions, even in a data-scarce location. This action-based forecasting methodology takes into account the parameters of each action, such as action lifetime, when verifying a forecast. Forecasts are linked with action based on an understanding of (1) the magnitude of previous flooding events and (2) the willingness to act "in vain" for specific actions. This is applied in the context of the Uganda Red Cross Society forecast-based financing pilot project, with forecasts from the Global Flood Awareness System (GloFAS). Using this method, we define the "danger level" of flooding, and we select the probabilistic forecast triggers that are appropriate for specific actions. Results from this methodology can be applied globally across hazards and fed into a financing system that ensures that automatic, pre-funded early action will be triggered by forecasts.

  9. New watershed-based climate forecast products for hydrologists and water managers

    Science.gov (United States)

    Baker, S. A.; Wood, A.; Rajagopalan, B.; Lehner, F.; Peng, P.; Ray, A. J.; Barsugli, J. J.; Werner, K.

    2017-12-01

    Operational sub-seasonal to seasonal (S2S) climate predictions have advanced in skill in recent years but are yet to be broadly utilized by stakeholders in the water management sector. While some of the challenges that relate to fundamental predictability are difficult or impossible to surmount, other hurdles related to forecast product formulation, translation, relevance, and accessibility can be directly addressed. These include products being misaligned with users' space-time needs, products disseminated in formats users cannot easily process, and products based on raw model outputs that are biased relative to user climatologies. In each of these areas, more can be done to bridge the gap by enhancing the usability, quality, and relevance of water-oriented predictions. In addition, water stakeholder impacts can benefit from short-range extremes predictions (such as 2-3 day storms or 1-week heat waves) at S2S time-scales, for which few products exist. We present interim results of a Research to Operations (R2O) effort sponsored by the NOAA MAPP Climate Testbed to (1) formulate climate prediction products so as to reduce hurdles to in water stakeholder adoption, and to (2) explore opportunities for extremes prediction at S2S time scales. The project is currently using CFSv2 and National Multi-­Model Ensemble (NMME) reforecasts and forecasts to develop real-time watershed-based climate forecast products, and to train post-processing approaches to enhance the skill and reliability of raw real-time S2S forecasts. Prototype S2S climate data products (forecasts and associated skill analyses) are now being operationally staged at NCAR on a public website to facilitate further product development through interactions with water managers. Initial demonstration products include CFSv2-based bi-weekly climate forecasts (weeks 1-2, 2-3, and 3-4) for sub-regional scale hydrologic units, and NMME-based monthly and seasonal prediction products. Raw model mean skill at these time

  10. Responses of Hail and Storm Days to Climate Change in the Tibetan Plateau

    Science.gov (United States)

    Zou, Tian; Zhang, Qinghong; Li, Wenhong; Li, Jihong

    2018-05-01

    There is increasing concern that local severe storm occurrence may be changing as a result of climate change. The Tibetan Plateau (TP), one of the world's most sensitive areas to climate change, became significantly warmer during recent decades. Since 1960 (1980), storm (hail) days have been decreasing by 6.2%/decade (18.3%/decade) in the region. However, what caused the frequency changes of storm and hail in the TP is largely unknown. Based on 53-year continuous weather records at 48 TP stations and reanalysis data, we show here for the first time that the consistent decline of storm days is strongly related to a drier midtroposphere since 1960. Further analysis demonstrated that fewer hail days are driven by an elevation of the melting level (thermodynamically) and a weaker wind shear (dynamically) in a warming climate. These results imply that less storm and hail may occur over TP when climate warms.

  11. Prediction of geomagnetic storm using neural networks: Comparison of the efficiency of the Satellite and ground-based input parameters

    International Nuclear Information System (INIS)

    Stepanova, Marina; Antonova, Elizavieta; Munos-Uribe, F A; Gordo, S L Gomez; Torres-Sanchez, M V

    2008-01-01

    Different kinds of neural networks have established themselves as an effective tool in the prediction of different geomagnetic indices, including the Dst being the most important constituent for determination of the impact of Space Weather on the human life. Feed-forward networks with one hidden layer are used to forecast the Dst variation, using separately the solar wind paramenters, polar cap index, and auroral electrojet index as input parameters. It was found that in all three cases the storm-time intervals were predicted much more precisely as quite time intervals. The majority of cross-correlation coefficients between predicted and observed Dst of strong geomagnetic storms are situated between 0.8 and 0.9. Changes in the neural network architecture, including the number of nodes in the input and hidden layers and the transfer functions between them lead to an improvement of a network performance up to 10%.

  12. Predicting the occurrence of super-storms

    Directory of Open Access Journals (Sweden)

    N. Srivastava

    2005-11-01

    Full Text Available A comparative study of five super-storms (Dst<-300 nT of the current solar cycle after the launch of SoHO, to identify solar and interplanetary variables that influence the magnitude of resulting geomagnetic storms, is described. Amongst solar variables, the initial speed of a CME is considered the most reliable predictor of the strength of the associated geomagnetic storm because fast mass ejections are responsible for building up the ram pressure at the Earth's magnetosphere. However, although most of the super-storms studied were associated with high speed CMEs, the Dst index of the resulting geomagnetic storms varied between -300 to -472 nT. The most intense storm of 20 November 2003, (Dst ~ -472 nT had its source in a comparatively smaller active region and was associated with a relatively weaker, M-class flare while all other super-storms had their origins in large active regions and were associated with strong X-class flares. However, this superstorm did not show any associated extraordinary solar and interplanetary characteristics. The study also reveals the challenge in the reliable prediction of the magnitude of a geomagnetic storm from solar and interplanetary variables.

  13. Nest mortality of sagebrush songbirds due to a severe hailstorm

    Science.gov (United States)

    Hightower, Jessica N.; Carlisle, Jason D.; Chalfoun, Anna D.

