WorldWideScience

Sample records for mesoscale model weather

  1. Adaptation of Mesoscale Weather Models to Local Forecasting

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

    2003-01-01

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

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

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

    2014-06-01

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

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

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

    2017-07-01

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

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

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

    2014-01-01

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

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

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

    2017-12-01

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

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

    Prashant K. Srivastava

    2017-10-01

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

  7. Modeling mesoscale eddies

    Canuto, V. M.; Dubovikov, M. S.

    Mesoscale eddies are not resolved in coarse resolution ocean models and must be modeled. They affect both mean momentum and scalars. At present, no generally accepted model exists for the former; in the latter case, mesoscales are modeled with a bolus velocity u∗ to represent a sink of mean potential energy. However, comparison of u∗(model) vs. u∗ (eddy resolving code, [J. Phys. Ocean. 29 (1999) 2442]) has shown that u∗(model) is incomplete and that additional terms, "unrelated to thickness source or sinks", are required. Thus far, no form of the additional terms has been suggested. To describe mesoscale eddies, we employ the Navier-Stokes and scalar equations and a turbulence model to treat the non-linear interactions. We then show that the problem reduces to an eigenvalue problem for the mesoscale Bernoulli potential. The solution, which we derive in analytic form, is used to construct the momentum and thickness fluxes. In the latter case, the bolus velocity u∗ is found to contain two types of terms: the first type entails the gradient of the mean potential vorticity and represents a positive contribution to the production of mesoscale potential energy; the second type of terms, which is new, entails the velocity of the mean flow and represents a negative contribution to the production of mesoscale potential energy, or equivalently, a backscatter process whereby a fraction of the mesoscale potential energy is returned to the original reservoir of mean potential energy. This type of terms satisfies the physical description of the additional terms given by [J. Phys. Ocean. 29 (1999) 2442]. The mesoscale flux that enters the momentum equations is also contributed by two types of terms of the same physical nature as those entering the thickness flux. The potential vorticity flux is also shown to contain two types of terms: the first is of the gradient-type while the other terms entail the velocity of the mean flow. An expression is derived for the mesoscale

  8. Evaluation of cloud prediction and determination of critical relative humidity for a mesoscale numerical weather prediction model

    Seaman, N.L.; Guo, Z.; Ackerman, T.P. [Pennsylvania State Univ., University Park, PA (United States)

    1996-04-01

    Predictions of cloud occurrence and vertical location from the Pennsylvannia State University/National Center for Atmospheric Research nonhydrostatic mesoscale model (MM5) were evaluated statistically using cloud observations obtained at Coffeyville, Kansas, as part of the Second International satellite Cloud Climatology Project Regional Experiment campaign. Seventeen cases were selected for simulation during a November-December 1991 field study. MM5 was used to produce two sets of 36-km simulations, one with and one without four-dimensional data assimilation (FDDA), and a set of 12-km simulations without FDDA, but nested within the 36-km FDDA runs.

  9. Turbulence Dissipation Rates in the Planetary Boundary Layer from Wind Profiling Radars and Mesoscale Numerical Weather Prediction Models during WFIP2

    Bianco, L.; McCaffrey, K.; Wilczak, J. M.; Olson, J. B.; Kenyon, J.

    2016-12-01

    When forecasting winds at a wind plant for energy production, the turbulence parameterizations in the forecast models are crucial for understanding wind plant performance. Recent research shows that the turbulence (eddy) dissipation rate in planetary boundary layer (PBL) parameterization schemes introduces significant uncertainty in the Weather Research and Forecasting (WRF) model. Thus, developing the capability to measure dissipation rates in the PBL will allow for identification of weaknesses in, and improvements to the parameterizations. During a preliminary field study at the Boulder Atmospheric Observatory in spring 2015, a 915-MHz wind profiling radar (WPR) measured dissipation rates concurrently with sonic anemometers mounted on a 300-meter tower. WPR set-up parameters (e.g., spectral resolution), post-processing techniques (e.g., filtering for non-atmospheric signals), and spectral averaging were optimized to capture the most accurate Doppler spectra for measuring spectral widths for use in the computation of the eddy dissipation rates. These encouraging results lead to the implementation of the observing strategy on a 915-MHz WPR in Wasco, OR, operating as part of the Wind Forecasting Improvement Project 2 (WFIP2). These observations are compared to dissipation rates calculated from the High-Resolution Rapid Refresh model, a WRF-based mesoscale numerical weather prediction model run for WFIP2 at 3000 m horizontal grid spacing and with a nest, which has 750-meter horizontal grid spacing, in the complex terrain region of the Columbia River Gorge. The observed profiles of dissipation rates are used to evaluate the PBL parameterization schemes used in the HRRR model, which are based on the modeled turbulent kinetic energy and a tunable length scale.

  10. Assimilation of Doppler weather radar observations in a mesoscale ...

    Research (PSU–NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation ... investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present ...... Results presented in this paper are based on.

  11. Wake modelling combining mesoscale and microscale models

    Badger, Jake; Volker, Patrick; Prospathospoulos, J.

    2013-01-01

    In this paper the basis for introducing thrust information from microscale wake models into mesocale model wake parameterizations will be described. A classification system for the different types of mesoscale wake parameterizations is suggested and outlined. Four different mesoscale wake paramet...

  12. Skills of different mesoscale models over Indian region during ...

    tion and prediction of high impact severe weather systems. Such models ... mesoscale models can be run at cloud resolving resolutions (∼1km) ... J. Earth Syst. Sci. 117, No. ..... similar to climate drift, indicating that those error components are ...

  13. Mesoscale Modeling, Forecasting and Remote Sensing Research.

    remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed

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

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

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

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

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

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

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

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

  18. Extreme gust wind estimation using mesoscale modeling

    Larsén, Xiaoli Guo; Kruger, Andries

    2014-01-01

    , surface turbulence characteristics. In this study, we follow a theory that is different from the local gust concept as described above. In this theory, the gust at the surface is non-local; it is produced by the deflection of air parcels flowing in the boundary layer and brought down to the surface...... from the Danish site Høvsøre help us to understand the limitation of the traditional method. Good agreement was found between the extreme gust atlases for South Africa and the existing map made from a limited number of measurements across the country. Our study supports the non-local gust theory. While...... through turbulent eddies. This process is modeled using the mesoscale Weather Forecasting and Research (WRF) model. The gust at the surface is calculated as the largest winds over a layer where the averaged turbulence kinetic energy is greater than the averaged buoyancy force. The experiments have been...

  19. Wind-Farm Parametrisations in Mesoscale Models

    Volker, Patrick; Badger, Jake; Hahmann, Andrea N.

    2013-01-01

    In this paper we compare three wind-farm parametrisations for mesoscale models against measurement data from the Horns Rev I offshore wind-farm. The parametrisations vary from a simple rotor drag method, to more sophisticated models. Additional to (4) we investigated the horizontal resolution dep...

  20. Numerical simulation of heavy precipitation events using mesoscale weather forecast models. Validation with radar data and diagnosis of the atmospheric moisture budget; Numerische Simulation von Starkniederschlagsereignissen mit mesoskaligen Wettervorhersagemodellen. Ueberpruefung mit Radar-Daten und Diagnose der atmosphaerischen Wasserbilanz

    Keil, C.

    2000-07-01

    Convective precipitation systems contribute substantially to the summertime rainfall maximum in the northern Alpine region. The capability of mesoscale weather forecast models in capturing such heavy precipitation events is investigated. The complementary application of so far hardly used areal radar data and conventional rain gauge observations enables a case-study-type evaluation of summertime precipitation episodes. Different rainfall episodes are simulated with the former operational model (DM, meshsize 14 km) of Deutscher Wetterdienst (DWD). The influence of the horizontal resolution and the parameterization of moist convection is subsequently studied with a higher resolution atmospheric model (MC2, meshsize 2 km). Diagnostic studies on the atmospheric water budget regarding the rainfall episode, which instigated the Oder-flood in summer 1997, allow an examination of the origin of the moisture and the genesis of the copious precipitation. (orig.) [German] Konvektive Niederschlagssysterne tragen im Nordalpenraum wesentlich zum sommerlichen Niederschlagsmaximum bei. Die Faehigkeit mesoskaliger Wettervorhersagemodelle, solche Starkniederschlagsereignisse zu erfassen, wird in dieser Arbeit untersucht. Durch den komplementaeren Gebrauch von, bisher kaum genutzten, flaechendeckenden Radardaten und konventionellen Niederschlagsmessungen des Bodenmessnetzes werden Modellergebnisse sommerlicher Niederschlagssysteme fallstudienhaft detailliert ueberprueft. Fuer verschiedene Starkniederschlagsereignisse werden dazu Modellsimulationen mit dem in den 90er Jahren operationellen Modell (DM, Maschenweite 14 km) des Deutschen Wetterdienstes (DWD) durchgefuehrt. Zur Untersuchung des Einflusses der horizontalen Maschenweite und der Niederschlagsparametrisierung werden ferner numerische Simulationen mit einem hoeher aufloesdenden Atmosphaerenmodell (MC2, Maschenweite 2 km) behandelt. Anhand diagnostischer Untersuchungen der atmosphaerischen Wasserbilanz laesst sich ausserdem die

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

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

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

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

  3. Mesoscale Models of Fluid Dynamics

    Boghosian, Bruce M.; Hadjiconstantinou, Nicolas G.

    During the last half century, enormous progress has been made in the field of computational materials modeling, to the extent that in many cases computational approaches are used in a predictive fashion. Despite this progress, modeling of general hydrodynamic behavior remains a challenging task. One of the main challenges stems from the fact that hydrodynamics manifests itself over a very wide range of length and time scales. On one end of the spectrum, one finds the fluid's "internal" scale characteristic of its molecular structure (in the absence of quantum effects, which we omit in this chapter). On the other end, the "outer" scale is set by the characteristic sizes of the problem's domain. The resulting scale separation or lack thereof as well as the existence of intermediate scales are key to determining the optimal approach. Successful treatments require a judicious choice of the level of description which is a delicate balancing act between the conflicting requirements of fidelity and manageable computational cost: a coarse description typically requires models for underlying processes occuring at smaller length and time scales; on the other hand, a fine-scale model will incur a significantly larger computational cost.

  4. Toward the use of a mesoscale model at a very high resolution

    Gasset, N.; Benoit, R.; Masson, C. [Canada Research Chair on Nordic Environment Aerodynamics of Wind Turbines, Ottawa, ON (Canada)

    2008-07-01

    This presentation described a new compressible mesoscale model designed to obtain wind speed data for potential wind power resource development. Microscale modelling and computerized fluid dynamics (CFD) are used to study the mean properties of the surface layer of the atmospheric boundary layer (ABL). Mesoscale models study the temporal evolution of synoptic to mesoscale atmospheric phenomena and environmental modelling. Mesoscale modelling is essential for wind energy applications and large-scale resource evaluation, and can be compared with microscale models in order to validate input data and determine boundary conditions. The compressible community mesoscale model (MC2) was comprised of a national weather prediction (NWP) model with semi-implicit semi-Lagrangian (SISL) dynamics and compressible Euler equation solutions. Physical parameters included radiations; microphysics; thermal stratification; turbulence; and convection. The turbulence diffusion feature included unsteady Reynolds averaged Navier-Stokes; transport equations for turbulent kinetic energy; and mixing lengths. Operating modes included 3-D weather data, and surface and ground properties as well as 1-way self-nesting abilities. The validation framework for the model included a simulation of a set of realistic cases and theoretical cases including full dynamics and physics. Theoretical cases included manually imposed initial and boundary conditions and minimalist physics. Further research is being conducted to refine operating modes and boundary conditions. tabs., figs.

  5. A Parameterization of Dry Thermals and Shallow Cumuli for Mesoscale Numerical Weather Prediction

    Pergaud, Julien; Masson, Valéry; Malardel, Sylvie; Couvreux, Fleur

    2009-07-01

    For numerical weather prediction models and models resolving deep convection, shallow convective ascents are subgrid processes that are not parameterized by classical local turbulent schemes. The mass flux formulation of convective mixing is now largely accepted as an efficient approach for parameterizing the contribution of larger plumes in convective dry and cloudy boundary layers. We propose a new formulation of the EDMF scheme (for Eddy DiffusivityMass Flux) based on a single updraft that improves the representation of dry thermals and shallow convective clouds and conserves a correct representation of stratocumulus in mesoscale models. The definition of entrainment and detrainment in the dry part of the updraft is original, and is specified as proportional to the ratio of buoyancy to vertical velocity. In the cloudy part of the updraft, the classical buoyancy sorting approach is chosen. The main closure of the scheme is based on the mass flux near the surface, which is proportional to the sub-cloud layer convective velocity scale w *. The link with the prognostic grid-scale cloud content and cloud cover and the projection on the non- conservative variables is processed by the cloud scheme. The validation of this new formulation using large-eddy simulations focused on showing the robustness of the scheme to represent three different boundary layer regimes. For dry convective cases, this parameterization enables a correct representation of the countergradient zone where the mass flux part represents the top entrainment (IHOP case). It can also handle the diurnal cycle of boundary-layer cumulus clouds (EUROCSARM) and conserve a realistic evolution of stratocumulus (EUROCSFIRE).

  6. Assimilation of Aircraft Observations in High-Resolution Mesoscale Modeling

    Brian P. Reen

    2018-01-01

    Full Text Available Aircraft-based observations are a promising source of above-surface observations for assimilation into mesoscale model simulations. The Tropospheric Airborne Meteorological Data Reporting (TAMDAR observations have potential advantages over some other aircraft observations including the presence of water vapor observations. The impact of assimilating TAMDAR observations via observation nudging in 1 km horizontal grid spacing Weather Research and Forecasting model simulations is evaluated using five cases centered over California. Overall, the impact of assimilating the observations is mixed, with the layer with the greatest benefit being above the surface in the lowest 1000 m above ground level and the variable showing the most consistent benefit being temperature. Varying the nudging configuration demonstrates the sensitivity of the results to details of the assimilation, but does not clearly demonstrate the superiority of a specific configuration.

  7. Rotational and divergent kinetic energy in the mesoscale model ALADIN

    V. Blažica

    2013-03-01

    Full Text Available Kinetic energy spectra from the mesoscale numerical weather prediction (NWP model ALADIN with horizontal resolution 4.4 km are split into divergent and rotational components which are then compared at horizontal scales below 300 km and various vertical levels. It is shown that about 50% of kinetic energy in the free troposphere in ALADIN is divergent energy. The percentage increases towards 70% near the surface and in the upper troposphere towards 100 hPa. The maximal percentage of divergent energy is found at stratospheric levels around 100 hPa and at scales below 100 km which are not represented by the global models. At all levels, the divergent energy spectra are characterised by shallower slopes than the rotational energy spectra, and the difference increases as horizontal scales become larger. A very similar vertical distribution of divergent energy is obtained by using the standard ALADIN approach for the computation of spectra based on the extension zone and by applying detrending approach commonly used in mesoscale NWP community.

  8. Probabilistic, meso-scale flood loss modelling

    Kreibich, Heidi; Botto, Anna; Schröter, Kai; Merz, Bruno

    2016-04-01

    Flood risk analyses are an important basis for decisions on flood risk management and adaptation. However, such analyses are associated with significant uncertainty, even more if changes in risk due to global change are expected. Although uncertainty analysis and probabilistic approaches have received increased attention during the last years, they are still not standard practice for flood risk assessments and even more for flood loss modelling. State of the art in flood loss modelling is still the use of simple, deterministic approaches like stage-damage functions. Novel probabilistic, multi-variate flood loss models have been developed and validated on the micro-scale using a data-mining approach, namely bagging decision trees (Merz et al. 2013). In this presentation we demonstrate and evaluate the upscaling of the approach to the meso-scale, namely on the basis of land-use units. The model is applied in 19 municipalities which were affected during the 2002 flood by the River Mulde in Saxony, Germany (Botto et al. submitted). The application of bagging decision tree based loss models provide a probability distribution of estimated loss per municipality. Validation is undertaken on the one hand via a comparison with eight deterministic loss models including stage-damage functions as well as multi-variate models. On the other hand the results are compared with official loss data provided by the Saxon Relief Bank (SAB). The results show, that uncertainties of loss estimation remain high. Thus, the significant advantage of this probabilistic flood loss estimation approach is that it inherently provides quantitative information about the uncertainty of the prediction. References: Merz, B.; Kreibich, H.; Lall, U. (2013): Multi-variate flood damage assessment: a tree-based data-mining approach. NHESS, 13(1), 53-64. Botto A, Kreibich H, Merz B, Schröter K (submitted) Probabilistic, multi-variable flood loss modelling on the meso-scale with BT-FLEMO. Risk Analysis.

  9. Mesoscale Modelling of the Response of Aluminas

    Bourne, N. K.

    2006-01-01

    The response of polycrystalline alumina to shock is not well addressed. There are several operating mechanisms that only hypothesized which results in models which are empirical. A similar state of affairs in reactive flow modelling led to the development of mesoscale representations of the flow to illuminate operating mechanisms. In this spirit, a similar effort is undergone for a polycrystalline alumina. Simulations are conducted to observe operating mechanisms at the micron scale. A method is then developed to extend the simulations to meet response at the continuum level where measurements are made. The approach is validated by comparison with continuum experiments. The method and results are presented, and some of the operating mechanisms are illuminated by the observed response

  10. Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

    Simmer, C.

    2015-12-01

    An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity.

  11. Multiscale Modeling of Mesoscale and Interfacial Phenomena

    Petsev, Nikolai Dimitrov

    With rapidly emerging technologies that feature interfaces modified at the nanoscale, traditional macroscopic models are pushed to their limits to explain phenomena where molecular processes can play a key role. Often, such problems appear to defy explanation when treated with coarse-grained continuum models alone, yet remain prohibitively expensive from a molecular simulation perspective. A prominent example is surface nanobubbles: nanoscopic gaseous domains typically found on hydrophobic surfaces that have puzzled researchers for over two decades due to their unusually long lifetimes. We show how an entirely macroscopic, non-equilibrium model explains many of their anomalous properties, including their stability and abnormally small gas-side contact angles. From this purely transport perspective, we investigate how factors such as temperature and saturation affect nanobubbles, providing numerous experimentally testable predictions. However, recent work also emphasizes the relevance of molecular-scale phenomena that cannot be described in terms of bulk phases or pristine interfaces. This is true for nanobubbles as well, whose nanoscale heights may require molecular detail to capture the relevant physics, in particular near the bubble three-phase contact line. Therefore, there is a clear need for general ways to link molecular granularity and behavior with large-scale continuum models in the treatment of many interfacial problems. In light of this, we have developed a general set of simulation strategies that couple mesoscale particle-based continuum models to molecular regions simulated through conventional molecular dynamics (MD). In addition, we derived a transport model for binary mixtures that opens the possibility for a wide range of applications in biological and drug delivery problems, and is readily reconciled with our hybrid MD-continuum techniques. Approaches that couple multiple length scales for fluid mixtures are largely absent in the literature, and

  12. On Improving 4-km Mesoscale Model Simulations

    Deng, Aijun; Stauffer, David R.

    2006-03-01

    A previous study showed that use of analysis-nudging four-dimensional data assimilation (FDDA) and improved physics in the fifth-generation Pennsylvania State University National Center for Atmospheric Research Mesoscale Model (MM5) produced the best overall performance on a 12-km-domain simulation, based on the 18 19 September 1983 Cross-Appalachian Tracer Experiment (CAPTEX) case. However, reducing the simulated grid length to 4 km had detrimental effects. The primary cause was likely the explicit representation of convection accompanying a cold-frontal system. Because no convective parameterization scheme (CPS) was used, the convective updrafts were forced on coarser-than-realistic scales, and the rainfall and the atmospheric response to the convection were too strong. The evaporative cooling and downdrafts were too vigorous, causing widespread disruption of the low-level winds and spurious advection of the simulated tracer. In this study, a series of experiments was designed to address this general problem involving 4-km model precipitation and gridpoint storms and associated model sensitivities to the use of FDDA, planetary boundary layer (PBL) turbulence physics, grid-explicit microphysics, a CPS, and enhanced horizontal diffusion. Some of the conclusions include the following: 1) Enhanced parameterized vertical mixing in the turbulent kinetic energy (TKE) turbulence scheme has shown marked improvements in the simulated fields. 2) Use of a CPS on the 4-km grid improved the precipitation and low-level wind results. 3) Use of the Hong and Pan Medium-Range Forecast PBL scheme showed larger model errors within the PBL and a clear tendency to predict much deeper PBL heights than the TKE scheme. 4) Combining observation-nudging FDDA with a CPS produced the best overall simulations. 5) Finer horizontal resolution does not always produce better simulations, especially in convectively unstable environments, and a new CPS suitable for 4-km resolution is needed. 6

  13. Modeling Air-Quality in Complex Terrain Using Mesoscale and ...

    Air-quality in a complex terrain (Colorado-River-Valley/Grand-Canyon Area, Southwest U.S.) is modeled using a higher-order closure mesoscale model and a higher-order closure dispersion model. Non-reactive tracers have been released in the Colorado-River valley, during winter and summer 1992, to study the ...

  14. Mesoscale meteorological model based on radioactive explosion cloud simulation

    Zheng Yi; Zhang Yan; Ying Chuntong

    2008-01-01

    In order to simulate nuclear explosion and dirty bomb radioactive cloud movement and concentration distribution, mesoscale meteorological model RAMS was used. Particles-size, size-active distribution and gravitational fallout in the cloud were considered. The results show that the model can simulate the 'mushroom' clouds of explosion. Three-dimension fluid field and radioactive concentration field were received. (authors)

  15. Intercomparison of state-of-the-art models for wind energy resources with mesoscale models:

    Olsen, Bjarke Tobias; Hahmann, Andrea N.; Sempreviva, Anna Maria; Badger, Jake; Joergensen, Hans E.

    2016-04-01

    vertical resolution, model parameterizations, surface roughness length) that could be used to group the various models and interpret the results of the intercomparison. 3. Main body abstract Twenty separate entries were received by the deadline of 31 March 2015. They included simulations done with various versions of the Weather Research and Forecast (WRF) model, but also of six other well-known mesoscale models. The various entries represent an excellent sample of the various models used in by the wind energy industry today. The analysis of the submitted time series included comparison to observations, summarized with well-known measures such as biases, RMSE, correlations, and of sector-wise statistics, e.g. frequency and Weibull A and k. The comparison also includes the observed and modeled temporal spectra. The various statistics were grouped as a function of the various models, their spatial resolution, forcing data, and the various integration methods. Many statistics have been computed and will be presented in addition to those shown in the Helsinki presentation. 4. Conclusions The analysis of the time series from twenty entries has shown to be an invaluable source of information about state of the art in wind modeling with mesoscale models. Biases between the simulated and observed wind speeds at hub heights (80-100 m AGL) from the various models are around ±1.0 m/s and fairly independent of the site and do not seem to be directly related to the model horizontal resolution used in the modeling. As probably expected, the wind speeds from the simulations using the various version of the WRF model cluster close to each other, especially in their description of the wind profile.

  16. Mesoscale modeling of solute precipitation and radiation damage

    Zhang, Yongfeng [Idaho National Lab. (INL), Idaho Falls, ID (United States); Schwen, Daniel [Idaho National Lab. (INL), Idaho Falls, ID (United States); Ke, Huibin [Idaho National Lab. (INL), Idaho Falls, ID (United States); Univ. of Wisconsin, Madison, WI (United States); Bai, Xianming [Idaho National Lab. (INL), Idaho Falls, ID (United States); Hales, Jason [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-09-01

    This report summarizes the low length scale effort during FY 2014 in developing mesoscale capabilities for microstructure evolution in reactor pressure vessels. During operation, reactor pressure vessels are subject to hardening and embrittlement caused by irradiation-induced defect accumulation and irradiation-enhanced solute precipitation. Both defect production and solute precipitation start from the atomic scale, and manifest their eventual effects as degradation in engineering-scale properties. To predict the property degradation, multiscale modeling and simulation are needed to deal with the microstructure evolution, and to link the microstructure feature to material properties. In this report, the development of mesoscale capabilities for defect accumulation and solute precipitation are summarized. Atomic-scale efforts that supply information for the mesoscale capabilities are also included.

  17. Initializing a Mesoscale Boundary-Layer Model with Radiosonde Observations

    Berri, Guillermo J.; Bertossa, Germán

    2018-01-01

    A mesoscale boundary-layer model is used to simulate low-level regional wind fields over the La Plata River of South America, a region characterized by a strong daily cycle of land-river surface-temperature contrast and low-level circulations of sea-land breeze type. The initial and boundary conditions are defined from a limited number of local observations and the upper boundary condition is taken from the only radiosonde observations available in the region. The study considers 14 different upper boundary conditions defined from the radiosonde data at standard levels, significant levels, level of the inversion base and interpolated levels at fixed heights, all of them within the first 1500 m. The period of analysis is 1994-2008 during which eight daily observations from 13 weather stations of the region are used to validate the 24-h surface-wind forecast. The model errors are defined as the root-mean-square of relative error in wind-direction frequency distribution and mean wind speed per wind sector. Wind-direction errors are greater than wind-speed errors and show significant dispersion among the different upper boundary conditions, not present in wind speed, revealing a sensitivity to the initialization method. The wind-direction errors show a well-defined daily cycle, not evident in wind speed, with the minimum at noon and the maximum at dusk, but no systematic deterioration with time. The errors grow with the height of the upper boundary condition level, in particular wind direction, and double the errors obtained when the upper boundary condition is defined from the lower levels. The conclusion is that defining the model upper boundary condition from radiosonde data closer to the ground minimizes the low-level wind-field errors throughout the region.

  18. Role of land state in a high resolution mesoscale model

    ... Proceedings – Mathematical Sciences · Resonance – Journal of Science ... Land surface characteristics; high resolution mesoscale model; Uttarakhand ... to predict realistic location, timing, amount,intensity and distribution of rainfall ... region embedded within two low pressure centers over Arabian Seaand Bay of Bengal.

  19. Calculation of extreme wind atlases using mesoscale modeling. Final report

    Larsén, Xiaoli Guo; Badger, Jake

    This is the final report of the project PSO-10240 "Calculation of extreme wind atlases using mesoscale modeling". The overall objective is to improve the estimation of extreme winds by developing and applying new methodologies to confront the many weaknesses in the current methodologies as explai...

  20. An Initial Assessment of the Impact of CYGNSS Ocean Surface Wind Assimilation on Navy Global and Mesoscale Numerical Weather Prediction

    Baker, N. L.; Tsu, J.; Swadley, S. D.

    2017-12-01

    We assess the impact of assimilation of CYclone Global Navigation Satellite System (CYGNSS) ocean surface winds observations into the NAVGEM[i] global and COAMPS®[ii] mesoscale numerical weather prediction (NWP) systems. Both NAVGEM and COAMPS® used the NRL 4DVar assimilation system NAVDAS-AR[iii]. Long term monitoring of the NAVGEM Forecast Sensitivity Observation Impact (FSOI) indicates that the forecast error reduction for ocean surface wind vectors (ASCAT and WindSat) are significantly larger than for SSMIS wind speed observations. These differences are larger than can be explained by simply two pieces of information (for wind vectors) versus one (wind speed). To help understand these results, we conducted a series of Observing System Experiments (OSEs) to compare the assimilation of ASCAT wind vectors with the equivalent (computed) ASCAT wind speed observations. We found that wind vector assimilation was typically 3 times more effective at reducing the NAVGEM forecast error, with a higher percentage of beneficial observations. These results suggested that 4DVar, in the absence of an additional nonlinear outer loop, has limited ability to modify the analysis wind direction. We examined several strategies for assimilating CYGNSS ocean surface wind speed observations. In the first approach, we assimilated CYGNSS as wind speed observations, following the same methodology used for SSMIS winds. The next two approaches converted CYGNSS wind speed to wind vectors, using NAVGEM sea level pressure fields (following Holton, 1979), and using NAVGEM 10-m wind fields with the AER Variational Analysis Method. Finally, we compared these methods to CYGNSS wind speed assimilation using multiple outer loops with NAVGEM Hybrid 4DVar. Results support the earlier studies suggesting that NAVDAS-AR wind speed assimilation is sub-optimal. We present detailed results from multi-month NAVGEM assimilation runs along with case studies using COAMPS®. Comparisons include the fit of

  1. Parameterization of phase change of water in a mesoscale model

    Levkov, L; Eppel, D; Grassl, H

    1987-01-01

    A parameterization scheme of phase change of water is suggested to be used in the 3-D numerical nonhydrostatic model GESIMA. The microphysical formulation follows the so-called bulk technique. With this procedure the net production rates in the balance equations for water and potential temperature are given both for liquid and ice-phase. Convectively stable as well as convectively unstable mesoscale systems are considered. With 2 figs..

  2. Mesoscale modeling of metal-loaded high explosives

    Bdzil, John Bohdan [Los Alamos National Laboratory; Lieberthal, Brandon [UNIV OF ILLINOIS; Srewart, Donald S [UNIV OF ILLINOIS

    2010-01-01

    We describe a 3D approach to modeling multi-phase blast explosive, which is primarily condensed explosive by volume with inert embedded particles. These embedded particles are uniform in size and placed on the array of a regular lattice. The asymptotic theory of detonation shock dynamics governs the detonation shock propagation in the explosive. Mesoscale hydrodynamic simulations are used to show how the particles are compressed, deformed, and accelerated by the high-speed detonation products flow.

  3. Development and analysis of prognostic equations for mesoscale kinetic energy and mesoscale (subgrid scale) fluxes for large-scale atmospheric models

    Avissar, Roni; Chen, Fei

    1993-01-01

    Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes

  4. Mesoscale modeling: solving complex flows in biology and biotechnology.

    Mills, Zachary Grant; Mao, Wenbin; Alexeev, Alexander

    2013-07-01

    Fluids are involved in practically all physiological activities of living organisms. However, biological and biorelated flows are hard to analyze due to the inherent combination of interdependent effects and processes that occur on a multitude of spatial and temporal scales. Recent advances in mesoscale simulations enable researchers to tackle problems that are central for the understanding of such flows. Furthermore, computational modeling effectively facilitates the development of novel therapeutic approaches. Among other methods, dissipative particle dynamics and the lattice Boltzmann method have become increasingly popular during recent years due to their ability to solve a large variety of problems. In this review, we discuss recent applications of these mesoscale methods to several fluid-related problems in medicine, bioengineering, and biotechnology. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Description of the University of Auckland Global Mars Mesoscale Meteorological Model (GM4)

    Wing, D. R.; Austin, G. L.

    2005-08-01

    The University of Auckland Global Mars Mesoscale Meteorological Model (GM4) is a numerical weather prediction model of the Martian atmosphere that has been developed through the conversion of the Penn State University / National Center for Atmospheric Research fifth generation mesoscale model (MM5). The global aspect of this model is self consistent, overlapping, and forms a continuous domain around the entire planet, removing the need to provide boundary conditions other than at initialisation, yielding independence from the constraint of a Mars general circulation model. The brief overview of the model will be given, outlining the key physical processes and setup of the model. Comparison between data collected from Mars Pathfinder during its 1997 mission and simulated conditions using GM4 have been performed. Diurnal temperature variation as predicted by the model shows very good correspondence with the surface truth data, to within 5 K for the majority of the diurnal cycle. Mars Viking Data is also compared with the model, with good agreement. As a further means of validation for the model, various seasonal comparisons of surface and vertical atmospheric structure are conducted with the European Space Agency AOPP/LMD Mars Climate Database. Selected simulations over regions of interest will also be presented.

  6. A Distributed Hydrological model Forced by DIMP2 Data and the WRF Mesoscale model

    Wayand, N. E.

    2010-12-01

    Forecasted warming over the next century will drastically reduce seasonal snowpack that provides 40% of the world’s drinking water. With increased climate warming, droughts may occur more frequently, which will increase society’s reliance on this same summer snowpack as a water supply. This study aims to reduce driving data errors that lead to poor simulations of snow ablation and accumulation, and streamflow. Results from the Distributed Hydrological Model Intercomparison Project Phase 2 (DMIP2) project using the Distributed Hydrology Soil and Vegetation Model (DHSVM) highlighted the critical need for accurate driving data that distributed models require. Currently, the meteorological driving data for distributed hydrological models commonly rely on interpolation techniques between a network of observational stations, as well as historical monthly means. This method is limited by two significant issues: snowpack is stored at high elevations, where interpolation techniques perform poorly due to sparse observations, and historic climatological means may be unsuitable in a changing climate. Mesoscale models may provide a physically-based approach to supplement surface observations over high-elevation terrain. Initial results have shown that while temperature lapse rates are well represented by multiple mesoscale models, significant precipitation biases are dependent on the particular model microphysics. We evaluate multiple methods of downscaling surface variables from the Weather and Research Forecasting (WRF) model that are then used to drive DHSVM over the North Fork American River basin in California. A comparison between each downscaled driving data set and paired DHSVM results to observations will determine how much improvement in simulated streamflow and snowpack are gained at the expense of each additional degree of downscaling. Our results from DMIP2 will be used as a benchmark for the best available DHSVM run using all available observational data. The

  7. Mesoscale Model Data Preparation and Execution: A New Method Utilizing the Internet

    Kirby, Stephen

    2002-01-01

    In order to streamline and simplify the methodologies required to obtain and process the requisite meteorological data for mesoscale meteorological models such as the Battlescale Forecast Model (BFM...

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

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

    2012-12-01

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

  9. Satellite-derived vertical profiles of temperature and dew point for mesoscale weather forecast

    Masselink, Thomas; Schluessel, P.

    1995-12-01

    Weather forecast-models need spatially high resolutioned vertical profiles of temperature and dewpoint for their initialisation. These profiles can be supplied by a combination of data from the Tiros-N Operational Vertical Sounder (TOVS) and the imaging Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbiting sate!- lites. In cloudy cases the profiles derived from TOVS data only are of insufficient accuracy. The stanthrd deviations from radiosonde ascents or numerical weather analyses likely exceed 2 K in temperature and 5Kin dewpoint profiles. It will be shown that additional cloud information as retrieved from AVHIRR allows a significant improvement in theaccuracy of vertical profiles. The International TOVS Processing Package (ITPP) is coupled to an algorithm package called AVHRR Processing scheme Over cLouds, Land and Ocean (APOLLO) where parameters like cloud fraction and cloud-top temperature are determined with higher accuracy than obtained from TOVS retrieval alone. Furthermore, a split-window technique is applied to the cloud-free AVHRR imagery in order to derive more accurate surface temperatures than can be obtained from the pure TOVS retrieval. First results of the impact of AVHRR cloud detection on the quality of the profiles are presented. The temperature and humidity profiles of different retrieval approaches are validated against analyses of the European Centre for Medium-Range Weatherforecasts.

  10. LBM estimation of thermal conductivity in meso-scale modelling

    Grucelski, A

    2016-01-01

    Recently, there is a growing engineering interest in more rigorous prediction of effective transport coefficients for multicomponent, geometrically complex materials. We present main assumptions and constituents of the meso-scale model for the simulation of the coal or biomass devolatilisation with the Lattice Boltzmann method. For the results, the estimated values of the thermal conductivity coefficient of coal (solids), pyrolytic gases and air matrix are presented for a non-steady state with account for chemical reactions in fluid flow and heat transfer. (paper)

  11. Optogenetic stimulation of a meso-scale human cortical model

    Selvaraj, Prashanth; Szeri, Andrew; Sleigh, Jamie; Kirsch, Heidi

    2015-03-01

    Neurological phenomena like sleep and seizures depend not only on the activity of individual neurons, but on the dynamics of neuron populations as well. Meso-scale models of cortical activity provide a means to study neural dynamics at the level of neuron populations. Additionally, they offer a safe and economical way to test the effects and efficacy of stimulation techniques on the dynamics of the cortex. Here, we use a physiologically relevant meso-scale model of the cortex to study the hypersynchronous activity of neuron populations during epileptic seizures. The model consists of a set of stochastic, highly non-linear partial differential equations. Next, we use optogenetic stimulation to control seizures in a hyperexcited cortex, and to induce seizures in a normally functioning cortex. The high spatial and temporal resolution this method offers makes a strong case for the use of optogenetics in treating meso scale cortical disorders such as epileptic seizures. We use bifurcation analysis to investigate the effect of optogenetic stimulation in the meso scale model, and its efficacy in suppressing the non-linear dynamics of seizures.

  12. A three-dimensional viscous topography mesoscale model

    Eichhorn, J; Flender, M; Kandlbinder, T; Panhans, W G; Trautmann, T; Zdunkowski, W G [Mainz Univ. (Germany). Inst. fuer Physik der Atmosphaere; Cui, K; Ries, R; Siebert, J; Wedi, N

    1997-11-01

    This study describes the theoretical foundation and applications of a newly designed mesoscale model named CLIMM (climate model Mainz). In contrast to terrain following coordinates, a cartesian grid is used to keep the finite difference equations as simple as possible. The method of viscous topography is applied to the flow part of the model. Since the topography intersects the cartesian grid cells, the new concept of boundary weight factors is introduced for the solution of Poisson`s equation. A three-dimensional radiosity model was implemented to handle radiative transfer at the ground. The model is applied to study thermally induced circulations and gravity waves at an idealized mountain. Furthermore, CLIMM was used to simulate typical wind and temperature distributions for the city of Mainz and its rural surroundings. It was found that the model in all cases produced realistic results. (orig.) 38 refs.

  13. Mesoscale modeling of amorphous metals by shear transformation zone dynamics

    Homer, Eric R.; Schuh, Christopher A.

    2009-01-01

    A new mesoscale modeling technique for the thermo-mechanical behavior of metallic glasses is proposed. The modeling framework considers the shear transformation zone (STZ) as the fundamental unit of deformation, and coarse-grains an amorphous collection of atoms into an ensemble of STZs on a mesh. By employing finite element analysis and a kinetic Monte Carlo algorithm, the modeling technique is capable of simulating glass processing and deformation on time and length scales greater than those usually attainable by atomistic modeling. A thorough explanation of the framework is presented, along with a specific two-dimensional implementation for a model metallic glass. The model is shown to capture the basic behaviors of metallic glasses, including high-temperature homogeneous flow following the expected constitutive law, and low-temperature strain localization into shear bands. Details of the effects of processing and thermal history on the glass structure and properties are also discussed.

  14. High-resolution numerical modeling of mesoscale island wakes and sensitivity to static topographic relief data

    C. G. Nunalee

    2015-08-01

    Full Text Available Recent decades have witnessed a drastic increase in the fidelity of numerical weather prediction (NWP modeling. Currently, both research-grade and operational NWP models regularly perform simulations with horizontal grid spacings as fine as 1 km. This migration towards higher resolution potentially improves NWP model solutions by increasing the resolvability of mesoscale processes and reducing dependency on empirical physics parameterizations. However, at the same time, the accuracy of high-resolution simulations, particularly in the atmospheric boundary layer (ABL, is also sensitive to orographic forcing which can have significant variability on the same spatial scale as, or smaller than, NWP model grids. Despite this sensitivity, many high-resolution atmospheric simulations do not consider uncertainty with respect to selection of static terrain height data set. In this paper, we use the Weather Research and Forecasting (WRF model to simulate realistic cases of lower tropospheric flow over and downstream of mountainous islands using the default global 30 s United States Geographic Survey terrain height data set (GTOPO30, the Shuttle Radar Topography Mission (SRTM, and the Global Multi-resolution Terrain Elevation Data set (GMTED2010 terrain height data sets. While the differences between the SRTM-based and GMTED2010-based simulations are extremely small, the GTOPO30-based simulations differ significantly. Our results demonstrate cases where the differences between the source terrain data sets are significant enough to produce entirely different orographic wake mechanics, such as vortex shedding vs. no vortex shedding. These results are also compared to MODIS visible satellite imagery and ASCAT near-surface wind retrievals. Collectively, these results highlight the importance of utilizing accurate static orographic boundary conditions when running high-resolution mesoscale models.

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

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

    2018-03-01

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

  16. North American Mesoscale Forecast System (NAM) [12 km

    National Oceanic and Atmospheric Administration, Department of Commerce — The North American Mesoscale Forecast System (NAM) is one of the major regional weather forecast models run by the National Centers for Environmental Prediction...

  17. Meso-scale modeling of irradiated concrete in test reactor

    Giorla, A.; Vaitová, M.; Le Pape, Y.; Štemberk, P.

    2015-01-01

    Highlights: • A meso-scale finite element model for irradiated concrete is developed. • Neutron radiation-induced volumetric expansion is a predominant degradation mode. • Confrontation with expansion and damage obtained from experiments is successful. • Effects of paste shrinkage, creep and ductility are discussed. - Abstract: A numerical model accounting for the effects of neutron irradiation on concrete at the mesoscale is detailed in this paper. Irradiation experiments in test reactor (Elleuch et al., 1972), i.e., in accelerated conditions, are simulated. Concrete is considered as a two-phase material made of elastic inclusions (aggregate) subjected to thermal and irradiation-induced swelling and embedded in a cementitious matrix subjected to shrinkage and thermal expansion. The role of the hardened cement paste in the post-peak regime (brittle-ductile transition with decreasing loading rate), and creep effects are investigated. Radiation-induced volumetric expansion (RIVE) of the aggregate cause the development and propagation of damage around the aggregate which further develops in bridging cracks across the hardened cement paste between the individual aggregate particles. The development of damage is aggravated when shrinkage occurs simultaneously with RIVE during the irradiation experiment. The post-irradiation expansion derived from the simulation is well correlated with the experimental data and, the obtained damage levels are fully consistent with previous estimations based on a micromechanical interpretation of the experimental post-irradiation elastic properties (Le Pape et al., 2015). The proposed modeling opens new perspectives for the interpretation of test reactor experiments in regards to the actual operation of light water reactors.

  18. Meso-scale modeling of irradiated concrete in test reactor

    Giorla, A. [Oak Ridge National Laboratory, One Bethel Valley Road, Oak Ridge, TN 37831 (United States); Vaitová, M. [Czech Technical University, Thakurova 7, 166 29 Praha 6 (Czech Republic); Le Pape, Y., E-mail: lepapeym@ornl.gov [Oak Ridge National Laboratory, One Bethel Valley Road, Oak Ridge, TN 37831 (United States); Štemberk, P. [Czech Technical University, Thakurova 7, 166 29 Praha 6 (Czech Republic)

    2015-12-15

    Highlights: • A meso-scale finite element model for irradiated concrete is developed. • Neutron radiation-induced volumetric expansion is a predominant degradation mode. • Confrontation with expansion and damage obtained from experiments is successful. • Effects of paste shrinkage, creep and ductility are discussed. - Abstract: A numerical model accounting for the effects of neutron irradiation on concrete at the mesoscale is detailed in this paper. Irradiation experiments in test reactor (Elleuch et al., 1972), i.e., in accelerated conditions, are simulated. Concrete is considered as a two-phase material made of elastic inclusions (aggregate) subjected to thermal and irradiation-induced swelling and embedded in a cementitious matrix subjected to shrinkage and thermal expansion. The role of the hardened cement paste in the post-peak regime (brittle-ductile transition with decreasing loading rate), and creep effects are investigated. Radiation-induced volumetric expansion (RIVE) of the aggregate cause the development and propagation of damage around the aggregate which further develops in bridging cracks across the hardened cement paste between the individual aggregate particles. The development of damage is aggravated when shrinkage occurs simultaneously with RIVE during the irradiation experiment. The post-irradiation expansion derived from the simulation is well correlated with the experimental data and, the obtained damage levels are fully consistent with previous estimations based on a micromechanical interpretation of the experimental post-irradiation elastic properties (Le Pape et al., 2015). The proposed modeling opens new perspectives for the interpretation of test reactor experiments in regards to the actual operation of light water reactors.

  19. Improvement of a mesoscale atmospheric dynamic model PHYSIC. Utilization of output from synoptic numerical prediction model for initial and boundary condition

    Nagai, Haruyasu; Yamazawa, Hiromi

    1995-03-01

    This report describes the improvement of the mesoscale atmospheric dynamic model which is a part of the atmospheric dispersion calculation model PHYSIC. To introduce large-scale meteorological changes into the mesoscale atmospheric dynamic model, it is necessary to make the initial and boundary conditions of the model by using GPV (Grid Point Value) which is the output of the numerical weather prediction model of JMA (Japan Meteorological Agency). Therefore, the program which preprocesses the GPV data to make a input file to PHYSIC was developed and the input process and the methods of spatial and temporal interpolation were improved to correspond to the file. Moreover, the methods of calculating the cloud amount and ground surface moisture from GPV data were developed and added to the model code. As the example of calculation by the improved model, the wind field simulations of a north-west monsoon in winter and a sea breeze in summer in the Tokai area were also presented. (author)

  20. EMMA model: an advanced operational mesoscale air quality model for urban and regional environments

    Jose, R.S.; Rodriguez, M.A.; Cortes, E.; Gonzalez, R.M.

