Rotational and divergent kinetic energy in the mesoscale model ALADIN

Directory of Open Access Journals (Sweden)

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.

WRF Mesoscale Pre-Run for the Wind Atlas of Mexico

OpenAIRE

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...

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

Science.gov (United States)

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

2016-12-01

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

Mesoscale Modeling, Forecasting and Remote Sensing Research.

Science.gov (United States)

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

Extreme gust wind estimation using mesoscale modeling

DEFF Research Database (Denmark)

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...

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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)

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

Science.gov (United States)

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.

Assimilation of Aircraft Observations in High-Resolution Mesoscale Modeling

Directory of Open Access Journals (Sweden)

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.

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

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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

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

Mesoscale wind fluctuations over Danish waters

DEFF Research Database (Denmark)

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...

Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

Science.gov (United States)

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.

Weather and forecasting at Wilkins ice runway, Antarctica

International Nuclear Information System (INIS)

Carpentier, Scott

2010-01-01

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

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

Science.gov (United States)

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).

Wind-Farm Parametrisations in Mesoscale Models

DEFF Research Database (Denmark)

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...

A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

2014-01-01

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

Mesoscale modeling of solute precipitation and radiation damage

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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

Characterizing the Meso-scale Plasma Flows in Earth's Coupled Magnetosphere-Ionosphere-Thermosphere System

Science.gov (United States)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

1996-04-01

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

Towards a generalization procedure for WRF mesoscale wind climatologies

DEFF Research Database (Denmark)

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...

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

International Nuclear Information System (INIS)

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)

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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

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

Directory of Open Access Journals (Sweden)

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

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

Intercomparison of oceanic and atmospheric forced and coupled mesoscale simulations Part I: Surface fluxes

Directory of Open Access Journals (Sweden)

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

Intercomparison of oceanic and atmospheric forced and coupled mesoscale simulations Part I: Surface fluxes

Directory of Open Access Journals (Sweden)

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

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

African Journals Online (AJOL)

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 ...

Using Virtualization to Integrate Weather, Climate, and Coastal Science Education

Science.gov (United States)

Davis, J. R.; Paramygin, V. A.; Figueiredo, R.; Sheng, Y.

2012-12-01

To better understand and communicate the important roles of weather and climate on the coastal environment, a unique publically available tool is being developed to support research, education, and outreach activities. This tool uses virtualization technologies to facilitate an interactive, hands-on environment in which students, researchers, and general public can perform their own numerical modeling experiments. While prior efforts have focused solely on the study of the coastal and estuary environments, this effort incorporates the community supported weather and climate model (WRF-ARW) into the Coastal Science Educational Virtual Appliance (CSEVA), an education tool used to assist in the learning of coastal transport processes; storm surge and inundation; and evacuation modeling. The Weather Research and Forecasting (WRF) Model is a next-generation, community developed and supported, mesoscale numerical weather prediction system designed to be used internationally for research, operations, and teaching. It includes two dynamical solvers (ARW - Advanced Research WRF and NMM - Nonhydrostatic Mesoscale Model) as well as a data assimilation system. WRF-ARW is the ARW dynamics solver combined with other components of the WRF system which was developed primarily at NCAR, community support provided by the Mesoscale and Microscale Meteorology (MMM) division of National Center for Atmospheric Research (NCAR). Included with WRF is the WRF Pre-processing System (WPS) which is a set of programs to prepare input for real-data simulations. The CSEVA is based on the Grid Appliance (GA) framework and is built using virtual machine (VM) and virtual networking technologies. Virtualization supports integration of an operating system, libraries (e.g. Fortran, C, Perl, NetCDF, etc. necessary to build WRF), web server, numerical models/grids/inputs, pre-/post-processing tools (e.g. WPS / RIP4 or UPS), graphical user interfaces, "Cloud"-computing infrastructure and other tools into a

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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)

Probabilistic, meso-scale flood loss modelling

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Prashant K. Srivastava

2017-10-01

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

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

Directory of Open Access Journals (Sweden)

D. Hari Prasad

2010-01-01

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

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

Science.gov (United States)

Dreher, Joseph G.

2009-01-01

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

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

Science.gov (United States)

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.

Intercomparison of oceanic and atmospheric forced and coupled mesoscale simulations. Part I: Surface fluxes

Science.gov (United States)

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

Optogenetic stimulation of a meso-scale human cortical model

Science.gov (United States)

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.

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

Science.gov (United States)

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

Atmospheric Diabatic Heating in Different Weather States and the General Circulation

Science.gov (United States)

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.

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

National Research Council Canada - National Science Library

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...

Mesoscale meteorological model based on radioactive explosion cloud simulation

International Nuclear Information System (INIS)

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)

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

Directory of Open Access Journals (Sweden)

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

Mesoscale modeling of metal-loaded high explosives

Energy Technology Data Exchange (ETDEWEB)

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.

Mesoscale modeling: solving complex flows in biology and biotechnology.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

Cassardo, C.; Loglisci, N.

2005-01-01

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

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

International Nuclear Information System (INIS)

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

Development of a parameterization scheme of mesoscale convective systems

International Nuclear Information System (INIS)

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

Role of land state in a high resolution mesoscale model

Indian Academy of Sciences (India)

... 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.

Verification of some numerical models for operationally predicting mesoscale winds aloft

International Nuclear Information System (INIS)

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

Spectral structure of mesoscale winds over the water

DEFF Research Database (Denmark)

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...

Initializing a Mesoscale Boundary-Layer Model with Radiosonde Observations

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Calculation of extreme wind atlases using mesoscale modeling. Final report

DEFF Research Database (Denmark)

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...

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

Science.gov (United States)

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

2018-06-01

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

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

Science.gov (United States)

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.

A three-dimensional viscous topography mesoscale model

Energy Technology Data Exchange (ETDEWEB)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

Meso-scale wind variability. Final report

Energy Technology Data Exchange (ETDEWEB)

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)

Numerical simulation of terrain-induced mesoscale circulation in the Chiang Mai area, Thailand

Science.gov (United States)

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.

Mesoscale Modelling of the Response of Aluminas

International Nuclear Information System (INIS)

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

Advanced Corrections for InSAR Using GPS and Numerical Weather Models

Science.gov (United States)

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

2017-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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.)

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

Science.gov (United States)

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

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Wai-Kin Wong

2013-01-01

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

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

International Nuclear Information System (INIS)

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

Mesoscale Benchmark Demonstration Problem 1: Mesoscale Simulations of Intra-granular Fission Gas Bubbles in UO2 under Post-irradiation Thermal Annealing

Energy Technology Data Exchange (ETDEWEB)

Li, Yulan; Hu, Shenyang Y.; Montgomery, Robert; Gao, Fei; Sun, Xin; Tonks, Michael; Biner, Bullent; Millet, Paul; Tikare, Veena; Radhakrishnan, Balasubramaniam; Andersson , David

2012-04-11

A study was conducted to evaluate the capabilities of different numerical methods used to represent microstructure behavior at the mesoscale for irradiated material using an idealized benchmark problem. The purpose of the mesoscale benchmark problem was to provide a common basis to assess several mesoscale methods with the objective of identifying the strengths and areas of improvement in the predictive modeling of microstructure evolution. In this work, mesoscale models (phase-field, Potts, and kinetic Monte Carlo) developed by PNNL, INL, SNL, and ORNL were used to calculate the evolution kinetics of intra-granular fission gas bubbles in UO2 fuel under post-irradiation thermal annealing conditions. The benchmark problem was constructed to include important microstructural evolution mechanisms on the kinetics of intra-granular fission gas bubble behavior such as the atomic diffusion of Xe atoms, U vacancies, and O vacancies, the effect of vacancy capture and emission from defects, and the elastic interaction of non-equilibrium gas bubbles. An idealized set of assumptions was imposed on the benchmark problem to simplify the mechanisms considered. The capability and numerical efficiency of different models are compared against selected experimental and simulation results. These comparisons find that the phase-field methods, by the nature of the free energy formulation, are able to represent a larger subset of the mechanisms influencing the intra-granular bubble growth and coarsening mechanisms in the idealized benchmark problem as compared to the Potts and kinetic Monte Carlo methods. It is recognized that the mesoscale benchmark problem as formulated does not specifically highlight the strengths of the discrete particle modeling used in the Potts and kinetic Monte Carlo methods. Future efforts are recommended to construct increasingly more complex mesoscale benchmark problems to further verify and validate the predictive capabilities of the mesoscale modeling

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

National Research Council Canada - National Science Library

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...

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

Science.gov (United States)

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.

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

DEFF Research Database (Denmark)

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...

Numerical simulations of island effects on airflow and weather during the summer over the island of Oahu

Science.gov (United States)

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...

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

Science.gov (United States)

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

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

Science.gov (United States)

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

2009-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Czech Academy of Sciences Publication Activity Database

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

Numerical simulation and decomposition of kinetic energy in the Central Mediterranean: insight on mesoscale circulation and energy conversion

Directory of Open Access Journals (Sweden)

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

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

Science.gov (United States)

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.

Mesoscale Effects on Carbon Export: A Global Perspective

Science.gov (United States)

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.

LBM estimation of thermal conductivity in meso-scale modelling

International Nuclear Information System (INIS)

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)

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

Science.gov (United States)

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.

Parameterization of phase change of water in a mesoscale model

Energy Technology Data Exchange (ETDEWEB)

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..

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

Science.gov (United States)

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

Meso-scale modeling of irradiated concrete in test reactor

International Nuclear Information System (INIS)

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.

Meso-scale modeling of irradiated concrete in test reactor

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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.

Evaluation of planetary boundary layer schemes in meso-scale simulations above the North and Baltic Sea

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

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.

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

Directory of Open Access Journals (Sweden)

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.

Final Report, University of California Merced: Uranium and strontium fate in waste-weathered sediments: Scaling of molecular processes to predict reactive transport (DE-SC0007095)

Energy Technology Data Exchange (ETDEWEB)

O' Day, Peggy Anne [University of California Merced; Chorover, Jon [University of Arizona; Steefel, Carl [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Mueller, Karl [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Um, Wooyong [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2016-06-30

Objectives of the Project: 1. Determine the process coupling that occurs between mineral transformation and contaminant (U and Sr) speciation in acid-uranium waste weathered Hanford sediments. 2. Establish linkages between molecular-scale contaminant speciation and meso-scale contaminant lability, release and reactive transport. 3. Make conjunctive use of molecular- to bench-scale data to constrain the development of a mechanistic, reactive transport model that includes coupling of contaminant sorption-desorption and mineral transformation reactions. Hypotheses Tested: Uranium and strontium speciation in legacy sediments from the U-8 and U-12 Crib sites can be reproduced in bench-scale weathering experiments conducted on unimpacted Hanford sediments from the same formations; Reactive transport modeling of future uranium and strontium releases from the vadose zone of acid-waste weathered sediments can be effectively constrained by combining molecular-scale information on contaminant bonding environment with grain-scale information on contaminant phase partitioning, and meso-scale kinetic data on contaminant release from the waste-weathered porous media; Although field contamination and laboratory experiments differ in their diagenetic time scales (decades for field vs. months to years for lab), sediment dissolution, neophase nucleation, and crystal growth reactions that occur during the initial disequilibrium induced by waste-sediment interaction leave a strong imprint that persists over subsequent longer-term equilibration time scales and, therefore, give rise to long-term memory effects. Enabling Capabilities Developed: Our team developed an iterative measure-model approach that is broadly applicable to elucidate the mechanistic underpinnings of reactive contaminant transport in geomedia subject to active weathering.

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

International Nuclear Information System (INIS)

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)

How accurate are the weather forecasts for Bierun (southern Poland)?

Science.gov (United States)

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

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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

2018-03-01

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

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

Science.gov (United States)

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

An introduction to Space Weather Integrated Modeling

Science.gov (United States)

Zhong, D.; Feng, X.

2012-12-01

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

Space Weather Models at the CCMC And Their Capabilities

Science.gov (United States)

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

2007-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

Online coupled regional meteorology chemistry models in Europe : Current status and prospects

NARCIS (Netherlands)

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

Models of Weather Impact on Air Traffic

Science.gov (United States)

Kulkarni, Deepak; Wang, Yao

2017-01-01

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

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

Science.gov (United States)

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

2012-04-01

. 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

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

DEFF Research Database (Denmark)

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...

Mesoscale modeling of amorphous metals by shear transformation zone dynamics

International Nuclear Information System (INIS)

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.

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

Science.gov (United States)

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

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

Energy Technology Data Exchange (ETDEWEB)

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)

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

Science.gov (United States)

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.

Upscale Impact of Mesoscale Disturbances of Tropical Convection on Convectively Coupled Kelvin Waves

Science.gov (United States)

Yang, Q.; Majda, A.

2017-12-01

Tropical convection associated with convectively coupled Kelvin waves (CCKWs) is typically organized by an eastward-moving synoptic-scale convective envelope with numerous embedded westward-moving mesoscale disturbances. It is of central importance to assess upscale impact of mesoscale disturbances on CCKWs as mesoscale disturbances propagate at various tilt angles and speeds. Here a simple multi-scale model is used to capture this multi-scale structure, where mesoscale fluctuations are directly driven by mesoscale heating and synoptic-scale circulation is forced by mean heating and eddy transfer of momentum and temperature. The two-dimensional version of the multi-scale model drives the synoptic-scale circulation, successfully reproduces key features of flow fields with a front-to-rear tilt and compares well with results from a cloud resolving model. In the scenario with an elevated upright mean heating, the tilted vertical structure of synoptic-scale circulation is still induced by the upscale impact of mesoscale disturbances. In a faster propagation scenario, the upscale impact becomes less important, while the synoptic-scale circulation response to mean heating dominates. In the unrealistic scenario with upward/westward tilted mesoscale heating, positive potential temperature anomalies are induced in the leading edge, which will suppress shallow convection in a moist environment. In its three-dimensional version, results show that upscale impact of mesoscale disturbances that propagate at tilt angles (110o 250o) induces negative lower-tropospheric potential temperature anomalies in the leading edge, providing favorable conditions for shallow convection in a moist environment, while the remaining tilt angle cases have opposite effects. Even in the presence of upright mean heating, the front-to-rear tilted synoptic-scale circulation can still be induced by eddy terms at tilt angles (120o 240o). In the case with fast propagating mesoscale heating, positive

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

Digital Repository Service at National Institute of Oceanography (India)

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...

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

Directory of Open Access Journals (Sweden)

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.

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

KAUST Repository

Deng, Liping

2015-05-01

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

Parameterization of Mixed Layer and Deep-Ocean Mesoscales Including Nonlinearity

Science.gov (United States)

Canuto, V. M.; Cheng, Y.; Dubovikov, M. S.; Howard, A. M.; Leboissetier, A.

2018-01-01

In 2011, Chelton et al. carried out a comprehensive census of mesoscales using altimetry data and reached the following conclusions: "essentially all of the observed mesoscale features are nonlinear" and "mesoscales do not move with the mean velocity but with their own drift velocity," which is "the most germane of all the nonlinear metrics."� Accounting for these results in a mesoscale parameterization presents conceptual and practical challenges since linear analysis is no longer usable and one needs a model of nonlinearity. A mesoscale parameterization is presented that has the following features: 1) it is based on the solutions of the nonlinear mesoscale dynamical equations, 2) it describes arbitrary tracers, 3) it includes adiabatic (A) and diabatic (D) regimes, 4) the eddy-induced velocity is the sum of a Gent and McWilliams (GM) term plus a new term representing the difference between drift and mean velocities, 5) the new term lowers the transfer of mean potential energy to mesoscales, 6) the isopycnal slopes are not as flat as in the GM case, 7) deep-ocean stratification is enhanced compared to previous parameterizations where being more weakly stratified allowed a large heat uptake that is not observed, 8) the strength of the Deacon cell is reduced. The numerical results are from a stand-alone ocean code with Coordinated Ocean-Ice Reference Experiment I (CORE-I) normal-year forcing.

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

Energy Technology Data Exchange (ETDEWEB)

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

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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)

Thermally forced mesoscale atmospheric flow over complex terrain in Southern Italy

International Nuclear Information System (INIS)

Baldi, M.; Colacino, M.; Dalu, G. A.; Piervitali, E.; Ye, Z.

1998-01-01

In this paper the Authors discuss some results concerning the analysis of the local atmospheric flow over the southern part of Italy, the peninsula of Calabria, using a mesoscale numerical model. Our study is focused on two different but related topics: a detailed analysis of the meteorology and climate of the region based on a data collection, reported in Colacino et al., 'Elementi di Climatologia della Calabria', edited by A. Guerrini, in the series P. S., 'Clima, Ambiente e Territorio nel Mezzogiorno' (CNR, Rome) 1997, pp. 218, and an analysis of the results based on the simulated flow produced using a mesoscale numerical model. The Colorado State University mesoscale numerical model has been applied to study several different climatic situations of particular interest for the region, as discussed in this paper

Thermally forced mesoscale atmospheric flow over complex terrain in Southern Italy

Energy Technology Data Exchange (ETDEWEB)

Baldi, M.; Colacino, M.; Dalu, G. A.; Piervitali, E.; Ye, Z. [CNR, Rome (Italy). Ist. di Fisica dell`Atmosfera

1998-07-01

In this paper the Authors discuss some results concerning the analysis of the local atmospheric flow over the southern part of Italy, the peninsula of Calabria, using a mesoscale numerical model. Our study is focused on two different but related topics: a detailed analysis of the meteorology and climate of the region based on a data collection, reported in Colacino et al., `Elementi di Climatologia della Calabria`, edited by A. Guerrini, in the series P. S., `Clima, Ambiente e Territorio nel Mezzogiorno` (CNR, Rome) 1997, pp. 218, and an analysis of the results based on the simulated flow produced using a mesoscale numerical model. The Colorado State University mesoscale numerical model has been applied to study several different climatic situations of particular interest for the region, as discussed in this paper.