    2018-01-01

    Demographic assessments of nesting birds typically focus on failures due to nest predation or brood parasitism. Extreme weather events such as hailstorms, however, can also destroy eggs and injure or kill juvenile and adult birds at the nest. We documented the effects of a severe hailstorm on 3 species of sagebrush-associated songbirds: Sage Thrasher (Oreoscoptes montanus), Brewer's Sparrow (Spizella breweri), and Vesper Sparrow (Pooecetes gramineus), nesting at eight 24 ha study plots in central Wyoming, USA. Across all plots, 17% of 128 nests failed due to the hailstorm; however, all failed nests were located at a subset of study plots (n = 3) where the hailstorm was most intense, and 45% of all nests failures on those plots were due to hail. Mortality rates varied by species, nest architecture, and nest placement. Nests with more robust architecture and those sited more deeply under the shrub canopy were more likely to survive the hailstorm, suggesting that natural history traits may modulate mortality risk due to hailstorms. While sporadic in nature, hailstorms may represent a significant source of nest failure to songbirds in certain locations, especially with increasing storm frequency and severity forecasted in some regions with ongoing climate change.

  14. Evaluation of the STORM model storm-time corrections for middle latitude

    Czech Academy of Sciences Publication Activity Database

    Burešová, Dalia; McKinnell, L.- A.; Šindelářová, Tereza; de la Morena, B. A.

    2010-01-01

    Roč. 46, č. 8 (2010), s. 1039-1046 ISSN 0273-1177 R&D Projects: GA ČR GA205/08/1356; GA AV ČR 1QS300120506 Institutional research plan: CEZ:AV0Z30420517 Keywords : Ionosphere * Geomagnetic storms * STORM model * International Reference Ionosphere (IRI) Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.076, year: 2010

  15. Teaching ocean wave forecasting using computer-generated visualization and animation—Part 1: sea forecasting

    Science.gov (United States)

    Whitford, Dennis J.

    2002-05-01

    Ocean waves are the most recognized phenomena in oceanography. Unfortunately, undergraduate study of ocean wave dynamics and forecasting involves mathematics and physics and therefore can pose difficulties with some students because of the subject's interrelated dependence on time and space. Verbal descriptions and two-dimensional illustrations are often insufficient for student comprehension. Computer-generated visualization and animation offer a visually intuitive and pedagogically sound medium to present geoscience, yet there are very few oceanographic examples. A two-part article series is offered to explain ocean wave forecasting using computer-generated visualization and animation. This paper, Part 1, addresses forecasting of sea wave conditions and serves as the basis for the more difficult topic of swell wave forecasting addressed in Part 2. Computer-aided visualization and animation, accompanied by oral explanation, are a welcome pedagogical supplement to more traditional methods of instruction. In this article, several MATLAB ® software programs have been written to visualize and animate development and comparison of wave spectra, wave interference, and forecasting of sea conditions. These programs also set the stage for the more advanced and difficult animation topics in Part 2. The programs are user-friendly, interactive, easy to modify, and developed as instructional tools. By using these software programs, teachers can enhance their instruction of these topics with colorful visualizations and animation without requiring an extensive background in computer programming.

  16. Assessing storm events for energy meteorology: using media and scientific reports to track a North Sea autumn storm.

    Science.gov (United States)

    Kettle, Anthony

    2016-04-01

    issuing authority, these reports include wind speed and atmospheric pressure for a number of stations. However, there is also important ancillary information that includes satellite images, weather radar pictures, sea state recordings, tide gauge records, and coastal surveys. When collated together, the literature survey gives good view of events related to the autumn storm. The key information from media reports is backed up by quantitative numbers from the scientific literature. For energy meteorology in the offshore environment, there is an outline of extreme wave events that may be important to help define the ultimate limit state of engineering structures and the return periods of extreme waves. While this contribution focusses on events from an old storm in the autumn of 2006, more severe regional storms have occurred since then, and the scientific literature indicates that these may be linked with climate warming. Literature surveys may help to fully define extreme meteorological conditions offshore and benefit different branches of the energy industry in Europe.

  17. Skill forecasting from ensemble predictions of wind power

    DEFF Research Database (Denmark)

    Pinson, Pierre; Nielsen, Henrik Aalborg; Madsen, Henrik

    2009-01-01

    Optimal management and trading of wind generation calls for the providing of uncertainty estimates along with the commonly provided short-term wind power point predictions. Alternative approaches for the use of probabilistic forecasting are introduced. More precisely, focus is given to prediction...... risk indices aiming to give a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the spread of ensemble forecasts (i.e. a set...... of alternative scenarios for the coming period) for a single prediction horizon or over a took-ahead period. It is shown on the test case of a Danish offshore wind farm how these prediction risk indices may be related to several levels of forecast uncertainty (and potential energy imbalances). Wind power...

  18. Geomagnetic storms in the Antarctic F-region

    International Nuclear Information System (INIS)

    Wrenn, G.L.; Rodger, A.S.; Rishbeth, H.

    1987-01-01

    New analysis procedures are used to show that the main phase mid-latitude storm effects conform to consistent patterns in local time when suitable selection rules are applied, with averaging over several years. Changes in the maximum plasma frequency, foF2, with respect to estimated quiet-time values, are analysed in terms of asub(p)(t), a new geomagnetic index derived to take account of integrated disturbance. Reduction of foF2 is greatest during the early morning hours, in summer, at higher geomagnetic latitudes, near solar minimum and through the more active periods. The various dependencies are quantitatively determined for the first time by creating an average 'steady state' disturbance, rather than following specific storm events. This approach permits tests of competing theories using available modelling programs. (author)

  19. Geomagnetic storms

    International Nuclear Information System (INIS)

    McNamara, A.G.

    1980-01-01

    Disturbances due to geomagnetic storms can affect the functioning of communications satellites and of power lines and other long conductors. Two general classes of geomagnetic activity can be distinguished: ionospheric current flow (the auroral electrojet), and magnetospheric compression. Super magnetic storms, such as the one of August 1972, can occur at any time and average about 17 occurrences per century. Electrical transmission systems can be made more tolerant of such events at a price, but the most effective way to minimize damage is by better operator training coupled with effective early warning systems. (LL)

  20. Measuring storm tide and high-water marks caused by Hurricane Sandy in New York: Chapter 2

    Science.gov (United States)

    Simonson, Amy E.; Behrens, Riley

    2015-01-01

    In response to Hurricane Sandy, personnel from the U.S. Geological Survey (USGS) deployed a temporary network of storm-tide sensors from Virginia to Maine. During the storm, real-time water levels were available from tide gages and rapid-deployment gages (RDGs). After the storm, USGS scientists retrieved the storm-tide sensors and RDGs and surveyed high-water marks. These data demonstrate that the timing of peak storm surge relative to astronomical tide was extremely important in southeastern New York. For example, along the south shores of New York City and western Suffolk County, the peak storm surge of 6–9 ft generally coincided with the astronomical high tide, which resulted in substantial coastal flooding. In the Peconic Estuary and northern Nassau County, however, the peak storm surge of 9 ft and nearly 12 ft, respectively, nearly coincided with normal low tide, which helped spare these communities from more severe coastal flooding.