    1999-01-01

    Mesoscale air quality models are an important tool to forecast and analyse the air quality in regional and urban areas. In recent years an increased interest has been shown by decision makers in these types of software tools. The complexity of such a model has grown exponentially with the increase of computer power. Nowadays, medium workstations can run operational versions of these modelling systems successfully. Presents a complex mesoscale air quality model which has been installed in the Environmental Office of the Madrid community (Spain) in order to forecast accurately the ozone, nitrogen dioxide and sulphur dioxide air concentrations in a 3D domain centred on Madrid city. Describes the challenging scientific matters to be solved in order to develop an operational version of the atmospheric mesoscale numerical pollution model for urban and regional areas (ANA). Some encouraging results have been achieved in the attempts to improve the accuracy of the predictions made by the version already installed. (Author)

  1. Mesoscale influence on long-range transport — evidence from ETEX modelling and observations

    Sørensen, Jens Havskov; Rasmussen, Alix; Ellermann, Thomas; Lyck, Erik

    During the first European Tracer Experiment (ETEX) tracer gas was released from a site in Brittany, France, and subsequently observed over a range of 2000 km. Hourly measurements were taken at the National Environmental Research Institute (NERI) located at Risø, Denmark, using two measurement techniques. At this location, the observed concentration time series shows a double-peak structure occurring between two and three days after the release. By using the Danish Emergency Response Model of the Atmosphere (DERMA), which is developed at the Danish Meteorological Institute (DMI), simulations of the dispersion of the tracer gas have been performed. Using numerical weather-prediction data from the European Centre for Medium-Range Weather Forecast (ECMWF) by DERMA, the arrival time of the tracer is quite well predicted, so also is the duration of the passage of the plume, but the double-peak structure is not reproduced. However, using higher-resolution data from the DMI version of the HIgh Resolution Limited Area Model (DMI-HIRLAM), DERMA reproduces the observed structure very well. The double-peak structure is caused by the influence of a mesoscale anti-cyclonic eddy on the tracer gas plume about one day earlier.

  2. A mesoscale chemical transport model (MEDIUM) nested in a global chemical transport model (MEDIANTE)

    Claveau, J; Ramaroson, R [Office National d` Etudes et de Recherches Aerospatiales (ONERA), 92 - Chatillon (France)

    1998-12-31

    The lower stratosphere and upper troposphere (UT-LS) are frequently subject to mesoscale or local scale exchange of air masses occurring along discontinuities. This exchange (e.g. downward) can constitute one of the most important source of ozone from the stratosphere down to the middle troposphere where strong mixing dilutes the air mass and competing the non-linear chemistry. The distribution of the chemical species in the troposphere and the lower stratosphere depends upon various source emissions, e.g. from polluted boundary layer or from aircraft emissions. Global models, as well as chemical transport models describe the climatological state of the atmosphere and are not able to describe correctly the stratosphere and troposphere exchange. Mesoscale models go further in the description of smaller scales and can reasonably include a rather detailed chemistry. They can be used to assess the budget of NO{sub x} from aircraft emissions in a mesoscale domain. (author) 4 refs.

  3. A mesoscale chemical transport model (MEDIUM) nested in a global chemical transport model (MEDIANTE)

    Claveau, J.; Ramaroson, R. [Office National d`Etudes et de Recherches Aerospatiales (ONERA), 92 - Chatillon (France)

    1997-12-31

    The lower stratosphere and upper troposphere (UT-LS) are frequently subject to mesoscale or local scale exchange of air masses occurring along discontinuities. This exchange (e.g. downward) can constitute one of the most important source of ozone from the stratosphere down to the middle troposphere where strong mixing dilutes the air mass and competing the non-linear chemistry. The distribution of the chemical species in the troposphere and the lower stratosphere depends upon various source emissions, e.g. from polluted boundary layer or from aircraft emissions. Global models, as well as chemical transport models describe the climatological state of the atmosphere and are not able to describe correctly the stratosphere and troposphere exchange. Mesoscale models go further in the description of smaller scales and can reasonably include a rather detailed chemistry. They can be used to assess the budget of NO{sub x} from aircraft emissions in a mesoscale domain. (author) 4 refs.

  4. Probabilistic flood damage modelling at the meso-scale

    Kreibich, Heidi; Botto, Anna; Schröter, Kai; Merz, Bruno

    2014-05-01

    Decisions on flood risk management and adaptation are usually based on risk analyses. Such analyses are associated with significant uncertainty, even more if changes in risk due to global change are expected. Although uncertainty analysis and probabilistic approaches have received increased attention during the last years, they are still not standard practice for flood risk assessments. Most damage models have in common that complex damaging processes are described by simple, deterministic approaches like stage-damage functions. Novel probabilistic, multi-variate flood damage models have been developed and validated on the micro-scale using a data-mining approach, namely bagging decision trees (Merz et al. 2013). In this presentation we show how the model BT-FLEMO (Bagging decision Tree based Flood Loss Estimation MOdel) can be applied on the meso-scale, namely on the basis of ATKIS land-use units. The model is applied in 19 municipalities which were affected during the 2002 flood by the River Mulde in Saxony, Germany. The application of BT-FLEMO provides a probability distribution of estimated damage to residential buildings per municipality. Validation is undertaken on the one hand via a comparison with eight other damage models including stage-damage functions as well as multi-variate models. On the other hand the results are compared with official damage data provided by the Saxon Relief Bank (SAB). The results show, that uncertainties of damage estimation remain high. Thus, the significant advantage of this probabilistic flood loss estimation model BT-FLEMO is that it inherently provides quantitative information about the uncertainty of the prediction. Reference: Merz, B.; Kreibich, H.; Lall, U. (2013): Multi-variate flood damage assessment: a tree-based data-mining approach. NHESS, 13(1), 53-64.

  5. Implementation of meso-scale radioactive dispersion model for GPU

    Sunarko [National Nuclear Energy Agency of Indonesia (BATAN), Jakarta (Indonesia). Nuclear Energy Assessment Center; Suud, Zaki [Bandung Institute of Technology (ITB), Bandung (Indonesia). Physics Dept.

    2017-05-15

    Lagrangian Particle Dispersion Method (LPDM) is applied to model atmospheric dispersion of radioactive material in a meso-scale of a few tens of kilometers for site study purpose. Empirical relationships are used to determine the dispersion coefficient for various atmospheric stabilities. Diagnostic 3-D wind-field is solved based on data from one meteorological station using mass-conservation principle. Particles representing radioactive pollutant are dispersed in the wind-field as a point source. Time-integrated air concentration is calculated using kernel density estimator (KDE) in the lowest layer of the atmosphere. Parallel code is developed for GTX-660Ti GPU with a total of 1 344 scalar processors using CUDA. A test of 1-hour release discovers that linear speedup is achieved starting at 28 800 particles-per-hour (pph) up to about 20 x at 14 4000 pph. Another test simulating 6-hour release with 36 000 pph resulted in a speedup of about 60 x. Statistical analysis reveals that resulting grid doses are nearly identical in both CPU and GPU versions of the code.

  6. Modeling of Mesoscale Variability in Biofilm Shear Behavior.

    Pallab Barai

    Full Text Available Formation of bacterial colonies as biofilm on the surface/interface of various objects has the potential to impact not only human health and disease but also energy and environmental considerations. Biofilms can be regarded as soft materials, and comprehension of their shear response to external forces is a key element to the fundamental understanding. A mesoscale model has been presented in this article based on digitization of a biofilm microstructure. Its response under externally applied shear load is analyzed. Strain stiffening type behavior is readily observed under high strain loads due to the unfolding of chains within soft polymeric substrate. Sustained shear loading of the biofilm network results in strain localization along the diagonal direction. Rupture of the soft polymeric matrix can potentially reduce the intercellular interaction between the bacterial cells. Evolution of stiffness within the biofilm network under shear reveals two regimes: a initial increase in stiffness due to strain stiffening of polymer matrix, and b eventual reduction in stiffness because of tear in polymeric substrate.

  7. Development of extended WRF variational data assimilation system (WRFDA) for WRF non-hydrostatic mesoscale model

    Pattanayak, Sujata; Mohanty, U. C.

    2018-06-01

    The paper intends to present the development of the extended weather research forecasting data assimilation (WRFDA) system in the framework of the non-hydrostatic mesoscale model core of weather research forecasting system (WRF-NMM), as an imperative aspect of numerical modeling studies. Though originally the WRFDA provides improved initial conditions for advanced research WRF, we have successfully developed a unified WRFDA utility that can be used by the WRF-NMM core, as well. After critical evaluation, it has been strategized to develop a code to merge WRFDA framework and WRF-NMM output. In this paper, we have provided a few selected implementations and initial results through single observation test, and background error statistics like eigenvalues, eigenvector and length scale among others, which showcase the successful development of extended WRFDA code for WRF-NMM model. Furthermore, the extended WRFDA system is applied for the forecast of three severe cyclonic storms: Nargis (27 April-3 May 2008), Aila (23-26 May 2009) and Jal (4-8 November 2010) formed over the Bay of Bengal. Model results are compared and contrasted within the analysis fields and later on with high-resolution model forecasts. The mean initial position error is reduced by 33% with WRFDA as compared to GFS analysis. The vector displacement errors in track forecast are reduced by 33, 31, 30 and 20% to 24, 48, 72 and 96 hr forecasts respectively, in data assimilation experiments as compared to control run. The model diagnostics indicates successful implementation of WRFDA within the WRF-NMM system.

  8. A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

    Pan, Yang; Archer, Cristina L.

    2018-04-01

    To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.

  9. Do we need full mesoscale models to simulate the urban heat island? A study over the city of Barcelona.

    García-Díez, Markel; Ballester, Joan; De Ridder, Koen; Hooyberghs, Hans; Lauwaet, Dirk; Rodó, Xavier

    2016-04-01

    As most of the population lives in urban environments, the simulation of the urban climate has become an important part of the global climate change impact assessment. However, due to the high resolution required, these simulations demand a large amount of computational resources. Here we present a comparison between a simplified fast urban climate model (UrbClim) and a widely used full mesoscale model, the Weather Research and Forecasting (WRF) model, over the city of Barcelona. In order to check the advantages and disadvantages of each approach, both simulations were compared with station data and with land surface temperature observations retrieved by satellites, focusing on the urban heat island. The effect of changing the UrbClim boundary conditions was studied too, by using low resolution global reanalysis data (70 km) and a higher resolution forecast model (15 km). Finally, a strict comparison of the computational resources consumed by both models was carried out. Results show that, generally, the performance of the simple model is comparable to or better than the mesoscale model. The exception are the winds and the day-to-day correlation in the reanalysis driven run, but these problems disappear when taking the boundary conditions from a higher resolution global model. UrbClim was found to run 133 times faster than WRF, using 4x times higher resolution and, thus, it is an efficient solution for running long climate change simulations over large city ensembles.

  10. Models of Weather Impact on Air Traffic

    Kulkarni, Deepak; Wang, Yao

    2017-01-01

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

  11. An Objective Verification of the North American Mesoscale Model for Kennedy Space Center and Cape Canaveral Air Force Station

    Bauman, William H., III

    2010-01-01

    The 45th Weather Squadron (45 WS) Launch Weather Officers (LWO's) use the 12-km resolution North American Mesoscale (NAM) model (MesoNAM) text and graphical product forecasts extensively to support launch weather operations. However, the actual performance of the model at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) has not been measured objectively. In order to have tangible evidence of model performance, the 45 WS tasked the Applied Meteorology Unit (AMU; Bauman et ai, 2004) to conduct a detailed statistical analysis of model output compared to observed values. The model products are provided to the 45 WS by ACTA, Inc. and include hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The objective analysis compared the MesoNAM forecast winds, temperature (T) and dew pOint (T d), as well as the changes in these parameters over time, to the observed values from the sensors in the KSC/CCAFS wind tower network shown in Table 1. These objective statistics give the forecasters knowledge of the model's strengths and weaknesses, which will result in improved forecasts for operations.

  12. Modelling study of mesoscale cyclogenesis over Ross Sea, Antarctica, on February 18, 1988

    Stortini, M.; Morelli, S.; Marchesi, S. [Modena e Reggio Emilia Univ., Modena (Italy). Dipt. di Scienze dell' Ingegneria, Sez. Osservatorio Geofisico

    2000-04-01

    This paper examines the development of a summer event of mesoscale cyclogenesis off the coast of Victoria Land in the presence of katabatic winds, by means of numerical simulations. These refer to the period from 00 UTC 17 February to 00 UTC 19 February 1988 and were performed using the hydrostatic ETA (1993 version) limited area model with resolution 55 km x 55 km x 17 levels. The ETA model reproduces katabatic winds from Terra Nova Bay and a trough on the southwestern Ross Sea. A cyclonic vortex is simulated in the trough, even though it is weaker than the one present in the analysis initialized by the European Center for Medium Range Weather Forecast (Reading, United Kingdom). Idealized simulations with varied surface conditions were also performed. In particular, an ice-covered ocean acts to weaken the atmospheric phenomena, while a no-mountain simulation emphasizes the influence of the orography and the cold winds from the coast of Victoria Land on the mesocyclonic activity.

  13. A Study of Mesoscale Gravity Waves over the North Atlantic with Satellite Observations and a Mesoscale Model

    Wu, Dong L.; Zhang, Fuqing

    2004-01-01

    Satellite microwave data are used to study gravity wave properties and variabilities over the northeastern United States and the North Atlantic in the December-January periods. The gravity waves in this region, found in many winters, can reach the stratopause with growing amplitude. The Advanced Microwave Sounding Unit-A (AMSU-A) observations show that the wave occurrences are correlated well with the intensity and location of the tropospheric baroclinic jet front systems. To further investigate the cause(s) and properties of the North Atlantic gravity waves, we focus on a series of wave events during 19-21 January 2003 and compare AMSU-A observations to simulations from a mesoscale model (MM5). The simulated gravity waves compare qualitatively well with the satellite observations in terms of wave structures, timing, and overall morphology. Excitation mechanisms of these large-amplitude waves in the troposphere are complex and subject to further investigations.

  14. An Evaluation of Mesoscale Model Based Model Output Statistics (MOS) During the 2002 Olympic and Paralympic Winter Games

    Hart, Kenneth

    2003-01-01

    The skill of a mesoscale model based Model Output Statistics (MOS) system that provided hourly forecasts for 18 sites over northern Utah during the 2002 Winter Olympic and Paralympic Games is evaluated...

  15. Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

    M. P. Mittermaier

    2008-05-01

    Full Text Available A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used.

    The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

  16. A three-dimensional meso-scale modeling for helium bubble growth in metals

    Suzudo, T.; Kaburaki, H.; Wakai, E.

    2007-01-01

    A three-dimensional meso-scale computer model using a Monte-Carlo simulation method has been proposed to simulate the helium bubble growth in metals. The primary merit of this model is that it enables the visual comparison between the microstructure observed by the TEM imaging and those by calculations. The modeling is so simple that one can control easily the calculation by tuning parameters. The simulation results are confirmed by the ideal gas law and the capillary relation. helium bubble growth, meso-scale modeling, Monte-Carlo simulation, the ideal gas law and the capillary relation. (authors)

  17. Mesoscale modeling of smoke radiative feedback over the Sahel region

    Yang, Z.; Wang, J.; Ichoku, C. M.; Ellison, L.; Zhang, F.; Yue, Y.

    2013-12-01

    This study employs satellite observations and a fully-coupled meteorology-chemistry-aerosol model, Weather Research and Forecasting model with Chemistry (WRF-Chem) to study the smoke radative feedback on surface energy budget, boundary layer processes, and atmospheric lapse rate in February 2008 over the Sahel region. The smoke emission inventories we use come from various sources, including but not limited to the Fire Locating and Modeling of Burning Emissions (FLAMBE) developed by NRL and the Fire Energetic and Emissions Research (FEER) developed by NASA GSFC. Model performance is evaluated using numerous satellite and ground-based datasets: MODIS true color images, ground-based Aerosol Optical Depth (AOD) measurements from AERONET, MODIS AOD retrievals, and Cloud-Aerosol Lidar data with Orthogonal Polarization (CALIOP) atmospheric backscattering and extinction products. Specification of smoke injection height of 650 m in WRF-Chem yields aerosol vertical profiles that are most consistent with CALIOP observations of aerosol layer height. Statistically, 5% of the CALIPSO valid measurements of aerosols in February 2008 show aerosol layers either above the clouds or between the clouds, reinforcing the importance of the aerosol vertical distribution for quantifying aerosol impact on climate in the Sahel region. The results further show that the smoke radiative feedbacks are sensitive to assumptions of black carbon and organic carbon ratio in the particle emission inventory. Also investigated is the smoke semi-direct effect as a function of cloud fraction.

  18. Confronting the WRF and RAMS mesoscale models with innovative observations in the Netherlands: Evaluating the boundary layer heat budget

    Steeneveld, G. J.; Tolk, L. F.; Moene, A. F.; Hartogensis, O. K.; Peters, W.; Holtslag, A. A. M.

    2011-12-01

    The Weather Research and Forecasting Model (WRF) and the Regional Atmospheric Mesoscale Model System (RAMS) are frequently used for (regional) weather, climate and air quality studies. This paper covers an evaluation of these models for a windy and calm episode against Cabauw tower observations (Netherlands), with a special focus on the representation of the physical processes in the atmospheric boundary layer (ABL). In addition, area averaged sensible heat flux observations by scintillometry are utilized which enables evaluation of grid scale model fluxes and flux observations at the same horizontal scale. Also, novel ABL height observations by ceilometry and of the near surface longwave radiation divergence are utilized. It appears that WRF in its basic set-up shows satisfactory model results for nearly all atmospheric near surface variables compared to field observations, while RAMS needed refining of its ABL scheme. An important inconsistency was found regarding the ABL daytime heat budget: Both model versions are only able to correctly forecast the ABL thermodynamic structure when the modeled surface sensible heat flux is much larger than both the eddy-covariance and scintillometer observations indicate. In order to clarify this discrepancy, model results for each term of the heat budget equation is evaluated against field observations. Sensitivity studies and evaluation of radiative tendencies and entrainment reveal that possible errors in these variables cannot explain the overestimation of the sensible heat flux within the current model infrastructure.

  19. North Pacific Mesoscale Coupled Air-Ocean Simulations Compared with Observations

    Cerovecki, Ivana [Univ. of California, San Diego, CA (United States). Scripps Inst. of Oceanography; McClean, Julie [Univ. of California, San Diego, CA (United States). Scripps Inst. of Oceanography; Koracin, Darko [Desert Research Inst. (DRI), Reno, NV (United States). Division of Atmospheric Sciences

    2014-11-14

    The overall objective of this study was to improve the representation of regional ocean circulation in the North Pacific by using high resolution atmospheric forcing that accurately represents mesoscale processes in ocean-atmosphere regional (North Pacific) model configuration. The goal was to assess the importance of accurate representation of mesoscale processes in the atmosphere and the ocean on large scale circulation. This is an important question, as mesoscale processes in the atmosphere which are resolved by the high resolution mesoscale atmospheric models such as Weather Research and Forecasting (WRF), are absent in commonly used atmospheric forcing such as CORE forcing, employed in e.g. the Community Climate System Model (CCSM).

  20. A shallow convection parameterization for the non-hydrostatic MM5 mesoscale model

    Seaman, N.L.; Kain, J.S.; Deng, A. [Pennsylvania State Univ., University Park, PA (United States)

    1996-04-01

    A shallow convection parameterization suitable for the Pennsylvannia State University (PSU)/National Center for Atmospheric Research nonhydrostatic mesoscale model (MM5) is being developed at PSU. The parameterization is based on parcel perturbation theory developed in conjunction with a 1-D Mellor Yamada 1.5-order planetary boundary layer scheme and the Kain-Fritsch deep convection model.

  1. Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

    Basile Pauthier

    2016-01-01

    Full Text Available A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1 PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2 both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3 PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE. This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

  2. Impact of SLA assimilation in the Sicily Channel Regional Model: model skills and mesoscale features

    A. Olita

    2012-07-01

    Full Text Available The impact of the assimilation of MyOcean sea level anomalies along-track data on the analyses of the Sicily Channel Regional Model was studied. The numerical model has a resolution of 1/32° degrees and is capable to reproduce mesoscale and sub-mesoscale features. The impact of the SLA assimilation is studied by comparing a simulation (SIM, which does not assimilate data with an analysis (AN assimilating SLA along-track multi-mission data produced in the framework of MyOcean project. The quality of the analysis was evaluated by computing RMSE of the misfits between analysis background and observations (sea level before assimilation. A qualitative evaluation of the ability of the analyses to reproduce mesoscale structures is accomplished by comparing model results with ocean colour and SST satellite data, able to detect such features on the ocean surface. CTD profiles allowed to evaluate the impact of the SLA assimilation along the water column. We found a significant improvement for AN solution in terms of SLA RMSE with respect to SIM (the averaged RMSE of AN SLA misfits over 2 years is about 0.5 cm smaller than SIM. Comparison with CTD data shows a questionable improvement produced by the assimilation process in terms of vertical features: AN is better in temperature while for salinity it gets worse than SIM at the surface. This suggests that a better a-priori description of the vertical error covariances would be desirable. The qualitative comparison of simulation and analyses with synoptic satellite independent data proves that SLA assimilation allows to correctly reproduce some dynamical features (above all the circulation in the Ionian portion of the domain and mesoscale structures otherwise misplaced or neglected by SIM. Such mesoscale changes also infer that the eddy momentum fluxes (i.e. Reynolds stresses show major changes in the Ionian area. Changes in Reynolds stresses reflect a different pumping of eastward momentum from the eddy to

  3. Meso-scale effects of tropical deforestation in Amazonia: preparatory LBA modelling studies

    A. J. Dolman

    1999-08-01

    Full Text Available As part of the preparation for the Large-Scale Biosphere Atmosphere Experiment in Amazonia, a meso-scale modelling study was executed to highlight deficiencies in the current understanding of land surface atmosphere interaction at local to sub-continental scales in the dry season. Meso-scale models were run in 1-D and 3-D mode for the area of Rondonia State, Brazil. The important conclusions are that without calibration it is difficult to model the energy partitioning of pasture; modelling that of forest is easier due to the absence of a strong moisture deficit signal. The simulation of the boundary layer above forest is good, above deforested areas (pasture poor. The models' underestimate of the temperature of the boundary layer is likely to be caused by the neglect of the radiative effects of aerosols caused by biomass burning, but other factors such as lack of sufficient entrainment in the model at the mixed layer top may also contribute. The Andes generate patterns of subsidence and gravity waves, the effects of which are felt far into the Rondonian area The results show that the picture presented by GCM modelling studies may need to be balanced by an increased understanding of what happens at the meso-scale. The results are used to identify key measurements for the LBA atmospheric meso-scale campaign needed to improve the model simulations. Similar modelling studies are proposed for the wet season in Rondonia, when convection plays a major role.Key words. Atmospheric composition and structure (aerosols and particles; biosphere-atmosphere interactions · Meterology and atmospheric dynamics (mesoscale meterology

  4. Meso-scale effects of tropical deforestation in Amazonia: preparatory LBA modelling studies

    A. J. Dolman

    Full Text Available As part of the preparation for the Large-Scale Biosphere Atmosphere Experiment in Amazonia, a meso-scale modelling study was executed to highlight deficiencies in the current understanding of land surface atmosphere interaction at local to sub-continental scales in the dry season. Meso-scale models were run in 1-D and 3-D mode for the area of Rondonia State, Brazil. The important conclusions are that without calibration it is difficult to model the energy partitioning of pasture; modelling that of forest is easier due to the absence of a strong moisture deficit signal. The simulation of the boundary layer above forest is good, above deforested areas (pasture poor. The models' underestimate of the temperature of the boundary layer is likely to be caused by the neglect of the radiative effects of aerosols caused by biomass burning, but other factors such as lack of sufficient entrainment in the model at the mixed layer top may also contribute. The Andes generate patterns of subsidence and gravity waves, the effects of which are felt far into the Rondonian area The results show that the picture presented by GCM modelling studies may need to be balanced by an increased understanding of what happens at the meso-scale. The results are used to identify key measurements for the LBA atmospheric meso-scale campaign needed to improve the model simulations. Similar modelling studies are proposed for the wet season in Rondonia, when convection plays a major role.

    Key words. Atmospheric composition and structure (aerosols and particles; biosphere-atmosphere interactions · Meterology and atmospheric dynamics (mesoscale meterology

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

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

    2012-01-01

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

  6. Phase Behavior of Semiflexible-Flexible Diblock Copolymer Melt: Insight from Mesoscale Modeling.

    Beránek, P.; Posel, Zbyšek

    2016-01-01

    Roč. 16, č. 8 (2016), s. 7832-7835 ISSN 1533-4880 R&D Projects: GA MŠk(CZ) LH12020 Institutional support: RVO:67985858 Keywords : conformational asymmetry * dissipative particle dynamics * mesoscale modeling Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.483, year: 2016

  7. Shadowing effects of offshore wind farms - an idealised mesoscale model study

    Volker, Patrick; Badger, Jake; Hahmann, Andrea N.

    The study of wind farm (WF) interaction is expected to gain importance, since the offshore wind farm density will increase especially in the North Sea in the near future. We present preliminary results of wind farm interaction simulated by mesoscale models. We use the Explicit Wake Parametrisatio...

  8. An introduction to Space Weather Integrated Modeling

    Zhong, D.; Feng, X.

    2012-12-01

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

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

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

    2014-01-01

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

  10. Mesoscale atmospheric modelling technology as a tool for the long-term meteorological dataset development

    Platonov, Vladimir; Kislov, Alexander; Rivin, Gdaly; Varentsov, Mikhail; Rozinkina, Inna; Nikitin, Mikhail; Chumakov, Mikhail

    2017-04-01

    The detailed hydrodynamic modelling of meteorological parameters during the last 30 years (1985 - 2014) was performed for the Okhotsk Sea and the Sakhalin island regions. The regional non-hydrostatic atmospheric model COSMO-CLM used for this long-term simulation with 13.2, 6.6 and 2.2 km horizontal resolutions. The main objective of creation this dataset was the outlook of the investigation of statistical characteristics and the physical mechanisms of extreme weather events (primarily, wind speed extremes) on the small spatio-temporal scales. COSMO-CLM is the climate version of the well-known mesoscale COSMO model, including some modifications and extensions adapting to the long-term numerical experiments. The downscaling technique was realized and developed for the long-term simulations with three consequent nesting domains. ERA-Interim reanalysis ( 0.75 degrees resolution) used as global forcing data for the starting domain ( 13.2 km horizontal resolution), then these simulation data used as initial and boundary conditions for the next model runs over the domain with 6.6 km resolution, and similarly, for the next step to 2.2 km domain. Besides, the COSMO-CLM model configuration for 13.2 km run included the spectral nudging technique, i.e. an additional assimilation of reanalysis data not only at boundaries, but also inside the whole domain. Practically, this computational scheme realized on the SGI Altix 4700 supercomputer system in the Main Computer Center of Roshydromet and used 2,400 hours of CPU time total. According to modelling results, the verification of the obtained dataset was performed on the observation data. Estimations showed the mean error -0.5 0C, up to 2 - 3 0C RMSE in temperature, and overestimation in wind speed (RMSE is up to 2 m/s). Overall, analysis showed that the used downscaling technique with applying the COSMO-CLM model reproduced the meteorological conditions, spatial distribution, seasonal and synoptic variability of temperature and

  11. The mesoscale dispersion modeling system a simulation tool for development of an emergency response system

    Uliasz, M.

    1990-01-01

    The mesoscale dispersion modeling system is under continuous development. The included numerical models require further improvements and evaluation against data from meteorological and tracer field experiments. The system can not be directly applied to real time predictions. However, it seems to be a useful simulation tool for solving several problems related to planning the monitoring network and development of the emergency response system for the nuclear power plant located in a coastal area. The modeling system can be also applied to another environmental problems connected with air pollution dispersion in complex terrain. The presented numerical models are designed for the use on personal computers and are relatively fast in comparison with the similar mesoscale models developed on mainframe computers

  12. Application of rain scanner SANTANU and transportable weather radar in analyze of Mesoscale Convective System (MCS) events over Bandung, West Java

    Nugroho, G. A.; Sinatra, T.; Trismidianto; Fathrio, I.

    2018-05-01

    Simultaneous observation of transportable weather radar LAPAN-GMR25SP and rain-scanner SANTANU were conducted in Bandung and vicinity. The objective is to observe and analyse the weather condition in this area during rainy and transition season from March until April 2017. From the observation result reported some heavy rainfall with hail and strong winds occurred on March 17th and April 19th 2017. This events were lasted within 1 to 2 hours damaged some properties and trees in Bandung. Mesoscale convective system (MCS) are assumed to be the cause of this heavy rainfall. From two radar data analysis showed a more local convective activity in around 11.00 until 13.00 LT. This local convective activity are showed from the SANTANU observation supported by the VSECT and CMAX of the Transportable radar data that signify the convective activity within those area. MCS activity were observed one hour after that. This event are confirm by the classification of convective-stratiform echoes from radar data and also from the high convective index from Tbb Himawari 8 satellite data. The different MCS activity from this two case study is that April 19 have much more MCS activity than in March 17, 2017.

  13. Mesoscale model parameterizations for radiation and turbulent fluxes at the lower boundary

    Somieski, F.

    1988-11-01

    A radiation parameterization scheme for use in mesoscale models with orography and clouds has been developed. Broadband parameterizations are presented for the solar and the terrestrial spectral ranges. They account for clear, turbid or cloudy atmospheres. The scheme is one-dimensional in the atmosphere, but the effects of mountains (inclination, shading, elevated horizon) are taken into account at the surface. In the terrestrial band, grey and black clouds are considered. Furthermore, the calculation of turbulent fluxes of sensible and latent heat and momentum at an inclined lower model boundary is described. Surface-layer similarity and the surface energy budget are used to evaluate the ground surface temperature. The total scheme is part of the mesoscale model MESOSCOP. (orig.) With 3 figs., 25 refs [de

  14. The Karlsruhe Atmospheric Mesoscale Model KAMM; Das Karlsruher Atmosphaerische Mesoskalige Modell KAMM

    Adrian, G. [Forschungszentrum Karlsruhe GmbH Umwelt und Technik (Germany). Inst. fuer Meteorologie und Klimaforschung]|[Karlsruhe Univ. (T.H.). (Germany). Inst. fuer Meteorologie und Klimaforschung

    1998-01-01

    The applications of the KAMM model range from real-time simulations over the analysis of mesoscale phenomena and the development of parametrizations to describing climatology. In the course of time, wishes emerged to change essential parts of the original model concept, calling for substantial reprogramming; so it was decided to entirely redraft the dynamic core of KAMM and to program it from the beginning including the parallelization of the code. The paper describes the basics of the new model core. (orig./KW) [Deutsch] Der Anwendungsbereich des KAMM-Modells erstreckt sich von Echtzeitsimulationen, ueber Analyse mesoskaliger Phaenomene, Entwicklung von Parametrisierungen bis hin zur beschreibenden Klimatologie. Weil im Laufe der Entstehungszeit wesentliche Aenderungswuensche des urspruenglichen Konzeptes entstanden sind, die eine Neuprogrammierung in wesentlichen Teilen erforderlich erscheinen lassen, wurde entschieden, den dynamischen Kern von KAMM voellig neu zu gestalten und bei der Programmierung eine Parallelisierung des Codes von Anfang an mit einzubeziehen. Die Grundlagen dieses neuen Modellkernes werden vorgestellt. (orig./KW)

  15. The impact of reflectivity correction and conversion methods to improve precipitation estimation by weather radar for an extreme low-land Mesoscale Convective System

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2014-05-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands. For most of the country this led to over 15 hours of near-continuous precipitation, which resulted in total event accumulations exceeding 150 mm in the eastern part of the Netherlands. Such accumulations belong to the largest sums ever recorded in this country and gave rise to local flooding. Measuring precipitation by weather radar within such mesoscale convective systems is known to be a challenge, since measurements are affected by multiple sources of error. For the current event the operational weather radar rainfall product only estimated about 30% of the actual amount of precipitation as measured by rain gauges. In the current presentation we will try to identify what gave rise to such large underestimations. In general weather radar measurement errors can be subdivided into two different groups: 1) errors affecting the volumetric reflectivity measurements taken, and 2) errors related to the conversion of reflectivity values in rainfall intensity and attenuation estimates. To correct for the first group of errors, the quality of the weather radar reflectivity data was improved by successively correcting for 1) clutter and anomalous propagation, 2) radar calibration, 3) wet radome attenuation, 4) signal attenuation and 5) the vertical profile of reflectivity. Such consistent corrections are generally not performed by operational meteorological services. Results show a large improvement in the quality of the precipitation data, however still only ~65% of the actual observed accumulations was estimated. To further improve the quality of the precipitation estimates, the second group of errors are corrected for by making use of disdrometer measurements taken in close vicinity of the radar. Based on these data the parameters of a normalized drop size distribution are estimated for the total event as well as for each precipitation type separately (convective

  16. Evaluation of kriging based surrogate models constructed from mesoscale computations of shock interaction with particles

    Sen, Oishik, E-mail: oishik-sen@uiowa.edu [Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Gaul, Nicholas J., E-mail: nicholas-gaul@ramdosolutions.com [RAMDO Solutions, LLC, Iowa City, IA 52240 (United States); Choi, K.K., E-mail: kyung-choi@uiowa.edu [Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Jacobs, Gustaaf, E-mail: gjacobs@sdsu.edu [Aerospace Engineering, San Diego State University, San Diego, CA 92115 (United States); Udaykumar, H.S., E-mail: hs-kumar@uiowa.edu [Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States)

    2017-05-01

    Macro-scale computations of shocked particulate flows require closure laws that model the exchange of momentum/energy between the fluid and particle phases. Closure laws are constructed in this work in the form of surrogate models derived from highly resolved mesoscale computations of shock-particle interactions. The mesoscale computations are performed to calculate the drag force on a cluster of particles for different values of Mach Number and particle volume fraction. Two Kriging-based methods, viz. the Dynamic Kriging Method (DKG) and the Modified Bayesian Kriging Method (MBKG) are evaluated for their ability to construct surrogate models with sparse data; i.e. using the least number of mesoscale simulations. It is shown that if the input data is noise-free, the DKG method converges monotonically; convergence is less robust in the presence of noise. The MBKG method converges monotonically even with noisy input data and is therefore more suitable for surrogate model construction from numerical experiments. This work is the first step towards a full multiscale modeling of interaction of shocked particle laden flows.

  17. THE APPLICATION OF AN EVOLUTIONARY ALGORITHM TO THE OPTIMIZATION OF A MESOSCALE METEOROLOGICAL MODEL

    Werth, D.; O' Steen, L.

    2008-02-11

    We show that a simple evolutionary algorithm can optimize a set of mesoscale atmospheric model parameters with respect to agreement between the mesoscale simulation and a limited set of synthetic observations. This is illustrated using the Regional Atmospheric Modeling System (RAMS). A set of 23 RAMS parameters is optimized by minimizing a cost function based on the root mean square (rms) error between the RAMS simulation and synthetic data (observations derived from a separate RAMS simulation). We find that the optimization can be efficient with relatively modest computer resources, thus operational implementation is possible. The optimization efficiency, however, is found to depend strongly on the procedure used to perturb the 'child' parameters relative to their 'parents' within the evolutionary algorithm. In addition, the meteorological variables included in the rms error and their weighting are found to be an important factor with respect to finding the global optimum.

  18. The impact of reflectivity correction and accounting for raindrop size distribution variability to improve precipitation estimation by weather radar for an extreme low-land mesoscale convective system

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2014-11-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z - R) and radar reflectivity-specific attenuation (Z - k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the

  19. Coastal Foredune Evolution, Part 2: Modeling Approaches for Meso-Scale Morphologic Evolution

    2017-03-01

    for Meso-Scale Morphologic Evolution by Margaret L. Palmsten1, Katherine L. Brodie2, and Nicholas J. Spore2 PURPOSE: This Coastal and Hydraulics ...managers because foredunes provide ecosystem services and can reduce storm damages to coastal infrastructure, both of which increase the resiliency...MS 2 U.S. Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, Duck, NC ERDC/CHL CHETN-II-57 March 2017 2 models of

  20. Framework of cloud parameterization including ice for 3-D mesoscale models

    Levkov, L; Jacob, D; Eppel, D; Grassl, H

    1989-01-01

    A parameterization scheme for the simulation of ice in clouds incorporated into the hydrostatic version of the GKSS three-dimensional mesoscale model. Numerical simulations of precipitation are performed: over the Northe Sea, the Hawaiian trade wind area and in the region of the intertropical convergence zone. Not only some major features of convective structures in all three areas but also cloud-aerosol interactions have successfully been simulated. (orig.) With 19 figs., 2 tabs.

  1. Statistical Studies of Mesoscale Forecast Models MM5 and WRF

    Henmi, Teizi

    2004-01-01

    ... models were carried out and the results were compared with surface observation data. Both models tended to overforecast temperature and dew-point temperature, although the correlation coefficients between forecast and observations were fairly high...

  2. Toward an extended-geostrophic Euler-Poincare model for mesoscale oceanographic flow

    Allen, J.S.; Newberger, P.A. [Oregon State Univ., Corvallis, OR (United States). Coll. of Oceanic and Atmospheric Sciences; Holm, D.D. [Los Alamos National Lab., NM (United States)

    1998-07-01

    The authors consider the motion of a rotating, continuously stratified fluid governed by the hydrostatic primitive equations (PE). An approximate Hamiltonian (L1) model for small Rossby number {var_epsilon} is derived for application to mesoscale oceanographic flow problems. Numerical experiments involving a baroclinically unstable oceanic jet are utilized to assess the accuracy of the L1 model compared to the PE and to other approximate models, such as the quasigeostrophic (QG) and the geostrophic momentum (GM) equations. The results of the numerical experiments for moderate Rossby number flow show that the L1 model gives accurate solutions with errors substantially smaller than QG or GM.

  3. Application of Prognostic Mesoscale Modeling in the Southeast United States

    Buckley, R.L.

    1999-01-01

    A prognostic model is being used to provide regional forecasts for a variety of applications at the Savannah River Site (SRS). Emergency response dispersion models available at SRS use the space and time-dependent meteorological data provided by this model to supplement local and regional observations. Output from the model is also used locally to aid in forecasting at SRS, and regionally in providing forecasts of the potential time and location of hurricane landfall within the southeast United States

  4. Toward a Mesoscale Model for the Dynamics of Polymer Solutions

    Miller, G H; Trebotich, D

    2006-10-02

    To model entire microfluidic systems containing solvated polymers we argue that it is necessary to have a numerical stability constraint governed only by the advective CFL condition. Advancements in the treatment of Kramers bead-rod polymer models are presented to enable tightly-coupled fluid-particle algorithms in the context of system-level modeling.

  5. Gasdynamic modeling and parametric study of mesoscale internal combustion swing engine/generator systems

    Gu, Yongxian

    The demand of portable power generation systems for both domestic and military applications has driven the advances of mesoscale internal combustion engine systems. This dissertation was devoted to the gasdynamic modeling and parametric study of the mesoscale internal combustion swing engine/generator systems. First, the system-level thermodynamic modeling for the swing engine/generator systems has been developed. The system performance as well as the potentials of both two- and four-stroke swing engine systems has been investigated based on this model. Then through parameterc studies, the parameters that have significant impacts on the system performance have been identified, among which, the burn time and spark advance time are the critical factors related to combustion process. It is found that the shorter burn time leads to higher system efficiency and power output and the optimal spark advance time is about half of the burn time. Secondly, the turbulent combustion modeling based on levelset method (G-equation) has been implemented into the commercial software FLUENT. Thereafter, the turbulent flame propagation in a generic mesoscale combustion chamber and realistic swing engine chambers has been studied. It is found that, in mesoscale combustion engines, the burn time is dominated by the mean turbulent kinetic energy in the chamber. It is also shown that in a generic mesoscale combustion chamber, the burn time depends on the longest distance between the initial ignition kernel to its walls and by changing the ignition and injection locations, the burn time can be reduced by a factor of two. Furthermore, the studies of turbulent flame propagation in real swing engine chambers show that the combustion can be enhanced through in-chamber turbulence augmentation and with higher engine frequency, the burn time is shorter, which indicates that the in-chamber turbulence can be induced by the motion of moving components as well as the intake gas jet flow. The burn time

  6. Adaptive Numerical Algorithms in Space Weather Modeling

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

    2010-01-01

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

  7. Mesoscale modelling methodology based on nudging to increase accuracy in WRA

    Mylonas Dirdiris, Markos; Barbouchi, Sami; Hermmann, Hugo

    2016-04-01

    The offshore wind energy has recently become a rapidly growing renewable energy resource worldwide, with several offshore wind projects in development in different planning stages. Despite of this, a better understanding of the atmospheric interaction within the marine atmospheric boundary layer (MABL) is needed in order to contribute to a better energy capture and cost-effectiveness. Light has been thrown in observational nudging as it has recently become an innovative method to increase the accuracy of wind flow modelling. This particular study focuses on the observational nudging capability of Weather Research and Forecasting (WRF) and ways the uncertainty of wind flow modelling in the wind resource assessment (WRA) can be reduced. Finally, an alternative way to calculate the model uncertainty is pinpointed. Approach WRF mesoscale model will be nudged with observations from FINO3 at three different heights. The model simulations with and without applying observational nudging will be verified against FINO1 measurement data at 100m. In order to evaluate the observational nudging capability of WRF two ways to derive the model uncertainty will be described: one global uncertainty and an uncertainty per wind speed bin derived using the recommended practice of the IEA in order to link the model uncertainty to a wind energy production uncertainty. This study assesses the observational data assimilation capability of WRF model within the same vertical gridded atmospheric column. The principal aim is to investigate whether having observations up to one height could improve the simulation at a higher vertical level. The study will use objective analysis implementing a Cress-man scheme interpolation to interpolate the observation in time and in sp ace (keeping the horizontal component constant) to the gridded analysis. Then the WRF model core will incorporate the interpolated variables to the "first guess" to develop a nudged simulation. Consequently, WRF with and without

  8. Weather forecasting based on hybrid neural model

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

    2017-11-01

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

  9. Mesoscale Modeling of Smoke Particles Distribution and Their Radiative Feedback over Northern Sub-Saharan African Region

    Yue, Y.; Wang, J.; Ichoku, C. M.; Ellison, L.

    2015-12-01

    Stretching from southern boundary of Sahara to the equator and expanding west to east from Atlantic Ocean coasts to the India Ocean coasts, the northern sub-Saharan African (NSSA) region has been subject to intense biomass burning. Comprised of savanna, shrub, tropical forest and a number of agricultural crops, the extensive fires burn belt covers central and south of NSSA during dry season (from October to March) contributes to one of the highest biomass burning rate per km2 in the world. Due to smoke particles' absorption effects of solar radiation, they can modify the surface and atmosphere temperature and thus change atmospheric stability, height of the boundary layer, regional atmospheric circulation, evaporation rate, cloud formation, and precipitation. Hence, smoke particles emitted from biomass burning over NSSA region has a significant influence to the air quality, weather and climate variability. In this study, the first version of this Fire Energetics and Emissions Research (FEER.v1) emissions of several smoke constituents including light-absorbing organic carbon (OC) and black carbon (BC) are applied to a state-of-science meteorology-chemistry model as NOAA Weather Research and Forecasting Model with Chemistry (WRF-Chem). We analyzed WRF-Chem simulations of surface and vertical distribution of various pollutants and their direct radiative effects in conjunction with satellite observation data from Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar data with Orthogonal Polarization (CALIPSO) to strengthen the importance of combining space measured emission products like FEER.v1 emission inventory with mesoscale model over intense biomass burning region, especially in area where ground-based air-quality and radiation-related observations are limited or absent.

  10. Physical modeling of shoreline bioremediation: Continuous flow mesoscale basins

    Sveum, P.; Ramstad, S.; Faksness, L.G.; Bech, C.; Johansen, B.