Analysis of mesoscale factors at the onset of deep convection on hailstorm days in Southern France and their relation to the synoptic patterns

Science.gov (United States)

Sanchez, Jose Luis; Wu, Xueke; Gascón, Estibaliz; López, Laura; Melcón, Pablo; García-Ortega, Eduardo; Berthet, Claude; Dessens, Jean; Merino, Andrés

2013-04-01

Storms and the weather phenomena associated to intense precipitation, lightning, strong winds or hail, are among the most common and dangerous weather risks in many European countries. To get a reliable forecast of their occurrence is remaining an open problem. The question is: how is possible to improve the reliability of forecast? Southwestern France is frequently affected by hailstorms, producing severe damages on crops and properties. Considerable efforts were made to improve the forecast of hailfall in this area. First of all, if we want to improve this type of forecast, it is necessary to have a good "ground truth" of the hail days and zones affected by hailfall. Fortunately, ANELFA has deployed thousands of hailpad stations in Southern France. The ANELFA processed the point hailfall data recorded during each hail season at these stations. The focus of this paper presents a methodology to improve the forecast of the occurrence of hailfall according to the synoptic environment and mesoscale factors in the study area. One hundred of hail days were selected, following spatial and severity criteria, occurred in the period 2000-2010. The mesoscale model WRF was applied for all cases to study the synoptic environment of mean geopotential and temperature fields at 500 hPa. Three nested domains have been defined following a two-way nesting strategy, with a horizontal spatial resolution of 36, 12 and 4 km, and 30 vertical terrains— following σ-levels. Then, using the Principal Component Analysis in T-Mode, 4 mesoscale configurations were defined for the fields of convective instability (CI), water vapor flux divergence and wind flow and humidity at low layer (850hPa), and several clusters were classified followed by using the K-means Clustering. Finally, we calculated several characteristic values of four hail forecast parameters: Convective Available Potential Energy (CAPE), Storm Relative Helicity between 0 and 3 km (SRH0-3), Energy-Helicity Index (EHI) and

Mesoscale simulation of concrete spall failure

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

2002-01-01

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

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

Science.gov (United States)

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.

The influence of mesoscale porosity on cortical bone anisotropy. Investigations via asymptotic homogenization

Science.gov (United States)

Parnell, William J; Grimal, Quentin

2008-01-01

Recently, the mesoscale of cortical bone has been given particular attention in association with novel experimental techniques such as nanoindentation, micro-computed X-ray tomography and quantitative scanning acoustic microscopy (SAM). A need has emerged for reliable mathematical models to interpret the related microscopic and mesoscopic data in terms of effective elastic properties. In this work, a new model of cortical bone elasticity is developed and used to assess the influence of mesoscale porosity on the induced anisotropy of the material. Only the largest pores (Haversian canals and resorption cavities), characteristic of the mesoscale, are considered. The input parameters of the model are derived from typical mesoscale experimental data (e.g. SAM data). We use the method of asymptotic homogenization to determine the local effective elastic properties by modelling the propagation of low-frequency elastic waves through an idealized material that models the local mesostructure. We use a novel solution of the cell problem developed by Parnell & Abrahams. This solution is stable for the physiological range of variation of mesoscopic porosity and elasticity found in bone. Results are computed efficiently (in seconds) and the solutions can be implemented easily by other workers. Parametric studies are performed in order to assess the influence of mesoscopic porosity, the assumptions regarding the material inside the mesoscale pores (drained or undrained bone) and the shape of pores. Results are shown to be in good qualitative agreement with existing schemes and we describe the potential of the scheme for future use in modelling more complex microstructures for cortical bone. In particular, the scheme is shown to be a useful tool with which to predict the qualitative changes in anisotropy due to variations in the structure at the mesoscale. PMID:18628200

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

DEFF Research Database (Denmark)

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...

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

DEFF Research Database (Denmark)

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

2006-01-01

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

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

Science.gov (United States)

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

2016-12-01

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

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

Science.gov (United States)

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.

Hydrological modeling using a multi-site stochastic weather generator

Science.gov (United States)

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

Space Weather Forecasting and Research at the Community Coordinated Modeling Center

Science.gov (United States)

Aronne, M.

2015-12-01

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

Simulating air temperature in an urban street canyon in all weather conditions using measured data at a reference meteorological station

Science.gov (United States)

Erell, E.; Williamson, T.

2006-10-01

A model is proposed that adapts data from a standard meteorological station to provide realistic site-specific air temperature in a city street exposed to the same meso-scale environment. In addition to a rudimentary description of the two sites, the canyon air temperature (CAT) model requires only inputs measured at standard weather stations; yet it is capable of accurately predicting the evolution of air temperature in all weather conditions for extended periods. It simulates the effect of urban geometry on radiant exchange; the effect of moisture availability on latent heat flux; energy stored in the ground and in building surfaces; air flow in the street based on wind above roof height; and the sensible heat flux from individual surfaces and from the street canyon as a whole. The CAT model has been tested on field data measured in a monitoring program carried out in Adelaide, Australia, in 2000-2001. After calibrating the model, predicted air temperature correlated well with measured data in all weather conditions over extended periods. The experimental validation provides additional evidence in support of a number of parameterisation schemes incorporated in the model to account for sensible heat and storage flux.

The Impacts of Different Meteorology Data Sets on Nitrogen Fate and Transport in the SWAT Watershed Model

Science.gov (United States)

In this study, we investigated how different meteorology data sets impacts nitrogen fate and transport responses in the Soil and Water Assessment Tool (SWAT) model. We used two meteorology data sets: National Climatic Data Center (observed) and Mesoscale Model 5/Weather Research ...

How Satellites Have Contributed to Building a Weather Ready Nation

Science.gov (United States)

Lapenta, W.

2017-12-01

NOAA's primary mission since its inception has been to reduce the loss of life and property, as well as disruptions from, high impact weather and water-related events. In recent years, significant societal losses resulting even from well forecast extreme events have shifted attention from the forecast alone toward ensuring societal response is equal to the risks that exist for communities, businesses and the public. The responses relate to decisions ranging from coastal communities planning years in advance to mitigate impacts from rising sea level, to immediate lifesaving decisions such as a family seeking adequate shelter during a tornado warning. NOAA is committed to building a "Weather-Ready Nation" where communities are prepared for and respond appropriately to these events. The Weather-Ready Nation (WRN) strategic priority is building community resilience in the face of increasing vulnerability to extreme weather, water, climate and environmental threats. To build a Weather-Ready Nation, NOAA is enhancing Impact-Based Decision Support Services (IDSS), transitioning science and technology advances into forecast operations, applying social science research to improve the communication and usefulness of information, and expanding its dissemination efforts to achieve far-reaching readiness, responsiveness and resilience. These four components of Weather-Ready Nation are helping ensure NOAA data, products and services are fully utilized to minimize societal impacts from extreme events. Satellite data and satellite products have been important elements of the national Weather Service (NWS) operations for more than 40 years. When one examines the uses of satellite data specific to the internal forecast and warning operations of NWS, two main applications are evident. The first is the use of satellite data in numerical weather prediction models; the second is the use of satellite imagery and derived products for mesoscale and short-range weather warning and

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

DEFF Research Database (Denmark)

Andersen, Ove; Torp, Kristian

2016-01-01

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

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)

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

J. Kukkonen

2012-01-01

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

Use of ground-based wind profiles in mesoscale forecasting

Science.gov (United States)

Schlatter, Thomas W.

1985-01-01

A brief review is presented of recent uses of ground-based wind profile data in mesoscale forecasting. Some of the applications are in real time, and some are after the fact. Not all of the work mentioned here has been published yet, but references are given wherever possible. As Gage and Balsley (1978) point out, sensitive Doppler radars have been used to examine tropospheric wind profiles since the 1970's. It was not until the early 1980's, however, that the potential contribution of these instruments to operational forecasting and numerical weather prediction became apparent. Profiler winds and radiosonde winds compare favorably, usually within a few m/s in speed and 10 degrees in direction (see Hogg et al., 1983), but the obvious advantage of the profiler is its frequent (hourly or more often) sampling of the same volume. The rawinsonde balloon is launched only twice a day and drifts with the wind. In this paper, I will: (1) mention two operational uses of data from a wind profiling system developed jointly by the Wave Propagation and Aeronomy Laboratories of NOAA; (2) describe a number of displays of these same data on a workstation for mesoscale forecasting developed by the Program for Regional Observing and Forecasting Services (PROFS); and (3) explain some interesting diagnostic calculations performed by meteorologists of the Wave Propagation Laboratory.

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

Science.gov (United States)

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.

Adaptive Numerical Algorithms in Space Weather Modeling

Science.gov (United States)

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

Weathering of oils at sea: model/field data comparisons

International Nuclear Information System (INIS)

Daling, Per S.; Stroem, Tove

1999-01-01

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

Explicit simulation of a midlatitude Mesoscale Convective System

Energy Technology Data Exchange (ETDEWEB)

Alexander, G.D.; Cotton, W.R. [Colorado State Univ., Fort Collins, CO (United States)

1996-04-01

We have explicitly simulated the mesoscale convective system (MCS) observed on 23-24 June 1985 during PRE-STORM, the Preliminary Regional Experiment for the Stormscale Operational and Research and Meterology Program. Stensrud and Maddox (1988), Johnson and Bartels (1992), and Bernstein and Johnson (1994) are among the researchers who have investigated various aspects of this MCS event. We have performed this MCS simulation (and a similar one of a tropical MCS; Alexander and Cotton 1994) in the spirit of the Global Energy and Water Cycle Experiment Cloud Systems Study (GCSS), in which cloud-resolving models are used to assist in the formulation and testing of cloud parameterization schemes for larger-scale models. In this paper, we describe (1) the nature of our 23-24 June MCS dimulation and (2) our efforts to date in using our explicit MCS simulations to assist in the development of a GCM parameterization for mesoscale flow branches. The paper is organized as follows. First, we discuss the synoptic situation surrounding the 23-24 June PRE-STORM MCS followed by a discussion of the model setup and results of our simulation. We then discuss the use of our MCS simulation. We then discuss the use of our MCS simulations in developing a GCM parameterization for mesoscale flow branches and summarize our results.

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

Science.gov (United States)

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.

Fractionaly Integrated Flux model and Scaling Laws in Weather and Climate

Science.gov (United States)

Schertzer, Daniel; Lovejoy, Shaun

2013-04-01

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

Boundary layer height determination under summertime anticyclonic weather conditions over the coastal area of Rijeka, Croatia

Energy Technology Data Exchange (ETDEWEB)

Nitis, T.; Moussiopoulos, N. [Aristotle Univ. Thessaloniki (Greece). Lab. of Heat Transfer and Environmental Engineering; Klaic, Z.B. [Univ. of Zagreb (Croatia). Andrija Mohorovicic Geophysical Inst., Faculty of Science; Kitsiou, D. [Univ. of the Aegean, Mytilene (Greece). Dept. of Marine Sciences

2004-07-01

The atmospheric boundary layer height is a fundamental parameter characterising the structure of the lower troposphere. The determination of this parameter is important in applications that range from meteorological modelling and forecasting to dispersion problems of atmospheric pollutants. Since substances emitted into the atmospheric boundary layer are dispersed horizontally and vertically through the action of turbulence, they are well-mixed over this layer that is widely known as ''mixing layer''. There are two basic approaches for the practical estimation of this height; the first approach suggests profile measurements, either in-situ or by remote sounding (sodar, clear-air radar, lidar) and the second one, the use of models with only a few measured parameters as input. As far as the second approach is concerned, the majority of the models use relatively crude estimates of the roughness length that is often based on constant values for land cover. Consequently, the model results are not quite accurate. The present work aims firstly to evaluate the effect of alternative calculations of the roughness length on the non-hydrostatic mesoscale model (MEMO) performance, based on the use of satellite data, and secondly, to estimate the mixing layer height and analyze its variability in relation to underlying topography and land use. Rijeka, a region with complex topography and several islands in its surroundings, offers the opportunity to examine the above mentioned relationships. The non-hydrostatic mesoscale model MEMO was applied under summertime anticyclonic weather conditions during two multi-day periods characterised by stagnant meteorological conditions. The results proved MEMO capable of simulating mesoscale wind flow reasonably well, however, the use of AVHRR satellite data for calculating the roughness length based on the calculation of the NDVI parameter, optimised the model performance and resulted to a more accurate determination of

Wind lidar profile measurements in the coastal boundary layer: comparison with WRF modelling

DEFF Research Database (Denmark)

Floors, Rogier; Pena Diaz, Alfredo; Vincent, Claire Louise

2012-01-01

the sensitivity of PBL schemes of mesoscale models to both lower and upper boundary conditions. We therefore run the mesoscale weather research and forecasting (WRF) model using two different roughness descriptions, two different synoptic forcings and two different PBL schemes at two vertical resolutions. When...... in the amount of observed low level jet. The wind speed predicted by WRF does not improve when a higher resolution is used. Therefore, both the inhomogeneous (westerly) and homogeneous (easterly) flow contribute to a large negative bias in the mean wind speed profile at heights between 100 and 200 m....

Dynamics of Clouds and Mesoscale Circulations over the Maritime Continent

Science.gov (United States)

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

Idealized Mesoscale Model Simulations of Open Cellular Convection Over the Sea

DEFF Research Database (Denmark)

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...

Three-dimensional Mesoscale Simulations of Detonation Initiation in Energetic Materials with Density-based Kinetics

Science.gov (United States)

Jackson, Thomas; Jost, A. M.; Zhang, Ju; Sridharan, P.; Amadio, G.

2017-06-01

In this work we present three-dimensional mesoscale simulations of detonation initiation in energetic materials. We solve the reactive Euler equations, with the energy equation augmented by a power deposition term. The reaction rate at the mesoscale is modelled using a density-based kinetics scheme, adapted from standard Ignition and Growth models. The deposition term is based on previous results of simulations of pore collapse at the microscale, modelled at the mesoscale as hot-spots. We carry out three-dimensional mesoscale simulations of random packs of HMX crystals in a binder, and show that the transition between no-detonation and detonation depends on the number density of the hot-spots, the initial radius of the hot-spot, the post-shock pressure of an imposed shock, and the amplitude of the power deposition term. The trends of transition at lower pressure of the imposed shock for larger number density of pore observed in experiments is reproduced. Initial attempts to improve the agreement between the simulation and experiments through calibration of various parameters will also be made.

Mesoscale Connections Summer 2017

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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

2009-09-01

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

Modeling Silicate Weathering for Elevated CO2 and Temperature

Science.gov (United States)

Bolton, E. W.

2016-12-01

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

The Lagrangian particle dispersion model FLEXPART-WRF VERSION 3.1

Energy Technology Data Exchange (ETDEWEB)

Brioude, J.; Arnold, D.; Stohl, A.; Cassiani, M.; Morton, Don; Seibert, P.; Angevine, W. M.; Evan, S.; Dingwell, A.; Fast, Jerome D.; Easter, Richard C.; Pisso, I.; Bukhart, J.; Wotawa, G.

2013-11-01

The Lagrangian particle dispersion model FLEXPART was originally designed for cal- culating long-range and mesoscale dispersion of air pollutants from point sources, such as after an accident in a nuclear power plant. In the meantime FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. This multiscale need from the modeler community has encouraged new developments in FLEXPART. In this document, we present a version that works with the Weather Research and Forecasting (WRF) mesoscale meteoro- logical model. Simple procedures on how to run FLEXPART-WRF are presented along with special options and features that differ from its predecessor versions. In addition, test case data, the source code and visualization tools are provided to the reader as supplementary material.

The Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS)

National Research Council Canada - National Science Library

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...

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

Energy Technology Data Exchange (ETDEWEB)

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.

Quality assurance of weather data for agricultural system model input

Science.gov (United States)

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

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

Science.gov (United States)

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.

Mesoscale characterization of local property distributions in heterogeneous electrodes

Science.gov (United States)

Hsu, Tim; Epting, William K.; Mahbub, Rubayyat; Nuhfer, Noel T.; Bhattacharya, Sudip; Lei, Yinkai; Miller, Herbert M.; Ohodnicki, Paul R.; Gerdes, Kirk R.; Abernathy, Harry W.; Hackett, Gregory A.; Rollett, Anthony D.; De Graef, Marc; Litster, Shawn; Salvador, Paul A.