  1. ARkStorm@Tahoe: Stakeholder perspectives on vulnerabilities and preparedness for an extreme storm event in the greater Lake Tahoe, Reno, and Carson City region

    Science.gov (United States)

    Albano, Christine M.; Cox, Dale A.; Dettinger, Michael; Shaller, Kevin; Welborn, Toby L.; McCarthy, Maureen

    2014-01-01

    coordination, credentialing, flood management, and coordination of health and human services during such an event. Mitigation options were identified for each of the key issues. Several science needs were identified, particularly the need for improved flood inundation maps. Finally, key lessons learned were identified and may help to increase preparedness, response and recovery from extreme storms in the future.

  2. A Short-term ESPERTA-based Forecast Tool for Moderate-to-extreme Solar Proton Events

    Science.gov (United States)

    Laurenza, M.; Alberti, T.; Cliver, E. W.

    2018-04-01

    The ESPERTA (Empirical model for Solar Proton Event Real Time Alert) forecast tool has a Probability of Detection (POD) of 63% for all >10 MeV events with proton peak intensity ≥10 pfu (i.e., ≥S1 events, S1 referring to minor storms on the NOAA Solar Radiation Storms scale), from 1995 to 2014 with a false alarm rate (FAR) of 38% and a median (minimum) warning time (WT) of ∼4.8 (0.4) hr. The NOAA space weather scale includes four additional categories: moderate (S2), strong (S3), severe (S4), and extreme (S5). As S1 events have only minor impacts on HF radio propagation in the polar regions, the effective threshold for significant space radiation effects appears to be the S2 level (100 pfu), above which both biological and space operation impacts are observed along with increased effects on HF propagation in the polar regions. We modified the ESPERTA model to predict ≥S2 events and obtained a POD of 75% (41/55) and an FAR of 24% (13/54) for the 1995–2014 interval with a median (minimum) WT of ∼1.7 (0.2) hr based on predictions made at the time of the S1 threshold crossing. The improved performance of ESPERTA for ≥S2 events is a reflection of the big flare syndrome, which postulates that the measures of the various manifestations of eruptive solar flares increase as one considers increasingly larger events.

  3. Sharing wind power forecasts in electricity markets: A numerical analysis

    DEFF Research Database (Denmark)

    Exizidis, Lazaros; Pinson, Pierre; Kazempour, Jalal

    2016-01-01

    In an electricity pool with significant share of wind power, all generators including conventional and wind power units are generally scheduled in a day-ahead market based on wind power forecasts. Then, a real-time market is cleared given the updated wind power forecast and fixed day......-ahead decisions to adjust power imbalances. This sequential market-clearing process may cope with serious operational challenges such as severe power shortage in real-time due to erroneous wind power forecasts in day-ahead market. To overcome such situations, several solutions can be considered such as adding...... flexible resources to the system. In this paper, we address another potential solution based on information sharing in which market players share their own wind power forecasts with others in day-ahead market. This solution may improve the functioning of sequential market-clearing process through making...

  4. The postsunset vertical plasma drift during geomagnetic storms and its effects on the generation of equatorial spread F

    Science.gov (United States)

    Huang, C.

    2017-12-01

    We will present two distinct phenomena related to the postsunset vertical plasma drift and equatorial spread F (ESF) observed by the Communication/Navigation Outage Forecasting System satellite over six years. The first phenomenon is the behavior of the prereversal enhancement (PRE) of the vertical plasma drift during geomagnetic storms. Statistically, storm-time disturbance dynamo electric fields cause the PRE to decrease from 30 to 0 m/s when Dst changes from -60 to -100 nT, but the PRE does not show obvious variations when Dst varies from 0 to -60 nT. The observations show that the storm activities affect the evening equatorial ionosphere only for Dst correlated with the PRE and that the occurrence of small-amplitude ESF irregularities does not show a clear pattern at low solar activity but is anti-correlated with large-amplitude irregularities and the PRE at moderate solar activity. That is, the months and longitudes with high occurrence probability of large-amplitude irregularities are exactly those with low occurrence probability of small-amplitude irregularities, and vice versa. The generation of large-amplitude ESF irregularities is controlled by the PRE, and the generation of small-amplitude ESF irregularities may be caused by gravity waves and other disturbances, rather than by the PRE.

  5. Profiling Radar Observations and Numerical Simulations of a Downslope Wind Storm and Rotor on the Lee of the Medicine Bow Mountains in Wyoming

    Directory of Open Access Journals (Sweden)

    Binod Pokharel

    2017-02-01

    Full Text Available This study describes a downslope wind storm event observed over the Medicine Bow range (Wyoming, USA on 11 January 2013. The University of Wyoming King Air (UWKA made four along-wind passes over a five-hour period over the mountain of interest. These passes were recognized as among the most turbulent ones encountered in many years by crew members. The MacCready turbulence meter aboard the UWKA measured moderate to severe turbulence conditions on each pass in the lee of the mountain range, with eddy dissipation rate values over 0.5 m2/3 s−1. Three rawinsondes were released from an upstream location at different times. This event is simulated using the non-hydrostatic Weather Research and Forecast (WRF model at an inner- domain resolution of 1 km. The model produces a downslope wind storm, notwithstanding some discrepancies between model and rawinsonde data in terms of upstream atmospheric conditions. Airborne Wyoming Cloud Radar (WCR vertical-plane Doppler velocity data from two beams, one pointing to the nadir and one pointing slant forward, are synthesized to obtain a two-dimensional velocity field in the vertical plane below flight level. This synthesis reveals the fine-scale details of an orographic wave breaking event, including strong, persistent downslope acceleration, a strong leeside updraft (up to 10 m·s−1 flanked by counter-rotating vortices, and deep turbulence, extending well above flight level. The analysis of WCR-derived cross-mountain flow in 19 winter storms over the same mountain reveals that cross-mountain flow acceleration and downslope wind formation are difficult to predict from upstream wind and stability profiles.