    1995-01-01

    This paper describes the design and use of continuous flow basin beach models in the study of bioremediation processes, and gives some results from an experiment designed to study the effects of different strategies for adding fertilizers. The continuous flow experimental basin system simulates an open system with natural tidal variation, wave action, and continuous supply and exchange of seawater. Biodegradation and bioremediation processes can thus be tested close to natural conditions. Results obtained using the models show a significant enhancement of biodegradation of oil in a sediment treated with an organic nutrient source, increased nutrient level in the interstitial water, and sediment microbial activity. These physical models gives biologically significant results, and can be used to simulate biodegradation and bioremediation in natural systems

  11. Mesoscale to microscale wind farm flow modeling and evaluation

    Sanz Rodrigo, Javier; Chávez Arroyo, Roberto Aurelio; Moriarty, Patrick

    2017-01-01

    The increasing size of wind turbines, with rotors already spanning more than 150m diameter and hub heights above 100m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer stru...

  12. Strain in the mesoscale kinetic Monte Carlo model for sintering

    Bjørk, Rasmus; Frandsen, Henrik Lund; Tikare, V.

    2014-01-01

    anisotropic strains for homogeneous powder compacts with aspect ratios different from unity. It is shown that the line direction biases shrinkage strains in proportion the compact dimension aspect ratios. A new algorithm that corrects this bias in strains is proposed; the direction for collapsing the column...... densification by vacancy annihilation removes an isolated pore site at a grain boundary and collapses a column of sites extending from the vacancy to the surface of sintering compact, through the center of mass of the nearest grain. Using this algorithm, the existing published kMC models are shown to produce...

  13. Verification of some numerical models for operationally predicting mesoscale winds aloft

    Cornett, J.S.; Randerson, D.

    1977-01-01

    Four numerical models are described for predicting mesoscale winds aloft for a 6 h period. These models are all tested statistically against persistence as the control forecast and against predictions made by operational forecasters. Mesoscale winds aloft data were used to initialize the models and to verify the predictions on an hourly basis. The model yielding the smallest root-mean-square vector errors (RMSVE's) was the one based on the most physics which included advection, ageostrophic acceleration, vertical mixing and friction. Horizontal advection was found to be the most important term in reducing the RMSVE's followed by ageostrophic acceleration, vertical advection, surface friction and vertical mixing. From a comparison of the mean absolute errors based on up to 72 independent wind-profile predictions made by operational forecasters, by the most complete model, and by persistence, we conclude that the model is the best wind predictor in the free air. In the boundary layer, the results tend to favor the forecaster for direction predictions. The speed predictions showed no overall superiority in any of these three models

  14. Wind Farm parametrization in the mesoscale model WRF

    Volker, Patrick; Badger, Jake; Hahmann, Andrea N.

    2012-01-01

    , but are parametrized as another sub-grid scale process. In order to appropriately capture the wind farm wake recovery and its direction, two properties are important, among others, the total energy extracted by the wind farm and its velocity deficit distribution. In the considered parametrization the individual...... the extracted force is proportional to the turbine area interfacing a grid cell. The sub-grid scale wake expansion is achieved by adding turbulence kinetic energy (proportional to the extracted power) to the flow. The validity of both wind farm parametrizations has been verified against observational data. We...... turbines produce a thrust dependent on the background velocity. For the sub-grid scale velocity deficit, the entrainment from the free atmospheric flow into the wake region, which is responsible for the expansion, is taken into account. Furthermore, since the model horizontal distance is several times...

  15. Mesoscale modelling of atmospheric CO2 across Denmark

    Lansø, Anne Sofie

    2016-01-01

    of the simulated atmospheric CO2 across Denmark was, in particular, affected by the Danish terrestrial surface exchanges and its temporal variability. This study urges all future modelling studies of air–sea CO2 to include short-term variability in pCO2. To capture the full heterogeneity of the surface exchanges......It is scientifically well-established that the increase of atmospheric CO2 affects the entire globe and will lead to higher surface temperatures. Although anthropogenic CO2is emitted straight into the atmosphere, it does not all contribute to the existing atmospheric CO2 reservoir. Approximately 29......% is taken up by the global oceans, due to under-saturation of CO2 in the surface waters, while another 33 % is taken up by the terrestrial biosphere, via photosynthesis. In order to estimate the effects of increasing anthropogenic emissions of CO2 more accurately in the future, it is essential to understand...

  16. Process analysis of the modelled 3-D mesoscale impact of aircraft emissions on the atmosphere

    Hendricks, J; Ebel, A; Lippert, E; Petry, H [Koeln Univ. (Germany). Inst. fuer Geophysik und Meterorologie

    1998-12-31

    A mesoscale chemistry transport model is applied to study the impact of aircraft emissions on the atmospheric trace gas composition. A special analysis of the simulations is conducted to separate the effects of chemistry, transport, diffusion and cloud processes on the transformation of the exhausts of a subsonic fleet cruising over the North Atlantic. The aircraft induced ozone production strongly depends on the tropopause height and the cruise altitude. Aircraft emissions may undergo an effective downward transport under the influence of stratosphere-troposphere exchange activity. (author) 12 refs.

  17. Estimation of parasitic losses in a proposed mesoscale resonant engine: Experiment and model

    Preetham, B. S.; Anderson, M.; Richards, C.

    2014-02-01

    A resonant engine in which the piston-cylinder assembly is replaced by a flexible cavity is realized at the mesoscale using flexible metal bellows to demonstrate the feasibility of the concept. A four stroke motoring technique is developed and measurements are performed to determine parasitic losses. A non-linear lumped parameter model is developed to evaluate the engine performance. Experimentally, the heat transfer and friction effects are separated by varying the engine speed and operating frequency. The engine energy flow diagram showing the energy distribution among various parasitic elements reveals that the friction loss in the bellows is smaller than the sliding friction loss in a typical piston-cylinder assembly.

  18. Simulations of a November thunderstorm event by two mesoscale models in the south Alpine region

    Borroni, A.

    2005-01-01

    Abstract: Two numerical models have been used to investigate the development of a thunderstorm event that took place on November 7th , 2004, in the northern Italy. A cold air mass moved from the northeast to the Alps and the Po valley, while the temperature in the lower layers was quite warm. A thunderstorm with rain and hail developed in the central and eastern part of Italy's subalpine region. In this work it's analyzed some aspects of the thunderstorm dynamics at the mesoscale using two di...

  19. On the sensitivity of mesoscale models to surface-layer parameterization constants

    Garratt, J. R.; Pielke, R. A.

    1989-09-01

    The Colorado State University standard mesoscale model is used to evaluate the sensitivity of one-dimensional (1D) and two-dimensional (2D) fields to differences in surface-layer parameterization “constants”. Such differences reflect the range in the published values of the von Karman constant, Monin-Obukhov stability functions and the temperature roughness length at the surface. The sensitivity of 1D boundary-layer structure, and 2D sea-breeze intensity, is generally less than that found in published comparisons related to turbulence closure schemes generally.

  20. Process analysis of the modelled 3-D mesoscale impact of aircraft emissions on the atmosphere

    Hendricks, J.; Ebel, A.; Lippert, E.; Petry, H. [Koeln Univ. (Germany). Inst. fuer Geophysik und Meterorologie

    1997-12-31

    A mesoscale chemistry transport model is applied to study the impact of aircraft emissions on the atmospheric trace gas composition. A special analysis of the simulations is conducted to separate the effects of chemistry, transport, diffusion and cloud processes on the transformation of the exhausts of a subsonic fleet cruising over the North Atlantic. The aircraft induced ozone production strongly depends on the tropopause height and the cruise altitude. Aircraft emissions may undergo an effective downward transport under the influence of stratosphere-troposphere exchange activity. (author) 12 refs.

  1. A Mesoscale Model-Based Climatography of Nocturnal Boundary-Layer Characteristics over the Complex Terrain of North-Western Utah.

    Serafin, Stefano; De Wekker, Stephan F J; Knievel, Jason C

    Nocturnal boundary-layer phenomena in regions of complex topography are extremely diverse and respond to a multiplicity of forcing factors, acting primarily at the mesoscale and microscale. The interaction between different physical processes, e.g., drainage promoted by near-surface cooling and ambient flow over topography in a statically stable environment, may give rise to special flow patterns, uncommon over flat terrain. Here we present a climatography of boundary-layer flows, based on a 2-year archive of simulations from a high-resolution operational mesoscale weather modelling system, 4DWX. The geographical context is Dugway Proving Ground, in north-western Utah, USA, target area of the field campaigns of the MATERHORN (Mountain Terrain Atmospheric Modeling and Observations Program) project. The comparison between model fields and available observations in 2012-2014 shows that the 4DWX model system provides a realistic representation of wind speed and direction in the area, at least in an average sense. Regions displaying strong spatial gradients in the field variables, thought to be responsible for enhanced nocturnal mixing, are typically located in transition areas from mountain sidewalls to adjacent plains. A key dynamical process in this respect is the separation of dynamically accelerated downslope flows from the surface.

  2. Comparison of the new intermediate complex atmospheric research (ICAR) model with the WRF model in a mesoscale catchment in Central Europe

    Härer, Stefan; Bernhardt, Matthias; Gutmann, Ethan; Bauer, Hans-Stefan; Schulz, Karsten

    2017-04-01

    Until recently, a large gap existed in the atmospheric downscaling strategies. On the one hand, computationally efficient statistical approaches are widely used, on the other hand, dynamic but CPU-intensive numeric atmospheric models like the weather research and forecast (WRF) model exist. The intermediate complex atmospheric research (ICAR) model developed at NCAR (Boulder, Colorado, USA) addresses this gap by combining the strengths of both approaches: the process-based structure of a dynamic model and its applicability in a changing climate as well as the speed of a parsimonious modelling approach which facilitates the modelling of ensembles and a straightforward way to test new parametrization schemes as well as various input data sources. However, the ICAR model has not been tested in Europe and on slightly undulated terrain yet. This study now evaluates for the first time the ICAR model to WRF model runs in Central Europe comparing a complete year of model results in the mesoscale Attert catchment (Luxembourg). In addition to these modelling results, we also describe the first implementation of ICAR on an Intel Phi architecture and consequently perform speed tests between the Vienna cluster, a standard workstation and the use of an Intel Phi coprocessor. Finally, the study gives an outlook on sensitivity studies using slightly different input data sources.

  3. An intercomparison of several diagnostic meteorological processors used in mesoscale air quality modeling

    Vimont, J.C. [National Park Service, Lakewood, CO (United States); Scire, J.S. [Sigma Research Corp., Concord, MA (United States)

    1994-12-31

    A major component, and area of uncertainty, in mesoscale air quality modeling, is the specification of the meteorological fields which affect the transport and dispersion of pollutants. Various options are available for estimating the wind and mixing depth fields over a mesoscale domain. Estimates of the wind field can be obtained from spatial and temporal interpolation of available observations or from diagnostic meteorological models, which estimate a meteorological field from available data and adjust those fields based on parameterizations of physical processes. A major weakness of these processors is their dependence on spatially and temporally sparse input data, particularly upper air data. These problems are exacerbated in regions of complex terrain and along the shorelines of large bodies of water. Similarly, the estimation of mixing depth is also reliant upon sparse observations and the parameterization of the convective and mechanical processes. The meteorological processors examined in this analysis were developed to drive different Lagrangian puff models. This paper describes the algorithms these processors use to estimate the wind fields and mixing depth fields.

  4. Space Weather Models at the CCMC And Their Capabilities

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

    2007-01-01

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

  5. Mesoscale wind fluctuations over Danish waters

    Vincent, C.L.

    2010-12-15

    Mesoscale wind fluctuations affect the large scale integration of wind power because they undermine the day-ahead predictability of wind speed and power production, and because they can result in large fluctuations in power generation that must be balanced using reserve power. Large fluctuations in generated power are a particular problem for offshore wind farms because the typically high concentration of turbines within a limited geographical area means that fluctuations can be correlated across large numbers of turbines. Furthermore, organised mesoscale structures that often form over water, such as convective rolls and cellular convection, have length scales of tens of kilometers, and can cause large wind fluctuations on a time scale of around an hour. This thesis is an exploration of the predictability of mesoscale wind fluctuations using observations from the world's first two large offshore wind farms - Horns Rev I in the North Sea, and Nysted in the Baltic Sea. The thesis begins with a climatological analysis of wind fluctuations on time scales of 1-10 hours at the two sites. A novel method for calculating conditional climatologies of spectral information is proposed, based on binning and averaging the time axis of the Hilbert spectrum. Results reveal clear patterns between wind fluctuations and locally observed meteorological conditions. The analysis is expanded by classifying wind fluctuations on time scales of 1-3 hours according to synoptic patterns, satellite pictures and wind classes. Results indicate that cold air outbreaks and open cellular convection are a significant contributor to mesoscale wind variability at Horns Rev. The predictability of mesoscale wind fluctuations is tested by implementing standard statistical models that relate local wind variability to parameters based on a large scale weather analysis. The models show some skill, but only achieve a 15% improvement on a persistence forecast. The possibility of explicitly modelling

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

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

  7. Preliminary analysis of four numerical models for calculating the mesoscale transport of Kr-85

    Pepper, D W; Cooper, R E [Du Pont de Nemours (E.I.) and Co., Aiken, SC (USA). Savannah River Lab.

    1983-01-01

    A performance study of four numerical algorithms for multi-dimensional advection-diffusion prediction on mesoscale grids has been made. Dispersion from point and distributed sources and a simulation of a continuous source are compared with analytical solutions to assess relative accuracy. Model predictions are then compared with actual measurements of Kr-85 emitted from the Savannah River Plant (SRP). The particle-in-cell and method of moments algorithms exhibit superior accuracy in modeling single source releases. For modeling distributed sources, algorithms based on the pseudospectral and finite element interpolation concepts exhibit comparable accuracy. The method of moments is felt to be the best overall performer, although all the models appear to be relatively close in accuracy.

  8. Simulation of coastal winds along the central west coast of India using the MM5 mesoscale model

    Pushpadas, D.; Vethamony, P.; Sudheesh, K.; George, S.; Babu, M.T.; Nair, T.M.B.

    A high-resolution mesoscale numerical model (MM5) has been used to study the coastal atmospheric circulation of the central west coast of India, and Goa in particular. The model is employed with three nested domains. The innermost domain of 3 km...

  9. Mesoscale spiral vortex embedded within a Lake Michigan snow squall band - High resolution satellite observations and numerical model simulations

    Lyons, Walter A.; Keen, Cecil S.; Hjelmfelt, Mark; Pease, Steven R.

    1988-01-01

    It is known that Great Lakes snow squall convection occurs in a variety of different modes depending on various factors such as air-water temperature contrast, boundary-layer wind shear, and geostrophic wind direction. An exceptional and often neglected source of data for mesoscale cloud studies is the ultrahigh resolution multispectral data produced by Landsat satellites. On October 19, 1972, a clearly defined spiral vortex was noted in a Landsat-1 image near the southern end of Lake Michigan during an exceptionally early cold air outbreak over a still very warm lake. In a numerical simulation using a three-dimensional Eulerian hydrostatic primitive equation mesoscale model with an initially uniform wind field, a definite analog to the observed vortex was generated. This suggests that intense surface heating can be a principal cause in the development of a low-level mesoscale vortex.

  10. The dependence of the oceans MOC on mesoscale eddy diffusivities: A model study

    Marshall, John; Scott, Jeffery R.; Romanou, Anastasia; Kelley, Maxwell; Leboissetier, Anthony

    2017-01-01

    The dependence of the depth and strength of the ocean's global meridional overturning cells (MOC) on the specification of mesoscale eddy diffusivity (K) is explored in two ocean models. The GISS and MIT ocean models are driven by the same prescribed forcing fields, configured in similar ways, spun up to equilibrium for a range of K 's and the resulting MOCs mapped and documented. Scaling laws implicit in modern theories of the MOC are used to rationalize the results. In all calculations the K used in the computation of eddy-induced circulation and that used in the representation of eddy stirring along neutral surfaces, is set to the same value but is changed across experiments. We are able to connect changes in the strength and depth of the Atlantic MOC, the southern ocean upwelling MOC, and the deep cell emanating from Antarctica, to changes in K.

  11. LDRD final report : mesoscale modeling of dynamic loading of heterogeneous materials

    Robbins, Joshua [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Dingreville, Remi Philippe Michel [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Voth, Thomas Eugene [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Furnish, Michael David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2013-12-01

    Material response to dynamic loading is often dominated by microstructure (grain structure, porosity, inclusions, defects). An example critically important to Sandia's mission is dynamic strength of polycrystalline metals where heterogeneities lead to localization of deformation and loss of shear strength. Microstructural effects are of broad importance to the scientific community and several institutions within DoD and DOE; however, current models rely on inaccurate assumptions about mechanisms at the sub-continuum or mesoscale. Consequently, there is a critical need for accurate and robust methods for modeling heterogeneous material response at this lower length scale. This report summarizes work performed as part of an LDRD effort (FY11 to FY13; project number 151364) to meet these needs.

  12. Developing Mesoscale Model of Fibrin-Platelet Network Representing Blood Clotting =

    Sun, Yueyi; Nikolov, Svetoslav; Bowie, Sam; Alexeev, Alexander; Lam, Wilbur; Myers, David

    Blood clotting disorders which prevent the body's natural ability to achieve hemostasis can lead to a variety of life threatening conditions such as, excessive bleeding, stroke, or heart attack. Treatment of these disorders is highly dependent on understanding the underlying physics behind the clotting process. Since clotting is a highly complex multi scale mechanism developing a fully atomistic model is currently not possible. We develop a mesoscale model based on dissipative particle dynamics (DPD) to gain fundamental understanding of the underlying principles controlling the clotting process. In our study, we examine experimental data on clot contraction using stacks of confocal microscopy images to estimate the crosslink density in the fibrin networks and platelet location. Using this data we reconstruct the platelet rich fibrin network and study how platelet-fibrin interactions affect clotting. Furthermore, we probe how different system parameters affect clot contraction. ANSF CAREER Award DMR-1255288.

  13. Simulating mesoscale coastal evolution for decadal coastal management: A new framework integrating multiple, complementary modelling approaches

    van Maanen, Barend; Nicholls, Robert J.; French, Jon R.; Barkwith, Andrew; Bonaldo, Davide; Burningham, Helene; Brad Murray, A.; Payo, Andres; Sutherland, James; Thornhill, Gillian; Townend, Ian H.; van der Wegen, Mick; Walkden, Mike J. A.

    2016-03-01

    Coastal and shoreline management increasingly needs to consider morphological change occurring at decadal to centennial timescales, especially that related to climate change and sea-level rise. This requires the development of morphological models operating at a mesoscale, defined by time and length scales of the order 101 to 102 years and 101 to 102 km. So-called 'reduced complexity' models that represent critical processes at scales not much smaller than the primary scale of interest, and are regulated by capturing the critical feedbacks that govern landform behaviour, are proving effective as a means of exploring emergent coastal behaviour at a landscape scale. Such models tend to be computationally efficient and are thus easily applied within a probabilistic framework. At the same time, reductionist models, built upon a more detailed description of hydrodynamic and sediment transport processes, are capable of application at increasingly broad spatial and temporal scales. More qualitative modelling approaches are also emerging that can guide the development and deployment of quantitative models, and these can be supplemented by varied data-driven modelling approaches that can achieve new explanatory insights from observational datasets. Such disparate approaches have hitherto been pursued largely in isolation by mutually exclusive modelling communities. Brought together, they have the potential to facilitate a step change in our ability to simulate the evolution of coastal morphology at scales that are most relevant to managing erosion and flood risk. Here, we advocate and outline a new integrated modelling framework that deploys coupled mesoscale reduced complexity models, reductionist coastal area models, data-driven approaches, and qualitative conceptual models. Integration of these heterogeneous approaches gives rise to model compositions that can potentially resolve decadal- to centennial-scale behaviour of diverse coupled open coast, estuary and inner

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

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

    2006-01-01

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

  15. Mesoscale wind fluctuations over Danish waters

    Vincent, Claire Louise

    in generated power are a particular problem for oshore wind farms because the typically high concentration of turbines within a limited geographical area means that uctuations can be correlated across large numbers of turbines. Furthermore, organised mesoscale structures that often form over water......Mesoscale wind uctuations aect the large scale integration of wind power because they undermine the day-ahead predictability of wind speed and power production, and because they can result in large uctuations in power generation that must be balanced using reserve power. Large uctuations...... that realistic hour-scale wind uctuations and open cellular convection patterns develop in WRF simulations with 2km horizontal grid spacing. The atmospheric conditions during one of the case studies are then used to initialise a simplied version of the model that has no large scale weather forcing, topography...

  16. Wind-Climate Estimation Based on Mesoscale and Microscale Modeling: Statistical-Dynamical Downscaling for Wind Energy Applications

    Badger, Jake; Frank, Helmut; Hahmann, Andrea N.

    2014-01-01

    This paper demonstrates that a statistical dynamical method can be used to accurately estimate the wind climate at a wind farm site. In particular, postprocessing of mesoscale model output allows an efficient calculation of the local wind climate required for wind resource estimation at a wind...

  17. Modeling rock weathering in small watersheds

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

    2014-01-01

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

  18. Modelling daily sediment yield from a meso-scale catchment, a case study in SW Poland

    Keesstra, S. D.; Schoorl, J.; Temme, A. J. A. M.

    2009-01-01

    For management purposes it is important to be able to assess the sediment yield of a catchment. however, at this moment models designed for estimating sediment yield are only capable to give either very detailed storm-based information or year averages. The storm-based models require input data that are not available for most catchment. However, models that estimate yearly averages, ignore a lot of other detailed information, like daily discharge and precipitation data. There are currently no models available that model sediment yield on the temporal scale of one day and the spatial scale of a meso-scale catchment, without making use of very detailed input data. To fill this scientific and management gap, landscape evolution model LAPSUS has been adapted to model sediment yield on a daily basis. This model has the water balance as a base. To allow calibration with the discharge at the outlet, a subsurface flow module has been added to the model. (Author) 12 refs.

  19. Modelling daily sediment yield from a meso-scale catchment, a case study in SW Poland

    Keesstra, S. D.; Schoorl, J.; Temme, A. J. A. M.

    2009-07-01

    For management purposes it is important to be able to assess the sediment yield of a catchment. however, at this moment models designed for estimating sediment yield are only capable to give either very detailed storm-based information or year averages. The storm-based models require input data that are not available for most catchment. However, models that estimate yearly averages, ignore a lot of other detailed information, like daily discharge and precipitation data. There are currently no models available that model sediment yield on the temporal scale of one day and the spatial scale of a meso-scale catchment, without making use of very detailed input data. To fill this scientific and management gap, landscape evolution model LAPSUS has been adapted to model sediment yield on a daily basis. This model has the water balance as a base. To allow calibration with the discharge at the outlet, a subsurface flow module has been added to the model. (Author) 12 refs.

  20. Probabilistic, Multivariable Flood Loss Modeling on the Mesoscale with BT-FLEMO.

    Kreibich, Heidi; Botto, Anna; Merz, Bruno; Schröter, Kai

    2017-04-01

    Flood loss modeling is an important component for risk analyses and decision support in flood risk management. Commonly, flood loss models describe complex damaging processes by simple, deterministic approaches like depth-damage functions and are associated with large uncertainty. To improve flood loss estimation and to provide quantitative information about the uncertainty associated with loss modeling, a probabilistic, multivariable Bagging decision Tree Flood Loss Estimation MOdel (BT-FLEMO) for residential buildings was developed. The application of BT-FLEMO provides a probability distribution of estimated losses to residential buildings per municipality. BT-FLEMO was applied and validated at the mesoscale in 19 municipalities that were affected during the 2002 flood by the River Mulde in Saxony, Germany. Validation was undertaken on the one hand via a comparison with six deterministic loss models, including both depth-damage functions and multivariable models. On the other hand, the results were compared with official loss data. BT-FLEMO outperforms deterministic, univariable, and multivariable models with regard to model accuracy, although the prediction uncertainty remains high. An important advantage of BT-FLEMO is the quantification of prediction uncertainty. The probability distribution of loss estimates by BT-FLEMO well represents the variation range of loss estimates of the other models in the case study. © 2016 Society for Risk Analysis.

  1. Space weather: Modeling and forecasting ionospheric

    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. The Challenge of Forecasting the Onset and Development of Radiation Fog Using Mesoscale Atmospheric Models

    Steeneveld, G.J.; Ronda, R.J.; Holtslag, A.A.M.

    2015-01-01

    The numerical weather prediction of radiation fog is challenging, as many models typically show large biases for the timing of the onset and dispersal of the fog, as well as for its depth and liquid water content. To understand the role of physical processes, i.e. turbulence, radiation, land-surface

  3. MELSAR: a mesoscale air quality model for complex terrain. Volume 2. Appendices

    Allwine, K.J.; Whiteman, C.D.

    1985-04-01

    This final report is submitted as part of the Green River Ambient Model Assessment (GRAMA) project conducted at the US Department of Energy's Pacific Northwest Laboratory for the US Environmental Protection Agency. The GRAMA Program has, as its ultimate goal, the development of validated air quality models that can be applied to the complex terrain of the Green River Formation of western Colorado, eastern Utah and southern Wyoming. The Green River Formation is a geologic formation containing large reserves of oil shale, coal, and other natural resources. Development of these resources may lead to a degradation of the air quality of the region. Air quality models are needed immediately for planning and regulatory purposes to assess the magnitude of these regional impacts. This report documents one of the models being developed for this purpose within GRAMA - specifically a model to predict short averaging time (less than or equal to 24 h) pollutant concentrations resulting from the mesoscale transport of pollutant releases from multiple sources. MELSAR has not undergone any rigorous operational testing, sensitivity analyses, or validation studies. Testing and evaluation of the model are needed to gain a measure of confidence in the model's performance. This report consists of two volumes. This volume contains the Appendices, which include listings of the FORTRAN code and Volume 1 contains the model overview, technical description, and user's guide. 13 figs., 10 tabs.

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

    Dreher, Joseph G.

    2009-01-01

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

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

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

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

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

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

    D. Hari Prasad

    2010-01-01

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

  8. The effect of network resolution on data assimilation in a mesoscale model

    Dudhia, J.

    1994-01-01

    One goal of the Atmospheric Radiation Measurement (ARM) Program is to characterize meteorological fields over wide areas (200-km square) in order to better parameterize sub-grid-scale variability in general circulation models used for climate studies. Such a detailed knowledge over these areas is impossible with current observational methods alone, but the synthesis of a dataset by combining observations with a mesoscale numerical model is feasible. Current data assimilation techniques allow observed data to be incorporated while a model is running, thus constraining the model to fit the data as well as the data to be dynamically consistent with the model atmosphere. This interaction may therefore be regarded as a dynamical analysis technique. The technique used for data assimilation here will be the nudging method (Stauffer and Seaman 1990, Kuo and Guo 1989). Specifically, observational nudging where data at observational sites are gradually forced in the model without the need for a gridded analysis. This method is particularly appropriate for asynoptic data covering meso-β-scales, such as will be available at the Cloud and Radiation Testbed (CART) sites. The method makes it possible to incorporate the wide variety of data coming from these sites

  9. Using SST and land cover data from EO Missions for improved mesoscale modelling of the coastal zone

    Karagali, Ioanna; Floors, Rogier Ralph; Lea, Guillaume

    was to evaluate the uncertainty of the modelled wind in the coastal zone and further improve it. Moreover LIDAR measurements were used to evaluate the wind speed retrieval from high resolution SAR systems (Sentinel-1 and TerraSAR-X). The WRF model used a high-resolution satellite SST reanalysis product from...... be implemented in the meso-scale model to better represent the actual conditions in the study area. Such improvements are expected to strengthen the model’s ability to represent land- sea and air-sea interactions, the atmospheric stability and the local topographic features that partly affect the coastal zone......Existing wind measurements in near-shore and offshore areas are sparse and scarce, therefore simulations from state-of-the-art meso-scale models are used for wind resource predictions. In coastal and near-shore areas, models are inaccurate and uncertain, mainly because of numerical approximations...

  10. Numerical modeling of a downwind-developing mesoscale convective system over the Masurian Lake District

    Wójcik Damian K.

    2017-01-01

    Full Text Available Meteorological data concerning the severe convective system from the 21 August 2007 are analyzed in this study. Compiled information allows to understand the reason for the storm development and to identify its fundamental convective mode. Next, the EULAG model is utilized to perform an idealized test that shows a downwind–developing storm growth in an environment comparable to the one that was observed on the 21 August 2007 in the Masurian Lake District. Finally, the COSMO numerical weather prediction model is applied to reconstruct the storm development. The experiment is carried out for various computational grids having the horizontal grid length between 7.0 and 0.55 km. It turns out that the COSMO model is capable in simulating storms of that type. Since the model is used for operational weather forecasting in Poland the evaluation of this skill contributes to the increase of public safety.

  11. Idealized Mesoscale Model Simulations of Open Cellular Convection Over the Sea

    Vincent, Claire Louise; Hahmann, Andrea N.; Kelly, Mark C.

    2012-01-01

    The atmospheric conditions during an observed case of open cellular convection over the North Sea were simulated using the Weather Research and Forecasting (WRF) numerical model. Wind, temperature and water vapour mixing ratio profiles from the WRF simulation were used to initialize an idealized...... version of the model, which excluded the effects of topography, surface inhomogeneities and large-scale weather forcing. Cells with an average diameter of 17.4 km developed. Simulations both with and without a capping inversion were made, and the cell-scale kinetic energy budget was calculated for each...... case. By considering all sources of explicit diffusion in the model, the budgets were balanced. In comparison with previous work based on observational studies, the use of three-dimensional, gridded model data afforded the possibility of calculating all terms in the budgets, which showed...

  12. Estimating the surface layer refractive index structure constant over snow and sea ice using Monin-Obukhov similarity theory with a mesoscale atmospheric model.

    Qing, Chun; Wu, Xiaoqing; Huang, Honghua; Tian, Qiguo; Zhu, Wenyue; Rao, Ruizhong; Li, Xuebin

    2016-09-05

    Since systematic direct measurements of refractive index structure constant ( Cn2) for many climates and seasons are not available, an indirect approach is developed in which Cn2 is estimated from the mesoscale atmospheric model outputs. In previous work, we have presented an approach that a state-of-the-art mesoscale atmospheric model called Weather Research and Forecasting (WRF) model coupled with Monin-Obukhov Similarity (MOS) theory which can be used to estimate surface layer Cn2 over the ocean. Here this paper is focused on surface layer Cn2 over snow and sea ice, which is the extending of estimating surface layer Cn2 utilizing WRF model for ground-based optical application requirements. This powerful approach is validated against the corresponding 9-day Cn2 data from a field campaign of the 30th Chinese National Antarctic Research Expedition (CHINARE). We employ several statistical operators to assess how this approach performs. Besides, we present an independent analysis of this approach performance using the contingency tables. Such a method permits us to provide supplementary key information with respect to statistical operators. These methods make our analysis more robust and permit us to confirm the excellent performances of this approach. The reasonably good agreement in trend and magnitude is found between estimated values and measurements overall, and the estimated Cn2 values are even better than the ones obtained by this approach over the ocean surface layer. The encouraging performance of this approach has a concrete practical implementation of ground-based optical applications over snow and sea ice.

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

    Landman, WA

    2009-12-01

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

  14. Evaluation of a mesoscale dispersion modelling tool during the CAPITOUL experiment

    Lac, C.; Bonnardot, F.; Connan, O.; Camail, C.; Maro, D.; Hebert, D.; Rozet, M.; Pergaud, J.

    2008-12-01

    Atmospheric transport and dispersion were investigated during the CAPITOUL campaign using measurements of sulphur hexafluoride (SF6) tracer. Six releases of SF6 tracer were performed (March 9-11 and July 1-3, 2004) in the same suburban area of Toulouse conurbation, during the Intensive Observing Periods (IOP) of CAPITOUL. Concentration data were collected both at ground-level along axes perpendicular to the wind direction (at distances ranging between 280 m and 5000 m from the release point), and above the ground at 100 m and 200 m height using aircraft flights. Meteorological conditions were all associated with daytime anticyclonic conditions with weak winds and convective clear and cloudy boundary layers. A meso-scale dispersion modelling system, PERLE, developed at Meteo-France for environmental emergencies in case of atmospheric accidental release, was evaluated in terms of meteorology and dispersion, for the different tracer experiments, in its operational configuration. PERLE is based on the combination of the non-hydrostatic meso-scale MESO-NH model, running at 2 km horizontal resolution, and the Lagrangian particle model SPRAY. The statistical meteorological evaluation includes two sets of simulations with initialisation from ECMWF or ALADIN. The meteorological day-to-day error statistics show fairly good Meso-NH predictions, in terms of wind speed, wind direction and near-surface temperature. A strong sensitivity to initial fields concerns the surface fluxes, crucial for dispersion, with an excessive drying of the convective boundary layer with ALADIN initial fields, leading to an overprediction of surface sensible heat fluxes. A parameterization of dry and shallow convection according to the Eddy-Diffusivity-Mass-Flux (EDMF) approach (Pergaud et al. 2008) allows an efficient mixing in the Convective Boundary Layer (CBL) and improves significantly the wind fields. A statistical evaluation of the dispersion prediction was then performed and shows a

  15. Satellite-derived land surface parameters for mesoscale modelling of the Mexico City basin

    B. de Foy

    2006-01-01

    Full Text Available Mesoscale meteorological modelling is an important tool to help understand air pollution and heat island effects in urban areas. Accurate wind simulations are difficult to obtain in areas of weak synoptic forcing. Local factors have a dominant role in the circulation and include land surface parameters and their interaction with the atmosphere. This paper examines an episode during the MCMA-2003 field campaign held in the Mexico City Metropolitan Area (MCMA in April of 2003. Because the episode has weak synoptic forcing, there is the potential for the surface heat budget to influence the local meteorology. High resolution satellite observations are used to specify the land use, vegetation fraction, albedo and surface temperature in the MM5 model. Making use of these readily available data leads to improved meteorological simulations in the MCMA, both for the wind circulation patterns and the urban heat island. Replacing values previously obtained from land-use tables with actual measurements removes the number of unknowns in the model and increases the accuracy of the energy budget. In addition to improving the understanding of local meteorology, this sets the stage for the use of advanced urban modules.

  16. Identification of Mesoscale Convective Complex (MCC) phenomenon with image of Himawari 8 Satellite and WRF ARW Model on Bangka Island (Case Study: 7-8 February 2016)

    Rinaldy, Nanda; Saragih, Immanuel J. A.; Wandala Putra, Agie; Redha Nugraheni, Imma; Wijaya Yonas, Banu

    2017-12-01

    Based on monitoring on 7th and 8th February 2016 there has been a flood that occurred due to heavy rainfall in a long time in some areas of Bangka Island. Mesoscale Convective Complex (MCC) is one type of Mesoscale Convective System (MCS). Previous research on MCC mentions that MCC can cause heavy rain for a long time. This study aims to identify the phenomenon of MCC in Bangka Island both in the satellite imagery and the output of the model. In addition, this study was also conducted to determine the effect of MCC on the weather conditions in Bangka Island. The study area in this research is Bangka Island with Pangkalpinang Meteorological Station as the centre of research. The data used in this research are FNL (Final Analysis) data from http://rda.ucar.edu/, Satellite Image of Himawari-8 IR1 Channel from BMKG, and meteorological observation data (synoptic and radiosonde) from Pangkalpinang Meteorological Station. The FNL data is simulated using the WRF-ARW model, verified using observation data and then visualized using GrADS. The results of the analysis of Himawari-8 satellite image data showed that two MCCs occurred on 7th and 8th February 2016 on Bangka Island and the MCC was nocturnal, which appeared at night which then continued until extinction in the morning the next day. In a peak cloud temperature review with the coordinates of Pangkalpinang Meteorological Station (-2,163 N 106,137 E) when 1st MCC and 2nd MCC events ranged from -60°C to -80°C. The result of WRF-ARW model output analysis shows that MCC area has high humidity value and positive vertical velocity value which indicates the potential of heavy rain for a long time.

  17. Mesoscale analysis of failure in quasi-brittle materials: comparison between lattice model and acoustic emission data.

    Grégoire, David; Verdon, Laura; Lefort, Vincent; Grassl, Peter; Saliba, Jacqueline; Regoin, Jean-Pierre; Loukili, Ahmed; Pijaudier-Cabot, Gilles

    2015-10-25

    The purpose of this paper is to analyse the development and the evolution of the fracture process zone during fracture and damage in quasi-brittle materials. A model taking into account the material details at the mesoscale is used to describe the failure process at the scale of the heterogeneities. This model is used to compute histograms of the relative distances between damaged points. These numerical results are compared with experimental data, where the damage evolution is monitored using acoustic emissions. Histograms of the relative distances between damage events in the numerical calculations and acoustic events in the experiments exhibit good agreement. It is shown that the mesoscale model provides relevant information from the point of view of both global responses and the local failure process. © 2015 The Authors. International Journal for Numerical and Analytical Methods in Geomechanics published by John Wiley & Sons Ltd.

  18. Short range forecasting of sea breeze generated thunderstorms at the Kennedy Space Center: A real-time experiment using a primitive equation mesoscale numerical model

    Lyons, Walter A.; Schuh, Jerome A.; Moon, Dennis; Pielke, Roger A.; Cotton, William; Arritt, Raymond

    1987-01-01

    The operational efficiency of using guidance from a mesoscale numerical model to improve sea breeze thunderstorm forecasts at and around the Shuttle landing strip was assessed. The Prognostic Three-Dimensional Mesoscale (P3DM) model, developed as a sea breeze model, reveals a strong correlation between regions of mesoscale convergence and the triggering of sea breeze convection thunderstorms. The P3DM was modified to generate stability parameters familiar to the operational forecaster. In addition to the mesoscale fields of wind, vertical motion, moisture, temperature, a stability indicator, a combination of model-predicted K and Lifted Indices and the maximum grid cell vertical motion, were proposed and tested. Results of blind tests indicate that a forecaster, provided with guidance derived from model output, could improve local thunderstorm forecasts.

  19. Mesoscale model response to random, surface-based perturbations — A sea-breeze experiment

    Garratt, J. R.; Pielke, R. A.; Miller, W. F.; Lee, T. J.

    1990-09-01

    The introduction into a mesoscale model of random (in space) variations in roughness length, or random (in space and time) surface perturbations of temperature and friction velocity, produces a measurable, but barely significant, response in the simulated flow dynamics of the lower atmosphere. The perturbations are an attempt to include the effects of sub-grid variability into the ensemble-mean parameterization schemes used in many numerical models. Their magnitude is set in our experiments by appeal to real-world observations of the spatial variations in roughness length and daytime surface temperature over the land on horizontal scales of one to several tens of kilometers. With sea-breeze simulations, comparisons of a number of realizations forced by roughness-length and surface-temperature perturbations with the standard simulation reveal no significant change in ensemble mean statistics, and only small changes in the sea-breeze vertical velocity. Changes in the updraft velocity for individual runs, of up to several cms-1 (compared to a mean of 14 cms-1), are directly the result of prefrontal temperature changes of 0.1 to 0.2K, produced by the random surface forcing. The correlation and magnitude of the changes are entirely consistent with a gravity-current interpretation of the sea breeze.

  20. Modeling mesoscale diffusion and transport processes for releases within coastal zones during land/sea breezes

    Lyons, W.A.; Keen, C.S.; Schuh, J.A.

    1983-12-01

    This document discusses the impacts of coastal mesoscale regimes (CMRs) upon the transport and diffusion of potential accidental radionuclide releases from a shoreline nuclear power plant. CMRs exhibit significant spatial (horizontal and vertical) and temporal variability. Case studies illustrate land breezes, sea/lake breeze inflows and return flows, thermal internal boundary layers, fumigation, plume trapping, coastal convergence zones, thunderstorms and snow squalls. The direct application of a conventional Gaussian straight-line dose assessment model, initialized only by on-site tower data, can potentially produce highly misleading guidance as to plume impact locations. Since much is known concerning CMRs, there are many potential improvements to modularized dose assessment codes, such as by proper parameterization of TIBLs, forecasting the inland penetration of convergence zones, etc. A three-dimensional primitive equation prognostic model showed excellent agreement with detailed lake breeze field measurements, giving indications that such codes can be used in both diagnostic and prognostic studies. The use of relatively inexpensive supplemental meteorological data especially from remote sensing systems (Doppler sodar, radar, lightning strike tracking) and computerized data bases should save significantly on software development costs. Better quality assurance of emergency response codes could include systems of flags providing personnel with confidence levels as to the applicability of a code being used during any given CMR

  1. Weather and forecasting at Wilkins ice runway, Antarctica

    Carpentier, Scott

    2010-01-01

    Aviation forecasts for Wilkins ice runway in East Antarctica are developed within the conceptual framework of flow against a single dome shaped hill. Forecast challenges include the sudden onset of blizzards associated with the formation of an internal gravity wave; frontal weather; transient wake vortices and mesoscale lows; temperature limitations on runway use; and snow and fog events. These key weather aspects are presented within the context of synoptic to local scale climatologies and numerical weather prediction models.

  2. Down-scaling wind energy resource from mesoscale to local scale by nesting and data assimilation with a CFD model

    Duraisamy Jothiprakasam, Venkatesh

    2014-01-01

    The development of wind energy generation requires precise and well-established methods for wind resource assessment, which is the initial step in every wind farm project. During the last two decades linear flow models were widely used in the wind industry for wind resource assessment and micro-siting. But the linear models inaccuracies in predicting the wind speeds in very complex terrain are well known and led to use of CFD, capable of modeling the complex flow in details around specific geographic features. Mesoscale models (NWP) are able to predict the wind regime at resolutions of several kilometers, but are not well suited to resolve the wind speed and turbulence induced by the topography features on the scale of a few hundred meters. CFD has proven successful in capturing flow details at smaller scales, but needs an accurate specification of the inlet conditions. Thus coupling NWP and CFD models is a better modeling approach for wind energy applications. A one-year field measurement campaign carried out in a complex terrain in southern France during 2007-2008 provides a well-documented data set both for input and validation data. The proposed new methodology aims to address two problems: the high spatial variation of the topography on the domain lateral boundaries, and the prediction errors of the mesoscale model. It is applied in this work using the open source CFD code Code-Saturne, coupled with the mesoscale forecast model of Meteo-France (ALADIN). The improvement is obtained by combining the mesoscale data as inlet condition and field measurement data assimilation into the CFD model. Newtonian relaxation (nudging) data assimilation technique is used to incorporate the measurement data into the CFD simulations. The methodology to reconstruct long term averages uses a clustering process to group the similar meteorological conditions and to reduce the number of CFD simulations needed to reproduce 1 year of atmospheric flow over the site. The assimilation

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

    Cassardo, C.; Loglisci, N.

    2005-01-01

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

  4. Meteorology, Macrophysics, Microphysics, Microwaves, and Mesoscale Modeling of Mediterranean Mountain Storms: The M8 Laboratory

    Starr, David O. (Technical Monitor); Smith, Eric A.

    2002-01-01

    Comprehensive understanding of the microphysical nature of Mediterranean storms can be accomplished by a combination of in situ meteorological data analysis and radar-passive microwave data analysis, effectively integrated with numerical modeling studies at various scales, from synoptic scale down through the mesoscale, the cloud macrophysical scale, and ultimately the cloud microphysical scale. The microphysical properties of and their controls on severe storms are intrinsically related to meteorological processes under which storms have evolved, processes which eventually select and control the dominant microphysical properties themselves. This involves intense convective development, stratiform decay, orographic lifting, and sloped frontal lifting processes, as well as the associated vertical motions and thermodynamical instabilities governing physical processes that affect details of the size distributions and fall rates of the various types of hydrometeors found within the storm environment. Insofar as hazardous Mediterranean storms, highlighted in this study by three mountain storms producing damaging floods in northern Italy between 1992 and 2000, developing a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution and the heterogeneous nature of precipitation fields within a storm domain. This involves convective development, stratiform transition and decay, orographic lifting, and sloped frontal lifting processes. This also involves vertical motions and thermodynamical instabilities governing physical processes that determine details of the liquid/ice water contents, size disi:ributions, and fall rates of the various modes of hydrometeors found within hazardous storm environments.

  5. Genesis of Hurricane Sandy (2012) Simulated with a Global Mesoscale Model

    Shen, Bo-Wen; DeMaria, Mark; Li, J.-L. F.; Cheung, S.