2018-05-01

The performance of electrochemical devices depends on the three-dimensional (3D) distributions of microstructural features in their electrodes. Several mature methods exist to characterize 3D microstructures over the microscale (tens of microns), which are useful in understanding homogeneous electrodes. However, methods that capture mesoscale (hundreds of microns) volumes at appropriate resolution (tens of nm) are lacking, though they are needed to understand more common, less ideal electrodes. Using serial sectioning with a Xe plasma focused ion beam combined with scanning electron microscopy (Xe PFIB-SEM), two commercial solid oxide fuel cell (SOFC) electrodes are reconstructed over volumes of 126 × 73 × 12.5 and 124 × 110 × 8 μm3 with a resolution on the order of ≈ 503 nm3. The mesoscale distributions of microscale structural features are quantified and both microscale and mesoscale inhomogeneities are found. We analyze the origin of inhomogeneity over different length scales by comparing experimental and synthetic microstructures, generated with different particle size distributions, with such synthetic microstructures capturing well the high-frequency heterogeneity. Effective medium theory models indicate that significant mesoscale variations in local electrochemical activity are expected throughout such electrodes. These methods offer improved understanding of the performance of complex electrodes in energy conversion devices.

Modeling of Mesoscale Variability in Biofilm Shear Behavior.

Directory of Open Access Journals (Sweden)

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.

Towards assimilation of InSAR data in operational weather models

Science.gov (United States)

Mulder, Gert; van Leijen, Freek; Barkmeijer, Jan; de Haan, Siebren; Hanssen, Ramon

2017-04-01

InSAR signal delays due to the varying atmospheric refractivity are a potential data source to improve weather models [1]. Especially with the launch of the new Sentinel-1 satellites, which increases data coverage, latency and accessibility, it may become possible to operationalize the assimilation of differential integrated refractivity (DIR) values in numerical weather models. Although studies exist on comparison between InSAR data and weather models [2], the impact of assimilation of DIR values in an operational weather model has never been assessed. In this study we present different ways to assimilate DIR values in an operational weather model and show the first forecast results. There are different possibilities to assimilate InSAR-data in a weather model. For example, (i) absolute DIR values can be derived using additional GNSS zenith or slant delay values, (ii) DIR values can be converted to water vapor pressures, or (iii) water vapor pressures can be derived for different heights by combining GNSS and InSAR data. However, an increasing number of assumptions in these processing steps will increase the uncertainty in the final results. Therefore, we chose to insert the InSAR derived DIR values after minimal additional processing. In this study we use the HARMONIE model [3], which is a spectral, non-hydrostatic model with a resolution of about 2.5 km. Currently, this is the operational model in 11 European countries and based on the AROME model [4]. To assimilate the DIR values in the weather model we use a simple adjustment of the weather parameters over the full slant column to match the DIR values. This is a first step towards a more sophisticated approach based on the 3D-VAR or 4D-VAR schemes [5]. Where both assimilation schemes can correct for different weather parameters simultaneously, and 4D-VAR allow us to assimilate DIR values at the exact moment of satellite overpass instead of the start of the forecast window. The approach will be demonstrated

The impact of convection in the West African monsoon region on global weather forecasts - explicit vs. parameterised convection simulations using the ICON model

Science.gov (United States)

Pante, Gregor; Knippertz, Peter

2017-04-01

The West African monsoon is the driving element of weather and climate during summer in the Sahel region. It interacts with mesoscale convective systems (MCSs) and the African easterly jet and African easterly waves. Poor representation of convection in numerical models, particularly its organisation on the mesoscale, can result in unrealistic forecasts of the monsoon dynamics. Arguably, the parameterisation of convection is one of the main deficiencies in models over this region. Overall, this has negative impacts on forecasts over West Africa itself but may also affect remote regions, as waves originating from convective heating are badly represented. Here we investigate those remote forecast impacts based on daily initialised 10-day forecasts for July 2016 using the ICON model. One set of simulations employs the default setup of the global model with a horizontal grid spacing of 13 km. It is compared with simulations using the 2-way nesting capability of ICON. A second model domain over West Africa (the nest) with 6.5 km grid spacing is sufficient to explicitly resolve MCSs in this region. In the 2-way nested simulations, the prognostic variables of the global model are influenced by the results of the nest through relaxation. The nest with explicit convection is able to reproduce single MCSs much more realistically compared to the stand-alone global simulation with parameterised convection. Explicit convection leads to cooler temperatures in the lower troposphere (below 500 hPa) over the northern Sahel due to stronger evaporational cooling. Overall, the feedback of dynamic variables from the nest to the global model shows clear positive effects when evaluating the output of the global domain of the 2-way nesting simulation and the output of the stand-alone global model with ERA-Interim re-analyses. Averaged over the 2-way nested region, bias and root mean squared error (RMSE) of temperature, geopotential, wind and relative humidity are significantly reduced in

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

International Nuclear Information System (INIS)

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

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

Directory of Open Access Journals (Sweden)

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.

Simulation and analysis of the mesoscale circulation in the northwestern Mediterranean Sea

Directory of Open Access Journals (Sweden)

V. Echevin

Full Text Available The large-scale and mesoscale circulation of the northwestern Mediterranean Sea are simulated with an eddy-resolving primitive-equation regional model (RM of 1/16° resolution embedded in a general circulation model (GM of the Mediterranean Sea of 1/8° resolution. The RM is forced by a monthly climatology of heat fluxes, precipitation and wind stress. The GM, which uses the same atmospheric forcing, provides initial and boundary conditions for the RM. Analysis of the RM results shows that several realistic features of the large-scale and mesoscale circulation are evident in this region. The mean cyclonic circulation is in good agreement with observations. Mesoscale variability is intense along the coasts of Sardinia and Corsica, in the Gulf of Lions and in the Catalan Sea. The length scales of the Northern Current meanders along the Provence coast and in the Gulf of Lions’ shelf are in good agreement with observations. Winter Intermediate Water is formed along most of the north-coast shelves, between the Gulf of Genoa and Cape Creus. Advection of this water by the mean cyclonic circulation generates a complex eddy field in the Catalan Sea. Intense anticyclonic eddies are generated northeast of the Balearic Islands. These results are in good agreement with mesoscale activity inferred from satellite altimetric data. This work demonstrates the feasibility of a down-scaling system composed of a general-circulation, a regional and a coastal model, which is one of the goals of the Mediterranean Forecasting System Pilot Project.

Key words. Oceanography: physical (currents; eddies and mesoscale processes; general circulation

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

Science.gov (United States)

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

Lightning characteristics of derecho producing mesoscale convective systems

Science.gov (United States)

Bentley, Mace L.; Franks, John R.; Suranovic, Katelyn R.; Barbachem, Brent; Cannon, Declan; Cooper, Stonie R.

2016-06-01

Derechos, or widespread, convectively induced wind storms, are a common warm season phenomenon in the Central and Eastern United States. These damaging and severe weather events are known to sweep quickly across large spatial regions of more than 400 km and produce wind speeds exceeding 121 km h-1. Although extensive research concerning derechos and their parent mesoscale convective systems already exists, there have been few investigations of the spatial and temporal distribution of associated cloud-to-ground lightning with these events. This study analyzes twenty warm season (May through August) derecho events between 2003 and 2013 in an effort to discern their lightning characteristics. Data used in the study included cloud-to-ground flash data derived from the National Lightning Detection Network, WSR-88D imagery from the University Corporation for Atmospheric Research, and damaging wind report data obtained from the Storm Prediction Center. A spatial and temporal analysis was conducted by incorporating these data into a geographic information system to determine the distribution and lightning characteristics of the environments of derecho producing mesoscale convective systems. Primary foci of this research include: (1) finding the approximate size of the lightning activity region for individual and combined event(s); (2) determining the intensity of each event by examining the density and polarity of lightning flashes; (3) locating areas of highest lightning flash density; and (4) to provide a lightning spatial analysis that outlines the temporal and spatial distribution of flash activity for particularly strong derecho producing thunderstorm episodes.

Contribution of mesoscale eddies to Black Sea ventilation

Science.gov (United States)

Capet, Arthur; Mason, Evan; Pascual, Ananda; Grégoire, Marilaure

2017-04-01

The shoaling of the Black Sea oxycline is one of the most urgent environmental issues in the Black Sea. The permanent oxycline derives directly from the Black Sea permanent stratification and has shoaled alarmingly in the last decades, due to a shifting balance between oxygen consumption and ventilation processes (Capet et al. 2016). The understanding of this balance is thus of the utmost importance and requires to quantify 1) the export of nutrients and organic materials from the shelf regions to the open sea and 2) the ventilation processes. These two processes being influenced by mesoscale features, it is critical to understand the role of the semi-permanent mesoscale structures in horizontal (center/periphery) and vertical (diapycnal and isopycnal) exchanges. A useful insight can be obtained by merging observations from satellite altimeter and in situ profilers (ARGO). In such composite analyses, eddies are first automatically identified and tracked from altimeter data (Mason et al. 2014, py-eddy-tracker). Vertical ARGO profiles are then expressed in terms of their position relative to eddy centers and radii. Derived statistics indicate how consistently mesoscale eddies alter the vertical structure, and provide a deeper understanding of the associated horizontal and vertical fluxes. However, this data-based approach is limited in the Black Sea due to the lower quality of gridded altimetric products in the vicinity of the coast, where semi-permanent mesoscale structures prevail. To complement the difficult analysis of this sparse dataset, a compositing methodology. is also applied to model outputs from the 5km GHER-BHAMBI Black Sea implementation (CMEMS BS-MFC). Characteristic biogeochemical anomalies associated with eddies in the model are analyzed per se, and compared to the observation-based analysis. Capet, A., Stanev, E. V., Beckers, J.-M., Murray, J. W., and Grégoire, M.: Decline of the Black Sea oxygen inventory, Biogeosciences, 13, 1287-1297, doi:10

Probabilistic flood damage modelling at the meso-scale

Science.gov (United States)

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.

Recipes for correcting the impact of effective mesoscale resolution on the estimation of extreme winds

DEFF Research Database (Denmark)

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...

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

African Journals Online (AJOL)

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

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

Science.gov (United States)

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

A reactive transport model for Marcellus shale weathering

Science.gov (United States)

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

2017-11-01

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

Mesoscale mixing of the Denmark Strait Overflow in the Irminger Basin

Science.gov (United States)

Koszalka, Inga M.; Haine, Thomas W. N.; Magaldi, Marcello G.

2017-04-01

The Denmark Strait Overflow (DSO) is a major export route for dense waters from the Nordic Seas forming the lower limb of the Atlantic Meridional Overturning Circulation, an important element of the climate system. Mixing processes along the DSO pathway influence its volume transport and properties contributing to the variability of the deep overturning circulation. They are poorly sampled by observations, however, which hinders development of a proper DSO representation in global circulation models. We employ a high resolution regional ocean model of the Irminger Basin to quantify impact of the mesoscale flows on DSO mixing focusing on geographical localization and the time-modulation of water property changes. The model reproduces the observed bulk warming of the DSO plume 100-200 km downstream of the Denmark Strait sill. It also reveals that mesoscale variability of the overflow ('DSO-eddies', of 20-30 km extent and a time scale of 2-5 day) modulates water property changes and turbulent mixing, diagnosed with the vertical shear of horizontal velocity and the eddy heat flux divergence. The space-time localization of the DSO mixing and warming and the role of coherent mesoscale structures should be explored by turbulence measurements and factored into the coarse circulation models.

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

Science.gov (United States)

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.

A three-dimensional ocean mesoscale simulation using data from the SEMAPHORE experiment: Mixed layer heat budget

Science.gov (United States)

Caniaux, Guy; Planton, Serge

1998-10-01

A primitive equation model is used to simulate the mesoscale circulation associated with a portion of the Azores Front investigated during the intensive observation period (IOP) of the Structure des Echanges Mer-Atmosphere, Proprietes des Heterogeneites Oceaniques: Recherche Experimentale (SEMAPHORE) experiment in fall 1993. The model is a mesoscale version of the ocean general circulation model (OGCM) developed at the Laboratoire d'Océanographie Dynamique et de Climatologie (LODYC) in Paris and includes open lateral boundaries, a 1.5-level-order turbulence closure scheme, and fine mesh resolution (0.11° for latitude and 0.09° for longitude). The atmospheric forcing is provided by satellite data for the solar and infrared fluxes and by analyzed (or reanalyzed for the wind) atmospheric data from the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model. The extended data set collected during the IOP of SEMAPHORE enables a detailed initialization of the model, a coupling with the rest of the basin through time dependent open boundaries, and a model/data comparison for validation. The analysis of model outputs indicates that most features are in good agreement with independent available observations. The surface front evolution is subject to an intense deformation different from that of the deep front system, which evolves only weakly. An estimate of the upper layer heat budget is performed during the 22 days of the integration of the model. Each term of this budget is analyzed according to various atmospheric events that occurred during the experiment, such as the passage of a strong storm. This facilitates extended estimates of mixed layer or relevant surface processes beyond those which are obtainable directly from observations. Surface fluxes represent 54% of the heat loss in the mixed layer and 70% in the top 100-m layer, while vertical transport at the mixed layer bottom accounts for 31% and three-dimensional processes account for 14%.

Aerosol radiative effects on mesoscale cloud-precipitation variables over Northeast Asia during the MAPS-Seoul 2015 campaign

Science.gov (United States)

Park, Shin-Young; Lee, Hyo-Jung; Kang, Jeong-Eon; Lee, Taehyoung; Kim, Cheol-Hee

2018-01-01

The online model, Weather Research and Forecasting Model with Chemistry (WRF-Chem) is employed to interpret the effects of aerosol-cloud-precipitation interaction on mesoscale meteorological fields over Northeast Asia during the Megacity Air Pollution Study-Seoul (MAPS-Seoul) 2015 campaign. The MAPS-Seoul campaign is a pre-campaign of the Korea-United States Air Quality (KORUS-AQ) campaign conducted over the Korean Peninsula. We validated the WRF-Chem simulations during the campaign period, and analyzed aerosol-warm cloud interactions by diagnosing both aerosol direct, indirect, and total effects. The results demonstrated that aerosol directly decreased downward shortwave radiation up to -44% (-282 W m-2) for this period and subsequently increased downward longwave radiation up to +15% (∼52 W m-2) in the presence of low-level clouds along the thematic area. Aerosol increased cloud fraction indirectly up to ∼24% with the increases of both liquid water path and the droplet number mixing ratio. Precipitation properties were altered both directly and indirectly. Direct effects simply changed cloud-precipitation quantities via simple updraft process associated with perturbed radiation and temperature, while indirect effects mainly suppressed precipitation, but sometimes increased precipitation in the higher relative humidity atmosphere or near vapor-saturated condition. The total aerosol effects caused a time lag of the precipitation rate with the delayed onset time of up to 9 h. This implies the importance of aerosol effects in improving mesoscale precipitation rate prediction in the online approach in the presence of non-linear warm cloud.

Modeling the influence of organic acids on soil weathering

Science.gov (United States)

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

2014-01-01

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

An equilibrium pricing model for weather derivatives in a multi-commodity setting

International Nuclear Information System (INIS)

Lee, Yongheon; Oren, Shmuel S.

2009-01-01

Many industries are exposed to weather risk. Weather derivatives can play a key role in hedging and diversifying such risk because the uncertainty in a company's profit function can be correlated to weather condition which affects diverse industry sectors differently. Unfortunately the weather derivatives market is a classical example of an incomplete market that is not amenable to standard methodologies used for derivative pricing in complete markets. In this paper, we develop an equilibrium pricing model for weather derivatives in a multi-commodity setting. The model is constructed in the context of a stylized economy where agents optimize their hedging portfolios which include weather derivatives that are issued in a fixed quantity by a financial underwriter. The supply and demand resulting from hedging activities and the supply by the underwriter are combined in an equilibrium pricing model under the assumption that all agents maximize some risk averse utility function. We analyze the gains due to the inclusion of weather derivatives in hedging portfolios and examine the components of that gain attributable to hedging and to risk sharing. (author)

Detailed modeling of mountain wave PSCs

Directory of Open Access Journals (Sweden)

S. Fueglistaler

2003-01-01

Full Text Available Polar stratospheric clouds (PSCs play a key role in polar ozone depletion. In the Arctic, PSCs can occur on the mesoscale due to orographically induced gravity waves. Here we present a detailed study of a mountain wave PSC event on 25-27 January 2000 over Scandinavia. The mountain wave PSCs were intensively observed by in-situ and remote-sensing techniques during the second phase of the SOLVE/THESEO-2000 Arctic campaign. We use these excellent data of PSC observations on 3 successive days to analyze the PSCs and to perform a detailed comparison with modeled clouds. We simulated the 3-dimensional PSC structure on all 3 days with a mesoscale numerical weather prediction (NWP model and a microphysical box model (using best available nucleation rates for ice and nitric acid trihydrate particles. We show that the combined mesoscale/microphysical model is capable of reproducing the PSC measurements within the uncertainty of data interpretation with respect to spatial dimensions, temporal development and microphysical properties, without manipulating temperatures or using other tuning parameters. In contrast, microphysical modeling based upon coarser scale global NWP data, e.g. current ECMWF analysis data, cannot reproduce observations, in particular the occurrence of ice and nitric acid trihydrate clouds. Combined mesoscale/microphysical modeling may be used for detailed a posteriori PSC analysis and for future Arctic campaign flight and mission planning. The fact that remote sensing alone cannot further constrain model results due to uncertainities in the interpretation of measurements, underlines the need for synchronous in-situ PSC observations in campaigns.