  6. Predicting the occurrence of super-storms

    Directory of Open Access Journals (Sweden)

    N. Srivastava

    2005-11-01

    Full Text Available A comparative study of five super-storms (Dst<-300 nT of the current solar cycle after the launch of SoHO, to identify solar and interplanetary variables that influence the magnitude of resulting geomagnetic storms, is described. Amongst solar variables, the initial speed of a CME is considered the most reliable predictor of the strength of the associated geomagnetic storm because fast mass ejections are responsible for building up the ram pressure at the Earth's magnetosphere. However, although most of the super-storms studied were associated with high speed CMEs, the Dst index of the resulting geomagnetic storms varied between -300 to -472 nT. The most intense storm of 20 November 2003, (Dst ~ -472 nT had its source in a comparatively smaller active region and was associated with a relatively weaker, M-class flare while all other super-storms had their origins in large active regions and were associated with strong X-class flares. However, this superstorm did not show any associated extraordinary solar and interplanetary characteristics. The study also reveals the challenge in the reliable prediction of the magnitude of a geomagnetic storm from solar and interplanetary variables.

  7. Thyroid storm: an updated review.

    Science.gov (United States)

    Chiha, Maguy; Samarasinghe, Shanika; Kabaker, Adam S

    2015-03-01

    Thyroid storm, an endocrine emergency first described in 1926, remains a diagnostic and therapeutic challenge. No laboratory abnormalities are specific to thyroid storm, and the available scoring system is based on the clinical criteria. The exact mechanisms underlying the development of thyroid storm from uncomplicated hyperthyroidism are not well understood. A heightened response to thyroid hormone is often incriminated along with increased or abrupt availability of free hormones. Patients exhibit exaggerated signs and symptoms of hyperthyroidism and varying degrees of organ decompensation. Treatment should be initiated promptly targeting all steps of thyroid hormone formation, release, and action. Patients who fail medical therapy should be treated with therapeutic plasma exchange or thyroidectomy. The mortality of thyroid storm is currently reported at 10%. Patients who have survived thyroid storm should receive definite therapy for their underlying hyperthyroidism to avoid any recurrence of this potentially fatal condition. © The Author(s) 2013.

  8. The electric storm of November 1882

    Science.gov (United States)

    Love, Jeffrey J.

    2018-01-01

    In November 1882, an intense magnetic storm related to a large sunspot group caused widespread interference to telegraph and telephone systems and provided spectacular and unusual auroral displays. The (ring current) storm time disturbance index for this storm reached maximum −Dst ≈ 386 nT, comparable to Halloween storm of 29–31 October 2003, but from 17 to 20 November the aa midlatitude geomagnetic disturbance index averaged 214.25 nT, the highest 4 day level of disturbance since the beginning of aa index in 1868. This storm contributed to scientists' understanding of the reality of solar‐terrestrial interaction. Past occurrences of magnetic storms, like that of November 1882, can inform modern evaluations of the deleterious effects that a magnetic superstorm might have on technological systems of importance to society.

  9. How does the predicted geomagnetic main field variation alter the thermosphere-ionosphere storm-time response?

    Science.gov (United States)

    Maute, A. I.; Lu, G.; Richmond, A. D.

    2017-12-01

    Earth's magnetic main field plays an important role in the thermosphere-ionosphere (TI) system, as well as its coupling to Earth's magnetosphere. The ionosphere consists of a weakly ionized plasma strongly influenced by the main field and embedded in the thermosphere. Therefore, ion-neutral coupling and ionospheric electrodynamics can influence the plasma distribution and neutral dynamics. There are strong longitude variations of the TI storm response. At high latitude magnetosphere-ionosphere coupling is organized by the geomagnetic main field, leading in general to stronger northern middle latitude storm time response in the American sector due to the geomagnetic dipole location. In addition, the weak geomagnetic main field in the American sector leads to larger local ExB drift and can alter the plasma densities. During geomagnetic storms the intense energy input into the high latitude region is redistributed globally, leading to thermospheric heating, wind circulation changes and alterations of the ionospheric electrodynamics. The storm time changes are measurable in the plasma density, ion drift, temperature, neutral composition, and other parameters. All these changes depend, to some degree, on the geomagnetic main field which changes on decadal time scales. In this study, we employ a forecast model of the geomagnetic main field based on data assimilation and geodynamo modeling [Aubert et al., 2015]. The main field model predicts that in 50 years the South Atlantic Anomaly is further weakened by 2 mT and drifts westward by approximately 10o. The dipole axis moves northward and westward by 2o and 6o, respectively. Simulating the March 2015 geomagnetic storm with the Thermosphere-Ionosphere Electrodynamics General Circulation Model (TIE-GCM) driven by the Assimilative Mapping of Ionospheric Electrodynamics (AMIE), we evaluate the thermosphere-ionosphere response using the geomagnetic main field of 2015, 2065, and 2115. We compare the TI response for 2015 with

  10. The analysis of dependence between extreme rainfall and storm surge in the coastal zone

    Science.gov (United States)

    Zheng, F.; Westra, S.

    2012-12-01

    Flooding in coastal catchments can be caused by runoff generated by an extreme rainfall event, elevated sea levels due to an extreme storm surge event, or the combination of both processes occurring simultaneously or in close succession. Dependence in extreme rainfall and storm surge arises because common meteorological forcings often drive both variables; for example, cyclonic systems may produce extreme rainfall, strong onshore winds and an inverse barometric effect simultaneously, which the former factor influencing catchment discharge and the latter two factors influencing storm surge. Nevertheless there is also the possibility that only one of the variables is extreme at any given time, so that the dependence between rainfall and storm surge is not perfect. Quantification of the strength of dependence between these processes is critical in evaluating the magnitude of flood risk in the coastal zone. This may become more important in the future as the majority of the coastal areas are threatened by the sea level rise due to the climate change. This research uses the most comprehensive record of rainfall and storm surge along the coastline of Australia collected to-date to investigate the strength of dependence between the extreme rainfall and storm surge along the Australia coastline. A bivariate logistic threshold-excess model was employed to this end to carry out the dependence analysis. The strength of the estimated dependence is then evaluated as a function of several factors including: the distance between the tidal gauge and the rain gauge; the lag between the extreme precipitation event and extreme surge event; and the duration of the maximum storm burst. The results show that the dependence between the extreme rainfall and storm surge along the Australia coastline is statistically significant, although some locations clearly exhibit stronger dependence than others. We hypothesize that this is due to a combination of large-scale meteorological effects as

  11. Is it safe to treat hyperthyroid patients with I-131 without fear of thyroid storm?

    International Nuclear Information System (INIS)

    Vijayakumar, V.; Nusynowitz, M.L.; Ali, S.