    2013-01-01

    In this study, we investigate the formation predictability of Hurricane Sandy (2012) with a global mesoscale model. We first present five track and intensity forecasts of Sandy initialized at 00Z 22-26 October 2012, realistically producing its movement with a northwestward turn prior to its landfall. We then show that three experiments initialized at 00Z 16-18 October captured the genesis of Sandy with a lead time of up to 6 days and simulated reasonable evolution of Sandy's track and intensity in the next 2 day period of 18Z 21-23 October. Results suggest that the extended lead time of formation prediction is achieved by realistic simulations of multiscale processes, including (1) the interaction between an easterly wave and a low-level westerly wind belt (WWB) and (2) the appearance of the upper-level trough at 200 hPa to Sandy's northwest. The low-level WWB and upper-level trough are likely associated with a Madden-Julian Oscillation.

  6. Energy- and humidity-budget of the non-hydrostatic mesoscale model GESIMA by nesting into the regional climate model REMO; Energie- und Feuchtehaushalt im nichthydrostatischen Mesoskalamodell GESIMA bei Nestung in das Regionalklimamodell REMO

    Horneffer, K. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Gewaesserphysik]|[Hamburg Univ. (Germany). Fachbereich 15 - Geowissenschaften

    1997-12-31

    The `Geesthacht Simulationsmodel of the Atmosphere` (GESIMA) was nested into the `Regional Climate Model` (REMO). Exemplary studies prove that the presented nesting scheme is suitable to resolve subscale phenomena in the regional climate model. Some results of simulations above the island Gotland in the Baltic Sea were presented. The mesoscale model GESIMA could now be used to analyze real synoptic weather situations. (orig.) [Deutsch] Das Geesthachter Simulationsmodell der Atmosphaere (GESIMA) wird in das Regionalklimamodell (REMO) genestet. Beispielhafte Untersuchungen zeigen, dass mit der genesteten Modellversion subskalige Effekte, die durch das grobe Raster des Regionalklimamodells fallen, aufgeloest werden. Dies wird anhand von Simulationen ueberprueft. Hauptuntersuchungsgegenstand ist die Insel Gotland in der Ostsee. Duch die Nestung kann das Mesoskalamodell fuer tatsaechliche synoptische Situationen eingesetzt werden. (orig.)

  7. Quantitative modelling of the closure of meso-scale parallel currents in the nightside ionosphere

    A. Marchaudon

    2004-01-01

    Full Text Available On 12 January 2000, during a northward IMF period, two successive conjunctions occur between the CUTLASS SuperDARN radar pair and the two satellites Ørsted and FAST. This situation is used to describe and model the electrodynamic of a nightside meso-scale arc associated with a convection shear. Three field-aligned current sheets, one upward and two downward on both sides, are observed. Based on the measurements of the parallel currents and either the conductance or the electric field profile, a model of the ionospheric current closure is developed along each satellite orbit. This model is one-dimensional, in a first attempt and a two-dimensional model is tested for the Ørsted case. These models allow one to quantify the balance between electric field gradients and ionospheric conductance gradients in the closure of the field-aligned currents. These radar and satellite data are also combined with images from Polar-UVI, allowing for a description of the time evolution of the arc between the two satellite passes. The arc is very dynamic, in spite of quiet solar wind conditions. Periodic enhancements of the convection and of electron precipitation associated with the arc are observed, probably associated with quasi-periodic injections of particles due to reconnection in the magnetotail. Also, a northward shift and a reorganisation of the precipitation pattern are observed, together with a southward shift of the convection shear. Key words. Ionosphere (auroral ionosphere; electric fields and currents; particle precipitation – Magnetospheric physics (magnetosphere-ionosphere interactions

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

    Rahmat, R. F.; Nasution, F. R.; Seniman; Syahputra, M. F.; Sitompul, O. S.

    2018-02-01

    Weather is condition of air in a certain region at a relatively short period of time, measured with various parameters such as; temperature, air preasure, wind velocity, humidity and another phenomenons in the atmosphere. In fact, extreme weather due to global warming would lead to drought, flood, hurricane and other forms of weather occasion, which directly affects social andeconomic activities. Hence, a forecasting technique is to predict weather with distinctive output, particullary mapping process based on GIS with information about current weather status in certain cordinates of each region with capability to forecast for seven days afterward. Data used in this research are retrieved in real time from the server openweathermap and BMKG. In order to obtain a low error rate and high accuracy of forecasting, the authors use Bayesian Model Averaging (BMA) method. The result shows that the BMA method has good accuracy. Forecasting error value is calculated by mean square error shows (MSE). The error value emerges at minumum temperature rated at 0.28 and maximum temperature rated at 0.15. Meanwhile, the error value of minimum humidity rates at 0.38 and the error value of maximum humidity rates at 0.04. Afterall, the forecasting error rate of wind speed is at 0.076. The lower the forecasting error rate, the more optimized the accuracy is.

  9. Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: the San Fruttuoso case of 1915

    Parodi, Antonio; Ferraris, Luca; Gallus, William; Maugeri, Maurizio; Molini, Luca; Siccardi, Franco; Boni, Giorgio

    2017-05-01

    Highly localized and persistent back-building mesoscale convective systems represent one of the most dangerous flash-flood-producing storms in the north-western Mediterranean area. Substantial warming of the Mediterranean Sea in recent decades raises concerns over possible increases in frequency or intensity of these types of events as increased atmospheric temperatures generally support increases in water vapour content. However, analyses of the historical record do not provide a univocal answer, but these are likely affected by a lack of detailed observations for older events. In the present study, 20th Century Reanalysis Project initial and boundary condition data in ensemble mode are used to address the feasibility of performing cloud-resolving simulations with 1 km horizontal grid spacing of a historic extreme event that occurred over Liguria: the San Fruttuoso case of 1915. The proposed approach focuses on the ensemble Weather Research and Forecasting (WRF) model runs that show strong convergence over the Ligurian Sea (17 out of 56 members) as these runs are the ones most likely to best simulate the event. It is found that these WRF runs generally do show wind and precipitation fields that are consistent with the occurrence of highly localized and persistent back-building mesoscale convective systems, although precipitation peak amounts are underestimated. Systematic small north-westward position errors with regard to the heaviest rain and strongest convergence areas imply that the reanalysis members may not be adequately representing the amount of cool air over the Po Plain outflowing into the Ligurian Sea through the Apennines gap. Regarding the role of historical data sources, this study shows that in addition to reanalysis products, unconventional data, such as historical meteorological bulletins, newspapers, and even photographs, can be very valuable sources of knowledge in the reconstruction of past extreme events.

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

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

    2018-06-01

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

  11. Complementary Use of Glider Data, Altimetry, and Model for Exploring Mesoscale Eddies in the Tropical Pacific Solomon Sea

    Gourdeau, L.; Verron, J.; Chaigneau, A.; Cravatte, S.; Kessler, W.

    2017-11-01

    Mesoscale activity is an important component of the Solomon Sea circulation that interacts with the energetic low-latitude western boundary currents of the South Tropical Pacific Ocean carrying waters of subtropical origin before joining the equatorial Pacific. Mixing associated with mesoscale activity could explain water mass transformation observed in the Solomon Sea that likely impacts El Niño Southern Oscillation dynamics. This study makes synergetic use of glider data, altimetry, and high-resolution model for exploring mesoscale eddies, especially their vertical structures, and their role on the Solomon Sea circulation. The description of individual eddies observed by altimetry and gliders provides the first elements to characterize the 3-D structure of these tropical eddies, and confirms the usefulness of the model to access a more universal view of such eddies. Mesoscale eddies appear to have a vertical extension limited to the Surface Waters (SW) and the Upper Thermocline Water (UTW), i.e., the first 140-150 m depth. Most of the eddies are nonlinear, meaning that eddies can trap and transport water properties. But they weakly interact with the deep New Guinea Coastal Undercurrent that is a key piece of the equatorial circulation. Anticyclonic eddies are particularly efficient to advect salty and warm SW coming from the intrusion of equatorial Pacific waters at Solomon Strait, and to impact the characteristics of the New Guinea Coastal Current. Cyclonic eddies are particularly efficient to transport South Pacific Tropical Water (SPTW) anomalies from the North Vanuatu Jet and to erode by diapycnal mixing the high SPTW salinity.

  12. Surface Energy Balance in Jakarta and Neighboring Regions As Simulated Using Fifth Mesoscale Model (MM5

    Yopi Ilhamsyah

    2014-04-01

    Full Text Available The objective of the present research was to assess the surface energy balance particularly in terms of the computed surface energy and radiation balance and the development of boundary layer over Jakarta and Neighboring Regions (JNR by means of numerical model of fifth generation of Mesoscale Model (MM5. The MM5 with four domains of 9 kilometers in spatial resolution presenting the outermost and the innermost of JNR is utilized. The research focuses on the third and fourth domains covering the entire JNR. The description between radiation and energy balance at the surface is obtained from the model. The result showed that energy balance is higher in the city area during daytime. Meanwhile, energy components, e.g., surface sensible and latent heat flux showed that at the sea and in the city areas were higher than other areas. Moreover, ground flux showed eastern region was higher than others. In general, radiation and energy balance was higher in the daytime and lower in the nighttime for all regions. The calculation of Bowen Ratio, the ratio of surface sensible and latent heat fluxes, was also higher in the city area, reflecting the dominations of urban and built-up land in the region. Meanwhile, Bowen Ratio in the rural area dominated by irrigated cropland was lower. It is consistent with changes of land cover properties, e.g. albedo, soil moisture, and thermal characteristics. In addition, the boundary layer is also higher in the city. Meanwhile western region dominated by suburban showed higher boundary layer instead of eastern region.

  13. Impact of aircraft exhaust on the atmosphere. Box model studies and 3-D mesoscale numerical case studies of seasonal differences

    Petry, H; Ebel, A; Franzkowiak, V; Hendricks, J; Lippert, E; Moellhoff, M [Koeln Univ. (Germany). Inst. fuer Geophysik und Meteorologie

    1998-12-31

    The impact of aircraft emissions released in the tropopause region on atmospheric trace gases as O{sub 3} or HNO{sub 3} is investigated by means of model studies. Special emphasis is drawn on seasonal effects. A box model is applied as well as a 3-D mesoscale chemistry transport model. These model studies show that the impact of aircraft emissions on ozone in the tropopause region is much stronger in summer than in late autumn with a difference of one order of magnitude. (author) 14 refs.

  14. Impact of aircraft exhaust on the atmosphere. Box model studies and 3-D mesoscale numerical case studies of seasonal differences

    Petry, H.; Ebel, A.; Franzkowiak, V.; Hendricks, J.; Lippert, E.; Moellhoff, M. [Koeln Univ. (Germany). Inst. fuer Geophysik und Meteorologie

    1997-12-31

    The impact of aircraft emissions released in the tropopause region on atmospheric trace gases as O{sub 3} or HNO{sub 3} is investigated by means of model studies. Special emphasis is drawn on seasonal effects. A box model is applied as well as a 3-D mesoscale chemistry transport model. These model studies show that the impact of aircraft emissions on ozone in the tropopause region is much stronger in summer than in late autumn with a difference of one order of magnitude. (author) 14 refs.

  15. WRF Mesoscale Pre-Run for the Wind Atlas of Mexico

    Hahmann, Andrea N.; Pena Diaz, Alfredo; Hansen, Jens Carsten

    2016-01-01

    This report documents the work performed by DTU Wind Energy for the project “Atlas Eólico Mexicano” or the Wind Atlas of Mexico. This document reports on the methods used in “Pre-run” of the windmapping project for Mexico. The interim mesoscale modeling results were calculated from the output of simulations using the Weather, Research and Forecasting (WRF) model. We document the method used to run the mesoscale simulations and to generalize the WRF model wind climatologies. A separate section...

  16. Meso-Scale Modeling of Spall in a Heterogeneous Two-Phase Material

    Springer, Harry Keo [Univ. of California, Davis, CA (United States)

    2008-07-11

    The influence of the heterogeneous second-phase particle structure and applied loading conditions on the ductile spall response of a model two-phase material was investigated. Quantitative metallography, three-dimensional (3D) meso-scale simulations (MSS), and small-scale spall experiments provided the foundation for this study. Nodular ductile iron (NDI) was selected as the model two-phase material for this study because it contains a large and readily identifiable second- phase particle population. Second-phase particles serve as the primary void nucleation sites in NDI and are, therefore, central to its ductile spall response. A mathematical model was developed for the NDI second-phase volume fraction that accounted for the non-uniform particle size and spacing distributions within the framework of a length-scale dependent Gaussian probability distribution function (PDF). This model was based on novel multiscale sampling measurements. A methodology was also developed for the computer generation of representative particle structures based on their mathematical description, enabling 3D MSS. MSS were used to investigate the effects of second-phase particle volume fraction and particle size, loading conditions, and physical domain size of simulation on the ductile spall response of a model two-phase material. MSS results reinforce existing model predictions, where the spall strength metric (SSM) logarithmically decreases with increasing particle volume fraction. While SSM predictions are nearly independent of applied load conditions at lower loading rates, which is consistent with previous studies, loading dependencies are observed at higher loading rates. There is also a logarithmic decrease in SSM for increasing (initial) void size, as well. A model was developed to account for the effects of loading rate, particle size, matrix sound-speed, and, in the NDI-specific case, the probabilistic particle volume fraction model. Small-scale spall experiments were designed

  17. GEM: a dynamic tracking model for mesoscale eddies in the ocean

    Li, Qiu-Yang; Sun, Liang; Lin, Sheng-Fu

    2016-12-01

    The Genealogical Evolution Model (GEM) presented here is an efficient logical model used to track dynamic evolution of mesoscale eddies in the ocean. It can distinguish between different dynamic processes (e.g., merging and splitting) within a dynamic evolution pattern, which is difficult to accomplish using other tracking methods. To this end, the GEM first uses a two-dimensional (2-D) similarity vector (i.e., a pair of ratios of overlap area between two eddies to the area of each eddy) rather than a scalar to measure the similarity between eddies, which effectively solves the "missing eddy" problem (temporarily lost eddy in tracking). Second, for tracking when an eddy splits, the GEM uses both "parent" (the original eddy) and "child" (eddy split from parent) and the dynamic processes are described as the birth and death of different generations. Additionally, a new look-ahead approach with selection rules effectively simplifies computation and recording. All of the computational steps are linear and do not include iteration. Given the pixel number of the target region L, the maximum number of eddies M, the number N of look-ahead time steps, and the total number of time steps T, the total computer time is O(LM(N + 1)T). The tracking of each eddy is very smooth because we require that the snapshots of each eddy on adjacent days overlap one another. Although eddy splitting or merging is ubiquitous in the ocean, they have different geographic distributions in the North Pacific Ocean. Both the merging and splitting rates of the eddies are high, especially at the western boundary, in currents and in "eddy deserts". The GEM is useful not only for satellite-based observational data, but also for numerical simulation outputs. It is potentially useful for studying dynamic processes in other related fields, e.g., the dynamics of cyclones in meteorology.

  18. Impact of two chemistry mechanisms fully coupled with mesoscale model on the atmospheric pollutants distribution

    Arteta, J.; Cautenet, S.; Taghavi, M.; Audiffren, N.

    time on SGI 3800 with 30 processors). Simplified mechanisms are really important to study cases for which an online coupling is necessary between meso-scale and chemistry models (clouds or aerosols plumes impacts, highly variable meteorology).

  19. Mesoscale atmospheric modeling of the July 12, 1992 tritium release from the Savannah River Site

    Fast, J.D.; O'Steen, B.L.; Addis, R.P.

    1992-01-01

    In August of 1991, the Environmental Transport Group (ETG) began the development of an advanced Emergency Response (ER) system based upon the Colorado State University Regional Atmospheric Modeling System (RAMS). This model simulates the three-dimensional, time-dependent, flow field and thermodynamic structure of the planetary boundary layer (PBL). A companion Lagrangian Particle Dispersion Model (LPDM) simulates contaminant transport based on the flow and turbulence fields generated by RAMS. This paper describes the performance of the advanced ER system in predicting transport and diffusion near the SRS when compared to meteorological and sampling data taken during the July 12, 1992 tritium release. Since PUFF/PLUME and 2DPUF are two Weather INformation and Display (WIND) System atmospheric models that were used to predict the transport and diffusion of the plume at the time of the release, the results from the advanced ER system are also compared to those produced by PUFF/PLUME and 2DPUF

  20. Ensemble modelling of nitrogen fluxes: data fusion for a Swedish meso-scale catchment

    J.-F. Exbrayat

    2010-12-01

    Full Text Available Model predictions of biogeochemical fluxes at the landscape scale are highly uncertain, both with respect to stochastic (parameter and structural uncertainty. In this study 5 different models (LASCAM, LASCAM-S, a self-developed tool, SWAT and HBV-N-D designed to simulate hydrological fluxes as well as mobilisation and transport of one or several nitrogen species were applied to the mesoscale River Fyris catchment in mid-eastern Sweden.

    Hydrological calibration against 5 years of recorded daily discharge at two stations gave highly variable results with Nash-Sutcliffe Efficiency (NSE ranging between 0.48 and 0.83. Using the calibrated hydrological parameter sets, the parameter uncertainty linked to the nitrogen parameters was explored in order to cover the range of possible predictions of exported loads for 3 nitrogen species: nitrate (NO3, ammonium (NH4 and total nitrogen (Tot-N. For each model and each nitrogen species, predictions were ranked in two different ways according to the performance indicated by two different goodness-of-fit measures: the coefficient of determination R2 and the root mean square error RMSE. A total of 2160 deterministic Single Model Ensembles (SME was generated using an increasing number of members (from the 2 best to the 10 best single predictions. Finally the best SME for each model, nitrogen species and discharge station were selected and merged into 330 different Multi-Model Ensembles (MME. The evolution of changes in R2 and RMSE was used as a performance descriptor of the ensemble procedure.

    In each studied case, numerous ensemble merging schemes were identified which outperformed any of their members. Improvement rates were generally higher when worse members were introduced. The highest improvements were achieved for the nitrogen SMEs compiled with multiple linear regression models with R2 selected members, which

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

    Andersen, Ove; Torp, Kristian

    2016-01-01

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

  2. How does the Redi parameter for mesoscale mixing impact global climate in an Earth System Model?

    Pradal, Marie-Aude; Gnanadesikan, Anand

    2014-09-01

    A coupled climate model is used to examine the impact of an increase in the mixing due to mesoscale eddies on the global climate system. A sixfold increase in the Redi mixing coefficient ARedi, which is within the admissible range of variation, has the overall effect of warming the global-mean surface air and sea surface temperatures by more than 1°C. Locally, sea surface temperatures increase by up to 7°C in the North Pacific and by up to 4°C in the Southern Ocean, with corresponding impacts on the ice concentration and ice extent in polar regions. However, it is not clear that the changes in heat transport from tropics to poles associated with changing this coefficient are primarily responsible for these changes. We found that the changes in the transport of heat are often much smaller than changes in long-wave trapping and short-wave absorption. Additionally, changes in the advective and diffusive transport of heat toward the poles often oppose each other. However, we note that the poleward transport of salt increases near the surface as ARedi increases. We suggest a causal chain in which enhanced eddy stirring leads to increased high-latitude surface salinity reducing salt stratification and water column stability and enhancing convection, triggering two feedback loops. In one, deeper convection prevents sea ice formation, which decreases albedo, which increases SW absorption, further increasing SST and decreasing sea ice formation. In the other, increased SST and reduced sea ice allow for more water vapor in the atmosphere, trapping long-wave radiation. Destratifying the polar regions is thus a potential way in which changes in ocean circulation might warm the planet.

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

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

    2018-03-01

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

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

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

  5. Mesoscale models for stacking faults, deformation twins and martensitic transformations: Linking atomistics to continuum

    Kibey, Sandeep A.

    We present a hierarchical approach that spans multiple length scales to describe defect formation---in particular, formation of stacking faults (SFs) and deformation twins---in fcc crystals. We link the energy pathways (calculated here via ab initio density functional theory, DFT) associated with formation of stacking faults and twins to corresponding heterogeneous defect nucleation models (described through mesoscale dislocation mechanics). Through the generalized Peieirls-Nabarro model, we first correlate the width of intrinsic SFs in fcc alloy systems to their nucleation pathways called generalized stacking fault energies (GSFE). We then establish a qualitative dependence of twinning tendency in fee metals and alloys---specifically, in pure Cu and dilute Cu-xAl (x= 5.0 and 8.3 at.%)---on their twin-energy pathways called the generalized planar fault energies (GPFE). We also link the twinning behavior of Cu-Al alloys to their electronic structure by determining the effect of solute Al on the valence charge density redistribution at the SF through ab initio DFT. Further, while several efforts have been undertaken to incorporate twinning for predicting stress-strain response of fcc materials, a fundamental law for critical twinning stress has not yet emerged. We resolve this long-standing issue by linking quantitatively the twin-energy pathways (GPFE) obtained via ab initio DFT to heterogeneous, dislocation-based twin nucleation models. We establish an analytical expression that quantitatively predicts the critical twinning stress in fcc metals in agreement with experiments without requiring any empiricism at any length scale. Our theory connects twinning stress to twin-energy pathways and predicts a monotonic relation between stress and unstable twin stacking fault energy revealing the physics of twinning. We further demonstrate that the theory holds for fcc alloys as well. Our theory inherently accounts for directional nature of twinning which available

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

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

    2009-01-01

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

  7. Assimilation of low-level wind in a high-resolution mesoscale model using the back and forth nudging algorithm

    Jean-François Mahfouf

    2012-06-01

    Full Text Available The performance of a new data assimilation algorithm called back and forth nudging (BFN is evaluated using a high-resolution numerical mesoscale model and simulated wind observations in the boundary layer. This new algorithm, of interest for the assimilation of high-frequency observations provided by ground-based active remote-sensing instruments, is straightforward to implement in a realistic atmospheric model. The convergence towards a steady-state profile can be achieved after five iterations of the BFN algorithm, and the algorithm provides an improved solution with respect to direct nudging. It is shown that the contribution of the nudging term does not dominate over other model physical and dynamical tendencies. Moreover, by running backward integrations with an adiabatic version of the model, the nudging coefficients do not need to be increased in order to stabilise the numerical equations. The ability of BFN to produce model changes upstream from the observations, in a similar way to 4-D-Var assimilation systems, is demonstrated. The capacity of the model to adjust to rapid changes in wind direction with the BFN is a first encouraging step, for example, to improve the detection and prediction of low-level wind shear phenomena through high-resolution mesoscale modelling over airports.

  8. Meso-Scale Modelling of Deformation, Damage and Failure in Dual Phase Steels

    Sari Sarraf, Iman

    Advanced high strength steels (AHSS), such as dual phase (DP) and transformation induced plasticity (TRIP) steels, offer high ductility, formability, and strength, as well as high strength-to-weight ratio and improved crash resistance. Dual phase steels belong to a family of high strength grades which consist of martensite, responsible for strengthening, distributed in a ductile ferrite matrix which accommodates the deformation throughout the forming process. It has been shown that the predominant damage mechanism and failure in DP steels depends on the ferrite and martensite grain sizes and their morphology, and can range from a mixture of brittle and ductile rupture to completely ductile rupture in a quasi-static uniaxial tension test. In this study, a hybrid finite element cellular automata model, initially proposed by Anton Shterenlikht (2003), was developed to evaluate the forming behaviour and predict the onset of instability and damage evolution in a dual phase steel. In this model, the finite element constitutive model is used to represent macro-level strain gradients and a damage variable, and two different cell arrays are designed to represent the ductile and brittle fracture modes in meso-scale. In the FE part of the model, a modified Rousselier ductile damage model is developed to account for nucleation, growth and coalescence of voids. Also, several rate-dependent hardening models were developed and evaluated to describe the work hardening flow curve of DP600. Based on statistical analysis and simulation results, a modified Johnson-Cook (JC) model and a multiplicative combination of the Voce-modified JC functions were found to be the most accurate hardening models. The developed models were then implemented in a user-defined material subroutine (VUMAT) for ABAQUS/Explicit finite element simulation software to simulate uniaxial tension tests at strain rates ranging from 0.001 1/s to 1000 1/s, Marciniak tests, and electrohydraulic free-forming (EHFF

  9. 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

    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.

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

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

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

    Anne M. Rosenthal; Francis Fujioka

    2004-01-01

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

  12. Modeling Silicate Weathering for Elevated CO2 and Temperature

    Bolton, E. W.

    2016-12-01

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

  13. On the influence of temporal and spatial resolution of aircraft emission inventories for mesoscale modeling of pollutant dispersion

    Franzkowiak, V.; Petry, H.; Ebel, A. [Cologne Univ. (Germany). Inst. for Geophysics and Meteorology

    1997-12-31

    The sensitivity of a mesoscale chemistry transport model to the temporal and spatial resolution of aircraft emission inventories is evaluated. A statistical analysis of air traffic in the North-Atlantic flight corridor is carried out showing a highly variable, fine structured spatial distribution and a pronounced daily variation. Sensitivity studies comparing different emission scenarios reveal a strong dependency to the emission time and location of both transport and response in chemical formation of subsequent products. The introduction of a pronounced daily variation leads to a 30% higher ozone production in comparison to uniformly distributed emissions. (author) 9 refs.

  14. On the influence of temporal and spatial resolution of aircraft emission inventories for mesoscale modeling of pollutant dispersion

    Franzkowiak, V; Petry, H; Ebel, A [Cologne Univ. (Germany). Inst. for Geophysics and Meteorology

    1998-12-31

    The sensitivity of a mesoscale chemistry transport model to the temporal and spatial resolution of aircraft emission inventories is evaluated. A statistical analysis of air traffic in the North-Atlantic flight corridor is carried out showing a highly variable, fine structured spatial distribution and a pronounced daily variation. Sensitivity studies comparing different emission scenarios reveal a strong dependency to the emission time and location of both transport and response in chemical formation of subsequent products. The introduction of a pronounced daily variation leads to a 30% higher ozone production in comparison to uniformly distributed emissions. (author) 9 refs.

  15. Modeling and Forecasting Average Temperature for Weather Derivative Pricing

    Zhiliang Wang

    2015-01-01

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

  16. Evaluation of data assimilation techniques for a mesoscale meteorological model and their effects on air quality model results

    Amicarelli, A; Pelliccioni, A [ISPESL - Dipartimento Insediamenti Produttivi e Interazione con l' Ambiente, Via Fontana Candida, 1 00040 Monteporzio Catone (RM) Italy (Italy); Finardi, S; Silibello, C [ARIANET, via Gilino 9, 20128 Milano (Italy); Gariazzo, C

    2008-05-01

    Data assimilation techniques are methods to limit the growth of errors in a dynamical model by allowing observations distributed in space and time to force (nudge) model solutions. They have become common for meteorological model applications in recent years, especially to enhance weather forecast and to support air-quality studies. In order to investigate the influence of different data assimilation techniques on the meteorological fields produced by RAMS model, and to evaluate their effects on the ozone and PM{sub 10} concentrations predicted by FARM model, several numeric experiments were conducted over the urban area of Rome, Italy, during a summer episode.

  17. Evaluation of data assimilation techniques for a mesoscale meteorological model and their effects on air quality model results

    Amicarelli, A.; Gariazzo, C.; Finardi, S.; Pelliccioni, A.; Silibello, C.

    2008-05-01

    Data assimilation techniques are methods to limit the growth of errors in a dynamical model by allowing observations distributed in space and time to force (nudge) model solutions. They have become common for meteorological model applications in recent years, especially to enhance weather forecast and to support air-quality studies. In order to investigate the influence of different data assimilation techniques on the meteorological fields produced by RAMS model, and to evaluate their effects on the ozone and PM10 concentrations predicted by FARM model, several numeric experiments were conducted over the urban area of Rome, Italy, during a summer episode.

  18. Evaluation of data assimilation techniques for a mesoscale meteorological model and their effects on air quality model results

    Amicarelli, A; Pelliccioni, A; Finardi, S; Silibello, C; Gariazzo, C

    2008-01-01

    Data assimilation techniques are methods to limit the growth of errors in a dynamical model by allowing observations distributed in space and time to force (nudge) model solutions. They have become common for meteorological model applications in recent years, especially to enhance weather forecast and to support air-quality studies. In order to investigate the influence of different data assimilation techniques on the meteorological fields produced by RAMS model, and to evaluate their effects on the ozone and PM 10 concentrations predicted by FARM model, several numeric experiments were conducted over the urban area of Rome, Italy, during a summer episode

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

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

    2017-12-01

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

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

    Riette, Sébastien; Lac, Christine

    2016-08-01

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

  1. Weather Derivatives and Stochastic Modelling of Temperature

    Fred Espen Benth

    2011-01-01

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

  2. Towards a generalization procedure for WRF mesoscale wind climatologies

    Hahmann, Andrea N.; Casso, P.; Campmany, E.

    We present a method for generalizing wind climatologies generated from mesoscale model output (e.g. the Weather, Research and Forecasting (WRF) model.) The generalization procedure is based on Wind Atlas framework of WAsP and KAMM/WAsP, and been extensively in wind resources assessment in DTU Wind...... generalized wind climatologies estimated by the microscale model WAsP and the methodology presented here. For the Danish wind measurements the mean absolute error in the ‘raw’ wind speeds is 9.2%, while the mean absolute error in the generalized wind speeds is 4.1%. The generalization procedure has been...

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

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

    2017-12-01

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

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

    Daling, Per S.; Stroem, Tove

    1999-01-01

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

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

    Wai-Kin Wong

    2013-01-01

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

  6. Mesoscale Characterization of Fracture Properties of Steel Fiber-Reinforced Concrete Using a Lattice–Particle Model

    Francisco Montero-Chacón

    2017-02-01

    Full Text Available This work presents a lattice–particle model for the analysis of steel fiber-reinforced concrete (SFRC. In this approach, fibers are explicitly modeled and connected to the concrete matrix lattice via interface elements. The interface behavior was calibrated by means of pullout tests and a range for the bond properties is proposed. The model was validated with analytical and experimental results under uniaxial tension and compression, demonstrating the ability of the model to correctly describe the effect of fiber volume fraction and distribution on fracture properties of SFRC. The lattice–particle model was integrated into a hierarchical homogenization-based scheme in which macroscopic material parameters are obtained from mesoscale simulations. Moreover, a representative volume element (RVE analysis was carried out and the results shows that such an RVE does exist in the post-peak regime and until localization takes place. Finally, the multiscale upscaling strategy was successfully validated with three-point bending tests.

  7. Mesoscale Characterization of Fracture Properties of Steel Fiber-Reinforced Concrete Using a Lattice-Particle Model.

    Montero-Chacón, Francisco; Cifuentes, Héctor; Medina, Fernando

    2017-02-21

    This work presents a lattice-particle model for the analysis of steel fiber-reinforced concrete (SFRC). In this approach, fibers are explicitly modeled and connected to the concrete matrix lattice via interface elements. The interface behavior was calibrated by means of pullout tests and a range for the bond properties is proposed. The model was validated with analytical and experimental results under uniaxial tension and compression, demonstrating the ability of the model to correctly describe the effect of fiber volume fraction and distribution on fracture properties of SFRC. The lattice-particle model was integrated into a hierarchical homogenization-based scheme in which macroscopic material parameters are obtained from mesoscale simulations. Moreover, a representative volume element (RVE) analysis was carried out and the results shows that such an RVE does exist in the post-peak regime and until localization takes place. Finally, the multiscale upscaling strategy was successfully validated with three-point bending tests.

  8. Mesoscale Characterization of Fracture Properties of Steel Fiber-Reinforced Concrete Using a Lattice–Particle Model

    Montero-Chacón, Francisco; Cifuentes, Héctor; Medina, Fernando

    2017-01-01

    This work presents a lattice–particle model for the analysis of steel fiber-reinforced concrete (SFRC). In this approach, fibers are explicitly modeled and connected to the concrete matrix lattice via interface elements. The interface behavior was calibrated by means of pullout tests and a range for the bond properties is proposed. The model was validated with analytical and experimental results under uniaxial tension and compression, demonstrating the ability of the model to correctly describe the effect of fiber volume fraction and distribution on fracture properties of SFRC. The lattice–particle model was integrated into a hierarchical homogenization-based scheme in which macroscopic material parameters are obtained from mesoscale simulations. Moreover, a representative volume element (RVE) analysis was carried out and the results shows that such an RVE does exist in the post-peak regime and until localization takes place. Finally, the multiscale upscaling strategy was successfully validated with three-point bending tests. PMID:28772568

  9. Meso-scale modelling of the heat conductivity effect on the shock response of a porous material

    Resnyansky, A. D.

    2017-06-01

    Understanding of deformation mechanisms of porous materials under shock compression is important for tailoring material properties at the shock manufacturing of advanced materials from substrate powders and for studying the response of porous materials under shock loading. Numerical set-up of the present work considers a set of solid particles separated by air representing a volume of porous material. Condensed material in the meso-scale set-up is simulated with a viscoelastic rate sensitive material model with heat conduction formulated from the principles of irreversible thermodynamics. The model is implemented in the CTH shock physics code. The meso-scale CTH simulation of the shock loading of the representative volume reveals the mechanism of pore collapse and shows in detail the transition from a high porosity case typical for abnormal Hugoniot response to a moderate porosity case typical for conventional Hugoniot response. Results of the analysis agree with previous analytical considerations and support hypotheses used in the two-phase approach.

  10. Geodetic Space Weather Monitoring by means of Ionosphere Modelling

    Schmidt, Michael

    2017-04-01

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

  11. Modeling the influence of organic acids on soil weathering

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

    2014-01-01

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

  12. Screen-level non-GTS data assimilation in a limited-area mesoscale model

    M. Milelli

    2010-06-01

    Full Text Available The forecast in areas of very complex topography, as for instance the Alpine region, is still a challenge even for the new generation of numerical weather prediction models which aim at reaching the km-scale. The problem is enhanced by a general lack of standard observations, which is even more evident over the southern side of the Alps. For this reason, it would be useful to increase the performance of the mathematical models by locally assimilating non-conventional data. Since in ARPA Piemonte there is the availability of a great number of non-GTS stations, it has been decided to assimilate the 2 m temperature, coming from this dataset, in the very-high resolution version of the COSMO model, which has a horizontal resolution of about 3 km, more similar to the average resolution of the thermometers. Four different weather situations have been considered, ranging from spring to winter, from cloudy to clear sky. The aim of the work is to investigate the effects of the assimilation of non-GTS data in order to create an operational very high-resolution analysis, but also to test the option of running in the future a very short-range forecast starting from these analyses (RUC or Rapid Update Cycle. The results, in terms of Root Mean Square Error, Mean Error and diurnal cycle of some surface variables such as 2 m temperature, 2 m relative humidity and 10 m wind intensity show a positive impact during the assimilation cycle which tends to dissipate a few hours after the end of it. Moreover, the 2 m temperature assimilation has a slightly positive or neutral impact on the vertical profiles of temperature, eventhough some calibration is needed for the precipitation field which is too much perturbed during the assimilation cycle, while it is unaffected in the forecast period. So the stability of the planetary boundary layer, on the one hand, has not been particularly improved by the new-data assimilation, but, on the other hand, it has not been destroyed

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

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

    2002-01-01

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

  14. Tracer experiment data sets for the verification of local and meso-scale atmospheric dispersion models including topographic effects

    Sartori, E.; Schuler, W.

    1992-01-01

    Software and data for nuclear energy applications are acquired, tested and distributed by several information centres; in particular, relevant computer codes are distributed internationally by the OECD/NEA Data Bank (France) and by ESTSC and EPIC/RSIC (United States). This activity is coordinated among the centres and is extended outside the OECD area through an arrangement with the IAEA. This article proposes more specifically a scheme for acquiring, storing and distributing atmospheric tracer experiment data (ATE) required for verification of atmospheric dispersion models especially the most advanced ones including topographic effects and specific to the local and meso-scale. These well documented data sets will form a valuable complement to the set of atmospheric dispersion computer codes distributed internationally. Modellers will be able to gain confidence in the predictive power of their models or to verify their modelling skills. (au)

  15. Modelling NOX concentrations through CFD-RANS in an urban hot-spot using high resolution traffic emissions and meteorology from a mesoscale model

    Sanchez, Beatriz; Santiago, Jose Luis; Martilli, Alberto; Martin, Fernando; Borge, Rafael; Quaassdorff, Christina; de la Paz, David

    2017-08-01

    Air quality management requires more detailed studies about air pollution at urban and local scale over long periods of time. This work focuses on obtaining the spatial distribution of NOx concentration averaged over several days in a heavily trafficked urban area in Madrid (Spain) using a computational fluid dynamics (CFD) model. A methodology based on weighted average of CFD simulations is applied computing the time evolution of NOx dispersion as a sequence of steady-state scenarios taking into account the actual atmospheric conditions. The inputs of emissions are estimated from the traffic emission model and the meteorological information used is derived from a mesoscale model. Finally, the computed concentration map correlates well with 72 passive samplers deployed in the research area. This work reveals the potential of using urban mesoscale simulations together with detailed traffic emissions so as to provide accurate maps of pollutant concentration at microscale using CFD simulations.

  16. Mesoscale modeling of smoke transport over the South Asian maritime continent: vertical distributions and topographic effect

    Ge, C.; Wang, J.; Yang, Z.; Hyer, E. J.; Reid, J. S.; Chew, B.; Mahamod, M.

    2011-12-01

    The online-coupled Weather Research and Forecasting model with Chemistry (WRF-Chem) is used in conjunction with the FLAMBE MODIS-based biomass burning emissions to simulate the transport of smoke particles over the southeast Asian Maritime Continent (MC, 10°S - 10°N, 90°E-150°E) during September - October 2006 when the moderate El Nino event caused the largest region biomass burning outbreak since 1998. The modeled smoke transport pathway is found to be consistent with the MODIS true color images. Quantitatively, the modeled smoke particle mass can explain ~50% of temporal variability in 24-hour average observed PM10 at most ground stations, with linear correlation coefficients often larger than 0.7. Analysis of CALIOP data shows that smoke aerosols are primarily located within 3.5 km above the surface, and we found that smoke injection height in the model should be at ~800 m above surface to best match CALIOP observations downwind, instead of 2 km as used in the past literature. Comparison of CALIOP data in October 2006 with that in other years (2007-2010) reveals that the peak of aerosol extinction always occurs at ~1 km above surface, but smoke events in 2006 doubled the aerosol extinction from the surface to 3.5 km. Numerical experiments further show that the Tama Abu topography in Malaysia Peninsula has a significant impact on smoke transport and the surface in the vicinity. A conceptual model, based upon our analysis of two-month WRFchem simulation and satellite data, is proposed to explain the meteorological causes for smoke layers above the clouds as seen in the CALIOP data.

  17. The Influence of Temperature on Time-Dependent Deformation and Failure in Granite: A Mesoscale Modeling Approach

    Xu, T.; Zhou, G. L.; Heap, Michael J.; Zhu, W. C.; Chen, C. F.; Baud, Patrick

    2017-09-01

    An understanding of the influence of temperature on brittle creep in granite is important for the management and optimization of granitic nuclear waste repositories and geothermal resources. We propose here a two-dimensional, thermo-mechanical numerical model that describes the time-dependent brittle deformation (brittle creep) of low-porosity granite under different constant temperatures and confining pressures. The mesoscale model accounts for material heterogeneity through a stochastic local failure stress field, and local material degradation using an exponential material softening law. Importantly, the model introduces the concept of a mesoscopic renormalization to capture the co-operative interaction between microcracks in the transition from distributed to localized damage. The mesoscale physico-mechanical parameters for the model were first determined using a trial-and-error method (until the modeled output accurately captured mechanical data from constant strain rate experiments on low-porosity granite at three different confining pressures). The thermo-physical parameters required for the model, such as specific heat capacity, coefficient of linear thermal expansion, and thermal conductivity, were then determined from brittle creep experiments performed on the same low-porosity granite at temperatures of 23, 50, and 90 °C. The good agreement between the modeled output and the experimental data, using a unique set of thermo-physico-mechanical parameters, lends confidence to our numerical approach. Using these parameters, we then explore the influence of temperature, differential stress, confining pressure, and sample homogeneity on brittle creep in low-porosity granite. Our simulations show that increases in temperature and differential stress increase the creep strain rate and therefore reduce time-to-failure, while increases in confining pressure and sample homogeneity decrease creep strain rate and increase time-to-failure. We anticipate that the

  18. A reactive transport model for Marcellus shale weathering

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

    2017-11-01

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

  19. Extending atomistic scale chemistry to mesoscale model of condensed-phase deflagration

    Joshi, Kaushik; Chaudhuri, Santanu

    2017-01-01

    Predictive simulations connecting chemistry that follow the shock or thermal initiation of energetic materials to subsequent deflagration or detonation events is currently outside the realm of possibilities. Molecular dynamics and first-principles based dynamics have made progress in understanding reactions in picosecond to nanosecond time scale. Results from thermal ignition of different phases of RDX show a complex reaction network and emergence of a deterministic behavior for critical temperature before ignition and hot spot growth rates. The kinetics observed is dependent on the hot spot temperature, system size and thermal conductivity. For cases where ignition is observed, the incubation period is dominated by intermolecular and intramolecular hydrogen transfer reactions. The gradual temperature and pressure increase in the incubation period is accompanied by accumulation of heavier polyradicals. The challenge of connecting such chemistry in mesoscale simulations remain in reducing the complexity of chemistry. The hot spot growth kinetics in RDX grains and interfaces is an important challenge for reactive simulations aiming to fill in the gaps in our knowledge in the nanoseconds to microseconds time scale. The results discussed indicate that the mesoscale chemistry may include large polyradical molecules in dense reactive mix reaching an instability point at certain temperatures and pressures.

  20. The Explicit Wake Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF

    P. J. H. Volker

    2015-11-01

    Full Text Available We describe the theoretical basis, implementation, and validation of a new parametrisation that accounts for the effect of large offshore wind farms on the atmosphere and can be used in mesoscale and large-scale atmospheric models. This new parametrisation, referred to as the Explicit Wake Parametrisation (EWP, uses classical wake theory to describe the unresolved wake expansion. The EWP scheme is validated for a neutral atmospheric boundary layer against filtered in situ measurements from two meteorological masts situated a few kilometres away from the Danish offshore wind farm Horns Rev I. The simulated velocity deficit in the wake of the wind farm compares well to that observed in the measurements, and the velocity profile is qualitatively similar to that simulated with large eddy simulation models and from wind tunnel studies. At the same time, the validation process highlights the challenges in verifying such models with real observations.

  1. Warm Season Statistical Verification of the Pennsylvania State University Real Time Mesoscale Model Version 5

    Fitzgerald, Mark

    1998-01-01

    .... Variables that are verified include temperature, dew point, relative humidity, wind direction, wind speed, geopotential height, sea-level pressure, as well as the total totals severe weather index...