Acoustic Characterization of Mesoscale Objects

Energy Technology Data Exchange (ETDEWEB)

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.

Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool

Directory of Open Access Journals (Sweden)

Swagata Payra

2014-01-01

Full Text Available The prediction of fog onset remains difficult despite the progress in numerical weather prediction. It is a complex process and requires adequate representation of the local perturbations in weather prediction models. It mainly depends upon microphysical and mesoscale processes that act within the boundary layer. This study utilizes a multirule based diagnostic (MRD approach using postprocessing of the model simulations for fog predictions. The empiricism involved in this approach is mainly to bridge the gap between mesoscale and microscale variables, which are related to mechanism of the fog formation. Fog occurrence is a common phenomenon during winter season over Delhi, India, with the passage of the western disturbances across northwestern part of the country accompanied with significant amount of moisture. This study implements the above cited approach for the prediction of occurrences of fog and its onset time over Delhi. For this purpose, a high resolution weather research and forecasting (WRF model is used for fog simulations. The study involves depiction of model validation and postprocessing of the model simulations for MRD approach and its subsequent application to fog predictions. Through this approach model identified foggy and nonfoggy days successfully 94% of the time. Further, the onset of fog events is well captured within an accuracy of 30–90 minutes. This study demonstrates that the multirule based postprocessing approach is a useful and highly promising tool in improving the fog predictions.

Unifying Inference of Meso-Scale Structures in Networks.

Science.gov (United States)

Tunç, Birkan; Verma, Ragini

2015-01-01

Networks are among the most prevalent formal representations in scientific studies, employed to depict interactions between objects such as molecules, neuronal clusters, or social groups. Studies performed at meso-scale that involve grouping of objects based on their distinctive interaction patterns form one of the main lines of investigation in network science. In a social network, for instance, meso-scale structures can correspond to isolated social groupings or groups of individuals that serve as a communication core. Currently, the research on different meso-scale structures such as community and core-periphery structures has been conducted via independent approaches, which precludes the possibility of an algorithmic design that can handle multiple meso-scale structures and deciding which structure explains the observed data better. In this study, we propose a unified formulation for the algorithmic detection and analysis of different meso-scale structures. This facilitates the investigation of hybrid structures that capture the interplay between multiple meso-scale structures and statistical comparison of competing structures, all of which have been hitherto unavailable. We demonstrate the applicability of the methodology in analyzing the human brain network, by determining the dominant organizational structure (communities) of the brain, as well as its auxiliary characteristics (core-periphery).

Unifying Inference of Meso-Scale Structures in Networks.

Directory of Open Access Journals (Sweden)

Birkan Tunç

Full Text Available Networks are among the most prevalent formal representations in scientific studies, employed to depict interactions between objects such as molecules, neuronal clusters, or social groups. Studies performed at meso-scale that involve grouping of objects based on their distinctive interaction patterns form one of the main lines of investigation in network science. In a social network, for instance, meso-scale structures can correspond to isolated social groupings or groups of individuals that serve as a communication core. Currently, the research on different meso-scale structures such as community and core-periphery structures has been conducted via independent approaches, which precludes the possibility of an algorithmic design that can handle multiple meso-scale structures and deciding which structure explains the observed data better. In this study, we propose a unified formulation for the algorithmic detection and analysis of different meso-scale structures. This facilitates the investigation of hybrid structures that capture the interplay between multiple meso-scale structures and statistical comparison of competing structures, all of which have been hitherto unavailable. We demonstrate the applicability of the methodology in analyzing the human brain network, by determining the dominant organizational structure (communities of the brain, as well as its auxiliary characteristics (core-periphery.

Modeling and Forecasting Average Temperature for Weather Derivative Pricing

Directory of Open Access Journals (Sweden)

Zhiliang Wang

2015-01-01

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

DEM investigation of weathered rocks using a novel bond contact model

Directory of Open Access Journals (Sweden)

Zhenming Shi

2015-06-01

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

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

Science.gov (United States)

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

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

Science.gov (United States)

Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje

2017-09-01

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

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

Science.gov (United States)

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

2013-12-01

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

On Improving 4-km Mesoscale Model Simulations

Science.gov (United States)

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

Evaluation of high-resolution forecasts with the non-hydrostaticnumerical weather prediction model Lokalmodell for urban air pollutionepisodes in Helsinki, Oslo and Valencia

Directory of Open Access Journals (Sweden)

B. Fay

2006-01-01

Full Text Available The operational numerical weather prediction model Lokalmodell LM with 7,km horizontal resolution was evaluated for forecasting meteorological conditions during observed urban air pollution episodes. The resolution was increased to experimental 2.8 km and 1.1 km resolution by one-way interactive nesting without introducing urbanisation of physiographic parameters or parameterisations. The episodes examined are two severe winter inversion-induced episodes in Helsinki in December 1995 and Oslo in January 2003, three suspended dust episodes in spring and autumn in Helsinki and Oslo, and a late-summer photochemical episode in the Valencia area. The evaluation was basically performed against observations and radiosoundings and focused on the LM skill at forecasting the key meteorological parameters characteristic for the specific episodes. These included temperature inversions, atmospheric stability and low wind speeds for the Scandinavian episodes and the development of mesoscale recirculations in the Valencia area. LM forecasts often improved due to higher model resolution especially in mountainous areas like Oslo and Valencia where features depending on topography like temperature, wind fields and mesoscale valley circulations were better described. At coastal stations especially in Helsinki, forecast gains were due to the improved physiographic parameters (land fraction, soil type, or roughness length. The Helsinki and Oslo winter inversions with extreme nocturnal inversion strengths of 18°C were not sufficiently predicted with all LM resolutions. In Helsinki, overprediction of surface temperatures and low-level wind speeds basically led to underpredicted inversion strength. In the Oslo episode, the situation was more complex involving erroneous temperature advection and mountain-induced effects for the higher resolutions. Possible explanations include the influence of the LM treatment of snow cover, sea ice and stability-dependence of transfer

ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS

Energy Technology Data Exchange (ETDEWEB)

Chiswell, S.; Buckley, R.

2009-01-15

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

Implementation of meso-scale radioactive dispersion model for GPU

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

Riette, Sébastien; Lac, Christine

2016-08-01

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

Space Weather Models and Their Validation and Verification at the CCMC

Science.gov (United States)

Hesse, Michael

2010-01-01

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

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

NARCIS (Netherlands)

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

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

Science.gov (United States)

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

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

International Nuclear Information System (INIS)

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

A Reactive Transport Model for Marcellus Shale Weathering

Science.gov (United States)

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

2017-12-01

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

The characteristics of local atmospheric circulation around the Wolsung NPP in Korea

International Nuclear Information System (INIS)

Lee, G.B.; Lee, M.C.; Song, Y.I.

1998-01-01

The transport of air pollutants in coastal regions has been known to be strongly affected by the mesoscale atmospheric circulations such as sea-land breezes. These mesoscale atmospheric circulations depend on synoptic weather conditions. In this study, a three-dimensional sea-land breeze model was developed to evaluate the effects of the sea and land breezes on the atmospheric dispersion of radioactive materials released from nuclear power plants in Korea. In the model, the hydrostatic primitive equations in the terrain-following coordinate system were used. The mesoscale atmospheric circulation simulation were carried out under various synoptic weather conditions for all seasons around the Wolsung nuclear power plant site

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

OpenAIRE

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...

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

Science.gov (United States)

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

2013-04-01

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

Weather forecasting based on hybrid neural model

Science.gov (United States)

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

2017-11-01

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

Modeling extreme "Carrington-type" space weather events using three-dimensional global MHD simulations

Science.gov (United States)

Ngwira, Chigomezyo M.; Pulkkinen, Antti; Kuznetsova, Maria M.; Glocer, Alex

2014-06-01

There is a growing concern over possible severe societal consequences related to adverse space weather impacts on man-made technological infrastructure. In the last two decades, significant progress has been made toward the first-principles modeling of space weather events, and three-dimensional (3-D) global magnetohydrodynamics (MHD) models have been at the forefront of this transition, thereby playing a critical role in advancing our understanding of space weather. However, the modeling of extreme space weather events is still a major challenge even for the modern global MHD models. In this study, we introduce a specially adapted University of Michigan 3-D global MHD model for simulating extreme space weather events with a Dst footprint comparable to the Carrington superstorm of September 1859 based on the estimate by Tsurutani et. al. (2003). Results are presented for a simulation run with "very extreme" constructed/idealized solar wind boundary conditions driving the magnetosphere. In particular, we describe the reaction of the magnetosphere-ionosphere system and the associated induced geoelectric field on the ground to such extreme driving conditions. The model setup is further tested using input data for an observed space weather event of Halloween storm October 2003 to verify the MHD model consistence and to draw additional guidance for future work. This extreme space weather MHD model setup is designed specifically for practical application to the modeling of extreme geomagnetically induced electric fields, which can drive large currents in ground-based conductor systems such as power transmission grids. Therefore, our ultimate goal is to explore the level of geoelectric fields that can be induced from an assumed storm of the reported magnitude, i.e., Dst˜=-1600 nT.

Mesoscale Eddies in the Solomon Sea

Science.gov (United States)

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).

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

Science.gov (United States)

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

2014-10-01

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

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

Science.gov (United States)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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

2018-02-01

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

Evaluation of a mesoscale dispersion modelling tool during the CAPITOUL experiment

Science.gov (United States)

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

Mesoscale modelling methodology based on nudging to increase accuracy in WRA

Science.gov (United States)

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

A mini-max principle for drift waves and mesoscale fluctuations

International Nuclear Information System (INIS)

Itoh, S-I; Itoh, K

2011-01-01

A mini-max principle for the system of the drift waves and mesoscale fluctuations (e.g. zonal flows, etc) is studied. For the system of model equations a Lyapunov function is constructed, which takes the minimum when the stationary state is realized. The dynamical evolution describes the access to the state that is realized. The competition between different mesoscale fluctuations is explained. The origins of irreversibility that cause an approach to the stationary state are discussed. A selection rule among fluctuations is derived, and conditions, under which different kinds of mesocale fluctuations coexist, are investigated. An analogy of this minimum principle to the principle of 'minimum Helmholtz free energy' in thermal equilibrium is shown.

Observations of mesoscale and boundary-layer scale circulations affecting dust transport and uplift over the Sahara

Directory of Open Access Journals (Sweden)

J. H. Marsham

2008-12-01

Full Text Available Observations of the Saharan boundary layer, made during the GERBILS field campaign, show that mesoscale land surface temperature variations (which were related to albedo variations induced mesoscale circulations. With weak winds along the aircraft track, land surface temperature anomalies with scales of greater than 10 km are shown to significantly affect boundary-layer temperatures and winds. Such anomalies are expected to affect the vertical mixing of the dusty and weakly stratified Saharan Residual Layer (SRL. Mesoscale variations in winds are also shown to affect dust loadings in the boundary layer.

Using the aircraft observations and data from the COSMO model, a region of local dust uplift, with strong along-track winds, was identified in one low-level flight. Large eddy model (LEM simulations based on this location showed linearly organised boundary-layer convection. Calculating dust uplift rates from the LEM wind field showed that the boundary-layer convection increased uplift by approximately 30%, compared with the uplift rate calculated neglecting the convection. The modelled effects of boundary-layer convection on uplift are shown to be larger when the boundary-layer wind is decreased, and most significant when the mean wind is below the threshold for dust uplift and the boundary-layer convection leads to uplift which would not otherwise occur.

Both the coupling of albedo features to the atmosphere on the mesoscale, and the enhancement of dust uplift by boundary-layer convection are unrepresented in many climate models, but may have significant impacts on the vertical transport and uplift of desert dust. Mesoscale effects in particular tend to be difficult to parametrise.

Multiscale Modeling of Mesoscale and Interfacial Phenomena

Science.gov (United States)

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

Towards high resolution mapping of 3-D mesoscale dynamics from observations

Directory of Open Access Journals (Sweden)

B. Buongiorno Nardelli

2012-10-01

Full Text Available The MyOcean R&D project MESCLA (MEsoSCaLe dynamical Analysis through combined model, satellite and in situ data was devoted to the high resolution 3-D retrieval of tracer and velocity fields in the oceans, based on the combination of in situ and satellite observations and quasi-geostrophic dynamical models. The retrieval techniques were also tested and compared with the output of a primitive equation model, with particular attention to the accuracy of the vertical velocity field as estimated through the Q vector formulation of the omega equation. The project focused on a test case, covering the region where the Gulf Stream separates from the US East Coast. This work demonstrated that innovative methods for the high resolution mapping of 3-D mesoscale dynamics from observations can be used to build the next generations of operational observation-based products.

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

International Nuclear Information System (INIS)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-06-28

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

Delayed shear enhancement in mesoscale atmospheric dispersion

Energy Technology Data Exchange (ETDEWEB)

Moran, M.D. [Atmospheric Environment Service, Ontario (Canada); Pielke, R.A. [Colorado State Univ., Fort Collins, CO (United States)

1994-12-31

Mesoscale atmospheric dispersion (MAD) is more complicated than smaller-scale dispersion because the mean wind field can no longer be considered steady or horizontally homogeneous over mesoscale time and space scales. Wind shear also plays a much more important role on the mesoscale: horizontal dispersion can be enhanced and often dominated by vertical wind shear on these scales through the interaction of horizontal differential advection and vertical mixing. Just over 30 years ago, Pasquill suggested that this interaction need not be simultaneous and that the combination of differential horizontal advection with delayed or subsequent vertical mixing could maintain effective horizontal diffusion in spite of temporal or spatial reductions in boundary-layer turbulence intensity. This two-step mechanism has not received much attention since then, but a recent analysis of observations from and numerical simulations of two mesoscale tracer experiments suggests that delayed shear enhancement can play an important role in MAD. This paper presents an overview of this analysis, with particular emphasis on the influence of resolvable vertical shear on MAD in these two case studies and the contributions made by delayed shear enhancement.

Geodetic Space Weather Monitoring by means of Ionosphere Modelling

Science.gov (United States)

Schmidt, Michael

2017-04-01

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

Micro- and meso-scale effects of forested terrain

DEFF Research Database (Denmark)

Dellwik, Ebba; Mann, Jakob; Sogachev, Andrey

2011-01-01

scales are the height of the planetary boundary layer and the Monin-Obukhov length, which both are related to the energy balance of the surface. Examples of important micro- and meso-scale effects of forested terrain are shown using data and model results from recent and ongoing experiments. For micro......The height and rotor diameter of modern wind turbines are so extensive, that the wind conditions they encounter often are well above the surface layer, where traditionally it is assumed that wind direction and turbulent fluxes are constant with respect to height, if the surface is homogenous....... Deviations from the requirement of homogeneity are often the focus of micro-scale studies in forested areas. Yet, to explain the wind climate in the relevant height range for turbines, it is necessary to also account for the length scales that are important parameters for the meso-scale flow. These length...

Linking the M&Rfi Weather Generator with Agrometeorological Models

Science.gov (United States)

Dubrovsky, Martin; Trnka, Miroslav

2015-04-01

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

Supercomputing for weather and climate modelling: convenience or necessity

CSIR Research Space (South Africa)

Landman, WA

2009-12-01

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

Evaluating the Contribution of NASA Remotely-Sensed Data Sets on a Convection-Allowing Forecast Model

Science.gov (United States)

Zavodsky, Bradley T.; Case, Jonathan L.; Molthan, Andrew L.

2012-01-01

The Short-term Prediction Research and Transition (SPoRT) Center is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service forecast offices. SPoRT provides real-time NASA products and capabilities to help its partners address specific operational forecast challenges. One challenge that forecasters face is using guidance from local and regional deterministic numerical models configured at convection-allowing resolution to help assess a variety of mesoscale/convective-scale phenomena such as sea-breezes, local wind circulations, and mesoscale convective weather potential on a given day. While guidance from convection-allowing models has proven valuable in many circumstances, the potential exists for model improvements by incorporating more representative land-water surface datasets, and by assimilating retrieved temperature and moisture profiles from hyper-spectral sounders. In order to help increase the accuracy of deterministic convection-allowing models, SPoRT produces real-time, 4-km CONUS forecasts using a configuration of the Weather Research and Forecasting (WRF) model (hereafter SPoRT-WRF) that includes unique NASA products and capabilities including 4-km resolution soil initialization data from the Land Information System (LIS), 2-km resolution SPoRT SST composites over oceans and large water bodies, high-resolution real-time Green Vegetation Fraction (GVF) composites derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and retrieved temperature and moisture profiles from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI). NCAR's Model Evaluation Tools (MET) verification package is used to generate statistics of model performance compared to in situ observations and rainfall analyses for three months during the summer of 2012 (June-August). Detailed analyses of specific severe weather outbreaks during the summer

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

Science.gov (United States)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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.