    2006-01-01

    Thyroid storm is extremely rare. However, hyperthyroid patients with severe thyrotoxicosis are frequently not treated immediately with I-131 for fear of thyroid storm but are placed on thiouracil drugs for varying periods of time. We demonstrate herein that it is safe to treat these patients with I-131, without pretreatment with thiouracil drugs, provided they do not have complicating intercurrent disease. Our definition of severe hyperthyroidism includes marked signs and symptoms of thyrotoxicosis, suppressed thyroid stimulating hormone (TSH), markedly elevated free T4 and/or free T3 and elevated radioactive iodine uptake (RAIU) (>30%) at 4 or 24 hours. Our diagnostic criteria for thyroid storm include two or more findings of fever (>38 deg C, 100 deg F), severe tachycardia, high pulse pressure, agitation with tremors, flushing, sweating, heart failure, nausea, vomiting, diarrhea, jaundice associated with high free T4 and/or free T3. Patients were selected retrospectively for the period between August 2003 and December 2004. One hundred and twenty-two patient visits were identified. These patients were treated with 370-740 MBq (10-20 mCi) of I-131 and were evaluated for any evidence of thyroid storm. Most of the patients were placed on beta blocker drugs at the time of initial I-131 therapy; these were continued for at least two months, when the first follow-up visit occurred. At the time of I-131 therapy, it is our policy to educate the patients to seek immediate medical attention for exacerbation of symptoms of thyrotoxicosis. Not one of these patients developed thyroid storm. A subset of 25% of these cases with higher potential for thyroid storm (RAIU more than 65%, very marked signs and symptoms, and very markedly elevated free T4 and/or free T3) also tolerated the I-131 therapy well with marked clinical improvement and no exacerbation of the thyrotoxic state. It is safe to administer I-131 to patients who are severely hyperthyroid without fear of thyroid

  12. Significantly Increased Extreme Precipitation Expected in Europe and North America from Extratropical Storms

    Science.gov (United States)

    Hawcroft, M.; Hodges, K.; Walsh, E.; Zappa, G.

    2017-12-01

    For the Northern Hemisphere extratropics, changes in circulation are key to determining the impacts of climate warming. The mechanisms governing these circulation changes are complex, leading to the well documented uncertainty in projections of the future location of the mid-latitude storm tracks simulated by climate models. These storms are the primary source of precipitation for North America and Europe and generate many of the large-scale precipitation extremes associated with flooding and severe economic loss. Here, we show that in spite of the uncertainty in circulation changes, by analysing the behaviour of the storms themselves, we find entirely consistent and robust projections across an ensemble of climate models. In particular, we find that projections of change in the most intensely precipitating storms (above the present day 99th percentile) in the Northern Hemisphere are substantial and consistent across models, with large increases in the frequency of both summer (June-August, +226±68%) and winter (December-February, +186±34%) extreme storms by the end of the century. Regionally, both North America (summer +202±129%, winter +232±135%) and Europe (summer +390±148%, winter +318±114%) are projected to experience large increases in the frequency of intensely precipitating storms. These changes are thermodynamic and driven by surface warming, rather than by changes in the dynamical behaviour of the storms. Such changes in storm behaviour have the potential to have major impacts on society given intensely precipitating storms are responsible for many large-scale flooding events.

  13. Fuel cycle forecasting - there are forecasts and there are forecasts

    International Nuclear Information System (INIS)

    Puechl, K.H.

    1975-01-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis. (author)

  14. Fuel cycle forecasting - there are forecasts and there are forecasts

    Energy Technology Data Exchange (ETDEWEB)

    Puechl, K H

    1975-12-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis.

  15. Klaus, an exceptional winter storm over Northern Iberia and Southern France - a comparison between storm diagnostics

    Science.gov (United States)

    Liberato, M. L. R.; Pinto, J. G.; Trigo, I. F.; Trigo, R. M.

    2010-05-01

    The synoptic evolution and dynamical characteristics of storm "Klaus" (23 and 24 January 2009) are analysed. "Klaus" was an extratropical cyclone which developed over the subtropical North Atlantic Ocean on the 21st January 2009, then moved eastward embedded in the strong westerly flow and experienced a notorious strengthening on the 23rd January. The storm moved into the Bay of Biscay and deepened further before hitting Northern Spain and Southwestern France with gusts of up to 198 km/h. Afterwards, it steered southeastwards across Southern France into Northern Italy and the Adriatic. "Klaus" was the most intense and damaging wind storm in the region in a decade, provoked more than 20 casualties and insured losses of several billion Euros. The evolution of "Klaus" is analysed using two standard cyclone detecting and tracking schemes: a) the vorticity maxima based algorithm originally developed by Murray and Simmonds [1991], adapted for Northern Hemisphere cyclone characteristics [Pinto et al. 2005]; and b) the pressure minima based algorithm first developed for the Mediterranean region [Trigo et al. 1999; 2002] and later extended to a larger Euro-Atlantic region [Trigo 2006]. Additionally, the synoptic and mesoscale features of the storm are analysed. The vorticity based method detects the storm earlier than the pressure minima one. Results show that both tracks exhibited similar features and positions throughout almost all of their lifecycles, with minor discrepancies being probably related to different ways of both methods handling the spatio-temporal evolution of multiple candidates for cyclonic centres. In its strengthening phase, "Klaus" presents deepening rates above 37 hPa/24h, a value that after geostrophically adjusted to the reference latitude of 60°N increases to 44 hPa/24h, implying an exceptional event with bomb characteristics. During maximum intensity change within 24 hours was 1.165hPa/(deglat)2. References: Murray RJ, Simmonds I (1991) Aust

  16. An operational coupled wave-current forecasting system for the northern Adriatic Sea

    Science.gov (United States)

    Russo, A.; Coluccelli, A.; Deserti, M.; Valentini, A.; Benetazzo, A.; Carniel, S.