  2. Extreme precipitation response to climate perturbations in an atmospheric mesoscale model

    Attema, Jisk J; Loriaux, Jessica M; Lenderink, Geert

    2014-01-01

    Observations of extreme (sub-)hourly precipitation at mid-latitudes show a large dependency on the dew point temperature often close to 14% per degree—2 times the dependency of the specific humidity on dew point temperature which is given by the Clausius–Clapeyron (CC) relation. By simulating a selection of 11 cases over the Netherlands characterized by intense showers, we investigate this behavior in the non-hydrostatic weather prediction model Harmonie at a resolution of 2.5 km. These experiments are repeated using perturbations of the atmospheric profiles of temperature and humidity: (i) using an idealized approach with a 2° warmer (colder) atmosphere assuming constant relative humidity, and (ii) using changes in temperature and humidity derived from a long climate change simulation at 2° global warming. All perturbations have a difference in the local dew point temperature compared to the reference of approximately 2°. Differences are considerable between the cases, with dependencies ranging from almost zero to an increase of 18% per degree rise of the dew point temperature. On average however, we find an increase of extreme precipitation intensity of 11% per degree for the idealized perturbation, and 9% per degree for the climate change perturbation. For the most extreme events these dependencies appear to approach a rate of 11–14% per degree, in closer agreement with the observed relation. (paper)

  3. Mesoscale modeling of smoke transport from equatorial Southeast Asian Maritime Continent to the Philippines: First comparison of ensemble analysis with in situ observations

    Ge, Cui; Wang, Jun; Reid, Jeffrey S.; Posselt, Derek J.; Xian, Peng; Hyer, Edward

    2017-05-01

    Atmospheric transport of smoke from equatorial Southeast Asian Maritime Continent (Indonesia, Singapore, and Malaysia) to the Philippines was recently verified by the first-ever measurement of aerosol composition in the region of the Sulu Sea from a research vessel named Vasco. However, numerical modeling of such transport can have large uncertainties due to the lack of observations for parameterization schemes and for describing fire emission and meteorology in this region. These uncertainties are analyzed here, for the first time, with an ensemble of 24 Weather Research and Forecasting model with Chemistry (WRF-Chem) simulations. The ensemble reproduces the time series of observed surface nonsea-salt PM2.5 concentrations observed from the Vasco vessel during 17-30 September 2011 and overall agrees with satellite (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Moderate Resolution Imaging Spectroradiometer (MODIS)) and Aerosol Robotic Network (AERONET) data. The difference of meteorology between National Centers for Environmental Prediction (NCEP's) Final (FNL) and European Center for Medium range Weather Forecasting (ECMWF's) ERA renders the biggest spread in the ensemble (up to 20 μg m-3 or 200% in surface PM2.5), with FNL showing systematically superior results. The second biggest uncertainty is from fire emissions; the 2 day maximum Fire Locating and Modelling of Burning Emissions (FLAMBE) emission is superior than the instantaneous one. While Grell-Devenyi (G3) and Betts-Miller-Janjić cumulus schemes only produce a difference of 3 μg m-3 of surface PM2.5 over the Sulu Sea, the ensemble mean agrees best with Climate Prediction Center (CPC) MORPHing (CMORPH)'s spatial distribution of precipitation. Simulation with FNL-G3, 2 day maximum FLAMBE, and 800 m injection height outperforms other ensemble members. Finally, the global transport model (Navy Aerosol Analysis and Prediction System (NAAPS)) outperforms all WRF

  4. Incorporation of a high-roughness lower boundary into a mesoscale model for studies of dry deposition over complex terrain

    Physick, W. L.; Garratt, J. R.

    1995-04-01

    For flow over natural surfaces, there exists a roughness sublayer within the atmospheric surface layer near the boundary. In this sublayer (typically 50 z 0 deep in unstable conditions), the Monin-Obukhov (M-O) flux profile relations for homogeneous surfaces cannot be applied. We have incorporated a modified form of the M-O stability functions (Garratt, 1978, 1980, 1983) in a mesoscale model to take account of this roughness sublayer and examined the diurnal variation of the boundary-layer wind and temperature profiles with and without these modifications. We have also investigated the effect of the modified M-O functions on the aerodynamic and laminar-sublayer resistances associated with the transfer of trace gases to vegetation. Our results show that when an observation height or the lowest level in a model is within the roughness sublayer, neglect of the flux-profile modifications leads to an underestimate of resistances by 7% at the most.

  5. A methodology to aid in the design of naval steels: Linking first principles calculations to mesoscale modeling

    Spanos, G.; Geltmacher, A.B.; Lewis, A.C.; Bingert, J.F.; Mehl, M.; Papaconstantopoulos, D.; Mishin, Y.; Gupta, A.; Matic, P.

    2007-01-01

    This paper provides a brief overview of a multidisciplinary effort at the Naval Research Laboratory aimed at developing a computationally-based methodology to assist in the design of advanced Naval steels. This program uses multiple computational techniques ranging from the atomistic length scale to continuum response. First-principles electronic structure calculations using density functional theory were employed, semi-empirical angular dependent potentials were developed based on the embedded atom method, and these potentials were used as input into Monte-Carlo and molecular dynamics simulations. Experimental techniques have also been applied to a super-austenitic stainless steel (AL6XN) to provide experimental input, guidance, verification, and enhancements to the models. These experimental methods include optical microscopy, scanning electron microscopy, transmission electron microscopy, electron backscatter diffraction, and serial sectioning in conjunction with computer-based three-dimensional reconstruction and quantitative analyses. The experimental results are also used as critical input into mesoscale finite element models of materials response

  6. A dual theory of price and value in a meso-scale economic model with stochastic profit rate

    Greenblatt, R. E.

    2014-12-01

    The problem of commodity price determination in a market-based, capitalist economy has a long and contentious history. Neoclassical microeconomic theories are based typically on marginal utility assumptions, while classical macroeconomic theories tend to be value-based. In the current work, I study a simplified meso-scale model of a commodity capitalist economy. The production/exchange model is represented by a network whose nodes are firms, workers, capitalists, and markets, and whose directed edges represent physical or monetary flows. A pair of multivariate linear equations with stochastic input parameters represent physical (supply/demand) and monetary (income/expense) balance. The input parameters yield a non-degenerate profit rate distribution across firms. Labor time and price are found to be eigenvector solutions to the respective balance equations. A simple relation is derived relating the expected value of commodity price to commodity labor content. Results of Monte Carlo simulations are consistent with the stochastic price/labor content relation.

  7. Application of a mesoscale forecasting model (NMM) coupled to the CALMET to develop forecast meteorology to use with the CALPUFF air dispersion model

    Radonjic, Z.; Telenta, B.; Kirklady, J.; Chambers, D.; Kleb, H.

    2006-01-01

    An air quality assessment was undertaken as part of the Environmental Assessment for the Port Hope Area Initiative. The assessment predicted potential effects associated with the remediation efforts for historic low-level radioactive wastes and construction of Long-Term Waste Management Facilities (LTWMFs) for both the Port Hope and Port Granby Projects. A necessary element of air dispersion modelling is the development of suitable meteorological data. For the Port Hope and Port Granby Projects, a meteorological station was installed in close proximity to the location of the recommended LTWMF in Port Hope. The recommended location for the Port Granby LTWMF is approximately 10 km west of the Port Hope LTWMF. Concerns were raised regarding the applicability of data collected for the Port Hope meteorological station to the Port Granby Site. To address this concern, a new method for processing meteorological data, which coupled mesoscale meteorological forecasting data the U.S. EPA CALMET meteorological data processor, was applied. This methodology is possible because a new and advanced mesoscale forecasting modelling system enables extensive numerical calculations on personal computers. As a result of this advancement, mesoscale forecasting systems can now be coupled with the CALMET meteorological data processor and the CALPUFF air dispersion modelling system to facilitate wind field estimations and air dispersion analysis. (author)

  8. Comparing Epileptiform Behavior of Mesoscale Detailed Models and Population Models of Neocortex

    Visser, S.; Meijer, Hil Gaétan Ellart; Lee, Hyong C.; van Drongelen, Wim; van Putten, Michel Johannes Antonius Maria; van Gils, Stephanus A.

    2010-01-01

    Two models of the neocortex are developed to study normal and pathologic neuronal activity. One model contains a detailed description of a neocortical microcolumn represented by 656 neurons, including superficial and deep pyramidal cells, four types of inhibitory neurons, and realistic synaptic

  9. ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS

    Chiswell, S.; Buckley, R.

    2009-01-15

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

  10. Development of satellite green vegetation fraction time series for use in mesoscale modeling: application to the European heat wave 2006

    Nielsen, Joakim Refslund; Dellwik, Ebba; Hahmann, Andrea N.

    2014-01-01

    A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution of veg...

  11. Mesoscale modelling in China: Risø DTU numerical wind atlas calculation for NE China (Dongbei)

    Badger, Jake; Larsén, Xiaoli Guo; Hahmann, Andrea N.

    of the wind resource for Dongbei south of 50oN. The results of the numerical wind atlas show a wind resource over the region of interest modulated mainly by topographic features. These are principally elevated terrain features, giving high resources on exposed ridges and lower resources adjacent to the low......This document reports on the methods and findings of project “A01 Mesoscale Modelling”, part of the CMA component of the Wind Energy Development (WED) programme, focusing mainly on the methods and work undertaken by Risø DTU. The KAMM/WAsP methodology for numerical wind atlas calculation....... The major new aspects of the project were the large number of KAMM/WAsP sensitivity studies, comparison with WRF, and the CMA’s numerical wind atlas method (WERAS). Additionally, the reliability of the input data for the methodology, and the wave-number spectra properties of the output data were...

  12. Evaluation of the performance of a meso-scale NWP model to forecast solar irradiance on Reunion Island for photovoltaic power applications

    Kalecinski, Natacha; Haeffelin, Martial; Badosa, Jordi; Periard, Christophe

    2013-04-01

    Solar photovoltaic power is a predominant source of electrical power on Reunion Island, regularly providing near 30% of electrical power demand for a few hours per day. However solar power on Reunion Island is strongly modulated by clouds in small temporal and spatial scales. Today regional regulations require that new solar photovoltaic plants be combined with storage systems to reduce electrical power fluctuations on the grid. Hence cloud and solar irradiance forecasting becomes an important tool to help optimize the operation of new solar photovoltaic plants on Reunion Island. Reunion Island, located in the South West of the Indian Ocean, is exposed to persistent trade winds, most of all in winter. In summer, the southward motion of the ITCZ brings atmospheric instabilities on the island and weakens trade winds. This context together with the complex topography of Reunion Island, which is about 60 km wide, with two high summits (3070 and 2512 m) connected by a 1500 m plateau, makes cloudiness very heterogeneous. High cloudiness variability is found between mountain and coastal areas and between the windward, leeward and lateral regions defined with respect to the synoptic wind direction. A detailed study of local dynamics variability is necessary to better understand cloud life cycles around the island. In the presented work, our approach to explore the short-term solar irradiance forecast at local scales is to use the deterministic output from a meso-scale numerical weather prediction (NWP) model, AROME, developed by Meteo France. To start we evaluate the performance of the deterministic forecast from AROME by using meteorological measurements from 21 meteorological ground stations widely spread around the island (and with altitudes from 8 to 2245 m). Ground measurements include solar irradiation, wind speed and direction, relative humidity, air temperature, precipitation and pressure. Secondly we study in the model the local dynamics and thermodynamics that

  13. High-frequency and meso-scale winter sea-ice variability in the Southern Ocean in a high-resolution global ocean model

    Stössel, Achim; von Storch, Jin-Song; Notz, Dirk; Haak, Helmuth; Gerdes, Rüdiger

    2018-03-01

    This study is on high-frequency temporal variability (HFV) and meso-scale spatial variability (MSV) of winter sea-ice drift in the Southern Ocean simulated with a global high-resolution (0.1°) sea ice-ocean model. Hourly model output is used to distinguish MSV characteristics via patterns of mean kinetic energy (MKE) and turbulent kinetic energy (TKE) of ice drift, surface currents, and wind stress, and HFV characteristics via time series of raw variables and correlations. We find that (1) along the ice edge, the MSV of ice drift coincides with that of surface currents, in particular such due to ocean eddies; (2) along the coast, the MKE of ice drift is substantially larger than its TKE and coincides with the MKE of wind stress; (3) in the interior of the ice pack, the TKE of ice drift is larger than its MKE, mostly following the TKE pattern of wind stress; (4) the HFV of ice drift is dominated by weather events, and, in the absence of tidal currents, locally and to a much smaller degree by inertial oscillations; (5) along the ice edge, the curl of the ice drift is highly correlated with that of surface currents, mostly reflecting the impact of ocean eddies. Where ocean eddies occur and the ice is relatively thin, ice velocity is characterized by enhanced relative vorticity, largely matching that of surface currents. Along the ice edge, ocean eddies produce distinct ice filaments, the realism of which is largely confirmed by high-resolution satellite passive-microwave data.

  14. A Reactive Transport Model for Marcellus Shale Weathering

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

    2017-12-01

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

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

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

    2017-11-01

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

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

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

    2013-01-01

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

  17. Data assimilation of a ten-day period during June 1993 over the Southern Great Plains Site using a nested mesoscale model

    Dudhia, J.; Guo, Y.R. [National Center for Atmospheric Research, Boulder, CO (United States)

    1996-04-01

    A goal of the Atmospheric Radiation Measurement (ARM) Program has been to obtain a complete representation of physical processes on the scale of a general circulation model (GCM) grid box in order to better parameterize radiative processes in these models. Since an observational network of practical size cannot be used alone to characterize the Cloud and Radiation Testbed (CART) site`s 3D structure and time development, data assimilation using the enhanced observations together with a mesoscale model is used to give a full 4D analysis at high resolution. The National Center for Atmospheric Research (NCAR)/Penn State Mesoscale Model (MM5) has been applied over a ten-day continuous period in a triple-nested mode with grid sizes of 60, 20 and 6.67 in. The outer domain covers the United States` 48 contiguous states; the innermost is a 480-km square centered on Lamont, Oklahoma. A simulation has been run with data assimilation using the Mesoscale Analysis and Prediction System (MAPS) 60-km analyses from the Forecast Systems Laboratory (FSL) of the National Ocean and Atmospheric Administration (NOAA). The nested domains take boundary conditions from and feed back continually to their parent meshes (i.e., they are two-way interactive). As reported last year, this provided a simulation of the basic features of mesoscale events over the CART site during the period 16-26 June 1993 when an Intensive Observation Period (IOP) was under way.

  18. Simulating an extreme over-the-horizon optical propagation event over Lake Michigan using a coupled mesoscale modeling and ray tracing framework

    Basu, S.

    2017-01-01

    Accurate simulation and forecasting of over-the-horizon propagation events are essential for various civilian and defense applications. We demonstrate the prowess of a newly proposed coupled mesoscale modeling and ray tracing framework in reproducing such an event. Wherever possible, routinely

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

    Schertzer, Daniel; Lovejoy, Shaun

    2013-04-01

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

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

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

    2003-01-01

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

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

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

    2003-01-01

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

  2. Constraining Methane Emissions from Natural Gas Production in Northeastern Pennsylvania Using Aircraft Observations and Mesoscale Modeling

    Barkley, Z.; Davis, K.; Lauvaux, T.; Miles, N.; Richardson, S.; Martins, D. K.; Deng, A.; Cao, Y.; Sweeney, C.; Karion, A.; Smith, M. L.; Kort, E. A.; Schwietzke, S.

    2015-12-01

    Leaks in natural gas infrastructure release methane (CH4), a potent greenhouse gas, into the atmosphere. The estimated fugitive emission rate associated with the production phase varies greatly between studies, hindering our understanding of the natural gas energy efficiency. This study presents a new application of inverse methodology for estimating regional fugitive emission rates from natural gas production. Methane observations across the Marcellus region in northeastern Pennsylvania were obtained during a three week flight campaign in May 2015 performed by a team from the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Division and the University of Michigan. In addition to these data, CH4 observations were obtained from automobile campaigns during various periods from 2013-2015. An inventory of CH4 emissions was then created for various sources in Pennsylvania, including coalmines, enteric fermentation, industry, waste management, and unconventional and conventional wells. As a first-guess emission rate for natural gas activity, a leakage rate equal to 2% of the natural gas production was emitted at the locations of unconventional wells across PA. These emission rates were coupled to the Weather Research and Forecasting model with the chemistry module (WRF-Chem) and atmospheric CH4 concentration fields at 1km resolution were generated. Projected atmospheric enhancements from WRF-Chem were compared to observations, and the emission rate from unconventional wells was adjusted to minimize errors between observations and simulation. We show that the modeled CH4 plume structures match observed plumes downwind of unconventional wells, providing confidence in the methodology. In all cases, the fugitive emission rate was found to be lower than our first guess. In this initial emission configuration, each well has been assigned the same fugitive emission rate, which can potentially impair our ability to match the observed spatial variability

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

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

    2012-04-01

    . Numerical modeling became a common tool in the daily practice of weather experts forecasters due to the i) increasing user demands for weather data by the costumers, ii) the growth in computer resources, iii) numerical weather prediction systems available for integration on affordable, off the shelf computers and iv) available input data (from ECMWF or NCEP) for model integrations. Beside learning the theoretical basis, since the last year. Students in their MSc or BSc Thesis Research or in Student's Research ProjectsStudent's Research Projects h have the opportunity to run numerical models and to analyze the outputs for different purposes including wind energy estimation, simulation of the dynamics of a polar low, and subtropical cyclones, analysis of the isentropic potential vorticity field, examination of coupled atmospheric dispersion models, etc. A special course in the application of numerical modeling has been held (is being announced for the upcoming semester) (is being announced for the upcoming semester) for our students in order to improve their skills on this field. Several numerical model (NRIPR ETA and WRF) systems have been adapted in the University and integrated WRF have been tested and used for the geographical region of the Carpathian Basin (NRIPR, ETA and WRF). Recently ALADIN/CHAPEAU the academic version of the ARPEGE ALADIN cy33t1 meso-scale numerical weather prediction model system (which is the operational forecasting tool of our National Weather Service) has been installed at our Institute. ALADIN is the operational forecasting model of the Hungarian Meteorological Service and developed in the framework of the international ALADIN co-operation. Our main objectives are i) the analysis of different typical weather situations, ii) fine tuning of parameterization schemes and the iii) comparison of the ALADIN/CHAPEAU and WRF model outputs based on case studies. The necessary hardware and software innovations has have been done. In the presentation the

  4. Mesoscale modeling for the Wind Atlas of South Africa (WASA) project

    Hahmann, Andrea N.; Lennard, Chris; Badger, Jake

    This document reports on the methods used to create and the results of the two numerical wind atlases developed for the Wind Atlas for South Africa (WASA) project. The wind atlases were created using the KAMM-WAsP method and from the output of climate-type simulations of the Weather, Research...

  5. Linking the M&Rfi Weather Generator with Agrometeorological Models

    Dubrovsky, Martin; Trnka, Miroslav

    2015-04-01

    Realistic meteorological inputs (representing the present and/or future climates) for the agrometeorological model simulations are often produced by stochastic weather generators (WGs). This contribution presents some methodological issues and results obtained in our recent experiments. We also address selected questions raised in the synopsis of this session. The input meteorological time series for our experiments are produced by the parametric single site weather generator (WG) Marfi, which is calibrated from the available observational data (or interpolated from surrounding stations). To produce meteorological series representing the future climate, the WG parameters are modified by climate change scenarios, which are prepared by the pattern scaling method: the standardised scenarios derived from Global or Regional Climate Models are multiplied by the change in global mean temperature (ΔTG) determined by the simple climate model MAGICC. The presentation will address following questions: (i) The dependence of the quality of the synthetic weather series and impact results on the WG settings. An emphasis will be put on an effect of conditioning the daily WG on monthly WG (presently being one of our hot topics), which aims at improvement of the reproduction of the low-frequency weather variability. Comparison of results obtained with various WG settings is made in terms of climatic and agroclimatic indices (including extreme temperature and precipitation characteristics and drought indices). (ii) Our methodology accounts for the uncertainties coming from various sources. We will show how the climate change impact results are affected by 1. uncertainty in climate modelling, 2. uncertainty in ΔTG, and 3. uncertainty related to the complexity of the climate change scenario (focusing on an effect of inclusion of changes in variability into the climate change scenarios). Acknowledgements: This study was funded by project "Building up a multidisciplinary scientific

  6. Modeling Apple Surface Temperature Dynamics Based on Weather Data

    Lei Li

    2014-10-01

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

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

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

    2014-10-27

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

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

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

    2015-10-01

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

  9. Utilization of mesoscale atmospheric dynamic model PHYSIC as a meteorological forecast model in nuclear emergency response system

    Nagai, Haruyasu; Yamazawa, Hiromi

    1997-01-01

    It is advantageous for an emergency response system to have a forecast function to provide a time margin for countermeasures in case of a nuclear accident. We propose to apply an atmospheric dynamic model PHYSIC (Prognostic HYdroStatic model Including turbulence Closure model) as a meteorological forecast model in the emergency system. The model uses GPV data which are the output of the numerical weather forecast model of Japan Meteorological Agency as the initial and boundary conditions. The roles of PHYSIC are the interface between GPV data and the emergency response system and the forecast of local atmospheric phenomena within the model domain. This paper presents a scheme to use PHYSIC to forecast local wind and its performance. Horizontal grid number of PHYSIC is fixed to 50 x 50, whereas the mesh and domain sizes are determined in consideration of topography causing local winds at an objective area. The model performance was examined for the introduction of GPV data through initial and boundary conditions and the predictability of local wind field and atmospheric stability. The model performance was on an acceptable level as the forecast model. It was also recognized that improvement of cloud calculation was necessary in simulating atmospheric stability. (author)

  10. Modeling of mesoscale dispersion effect on the piezoresistivity of carbon nanotube-polymer nanocomposites via 3D computational multiscale micromechanics methods

    Ren, Xiang; Seidel, Gary D; Chaurasia, Adarsh K; Oliva-Avilés, Andrés I; Ku-Herrera, José J; Avilés, Francis

    2015-01-01

    In uniaxial tension and compression experiments, carbon nanotube (CNT)-polymer nanocomposites have demonstrated exceptional mechanical and coupled electrostatic properties in the form of piezoresistivity. In order to better understand the correlation of the piezoresistive response with the CNT dispersion at the mesoscale, a 3D computational multiscale micromechanics model based on finite element analysis is constructed to predict the effective macroscale piezoresistive response of CNT/polymer nanocomposites. The key factors that may contribute to the overall piezoresistive response, i.e. the nanoscale electrical tunneling effect, the inherent CNT piezoresistivity and the CNT mesoscale network effect are incorporated in the model based on a 3D multiscale mechanical–electrostatic coupled code. The results not only explain how different nanoscale mechanisms influence the overall macroscale piezoresistive response through the mesoscale CNT network, but also give reason and provide bounds for the wide range of gauge factors found in the literature offering insight regarding how control of the mesoscale CNT networks can be used to tailor nanocomposite piezoresistive response. (paper)

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

    Dmitrii Mironov

    2012-04-01

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

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

    2010-12-01

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

  13. A Novel Observation-Guided Approach for Evaluating Mesoscale Convective Systems Simulated by the DOE ACME Model

    Feng, Z.; Ma, P. L.; Hardin, J. C.; Houze, R.

    2017-12-01

    Mesoscale convective systems (MCSs) are the largest type of convective storms that develop when convection aggregates and induces mesoscale circulation features. Over North America, MCSs contribute over 60% of the total warm-season precipitation and over half of the extreme daily precipitation in the central U.S. Our recent study (Feng et al. 2016) found that the observed increases in springtime total and extreme rainfall in this region are dominated by increased frequency and intensity of long-lived MCSs*. To date, global climate models typically do not run at a resolution high enough to explicitly simulate individual convective elements and may not have adequate process representations for MCSs, resulting in a large deficiency in projecting changes of the frequency of extreme precipitation events in future climate. In this study, we developed a novel observation-guided approach specifically designed to evaluate simulated MCSs in the Department of Energy's climate model, Accelerated Climate Modeling for Energy (ACME). The ACME model has advanced treatments for convection and subgrid variability and for this study is run at 25 km and 100 km grid spacings. We constructed a robust MCS database consisting of over 500 MCSs from 3 warm-season observations by applying a feature-tracking algorithm to 4-km resolution merged geostationary satellite and 3-D NEXRAD radar network data over the Continental US. This high-resolution MCS database is then down-sampled to the 25 and 100 km ACME grids to re-characterize key MCS properties. The feature-tracking algorithm is adapted with the adjusted characteristics to identify MCSs from ACME model simulations. We demonstrate that this new analysis framework is useful for evaluating ACME's warm-season precipitation statistics associated with MCSs, and provides insights into the model process representations related to extreme precipitation events for future improvement. *Feng, Z., L. R. Leung, S. Hagos, R. A. Houze, C. D. Burleyson

  14. Numerical simulation of mesoscale surface pressure features with trailing stratiform squall lines using WRF -ARW model over Gangetic West Bengal region

    Dawn, Soma; Satyanarayana, A. N. V.

    2018-01-01

    In the present study, an attempt has been made to investigate the simulation of mesoscale surface pressure patterns like pre-squall mesolow, mesohigh and wake low associated with leading convective line-trailing stratiform (TS) squall lines over Gangetic West Bengal (GWB). For this purpose, a two way interactive triple nested domain with high resolution WRF model having2 km grid length in the innermost domain is used. The model simulated results are compared with the available in-situ observations obtained as a part of Severe Thunderstorm: Observations and Regional Modeling (STORM) programme, reflectivity products of Doppler Weather Radar (DWR) Kolkata and TRMM rainfall. Three TS squall lines (15 May 2009, 5 May 2010 and 7 May 2010) are chosen during pre-monsoon thunderstorm season for this study. The model simulated results of diurnal variation of temperature, relative humidity, wind speed and direction at the station Kharagpur in GWB region reveal a sudden fall in temperature, increase in the amount of relative humidity and sudden rise in wind speed during the arrival of the storms. Such results are well comparable with the observations though there are some leading or lagging of time in respect of actual occurrences of such events. The study indicates that the model is able to predict the occurrences of three typical surface pressure features namely: pre-squall mesolow, meso high and wake low. The predicted surface parameters like accumulated rainfall, maximum reflectivity and vertical profiles (temperature, relative humidity and winds) are well accorded with the observations. The convective and stratiform precipitation region of the TS squall lines are well represented by the model. A strong downdraft is observed to be a contributory factor for formation of mesohigh in the convective region of the squall line. Wake low is observed to reside in the stratiform rain region and the descending dry air at this place has triggered the wake low through adiabatic

  15. The origins of computer weather prediction and climate modeling

    Lynch, Peter

    2008-01-01

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

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

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

    1999-10-01

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

  17. Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

    H. Kreibich

    2016-05-01

    Full Text Available Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB.In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.

  18. Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

    Kreibich, Heidi; Schröter, Kai; Merz, Bruno

    2016-05-01

    Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB).In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.

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

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

  20. Reduced fractal model for quantitative analysis of averaged micromotions in mesoscale: Characterization of blow-like signals

    Nigmatullin, Raoul R.; Toboev, Vyacheslav A.; Lino, Paolo; Maione, Guido

    2015-01-01

    Highlights: •A new approach describes fractal-branched systems with long-range fluctuations. •A reduced fractal model is proposed. •The approach is used to characterize blow-like signals. •The approach is tested on data from different fields. -- Abstract: It has been shown that many micromotions in the mesoscale region are averaged in accordance with their self-similar (geometrical/dynamical) structure. This distinctive feature helps to reduce a wide set of different micromotions describing relaxation/exchange processes to an averaged collective motion, expressed mathematically in a rather general form. This reduction opens new perspectives in description of different blow-like signals (BLS) in many complex systems. The main characteristic of these signals is a finite duration also when the generalized reduced function is used for their quantitative fitting. As an example, we describe quantitatively available signals that are generated by bronchial asthmatic people, songs by queen bees, and car engine valves operating in the idling regime. We develop a special treatment procedure based on the eigen-coordinates (ECs) method that allows to justify the generalized reduced fractal model (RFM) for description of BLS that can propagate in different complex systems. The obtained describing function is based on the self-similar properties of the different considered micromotions. This kind of cooperative model is proposed here for the first time. In spite of the fact that the nature of the dynamic processes that take place in fractal structure on a mesoscale level is not well understood, the parameters of the RFM fitting function can be used for construction of calibration curves, affected by various external/random factors. Then, the calculated set of the fitting parameters of these calibration curves can characterize BLS of different complex systems affected by those factors. Though the method to construct and analyze the calibration curves goes beyond the scope

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

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

    2018-01-01

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

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

    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.

  3. Impact of deep convection in the tropical tropopause layer in West Africa: in-situ observations and mesoscale modelling

    F. Fierli

    2011-01-01

    Full Text Available We present the analysis of the impact of convection on the composition of the tropical tropopause layer region (TTL in West-Africa during the AMMA-SCOUT campaign. Geophysica M55 aircraft observations of water vapor, ozone, aerosol and CO2 during August 2006 show perturbed values at altitudes ranging from 14 km to 17 km (above the main convective outflow and satellite data indicates that air detrainment is likely to have originated from convective cloud east of the flights. Simulations of the BOLAM mesoscale model, nudged with infrared radiance temperatures, are used to estimate the convective impact in the upper troposphere and to assess the fraction of air processed by convection. The analysis shows that BOLAM correctly reproduces the location and the vertical structure of convective outflow. Model-aided analysis indicates that convection can influence the composition of the upper troposphere above the level of main outflow for an event of deep convection close to the observation site. Model analysis also shows that deep convection occurring in the entire Sahelian transect (up to 2000 km E of the measurement area has a non negligible role in determining TTL composition.

  4. Radiation-induced aging of PDMS Elastomer TR-55: a summary of constitutive, mesoscale, and population-based models

    Maiti, A [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Weisgraber, T. H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Dinh, L. N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-11-16

    Filled and cross-linked elastomeric rubbers are versatile network materials with a multitude of applications ranging from artificial organs and biomedical devices to cushions, coatings, adhesives, interconnects, and seismic-isolation-, thermal-, and electrical barriers. External factors like mechanical stress, temperature fluctuations, or radiation are known to create chemical changes in such materials that can directly affect the molecular weight distribution (MWD) of the polymer between cross-links and alter the structural and mechanical properties. From a Materials Science point of view it is highly desirable to understand, effect, and manipulate such property changes in a controlled manner. In this report we summarize our modeling efforts on a polysiloxane elastomer TR-55, which is an important component in several of our systems, and representative of a wide class of filled rubber materials. The primary aging driver in this work has been γ-radiation, and a variety of modeling approaches have been employed, including constitutive, mesoscale, and population-based models. The work utilizes diverse experimental data, including mechanical stress-strain and compression set measurements, as well as MWD measurements using multiquantum NMR.

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

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

    2013-01-01

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

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

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

    2009-09-01

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

  7. A unified bond theory, probabilistic meso-scale modeling, and experimental validation of deformed steel rebar in normal strength concrete

    Wu, Chenglin

    Bond between deformed rebar and concrete is affected by rebar deformation pattern, concrete properties, concrete confinement, and rebar-concrete interfacial properties. Two distinct groups of bond models were traditionally developed based on the dominant effects of concrete splitting and near-interface shear-off failures. Their accuracy highly depended upon the test data sets selected in analysis and calibration. In this study, a unified bond model is proposed and developed based on an analogy to the indentation problem around the rib front of deformed rebar. This mechanics-based model can take into account the combined effect of concrete splitting and interface shear-off failures, resulting in average bond strengths for all practical scenarios. To understand the fracture process associated with bond failure, a probabilistic meso-scale model of concrete is proposed and its sensitivity to interface and confinement strengths are investigated. Both the mechanical and finite element models are validated with the available test data sets and are superior to existing models in prediction of average bond strength (rib spacing-to-height ratio of deformed rebar. It can accurately predict the transition of failure modes from concrete splitting to rebar pullout and predict the effect of rebar surface characteristics as the rib spacing-to-height ratio increases. Based on the unified theory, a global bond model is proposed and developed by introducing bond-slip laws, and validated with testing of concrete beams with spliced reinforcement, achieving a load capacity prediction error of less than 26%. The optimal rebar parameters and concrete cover in structural designs can be derived from this study.

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

    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.

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

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

    2014-10-01

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

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

    Jensen, David Getreuer

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

  11. On the forcing mechanisms of mesocyclones in the eastern Weddell Sea region, Antarctica: Process studies using a mesoscale numerical model

    Thomas Klein

    2001-04-01

    Full Text Available Development mechanisms of Antarctic mesocyclones in the eastern Weddell Sea area are examined by means of simulations with a mesoscale model using different idealized initial conditions. In one of the experiments, a mesocyclone develops over an area of open water close to the coast of the Antarctic continent. The forcing mechanisms of this mesocyclogenesis are investigated by means of sensitivity studies in which certain physical processes and the relevance of the surface conditions topography, sea surface temperature and sea ice coverage are examined. The sensitivity experiments show that the simulated mesocyclone is forced by an interaction of several forcing mechanisms at different stages of the development rather than by a single mechanism. The topography of the eastern Weddell Sea region and the summertime coastal polynia are shown to be of great importance for the mesocyclogenesis. A suitable synoptic-scale flow is necessary to support the katabatic flow over the sloped ice sheet, and to enhance the generation of cyclonic vorticity due to vertical stretching for the initial mesocyclogenesis. The diabatic process of the convergence of the sensible and latent heat fluxes in the boundary layer over the coastal polynia then becomes the dominant forcing mechanism for the further development of the mesocyclone.

  12. Suitability of Water Harvesting in the Upper Blue Nile Basin, Ethiopia: A First Step towards a Mesoscale Hydrological Modeling Framework

    Yihun T. Dile

    2016-01-01

    Full Text Available Extreme rainfall variability has been one of the major factors to famine and environmental degradation in Ethiopia. The potential for water harvesting in the Upper Blue Nile Basin was assessed using two GIS-based Multicriteria Evaluation methods: (1 a Boolean approach to locate suitable areas for in situ and ex situ systems and (2 a weighted overlay analysis to classify suitable areas into different water harvesting suitability levels. The sensitivity of the results was analyzed to the influence given to different constraining factors. A large part of the basin was suitable for water harvesting: the Boolean analysis showed that 36% of the basin was suitable for in situ and ex situ systems, while the weighted overlay analysis showed that 6–24% of the basin was highly suitable. Rainfall has the highest influence on suitability for water harvesting. Implementing water harvesting in nonagricultural land use types may further increase the benefit. Assessing water harvesting suitability at the larger catchment scale lays the foundation for modeling of water harvesting at mesoscale, which enables analysis of the potential and implications of upscaling of water harvesting practices for building resilience against climatic shocks. A complete water harvesting suitability study requires socioeconomic analysis and stakeholder consultation.

  13. Scaling and Numerical Model Evaluation of Snow-Cover Effects on the Generation and Modification of Daytime Mesoscale Circulations.

    Segal, M.; Garratt, J. R.; Pielke, R. A.; Ye, Z.

    1991-04-01

    Consideration of the sensible heat flux characteristics over a snow surface suggests a significant diminution in the magnitude of the flux, compared to that over a snow-free surface under the same environmental conditions. Consequently, the existence of snow-covered mesoscale areas adjacent to snow-free areas produces horizontal thermal gradients in the lower atmosphere during the daytime, possibly resulting in a `snow breeze.' In addition, suppression of the daytime thermally induced upslope flow over snow-covered slopes is likely to occur. The present paper provides scaling and modeling evaluations of these situations, with quantification of the generated and modified circulations. These evaluations suggest that under ideal situations involved with uniform snow cover over large areas, particularly in late winter and early spring, a noticeable `snow breeze' is likely to develop. Additionally: suppression of the daytime thermally induced upslope flow is significant and may even result in a daytime drainage flow. The effects of bare ground patchiness in the snow cover on these circulations are also explored, both for flat terrain and slope-flow situations. A patchiness fraction greater than 0.5 is found to result in a noticeably reduced snow-breeze circulation, while a patchiness fraction of only 0.1 caused the simulated daytime drainage flow over slopes to he reversed.

  14. Electronic and Magnetic Properties of Transition-Metal Oxide Nanocomposites: A Tight-Binding Modeling at Mesoscale

    Tai, Yuan-Yen; Zhu, Jian-Xin

    Transition metal oxides (TMOs) exhibit many emergent phenomena ranging from high-temperature superconductivity and giant magnetoresistance to magnetism and ferroelectricity. In addition, when TMOs are interfaced with each other, new functionalities can arise, which are absent in individual components. In this talk, I will present an overview on our recent efforts in theoretical understanding of the electronic and magnetic properties TMO nanocomposites. In particular, I will introduce our recently developed tight-binding modeling of these properties arising from the interplay of competing interactions at the interfaces of planar and pillar nanocomposites. Our theoretical tool package will provide a unique capability to address the emergent phenomena in TMO nanocomposites and their mesoscale response to such effects like strain and microstructures at the interfaces, and ultimately help establish design principles of new multifunctionality with TMOs. This work was carried out under the auspices of the National Nuclear Security Administration of the U.S. Department of Energy at LANL under Contract No. DE-AC52-06NA25396, and was supported by the LANL LDRD Program.

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

    Aronne, M.

    2015-12-01

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

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

    Jahn, Malte

    2015-01-01

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

  17. Modeling the TTL at Continental Scale for a Wet Season: An Evaluation of the BRAMS Mesoscale Model Using TRO-Pico Campaign, and Measurements From Airborne and Spaceborne Sensors

    Behera, Abhinna K.; Rivière, Emmanuel D.; Marécal, Virginie; Rysman, Jean-François; Chantal, Claud; Sèze, Geneviève; Amarouche, Nadir; Ghysels, Mélanie; Khaykin, Sergey M.; Pommereau, Jean-Pierre; Held, Gerhard; Burgalat, Jérémie; Durry, Georges

    2018-03-01

    In order to better understand the water vapor (WV) intrusion into the tropical stratosphere, a mesoscale simulation of the tropical tropopause layer using the BRAMS (Brazilian version of Regional Atmospheric Modeling System (RAMS)) model is evaluated for a wet season. This simulation with a horizontal grid point resolution of 20 km × 20 km cannot resolve the stratospheric overshooting convection (SOC). Its ability to reproduce other key parameters playing a role in the stratospheric WV abundance is investigated using the balloon-borne TRO-Pico campaign measurements, the upper-air soundings over Brazil, and the satellite observations by Aura Microwave Limb Sounder, Microwave Humidity Sounder, and Geostationary Operational Environmental Satellite 12. The BRAMS exhibits a good ability in simulating temperature, cold-point, WV variability around the tropopause. However, the simulation is typically observed to be warmer by ˜2.0°C and wetter by ˜0.4 ppmv at the hygropause, which can be partly affiliated with the grid boundary nudging of the model by European Centre for Medium-Range Weather Forecasts operational analyses. The modeled cloud tops show a good correlation (maximum cross-correlation of ˜0.7) with Geostationary Operational Environmental Satellite 12. Furthermore, the overshooting cells detected by Microwave Humidity Sounder are observed at the locations, where 75% of the modeled cloud tops are higher than 11 km. Finally, the modeled inertia-gravity wave periodicity and wavelength are comparable with those deduced from the radio sounding measurements during TRO-Pico campaign. The good behavior of BRAMS confirms the SOC contribution in the WV abundance, and variability is of lesser importance than the large-scale processes. This simulation can be used as a reference run for upscaling the impact of SOC at a continental scale for future studies.

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

    Dawei Han

    2012-02-01

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

  19. Improvement of AEP Predictions Using Diurnal CFD Modelling with Site-Specific Stability Weightings Provided from Mesoscale Simulation

    Hristov, Y; Oxley, G; Žagar, M

    2014-01-01

    The Bolund measurement campaign, performed by Danish Technical University (DTU) Wind Energy Department (also known as RISØ), provided significant insight into wind flow modeling over complex terrain. In the blind comparison study several modelling solutions were submitted with the vast majority being steady-state Computational Fluid Dynamics (CFD) approaches with two equation k-ε turbulence closure. This approach yielded the most accurate results, and was identified as the state-of-the-art tool for wind turbine generator (WTG) micro-siting. Based on the findings from Bolund, further comparison between CFD and field measurement data has been deemed essential in order to improve simulation accuracy for turbine load and long-term Annual Energy Production (AEP) estimations. Vestas Wind Systems A/S is a major WTG original equipment manufacturer (OEM) with an installed base of over 60GW in over 70 countries accounting for 19% of the global installed base. The Vestas Performance and Diagnostic Centre (VPDC) provides online live data to more than 47GW of these turbines allowing a comprehensive comparison between modelled and real-world energy production data. In previous studies, multiple sites have been simulated with a steady neutral CFD formulation for the atmospheric surface layer (ASL), and wind resource (RSF) files have been generated as a base for long-term AEP predictions showing significant improvement over predictions performed with the industry standard linear WAsP tool. In this study, further improvements to the wind resource file generation with CFD are examined using an unsteady diurnal cycle approach with a full atmospheric boundary layer (ABL) formulation, with the unique stratifications throughout the cycle weighted according to mesoscale simulated sectorwise stability frequencies

  20. Constructing irregular surfaces to enclose macromolecular complexes for mesoscale modeling using the discrete surface charge optimization (DISCO) algorithm.

    Zhang, Qing; Beard, Daniel A; Schlick, Tamar

    2003-12-01

    minimizer) is efficient and does not depend on the initial assigned values, and that the residual is acceptable when the distance to the model surface is close to, or larger than, the Debye length. We illustrate applications of DiSCO's model-building procedure to chromatin folding and supercoiled DNA bound to Hin and Fis proteins. DiSCO is generally applicable to other interesting macromolecular systems for which mesoscale models are appropriate, to yield a resolution between the all-atom representative and the polymer level. Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 2063-2074, 2003

  1. Meso-scale wind variability. Final report

    Larsen, S.; Larsen, X.; Vincent, C.; Soerensen, P.; Pinson, P.; Trombe, P.-J.; Madsen, H.; Cutululis, N.

    2011-11-15

    The project has aimed to characterize mesoscale meteorological phenomenon for the North Sea and the Inner Danish waters, and additionally aimed on improving the predictability and quality of the power production from offshore windfarms. The meso-scale meteorology has been characterized with respect to the physical processes, climatology, spectral characteristics and correlation properties based on measurements from wind farms, satellite data (SAR) and mesoscale numerical modeling (WRF). The abilities of the WRF model to characterize and predict relevant mesoscale phenomenon has been proven. Additionally application of statistical forecasting, using a Markov switching approach that can be related to the meteorological conditions, to analyze and short term predict the power production from an offshore wind farms have been documented. Two PhD studies have been conducted in connection with the project. The project has been a cooperative project between Risoe DTU, IMM DTU, DONG Energy, Vattenfall and VESTAS. It is registered as Energinet.dk, project no. 2007-1-7141. (Author)

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

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

    1989-01-01

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

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

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

  4. Genesis of Twin Tropical Cyclones as Revealed by a Global Mesoscale Model: The Role of Mixed Rossby Gravity Waves

    Shen, Bo-Wen; Tao, Wei-Kuo; Lin, Yuh-Lang; Laing, Arlene

    2012-01-01

    In this study, it is proposed that twin tropical cyclones (TCs), Kesiny and 01A, in May 2002 formed in association with the scale interactions of three gyres that appeared as a convectively coupled mixed Rossby gravity (ccMRG) wave during an active phase of the Madden-Julian Oscillation (MJO). This is shown by analyzing observational data, including NCEP reanalysis data and METEOSAT 7 IR satellite imagery, and performing numerical simulations using a global mesoscale model. A 10-day control run is initialized at 0000 UTC 1 May 2002 with grid-scale condensation but no sub-grid cumulus parameterizations. The ccMRG wave was identified as encompassing two developing and one non-developing gyres, the first two of which intensified and evolved into the twin TCs. The control run is able to reproduce the evolution of the ccMRG wave and thus the formation of the twin TCs about two and five days in advance as well as their subsequent intensity evolution and movement within an 8-10 day period. Five additional 10-day sensitivity experiments with different model configurations are conducted to help understand the interaction of the three gyres, leading to the formation of the TCs. These experiments suggest the improved lead time in the control run may be attributed to the realistic simulation of the ccMRG wave with the following processes: (1) wave deepening (intensification) associated with a reduction in wavelength and/or the intensification of individual gyres, (2) poleward movement of gyres that may be associated with boundary layer processes, (3) realistic simulation of moist processes at regional scales in association with each of the gyres, and (4) the vertical phasing of low- and mid-level cyclonic circulations associated with a specific gyre.

  5. Weather forecasting for Eastern Amazon with OLAM model

    Renato Ramos da Silva

    2014-12-01

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

  6. An intercomparison of mesoscale models at simple sites for wind energy applications

    Olsen, Bjarke Tobias; Hahmann, Andrea N.; Sempreviva, Anna Maria

    2017-01-01

    of the output from 25 NWP models is presented for three sites in northern Europe characterized by simple terrain. The models are evaluated sing a number of statistical properties relevant to wind energy and verified with observations. On average the models have small wind speed biases offshore and aloft ( ... %) and larger biases closer to the surface over land (> 7 %). A similar pattern is detected for the inter-model spread. Strongly stable and strongly unstable atmospheric stability conditions are associated with larger wind speed errors. Strong indications are found that using a grid spacing larger than 3 km...... decreases the accuracy of the models, but we found no evidence that using a grid spacing smaller than 3 km is necessary for these simple sites. Applying the models to a simple wind energy offshore wind farm highlights the importance of capturing the correct distributions of wind speed and direction....

  7. A meso-scale model to study the compressive strength of woven carbon fiber reinforced plastics

    Schormans, J.M.J.; Remmers, J.J.C.; Wilson, W.; Deshpande, V.S.