From Quanta to the Continuum: Opportunities for Mesoscale Science

Energy Technology Data Exchange (ETDEWEB)

Crabtree, George [Argonne National Lab. (ANL), Argonne, IL (United States); Sarrao, John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Alivisatos, Paul [Univ. of California, Berkeley, CA (United States); Barletta, William [MIT (Massachusetts Inst. of Technology), Cambridge, MA (United States); Bates, Frank [Univ. of Minnesota, Minneapolis, MN (United States); Brown, Gordon [Stanford Univ., CA (United States); French, Roger [Case Western Reserve Univ., Cleveland, OH (United States); Greene, Laura [Univ. of Illinois, Urbana, IL (United States); Hemminger, John [Univ. of California, Irvine, CA (United States); Kastner, Marc [MIT (Massachusetts Inst. of Technology), Cambridge, MA (United States); Kay, Bruce [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lewis, Jennifer [Univ. of Illinois, Urbana, IL (United States); Ratner, Mark [Northwestern Univ., Evanston, IL (United States); Anthony, Rollett [Carnegie Mellon Univ., Pittsburgh, PA (United States); Rubloff, Gary [University of Maryland, College Park, MD (United States); Spence, John [Arizona State Univ., Mesa, AZ (United States); Tobias, Douglas [Univ. of California, Irvine, CA (United States); Tranquada, John [Brookhaven National Lab. (BNL), Upton, NY (United States)

2012-09-01

This report explores the opportunity and defines the research agenda for mesoscale science—discovering, understanding, and controlling interactions among disparate systems and phenomena to reach the full potential of materials complexity and functionality. The ability to predict and control mesoscale phenomena and architectures is essential if atomic and molecular knowledge is to blossom into a next generation of technology opportunities, societal benefits, and scientific advances.. The body of this report outlines the need, the opportunities, the challenges, and the benefits of mastering mesoscale science.

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

Science.gov (United States)

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

2009-01-01

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

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

Science.gov (United States)

Yokota, Kohei; Kanzaki, Yoshiki; Murakami, Takashi

2013-09-01

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

Creating Weather System Ensembles Through Synergistic Process Modeling and Machine Learning

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

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.

Assessment of MARMOT. A Mesoscale Fuel Performance Code

Energy Technology Data Exchange (ETDEWEB)

Tonks, M. R. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Schwen, D. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhang, Y. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Chakraborty, P. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Bai, X. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Fromm, B. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Yu, J. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Teague, M. C. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Andersson, D. A. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-04-01

MARMOT is the mesoscale fuel performance code under development as part of the US DOE Nuclear Energy Advanced Modeling and Simulation Program. In this report, we provide a high level summary of MARMOT, its capabilities, and its current state of validation. The purpose of MARMOT is to predict the coevolution of microstructure and material properties of nuclear fuel and cladding. It accomplished this using the phase field method coupled to solid mechanics and heat conduction. MARMOT is based on the Multiphysics Object-Oriented Simulation Environment (MOOSE), and much of its basic capability in the areas of the phase field method, mechanics, and heat conduction come directly from MOOSE modules. However, additional capability specific to fuel and cladding is available in MARMOT. While some validation of MARMOT has been completed in the areas of fission gas behavior and grain growth, much more validation needs to be conducted. However, new mesoscale data needs to be obtained in order to complete this validation.

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

Science.gov (United States)

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

2018-01-01

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

Hindcast experiments of the derecho in Estonia on 08 August, 2010: Modelling derecho with NWP model HARMONIE

Science.gov (United States)

Toll, Velle; Männik, Aarne; Luhamaa, Andres; Rõõm, Rein

2015-05-01

On August 8, 2010, a derecho swept over Northern Europe, causing widespread wind damage and more than 2 million Euros in economic loss in Estonia during its most destructive stage. This paper presents a modelling study of the derecho-producing storm utilising the Hirlam Aladin Research for Mesoscale Operational Numerical Weather Prediction in Europe (HARMONIE) model. The model setup is chosen to mimic near-future, nearly kilometre-scale, operational environments in European national weather services. The model simulations are compared to remote sensing and in situ observations. The HARMONIE model is capable of reproducing the wind gust severity and precipitation intensity. Moreover, 2.5-km grid spacing is shown to be sufficient for producing a reliable signal of the severe convective storm. Storm dynamics are well simulated, including the rear inflow jet. Although the model performance is promising, a strong dependence on the initial data, a weak trailing stratiform precipitation region and an incorrect timing of the storm are identified.

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

Science.gov (United States)

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

2009-12-01

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

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

Science.gov (United States)

2010-12-01

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

Assessing the value of increased model resolution in forecasting fire danger

Science.gov (United States)

Jeanne Hoadley; Miriam Rorig; Ken Westrick; Larry Bradshaw; Sue Ferguson; Scott Goodrick; Paul Werth

2003-01-01

The fire season of 2000 was used as a case study to assess the value of increasing mesoscale model resolution for fire weather and fire danger forecasting. With a domain centered on Western Montana and Northern Idaho, MM5 simulations were run at 36, 12, and 4-km resolutions for a 30 day period at the height of the fire season. Verification analyses for meteorological...

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Simulation of mesoscale circulation in the Tatar Strait of the Japan Sea

Science.gov (United States)

Ponomarev, V. I.; Fayman, P. A.; Prants, S. V.; Budyansky, M. V.; Uleysky, M. Yu.

2018-06-01

The eddy-resolved ocean circulation model RIAMOM (Lee et al., 2003) is used to analyze seasonal variability of mesoscale circulation in the Tatar Strait of the Japan Sea. The model domain is a vast area including the northern Japan Sea, Okhotsk Sea and adjacent region in the Pacific Ocean. A numerical experiment with a horizontal 1/18° resolution has been carried out under realistic meteorological conditions from the ECMWF ERA-40 reanalysis with restoring of surface temperature and salinity. The simulated seasonal variability of both the current system and mesoscale eddy dynamics in the Tatar Strait is in a good agreement with temperature and salinity distributions of oceanographic observation data collected during various seasons and years. Two general circulation regimes in the Strait have been found. The circulation regime changes from summer to winter due to seasonal change of the North Asian Monsoon. On a synoptic time scale, the similar change of the circulation regime occurs due to change of the southeastern wind to the northwestern one when the meteorological situation with an anticyclone over the Okhotsk Sea changes to that with a strong cyclone. The Lagrangian maps illustrate seasonal changes in direction of the main currents and in polarity and location of mesoscale eddies in the Strait.

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

Krissansen-Totton, Joshua; Catling, David C

2017-05-22

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

Experimental Study on Meso-Scale Milling Process Using Nanofluid Minimum Quantity Lubrication

International Nuclear Information System (INIS)

Lee, P. H.; Nam, T. S.; Li, Cheng Jun; Lee, S. W.

2010-01-01

This paper present the characteristics of micro- and meso-scale milling processes in which compressed cold air, minimum quantity lubrication (MQL) and MoS 2 nanofluid MQL are used. For process characterization, the micro and meso-scale milling experiments are conducted using desktop meso-scale machine tool system and the surface roughness is measured. The experimental results show that the use of compressed chilly air and nanofluid MQL in the micro- and meso-scale milling processes is effective in improving the surface finish

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

Science.gov (United States)

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

HIGH-RESOLUTION ATMOSPHERIC ENSEMBLE MODELING AT SRNL

Energy Technology Data Exchange (ETDEWEB)

Buckley, R.; Werth, D.; Chiswell, S.; Etherton, B.

2011-05-10

The High-Resolution Mid-Atlantic Forecasting Ensemble (HME) is a federated effort to improve operational forecasts related to precipitation, convection and boundary layer evolution, and fire weather utilizing data and computing resources from a diverse group of cooperating institutions in order to create a mesoscale ensemble from independent members. Collaborating organizations involved in the project include universities, National Weather Service offices, and national laboratories, including the Savannah River National Laboratory (SRNL). The ensemble system is produced from an overlapping numerical weather prediction model domain and parameter subsets provided by each contributing member. The coordination, synthesis, and dissemination of the ensemble information are performed by the Renaissance Computing Institute (RENCI) at the University of North Carolina-Chapel Hill. This paper discusses background related to the HME effort, SRNL participation, and example results available from the RENCI website.

Dynamical and statistical-dynamical modelling of wind farm flows with WRF

DEFF Research Database (Denmark)

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

2016-01-01

the power production of a target wind farm and (II) how large wind farms can get if they are to remain efficient and productive power generators. The modelling of wind farm wake flows is challenging, since it includes processes from the micro- to mesoscale meteorology. We use the Weather Research......A pledge to increase the share of renewable energies has led to a focus on offshore wind energy in many western European countries. With an increasing number of offshore wind farms to be installed it becomes important to understand (I) the degree to which wakes from neighbouring wind farms affect...... and Forecast (WRF) model that allows us to simulate mesoscale features of wind farm wakes. Its limited horizontal resolution – in microscale terms – however, requires flow characteristics, such as single turbine wakes, to be parametrised....

WRF Mesoscale Pre-Run for the Wind Atlas of Mexico

DEFF Research Database (Denmark)

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

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...

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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

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

International Nuclear Information System (INIS)

Ekman, Annica

2000-02-01

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

A statistical model to estimate the local vulnerability to severe weather

Science.gov (United States)

Pardowitz, Tobias

2018-06-01

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

Mesoscale Climate Evaluation Using Grid Computing

Science.gov (United States)

Campos Velho, H. F.; Freitas, S. R.; Souto, R. P.; Charao, A. S.; Ferraz, S.; Roberti, D. R.; Streck, N.; Navaux, P. O.; Maillard, N.; Collischonn, W.; Diniz, G.; Radin, B.

2012-04-01

The CLIMARS project is focused to establish an operational environment for seasonal climate prediction for the Rio Grande do Sul state, Brazil. The dynamical downscaling will be performed with the use of several software platforms and hardware infrastructure to carry out the investigation on mesoscale of the global change impact. The grid computing takes advantage of geographically spread out computer systems, connected by the internet, for enhancing the power of computation. The ensemble climate prediction is an appropriated application for processing on grid computing, because the integration of each ensemble member does not have a dependency on information from another ensemble members. The grid processing is employed to compute the 20-year climatology and the long range simulations under ensemble methodology. BRAMS (Brazilian Regional Atmospheric Model) is a mesoscale model developed from a version of the RAMS (from the Colorado State University - CSU, USA). BRAMS model is the tool for carrying out the dynamical downscaling from the IPCC scenarios. Long range BRAMS simulations will provide data for some climate (data) analysis, and supply data for numerical integration of different models: (a) Regime of the extreme events for temperature and precipitation fields: statistical analysis will be applied on the BRAMS data, (b) CCATT-BRAMS (Coupled Chemistry Aerosol Tracer Transport - BRAMS) is an environmental prediction system that will be used to evaluate if the new standards of temperature, rain regime, and wind field have a significant impact on the pollutant dispersion in the analyzed regions, (c) MGB-IPH (Portuguese acronym for the Large Basin Model (MGB), developed by the Hydraulic Research Institute, (IPH) from the Federal University of Rio Grande do Sul (UFRGS), Brazil) will be employed to simulate the alteration of the river flux under new climate patterns. Important meteorological input variables for the MGB-IPH are the precipitation (most relevant

Performance of WRF for Simulation of Mesoscale Meteorological Characteristics for Air Quality Assessment over Tropical Coastal City, Chennai

Science.gov (United States)

Madala, Srikanth; Srinivas, C. V.; Satyanarayana, A. N. V.

2018-01-01

The land-sea breezes (LSBs) play an important role in transporting air pollution from urban areas on the coast. In this study, the Advanced Research WRF (ARW) mesoscale model is used for predicting boundary layer features to understand the transport of pollution in different seasons over the coastal region of Chennai in Southern India. Sensitivity experiments are conducted with two non-local [Yonsei University (YSU) and Asymmetric Convective Model version 2 (ACM2)] and three turbulence kinetic energy (TKE) closure [Mellor-Yamada-Nakanishi and Niino Level 2.5 (MYNN2) and Mellor-Yamada-Janjic (MYJ) and quasi-normal scale elimination (QNSE)], planetary boundary layer (PBL) parameterization schemes for simulating the thermodynamic structure, and low-level atmospheric flow in different seasons. Comparison of simulations with observations from a global positioning system (GPS) radiosonde, meteorological tower, automated weather stations, and Doppler weather radar (DWR)-derived wind data reveals that the characteristics of LSBs vary widely in different seasons and are more prominent during the pre-monsoon and monsoon seasons (March-September) with large horizontal and vertical extents compared to the post-monsoon and winter seasons. The qualitative and quantitative results indicate that simulations with ACM2 followed by MYNN2 and YSU produced various features of the LSBs, boundary layer parameters and the thermo-dynamical structure in better agreement with observations than other tested physical parameterization schemes. Simulations revealed seasonal variation of onset time, vertical extent of LSBs, and mixed layer depth, which would influence the air pollution dispersion in different seasons over the study region.

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

Science.gov (United States)

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

1983-01-01

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

Regionalization of meso-scale physically based nitrogen modeling outputs to the macro-scale by the use of regression trees

Science.gov (United States)

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).

Low-level wind response to mesoscale pressure systems

Science.gov (United States)

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

1983-09-01

Observations are presented which show a strong correlation between low-level wind behaviour (e.g., rotation near the surface) and the passage of mesoscale pressure systems. The latter are associated with frontal transition zones, are dominated by a pressure-jump line and a mesoscale high pressure area, and produce locally large horizontal pressure gradients. The wind observations are simulated by specifying a time sequence of perturbation pressure gradient and subsequently solving the vertically-integrated momentum equations with appropriate initial conditions. Very good agreement is found between observed and calculated winds; in particular, (i) a 360 ° rotation in wind on passage of the mesoscale high; (ii) wind-shift lines produced dynamically by the pressure-jump line; (iii) rapid linear increase in wind speed on passage of the pressure jump.

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

Science.gov (United States)

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

2010-01-01

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

Time series regression model for infectious disease and weather.

Science.gov (United States)

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

2015-10-01

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

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

Science.gov (United States)

Ma, Xiaohui; Chang, Ping; Saravanan, R; Montuoro, Raffaele; Hsieh, Jen-Shan; Wu, Dexing; Lin, Xiaopei; Wu, Lixin; Jing, Zhao

2015-12-04

High-resolution satellite measurements of surface winds and sea-surface temperature (SST) reveal strong coupling between meso-scale ocean eddies and near-surface atmospheric flow over eddy-rich oceanic regions, such as the Kuroshio and Gulf Stream, highlighting the importance of meso-scale oceanic features in forcing the atmospheric planetary boundary layer (PBL). Here, we present high-resolution regional climate modeling results, supported by observational analyses, demonstrating that meso-scale SST variability, largely confined in the Kuroshio-Oyashio confluence region (KOCR), can further exert a significant distant influence on winter rainfall variability along the U.S. Northern Pacific coast. The presence of meso-scale SST anomalies enhances the diabatic conversion of latent heat energy to transient eddy energy, intensifying winter cyclogenesis via moist baroclinic instability, which in turn leads to an equivalent barotropic downstream anticyclone anomaly with reduced rainfall. The finding points to the potential of improving forecasts of extratropical winter cyclones and storm systems and projections of their response to future climate change, which are known to have major social and economic impacts, by improving the representation of ocean eddy-atmosphere interaction in forecast and climate models.

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

Science.gov (United States)

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

2017-12-01

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

Research Opportunities from Emerging Atmospheric Observing and Modeling Capabilities.

Science.gov (United States)

Dabberdt, Walter F.; Schlatter, Thomas W.

1996-02-01

The Second Prospectus Development Team (PDT-2) of the U.S. Weather Research Program was charged with identifying research opportunities that are best matched to emerging operational and experimental measurement and modeling methods. The overarching recommendation of PDT-2 is that inputs for weather forecast models can best be obtained through the use of composite observing systems together with adaptive (or targeted) observing strategies employing both in situ and remote sensing. Optimal observing systems and strategies are best determined through a three-part process: observing system simulation experiments, pilot field measurement programs, and model-assisted data sensitivity experiments. Furthermore, the mesoscale research community needs easy and timely access to the new operational and research datasets in a form that can readily be reformatted into existing software packages for analysis and display. The value of these data is diminished to the extent that they remain inaccessible.The composite observing system of the future must combine synoptic observations, routine mobile observations, and targeted observations, as the current or forecast situation dictates. High costs demand fuller exploitation of commercial aircraft, meteorological and navigation [Global Positioning System (GPS)] satellites, and Doppler radar. Single observing systems must be assessed in the context of a composite system that provides complementary information. Maintenance of the current North American rawinsonde network is critical for progress in both research-oriented and operational weather forecasting.Adaptive sampling strategies are designed to improve large-scale and regional weather prediction but they will also improve diagnosis and prediction of flash flooding, air pollution, forest fire management, and other environmental emergencies. Adaptive measurements can be made by piloted or unpiloted aircraft. Rawinsondes can be launched and satellites can be programmed to make

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

Directory of Open Access Journals (Sweden)

Dawei Han

2012-02-01

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

Mesoscale storm and dry period parameters from hourly precipitation data: program documentation

Energy Technology Data Exchange (ETDEWEB)

Thorp, J.M.