    2012-04-01

    Since 2005 an Adriatic implementation of the Regional Ocean Modeling System (AdriaROMS) is being producing operational short-term forecasts (72 hours) of some hydrodynamic properties (currents, sea level, temperature, salinity) of the Adriatic Sea at 2 km horizontal resolution and 20 vertical s-levels, on a daily basis. The main objective of AdriaROMS, which is managed by the Hydro-Meteo-Clima Service (SIMC) of ARPA Emilia Romagna, is to provide useful products for civil protection purposes (sea level forecasts, outputs to run other forecasting models as for saline wedge, oil spills and coastal erosion). In order to improve the forecasts in the coastal area, where most of the attention is focused, a higher resolution model (0.5 km, again with 20 vertical s-levels) has been implemented for the northern Adriatic domain. The new implementation is based on the Coupled-Ocean-Atmosphere-Wave-Sediment Transport Modeling System (COAWST)and adopts ROMS for the hydrodynamic and Simulating WAve Nearshore (SWAN) for the wave module, respectively. Air-sea fluxes are computed using forecasts produced by the COSMO-I7 operational atmospheric model. At the open boundary of the high resolution model, temperature, salinity and velocity fields are provided by AdriaROMS while the wave characteristics are provided by an operational SWAN implementation (also managed by SIMC). Main tidal components are imposed as well, derived from a tidal model. Work in progress is oriented now on the validation of model results by means of extensive comparisons with acquired hydrographic measurements (such as CTDs or XBTs from sea-truth campaigns), currents and waves acquired at observational sites (including those of SIMC, CNR-ISMAR network and its oceanographic tower, located off the Venice littoral) and satellite-derived wave-heights data. Preliminary results on the forecast waves denote how, especially during intense storms, the effect of coupling can lead to significant variations in the wave

  17. Development of a multi-sensor based urban discharge forecasting system using remotely sensed data: A case study of extreme rainfall in South Korea

    Science.gov (United States)

    Yoon, Sunkwon; Jang, Sangmin; Park, Kyungwon

    2017-04-01

    Extreme weather due to changing climate is a main source of water-related disasters such as flooding and inundation and its damage will be accelerated somewhere in world wide. To prevent the water-related disasters and mitigate their damage in urban areas in future, we developed a multi-sensor based real-time discharge forecasting system using remotely sensed data such as radar and satellite. We used Communication, Ocean and Meteorological Satellite (COMS) and Korea Meteorological Agency (KMA) weather radar for quantitative precipitation estimation. The Automatic Weather System (AWS) and McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) were used for verification of rainfall accuracy. The optimal Z-R relation was applied the Tropical Z-R relationship (Z=32R1.65), it has been confirmed that the accuracy is improved in the extreme rainfall events. In addition, the performance of blended multi-sensor combining rainfall was improved in 60mm/h rainfall and more strong heavy rainfall events. Moreover, we adjusted to forecast the urban discharge using Storm Water Management Model (SWMM). Several statistical methods have been used for assessment of model simulation between observed and simulated discharge. In terms of the correlation coefficient and r-squared discharge between observed and forecasted were highly correlated. Based on this study, we captured a possibility of real-time urban discharge forecasting system using remotely sensed data and its utilization for real-time flood warning. Acknowledgement This research was supported by a grant (13AWMP-B066744-01) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korean government.

  18. Wave ensemble forecast in the Western Mediterranean Sea, application to an early warning system.

    Science.gov (United States)

    Pallares, Elena; Hernandez, Hector; Moré, Jordi; Espino, Manuel; Sairouni, Abdel

    2015-04-01

    The Western Mediterranean Sea is a highly heterogeneous and variable area, as is reflected on the wind field, the current field, and the waves, mainly in the first kilometers offshore. As a result of this variability, the wave forecast in these regions is quite complicated to perform, usually with some accuracy problems during energetic storm events. Moreover, is in these areas where most of the economic activities take part, including fisheries, sailing, tourism, coastal management and offshore renewal energy platforms. In order to introduce an indicator of the probability of occurrence of the different sea states and give more detailed information of the forecast to the end users, an ensemble wave forecast system is considered. The ensemble prediction systems have already been used in the last decades for the meteorological forecast; to deal with the uncertainties of the initial conditions and the different parametrizations used in the models, which may introduce some errors in the forecast, a bunch of different perturbed meteorological simulations are considered as possible future scenarios and compared with the deterministic forecast. In the present work, the SWAN wave model (v41.01) has been implemented for the Western Mediterranean sea, forced with wind fields produced by the deterministic Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS). The wind fields includes a deterministic forecast (also named control), between 11 and 21 ensemble members, and some intelligent member obtained from the ensemble, as the mean of all the members. Four buoys located in the study area, moored in coastal waters, have been used to validate the results. The outputs include all the time series, with a forecast horizon of 8 days and represented in spaghetti diagrams, the spread of the system and the probability at different thresholds. The main goal of this exercise is to be able to determine the degree of the uncertainty of the wave forecast, meaningful

  19. Examining Dense Data Usage near the Regions with Severe Storms in All-Sky Microwave Radiance Data Assimilation and Impacts on GEOS Hurricane Analyses

    Science.gov (United States)

    Kim, Min-Jeong; Jin, Jianjun; McCarty, Will; El Akkraoui, Amal; Todling, Ricardo; Gelaro, Ron

    2018-01-01

    Many numerical weather prediction (NWP) centers assimilate radiances affected by clouds and precipitation from microwave sensors, with the expectation that these data can provide critical constraints on meteorological parameters in dynamically sensitive regions to make significant impacts on forecast accuracy for precipitation. The Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center assimilates all-sky microwave radiance data from various microwave sensors such as all-sky GPM Microwave Imager (GMI) radiance in the Goddard Earth Observing System (GEOS) atmospheric data assimilation system (ADAS), which includes the GEOS atmospheric model, the Gridpoint Statistical Interpolation (GSI) atmospheric analysis system, and the Goddard Aerosol Assimilation System (GAAS). So far, most of NWP centers apply same large data thinning distances, that are used in clear-sky radiance data to avoid correlated observation errors, to all-sky microwave radiance data. For example, NASA GMAO is applying 145 km thinning distances for most of satellite radiance data including microwave radiance data in which all-sky approach is implemented. Even with these coarse observation data usage in all-sky assimilation approach, noticeable positive impacts from all-sky microwave data on hurricane track forecasts were identified in GEOS-5 system. The motivation of this study is based on the dynamic thinning distance method developed in our all-sky framework to use of denser data in cloudy and precipitating regions due to relatively small spatial correlations of observation errors. To investigate the benefits of all-sky microwave radiance on hurricane forecasts, several hurricane cases selected between 2016-2017 are examined. The dynamic thinning distance method is utilized in our all-sky approach to understand the sources and mechanisms to explain the benefits of all-sky microwave radiance data from various microwave radiance sensors like Advanced Microwave Sounder Unit