    2016-01-01

    Modeling kink-band formation in woven composites using a detailed micro-model is numerically expensive. In order to reduce the computational resources, a method to homogenize fiber-tows is proposed which uses a rules of mixture approach. The method is tested by comparing the stiffness and

  8. Meso-scale modeling of air pollution transport/chemistry/deposition and its application

    Kitada, Toshihiro

    2007-01-01

    Transport/chemistry/deposition model for atmospheric trace chemical species is now regarded as an important tool for an understanding of the effects of various human activities, such as fuel combustion and deforestation, on human health, eco-system, and climate and for planning of appropriate control of emission sources. Several 'comprehensive' models have been proposed such as RADM (Chang, et al., 1987), STEM-II (Carmichael, et al., 1986), and CMAQ (Community Multi-scale Air Quality model, e.g., EPA website, 2003); the 'comprehensive' models include not only gas/aerosol phase chemistry but also aqueous phase chemistry in cloud/rain water in addition to the processes of advection, diffusion, wet deposition (mass transfer between aqueous and gas/aerosol phases), and dry deposition. The target of the development of the 'comprehensive' model will be that the model can correctly reproduce mass balance of various chemical species in the atmosphere with keeping adequate accuracy for calculated concentration distributions of chemical species. For the purpose, one of the important problems is a reliable wet deposition modeling, and here, we introduce two types of methods of 'cloud-resolving' and 'non-cloud-resolving' modeling for the wet deposition of pollutants. (author)

  9. High-Resolution Mesoscale Simulations of the 6-7 May 2000 Missouri Flash Flood: Impact of Model Initialization and Land Surface Treatment

    Baker, R. David; Wang, Yansen; Tao, Wei-Kuo; Wetzel, Peter; Belcher, Larry R.

    2004-01-01

    High-resolution mesoscale model simulations of the 6-7 May 2000 Missouri flash flood event were performed to test the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation. In this flash flood event, a mesoscale convective system (MCS) produced over 340 mm of rain in roughly 9 hours in some locations. Two different types of model initialization were employed: 1) NCEP global reanalysis with 2.5-degree grid spacing and 12-hour temporal resolution, and 2) Eta reanalysis with 40- km grid spacing and $hour temporal resolution. In addition, two different land surface treatments were considered. A simple land scheme. (SLAB) keeps soil moisture fixed at initial values throughout the simulation, while a more sophisticated land model (PLACE) allows for r interactive feedback. Simulations with high-resolution Eta model initialization show considerable improvement in the intensity of precipitation due to the presence in the initialization of a residual mesoscale convective vortex (hlCV) from a previous MCS. Simulations with the PLACE land model show improved location of heavy precipitation. Since soil moisture can vary over time in the PLACE model, surface energy fluxes exhibit strong spatial gradients. These surface energy flux gradients help produce a strong low-level jet (LLJ) in the correct location. The LLJ then interacts with the cold outflow boundary of the MCS to produce new convective cells. The simulation with both high-resolution model initialization and time-varying soil moisture test reproduces the intensity and location of observed rainfall.

  10. Mesoscale atmospheric modeling of accidental toxic and radioactive releases for emergency response at SRS

    O'Steen, B.L.; Fast, J.D.

    1992-01-01

    In August of 1991, the Environmental Transport Group (ETG) began the development of an advanced Emergency Response (ER) system based upon the Colorado State University Regional Atmospheric Modeling System 1 (RAMS). This model simulates the three-dimensional, time-dependent, flow field and thermodynamic structure of the planetary boundary layer (PBL). A companion Lagrangian Particle Dispersion Model 2 (LPDM) simulates contaminant transport based on the flow and turbulence fields generated by RAMS. The current report describes progress to date on this project in the areas of data development, data assimilation, and operational (real-time) procedures. In particular, a diagnostic capability for simulating contaminant transport is demonstrated

  11. Modeling Hot-Spot Contributions in Shocked High Explosives at the Mesoscale

    Harrier, Danielle [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-08-12

    When looking at performance of high explosives, the defects within the explosive become very important. Plastic bonded explosives, or PBXs, contain voids of air and bonder between the particles of explosive material that aid in the ignition of the explosive. These voids collapse in high pressure shock conditions, which leads to the formation of hot spots. Hot spots are localized high temperature and high pressure regions that cause significant changes in the way the explosive material detonates. Previously hot spots have been overlooked with modeling, but now scientists are realizing their importance and new modeling systems that can accurately model hot spots are underway.

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

    J. Kukkonen

    2012-01-01

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

  13. Application of two phosphorus models with different complexities in a mesoscale river catchment

    B. Guse

    2007-06-01

    Full Text Available The water balance and phosphorus inputs of surface waters of the Weiße Elster catchment, Germany, have been quantified using the models GROWA/MEPhos and SWAT. A comparison of the model results shows small differences in the mean long-term total runoff for the entire study area. All relevant pathways of phosphorus transport were considered in MEPhos with phosphorus inputs resulting to about 65% from point sources. SWAT focuses on agricultural areas and estimates a phosphorus input of about 60% through erosion. The mean annual phosphorus input from erosion calculated with SWAT is six times higher than the estimation with MEPhos due to the differing model concepts. This shows the uncertainty contributed by the modelling description of phosphorus pathways.

  14. Atmosphere surface storm track response to resolved ocean mesoscale in two sets of global climate model experiments

    Small, R. Justin; Msadek, Rym; Kwon, Young-Oh; Booth, James F.; Zarzycki, Colin

    2018-05-01

    It has been hypothesized that the ocean mesoscale (particularly ocean fronts) can affect the strength and location of the overlying extratropical atmospheric storm track. In this paper, we examine whether resolving ocean fronts in global climate models indeed leads to significant improvement in the simulated storm track, defined using low level meridional wind. Two main sets of experiments are used: (i) global climate model Community Earth System Model version 1 with non-eddy-resolving standard resolution or with ocean eddy-resolving resolution, and (ii) the same but with the GFDL Climate Model version 2. In case (i), it is found that higher ocean resolution leads to a reduction of a very warm sea surface temperature (SST) bias at the east coasts of the U.S. and Japan seen in standard resolution models. This in turn leads to a reduction of storm track strength near the coastlines, by up to 20%, and a better location of the storm track maxima, over the western boundary currents as observed. In case (ii), the change in absolute SST bias in these regions is less notable, and there are modest (10% or less) increases in surface storm track, and smaller changes in the free troposphere. In contrast, in the southern Indian Ocean, case (ii) shows most sensitivity to ocean resolution, and this coincides with a larger change in mean SST as ocean resolution is changed. Where the ocean resolution does make a difference, it consistently brings the storm track closer in appearance to that seen in ERA-Interim Reanalysis data. Overall, for the range of ocean model resolutions used here (1° versus 0.1°) we find that the differences in SST gradient have a small effect on the storm track strength whilst changes in absolute SST between experiments can have a larger effect. The latter affects the land-sea contrast, air-sea stability, surface latent heat flux, and the boundary layer baroclinicity in such a way as to reduce storm track activity adjacent to the western boundary in the N

  15. The Impact of Microphysics on Intensity and Structure of Hurricanes and Mesoscale Convective Systems

    Tao, Wei-Kuo; Shi, Jainn J.; Jou, Ben Jong-Dao; Lee, Wen-Chau; Lin, Pay-Liam; Chang, Mei-Yu

    2007-01-01

    During the past decade, both research and operational numerical weather prediction models, e.g. Weather Research and Forecast (WRF) model, have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. WRF is a next-generation mesoscale forecast model and assimilation system that has incorporated modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WRF model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options such as Purdue Lin et al. (1983), WSM 6-class and Thompson microphysics schemes. We have recently implemented three sophisticated cloud microphysics schemes into WRF. The cloud microphysics schemes have been extensively tested and applied for different mesoscale systems in different geographical locations. The performances of these schemes have been compared to those from other WRF microphysics options. We are performing sensitivity tests in using WRF to examine the impact of six different cloud microphysical schemes on precipitation processes associated hurricanes and mesoscale convective systems developed at different geographic locations [Oklahoma (IHOP), Louisiana (Hurricane Katrina), Canada (C3VP - snow events), Washington (fire storm), India (Monsoon), Taiwan (TiMREX - terrain)]. We will determine the microphysical schemes for good simulated convective systems in these geographic locations. We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems.

  16. Network-based Modeling of Mesoscale Catchments - The Hydrology Perspective of Glowa-danube

    Ludwig, R.; Escher-Vetter, H.; Hennicker, R.; Mauser, W.; Niemeyer, S.; Reichstein, M.; Tenhunen, J.

    Within the GLOWA initiative of the German Ministry for Research and Educa- tion (BMBF), the project GLOWA-Danube is funded to establish a transdisciplinary network-based decision support tool for water related issues in the Upper Danube wa- tershed. It aims to develop and validate integration techniques, integrated models and integrated monitoring procedures and to implement them in the network-based De- cision Support System DANUBIA. An accurate description of processes involved in energy, water and matter fluxes and turnovers requires an intense collaboration and exchange of water related expertise of different scientific disciplines. DANUBIA is conceived as a distributed expert network and is developed on the basis of re-useable, refineable, and documented sub-models. In order to synthesize a common understand- ing between the project partners, a standardized notation of parameters and functions and a platform-independent structure of computational methods and interfaces has been established using the Unified Modeling Language UML. DANUBIA is object- oriented, spatially distributed and raster-based at its core. It applies the concept of "proxels" (Process Pixel) as its basic object, which has different dimensions depend- ing on the viewing scale and connects to its environment through fluxes. The presented study excerpts the hydrological view point of GLOWA-Danube, its approach of model coupling and network based communication (using the Remote Method Invocation RMI), the object-oriented technology to simulate physical processes and interactions at the land surface and the methodology to treat the issue of spatial and temporal scal- ing in large, heterogeneous catchments. The mechanisms applied to communicate data and model parameters across the typical discipline borders will be demonstrated from the perspective of a land-surface object, which comprises the capabilities of interde- pendent expert models for snowmelt, soil water movement, runoff formation, plant

  17. MESOI Version 2.0: an interactive mesoscale Lagrangian puff dispersion model with deposition and decay

    Ramsdell, J.V.; Athey, G.F.; Glantz, C.S.

    1983-11-01

    MESOI Version 2.0 is an interactive Lagrangian puff model for estimating the transport, diffusion, deposition and decay of effluents released to the atmosphere. The model is capable of treating simultaneous releases from as many as four release points, which may be elevated or at ground-level. The puffs are advected by a horizontal wind field that is defined in three dimensions. The wind field may be adjusted for expected topographic effects. The concentration distribution within the puffs is initially assumed to be Gaussian in the horizontal and vertical. However, the vertical concentration distribution is modified by assuming reflection at the ground and the top of the atmospheric mixing layer. Material is deposited on the surface using a source depletion, dry deposition model and a washout coefficient model. The model also treats the decay of a primary effluent species and the ingrowth and decay of a single daughter species using a first order decay process. This report is divided into two parts. The first part discusses the theoretical and mathematical bases upon which MESOI Version 2.0 is based. The second part contains the MESOI computer code. The programs were written in the ANSI standard FORTRAN 77 and were developed on a VAX 11/780 computer. 43 references, 14 figures, 13 tables

  18. Development of a prototype mesoscale computer model incorporating treatment of topography

    Apsimon, H.; Kitson, K.; Fawcett, M.; Goddard, A.J.H.

    1984-01-01

    Models are available for simulating dispersal of accidental releases, using mass-consistent wind-fields and accounting for site-specific topography. These techniques were examined critically to see if they might be improved, and to assess their limitations. An improved model, windfield adjusted for topography (WAFT), was developed (with advantages over MATHEW used in the Atmospheric Release Advisory Capability - ARAC system). To simulate dispersion in the windfields produced by WAFT and calculate time integrated air concentrations and dry and wet deposition the TOMCATS model was developed. It treats the release as an assembly of pseudo-particles using Monte Carlo techniques to simulate turbulent displacements. It allows for larger eddy effects in the horizontal turbulence spectrum. Wet deposition is calculated using inhomogeneous rainfields evolving in time and space. The models were assessed, applying them to hypothetical releases in complex terrain, using typical data applicable in accident conditions, and undertaking sensitivity studies. One finds considerable uncertainty in results produced by these models. Although useful for post-facto analysis, such limitations cast doubt on their advantages, relative to simpler techniques, during an actual emergency

  19. Random variability in mesoscale wind observations and implications for diffusion models

    Hanna, S.R. [Sigma Research Corp., Concord, MA (United States)

    1994-12-31

    The investigation reported in this paper grew out of a preliminary analysis of methods by which regional air quality models such as the Regional Oxidant Model account for horizontal transport and diffusion. It was discovered that there is a variety of often inconsistent methods used to parameterize horizontal diffusion at meso- and regional scales, and the time seemed ripe to review and compare and contrast these schemes. This paper provides a brief overview of the major issues that were uncovered and lists a few specific examples of the technical approaches that are used. Subsequent sections cover the basic physics of horizontal diffusion, the characteristics of observed wind fields, and methods of parameterizing horizontal diffusion in air quality models.

  20. Mesoscale modeling and simulation of microstructure evolution during dynamic recrystallization of a Ni-based superalloy

    Chen, Fei [University of Nottingham, Department of Mechanical, Materials and Manufacturing Engineering, Nottingham (United Kingdom); Shanghai Jiao Tong University, Institute of Forming Technology and Equipment, Shanghai (China); Cui, Zhenshan [Shanghai Jiao Tong University, Institute of Forming Technology and Equipment, Shanghai (China); Ou, Hengan [University of Nottingham, Department of Mechanical, Materials and Manufacturing Engineering, Nottingham (United Kingdom); Long, Hui [University of Sheffield, Department of Mechanical Engineering, Sheffield (United Kingdom)

    2016-10-15

    Microstructural evolution and plastic flow characteristics of a Ni-based superalloy were investigated using a simulative model that couples the basic metallurgical principle of dynamic recrystallization (DRX) with the two-dimensional (2D) cellular automaton (CA). Variation of dislocation density with local strain of deformation is considered for accurate determination of the microstructural evolution during DRX. The grain topography, the grain size and the recrystallized fraction can be well predicted by using the developed CA model, which enables to the establishment of the relationship between the flow stress, dislocation density, recrystallized fraction volume, recrystallized grain size and the thermomechanical parameters. (orig.)

  1. The dynamic background of a non-hydrostatic mesoscale model of the atmospheric circulation

    Kapitza, H.

    1987-01-01

    The anelastically approximated basic equations are transformed into a rectangular computational domain. The integration is performed with the McCormack-Scheme, while the pressure is calculated by a CG-method (KAPITZA and EPPEL, 1987). Useful boundary conditions are discussed. The model is tested with stratified flow over isolated hills. Analytic solutions derived from the linearized equations are compared with results of the linear model version. Very good agreement is found as long as wave reflexions at the upper boundary are prevented. With 27 figs [de

  2. Role of land state in a high resolution mesoscale model for ...

    13

    2015-10-02

    Oct 2, 2015 ... School of Earth, Ocean and Climate Sciences ... Though global models predicted the large scale event, but they had failed to predict realistic ... this study is to assess the impact of land state conditions in ...... Chand, R and C Singh 2015 Movements of western disturbance and associated cloud convection J.

  3. Development of a prototype mesoscale computer model incorporating treatment of topography

    Apsimon, H.M.; Goddard, A.J.H.; Kitson, K.; Fawcett, M.

    1985-01-01

    More sophisticated models are now available to simulate dispersal of accidental radioactive releases to the atmosphere; these use mass-consistent windfields and attempt allowance for site-specific topographical features. Our aim has been to examine these techniques critically, develop where possible, and assess limitations and accuracy. The resulting windfield model WAFT uses efficient numerical techniques with improved orographic resolution and treatment of meteorological conditions. Time integrated air concentrations, dry and wet deposition are derived from TOMCATS, which applies Monte-Carlo techniques to an assembly of pseudo-particles representing the release, with specific attention to the role of large eddies and evolving inhomogeneous rainfields. These models have been assessed by application to hypothetical releases in complex terrain using data which would have been available in the event of an accident, and undertaking sensitivity studies. It is concluded that there is considerable uncertainty in results produced by such models; although they may be useful in post-facto analysis, such limitations cast doubt on their advantages relative to simpler techniques, with more modest requirements, during an actual emergency. (author)

  4. Validation of a mesoscale hydrological model in a small-scale forested catchment

    Šípek, Václav; Tesař, Miroslav

    2016-01-01

    Roč. 47, č. 1 (2016), s. 27-41 ISSN 1998-9563 R&D Projects: GA TA ČR TA02021451 Institutional support: RVO:67985874 Keywords : hydrological modelling * small catchment * soil moisture * subsurface lateral flow * SWIM Subject RIV: DA - Hydrology ; Limnology Impact factor: 1.754, year: 2016

  5. Ecohydrological modelling of water discharge and nitrate loads in a mesoscale lowland catchment, Germany

    N. Fohrer

    2009-08-01

    Full Text Available The aims of this study are to identify the capacities of applying an ecohydrological model for simulating flow and to assess the impact of point and non-point source pollution on nitrate loads in a complex lowland catchment, which has special hydrological characteristics in comparison with those of other catchments. The study area Kielstau catchment has a size of approximately 50 km2 and is located in the North German lowlands. The water quality is not only influenced by the predominating agricultural land use in the catchment as cropland and pasture, but also by six municipal wastewater treatment plants.

    Ecohydrological models like the SWAT model (Soil and Water Assessment Tool are useful tools for simulating nutrient loads in river catchments. Diffuse entries from the agriculture resulting from fertilizers as well as punctual entries from the wastewater treatment plants are implemented in the model set-up.

    The results of this study show good agreement between simulated and measured daily discharges with a Nash-Sutcliffe efficiency and a correlation coefficient of 0.76 and 0.88 for the calibration period (November 1998 to October 2004; 0.75 and 0.92 for the validation period (November 2004 to December 2007. The model efficiency for daily nitrate loads is 0.64 and 0.5 for the calibration period (June 2005 to May 2007 and the validation period (June 2007 to December 2007, respectively. The study revealed that SWAT performed satisfactorily in simulating daily flow and nitrate loads at the lowland catchment in Northern Germany.

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

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

  7. Thermomechanical properties of polypropylene-based lightweight composites modeled on the mesoscale

    Dostálová, Darina; Kafka, Vratislav; Vokoun, David; Heller, Luděk; Matějka, L.; Kadeřávek, Lukáš; Pěnčík, J.

    2017-01-01

    Roč. 26, Oct (2017), s. 5166-5172 ISSN 1059-9495 R&D Projects: GA ČR GB14-36566G Institutional support: RVO:68378271 ; RVO:68378297 Keywords : building material * composite * creep tests * mesomechanical model * thermal insulation Subject RIV: JI - Composite Materials OBOR OECD: Composites (including laminates, reinforced plastics, cermets, combined natural and synthetic fibre fabrics Impact factor: 1.331, year: 2016

  8. A hybrid, coupled approach for modeling charged fluids from the nano to the mesoscale

    Cheung, James; Frischknecht, Amalie L.; Perego, Mauro; Bochev, Pavel

    2017-11-01

    We develop and demonstrate a new, hybrid simulation approach for charged fluids, which combines the accuracy of the nonlocal, classical density functional theory (cDFT) with the efficiency of the Poisson-Nernst-Planck (PNP) equations. The approach is motivated by the fact that the more accurate description of the physics in the cDFT model is required only near the charged surfaces, while away from these regions the PNP equations provide an acceptable representation of the ionic system. We formulate the hybrid approach in two stages. The first stage defines a coupled hybrid model in which the PNP and cDFT equations act independently on two overlapping domains, subject to suitable interface coupling conditions. At the second stage we apply the principles of the alternating Schwarz method to the hybrid model by using the interface conditions to define the appropriate boundary conditions and volume constraints exchanged between the PNP and the cDFT subdomains. Numerical examples with two representative examples of ionic systems demonstrate the numerical properties of the method and its potential to reduce the computational cost of a full cDFT calculation, while retaining the accuracy of the latter near the charged surfaces.

  9. Mesoscale modelling of radioactive contamination formation in Ukraine caused by the Chernobyl accident

    Talerko, Nikolai

    2005-01-01

    This work is devoted to the reconstruction of time-dependent radioactive contamination fields in the territory of Ukraine in the initial period of the Chernobyl accident using the model of atmospheric transport LEDI (Lagrangian-Eulerian DIffusion model). The modelling results were compared with available 137 Cs air and ground contamination measurement data. The 137 Cs atmospheric transport over the territory of Ukraine was simulated during the first 12 days after the accident (from 26 April to 7 May 1986) using real aerological information and rain measurement network data. The detailed scenario of the release from the accidental unit of the Chernobyl nuclear plant has been built (including time-dependent radioactivity release intensity and time-varied height of the release). The calculations have enabled to explain the main features of spatial and temporal variations of radioactive contamination fields over the territory of Ukraine on the regional scale, including the formation of the major large-scale spots of radioactive contamination caused by dry and wet deposition

  10. Multiscale modeling of dislocation processes in BCC tantalum: bridging atomistic and mesoscale simulations

    Yang, L H; Tang, M; Moriarty, J A

    2001-01-01

    Plastic deformation in bcc metals at low temperatures and high-strain rates is controlled by the motion of a/2 screw dislocations, and understanding the fundamental atomistic processes of this motion is essential to develop predictive multiscale models of crystal plasticity. The multiscale modeling approach presented here for bcc Ta is based on information passing, where results of simulations at the atomic scale are used in simulations of plastic deformation at mesoscopic length scales via dislocation dynamics (DD). The relevant core properties of a/2 screw dislocations in Ta have been obtained using quantum-based interatomic potentials derived from model generalized pseudopotential theory and an ab-initio data base together with an accurate Green's-function simulation method that implements flexible boundary conditions. In particular, the stress-dependent activation enthalpy for the lowest-energy kink-pair mechanism has been calculated and fitted to a revealing analytic form. This is the critical quantity determining dislocation mobility in the DD simulations, and the present activation enthalpy is found to be in good agreement with the previous empirical form used to explain the temperature dependence of the yield stress

  11. Mapping Offshore Winds Around Iceland Using Satellite Synthetic Aperture Radar and Mesoscale Model Simulations

    Hasager, Charlotte Bay; Badger, Merete; Nawri, Nikolai

    2015-01-01

    effects, gap flow, coastal barrier jets, and atmospheric gravity waves are not only observed in SAR, but are also modeled well from HARMONIE. Offshore meteorological observations are not available, but wind speed and wind direction measurements from coastal meteorological masts are found to compare well...... to nearby offshore locations observed by SAR. More than 2500 SAR scenes from the Envisat ASAR wide swathmode are used for wind energy resource estimation. The wind energy potential observed from satellite SAR shows high values above 1000 Wm −2 in coastal regions in the south, east, and west, with lower...

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

    Schubert, Siegfried D.; Lim, Young-Kwon

    2012-01-01

    Extremes in weather and climate encompass a wide array of phenomena including tropical storms, mesoscale convective systems, snowstorms, floods, heat waves, and drought. Understanding how such extremes might change in the future requires an understanding of their past behavior including their connections to large-scale climate variability and trends. Previous studies suggest that the most robust findings concerning changes in short-term extremes are those that can be most directly (though not completely) tied to the increase in the global mean temperatures. These include the findings that (IPCC 2007): There has been a widespread reduction in the number of frost days in mid-latitude regions in recent decades, an increase in the number of warm extremes, particularly warm nights, and a reduction in the number of cold extremes, particularly cold nights. For North America in particular (CCSP SAP 3.3, 2008): There are fewer unusually cold days during the last few decades. The last 10 years have seen a lower number of severe cold waves than for any other 10-year period in the historical record that dates back to 1895. There has been a decrease in the number of frost days and a lengthening of the frost-free season, particularly in the western part of North America. Other aspects of extremes such as the changes in storminess have a less clear signature of long term change, with considerable interannual, and decadal variability that can obscure any climate change signal. Nevertheless, regarding extratropical storms (CCSP SAP 3.3, 2008): The balance of evidence suggests that there has been a northward shift in the tracks of strong low pressure systems (storms) in both the North Atlantic and North Pacific basins. For North America: Regional analyses suggest that there has been a decrease in snowstorms in the South and lower Midwest of the United States, and an increase in snowstorms in the upper Midwest and Northeast. Despite the progress already made, our understanding of the

  13. Mathematical modeling of a four-stroke resonant engine for micro and mesoscale applications

    Preetham, B. S.; Anderson, M.; Richards, C.

    2014-12-01

    In order to mitigate frictional and leakage losses in small scale engines, a compliant engine design is proposed in which the piston in cylinder arrangement is replaced by a flexible cavity. A physics-based nonlinear lumped-parameter model is derived to predict the performance of a prototype engine. The model showed that the engine performance depends on input parameters, such as heat input, heat loss, and load on the engine. A sample simulation for a reference engine with octane fuel/air ratio of 0.043 resulted in an indicated thermal efficiency of 41.2%. For a fixed fuel/air ratio, higher output power is obtained for smaller loads and vice-versa. The heat loss from the engine and the work done on the engine during the intake stroke are found to decrease the indicated thermal efficiency. The ratio of friction work to indicated work in the prototype engine is about 8%, which is smaller in comparison to the traditional reciprocating engines.

  14. Mesoscale Modeling of Kinetic Phase Behaviors in Mg-B-H (Subcontract Report)

    Yu, H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Thornton, K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Wood, B. C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-10-13

    Storage of hydrogen on board vehicles is one of the critical enabling technologies for creating hydrogenfueled transportation systems that can reduce oil dependency and mitigate the long-term effects of fossil fuels on climate change. Stakeholders in developing hydrogen infrastructure are currently focused on highpressure storage at 350 bar and 700 bar, in part because no viable solid-phase storage material has emerged. Nevertheless, solid-state materials, including high-density hydrides, remain of interest because of their unique potential to meet all DOE targets and deliver hydrogen at lower pressures and higher on-board densities. A successful solution would significantly reduce costs and ensure the economic viability of a U.S. hydrogen infrastructure. The Mg(BH4)2-MgB2 system represents a highly promising solution because of its reasonable reaction enthalpy, high intrinsic capacity, and demonstrated reversibility, yet suffers from poor reaction kinetics. This subcontract aims to deliver a phase-field model for the kinetics of the evolution of the relevant phases within the Mg-B-H system during hydrogenation and dehydrogenation. This model will be used within a broader theory, synthesis, and characterization framework to study the properties of geometry-selected nanoparticles of pristine and doped MgB2/Mg(BH4)2 with two aims: (1) understand the intrinsic limitations in (de)hydrogenation; (2) devise strategies for improving thermodynamics and kinetics through nanostructuring.

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

    Chim, Kin-Sang

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

  16. Meso-scale Modeling of Block Copolymers Self-Assembly in Casting Solutions for Membrane Manufacture

    Moreno Chaparro, Nicolas

    2016-05-01

    Isoporous membranes manufactured from diblock copolymer are successfully produced at laboratory scale under controlled conditions. Because of the complex phenomena involved, membrane preparation requires trial and error methodologies to find the optimal conditions, leading to a considerable demand of resources. Experimental insights demonstrate that the self-assembly of the block copolymers in solution has an effect on the final membrane structure. Nevertheless, the complete understanding of these multi-scale phenomena is elusive. Herein we use the coarse-grained method Dissipative Particle Dynamics to study the self-assembly of block copolymers that are used for the preparation of the membranes. To simulate representative time and length scales, we introduce a framework for model reduction of polymer chain representations for dissipative particle dynamics, which preserves the properties governing the phase equilibria. We reduce the number of degrees of freedom by accounting for the correlation between beads in fine-grained models via power laws and the consistent scaling of the simulation parameters. The coarse-graining models are consistent with the experimental evidence, showing a morphological transition of the aggregates as the polymer concentration and solvent affinity change. We show that hexagonal packing of the micelles can occur in solution within different windows of polymer concentration depending on the solvent affinity. However, the shape and size dispersion of the micelles determine the characteristic arrangement. We describe the order of crew-cut micelles using a rigid-sphere approximation and propose different phase parameters that characterize the emergence of monodisperse-spherical micelles in solution. Additionally, we investigate the effect of blending asymmetric diblock copolymers (AB/AC) over the properties of the membranes. We observe that the co-assembly mechanism localizes the AC molecules at the interface of A and B domains, and induces

  17. A mesoscale granular model for the mechanical behavior of alloys during solidification

    Vernede, Stephane [Computational Materials Laboratory, Ecole Polytechnique Federale de Lausanne, Station 12, Lausanne CH-1015 (Switzerland); Alcan Centre de Recherches de Voreppe, ZI Centr' Alp, 725 rue Aristide Berges, BP 27, Voreppe FR-38341 (France)], E-mail: stephane.vernede@alcan.com; Dantzig, Jonathan A. [Computational Materials Laboratory, Ecole Polytechnique Federale de Lausanne, Station 12, Lausanne CH-1015 (Switzerland); Department of Mechanical Science and Engineering, University of Illinois, 1206 West Green Street Urbana, IL 61801 (United States); Rappaz, Michel [Computational Materials Laboratory, Ecole Polytechnique Federale de Lausanne, Station 12, Lausanne CH-1015 (Switzerland)

    2009-03-15

    We present a two-dimensional granular model for the mechanical behavior of an ensemble of globular grains during solidification. The grain structure is produced by a Voronoi tessellation based on an array of predefined nuclei. We consider the fluid flow caused by grain movement and solidification shrinkage in the network of channels that is formed by the faces of the grains in the tessellation. We develop the governing equations for the flow rate and pressure drop across each channel when the grains are allowed to move, and we then assemble the equations into a global expression that conserves mass and force in the system. We show that the formulation is consistent with dissipative formulations of non-equilibrium thermodynamics. Several example problems are presented to illustrate the effect of tensile strains and the availability of liquid to feed the deforming microstructure. For solid fractions below g{sub s}=0.97, we find that the fluid is able to feed the deformation at low strain, even if external feeding is not permitted. For solid fractions above g{sub s}=0.97, clusters of grains with 'dry' boundaries form and fluid flow becomes highly localized.

  18. Nesting Large-Eddy Simulations Within Mesoscale Simulations for Wind Energy Applications

    Lundquist, J. K.; Mirocha, J. D.; Chow, F. K.; Kosovic, B.; Lundquist, K. A.

    2008-12-01

    With increasing demand for more accurate atmospheric simulations for wind turbine micrositing, for operational wind power forecasting, and for more reliable turbine design, simulations of atmospheric flow with resolution of tens of meters or higher are required. These time-dependent large-eddy simulations (LES) account for complex terrain and resolve individual atmospheric eddies on length scales smaller than turbine blades. These small-domain high-resolution simulations are possible with a range of commercial and open- source software, including the Weather Research and Forecasting (WRF) model. In addition to "local" sources of turbulence within an LES domain, changing weather conditions outside the domain can also affect flow, suggesting that a mesoscale model provide boundary conditions to the large-eddy simulations. Nesting a large-eddy simulation within a mesoscale model requires nuanced representations of turbulence. Our group has improved the Weather and Research Forecating model's (WRF) LES capability by implementing the Nonlinear Backscatter and Anisotropy (NBA) subfilter stress model following Kosoviæ (1997) and an explicit filtering and reconstruction technique to compute the Resolvable Subfilter-Scale (RSFS) stresses (following Chow et al, 2005). We have also implemented an immersed boundary method (IBM) in WRF to accommodate complex terrain. These new models improve WRF's LES capabilities over complex terrain and in stable atmospheric conditions. We demonstrate approaches to nesting LES within a mesoscale simulation for farms of wind turbines in hilly regions. Results are sensitive to the nesting method, indicating that care must be taken to provide appropriate boundary conditions, and to allow adequate spin-up of turbulence in the LES domain. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  19. Development of a parameterization scheme of mesoscale convective systems

    Cotton, W.R.

    1994-01-01

    The goal of this research is to develop a parameterization scheme of mesoscale convective systems (MCS) including diabatic heating, moisture and momentum transports, cloud formation, and precipitation. The approach is to: Perform explicit cloud-resolving simulation of MCSs; Perform statistical analyses of simulated MCSs to assist in fabricating a parameterization, calibrating coefficients, etc.; Test the parameterization scheme against independent field data measurements and in numerical weather prediction (NWP) models emulating general circulation model (GCM) grid resolution. Thus far we have formulated, calibrated, implemented and tested a deep convective engine against explicit Florida sea breeze convection and in coarse-grid regional simulations of mid-latitude and tropical MCSs. Several explicit simulations of MCSs have been completed, and several other are in progress. Analysis code is being written and run on the explicitly simulated data

  20. Wildfire particulate matter in Europe during summer 2003: meso-scale modeling of smoke emissions, transport and radiative effects

    A. Hodzic

    2007-08-01

    Full Text Available The present study investigates effects of wildfire emissions on air quality in Europe during an intense fire season that occurred in summer 2003. A meso-scale chemistry transport model CHIMERE is used, together with ground based and satellite aerosol optical measurements, to assess the dispersion of fire emissions and to quantify the associated radiative effects. The model has been improved to take into account a MODIS-derived daily smoke emission inventory as well as the injection altitude of smoke particles. The simulated aerosol optical properties are put into a radiative transfer model to estimate (off-line the effects of smoke particles on photolysis rates and atmospheric radiative forcing. We have found that the simulated wildfires generated comparable amounts of primary aerosol pollutants (130 kTons of PM2.5, fine particles to anthropogenic sources during August 2003, and caused significant changes in aerosol optical properties not only close to the fire source regions, but also over a large part of Europe as a result of the long-range transport of the smoke. Including these emissions into the model significantly improved its performance in simulating observed aerosol concentrations and optical properties. Quantitative comparison with MODIS and POLDER data during the major fire event (3–8 August 2003 showed the ability of the model to reproduce high aerosol optical thickness (AOT over Northern Europe caused by the advection of the smoke plume from the Portugal source region. Although there was a fairly good spatial agreement with satellite data (correlation coefficients ranging from 0.4 to 0.9, the temporal variability of AOT data at specific AERONET locations was not well captured by the model. Statistical analyses of model-simulated AOT data at AERONET ground stations showed a significant decrease in the model biases suggesting that wildfire emissions are responsible for a 30% enhancement in mean AOT values during the heat

  1. Measurements and Mesoscale Modeling of Autumnal Vertical Ozone Profiles in Southern Taiwan

    Yen-Ping Peng

    2008-01-01

    Full Text Available Vertical measurements of ozone were made using a tethered balloon at the Linyuan site in Kaohsiung County, southern Taiwan. Ozone was monitored at altitudes of 0, 100, 300, 500, and 1000 m from November 23 to 25 in 2005. The potential temperature profiles revealed a stable atmosphere during the study period, largely because of the dominance of the high-pressure system and nocturnal radiation cooling close to the surface. The mixing height was low (50 - 300 m, particularly in the late night and early morning. The surface ozone concentrations that were predicted using TAPM (The Air Pollution Model were high (33.7 - 119 ppbv in the daytime (10:00 - 16:00 and were low (10 - 40 ppbv at other times; the predictions of which were consistent with the observations. The simulated surface ozone concentrations reveal that costal lands typically had higher ozone concentrations than those inland, because most industrial parks are located in or close to the boundaries of Kaohsiung City. Both measurements and simulations indicate that daytime ozone concentrations decreased quickly with increasing height at altitudes below 300 m; while nighttime ozone concentrations were lower at low altitudes (50 to 300 m than at higher altitudes, partly because of dry deposition and titration of surface ozone by the near-surface nitrogen oxides (NOx and partly because of the existence of the residual layer above the stable nocturnal boundary layer. The simulations show a good correlation between the maximum daytime surface ozone concentration and average nighttime ozone concentration above the nocturnal boundary layer.

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

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

    2013-12-01

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

  3. Climate and weather risk in natural resource models

    Merrill, Nathaniel Henry

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

  4. Validation of satellite SAR offshore wind speed maps to in-situ data, microscala and mesoscale model results

    Hasager, C B; Astrup, P; Barthelmie, R; Dellwik, E; Hoffmann Joergensen, B; Gylling Mortensen, N; Nielsen, M; Pryor, S; Rathmann, O

    2002-05-01

    A validation study has been performed in order to investigate the precision and accuracy of the satellite-derived ERS-2 SAR wind products in offshore regions. The overall project goal is to develop a method for utilizing the satellite wind speed maps for offshore wind resources, e.g. in future planning of offshore wind farms. The report describes the validation analysis in detail for three sites in Denmark, Italy and Egypt. The site in Norway is analyzed by the Nansen Environmental and Remote Sensing Centre (NERSC). Wind speed maps and wind direction maps from Earth Observation data recorded by the ERS-2 SAR satellite have been obtained from the NERSC. For the Danish site the wind speed and wind direction maps have been compared to in-situ observations from a met-mast at Horns Rev in the North Sea located 14 km offshore. The SAR wind speeds have been area-averaged by simple and advanced footprint modelling, ie. the upwind conditions to the meteorological mast are explicitly averaged in the SAR wind speed maps before comparison. The comparison results are very promising with a standard error of {+-} 0.61 m s{sup -1}, a bias {approx}2 m s{sup -1} and R{sup 2} {approx}0.88 between in-situ wind speed observations and SAR footprint averaged values at 10 m level. Wind speeds predicted by the local scale model LINCOM and the mesoscale model KAMM2 have been compared to the spatial variations in the SAR wind speed maps. The finding is a good correspondence between SAR observations and model results. Near the coast is an 800 m wide band in which the SAR wind speed observations have a strong negative bias. The bathymetry of Horns Rev combined with tidal currents give rise to bias in the SAR wind speed maps near areas of shallow, complex bottom topography in some cases. A total of 16 cases were analyzed for Horns Rev. For Maddalena in Italy five cases were analyzed. At the Italian site the SAR wind speed maps were compared to WAsP and KAMM2 model results. The WAsP model

  5. Evaluation of meteorological fields generated by a prognostic mesoscale model using data collected during the 1993 GMAQS/COAST field study

    Lolk, N.K.; Douglas, S.G.

    1996-01-01

    In 1993, the US Interior Department's Minerals Management Service (MMS) sponsored the Gulf of Mexico Air Quality Study (GMAQS). Its purpose was to assess potential impacts of offshore petrochemical development on ozone concentrations in nonattainment areas in the Texas/Louisiana Gulf Coast region as mandated by the 1990 Clean Air Act Amendments. The GMAQS comprised data collection, data analysis, and applications of an advanced photochemical air quality model, the variable-grid Urban Airshed Model (UAM-V), and a prognostic mesoscale meteorological model (SAIMM -- Systems Applications International Mesoscale Model) to simulate two ozone episodes that were captured during the summer field study. The primary purpose of this paper is to evaluate the SAIMM-simulated meteorological fields using graphical analysis that utilize the comprehensive GMAQS/COAST (Gulf of Mexico Air Quality Study/Coastal Oxidant Assessment for Southeast Texas) database and to demonstrate the ability of the SAIMM to simulate the day-to-day variations in the evolution and structure of the gulf breeze and the mixed layer

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

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

    2015-12-01

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

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

    Hesse, Michael

    2010-01-01

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

  8. Mesoscale modeling of smoke transport over Central Africa: influences of trade winds, subtropical high, ITCZ and vertical statistics

    Yang, Z.; Wang, J.; Hyer, E. J.; Ichoku, C. M.

    2012-12-01

    A fully-coupled meteorology-chemistry-aerosol model, Weather Research and Forecasting model with Chemistry (WRF-Chem), is used to simulate the transport of smoke aerosol over the Central Africa during February 2008. Smoke emission used in this study is specified from the Fire Locating and Modeling of Burning Emissions (FLAMBE) database derived from Moderate Resolution Imaging Spectroradiometer (MODIS) fire products. Model performance is evaluated using MODIS true color images, measured Aerosol Optical Depth (AOD) from space-borne MODIS (550 nm) and ground-based AERONET (500 nm), and Cloud-Aerosol Lidar data with Orthogonal Polarization (CALIOP) level 1 and 2 products. The simulated smoke transport is in good agreement with the validation data. Analyzing from three smoke events, smoke is constrained in a narrow belt between the Equator and 10°N near the surface, with the interplay of trade winds, subtropical high, and ITCZ. At the 700 hpa level, smoke expands farther meridionally. Topography blocks the smoke transport to the southeast of study area, because of high mountains located near the Great Rift Valley region. The simulation with injection height of 650 m is consistent with CALIOP measurements. The particular phenomenon, aerosol above cloud, is studied statistically from CALIOP observations. The total percentage of aerosol above cloud is about 5%.

  9. O the Development and Use of Four-Dimensional Data Assimilation in Limited-Area Mesoscale Models Used for Meteorological Analysis.

    Stauffer, David R.

    1990-01-01

    The application of dynamic relationships to the analysis problem for the atmosphere is extended to use a full-physics limited-area mesoscale model as the dynamic constraint. A four-dimensional data assimilation (FDDA) scheme based on Newtonian relaxation or "nudging" is developed and evaluated in the Penn State/National Center for Atmospheric Research (PSU/NCAR) mesoscale model, which is used here as a dynamic-analysis tool. The thesis is to determine what assimilation strategies and what meterological fields (mass, wind or both) have the greatest positive impact on the 72-h numerical simulations (dynamic analyses) of two mid-latitude, real-data cases. The basic FDDA methodology is tested in a 10-layer version of the model with a bulk-aerodynamic (single-layer) representation of the planetary boundary layer (PBL), and refined in a 15-layer version of the model by considering the effects of data assimilation within a multi-layer PBL scheme. As designed, the model solution can be relaxed toward either gridded analyses ("analysis nudging"), or toward the actual observations ("obs nudging"). The data used for assimilation include standard 12-hourly rawinsonde data, and also 3-hourly mesoalpha-scale surface data which are applied within the model's multi-layer PBL. Continuous assimilation of standard-resolution rawinsonde data into the 10-layer model successfully reduced large-scale amplitude and phase errors while the model realistically simulated mesoscale structures poorly defined or absent in the rawinsonde analyses and in the model simulations without FDDA. Nudging the model fields directly toward the rawinsonde observations generally produced results comparable to nudging toward gridded analyses. This obs -nudging technique is especially attractive for the assimilation of high-frequency, asynoptic data. Assimilation of 3-hourly surface wind and moisture data into the 15-layer FDDA system was most effective for improving the simulated precipitation fields because a

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

    Utili, Stefano; Crosta, Giovanni B.

    2011-01-01

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

  11. Simulating the Refractive Index Structure Constant ({C}_{n}^{2}) in the Surface Layer at Antarctica with a Mesoscale Model

    Qing, Chun; Wu, Xiaoqing; Li, Xuebin; Tian, Qiguo; Liu, Dong; Rao, Ruizhong; Zhu, Wenyue

    2018-01-01

    In this paper, we introduce an approach wherein the Weather Research and Forecasting (WRF) model is coupled with the bulk aerodynamic method to estimate the surface layer refractive index structure constant (C n 2) above Taishan Station in Antarctica. First, we use the measured meteorological parameters to estimate C n 2 using the bulk aerodynamic method, and second, we use the WRF model output parameters to estimate C n 2 using the bulk aerodynamic method. Finally, the corresponding C n 2 values from the micro-thermometer are compared with the C n 2 values estimated using the WRF model coupled with the bulk aerodynamic method. We analyzed the statistical operators—the bias, root mean square error (RMSE), bias-corrected RMSE (σ), and correlation coefficient (R xy )—in a 20 day data set to assess how this approach performs. In addition, we employ contingency tables to investigate the estimation quality of this approach, which provides complementary key information with respect to the bias, RMSE, σ, and R xy . The quantitative results are encouraging and permit us to confirm the fine performance of this approach. The main conclusions of this study tell us that this approach provides a positive impact on optimizing the observing time in astronomical applications and provides complementary key information for potential astronomical sites.

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

    Krissansen-Totton, Joshua; Catling, David C

    2017-05-22

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

  13. Regionalization of meso-scale physically based nitrogen modeling outputs to the macro-scale by the use of regression trees

    Künne, A.; Fink, M.; Kipka, H.; Krause, P.; Flügel, W.-A.