1984-09-01

Wet deposition of airborne chemical pollutants occurs primarily from precipitation. Precipitation rate, amount, duration, and location are important meteorological factors to be considered when attempting to understand the relationship of precipitation to pollutant deposition. The Pacific Northwest Laboratory (PNL) has conducted studies and experiments in numerous locations to collect data that can be incorporated into theories and models that attempt to describe the complex relationship between precipitation occurrence and chemical wet desposition. Model development often requires the use of average rather than random condition as input. To provide mean values of storm parameters, the task, Climatological Analysis of Mesoscale Storms, was created as a facet of the Environmental Protection Agency's related-service project, Precipitation Scavenging Module Development. Within this task computer programs have been developed at PNL which incorporate hourly precipitation data from National Weather Service stations to calculate mean values and frequency distributions of precipitation periods and of the interspersed dry periods. These programs have been written with a degree of flexibiity that will allow user modification for applications to different, but similar, analyses. This report describes in detail the rationale and operation of the two computer programs which produce the tables of average and frequency distributions of storm and dry period parameters from the precipitation data. A listing of the programs and examples of the generated output are included in the appendices. 3 references, 3 figures, 6 tables.

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

Science.gov (United States)

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

2015-01-01

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

Intense mesoscale variability in the Sardinia Sea

Science.gov (United States)

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.

Weather Prediction Center (WPC) Home Page

Science.gov (United States)

Products Heat Index Mesoscale Precip Discussion National Forecast Charts National High & Low PQPF QPF Valid Mon May 28, 2018 Valid Tue May 29, 2018 Day 1 Day 2 Day 3 options Image Format: English (PDF) (PDF Mesoscale Precipitation Discussion #0209 is currently in effect headline3 Mesoscale Precipitation Discussion

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

Science.gov (United States)

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

2014-05-01

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

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

Science.gov (United States)

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

2015-12-01

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

Scaling of mesoscale simulations of polymer melts with the bare friction coefficient

NARCIS (Netherlands)

Kindt, P.; Kindt, P.; Briels, Willem J.

2005-01-01

Both the Rouse and reptation model predict that the dynamics of a polymer melt scale inversely proportional with the Langevin friction coefficient (E). Mesoscale Brownian dynamics simulations of polyethylene validate these scaling predictions, providing the reptational friction (E)R=(E)+(E)C is

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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

2015-12-01

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

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

OpenAIRE

Utili, Stefano; Crosta, Giovanni B.

2011-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2000-02-01

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

Mesoscale surface equivalent temperature (T E) for East Central USA

Science.gov (United States)

Younger, Keri; Mahmood, Rezaul; Goodrich, Gregory; Pielke, Roger A.; Durkee, Joshua

2018-04-01

The purpose of this research is to investigate near surface mesoscale equivalent temperatures (T E) in Kentucky (located in east central USA) and potential land cover influences. T E is a measure of the moist enthalpy composed of the dry bulb temperature, T, and absolute humidity. Kentucky presents a unique opportunity to perform a study of this kind because of the observational infrastructure provided by the Kentucky Mesonet (www.kymesonet.org). This network maintains 69 research-grade, in-situ weather and climate observing stations across the Commonwealth. Equivalent temperatures were calculated utilizing high-quality observations from 33 of these stations. In addition, the Kentucky Mesonet offers higher spatial and temporal resolution than previous research on this topic. As expected, the differences (T E - T) were greatest in the summer (smallest in the winter), with an average of 35 °C (5 °C). In general, the differences were found to be the largest in the western climate division. This is attributed to agricultural land use and poorly drained land. These differences are smaller during periods of drought, signifying less influence of moisture.

Comparison of methods for the identification of mesoscale wind speed fluctuations

Directory of Open Access Journals (Sweden)

Anna Rieke Mehrens

2017-06-01

Full Text Available Mesoscale wind speed fluctuations influence the characteristics of offshore wind energy. These recurring wind speed changes on time scales between tens of minutes and six hours lead to power output fluctuations. In order to investigate the meteorological conditions associated with mesoscale wind speed fluctuations, a measure is needed to detect these situations in wind speed time series. Previous studies used the empirical Hilbert-Huang Transform to determine the energy in the mesoscale frequency range or calculated the standard deviation of a band-pass filtered wind speed time series. The aim of this paper is to introduce newly developed empirical mesoscale fluctuation measures and to compare them with existing measures in regard to their sensitivity to recurring wind speed changes. One of the methods is based on the Hilbert-Huang Transform, two on the Fast Fourier Transform and one on wind speed increments. It is found that despite various complexity of the methods, all methods can identify days with highly variable mesoscale wind speeds equally well.

A Reanalysis System for the Generation of Mesoscale Climatographies

DEFF Research Database (Denmark)

Hahmann, Andrea N.; Rostkier-Edelstein, Dorita; Warner, Thomas T.

2010-01-01

), wherein Newtonian relaxation terms in the prognostic equations continually nudge the model solution toward surface and upper-air observations. When applied to a mesoscale climatography, the system is called Climate-FDDA (CFDDA). Here, the CFDDA system is used for downscaling eastern Mediterranean...... the frequency distributions of atmospheric states in addition to time means. The verification of the monthly rainfall climatography shows that CFDDA captures most of the observed spatial and interannual variability, although the model tends to underestimate rainfall amounts over the sea. The frequency...

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

Science.gov (United States)

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

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

International Nuclear Information System (INIS)

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

Mesoscale variability in the Bransfield Strait region (Antarctica during Austral summer

Directory of Open Access Journals (Sweden)

M. A. García

1994-08-01

Full Text Available The Bransfield Strait is one the best-known areas of Antarctica's oceanic surroundings. In spite of this, the study of the mesoscale variability of its local circulation has been addressed only recently. This paper focuses on the mesoscale structure of local physical oceanographic conditions in the Bransfield Strait during the Austral summer as derived from the BIOANTAR 93 cruise and auxiliary remote sensing data. Moreover, data recovered from moored current meters allow identification of transient mesoscale phenomena.

Visualizing Current Flow at the Mesoscale in Disordered Assemblies of Touching Semiconductor Nanocrystals

Energy Technology Data Exchange (ETDEWEB)

Chen, Qinyi; Guest, Jeffrey R. [Center; Thimsen, Elijah

2017-07-12

The transport of electrons through assemblies of nanocrystals is important to performance in optoelectronic applications for these materials. Previous work has primarily focused on single nanocrystals or transitions between pairs of nanocrystals. There is a gap in knowledge of how large numbers of nanocrystals in an assembly behave collectively, and how this collective behavior manifests at the mesoscale. In this work, the variable range hopping (VRH) transport of electrons in disordered assemblies of touching, heavily doped ZnO nanocrystals was visualized at the mesoscale as a function of temperature both theoretically, using the model of Skinner, Chen and Shklovskii (SCS), and experimentally, with conductive atomic force microscopy on ultrathin films only a few particle layers thick. Agreement was obtained between the model and experiments, with a few notable exceptions. The SCS model predicts that a single network within the nanocrystal assembly, comprised of sites connected by small resistances, dominates conduction - namely the optimum band from variable range hopping theory. However, our experiments revealed that in addition to the optimum band, there are subnetworks that appear as additional peaks in the resistance histogram of conductive atomic force microscopy (CAFM) maps. Furthermore, the connections of these subnetworks to the optimum band change in time, such that some subnetworks become connected to the optimum band while others become disconnected and isolated from the optimum band; this observation appears to be an experimental manifestation of the ‘blinking’ phenomenon in our images of mesoscale transport.

Modeling rock weathering in small watersheds

NARCIS (Netherlands)

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

2014-01-01

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

Evaluation of weather-based rice yield models in India

Science.gov (United States)

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

2013-01-01

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

Managing wildland fires: integrating weather models into fire projections

Science.gov (United States)

Anne M. Rosenthal; Francis Fujioka

2004-01-01

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

Atlas : A library for numerical weather prediction and climate modelling

Science.gov (United States)

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

2017-11-01

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

Statistical Analysis of Model Data for Operational Space Launch Weather Support at Kennedy Space Center and Cape Canaveral Air Force Station

Science.gov (United States)

Bauman, William H., III

2010-01-01

The 12-km resolution North American Mesoscale (NAM) model (MesoNAM) is used by the 45th Weather Squadron (45 WS) Launch Weather Officers at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to support space launch weather operations. The 45 WS tasked the Applied Meteorology Unit to conduct an objective statistics-based analysis of MesoNAM output compared to wind tower mesonet observations and then develop a an operational tool to display the results. The National Centers for Environmental Prediction began running the current version of the MesoNAM in mid-August 2006. The period of record for the dataset was 1 September 2006 - 31 January 2010. The AMU evaluated MesoNAM hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The MesoNAM forecast winds, temperature and dew point were compared to the observed values of these parameters from the sensors in the KSC/CCAFS wind tower network. The data sets were stratified by model initialization time, month and onshore/offshore flow for each wind tower. Statistics computed included bias (mean difference), standard deviation of the bias, root mean square error (RMSE) and a hypothesis test for bias = O. Twelve wind towers located in close proximity to key launch complexes were used for the statistical analysis with the sensors on the towers positioned at varying heights to include 6 ft, 30 ft, 54 ft, 60 ft, 90 ft, 162 ft, 204 ft and 230 ft depending on the launch vehicle and associated weather launch commit criteria being evaluated. These twelve wind towers support activities for the Space Shuttle (launch and landing), Delta IV, Atlas V and Falcon 9 launch vehicles. For all twelve towers, the results indicate a diurnal signal in the bias of temperature (T) and weaker but discernable diurnal signal in the bias of dewpoint temperature (T(sub d)) in the MesoNAM forecasts. Also, the standard deviation of the bias and RMSE of T, T(sub d), wind speed and wind

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

Directory of Open Access Journals (Sweden)

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.

Development and validation of a regional coupled forecasting system for S2S forecasts

Science.gov (United States)

Sun, R.; Subramanian, A. C.; Hoteit, I.; Miller, A. J.; Ralph, M.; Cornuelle, B. D.

2017-12-01

Accurate and efficient forecasting of oceanic and atmospheric circulation is essential for a wide variety of high-impact societal needs, including: weather extremes; environmental protection and coastal management; management of fisheries, marine conservation; water resources; and renewable energy. Effective forecasting relies on high model fidelity and accurate initialization of the models with observed state of the ocean-atmosphere-land coupled system. A regional coupled ocean-atmosphere model with the Weather Research and Forecasting (WRF) model and the MITGCM ocean model coupled using the ESMF (Earth System Modeling Framework) coupling framework is developed to resolve mesoscale air-sea feedbacks. The regional coupled model allows oceanic mixed layer heat and momentum to interact with the atmospheric boundary layer dynamics at the mesoscale and submesoscale spatiotemporal regimes, thus leading to feedbacks which are otherwise not resolved in coarse resolution global coupled forecasting systems or regional uncoupled forecasting systems. The model is tested in two scenarios in the mesoscale eddy rich Red Sea and Western Indian Ocean region as well as mesoscale eddies and fronts of the California Current System. Recent studies show evidence for air-sea interactions involving the oceanic mesoscale in these two regions which can enhance predictability on sub seasonal timescale. We will present results from this newly developed regional coupled ocean-atmosphere model for forecasts over the Red Sea region as well as the California Current region. The forecasts will be validated against insitu observations in the region as well as reanalysis fields.

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

African Journals Online (AJOL)

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

Analysis and simulation of mesoscale convective systems accompanying heavy rainfall: The goyang case

Science.gov (United States)

Choi, Hyun-Young; Ha, Ji-Hyun; Lee, Dong-Kyou; Kuo, Ying-Hwa

2011-05-01

We investigated a torrential rainfall case with a daily rainfall amount of 379 mm and a maximum hourly rain rate of 77.5 mm that took place on 12 July 2006 at Goyang in the middlewestern part of the Korean Peninsula. The heavy rainfall was responsible for flash flooding and was highly localized. High-resolution Doppler radar data from 5 radar sites located over central Korea were analyzed. Numerical simulations using the Weather Research and Forecasting (WRF) model were also performed to complement the high-resolution observations and to further investigate the thermodynamic structure and development of the convective system. The grid nudging method using the Global Final (FNL) Analyses data was applied to the coarse model domain (30 km) in order to provide a more realistic and desirable initial and boundary conditions for the nested model domains (10 km, 3.3 km). The mesoscale convective system (MCS) which caused flash flooding was initiated by the strong low level jet (LLJ) at the frontal region of high equivalent potential temperature (θe) near the west coast over the Yellow Sea. The ascending of the warm and moist air was induced dynamically by the LLJ. The convective cells were triggered by small thermal perturbations and abruptly developed by the warm θe inflow. Within the MCS, several convective cells responsible for the rainfall peak at Goyang simultaneously developed with neighboring cells and interacted with each other. Moist absolutely unstable layers (MAULs) were seen at the lower troposphere with the very moist environment adding the instability for the development of the MCS.

The Influence of Aerosol Hygroscopicity on Precipitation Intensity During a Mesoscale Convective Event

Science.gov (United States)

Kawecki, Stacey; Steiner, Allison L.

2018-01-01

We examine how aerosol composition affects precipitation intensity using the Weather and Research Forecasting Model with Chemistry (version 3.6). By changing the prescribed default hygroscopicity values to updated values from laboratory studies, we test model assumptions about individual component hygroscopicity values of ammonium, sulfate, nitrate, and organic species. We compare a baseline simulation (BASE, using default hygroscopicity values) with four sensitivity simulations (SULF, increasing the sulfate hygroscopicity; ORG, decreasing organic hygroscopicity; SWITCH, using a concentration-dependent hygroscopicity value for ammonium; and ALL, including all three changes) to understand the role of aerosol composition on precipitation during a mesoscale convective system (MCS). Overall, the hygroscopicity changes influence the spatial patterns of precipitation and the intensity. Focusing on the maximum precipitation in the model domain downwind of an urban area, we find that changing the individual component hygroscopicities leads to bulk hygroscopicity changes, especially in the ORG simulation. Reducing bulk hygroscopicity (e.g., ORG simulation) initially causes fewer activated drops, weakened updrafts in the midtroposphere, and increased precipitation from larger hydrometeors. Increasing bulk hygroscopicity (e.g., SULF simulation) simulates more numerous and smaller cloud drops and increases precipitation. In the ALL simulation, a stronger cold pool and downdrafts lead to precipitation suppression later in the MCS evolution. In this downwind region, the combined changes in hygroscopicity (ALL) reduces the overprediction of intense events (>70 mm d-1) and better captures the range of moderate intensity (30-60 mm d-1) events. The results of this single MCS analysis suggest that aerosol composition can play an important role in simulating high-intensity precipitation events.

Model for expressing leaf photosynthesis in terms of weather variables

African Journals Online (AJOL)

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

Dynamic Weather Routes: A Weather Avoidance Concept for Trajectory-Based Operations

Science.gov (United States)

McNally, B. David; Love, John

2011-01-01

The integration of convective weather modeling with trajectory automation for conflict detection, trial planning, direct routing, and auto resolution has uncovered a concept that could help controllers, dispatchers, and pilots identify improved weather routes that result in significant savings in flying time and fuel burn. Trajectory automation continuously and automatically monitors aircraft in flight to find those that could potentially benefit from improved weather reroutes. Controllers, dispatchers, and pilots then evaluate reroute options to assess their suitability given current weather and traffic. In today's operations aircraft fly convective weather avoidance routes that were implemented often hours before aircraft approach the weather and automation does not exist to automatically monitor traffic to find improved weather routes that open up due to changing weather conditions. The automation concept runs in real-time and employs two keysteps. First, a direct routing algorithm automatically identifies flights with large dog legs in their routes and therefore potentially large savings in flying time. These are common - and usually necessary - during convective weather operations and analysis of Fort Worth Center traffic shows many aircraft with short cuts that indicate savings on the order of 10 flying minutes. The second and most critical step is to apply trajectory automation with weather modeling to determine what savings could be achieved by modifying the direct route such that it avoids weather and traffic and is acceptable to controllers and flight crews. Initial analysis of Fort Worth Center traffic suggests a savings of roughly 50% of the direct route savings could be achievable.The core concept is to apply trajectory automation with convective weather modeling in real time to identify a reroute that is free of weather and traffic conflicts and indicates enough time and fuel savings to be considered. The concept is interoperable with today

On the CO2 exchange between the atmosphere and the biosphere: the role of synoptic and mesoscale processes

International Nuclear Information System (INIS)

Chan, Douglas; Higuchi, Kaz; Shashkov, Alexander; Worthy, Douglas; Liu, Jane; Chen Jing; Yuen Chiu Wai

2004-01-01

Estimating global carbon fluxes by inverting atmospheric CO 2 through the use of atmospheric transport models has shown the importance of the covariance between biospheric fluxes and atmospheric transport on the carbon budget. This covariance or coupling occurs on many time scales. This study examines the coupling of the biosphere and the atmosphere on the meso- and synoptic scales using a coupled atmosphere-biosphere regional model covering Canada. The results are compared with surface and light aircraft measurement campaigns at two boreal forest sites in Canada. Associated with cold and warm frontal features, the model results showed that the biospheric fluxes are strongly coupled to the atmosphere through radiative forcing. The presence of cloud near frontal regions usually results in reduced photosynthetic uptake, producing CO 2 concentration gradients across the frontal regions on the order of 10 parts per million (ppm). Away from the frontal region, the biosphere is coupled to the mesoscale variations in similar ways, resulting in mesoscale variations in CO 2 concentrations of about 5 ppm. The CO 2 field is also coupled strongly to the atmospheric dynamics. In the presence of frontal circulation, the CO 2 near the surface can be transported to the mid to upper troposphere. Mesoscale circulation also plays a significant part in transporting the CO 2 from the planetary boundary layer (PBL) to the mid-troposphere. In the absence of significant mesoscale or synoptic scale circulation, the CO 2 in the PBL has minimal exchange with the free troposphere, leading to strong gradients across the top of the PBL. We speculate that the ubiquity of the common synoptic and mesoscale processes in the atmosphere may contribute significantly to the rectifier effect and hence CO 2 inversion calculations

A Weather Analysis and Forecasting System for Baja California, Mexico

Science.gov (United States)

Farfan, L. M.