  20. Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

    Directory of Open Access Journals (Sweden)

    Jinyin Ye

    2016-01-01

    Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

  1. Operation of a real-time warning system for debris flows in the San Francisco bay area, California

    Science.gov (United States)

    Wilson, Raymond C.; Mark, Robert K.; Barbato, Gary; ,

    1993-01-01

    The United States Geological Survey (USGS) and the National Weather Service (NWS) have developed an operational warning system for debris flows during severe rainstorms in the San Francisco Bay region. The NWS makes quantitative forecasts of precipitation from storm systems approaching the Bay area and coordinates a regional network of radio-telemetered rain gages. The USGS has formulated thresholds for the intensity and duration of rainfall required to initiate debris flows. The first successful public warnings were issued during a severe storm sequence in February 1986. Continued operation of the warning system since 1986 has provided valuable working experience in rainfall forecasting and monitoring, refined rainfall thresholds, and streamlined procedures for issuing public warnings. Advisory statements issued since 1986 are summarized.

  2. STORM WATER MANAGEMENT MODEL USER'S MANUAL VERSION 5.0

    Science.gov (United States)

    The EPA Storm Water Management Model (SWMM) is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. SWMM was first developed in 1971 and has undergone several major upgrade...

  3. Operational hydrological forecasting during the IPHEx-IOP campaign - Meet the challenge

    Science.gov (United States)

    Tao, Jing; Wu, Di; Gourley, Jonathan; Zhang, Sara Q.; Crow, Wade; Peters-Lidard, Christa; Barros, Ana P.

    2016-10-01

    were significantly improved by assimilating discharge observations into the DCHM. Specifically, Nash-Sutcliff Efficiency (NSE) values as high as 0.98, 0.71 and 0.99 at 15-min time-scales were attained for three headwater catchments in the inner mountain region demonstrating that the assimilation of discharge observations at the basin's outlet can reduce the errors and uncertainties in soil moisture at very small scales. Success in operational flood forecasting at lead times of 6, 9, 12 and 15 h was also achieved through discharge assimilation with NSEs of 0.87, 0.78, 0.72 and 0.51, respectively. Analysis of experiments using various data assimilation system configurations indicates that the optimal assimilation time window depends both on basin properties and storm-specific space-time-structure of rainfall, and therefore adaptive, context-aware configurations of the data assimilation system are recommended to address the challenges of flood prediction in headwater basins.

  4. Operational Hydrological Forecasting During the Iphex-iop Campaign - Meet the Challenge

    Science.gov (United States)

    Tao, Jing; Wu, Di; Gourley, Jonathan; Zhang, Sara Q.; Crow, Wade; Peters-Lidard, Christa D.; Barros, Ana P.

    2016-01-01

    were significantly improved by assimilating discharge observations into the DCHM. Specifically, Nash-Sutcliff Efficiency (NSE) values as high as 0.98, 0.71 and 0.99 at 15-min time-scales were attained for three headwater catchments in the inner mountain region demonstrating that the assimilation of discharge observations at the basins outlet can reduce the errors and uncertainties in soil moisture at very small scales. Success in operational flood forecasting at lead times of 6, 9, 12 and 15 h was also achieved through discharge assimilation with NSEs of 0.87, 0.78, 0.72 and 0.51, respectively. Analysis of experiments using various data assimilation system configurations indicates that the optimal assimilation time window depends both on basin properties and storm-specific space-time-structure of rainfall, and therefore adaptive, context-aware configurations of the data assimilation system are recommended to address the challenges of flood prediction in headwater basins.

  5. Forecasting Housing Approvals in Australia: Do Forecasters Herd?

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Rülke

    2012-01-01

    Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

  6. A Case of Thyroid Storm Associated with Cardiomyopathy and Poststreptococcal Glomerulonephritis

    Directory of Open Access Journals (Sweden)

    Lisa J. Underland

    2016-01-01

    Full Text Available Thyroid storm has a high mortality rate and is often associated with a precipitating factor such as intercurrent illness or infection. It is rare in pediatric patients. Cardiac disease in hyperthyroidism mostly manifests itself as tachycardia but more serious cardiac findings have also been described. A 5-year-old male with recent strep throat infection presented with dilated cardiomyopathy, hematuria, and symptoms and lab findings consistent with severe hyperthyroidism. He was diagnosed with thyroid storm secondary to concurrent Graves’ disease and poststreptococcal glomerulonephritis (PSGN. After starting the treatment with methimazole and a beta-blocker, his cardiac disease gradually improved and the PSGN resolved over time. There are no specific pediatric criteria for thyroid storm. Adult criteria can be difficult to apply to pediatric cases. Criteria for diagnosis of thyroid storm are less clear for pediatric patients. Dilated cardiomyopathy is a rare cardiac manifestation of hyperthyroidism. PSGN is due to glomerular immune complexes and can complicate group A strep infection. Providers should be aware of cardiac disease as a complication of hyperthyroidism. PSGN should not mechanistically be related to hyperthyroidism but can precipitate the signs of thyroid storm such as hypertension. This association has not been previously reported in the literature.

  7. Thyroid storm with multiple organ failure, disseminated intravascular coagulation, and stroke with a normal serum FT3 level.

    Science.gov (United States)

    Harada, Yuko; Akiyama, Hisanao; Yoshimoto, Tatsuji; Urao, Yasuko; Ryuzaki, Munekazu; Handa, Michiko

    2012-01-01

    Thyroid storm is a rare disorder with a sudden onset, rapid progression and high mortality. We experienced a case of thyroid storm which had a devastating course, including multiple organ failure (MOF), severe hypoglycemia, disseminated intravascular coagulation (DIC), and stroke. It was difficult to make a diagnosis of thyroid storm in the present patient, because she did not have a history of thyroid disease and her serum FT3 level was normal. Clinicians should be aware that thyroid storm can occur even when there is an almost normal level of thyroid hormones, and that intensive anticoagulation is required for patients with atrial fibrillation to prevent stroke after thyroid storm.