    2012-06-01

    In this paper, a method is presented to estimate excess nitrogen on large scales considering single field processes. The approach was implemented by using the physically based model J2000-S to simulate the nitrogen balance as well as the hydrological dynamics within meso-scale test catchments. The model input data, the parameterization, the results and a detailed system understanding were used to generate the regression tree models with GUIDE (Loh, 2002). For each landscape type in the federal state of Thuringia a regression tree was calibrated and validated using the model data and results of excess nitrogen from the test catchments. Hydrological parameters such as precipitation and evapotranspiration were also used to predict excess nitrogen by the regression tree model. Hence they had to be calculated and regionalized as well for the state of Thuringia. Here the model J2000g was used to simulate the water balance on the macro scale. With the regression trees the excess nitrogen was regionalized for each landscape type of Thuringia. The approach allows calculating the potential nitrogen input into the streams of the drainage area. The results show that the applied methodology was able to transfer the detailed model results of the meso-scale catchments to the entire state of Thuringia by low computing time without losing the detailed knowledge from the nitrogen transport modeling. This was validated with modeling results from Fink (2004) in a catchment lying in the regionalization area. The regionalized and modeled excess nitrogen correspond with 94%. The study was conducted within the framework of a project in collaboration with the Thuringian Environmental Ministry, whose overall aim was to assess the effect of agro-environmental measures regarding load reduction in the water bodies of Thuringia to fulfill the requirements of the European Water Framework Directive (Bäse et al., 2007; Fink, 2006; Fink et al., 2007).

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

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

    2012-01-01

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

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

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

    2013-06-28

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

  16. ORILAM, a three-moment lognormal aerosol scheme for mesoscale atmospheric model: Online coupling into the Meso-NH-C model and validation on the Escompte campaign

    Tulet, Pierre; Crassier, Vincent; Cousin, Frederic; Suhre, Karsten; Rosset, Robert

    2005-09-01

    Classical aerosol schemes use either a sectional (bin) or lognormal approach. Both approaches have particular capabilities and interests: the sectional approach is able to describe every kind of distribution, whereas the lognormal one makes assumption of the distribution form with a fewer number of explicit variables. For this last reason we developed a three-moment lognormal aerosol scheme named ORILAM to be coupled in three-dimensional mesoscale or CTM models. This paper presents the concept and hypothesis of a range of aerosol processes such as nucleation, coagulation, condensation, sedimentation, and dry deposition. One particular interest of ORILAM is to keep explicit the aerosol composition and distribution (mass of each constituent, mean radius, and standard deviation of the distribution are explicit) using the prediction of three-moment (m0, m3, and m6). The new model was evaluated by comparing simulations to measurements from the Escompte campaign and to a previously published aerosol model. The numerical cost of the lognormal mode is lower than two bins of the sectional one.

  17. Comparison of mesoscale model and tower measurements of surface fluxes during Winter Icing and Storms Program/Atmospheric Radiation Measurement 91

    Oncley, S.P.; Dudhia, J.

    1994-01-01

    This study is an evaluation of the ability of the Pennsylvania State University/National Center for Atmospheric Research (NCAR) mesoscale model (MM4) to determine surface fluxes to see if measured fluxes should be assimilated into model runs. Fluxes were compared from a high-resolution (5 km grid spacing) MM4 run during one day of the Winter Icing and Storms Programs/Atmospheric Radiation Measurement (WISP/ARM) experiment (over NE Colorado in winter 1991) with direct flux measurements made from a tower over a representative site by a three-dimensional sonic anemometer and fast response temperature and humidity sensors. This tower was part of the NCAR Atmosphere-Surface Turbulent Exchange Research (ASTER) facility. Also, mean values were compared to check whether any differences were due to the model parameterization or model variables

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

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

    2016-12-01

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

  19. The impact of convection in the West African monsoon region on global weather forecasts - explicit vs. parameterised convection simulations using the ICON model

    Pante, Gregor; Knippertz, Peter

    2017-04-01

    The West African monsoon is the driving element of weather and climate during summer in the Sahel region. It interacts with mesoscale convective systems (MCSs) and the African easterly jet and African easterly waves. Poor representation of convection in numerical models, particularly its organisation on the mesoscale, can result in unrealistic forecasts of the monsoon dynamics. Arguably, the parameterisation of convection is one of the main deficiencies in models over this region. Overall, this has negative impacts on forecasts over West Africa itself but may also affect remote regions, as waves originating from convective heating are badly represented. Here we investigate those remote forecast impacts based on daily initialised 10-day forecasts for July 2016 using the ICON model. One set of simulations employs the default setup of the global model with a horizontal grid spacing of 13 km. It is compared with simulations using the 2-way nesting capability of ICON. A second model domain over West Africa (the nest) with 6.5 km grid spacing is sufficient to explicitly resolve MCSs in this region. In the 2-way nested simulations, the prognostic variables of the global model are influenced by the results of the nest through relaxation. The nest with explicit convection is able to reproduce single MCSs much more realistically compared to the stand-alone global simulation with parameterised convection. Explicit convection leads to cooler temperatures in the lower troposphere (below 500 hPa) over the northern Sahel due to stronger evaporational cooling. Overall, the feedback of dynamic variables from the nest to the global model shows clear positive effects when evaluating the output of the global domain of the 2-way nesting simulation and the output of the stand-alone global model with ERA-Interim re-analyses. Averaged over the 2-way nested region, bias and root mean squared error (RMSE) of temperature, geopotential, wind and relative humidity are significantly reduced in

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

    Lee, Yongheon; Oren, Shmuel S.

    2009-01-01

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

  1. Simulation of atmospheric temperature inversions over greater cairo using the MM5 Meso-Scale atmospheric model

    Kandil, H.A.; Elhadidi, B.M.; Kader, A. A.; Moaty, A.A.; Sherif, A.O.

    2006-01-01

    Air pollution episodes have been recorded in Cairo, during the fall season, since 1999, as a result of specific meteorological conditions combined with large quantity of pollutants created by several ground-based sources. The main reason for the smog-like episodes (black clouds) is adverse weather conditions with low and variable winds, high humidity and strong temperature inversions in the few-hundred meters above the ground. The two important types of temperature inversion affecting the air pollution are surface or ground (radiation) inversion and subsidence (elevated) inversion. The surface temperature inversion is associated with a rapid decrease in the ground surface temperature with the simultaneous existence of warm air in the lower troposphere. The inversion develops at dusk and continues until the surface warms again the following day. Pollutants emitted during the night are caught under this i nversion lid. S ubsidence inversion forms when warm air masses move over colder air masses. The inversion develops with a stagnating high-pressure system (generally associated with fair weather). Under these conditions, the pressure gradient becomes progressively weaker so that winds become light. These light winds greatly reduce the horizontal transport and dispersion of pollutants. At the same time, the subsidence inversion acts as a barrier to the vertical dispersion of the pollutants. In this study, the Penn State/NCAR meso -scale model (MM5) is used to simulate the temperature inversion phenomenon over Greater Cairo region during the fall season of 2004. Accurate computations of the heat transfer at the surface are needed to capture this phenomenon. This can only be achieved by high-resolution simulations in both horizontal and vertical directions. Hence, for accurate simulation of the temperature inversion over Greater Cairo, four nested domains of resolutions of 27 km, 9 km, 3 km and 1 km, respectively, were used in the horizontal planes. Furthermore, 42

  2. Atmospheric Diabatic Heating in Different Weather States and the General Circulation

    Rossow, William B.; Zhang, Yuanchong; Tselioudis, George

    2016-01-01

    Analysis of multiple global satellite products identifies distinctive weather states of the atmosphere from the mesoscale pattern of cloud properties and quantifies the associated diabatic heating/cooling by radiative flux divergence, precipitation, and surface sensible heat flux. The results show that the forcing for the atmospheric general circulation is a very dynamic process, varying strongly at weather space-time scales, comprising relatively infrequent, strong heating events by ''stormy'' weather and more nearly continuous, weak cooling by ''fair'' weather. Such behavior undercuts the value of analyses of time-averaged energy exchanges in observations or numerical models. It is proposed that an analysis of the joint time-related variations of the global weather states and the general circulation on weather space-time scales might be used to establish useful ''feedback like'' relationships between cloud processes and the large-scale circulation.

  3. Mesoscale Connections Summer 2017

    Kippen, Karen Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Bourke, Mark Andrew M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-06-21

    Our challenge derives from the fact that in metals or explosives grains, interfaces and defects control engineering performance in ways that are neither amenable to continuum codes (which fail to rigorously describe the heterogeneities derived from microstructure) nor computationally tractable to first principles atomistic calculations. This is a region called the mesoscale, which stands at the frontier of our desire to translate fundamental science insights into confidence in aging system performance over the range of extreme conditions relevant in a nuclear weapon. For dynamic problems, the phenomena of interest can require extremely good temporal resolutions. A shock wave traveling at 1000 m/s (or 1 mm/μs) passes through a grain with a diameter of 1 micron in a nanosecond (10-9 sec). Thus, to observe the mesoscale phenomena—such as dislocations or phase transformations—as the shock passes, temporal resolution better than picoseconds (10-12 sec) may be needed. As we anticipate the science challenges over the next decade, experimental insights on material performance at the micron spatial scale with picosecond temporal resolution—at the mesoscale— are a clear challenge. This is a challenge fit for Los Alamos in partnership with our sister labs and academia. Mesoscale Connections will draw attention to our progress as we tackle the mesoscale challenge. We hope you like it and encourage suggestions of content you are interested in.

  4. Sensitivity of an Integrated Mesoscale Atmosphere and Agriculture Land Modeling System (WRF/CMAQ-EPIC) to MODIS Vegetation and Lightning Assimilation

    The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteo...

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

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

    2013-04-01

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

  6. On Verifying Currents and Other Features in the Hawaiian Islands Region Using Fully Coupled Ocean/Atmosphere Mesoscale Prediction System Compared to Global Ocean Model and Ocean Observations

    Jessen, P. G.; Chen, S.

    2014-12-01

    This poster introduces and evaluates features concerning the Hawaii, USA region using the U.S. Navy's fully Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS-OS™) coupled to the Navy Coastal Ocean Model (NCOM). It also outlines some challenges in verifying ocean currents in the open ocean. The system is evaluated using in situ ocean data and initial forcing fields from the operational global Hybrid Coordinate Ocean Model (HYCOM). Verification shows difficulties in modelling downstream currents off the Hawaiian islands (Hawaii's wake). Comparing HYCOM to NCOM current fields show some displacement of small features such as eddies. Generally, there is fair agreement from HYCOM to NCOM in salinity and temperature fields. There is good agreement in SSH fields.

  7. Intercomparison of oceanic and atmospheric forced and coupled mesoscale simulations. Part I: Surface fluxes

    Josse, P.; Caniaux, G.; Giordani, H.; Planton, S.

    1999-04-01

    A mesoscale non-hydrostatic atmospheric model has been coupled with a mesoscale oceanic model. The case study is a four-day simulation of a strong storm event observed during the SEMAPHORE experiment over a 500 × 500 km2 domain. This domain encompasses a thermohaline front associated with the Azores current. In order to analyze the effect of mesoscale coupling, three simulations are compared: the first one with the atmospheric model forced by realistic sea surface temperature analyses; the second one with the ocean model forced by atmospheric fields, derived from weather forecast re-analyses; the third one with the models being coupled. For these three simulations the surface fluxes were computed with the same bulk parametrization. All three simulations succeed well in representing the main oceanic or atmospheric features observed during the storm. Comparison of surface fields with in situ observations reveals that the winds of the fine mesh atmospheric model are more realistic than those of the weather forecast re-analyses. The low-level winds simulated with the atmospheric model in the forced and coupled simulations are appreciably stronger than the re-analyzed winds. They also generate stronger fluxes. The coupled simulation has the strongest surface heat fluxes: the difference in the net heat budget with the oceanic forced simulation reaches on average 50 Wm-2 over the simulation period. Sea surface-temperature cooling is too weak in both simulations, but is improved in the coupled run and matches better the cooling observed with drifters. The spatial distributions of sea surface-temperature cooling and surface fluxes are strongly inhomogeneous over the simulation domain. The amplitude of the flux variation is maximum in the coupled run. Moreover the weak correlation between the cooling and heat flux patterns indicates that the surface fluxes are not responsible for the whole cooling and suggests that the response of the ocean mixed layer to the atmosphere is

  8. Combined meso-scale modeling and experimental investigation of the effect of mechanical damage on the transport properties of cementitious composites

    Raghavan, Balaji; Niknezhad, Davood; Bernard, Fabrice; Kamali-Bernard, Siham

    2016-09-01

    The transport properties of cementitious composites such as concrete are important indicators of their durability, and are known to be heavily influenced by mechanical loading. In the current work, we use meso-scale hygro-mechanical modeling with a morphological 3D two phase mortar-aggregate model, in conjunction with experimentally obtained properties, to investigate the coupling between mechanical loading and damage and the permeability of the composite. The increase in permeability of a cylindrical test specimen at 28% aggregate fraction during a uniaxial displacement-controlled compression test at 85% of the peak load was measured using a gas permeameter. The mortar's mechanical behavior is assumed to follow the well-known compression damaged plasticity (CDP) model with isotropic damage, at varying thresholds, and obtained from different envelope curves. The damaged intrinsic permeability of the mortar evolves according to a logarithmic matching law with progressive loading. We fit the matching law parameters to the experimental result for the test specimen by inverse identification using our meso-scale model. We then subject a series of virtual composite specimens to quasi-static uniaxial compressive loading with varying boundary conditions to obtain the simulated damage and strain evolutions, and use the damage data and the previously identified parameters to determine the evolution of the macroscopic permeability tensor for the specimens, using a network model. We conduct a full parameter study by varying aggregate volume fraction, granulometric distribution, loading/boundary conditions and "matching law" parameters, as well as for different strain-damage thresholds and uniaxial loading envelope curves. Based on this study, we propose Avrami equation-based upper and lower bounds for the evolution of the damaged permeability of the composite.

  9. Evaluation of high-resolution forecasts with the non-hydrostaticnumerical weather prediction model Lokalmodell for urban air pollutionepisodes in Helsinki, Oslo and Valencia

    B. Fay

    2006-01-01

    Full Text Available The operational numerical weather prediction model Lokalmodell LM with 7,km horizontal resolution was evaluated for forecasting meteorological conditions during observed urban air pollution episodes. The resolution was increased to experimental 2.8 km and 1.1 km resolution by one-way interactive nesting without introducing urbanisation of physiographic parameters or parameterisations. The episodes examined are two severe winter inversion-induced episodes in Helsinki in December 1995 and Oslo in January 2003, three suspended dust episodes in spring and autumn in Helsinki and Oslo, and a late-summer photochemical episode in the Valencia area. The evaluation was basically performed against observations and radiosoundings and focused on the LM skill at forecasting the key meteorological parameters characteristic for the specific episodes. These included temperature inversions, atmospheric stability and low wind speeds for the Scandinavian episodes and the development of mesoscale recirculations in the Valencia area. LM forecasts often improved due to higher model resolution especially in mountainous areas like Oslo and Valencia where features depending on topography like temperature, wind fields and mesoscale valley circulations were better described. At coastal stations especially in Helsinki, forecast gains were due to the improved physiographic parameters (land fraction, soil type, or roughness length. The Helsinki and Oslo winter inversions with extreme nocturnal inversion strengths of 18°C were not sufficiently predicted with all LM resolutions. In Helsinki, overprediction of surface temperatures and low-level wind speeds basically led to underpredicted inversion strength. In the Oslo episode, the situation was more complex involving erroneous temperature advection and mountain-induced effects for the higher resolutions. Possible explanations include the influence of the LM treatment of snow cover, sea ice and stability-dependence of transfer

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

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

    2014-06-01

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

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

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

    2009-01-01

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

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

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

    2017-12-01

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

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

    Pedro M. M. Soares

    2013-01-01

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

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

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

    2018-02-01

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

  15. Mesoscale modeling of smoke transport over the Southeast Asian Maritime Continent: Interplay of sea breeze, trade wind, typhoon, and topography

    Wang, Jun; Ge, Cui; Yang, Zhifeng; Hyer, Edward J.; Reid, Jeffrey S.; Chew, Boon-Ning; Mahmud, Mastura; Zhang, Yongxin; Zhang, Meigen

    2013-03-01

    The online-coupled Weather Research and Forecasting model with Chemistry (WRFchem) is used to simulate the transport of smoke particles over the Southeast Asian Maritime Continent during September-October 2006. In this period, dry conditions associated with the moderate El Niño event caused the largest regional biomass burning outbreak since 1997. Smoke emission in WRFchem is specified according to the Fire Locating and Modeling of Burning Emissions (FLAMBE) database derived from Moderate Resolution Imaging Spectroradiometer (MODIS) fire products. The modeled smoke transport pathway is found to be consistent with the MODIS true color images and measured mass concentration of surface PM10 (particulate matter with diameter less than 10 μm). The interplay of sea/land breezes, typhoons and storms over the subtropical western Pacific Ocean, trade winds, and topographic effects, can be clearly seen in the model simulation. The most severe smoke events in 1-5 October 2006 are found to be associated with the meteorological responses to the typhoon Xangsane (#18) over the western subtropical Pacific Ocean, which moved smoke from Sumatra eastward in the lower troposphere (below 700 hPa), forming smoke layers mixed with and above the boundary layer clouds over Borneo. In contrast, the second largest week-long smoke transport event of 15-18 October 2006 was associated with the seasonal monsoonal transition period, during which smoke plumes were wide spread over the 5°S-5°N zone as a result of (a) the near surface divergence coupled with the 700 hPa bifurcation of wind (flowing both to the west and to the east), and (b) the near-surface southeasterly and easterly winds along the equator transporting smoke from Borneo to Sumatra and Peninsular Malaysia. Analysis of data from the Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP) shows that smoke particles in October 2006 were primarily located within 3.5 km above the surface. Smoke particles contributed roughly half

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

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

    1983-01-01

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

  17. Characterizing the Meso-scale Plasma Flows in Earth's Coupled Magnetosphere-Ionosphere-Thermosphere System

    Gabrielse, C.; Nishimura, T.; Lyons, L. R.; Gallardo-Lacourt, B.; Deng, Y.; McWilliams, K. A.; Ruohoniemi, J. M.

    2017-12-01

    NASA's Heliophysics Decadal Survey put forth several imperative, Key Science Goals. The second goal communicates the urgent need to "Determine the dynamics and coupling of Earth's magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs...over a range of spatial and temporal scales." Sun-Earth connections (called Space Weather) have strong societal impacts because extreme events can disturb radio communications and satellite operations. The field's current modeling capabilities of such Space Weather phenomena include large-scale, global responses of the Earth's upper atmosphere to various inputs from the Sun, but the meso-scale ( 50-500 km) structures that are much more dynamic and powerful in the coupled system remain uncharacterized. Their influences are thus far poorly understood. We aim to quantify such structures, particularly auroral flows and streamers, in order to create an empirical model of their size, location, speed, and orientation based on activity level (AL index), season, solar cycle (F10.7), interplanetary magnetic field (IMF) inputs, etc. We present a statistical study of meso-scale flow channels in the nightside auroral oval and polar cap using SuperDARN. These results are used to inform global models such as the Global Ionosphere Thermosphere Model (GITM) in order to evaluate the role of meso-scale disturbances on the fully coupled magnetosphere-ionosphere-thermosphere system. Measuring the ionospheric footpoint of magnetospheric fast flows, our analysis technique from the ground also provides a 2D picture of flows and their characteristics during different activity levels that spacecraft alone cannot.

  18. Mesoscale hybrid calibration artifact

    Tran, Hy D.; Claudet, Andre A.; Oliver, Andrew D.

    2010-09-07

    A mesoscale calibration artifact, also called a hybrid artifact, suitable for hybrid dimensional measurement and the method for make the artifact. The hybrid artifact has structural characteristics that make it suitable for dimensional measurement in both vision-based systems and touch-probe-based systems. The hybrid artifact employs the intersection of bulk-micromachined planes to fabricate edges that are sharp to the nanometer level and intersecting planes with crystal-lattice-defined angles.

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

    Zhenming Shi

    2015-06-01

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

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

    Stewart, A. E.

    2017-12-01

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

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

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

    2015-01-01

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

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

    Ekman, Annica

    2000-02-01

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

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

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

    2014-05-01

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

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

    Šaltytė Benth, Jūratė; Benth, Fred Espen

    2012-01-01

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

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

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

    2012-01-01

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

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

    Landman, S

    2010-09-01

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

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

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

    2012-01-01

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

  8. Numerical simulation of terrain-induced mesoscale circulation in the Chiang Mai area, Thailand

    Sathitkunarat, Surachai; Wongwises, Prungchan; Pan-Aram, Rudklao; Zhang, Meigen

    2008-11-01

    The regional atmospheric modeling system (RAMS) was applied to Chiang Mai province, a mountainous area in Thailand, to study terrain-induced mesoscale circulations. Eight cases in wet and dry seasons under different weather conditions were analyzed to show thermal and dynamic impacts on local circulations. This is the first study of RAMS in Thailand especially investigating the effect of mountainous area on the simulated meteorological data. Analysis of model results indicates that the model can reproduce major features of local circulation and diurnal variations in temperatures. For evaluating the model performance, model results were compared with observed wind speed, wind direction, and temperature monitored at a meteorological tower. Comparison shows that the modeled values are generally in good agreement with observations and that the model captured many of the observed features.

  9. Towards assimilation of InSAR data in operational weather models

    Mulder, Gert; van Leijen, Freek; Barkmeijer, Jan; de Haan, Siebren; Hanssen, Ramon

    2017-04-01

    InSAR signal delays due to the varying atmospheric refractivity are a potential data source to improve weather models [1]. Especially with the launch of the new Sentinel-1 satellites, which increases data coverage, latency and accessibility, it may become possible to operationalize the assimilation of differential integrated refractivity (DIR) values in numerical weather models. Although studies exist on comparison between InSAR data and weather models [2], the impact of assimilation of DIR values in an operational weather model has never been assessed. In this study we present different ways to assimilate DIR values in an operational weather model and show the first forecast results. There are different possibilities to assimilate InSAR-data in a weather model. For example, (i) absolute DIR values can be derived using additional GNSS zenith or slant delay values, (ii) DIR values can be converted to water vapor pressures, or (iii) water vapor pressures can be derived for different heights by combining GNSS and InSAR data. However, an increasing number of assumptions in these processing steps will increase the uncertainty in the final results. Therefore, we chose to insert the InSAR derived DIR values after minimal additional processing. In this study we use the HARMONIE model [3], which is a spectral, non-hydrostatic model with a resolution of about 2.5 km. Currently, this is the operational model in 11 European countries and based on the AROME model [4]. To assimilate the DIR values in the weather model we use a simple adjustment of the weather parameters over the full slant column to match the DIR values. This is a first step towards a more sophisticated approach based on the 3D-VAR or 4D-VAR schemes [5]. Where both assimilation schemes can correct for different weather parameters simultaneously, and 4D-VAR allow us to assimilate DIR values at the exact moment of satellite overpass instead of the start of the forecast window. The approach will be demonstrated

  10. Mesoscale Effects on Carbon Export: A Global Perspective

    Harrison, Cheryl S.; Long, Matthew C.; Lovenduski, Nicole S.; Moore, Jefferson K.

    2018-04-01

    Carbon export from the surface to the deep ocean is a primary control on global carbon budgets and is mediated by plankton that are sensitive to physical forcing. Earth system models generally do not resolve ocean mesoscale circulation (O(10-100) km), scales that strongly affect transport of nutrients and plankton. The role of mesoscale circulation in modulating export is evaluated by comparing global ocean simulations conducted at 1° and 0.1° horizontal resolution. Mesoscale resolution produces a small reduction in globally integrated export production (export production can be large (±50%), with compensating effects in different ocean basins. With mesoscale resolution, improved representation of coastal jets block off-shelf transport, leading to lower export in regions where shelf-derived nutrients fuel production. Export is further reduced in these regions by resolution of mesoscale turbulence, which restricts the spatial area of production. Maximum mixed layer depths are narrower and deeper across the Subantarctic at higher resolution, driving locally stronger nutrient entrainment and enhanced summer export production. In energetic regions with seasonal blooms, such as the Subantarctic and North Pacific, internally generated mesoscale variability drives substantial interannual variation in local export production. These results suggest that biogeochemical tracer dynamics show different sensitivities to transport biases than temperature and salinity, which should be considered in the formulation and validation of physical parameterizations. Efforts to compare estimates of export production from observations and models should account for large variability in space and time expected for regions strongly affected by mesoscale circulation.

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

    Jabar H. Yousif

    2017-07-01

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

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

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

    2016-01-01

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

  13. Dynamics of Clouds and Mesoscale Circulations over the Maritime Continent

    Jin, Y.; Wang, S.; Xian, P.; Reid, J. S.; Nachamkin, J.

    2010-12-01

    In recent decades Southeast Asia (SEA) has seen rapid economic growth as well as increased biomass burning, resulting in high air pollution levels and reduced air qual-ity. At the same time clouds often prevent accurate air-quality monitoring and analysis using satellite observations. The Seven SouthEast Asian Studies (7SEAS) field campaign currently underway over SEA provides an unprecedented opportunity to study the com-plex interplay between aerosol and clouds. 7SEAS is a comprehensive interdisciplinary atmospheric sciences program through international partnership of NASA, NRL, ONR and seven local institutions including those from Indonesia, Malaysia, the Philippines, Singapore, Taiwan, Thailand, and Vietnam. While the original goal of 7SEAS is to iso-late the impacts of aerosol particles on weather and the environment, it is recognized that better understanding of SEA meteorological conditions, especially those associated with cloud formation and evolution, is critical to the success of the campaign. In this study we attempt to gain more insight into the dynamic and physical processes associated with low level clouds and atmospheric circulation at the regional scale over SEA, using the Navy’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS® ), a regional forecast model in operation at FNMOC since 1998. This effort comprises two main components. First, multiple-years of COAMPS operational forecasts over SEA are analyzed for basic climatology of atmospheric fea-tures. Second, mesoscale circulation and cloud properties are simulated at relatively higher resolution (15-km) for selected periods in the Gulf of Tonkin and adjacent coastal areas. Simulation results are compared to MODIS cloud observations and local sound-ings obtained during 7SEAS for model verifications. Atmospheric boundary layer proc-esses are examined in relation to spatial and temporal variations of cloud fields. The cur-rent work serves as an important step toward improving our

  14. Intercomparison of oceanic and atmospheric forced and coupled mesoscale simulations Part I: Surface fluxes

    P. Josse

    1999-04-01

    Full Text Available A mesoscale non-hydrostatic atmospheric model has been coupled with a mesoscale oceanic model. The case study is a four-day simulation of a strong storm event observed during the SEMAPHORE experiment over a 500 × 500 km2 domain. This domain encompasses a thermohaline front associated with the Azores current. In order to analyze the effect of mesoscale coupling, three simulations are compared: the first one with the atmospheric model forced by realistic sea surface temperature analyses; the second one with the ocean model forced by atmospheric fields, derived from weather forecast re-analyses; the third one with the models being coupled. For these three simulations the surface fluxes were computed with the same bulk parametrization. All three simulations succeed well in representing the main oceanic or atmospheric features observed during the storm. Comparison of surface fields with in situ observations reveals that the winds of the fine mesh atmospheric model are more realistic than those of the weather forecast re-analyses. The low-level winds simulated with the atmospheric model in the forced and coupled simulations are appreciably stronger than the re-analyzed winds. They also generate stronger fluxes. The coupled simulation has the strongest surface heat fluxes: the difference in the net heat budget with the oceanic forced simulation reaches on average 50 Wm-2 over the simulation period. Sea surface-temperature cooling is too weak in both simulations, but is improved in the coupled run and matches better the cooling observed with drifters. The spatial distributions of sea surface-temperature cooling and surface fluxes are strongly inhomogeneous over the simulation domain. The amplitude of the flux variation is maximum in the coupled run. Moreover the weak correlation between the cooling and heat flux patterns indicates that the surface fluxes are not responsible for the whole cooling and suggests that the response of the ocean mixed layer

  15. Intercomparison of oceanic and atmospheric forced and coupled mesoscale simulations Part I: Surface fluxes

    H. Giordani

    Full Text Available A mesoscale non-hydrostatic atmospheric model has been coupled with a mesoscale oceanic model. The case study is a four-day simulation of a strong storm event observed during the SEMAPHORE experiment over a 500 × 500 km2 domain. This domain encompasses a thermohaline front associated with the Azores current. In order to analyze the effect of mesoscale coupling, three simulations are compared: the first one with the atmospheric model forced by realistic sea surface temperature analyses; the second one with the ocean model forced by atmospheric fields, derived from weather forecast re-analyses; the third one with the models being coupled. For these three simulations the surface fluxes were computed with the same bulk parametrization. All three simulations succeed well in representing the main oceanic or atmospheric features observed during the storm. Comparison of surface fields with in situ observations reveals that the winds of the fine mesh atmospheric model are more realistic than those of the weather forecast re-analyses. The low-level winds simulated with the atmospheric model in the forced and coupled simulations are appreciably stronger than the re-analyzed winds. They also generate stronger fluxes. The coupled simulation has the strongest surface heat fluxes: the difference in the net heat budget with the oceanic forced simulation reaches on average 50 Wm-2 over the simulation period. Sea surface-temperature cooling is too weak in both simulations, but is improved in the coupled run and matches better the cooling observed with drifters. The spatial distributions of sea surface-temperature cooling and surface fluxes are strongly inhomogeneous over the simulation domain. The amplitude of the flux variation is maximum in the coupled run. Moreover the weak correlation between the cooling and heat flux patterns indicates that the surface fluxes are not responsible for the whole cooling and suggests that the response of the ocean mixed layer

  16. The Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS)

    Hodur, Richard M; Hong, Xiaodong; Doyle, James D; Pullen, Julie; Cummings, James; Martin, Paul; Rennick, Mary Alice

    2002-01-01

    ... of the Couple Ocean/Atmosphere Mesoscale Prediction System (COAMPS). The goal of this modeling project is to gain predictive skill in simulating the ocean and atmosphere at high resolution on time-scales of hours to several days...

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

    Liu, Zedong; Wan, Xiuquan

    2018-04-01

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

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

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

    2014-12-01

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

  19. An Evaluation of Mesoscale Model Predictions of Down-Valley and Canyon Flows and Their Consequences Using Doppler Lidar Measurements During VTMX 2000

    Fast, Jerome D.; Darby, Lisa S.

    2004-01-01

    A mesoscale model, a Lagrangian particle dispersion model, and extensive Doppler lidar wind measurements during the VTMX 2000 field campaign were used to examine converging flows over the Salt Lake Valley and their effect on vertical mixing of tracers at night and during the morning transition period. The simulated wind components were transformed into radial velocities to make a direct comparison with about 1.3 million Doppler lidar data points and critically evaluate, using correlation coefficients, the spatial variations in the simulated wind fields aloft. The mesoscale model captured reasonably well the general features of the observed circulations including the daytime up-valley flow, the nighttime slope, canyon, and down-valley flows, and the convergence of the flows over the valley. When there were errors in the simulated wind fields, they were usually associated with the timing, structure, or strength of specific flows. Simulated outflows from canyons along the Wasatch Mountains propagated over the valley and converged with the down-valley flow, but the advance and retreat of these simulated flows was often out of phase with the lidar measurements. While the flow reversal during the evening transition period produced rising motions over much of the valley atmosphere in the absence of significant ambient winds, average vertical velocities became close to zero as the down-valley flow developed. Still, vertical velocities between 5 and 15 cm s-1 occurred where down-slope, canyon and down-valley flows converged and vertical velocities greater than 50 cm s-1 were produced by hydraulic jumps at the base of the canyons. The presence of strong ambient winds resulted in smaller average rising motions during the evening transition period and larger average vertical velocities after that. A fraction of the tracer released at the surface was transported up to the height of the surrounding mountains; however, higher concentrations were produced aloft for evening s

  20. Land use and topography influence in a complex terrain area: A high resolution mesoscale modelling study over the Eastern Pyrenees using the WRF model

    Jiménez-Esteve, B.; Udina, M.; Soler, M. R.; Pepin, N.; Miró, J. R.

    2018-04-01

    Different types of land use (LU) have different physical properties which can change local energy balance and hence vertical fluxes of moisture, heat and momentum. This in turn leads to changes in near-surface temperature and moisture fields. Simulating atmospheric flow over complex terrain requires accurate local-scale energy balance and therefore model grid spacing must be sufficient to represent both topography and land-use. In this study we use both the Corine Land Cover (CLC) and United States Geological Survey (USGS) land use databases for use with the Weather Research and Forecasting (WRF) model and evaluate the importance of both land-use classification and horizontal resolution in contributing to successful modelling of surface temperatures and humidities observed from a network of 39 sensors over a 9 day period in summer 2013. We examine case studies of the effects of thermal inertia and soil moisture availability at individual locations. The scale at which the LU classification is observed influences the success of the model in reproducing observed patterns of temperature and moisture. Statistical validation of model output demonstrates model sensitivity to both the choice of LU database used and the horizontal resolution. In general, results show that on average, by a) using CLC instead of USGS and/or b) increasing horizontal resolution, model performance is improved. We also show that the sensitivity to these changes in the model performance shows a daily cycle.

  1. Simulation of Wind-Driven Snow Redistribution at a High-Elevation Alpine Site Using a Meso-Scale Atmospheric Model

    Vionnet, V.; Martin, E.; Masson, V.; Guyomarc'h, G.; Naaim-Bouvet, F.; Prokop, A.; Durand, Y.; Lac, C.

    2012-12-01

    In alpine regions, blowing snow events strongly influence the temporal and spatial evolution of the snow depth distribution throughout the winter season. We recently developed a new simulation system to gain understanding on the complex processes that drive the redistribution of snow by the wind in complex terrain. This new system couples directly the detailed snow-pack model Crocus with the meso-scale atmospheric model Meso-NH. A blowing snow scheme allows Meso-NH to simulate the transport of snow particles in the atmosphere. We used the coupled system to study a blowing snow event with snowfall that occurred in February 2011 in the Grandes Rousses range (French Alps). Three nested domains at an horizontal resolution of 450, 150 and 50 m allow the model to simulate the complex 3D precipitation and wind fields around our experimental site (2720 m a.s.l.) during this 22-hour event. Wind-induced snow transport is activated over the domains of higher resolution (150 and 50 m). We firstly assessed the ability of the model to reproduce atmospheric flows at high resolution in alpine terrain using a large dataset of observations (meteorological data, vertical profile of wind speed). Simulated blowing snow fluxes are then compared with measurements from SPC and mechanical snow traps. Finally a map of snow erosion and accumulation produced by Terrestrial Laser measurements allows to evaluate the quality of the simulated snow depth redistribution.

  2. Integrated modelling of physical, chemical and biological weather

    Kurganskiy, Alexander

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

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

    Passner, Jeffrey E

    2007-01-01

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

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

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

    2012-01-01

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

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

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

    2011-01-01

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

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

    Miyauchi, T.; Machimura, T.

    2014-12-01

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

  7. Numerical simulations of island effects on airflow and weather during the summer over the island of Oahu

    Hiep Van Nguyen; Yie-Leng Chen; Francis Fujioka

    2010-01-01

    The high-resolution (1.5 km) nonhydrostatic fifth-generation Pennsylvania StateUniversity–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and an advanced land surface model (LSM) are used to study the island-induced airflow and weather for the island of Oahu, Hawaii, under summer trade wind conditions. Despite Oahu’s relatively small...

  8. Mesoscale simulation of concrete spall failure

    Knell, S.; Sauer, M.; Millon, O.; Riedel, W.

    2012-05-01

    Although intensively studied, it is still being debated which physical mechanisms are responsible for the increase of dynamic strength and fracture energy of concrete observed at high loading rates, and to what extent structural inertia forces on different scales contribute to the observation. We present a new approach for the three dimensional mesoscale modelling of dynamic damage and cracking in concrete. Concrete is approximated as a composite of spherical elastic aggregates of mm to cm size embedded in an elastic cement stone matrix. Cracking within the matrix and at aggregate interfaces in the μm range are modelled with adaptively inserted—initially rigid—cohesive interface elements. The model is applied to analyse the dynamic tensile failure observed in Hopkinson-Bar spallation experiments with strain rates up to 100/s. The influence of the key mesoscale failure parameters of strength, fracture energy and relative weakening of the ITZ on macromechanic strength, momentum and energy conservation is numerically investigated.

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

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

    2017-12-01

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

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

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

    2012-12-01

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

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

    2012-09-01

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

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

    Yokota, Kohei; Kanzaki, Yoshiki; Murakami, Takashi

    2013-09-01

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

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

    Rössler, Ole; Keller, Denise; Fischer, Andreas

    2016-04-01

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

  14. A New Scheme for the Simulation of Microscale Flow and Dispersion in Urban Areas by Coupling Large-Eddy Simulation with Mesoscale Models

    Li, Haifeng; Cui, Guixiang; Zhang, Zhaoshun

    2018-04-01

    A coupling scheme is proposed for the simulation of microscale flow and dispersion in which both the mesoscale field and small-scale turbulence are specified at the boundary of a microscale model. The small-scale turbulence is obtained individually in the inner and outer layers by the transformation of pre-computed databases, and then combined in a weighted sum. Validation of the results of a flow over a cluster of model buildings shows that the inner- and outer-layer transition height should be located in the roughness sublayer. Both the new scheme and the previous scheme are applied in the simulation of the flow over the central business district of Oklahoma City (a point source during intensive observation period 3 of the Joint Urban 2003 experimental campaign), with results showing that the wind speed is well predicted in the canopy layer. Compared with the previous scheme, the new scheme improves the prediction of the wind direction and turbulent kinetic energy (TKE) in the canopy layer. The flow field influences the scalar plume in two ways, i.e. the averaged flow field determines the advective flux and the TKE field determines the turbulent flux. Thus, the mean, root-mean-square and maximum of the concentration agree better with the observations with the new scheme. These results indicate that the new scheme is an effective means of simulating the complex flow and dispersion in urban canopies.

  15. How accurate are the weather forecasts for Bierun (southern Poland)?

    Gawor, J.

    2012-04-01

    Weather forecast accuracy has increased in recent times mainly thanks to significant development of numerical weather prediction models. Despite the improvements, the forecasts should be verified to control their quality. The evaluation of forecast accuracy can also be an interesting learning activity for students. It joins natural curiosity about everyday weather and scientific process skills: problem solving, database technologies, graph construction and graphical analysis. The examination of the weather forecasts has been taken by a group of 14-year-old students from Bierun (southern Poland). They participate in the GLOBE program to develop inquiry-based investigations of the local environment. For the atmospheric research the automatic weather station is used. The observed data were compared with corresponding forecasts produced by two numerical weather prediction models, i.e. COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) developed by Naval Research Laboratory Monterey, USA; it runs operationally at the Interdisciplinary Centre for Mathematical and Computational Modelling in Warsaw, Poland and COSMO (The Consortium for Small-scale Modelling) used by the Polish Institute of Meteorology and Water Management. The analysed data included air temperature, precipitation, wind speed, wind chill and sea level pressure. The prediction periods from 0 to 24 hours (Day 1) and from 24 to 48 hours (Day 2) were considered. The verification statistics that are commonly used in meteorology have been applied: mean error, also known as bias, for continuous data and a 2x2 contingency table to get the hit rate and false alarm ratio for a few precipitation thresholds. The results of the aforementioned activity became an interesting basis for discussion. The most important topics are: 1) to what extent can we rely on the weather forecasts? 2) How accurate are the forecasts for two considered time ranges? 3) Which precipitation threshold is the most predictable? 4) Why

  16. How biophysical interactions associated with sub- and mesoscale structures and migration behavior affect planktonic larvae of the spiny lobster in the Juan Fernández Ridge: A modeling approach

    Medel, Carolina; Parada, Carolina; Morales, Carmen E.; Pizarro, Oscar; Ernst, Billy; Conejero, Carlos

    2018-03-01

    The Juan Fernández Ridge (JFR) is a chain of topographical elevations in the eastern South Pacific (∼33-35°S, 76-81.5°W). Rich in endemic marine species, this ridge is frequently affected by the arrival of mesoscale eddies originating in the coastal upwelling zone off central-southern Chile. The impacts of these interactions on the structure and dynamics of the JFR pelagic system have, however, not been addressed yet. The present model-based study is focused on the coupled influence of mesoscale-submesoscale processes and biological behavior (i.e., diel vertical migration) on the horizontal distribution of planktonic larvae of the spiny lobster (Jasus frontalis) around the JFR waters. Two case studies were selected from a hydrodynamic Regional Ocean Modeling System to characterize mesoscale and submesoscale structures and an Individual-based model (IBM) to simulate diel vertical migration (DVM) and its impact on the horizontal distribution and the patchiness level. DVM behavior of these larvae has not been clearly characterized, therefore, three types of vertical mechanisms were assessed on the IBM: (1) no migration (LG), (2) a short migration (0-50 m depth, DVM1), and (3) a long migration (10-200 m depth, DVM2). The influence of physical properties (eddy kinetic energy, stretching deformation and divergence) on larval aggregation within meso and submesoscale features was quantified. The patchiness index assessed for mesoscale and submesoscale structures showed higher values in the mesoscale than in the submesoscale. However, submesoscale structures revealed a higher accumulation of particles by unit of area. Both vertical migration mechanisms produced larger patchiness indices compared to the no migration experiment. DVM2 was the one that showed by far the largest aggregation of almost all the aggregation zones. Larval concentrations were highest in the submesoscale structures; these zones were characterized by low eddy kinetic energy, negative stretching

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

    Butgereit, L

    2014-05-01

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

  18. Numerical simulation and decomposition of kinetic energy in the Central Mediterranean: insight on mesoscale circulation and energy conversion

    R. Sorgente

    2011-08-01

    Full Text Available The spatial and temporal variability of eddy and mean kinetic energy of the Central Mediterranean region has been investigated, from January 2008 to December 2010, by mean of a numerical simulation mainly to quantify the mesoscale dynamics and their relationships with physical forcing. In order to understand the energy redistribution processes, the baroclinic energy conversion has been analysed, suggesting hypotheses about the drivers of the mesoscale activity in this area. The ocean model used is based on the Princeton Ocean Model implemented at 1/32° horizontal resolution. Surface momentum and buoyancy fluxes are interactively computed by mean of standard bulk formulae using predicted model Sea Surface Temperature and atmospheric variables provided by the European Centre for Medium Range Weather Forecast operational analyses. At its lateral boundaries the model is one-way nested within the Mediterranean Forecasting System operational products.

    The model domain has been subdivided in four sub-regions: Sardinia channel and southern Tyrrhenian Sea, Sicily channel, eastern Tunisian shelf and Libyan Sea. Temporal evolution of eddy and mean kinetic energy has been analysed, on each of the four sub-regions, showing different behaviours. On annual scales and within the first 5 m depth, the eddy kinetic energy represents approximately the 60 % of the total kinetic energy over the whole domain, confirming the strong mesoscale nature of the surface current flows in this area. The analyses show that the model well reproduces the path and the temporal behaviour of the main known sub-basin circulation features. New mesoscale structures have been also identified, from numerical results and direct observations, for the first time as the Pantelleria Vortex and the Medina Gyre.

    The classical kinetic energy decomposition (eddy and mean allowed to depict and to quantify the permanent and fluctuating parts of the circulation in the region, and

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

    Hans Schermeyer

    2015-12-01

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

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

    Pardowitz, Tobias

    2018-06-01

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

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

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

    2010-01-01

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

  2. Evaluation of high intensity precipitation from 16 Regional climate models over a meso-scale catchment in the Midlands Regions of England

    Wetterhall, F.; He, Y.; Cloke, H.; Pappenberger, F.; Freer, J.; Wilson, M.; McGregor, G.

    2009-04-01

    Local flooding events are often triggered by high-intensity rain-fall events, and it is important that these can be correctly modelled by Regional Climate Models (RCMs) if the results are to be used in climate impact assessment. In this study, daily precipitation from 16 RCMs was compared with observations over a meso-scale catchment in the Midlands Region of England. The RCM data was provided from the European research project ENSEMBLES and the precipitation data from the UK MetOffice. The RCMs were all driven by reanalysis data from the ERA40 dataset over the time period 1961-2000. The ENSEMBLES data is on the spatial scale of 25 x 25 km and it was disaggregated onto a 5 x 5 km grid over the catchment and compared with interpolated observational data with the same resolution. The mean precipitation was generally underestimated by the ENSEMBLES data, and the maximum and persistence of high intensity rainfall was even more underestimated. The inter-annual variability was not fully captured by the RCMs, and there was a systematic underestimation of precipitation during the autumn months. The spatial pattern in the modelled precipitation data was too smooth in comparison with the observed data, especially in the high altitudes in the western part of the catchment where the high precipitation usually occurs. The RCM outputs cannot reproduce the current high intensity precipitation events that are needed to sufficiently model extreme flood events. The results point out the discrepancy between climate model output and the high intensity precipitation input needs for hydrological impact modelling.