2006-05-01

The weather of the Baja California Peninsula, part of northwestern Mexico, is mild and dry most of the year. However, during the summer, humid air masses associated with tropical cyclones move northward in the eastern Pacific Ocean. Added features that create a unique meteorological situation include mountain ranges along the spine of the peninsula, warm water in the Gulf of California, and the cold California Current in the Pacific. These features interact with the environmental flow to induce conditions that play a role in the occurrence of localized, convective systems during the approach of tropical cyclones. Most of these events occur late in the summer, generating heavy precipitation, strong winds, lightning, and are associated with significant property damage to the local populations. Our goal is to provide information on the characteristics of these weather systems by performing an analysis of observations derived from a regional network. This includes imagery from radar and geostationary satellite, and data from surface stations. A set of real-time products are generated in our research center and are made available to a broad audience (researchers, students, and business employees) by using an internet site. Graphical products are updated anywhere from one to 24 hours and includes predictions from numerical models. Forecasts are derived from an operational model (GFS) and locally generated simulations based on a mesoscale model (MM5). Our analysis and forecasting system has been in operation since the summer of 2005 and was used as a reference for a set of discussions during the development of eastern Pacific tropical cyclones. This basin had 15 named storms and none of them made landfall on the west coast of Mexico; however, four systems were within 800 km from the area of interest, resulting in some convective activity. During the whole season, a group of 30 users from our institution, government offices, and local businesses received daily information

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

International Nuclear Information System (INIS)

Šaltytė Benth, Jūratė; Benth, Fred Espen

2012-01-01

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

Microphysical/mesoscale aspects of nuclear winter and new directions in assessments

International Nuclear Information System (INIS)

Knox, J.B.

1985-06-01

Recent results of model studies and sensitivity tests have shown the degree to which the intensity and duration of ''nuclear winter'' depends on the mass of soot and dust suspended, its optical properties, its vertical distribution in the atmosphere, and the residence time. The soot from urban fires is viewed as evolving during its dispersion from the early fire induced plumes, to cloud scale systems, to the mesoscale and larger systems. Micro-physical processes are perceived as operating within these systems in a manner to enhance removal from the troposphere, and to alter the verical distribution of the soot or its subsequent, aging or evolving aerosol. Relevant observations and studies of these processes are presented and discussed. Critical inputs to the climate simulation models may well be altered significantly by these process effects, many of which are in need of better definition. Appropriate research needs to be initiated to address and better define these microphysical/mesoscale processes of potential importance in the altered atmospheric system after a major nuclear exchange. 11 refs., 2 figs

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

DEFF Research Database (Denmark)

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

2013-01-01

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

Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

Science.gov (United States)

Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

2018-01-01

Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

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

DEFF Research Database (Denmark)

Jensen, David Getreuer

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

1989-01-01

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

Combined meso-scale modeling and experimental investigation of the effect of mechanical damage on the transport properties of cementitious composites

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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)

Investigating the Effects of Grid Resolution of WRF Model for Simulating the Atmosphere for use in the Study of Wake Turbulence

Science.gov (United States)

Prince, Alyssa; Trout, Joseph; di Mercurio, Alexis

2017-01-01

The Weather Research and Forecasting (WRF) Model is a nested-grid, mesoscale numerical weather prediction system maintained by the Developmental Testbed Center. The model simulates the atmosphere by integrating partial differential equations, which use the conservation of horizontal momentum, conservation of thermal energy, and conservation of mass along with the ideal gas law. This research investigated the possible use of WRF in investigating the effects of weather on wing tip wake turbulence. This poster shows the results of an investigation into the accuracy of WRF using different grid resolutions. Several atmospheric conditions were modeled using different grid resolutions. In general, the higher the grid resolution, the better the simulation, but the longer the model run time. This research was supported by Dr. Manuel A. Rios, Ph.D. (FAA) and the grant ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA'' (13-G-006). Dr. Manuel A. Rios, Ph.D. (FAA), and the grant ``A Pilot Project to Investigate Wake Vortex Patterns and Weather Patterns at the Atlantic City Airport by the Richard Stockton College of NJ and the FAA''

Evaluation of a Mesoscale Convective System in Variable-Resolution CESM

Science.gov (United States)

Payne, A. E.; Jablonowski, C.

2017-12-01

Warm season precipitation over the Southern Great Plains (SGP) follows a well observed diurnal pattern of variability, peaking at night-time, due to the eastward propagation of mesoscale convection systems that develop over the eastern slopes of the Rockies in the late afternoon. While most climate models are unable to adequately capture the organization of convection and characteristic pattern of precipitation over this region, models with high enough resolution to explicitly resolve convection show improvement. However, high resolution simulations are computationally expensive and, in the case of regional climate models, are subject to boundary conditions. Newly developed variable resolution global climate models strike a balance between the benefits of high-resolution regional climate models and the large-scale dynamics of global climate models and low computational cost. Recently developed parameterizations that are insensitive to the model grid scale provide a way to improve model performance. Here, we present an evaluation of the newly available Cloud Layers Unified by Binormals (CLUBB) parameterization scheme in a suite of variable-resolution CESM simulations with resolutions ranging from 110 km to 7 km within a regionally refined region centered over the SGP Atmospheric Radiation Measurement (ARM) site. Simulations utilize the hindcast approach developed by the Department of Energy's Cloud-Associated Parameterizations Testbed (CAPT) for the assessment of climate models. We limit our evaluation to a single mesoscale convective system that passed over the region on May 24, 2008. The effects of grid-resolution on the timing and intensity of precipitation, as well as, on the transition from shallow to deep convection are assessed against ground-based observations from the SGP ARM site, satellite observations and ERA-Interim reanalysis.

Role of mesoscale eddies in the global ocean uptake of anthropogenic CO2

International Nuclear Information System (INIS)

Zouhair, Lachkar

2007-02-01

Mesoscale eddies play a fundamental role in ocean dynamics particularly in the Southern Ocean. Global-scale tracer simulations are typically made at coarse resolution without explicitly modeling eddies. Here we ask what role do eddies play in ocean uptake, storage, and meridional transport of anthropogenic CO 2 , CFC-11 and bomb Δ 14 C. We made global anthropogenic transient tracer simulations in coarse-resolution, ORCA2, and eddy-permitting, ORCA05 and ORCA025, versions of the ocean modelling system NEMO. We focus on the Southern Ocean where tracer air-sea fluxes are largest. Eddies have little effect on bomb Δ 14 C uptake and storage. Yet for CFC-11 and anthropogenic CO 2 , increased eddy activity reduces southern extra-tropical uptake by 28% and 25% respectively, thereby providing better agreement with observations. It is shown that the discrepancies in the equilibration times between the three tracers determine their respective sensitivities to the model horizontal resolution. Applying Gent and McWilliams (1990) (GM) parameterization of eddies in the non-eddying version of the model does improve results, but not enough. An in-depth investigation of the mechanisms by which eddies affect the uptake of the transient tracers shows that including mesoscale eddies leads to an overall reduction in the Antarctic Intermediate Water (AAIW) ventilation, and modifies substantially the spatial distribution of their source regions. This investigation reveals also that the GM parameterization still overestimates the ventilation and the subduction of AAIW in the Indian Ocean where the simulated mixed layer is particularly deep during the winter. This work suggests that most current coarse-resolution models may overestimate the ventilation of AAIW in the Indian sector of the Southern Ocean. This study shows also that the use of the GM parameterization may be of limited utility where mixed layer is relatively deep and confirms the general need for a more adequate

Improved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS)

Science.gov (United States)

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.

Will high-resolution global ocean models benefit coupled predictions on short-range to climate timescales?

Science.gov (United States)

Hewitt, Helene T.; Bell, Michael J.; Chassignet, Eric P.; Czaja, Arnaud; Ferreira, David; Griffies, Stephen M.; Hyder, Pat; McClean, Julie L.; New, Adrian L.; Roberts, Malcolm J.

2017-12-01

As the importance of the ocean in the weather and climate system is increasingly recognised, operational systems are now moving towards coupled prediction not only for seasonal to climate timescales but also for short-range forecasts. A three-way tension exists between the allocation of computing resources to refine model resolution, the expansion of model complexity/capability, and the increase of ensemble size. Here we review evidence for the benefits of increased ocean resolution in global coupled models, where the ocean component explicitly represents transient mesoscale eddies and narrow boundary currents. We consider lessons learned from forced ocean/sea-ice simulations; from studies concerning the SST resolution required to impact atmospheric simulations; and from coupled predictions. Impacts of the mesoscale ocean in western boundary current regions on the large-scale atmospheric state have been identified. Understanding of air-sea feedback in western boundary currents is modifying our view of the dynamics in these key regions. It remains unclear whether variability associated with open ocean mesoscale eddies is equally important to the large-scale atmospheric state. We include a discussion of what processes can presently be parameterised in coupled models with coarse resolution non-eddying ocean models, and where parameterizations may fall short. We discuss the benefits of resolution and identify gaps in the current literature that leave important questions unanswered.

Reconstruction of Historical Weather by Assimilating Old Weather Diary Data

Science.gov (United States)

Neluwala, P.; Yoshimura, K.; Toride, K.; Hirano, J.; Ichino, M.; Okazaki, A.

2017-12-01

Climate can control not only human life style but also other living beings. It is important to investigate historical climate to understand the current and future climates. Information about daily weather can give a better understanding of past life on earth. Long-term weather influences crop calendar as well as the development of civilizations. Unfortunately, existing reconstructed daily weather data are limited to 1850s due to the availability of instrumental data. The climate data prior to that are derived from proxy materials (e.g., tree-ring width, ice core isotopes, etc.) which are either in annual or decadal scale. However, there are many historical documents which contain information about weather such as personal diaries. In Japan, around 20 diaries in average during the 16th - 19th centuries have been collected and converted into a digitized form. As such, diary data exist in many other countries. This study aims to reconstruct historical daily weather during the 18th and 19th centuries using personal daily diaries which have analogue weather descriptions such as `cloudy' or `sunny'. A recent study has shown the possibility of assimilating coarse weather data using idealized experiments. We further extend this study by assimilating modern weather descriptions similar to diary data in recent periods. The Global Spectral model (GSM) of National Centers for Environmental Prediction (NCEP) is used to reconstruct weather with the Local Ensemble Kalman filter (LETKF). Descriptive data are first converted to model variables such as total cloud cover (TCC), solar radiation and precipitation using empirical relationships. Those variables are then assimilated on a daily basis after adding random errors to consider the uncertainty of actual diary data. The assimilation of downward short wave solar radiation using weather descriptions improves RMSE from 64.3 w/m2 to 33.0 w/m2 and correlation coefficient (R) from 0.5 to 0.8 compared with the case without any

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

Science.gov (United States)

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

2014-12-01

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

Dynamic Mesoscale Land-Atmosphere Feedbacks in Fragmented Forests in Amazonia

Science.gov (United States)

Rastogi, D.; Baidya Roy, S.

2011-12-01

This paper investigates land-atmosphere feedbacks in disturbed rainforests of Amazonia. Deforestation along the rapidly expanding highways and road network has created the unique fishbone land cover pattern in Rondonia, a state in southwestern Amazonia. Numerical experiments and observations show that sharp gradients in land cover due to the fishbone heterogeneity triggers mesoscale circulations. These circulations significantly change the spatial pattern of local hydrometeorology, especially convection, clouds and precipitation. The primary research question now is can these changes in local hydrometeorology affect vegetation growth in the clearings. If so, that would be a clear indication that land-atmosphere feedbacks can affect vegetation recovery in fragmented forests. A computationally-efficient modeling tool consisting of a mesoscale atmospheric model dynamically coupled with a plant growth model has been specifically developed to identify the atmospheric feedback pathways. Preliminary experiments focus on the seasonal-scale feedbacks during the dry season. Results show that temperature, incoming shortwave and precipitation are the three primary drivers through which the feedbacks operate. Increasing temperature increases respiratory losses generating a positive feedback. Increased cloud cover reduces incoming PAR and photosynthesis, resulting in a positive feedback. Increased precipitation reduces water stress and promotes growth resulting in a negative feedback. The net effect is a combination of these 3 feedback loops. These findings can significantly improve our understanding of ecosystem resiliency in disturbed tropical forests.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

Asteroid age distributions determined by space weathering and collisional evolution models

Science.gov (United States)

Willman, Mark; Jedicke, Robert

2011-01-01

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

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

Science.gov (United States)

Miyauchi, T.; Machimura, T.

2014-12-01

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

Automated Tracking of Tornado-Producing Mesoscale Convective Systems in the United States

Science.gov (United States)

Kuo, K.; Hong, Y.; Clune, T. L.

2011-12-01

The great majority of Earth Science events are studied using "snap-shot" observations in time, mainly due to the scarcity of observations with dense temporal coverage and the lack of robust methods amenable to connecting the "snap shots". To enable the studies of these events in the four-dimensional (4D) spatiotemporal space and to demonstrate the utility of this capability, we have applied the neighbor enclosed area tracking (NEAT) method of Inatsu (2009) to three years of high-resolution (in both time and space) NEXRAD-derived and rain-gauge-corrected QE2 precipitation observations and GOES satellite Rapid Scan Operation imagery to track tornado-producing mesoscale convective systems (MCS's). We combine information from the databases of the Tornado History Project (which provides tornado occurrence and trajectory) and the NWS Watch/Warning Archive (which provides severe weather watch/warning locations) to obtain initial estimate of the time and location of a tornado-producing MCS. The NEAT algorithm is then applied to QE2 and GOES data, both forward and backward in time, to identify the entire system as one integral entity from its inception to its eventual dissipation in the 4D spatiotemporal space. For each system so identified, we extract its morphological/structural parameters, such as perimeter length, area, and orientation, from each of the snap shots in time. We also record physical parameters such as minimum and maximum precipitation rates. In addition, we perform areal integral on the precipitation rate field, which in turn enables time integral for the entire MCS throughout its lifecycle to obtain an estimate of the system's precipitation production. We can extend this proof-of-concept prototype to other precipitation producing severe weather events, such as blizzards. Furthermore, the spatiotemporal data collected may be used to discover other data, such as satellite remote sensing observations and model analyses/simulations, which can then be combined

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

Science.gov (United States)

Rössler, Ole; Keller, Denise; Fischer, Andreas

2016-04-01

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

NASA Space Weather Center Services: Potential for Space Weather Research

Science.gov (United States)

Zheng, Yihua; Kuznetsova, Masha; Pulkkinen, Antti; Taktakishvili, A.; Mays, M. L.; Chulaki, A.; Lee, H.; Hesse, M.

2012-01-01

The NASA Space Weather Center's primary objective is to provide the latest space weather information and forecasting for NASA's robotic missions and its partners and to bring space weather knowledge to the public. At the same time, the tools and services it possesses can be invaluable for research purposes. Here we show how our archive and real-time modeling of space weather events can aid research in a variety of ways, with different classification criteria. We will list and discuss major CME events, major geomagnetic storms, and major SEP events that occurred during the years 2010 - 2012. Highlights of major tools/resources will be provided.