  8. Forecasting freight flows

    DEFF Research Database (Denmark)

    Lyk-Jensen, Stéphanie

    2011-01-01

    Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...... constitute a valuable input to freight models for forecasting future capacity problems.......Trade patterns and transport markets are changing as a result of the growth and globalization of international trade, and forecasting future freight flow has to rely on trade forecasts. Forecasting freight flows is critical for matching infrastructure supply to demand and for assessing investment...

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

    Science.gov (United States)

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

    2013-12-01

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

  10. Coastal Storm Surge Analysis: Storm Surge Results. Report 5: Intermediate Submission No. 3

    Science.gov (United States)

    2013-11-01

    Vickery, P., D. Wadhera, A. Cox, V. Cardone , J. Hanson, and B. Blanton. 2012. Coastal storm surge analysis: Storm forcing (Intermediate Submission No...CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Jeffrey L. Hanson, Michael F. Forte, Brian Blanton

  11. Robust forecast comparison

    OpenAIRE

    Jin, Sainan; Corradi, Valentina; Swanson, Norman

    2015-01-01

    Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority, and we establish a ...

  12. Prediction of a service demand using combined forecasting approach

    Science.gov (United States)

    Zhou, Ling

    2017-08-01

    Forecasting facilitates cutting down operational and management costs while ensuring service level for a logistics service provider. Our case study here is to investigate how to forecast short-term logistic demand for a LTL carrier. Combined approach depends on several forecasting methods simultaneously, instead of a single method. It can offset the weakness of a forecasting method with the strength of another, which could improve the precision performance of prediction. Main issues of combined forecast modeling are how to select methods for combination, and how to find out weight coefficients among methods. The principles of method selection include that each method should apply to the problem of forecasting itself, also methods should differ in categorical feature as much as possible. Based on these principles, exponential smoothing, ARIMA and Neural Network are chosen to form the combined approach. Besides, least square technique is employed to settle the optimal weight coefficients among forecasting methods. Simulation results show the advantage of combined approach over the three single methods. The work done in the paper helps manager to select prediction method in practice.

  13. Great magnetic storms

    International Nuclear Information System (INIS)

    Tsurutani, B.T.; Yen Te Lee; Tang, F.; Gonzalez, W.D.

    1992-01-01

    The five largest magnetic storms that occurred between 1971 and 1986 are studied to determine their solar and interplanetary causes. All of the events are found to be associated with high speed solar wind streams led by collisionless shocks. The high speed streams are clearly related to identifiable solar flares. It is found that (1) it is the extreme values of the southward interplanetary magnetic fields rather than solar wind speeds that are the primary causes of great magnetic storms, (2) shocked and draped sheath fields preceding the driver gas (magnetic cloud) are at least as effective in causing the onset of great magnetic storms (3 of 5 events ) as the strong fields within the driver gas itself, and (3) precursor southward fields ahead of the high speed streams allow the shock compression mechanism (item 2) to be particularly geoeffective

  14. Assessing storm erosion hazards

    NARCIS (Netherlands)

    Ranasinghe, Ranasinghe W M R J B; Callaghan, D.; Ciavola, Paolo; Coco, Giovanni

    2017-01-01

    The storm erosion hazard on coasts is usually expressed as an erosion volume and/or associated episodic coastline retreat. The accurate assessment of present-day and future storm erosion volumes is a key task for coastal zone managers, planners and engineers. There are four main approaches that can

  15. Impacts of ionospheric electric fields on the GPS tropospheric delays during geomagnetic storms in Antarctica

    International Nuclear Information System (INIS)

    Suparta, W

    2017-01-01

    This paper aimed to overview the interaction of the thunderstorm with the ionospheric electric fields during major geomagnetic storms in Antarctica through the GPS tropospheric delays. For the purpose of study, geomagnetic activity and electric fields data for the period from 13 to 21 March 2015 representing the St. Patrick’s Day storm is analyzed. To strengthen the analysis, data for the period of 27 October to 1 st November 2003 representing for the Halloween storm is also compared. Our analysis showed that both geomagnetic storms were severe ( Ap ≥ 100 nT), where the intensity of Halloween storm is double compared to St. Patrick’s Day storm. For the ionospheric electric field, the peaks were dropped to -1.63 mV/m and -2.564 mV/m for St. Patrick and Halloween storms, respectively. At this time, the interplanetary magnetic field Bz component was significantly dropped to -17.31 nT with Ap > 150 nT (17 March 2015 at 19:20 UT) and -26.51 nT with Ap = 300 nT (29 October 2003 at 19:40 UT). For both geomagnetic storms, the electric field was correlated well with the ionospheric activity where tropospheric delays show a different characteristic. (paper)

  16. 46 CFR 169.329 - Storm rails.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 7 2010-10-01 2010-10-01 false Storm rails. 169.329 Section 169.329 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) NAUTICAL SCHOOLS SAILING SCHOOL VESSELS Construction and Arrangement Rails and Guards § 169.329 Storm rails. Suitable storm rails or hand grabs must be...

  17. 46 CFR 72.40-10 - Storm rails.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 3 2010-10-01 2010-10-01 false Storm rails. 72.40-10 Section 72.40-10 Shipping COAST... and Guards § 72.40-10 Storm rails. (a) Suitable storm rails shall be installed in all passageways and at the deckhouse sides where passengers or crew might have normal access. Storm rails shall be...

  18. 46 CFR 116.920 - Storm rails.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Storm rails. 116.920 Section 116.920 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) SMALL PASSENGER VESSELS CARRYING MORE THAN 150... and Guards § 116.920 Storm rails. Suitable storm rails or hand grabs must be installed where necessary...

  19. 46 CFR 177.920 - Storm rails.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 7 2010-10-01 2010-10-01 false Storm rails. 177.920 Section 177.920 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) SMALL PASSENGER VESSELS (UNDER 100 GROSS TONS) CONSTRUCTION AND ARRANGEMENT Rails and Guards § 177.920 Storm rails. Suitable storm rails or hand grabs must be...

  20. 46 CFR 127.320 - Storm rails.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 4 2010-10-01 2010-10-01 false Storm rails. 127.320 Section 127.320 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) OFFSHORE SUPPLY VESSELS CONSTRUCTION AND ARRANGEMENTS Rails and Guards § 127.320 Storm rails. Suitable storm rails must be installed in each passageway and at...