  3. Application and comparison of the SCS-CN-based rainfall-runoff model in meso-scale watershed and field scale

    Luo, L.; Wang, Z.

    2010-12-01

    Soil Conservation Service Curve Number (SCS-CN) based hydrologic model, has widely been used for agricultural watersheds in recent years. However, there will be relative error when applying it due to differentiation of geographical and climatological conditions. This paper introduces a more adaptable and propagable model based on the modified SCS-CN method, which specializes into two different scale cases of research regions. Combining the typical conditions of the Zhanghe irrigation district in southern part of China, such as hydrometeorologic conditions and surface conditions, SCS-CN based models were established. The Xinbu-Qiao River basin (area =1207 km2) and the Tuanlin runoff test area (area =2.87 km2)were taken as the study areas of basin scale and field scale in Zhanghe irrigation district. Applications were extended from ordinary meso-scale watershed to field scale in Zhanghe paddy field-dominated irrigated . Based on actual measurement data of land use, soil classification, hydrology and meteorology, quantitative evaluation and modifications for two coefficients, i.e. preceding loss and runoff curve, were proposed with corresponding models, table of CN values for different landuse and AMC(antecedent moisture condition) grading standard fitting for research cases were proposed. The simulation precision was increased by putting forward a 12h unit hydrograph of the field area, and 12h unit hydrograph were simplified. Comparison between different scales show that it’s more effectively to use SCS-CN model on field scale after parameters calibrated in basin scale These results can help discovering the rainfall-runoff rule in the district. Differences of established SCS-CN model's parameters between the two study regions are also considered. Varied forms of landuse and impacts of human activities were the important factors which can impact the rainfall-runoff relations in Zhanghe irrigation district.

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

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

    2000-02-01

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

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

    Jing Lu

    2014-11-01

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

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

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

    2014-12-01

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

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

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

  8. Crucial role of dynamic linker histone binding and divalent ions for DNA accessibility and gene regulation revealed by mesoscale modeling of oligonucleosomes

    Collepardo-Guevara, Rosana; Schlick, Tamar

    2012-01-01

    Monte Carlo simulations of a mesoscale model of oligonucleosomes are analyzed to examine the role of dynamic-linker histone (LH) binding/unbinding in high monovalent salt with divalent ions, and to further interpret noted chromatin fiber softening by dynamic LH in monovalent salt conditions. We find that divalent ions produce a fiber stiffening effect that competes with, but does not overshadow, the dramatic softening triggered by dynamic-LH behavior. Indeed, we find that in typical in vivo conditions, dynamic-LH binding/unbinding reduces fiber stiffening dramatically (by a factor of almost 5, as measured by the elasticity modulus) compared with rigidly fixed LH, and also the force needed to initiate chromatin unfolding, making it consistent with those of molecular motors. Our data also show that, during unfolding, divalent ions together with LHs induce linker-DNA bending and DNA–DNA repulsion screening, which guarantee formation of heteromorphic superbeads-on-a-string structures that combine regions of loose and compact fiber independently of the characteristics of the LH–core bond. These structures might be important for gene regulation as they expose regions of the DNA selectively. Dynamic control of LH binding/unbinding, either globally or locally, in the presence of divalent ions, might constitute a mechanism for regulation of gene expression. PMID:22790986

  9. Weather forecast

    Courtier, P

    1994-02-07

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

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

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

    2017-12-01

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

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

    Ośródka Katarzyna

    2014-09-01

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

  12. Biogeography of seabirds within a high-latitude ecosystem: Use of a data-assimilative ocean model to assess impacts of mesoscale oceanography

    Santora, Jarrod A.; Eisner, Lisa B.; Kuletz, Kathy J.; Ladd, Carol; Renner, Martin; Hunt, George L., Jr.

    2018-02-01

    We assessed the biogeography of seabirds within the Bering Sea Large Marine Ecosystem (LME), a highly productive and extensive continental shelf system that supports important fishing grounds. Our objective was to investigate how physical ocean conditions impact distribution of seabirds along latitudinal gradients. We tested the hypothesis that seabird biogeographic patterns reflect differences in ocean conditions relating to the boundary between northern and southern shelf ecosystems. We used a grid-based approach to develop spatial means (1975-2014) of summertime seabird species' abundance, species' richness, and a multivariate seabird assemblage index to examine species composition. Seabird indices were linked to ocean conditions derived from a data-assimilative oceanographic model to quantify relationships between physics (e.g., temperature, salinity, and current velocity), bathymetry and seabirds along latitudinal gradients. Species assemblages reflected two main sources of variation, a mode for elevated richness and abundance, and a mode related to partitioning of inner/middle shelf species from outer shelf-slope species. Overall, species richness and abundance increased markedly at higher latitudes. We found that latitudinal changes in species assemblages, richness and abundance indicates a major shift around 59-60°N within inner and middle shelf regions, but not in the outer shelf. Within the middle shelf, latitudinal shifts in seabird assemblages strongly related to hydrographic structure, as opposed to the inner and outer shelf waters. As expected, elevated species richness and abundance was associated with major breeding colonies and within important coastal foraging areas. Our study also indicates that seabird observations supported the conclusion that the oceanographic model captured mesoscale variability of ocean conditions important for understanding seabird distributions and represents an important step for evaluating modeling and empirical studies

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

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

    2013-01-01

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

  14. Mesoscale modeling of the water vapor cycle at Mawrth Vallis: a Mars2020 and ExoMars exploration rovers high-priority landing site

    Pla-García, Jorge

    2017-04-01

    Introduction: The Mars Regional Atmospheric Modeling System (MRAMS) was used to predict meteorological conditions that are likely to be encountered by the Mars 2020 (NASA) Rover at several of their respective proposed landing sites during entry, descent, and landing at Ls5 [1] and by the ExoMars (ESA) Rover at one of the final landing sites. MRAMS is ideally suited for this type of investigation; the model is explicitly designed to simu-late Mars' atmospheric circulations at the mesoscale and smaller with realistic, high-resolution surface proper-ties [2, 3]. One of the sights studied for both rovers was Mawrth Vallis (MV), an ancient water outflow channel with light colored clay-rich rocks in the mid-latitude north hemisphere (Oxia Palus quadrangle). MV is the northernmost of the Mars2020 and ExoMars landing sites and the closest to the northern polar cap water source. The primary source of water vapor to the atmosphere is the northern polar cap during the northern summer. In order to highlight MV habitability implications, additional numerical experiments at Ls90, 140 and 180, highest column abundance of water vapor is found over MV [4], were performed to study how the atmospheric circulation connects MV with the polar water source. Once the winter CO2 retreats, the underlying polar water ice is exposed and begins to sublimate. The water is transported equatorward where it is manifested in the tropical aphelion cloud belt. If transport is assumed to be the result of the summer Hadley Cell, then the polar water is carried aloft in the northern high latitude rising branch before moving equatorward and eventually toward the southern high latitudes. Thus, the mean meridional summer circulation precludes a direct water vapor connection between MV and the polar source. Around the equinoxes (Ls0 and Ls180), there is a brief transition period where the rising branch quickly crosses from one hemisphere into the other as it migrates to its more typical solstitial location

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

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

    2017-11-01

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

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

    F. Garavaglia

    2010-06-01

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

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

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

  17. Effect of Mesoscale and Multiscale Modeling on the Performance of Kevlar Woven Fabric Subjected to Ballistic Impact: A Numerical Study

    Jia, Xin; Huang, Zhengxiang; Zu, Xudong; Gu, Xiaohui; Xiao, Qiangqiang

    2013-12-01

    In this study, an optimal finite element model of Kevlar woven fabric that is more computational efficient compared with existing models was developed to simulate ballistic impact onto fabric. Kevlar woven fabric was modeled to yarn level architecture by using the hybrid elements analysis (HEA), which uses solid elements in modeling the yarns at the impact region and uses shell elements in modeling the yarns away from the impact region. Three HEA configurations were constructed, in which the solid element region was set as about one, two, and three times that of the projectile's diameter with impact velocities of 30 m/s (non-perforation case) and 200 m/s (perforation case) to determine the optimal ratio between the solid element region and the shell element region. To further reduce computational time and to maintain the necessary accuracy, three multiscale models were presented also. These multiscale models combine the local region with the yarn level architecture by using the HEA approach and the global region with homogenous level architecture. The effect of the varying ratios of the local and global area on the ballistic performance of fabric was discussed. The deformation and damage mechanisms of fabric were analyzed and compared among numerical models. Simulation results indicate that the multiscale model based on HEA accurately reproduces the baseline results and obviously decreases computational time.

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

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

    2009-12-01

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

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

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

    2017-06-01

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

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

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

    2012-01-01

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

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

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

    2012-01-01

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

  2. Online coupled regional meteorology chemistry models in Europe : Current status and prospects

    Baklanov, A.; Schlünzen, K.; Suppan, P.; Baldasano, J.; Brunner, D.; Aksoyoglu, S.; Carmichael, G.; Douros, J.; Flemming, J.; Forkel, R.; Galmarini, S.; Gauss, M.; Grell, G.; Hirtl, M.; Joffre, S.; Jorba, O.; Kaas, E.; Kaasik, M.; Kallos, G.; Kong, X.; Korsholm, U.; Kurganskiy, A.; Kushta, J.; Lohmann, U.; Mahura, A.; Manders-Groot, A.; Maurizi, A.; Moussiopoulos, N.; Rao, S.T.; Savage, N.; Seigneur, C.; Sokhi, R.S.; Solazzo, E.; Solomos, S.; Sørensen, B.; Tsegas, G.; Vignati, E.; Vogel, B.; Zhang, Y.

    2014-01-01

    Online coupled mesoscale meteorology atmospheric chemistry models have undergone a rapid evolution in recent years. Although mainly developed by the air quality modelling community, these models are also of interest for numerical weather prediction and regional climate modelling as they can consider

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

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

    2013-01-01

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

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

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

    1999-03-01

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

  5. Laser guidance of mesoscale particles

    Underdown, Frank Hartman, Jr.

    Mesoscale particles are guided and trapped in hollow optical fibers using radiation pressure forces. Laser light from a 0.4W, 780nm diode laser is guided in a low- loss fiber mode and used to generate the guidance forces. Laser scattering and absorption forces propels particles along the fiber and polarization gradient forces attract them to the fiber's axial center. Using two counter propagating laser beams, inside the fiber, particles can be trapped in three dimensions. Measuring the spring constant of the trap gives the gradient force. This dissertation describes Rayleigh and Mie scattering models for calculating guidance forces. Calculated forces as a function of particle size and composition (i.e. dielectric, semiconductor, and metals) will be presented. For example, under typical experimental conditions 100nm Au particles are guided by a 2 × 10-14 N propulsive force in a water filled fiber. In comparison, the measured force, obtained from the particle's velocity and Stokes' law, is 7.98 × 10-14 N.

  6. Statistical Analysis of Model Data for Operational Space Launch Weather Support at Kennedy Space Center and Cape Canaveral Air Force Station

    Bauman, William H., III

    2010-01-01

    The 12-km resolution North American Mesoscale (NAM) model (MesoNAM) is used by the 45th Weather Squadron (45 WS) Launch Weather Officers at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to support space launch weather operations. The 45 WS tasked the Applied Meteorology Unit to conduct an objective statistics-based analysis of MesoNAM output compared to wind tower mesonet observations and then develop a an operational tool to display the results. The National Centers for Environmental Prediction began running the current version of the MesoNAM in mid-August 2006. The period of record for the dataset was 1 September 2006 - 31 January 2010. The AMU evaluated MesoNAM hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The MesoNAM forecast winds, temperature and dew point were compared to the observed values of these parameters from the sensors in the KSC/CCAFS wind tower network. The data sets were stratified by model initialization time, month and onshore/offshore flow for each wind tower. Statistics computed included bias (mean difference), standard deviation of the bias, root mean square error (RMSE) and a hypothesis test for bias = O. Twelve wind towers located in close proximity to key launch complexes were used for the statistical analysis with the sensors on the towers positioned at varying heights to include 6 ft, 30 ft, 54 ft, 60 ft, 90 ft, 162 ft, 204 ft and 230 ft depending on the launch vehicle and associated weather launch commit criteria being evaluated. These twelve wind towers support activities for the Space Shuttle (launch and landing), Delta IV, Atlas V and Falcon 9 launch vehicles. For all twelve towers, the results indicate a diurnal signal in the bias of temperature (T) and weaker but discernable diurnal signal in the bias of dewpoint temperature (T(sub d)) in the MesoNAM forecasts. Also, the standard deviation of the bias and RMSE of T, T(sub d), wind speed and wind

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

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

    1978-03-01

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

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

    Willman, Mark; Jedicke, Robert

    2011-01-01

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

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

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

    1997-12-31

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

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

    Miller, Reid; Golab, Lukasz; Rosenberg, Catherine

    2017-01-01

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

  11. NORSEWIND – Mesoscale model derived Wind Atlases for the Irish Sea, the North Sea and the Baltic Sea

    Berge, Erik; Hasager, Charlotte Bay; Bredesen, Rolv Erlend

    2013-01-01

    estimate a random uncertainty of ±4.0 % and a bias of -6.4 % which is higher than for the average annual wind speed. It is emphasized that the amount of validation data is small and considerable spatial variability of the uncertainty may be expected. For example, near coastal zones model errors could...

  12. Sensitivity of an Integrated Mesoscale Atmosphere and Agriculture Land Modeling System (WRF/CMAQ-EPIC) to MODIS Vegetation and Lightning Assimilation

    Ran, L.; Cooter, E. J.; Gilliam, R. C.; Foroutan, H.; Kang, D.; Appel, W.; Wong, D. C.; Pleim, J. E.; Benson, V.; Pouliot, G.

    2017-12-01

    The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteorology, climate, and chemical transport. The Environmental Policy Integrated Climate (EPIC) is a cropping model which has long been used in a range of applications related to soil erosion, crop productivity, climate change, and water quality around the world. We have integrated WRF/CMAQ with EPIC using the Fertilizer Emission Scenario Tool for CMAQ (FEST-C) to estimate daily soil N information with fertilization for CMAQ bi-directional ammonia flux modeling. Driven by the weather and N deposition from WRF/CMAQ, FEST-C EPIC simulations are conducted on 22 different agricultural production systems ranging from managed grass lands (e.g. hay and alfalfa) to crop lands (e.g. corn grain and soybean) with rainfed and irrigated information across any defined conterminous United States (U.S.) CMAQ domain and grid resolution. In recent years, this integrated system has been enhanced and applied in many different air quality and ecosystem assessment projects related to land-water-atmosphere interactions. These enhancements have advanced this system to become a valuable tool for integrated assessments of air, land and water quality in light of social drivers and human and ecological outcomes. This presentation will focus on evaluating the sensitivity of precipitation and N deposition in the integrated system to MODIS vegetation input and lightning assimilation and their impacts on agricultural production and fertilization. We will describe the integrated modeling system and evaluate simulated precipitation and N deposition along with other weather information (e.g. temperature, humidity) for 2011 over the conterminous U.S. at 12 km grids from a coupled WRF/CMAQ with MODIS and lightning assimilation

  13. Land surface sensitivity of mesoscale convective systems

    Tournay, Robert C.

    Mesoscale convective systems (MCSs) are important contributors to the hydrologic cycle in many regions of the world as well as major sources of severe weather. MCSs continue to challenge forecasters and researchers alike, arising from difficulties in understanding system initiation, propagation, and demise. One distinct type of MCS is that formed from individual convective cells initiated primarily by daytime heating over high terrain. This work is aimed at improving our understanding of the land surface sensitivity of this class of MCS in the contiguous United States. First, a climatology of mesoscale convective systems originating in the Rocky Mountains and adjacent high plains from Wyoming southward to New Mexico is developed through a combination of objective and subjective methods. This class of MCS is most important, in terms of total warm season precipitation, in the 500 to 1300m elevations of the Great Plains (GP) to the east in eastern Colorado to central Nebraska and northwest Kansas. Examining MCSs by longevity, short lasting MCSs (15 hrs) reveals that longer lasting systems tend to form further south and have a longer track with a more southerly track. The environment into which the MCS is moving showed differences across commonly used variables in convection forecasting, with some variables showing more favorable conditions throughout (convective inhibition, 0-6 km shear and 250 hPa wind speed) ahead of longer lasting MCSs. Other variables, such as convective available potential energy, showed improving conditions through time for longer lasting MCSs. Some variables showed no difference across longevity of MCS (precipitable water and large-scale vertical motion). From subsets of this MCS climatology, three regions of origin were chosen based on the presence of ridgelines extending eastward from the Rocky Mountains known to be foci for convection initiation and subsequent MCS formation: Southern Wyoming (Cheyenne Ridge), Colorado (Palmer divide) and

  14. Spectral structure of mesoscale winds over the water

    Larsén, Xiaoli Guo; Vincent, Claire Louise; Larsen, Søren Ejling

    2013-01-01

    to describe the spectral slope transition as well as the limit for application of the Taylor hypothesis. The stability parameter calculated from point measurements, the bulk Richardson number, is found insufficient to represent the various atmospheric structures that have their own spectral behaviours under...... spectra show universal characteristics, in agreement with the findings in literature, including the energy amplitude and the −5/3 spectral slope in the mesoscale range transitioning to a slope of −3 for synoptic and planetary scales. The integral time-scale of the local weather is found to be useful...... different stability conditions, such as open cells and gravity waves. For stationary conditions, the mesoscale turbulence is found to bear some characteristics of two-dimensional isotropy, including (1) very minor vertical variation of spectra; (2) similar spectral behaviour for the along- and across...

  15. Acoustic Characterization of Mesoscale Objects

    Chinn, D; Huber, R; Chambers, D; Cole, G; Balogun, O; Spicer, J; Murray, T

    2007-03-13

    This report describes the science and engineering performed to provide state-of-the-art acoustic capabilities for nondestructively characterizing mesoscale (millimeter-sized) objects--allowing micrometer resolution over the objects entire volume. Materials and structures used in mesoscale objects necessitate the use of (1) GHz acoustic frequencies and (2) non-contacting laser generation and detection of acoustic waves. This effort demonstrated that acoustic methods at gigahertz frequencies have the necessary penetration depth and spatial resolution to effectively detect density discontinuities, gaps, and delaminations. A prototype laser-based ultrasonic system was designed and built. The system uses a micro-chip laser for excitation of broadband ultrasonic waves with frequency components reaching 1.0 GHz, and a path-stabilized Michelson interferometer for detection. The proof-of-concept for mesoscale characterization is demonstrated by imaging a micro-fabricated etched pattern in a 70 {micro}m thick silicon wafer.

  16. Mesoscale model simulation of low level equatorial winds over Borneo during the haze episode of September 1997

    Mahmud, Mastura

    2009-08-01

    The large-scale vegetation fires instigated by the local farmers during the dry period of the major El Niño event in 1997 can be considered as one of the worst environmental disasters that have occurred in southeast Asia in recent history. This study investigated the local meteorology characteristics of an equatorial environment within a domain that includes the northwestern part of Borneo from the 17 to 27 September 1997 during the height of the haze episode by utilizing a limited area three-dimensional meteorological and dispersion model, The Air Pollution Model (TAPM). Daily land and sea breeze conditions near the northwestern coast of Borneo in the state of Sarawak, Malaysia were predicted with moderate success by the index of agreement of less than one between the observed and simulated values for wind speed and a slight overprediction of 2.3 of the skill indicator that evaluates the standard deviation to the observed values. The innermost domain of study comprises an area of 24,193 km2, from approximately 109°E to 111°E, and from 1°N to 2.3°N, which includes a part of the South China Sea. Tracer analysis of air particles that were sourced in the state of Sarawak on the island of Borneo verified the existence of the landward and shoreward movements of the air during the simulation of the low level wind field. Polluted air particles were transported seawards during night-time, and landwards during daytime, highlighting the recirculation features of aged and newer air particles during the length of eleven days throughout the model simulation. Near calm conditions at low levels were simulated by the trajectory analysis from midnight to mid-day on the 22 of September 1997. Low-level turbulence within the planetary boundary layer in terms of the total kinetic energy was weak, congruent with the weak strength of low level winds that reduced the ability of the air to transport the pollutants. Statistical evaluation showed that parameters such as the systematic

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

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

    2011-12-01

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

  18. Sensitivity Studies on the Influence of Aerosols on Cloud and Precipitation Development Using WRF Mesoscale Model Simulations

    Thompson, G.; Eidhammer, T.; Rasmussen, R.

    2011-12-01

    Using the WRF model in simulations of shallow and deep precipitating cloud systems, we investigated the sensitivity to aerosols initiating as cloud condensation and ice nuclei. A global climatological dataset of sulfates, sea salts, and dust was used as input for a control experiment. Sensitivity experiments with significantly more polluted conditions were conducted to analyze the resulting impacts to cloud and precipitation formation. Simulations were performed using the WRF model with explicit treatment of aerosols added to the Thompson et al (2008) bulk microphysics scheme. The modified scheme achieves droplet formation using pre-tabulated CCN activation tables provided by a parcel model. The ice nucleation is parameterized as a function of dust aerosols as well as homogeneous freezing of deliquesced aerosols. The basic processes of aerosol activation and removal by wet scavenging are considered, but aerosol characteristic size or hygroscopicity does not change due to evaporating droplets. In other words, aerosol processing was ignored. Unique aspects of this study include the usage of one to four kilometer grid spacings and the direct parameterization of ice nucleation from aerosols rather than typical temperature and/or supersaturation relationships alone. Initial results from simulations of a deep winter cloud system and its interaction with significant orography show contrasting sensitivities in regions of warm rain versus mixed liquid and ice conditions. The classical view of higher precipitation amounts in relatively clean maritime clouds with fewer but larger droplets is confirmed for regions dominated by the warm-rain process. However, due to complex interactions with the ice phase and snow riming, the simulations revealed the reverse situation in high terrain areas dominated by snow reaching the surface. Results of other cloud systems will be summarized at the conference.

  19. Comparison of Hourly Solar Radiation from a Ground–Based Station, Remote Sensing and Weather Forecast Models at a Coastal Site of South Italy (Lamezia Terme)

    Feudo, Teresa Lo; Avolio, Elenio; Gullì, Daniel

    2015-01-01

    The solar radiation is a critical input parameter when working with solar energy and radiation dependent surface processes. In this study, we present preliminary results from an inter-comparison between hourly values from a pyranometer, MSG-SEVIRI sensor and two meso-scale models, WRF and RAMS, i...

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

    Hashino, Tempei

    2007-05-01

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

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

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

    2017-12-01

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

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

    Drusch, M.

    2006-12-01

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

  3. Improved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS)

    Jing, Miao; Heße, Falk; Kumar, Rohini; Wang, Wenqing; Fischer, Thomas; Walther, Marc; Zink, Matthias; Zech, Alraune; Samaniego, Luis; Kolditz, Olaf; Attinger, Sabine

    2018-06-01

    Most large-scale hydrologic models fall short in reproducing groundwater head dynamics and simulating transport process due to their oversimplified representation of groundwater flow. In this study, we aim to extend the applicability of the mesoscale Hydrologic Model (mHM v5.7) to subsurface hydrology by coupling it with the porous media simulator OpenGeoSys (OGS). The two models are one-way coupled through model interfaces GIS2FEM and RIV2FEM, by which the grid-based fluxes of groundwater recharge and the river-groundwater exchange generated by mHM are converted to fixed-flux boundary conditions of the groundwater model OGS. Specifically, the grid-based vertical reservoirs in mHM are completely preserved for the estimation of land-surface fluxes, while OGS acts as a plug-in to the original mHM modeling framework for groundwater flow and transport modeling. The applicability of the coupled model (mHM-OGS v1.0) is evaluated by a case study in the central European mesoscale river basin - Nägelstedt. Different time steps, i.e., daily in mHM and monthly in OGS, are used to account for fast surface flow and slow groundwater flow. Model calibration is conducted following a two-step procedure using discharge for mHM and long-term mean of groundwater head measurements for OGS. Based on the model summary statistics, namely the Nash-Sutcliffe model efficiency (NSE), the mean absolute error (MAE), and the interquartile range error (QRE), the coupled model is able to satisfactorily represent the dynamics of discharge and groundwater heads at several locations across the study basin. Our exemplary calculations show that the one-way coupled model can take advantage of the spatially explicit modeling capabilities of surface and groundwater hydrologic models and provide an adequate representation of the spatiotemporal behaviors of groundwater storage and heads, thus making it a valuable tool for addressing water resources and management problems.

  4. A cloud chemistry module for the 3-D cloud-resolving mesoscale model Meso-NH with application to idealized cases

    M. Leriche

    2013-08-01

    Full Text Available A complete chemical module has been developed for use in the Meso-NH three-dimensional cloud resolving mesoscale model. This module includes gaseous- and aqueous-phase chemical reactions that are analysed by a pre-processor generating the Fortran90 code automatically. The kinetic solver is based on a Rosenbrock algorithm, which is robust and accurate for integrating stiff systems and especially multiphase chemistry. The exchange of chemical species between the gas phase and cloud droplets and raindrops is computed kinetically by mass transfers considering non-equilibrium between the gas- and the condensed phases. Microphysical transfers of chemical species are considered for the various cloud microphysics schemes available, which are based on one-moment or two-moment schemes. The pH of the droplets and of the raindrops is diagnosed separately as the root of a high order polynomial equation. The chemical concentrations in the ice phase are modelled in a single phase encompassing the two categories of precipitating ice particles (snow and graupel of the microphysical scheme. The only process transferring chemical species in ice is retention during freezing or riming of liquid hydrometeors. Three idealized simulations are reported, which highlight the sensitivity of scavenging efficiency to the choice of the microphysical scheme and the retention coefficient in the ice phase. A two-dimensional warm, shallow convection case is used to compare the impact of the microphysical schemes on the temporal evolution and rates of acid precipitation. Acid wet deposition rates are shown to be overestimated when a one-moment microphysics scheme is used compared to a two-moment scheme. The difference is induced by a better prediction of raindrop radius and raindrop number concentration in the latter scheme. A two-dimensional mixed-phase squall line and a three-dimensional mixed-phase supercell were simulated to test the sensitivity of cloud vertical transport to

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

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen; Plósz, Benedek Gy

    2014-10-15

    Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D) SST model structures and parameters. We identify the critical sources of uncertainty in WWTP models through global sensitivity analysis (GSA) using the Benchmark simulation model No. 1 in combination with first- and second-order 1-D SST models. The results obtained illustrate that the contribution of settling parameters to the total variance of the key WWTP process outputs significantly depends on the influent flow and settling conditions. The magnitude of the impact is found to vary, depending on which type of 1-D SST model is used. Therefore, we identify and recommend potential parameter subsets for WWTP model calibration, and propose optimal choice of 1-D SST models under different flow and settling boundary conditions. Additionally, the hydraulic parameters in the second-order SST model are found significant under dynamic wet-weather flow conditions. These results highlight the importance of developing a more mechanistic based flow-dependent hydraulic sub-model in second-order 1-D SST models in the future. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

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

    2014-01-01

    Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks...... (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D...... of settling parameters to the total variance of the key WWTP process outputs significantly depends on the influent flow and settling conditions. The magnitude of the impact is found to vary, depending on which type of 1-D SST model is used. Therefore, we identify and recommend potential parameter subsets...

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

    Xiaonan Cai

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

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

    Jin, Jiming; Wen, Lijuan

    2012-05-01

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

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

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

    2009-01-01

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

  10. Recipes for correcting the impact of effective mesoscale resolution on the estimation of extreme winds

    Larsén, Xiaoli Guo; Ott, Søren; Badger, Jake

    2012-01-01

    Extreme winds derived from simulations using mesoscale models are underestimated due to the effective spatial and temporal resolutions. This is reflected in the spectral domain as an energy deficit in the mesoscale range. The energy deficit implies smaller spectral moments and thus underestimatio...

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

    Orth, Rene; Dutra, Emanuel; Pappenberger, Florian

    2016-04-01

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

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

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

    2017-12-01

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

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

    Petritsch, Richard; Pietsch, Stephan A.

    2010-05-01

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

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

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

    2015-12-01

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

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

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

    2017-10-01

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

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

    M. Palme

    2017-10-01

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

  17. Web-based modelling of energy, water and matter fluxes to support decision making in mesoscale catchments??the integrative perspective of GLOWA-Danube

    Ludwig, R.; Mauser, W.; Niemeyer, S.; Colgan, A.; Stolz, R.; Escher-Vetter, H.; Kuhn, M.; Reichstein, M.; Tenhunen, J.; Kraus, A.; Ludwig, M.; Barth, M.; Hennicker, R.

    The GLOWA-initiative (Global Change of the water cycle), funded by the German Ministry of Research and Education (BMBF), has been established to address the manifold consequences of Global Change on regional water resources in a variety of catchment areas with different natural and cultural characteristics. Within this framework, the GLOWA-Danube project is dealing with the Upper Danube watershed as a representative mesoscale test site (∼75.000 km 2) for mountain-foreland regions in the temperate mid-latitudes. The principle objective is to identify, examine and develop new techniques of coupled distributed modelling for the integration of natural and socio-economic sciences. The transdisciplinary research in GLOWA-Danube develops an integrated decision support system, called DANUBIA, to investigate the sustainability of future water use. GLOWA-Danube, which is scheduled for a total run-time of eight years to operationally implement and establish DANUBIA, comprises a university-based network of experts with water-related competence in the fields of engineering, natural and social sciences. Co-operation with a network of stakeholders in water resources management of the Upper Danube catchment ensures that practical issues and future problems in the water sector of the region can be addressed. In order to synthesize a common understanding between the project partners, a standardized notation of parameters and functions and a platform-independent structure of computational methods and interfaces has been established, by making use of the unified modelling language, an industry standard for the structuring and co-ordination of large projects in software development [Booch et al., The Unified Modelling Language User Guide, Addison-Wesley, Reading, 1999]. DANUBIA is object-oriented, spatially distributed and raster-based at its core. It applies the concept of “proxels” (process pixels) as its basic objects, which have different dimensions depending on the viewing

  18. Operational forecasting based on a modified Weather Research and Forecasting model

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

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

  19. Mesoscale modeling of the production and the three-dimensional transport of nitrogen oxides in thunderstorms; Mesoskalige Modellierung der Produktion und des dreidimensionalen Transports von Stickoxiden durch Gewitter

    Fehr, T.

    2000-07-01

    Nitrogen oxides, NO{sub x} = NO + NO{sub 2}, play a fundamental role in tropospheric chemistry. Compared to other sources, the contribution of lightning induced NO{sub x} (LNO{sub x}) is known with considerable uncertainties and difficult to determine experimentally. The distribution of nitrogen oxides in an isolated thunderstorm is investigated using a modified version of the Penn State/NCAR Mesoscale Model (MM5) with cloud-scale resolution. A Lagrangian particle model has been developed to represent the NO{sub x} released by individual flashes. The position of the flash, the flash type, the geometrical properties of the channel, and the amount of emitted NO{sub x} are introduced to the MM5 in a parameterized form. On July 21, 1998, during the European lightning nitrogen oxides project (EULINOX) field campaign, a supercell development was observed in the German alpine foreland. Anvil penetrations by the DLR Falcon aircraft contributed high resolution profiles of NO{sub x}. DLR radar observation covered the complete life cycle of the thunderstorm. The lightning activity was recorded with a lightning positioning and tracking system (LPATS) run by local power suppliers, while radiosonde and aircraft measurements supplied detailed information on the atmospheric stratification ahead of the thunderstorm. This meteorological information was used to initalize a cloud-scale MM5 simulation. The modeled thunderstorm reproduces many observed properties, e.g. cell splitting, propagation speed and direction, anvil and overshooting top height, and WER (weak echo region). The number of simulated cloud-to-ground flashes, as well as the temporal evolution of the lightning activity are comparable to the LPAT observations. The general transport properties of the model thunderstorm are investigated using an inert PBL-tracer, as well as trajectory analysis. The simulated lightning activity leads to the release of approximately 1 000 000 NO{sub x}-particles. The thunderstorm produces 28

  20. Evaluation of planetary boundary layer schemes in meso-scale simulations above the North and Baltic Sea

    Wurps, Hauke; Tambke, Jens; Steinfeld, Gerald; von Bremen, Lueder

    2014-05-01

    The development and design of wind energy converters for offshore wind farms require profound knowledge of the wind profile in the lower atmosphere. Especially an accurate and reliable estimation of turbulence, shear and veer are necessary for the prediction of energy production and loads. Currently existing wind energy turbines in the North Sea have hub heights of around 90 m and upper tip heights around 150 m, which is already higher than the highest measurement masts (e.g. FINO1: 103 m). The next generation of wind turbines will clearly outrange these altitudes, so the interest is to examine the atmosphere's properties above the North Sea up to 300 m. Therefore, besides the Prandtl layer also the Ekman layer has to be taken into account, which implies that changes of the wind direction with height become more relevant. For this investigation we use the Weather Research and Forecasting Model (WRF), a meso-scale numerical weather prediction system. In this study we compare different planetary boundary layer (PBL) schemes (MYJ, MYNN, QNSE) with the same high quality input from ECMWF used as boundary conditions (ERA-Interim). It was found in previous studies that the quality of the boundary conditions is crucially important for the accuracy of comparisons between different PBL schemes. This is due to the fact that the major source of meso-scale simulation errors is introduced by the driving boundary conditions and not by the different schemes of the meso-scale model itself. Hence, small differences in results from different PBL schemes can be distorted arbitrarily by coarse input data. For instance, ERA-Interim data leads to meso-scale RMSE values of 1.4 m/s at 100 m height above sea surface with mean wind speeds around 10 m/s, whereas other Reanalysis products lead to RMSEs larger than 2 m/s. Second, we compare our simulations to operational NWP results from the COSMO model (run by the DWD). In addition to the wind profile, also the turbulent kinetic energy (TKE

  1. Mesoscale Eddies in the Solomon Sea

    Hristova, H. G.; Kessler, W. S.; McWilliams, J. C.; Molemaker, M. J.

    2011-12-01

    Water mass transformation in the strong equatorward flows through the Solomon Sea influences the properties of the Equatorial Undercurrent and subsequent cold tongue upwelling. High eddy activity in the interior Solomon Sea seen in altimetric sea surface height (SSH) and in several models may provide a mechanism for these transformations. We investigate these effects using a mesoscale (4-km resolution) sigma-coordinate (ROMS) model of the Solomon Sea nested in a basin solution, forced by a repeating seasonal cycle, and evaluated against observational data. The model generates a vigorous upper layer eddy field; some of these are apparently shed as the New Guinea Coastal Undercurrent threads through the complex topography of the region, others are independent of the strong western boundary current. We diagnose the scales and vertical structure of the eddies in different parts of the Solomon Sea to illuminate their generation processes and propagation characteristics, and compare these to observed eddy statistics. Hypotheses tested are that the Solomon Sea mesoscale eddies are generated locally by baroclinic instability, that the eddies are shed as the South Equatorial Current passes around and through the Solomon Island chain, that eddies are generated by the New Guinea Coastal Undercurrent, or that eddies occurring outside of the Solomon Sea propagate into the Solomon Sea. These different mechanisms have different implications for the resulting mixing and property fluxes. They also provide different interpretations for SSH signals observed from satellites (e.g., that will be observed by the upcoming SWOT satellite).

  2. Intense mesoscale variability in the Sardinia Sea

    Russo, Aniello; Borrione, Ines; Falchetti, Silvia; Knoll, Michaela; Fiekas, Heinz-Volker; Heywood, Karen; Oddo, Paolo; Onken, Reiner

    2015-04-01

    From the 6 to 25 June 2014, the REP14-MED sea trial was conducted by CMRE, supported by 20 partners from six different nations. The at-sea activities were carried out onboard the research vessels Alliance (NATO) and Planet (German Ministry of Defense), comprising a marine area of about 110 x 110 km2 to the west of the Sardinian coast. More than 300 CTD casts typically spaced at 10 km were collected; both ships continuously recorded vertical profiles of currents by means of their ADCPs, and a ScanFish® and a CTD chain were towed for almost three days by Alliance and Planet, respectively, following parallel routes. Twelve gliders from different manufacturers (Slocum, SeaGliderTM and SeaExplorer) were continuously sampling the study area following zonal tracks spaced at 10 km. In addition, six moorings, 17 surface drifters and one ARVOR float were deployed. From a first analysis of the observations, several mesoscale features were identified in the survey area, in particular: (i) a warm-core anticyclonic eddy in the southern part of the domain, about 50 km in diameter and with the strongest signal at about 50-m depth (ii) another warm-core anticyclonic eddy of comparable dimensions in the central part of the domain, but extending to greater depth than the former one, and (iii) a small (less than 15 km in diameter) cold-core cyclonic eddy of Winter Intermediate Water in the depth range between 170 m and 370 m. All three eddies showed intensified currents, up to 50 cm s-1. The huge high-resolution observational data set and the variety of observation techniques enabled the mesoscale features and their variability to be tracked for almost three weeks. In order to obtain a deeper understanding of the mesoscale dynamic behaviour and their interactions, assimilation studies with an ocean circulation model are underway.

  3. Space Weather Laboratory

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

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

    ten Veldhuis, Marie-claire; van Riemsdijk, Birna

    2013-04-01

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

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

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

    2005-01-01

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

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

    B. N. Lawrence

    2018-05-01

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

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

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

    2018-05-01

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

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

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

    2016-01-01

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

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

    C. Zhou

    2016-01-01

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

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

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

    2014-05-01

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

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

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

    2011-12-01

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

  12. Effects of airplane emissions on the composition of the atmosphere: Investigations using a mesoscale chemical transport model; Der Einfluss von Flugzeugabgasen auf die Zusammensetzung der Atmosphaere: Untersuchungen mit einem mesoskaligen Chemie-Transport-Modell

    Lippert, E

    1997-12-31

    In the present work the impact of aircraft emissions on the atmospheric composition is studied using a mesoscale chemistry transport model. To simulate the impact of aircraft exhausts several modifications on the EURAD model system have been performed. The upper boundary of the model has been extended from 100 hPa up to 10 hPa. The vertical resolution of the model has been refined especially in tropopause altitudes extending the number of model layers from 15 to 29. Additionally the initialization and the treatment of the boundary conditions has been improved by coupling the trace gas concentration fields with the individual meteorological situation. To guarantee an adequate representation of the atmospheric chemistry the chemical mechanism CHEST has been developed and implemented into the chemistry transport model. CHEST treats the most important chemical processes of the troposphere and lower stratosphere. In the frame of the present work sensitivity studies with a box model and with the threedimensional chemistry transport model have been performed to investigate the impact of aircraft emissions upon the atmosphere. (KW) [Deutsch] In der vorliegenden Arbeit werden die Auswirkungen der Flugzeugemissionen auf die Zusammensetzung der Atmosphaere mit Hilfe eines mesoskaligen Chemie-Transport-Modells untersucht. Zur Simulation der Ausbreitung der Flugzeugabgase wurden am EURAD-Modell-System umfangreiche Veraenderungen vorgenommen. Der obere Modellrand des Chemie-Transport-Modells ist von 100 hPa auf 10 hPa erhoeht worden. Die vertikale Aufloesung des Modells wurde insbesondere im Tropopausenbereich durch eine Erhoehung der Gesamtzahl der Modellschichten von 15 auf 29 wesentlich verfeinert. Ausserdem ist die Initialisierung der Spurenstoffverteilung im Modell an die Dynamik gekoppelt worden. Dem Chemie-Transport-Modell stehen damit an die jeweilige meteorologische Situation angepasste Konzentrationsfelder zur Initialisierung und zur Behandlung der Fluesse durch den

  13. Effects of airplane emissions on the composition of the atmosphere: Investigations using a mesoscale chemical transport model; Der Einfluss von Flugzeugabgasen auf die Zusammensetzung der Atmosphaere: Untersuchungen mit einem mesoskaligen Chemie-Transport-Modell

    Lippert, E.

    1996-12-31

    In the present work the impact of aircraft emissions on the atmospheric composition is studied using a mesoscale chemistry transport model. To simulate the impact of aircraft exhausts several modifications on the EURAD model system have been performed. The upper boundary of the model has been extended from 100 hPa up to 10 hPa. The vertical resolution of the model has been refined especially in tropopause altitudes extending the number of model layers from 15 to 29. Additionally the initialization and the treatment of the boundary conditions has been improved by coupling the trace gas concentration fields with the individual meteorological situation. To guarantee an adequate representation of the atmospheric chemistry the chemical mechanism CHEST has been developed and implemented into the chemistry transport model. CHEST treats the most important chemical processes of the troposphere and lower stratosphere. In the frame of the present work sensitivity studies with a box model and with the threedimensional chemistry transport model have been performed to investigate the impact of aircraft emissions upon the atmosphere. (KW) [Deutsch] In der vorliegenden Arbeit werden die Auswirkungen der Flugzeugemissionen auf die Zusammensetzung der Atmosphaere mit Hilfe eines mesoskaligen Chemie-Transport-Modells untersucht. Zur Simulation der Ausbreitung der Flugzeugabgase wurden am EURAD-Modell-System umfangreiche Veraenderungen vorgenommen. Der obere Modellrand des Chemie-Transport-Modells ist von 100 hPa auf 10 hPa erhoeht worden. Die vertikale Aufloesung des Modells wurde insbesondere im Tropopausenbereich durch eine Erhoehung der Gesamtzahl der Modellschichten von 15 auf 29 wesentlich verfeinert. Ausserdem ist die Initialisierung der Spurenstoffverteilung im Modell an die Dynamik gekoppelt worden. Dem Chemie-Transport-Modell stehen damit an die jeweilige meteorologische Situation angepasste Konzentrationsfelder zur Initialisierung und zur Behandlung der Fluesse durch den

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

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

    2012-08-01

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

  15. Preliminary Results of a U.S. Deep South Warm Season Deep Convective Initiation Modeling Experiment using NASA SPoRT Initialization Datasets for Operational National Weather Service Local Model Runs

    Medlin, Jeffrey M.; Wood, Lance; Zavodsky, Brad; Case, Jon; Molthan, Andrew

    2012-01-01

    The initiation of deep convection during the warm season is a forecast challenge in the relative high instability and low wind shear environment of the U.S. Deep South. Despite improved knowledge of the character of well known mesoscale features such as local sea-, bay- and land-breezes, observations show the evolution of these features fall well short in fully describing the location of first initiates. A joint collaborative modeling effort among the NWS offices in Mobile, AL, and Houston, TX, and NASA s Short-term Prediction Research and Transition (SPoRT) Center was undertaken during the 2012 warm season to examine the impact of certain NASA produced products on the Weather Research and Forecasting Environmental Modeling System. The NASA products were: a 4-km Land Information System data, a 1-km sea surface temperature analysis, and a 4-km greenness vegetation fraction analysis. Similar domains were established over the southeast Texas and Alabama coastlines, each with a 9 km outer grid spacing and a 3 km inner nest spacing. The model was run at each NWS office once per day out to 24 hours from 0600 UTC, using the NCEP Global Forecast System for initial and boundary conditions. Control runs without the NASA products were made at the NASA SPoRT Center. The NCAR Model Evaluation Tools verification package was used to evaluate both the forecast timing and location of the first initiates, with a focus on the impacts of the NASA products on the model forecasts. Select case studies will be presented to highlight the influence of the products.

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

    D. Bachmann

    2004-01-01

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

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

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

    2015-12-01

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

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

    Kiilsholm, S.; Rasmussen, A.

    2000-01-01

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

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

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

    2014-06-01

    Advanced forecasting of space weather requires simulation of the whole Sun-to-Earth system, which necessitates driving magnetospheric models with the outputs from solar wind models. This presents a fundamental difficulty, as the magnetosphere is sensitive to both large-scale solar wind structures, which can be captured by solar wind models, and small-scale solar wind "noise," which is far below typical solar wind model resolution and results primarily from stochastic processes. Following similar approaches in terrestrial climate modeling, we propose statistical "downscaling" of solar wind model results prior to their use as input to a magnetospheric model. As magnetospheric response can be highly nonlinear, this is preferable to downscaling the results of magnetospheric modeling. To demonstrate the benefit of this approach, we first approximate solar wind model output by