Subregional characterization of mesoscale eddies across the Brazil-Malvinas Confluence

Science.gov (United States)

Mason, Evan; Pascual, Ananda; Gaube, Peter; Ruiz, Simón; Pelegrí, Josep L.; Delepoulle, Antoine

2017-04-01

Horizontal and vertical motions associated with coherent mesoscale structures, including eddies and meanders, are responsible for significant global transports of many properties, including heat and mass. Mesoscale vertical fluxes also influence upper ocean biological productivity by mediating the supply of nutrients into the euphotic layer, with potential impacts on the global carbon cycle. The Brazil-Malvinas Confluence (BMC) is a western boundary current region in the South Atlantic with intense mesoscale activity. This region has an active role in the genesis and transformation of water masses and thus is a critical component of the Atlantic meridional overturning circulation. The collision between the Malvinas and Brazil Currents over the Patagonian shelf/slope creates an energetic front that translates offshore to form a vigorous eddy field. Recent improvements in gridded altimetric sea level anomaly fields allow us to track BMC mesoscale eddies with high spatial and temporal resolutions using an automated eddy tracker. We characterize the eddies across fourteen 5° × 5° subregions. Eddy-centric composites of tracers and geostrophic currents diagnosed from a global reanalysis of surface and in situ data reveal substantial subregional heterogeneity. The in situ data are also used to compute the evolving quasi-geostrophic vertical velocity (QG-ω) associated with each instantaneous eddy instance. The QG-ω eddy composites have the expected dipole patterns of alternating upwelling/downwelling, however, the magnitude and sign of azimuthally averaged vertical velocity varies among subregions. Maximum eddy values are found near fronts and sharp topographic gradients. In comparison with regional eddy composites, subregional composites provide refined information about mesoscale eddy heterogeneity.

Modeling Apple Surface Temperature Dynamics Based on Weather Data

Directory of Open Access Journals (Sweden)

Lei Li

2014-10-01

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

Modeling apple surface temperature dynamics based on weather data.

Science.gov (United States)

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

2014-10-27

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

Fair weather atmospheric electricity

International Nuclear Information System (INIS)

Harrison, R G

2011-01-01

Not long after Franklin's iconic studies, an atmospheric electric field was discovered in 'fair weather' regions, well away from thunderstorms. The origin of the fair weather field was sought by Lord Kelvin, through development of electrostatic instrumentation and early data logging techniques, but was ultimately explained through the global circuit model of C.T.R. Wilson. In Wilson's model, charge exchanged by disturbed weather electrifies the ionosphere, and returns via a small vertical current density in fair weather regions. New insights into the relevance of fair weather atmospheric electricity to terrestrial and planetary atmospheres are now emerging. For example, there is a possible role of the global circuit current density in atmospheric processes, such as cloud formation. Beyond natural atmospheric processes, a novel practical application is the use of early atmospheric electrostatic investigations to provide quantitative information on past urban air pollution.

Do mesoscale faults in a young fold belt indicate regional or local stress?

Science.gov (United States)

Kokado, Akihiro; Yamaji, Atsushi; Sato, Katsushi

2017-04-01

The result of paleostress analyses of mesoscale faults is usually thought of as evidence of a regional stress. On the other hand, the recent advancement of the trishear modeling has enabled us to predict the deformation field around fault-propagation folds without the difficulty of assuming paleo mechanical properties of rocks and sediments. We combined the analysis of observed mesoscale faults and the trishear modeling to understand the significance of regional and local stresses for the formation of mesoscale faults. To this end, we conducted the 2D trishear inverse modeling with a curved thrust fault to predict the subsurface structure and strain field of an anticline, which has a more or less horizontal axis and shows a map-scale plane strain perpendicular to the axis, in the active fold belt of Niigata region, central Japan. The anticline is thought to have been formed by fault-propagation folding under WNW-ESE regional compression. Based on the attitudes of strata and the positions of key tephra beds in Lower Pleistocene soft sediments cropping out at the surface, we obtained (1) a fault-propagation fold with the fault tip at a depth of ca. 4 km as the optimal subsurface structure, and (2) the temporal variation of deformation field during the folding. We assumed that mesoscale faults were activated along the direction of maximum shear strain on the faults to test whether the fault-slip data collected at the surface were consistent with the deformation in some stage(s) of folding. The Wallace-Bott hypothesis was used to estimate the consistence of faults with the regional stress. As a result, the folding and the regional stress explained 27 and 33 of 45 observed faults, respectively, with the 11 faults being consistent with the both. Both the folding and regional one were inconsistent with the remaining 17 faults, which could be explained by transfer faulting and/or the gravitational spreading of the growing anticline. The lesson we learnt from this work was

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

Science.gov (United States)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

International Nuclear Information System (INIS)

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

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

Science.gov (United States)

Tulich, S. N.

2015-06-01

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

Integration of Weather Avoidance and Traffic Separation

Science.gov (United States)

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

2011-01-01

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

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

Science.gov (United States)

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

2017-12-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-12-01

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

Mesoscale Frontogenesis: An Analysis of Two Cold Front Case Studies

Science.gov (United States)

1993-01-01

marked the boundary of warm air or the "warm sector". Further development of this cyclone model by Bjerknes and Solberg (1922) and Bergeron (1928) provided...represent 25 mn s -1 Relative humidity of greater than 80% indicated by the shaded region in gray. Frontal zones marked with solid black lines. 24 two... Zuckerberg , J.T. Schaefer, and G.E. Rasch, 1986: Forecast problems: The meteorological and operational factors, In: Mesoscale Meteorology and Forecasting

Space Weather Services of Korea

Science.gov (United States)

Yoon, K.; Hong, S.; Jangsuk, C.; Dong Kyu, K.; Jinyee, C.; Yeongoh, C.

2016-12-01

The Korean Space Weather Center (KSWC) of the National Radio Research Agency (RRA) is a government agency which is the official source of space weather information for Korean Government and the primary action agency of emergency measure to severe space weather condition. KSWC's main role is providing alerts, watches, and forecasts in order to minimize the space weather impacts on both of public and commercial sectors of satellites, aviation, communications, navigations, power grids, and etc. KSWC is also in charge of monitoring the space weather condition and conducting research and development for its main role of space weather operation in Korea. In this study, we will present KSWC's recent efforts on development of application-oriented space weather research products and services on user needs, and introduce new international collaborative projects, such as IPS-Driven Enlil model, DREAM model estimating electron in satellite orbit, global network of DSCOVR and STEREO satellites tracking, and ARMAS (Automated Radiation Measurement for Aviation Safety).

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

Science.gov (United States)

Stewart, A. E.

2017-12-01

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

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

Science.gov (United States)

Schubert, Siegfried D.; Lim, Young-Kwon

2012-01-01

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

Effects of Weather on Tourism and its Moderation

Science.gov (United States)

Park, J. H.; Kim, S.; Lee, D. K.

2016-12-01

Tourism is weather sensitive industry (Gómez Martín, 2005). As climate change has been intensifying, the concerns about negative effects of weather on tourism also have been increasing. This study attempted to find ways that mitigate the negative effects from weather on tourism, by analyzing a path of the effects of weather on intention to revisit and its moderation. The data of the study were collected by a self-recording online questionnaire survey of South Korean domestic tourists during August 2015, and 2,412 samples were gathered. A path model of effects of weather on intention to revisit that including moderating effects from physical attraction satisfaction and service satisfaction was ran. Season was controlled in the path model. The model fit was adequate (CMIN/DF=2.372(p=.000), CFI=.974, RMSEA=.024, SRMR=0.040), and the Model Comparison, which assumes that the base model to be correct with season constrained model, showed that there was a seasonal differences in the model ( DF=24, CMIN=32.430, P=.117). By the analysis, it was figured out that weather and weather expectation affected weather satisfaction, and the weather satisfaction affected intention to revisit (spring/fall: .167**, summer: .104**, and winter: .114**). Meanwhile physical attraction satisfaction (.200**), and service satisfaction (.210**) of tourism positively moderated weather satisfaction in summer, and weather satisfaction positively moderated physical attraction (.238**) satisfaction and service satisfaction (.339**). In other words, in summer, dissatisfaction from hot weather was moderated by satisfaction from physical attractions and services, and in spring/fall, comfort weather conditions promoted tourists to accept tourism experience and be satisfied from attractions and services positively. Based on the result, it was expected that if industries focus on offering the good attractions and services based on weather conditions, there would be positive effects to alleviate tourists

Mesoscale brain explorer, a flexible python-based image analysis and visualization tool.

Science.gov (United States)

Haupt, Dirk; Vanni, Matthieu P; Bolanos, Federico; Mitelut, Catalin; LeDue, Jeffrey M; Murphy, Tim H

2017-07-01

Imaging of mesoscale brain activity is used to map interactions between brain regions. This work has benefited from the pioneering studies of Grinvald et al., who employed optical methods to image brain function by exploiting the properties of intrinsic optical signals and small molecule voltage-sensitive dyes. Mesoscale interareal brain imaging techniques have been advanced by cell targeted and selective recombinant indicators of neuronal activity. Spontaneous resting state activity is often collected during mesoscale imaging to provide the basis for mapping of connectivity relationships using correlation. However, the information content of mesoscale datasets is vast and is only superficially presented in manuscripts given the need to constrain measurements to a fixed set of frequencies, regions of interest, and other parameters. We describe a new open source tool written in python, termed mesoscale brain explorer (MBE), which provides an interface to process and explore these large datasets. The platform supports automated image processing pipelines with the ability to assess multiple trials and combine data from different animals. The tool provides functions for temporal filtering, averaging, and visualization of functional connectivity relations using time-dependent correlation. Here, we describe the tool and show applications, where previously published datasets were reanalyzed using MBE.

Error Covariance Estimation of Mesoscale Data Assimilation

National Research Council Canada - National Science Library

Xu, Qin

2005-01-01

The goal of this project is to explore and develop new methods of error covariance estimation that will provide necessary statistical descriptions of prediction and observation errors for mesoscale data assimilation...

Statistical relationship between surface PM10 concentration and aerosol optical depth over the Sahel as a function of weather type, using neural network methodology

Science.gov (United States)

Yahi, H.; Marticorena, B.; Thiria, S.; Chatenet, B.; Schmechtig, C.; Rajot, J. L.; Crepon, M.

2013-12-01

work aims at assessing the capability of passive remote-sensed measurements such as aerosol optical depth (AOD) to monitor the surface dust concentration during the dry season in the Sahel region (West Africa). We processed continuous measurements of AODs and surface concentrations for the period (2006-2010) in Banizoumbou (Niger) and Cinzana (Mali). In order to account for the influence of meteorological condition on the relationship between PM10 surface concentration and AOD, we decomposed the mesoscale meteorological fields surrounding the stations into five weather types having similar 3-dimensional atmospheric characteristics. This classification was obtained by a clustering method based on nonlinear artificial neural networks, the so-called self-organizing map. The weather types were identified by processing tridimensional fields of meridional and zonal winds and air temperature obtained from European Centre for Medium-Range Weather Forecasts (ECMWF) model output centered on each measurement station. Five similar weather types have been identified at the two stations. Three of them are associated with the Harmattan flux; the other two correspond to northward inflow of the monsoon flow at the beginning or the end of the dry season. An improved relationship has been found between the surface PM10 concentrations and the AOD by using a dedicated statistical relationship for each weather type. The performances of the statistical inversion computed on the test data sets show satisfactory skills for most of the classes, much better than a linear regression. This should permit the inversion of the mineral dust concentration from AODs derived from satellite observations over the Sahel.

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

Energy Technology Data Exchange (ETDEWEB)

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

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

Science.gov (United States)

Liu, Zedong; Wan, Xiuquan

2018-04-01

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

Mesoscale hybrid calibration artifact

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Comparison of mesoscale model and tower measurements of surface fluxes during Winter Icing and Storms Program/Atmospheric Radiation Measurement 91

International Nuclear Information System (INIS)

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

New Mesoscale Fluvial Landscapes - Seismic Geomorphology and Exploration

Science.gov (United States)

Wilkinson, M. J.

2013-01-01

Megafans (100-600 km radius) are very large alluvial fans that cover significant areas on most continents, the surprising finding of recent global surveys. The number of such fans and patterns of sedimentation on them provides new mesoscale architectures that can now be applied on continental fluvial depositional systems, and therefore on. Megafan-scale reconstructions underground as yet have not been attempted. Seismic surveys offer new possibilities in identifying the following prospective situations at potentially unsuspected locations: (i) sand concentrations points, (ii) sand-mud continuums at the mesoscale, (iii) paleo-valley forms in these generally unvalleyed landscapes, (iv) stratigraphic traps, and (v) structural traps.

The origins of computer weather prediction and climate modeling

International Nuclear Information System (INIS)

Lynch, Peter

2008-01-01

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

Climate Prediction - NOAA's National Weather Service

Science.gov (United States)

Statistical Models... MOS Prod GFS-LAMP Prod Climate Past Weather Predictions Weather Safety Weather Radio National Weather Service on FaceBook NWS on Facebook NWS Director Home > Climate > Predictions Climate Prediction Long range forecasts across the U.S. Climate Prediction Web Sites Climate Prediction

Study of the air-sea interactions at the mesoscale: the SEMAPHORE experiment

Directory of Open Access Journals (Sweden)

L. Eymard

1996-09-01

Full Text Available The SEMAPHORE (Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale experiment has been conducted from June to November 1993 in the Northeast Atlantic between the Azores and Madeira. It was centered on the study of the mesoscale ocean circulation and air-sea interactions. The experimental investigation was achieved at the mesoscale using moorings, floats, and ship hydrological survey, and at a smaller scale by one dedicated ship, two instrumented aircraft, and surface drifting buoys, for one and a half month in October-November (IOP: intense observing period. Observations from meteorological operational satellites as well as spaceborne microwave sensors were used in complement. The main studies undertaken concern the mesoscale ocean, the upper ocean, the atmospheric boundary layer, and the sea surface, and first results are presented for the various topics. From data analysis and model simulations, the main characteristics of the ocean circulation were deduced, showing the close relationship between the Azores front meander and the occurrence of Mediterranean water lenses (meddies, and the shift between the Azores current frontal signature at the surface and within the thermocline. Using drifting buoys and ship data in the upper ocean, the gap between the scales of the atmospheric forcing and the oceanic variability was made evident. A 2 °C decrease and a 40-m deepening of the mixed layer were measured within the IOP, associated with a heating loss of about 100 W m-2. This evolution was shown to be strongly connected to the occurrence of storms at the beginning and the end of October. Above the surface, turbulent measurements from ship and aircraft were analyzed across the surface thermal front, showing a 30% difference in heat fluxes between both sides during a 4-day period, and the respective contributions of the wind and the surface temperature were evaluated. The classical

Study of the air-sea interactions at the mesoscale: the SEMAPHORE experiment

Science.gov (United States)

Eymard, L.; Planton, S.; Durand, P.; Le Visage, C.; Le Traon, P. Y.; Prieur, L.; Weill, A.; Hauser, D.; Rolland, J.; Pelon, J.; Baudin, F.; Bénech, B.; Brenguier, J. L.; Caniaux, G.; de Mey, P.; Dombrowski, E.; Druilhet, A.; Dupuis, H.; Ferret, B.; Flamant, C.; Flamant, P.; Hernandez, F.; Jourdan, D.; Katsaros, K.; Lambert, D.; Lefèvre, J. M.; Le Borgne, P.; Le Squere, B.; Marsoin, A.; Roquet, H.; Tournadre, J.; Trouillet, V.; Tychensky, A.; Zakardjian, B.

1996-09-01

The SEMAPHORE (Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale) experiment has been conducted from June to November 1993 in the Northeast Atlantic between the Azores and Madeira. It was centered on the study of the mesoscale ocean circulation and air-sea interactions. The experimental investigation was achieved at the mesoscale using moorings, floats, and ship hydrological survey, and at a smaller scale by one dedicated ship, two instrumented aircraft, and surface drifting buoys, for one and a half month in October-November (IOP: intense observing period). Observations from meteorological operational satellites as well as spaceborne microwave sensors were used in complement. The main studies undertaken concern the mesoscale ocean, the upper ocean, the atmospheric boundary layer, and the sea surface, and first results are presented for the various topics. From data analysis and model simulations, the main characteristics of the ocean circulation were deduced, showing the close relationship between the Azores front meander and the occurrence of Mediterranean water lenses (meddies), and the shift between the Azores current frontal signature at the surface and within the thermocline. Using drifting buoys and ship data in the upper ocean, the gap between the scales of the atmospheric forcing and the oceanic variability was made evident. A 2 °C decrease and a 40-m deepening of the mixed layer were measured within the IOP, associated with a heating loss of about 100 W m-2. This evolution was shown to be strongly connected to the occurrence of storms at the beginning and the end of October. Above the surface, turbulent measurements from ship and aircraft were analyzed across the surface thermal front, showing a 30% difference in heat fluxes between both sides during a 4-day period, and the respective contributions of the wind and the surface temperature were evaluated. The classical momentum flux bulk

Study of the air-sea interactions at the mesoscale: the SEMAPHORE experiment

Directory of Open Access Journals (Sweden)

L. Eymard

Full Text Available The SEMAPHORE (Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale experiment has been conducted from June to November 1993 in the Northeast Atlantic between the Azores and Madeira. It was centered on the study of the mesoscale ocean circulation and air-sea interactions. The experimental investigation was achieved at the mesoscale using moorings, floats, and ship hydrological survey, and at a smaller scale by one dedicated ship, two instrumented aircraft, and surface drifting buoys, for one and a half month in October-November (IOP: intense observing period. Observations from meteorological operational satellites as well as spaceborne microwave sensors were used in complement. The main studies undertaken concern the mesoscale ocean, the upper ocean, the atmospheric boundary layer, and the sea surface, and first results are presented for the various topics. From data analysis and model simulations, the main characteristics of the ocean circulation were deduced, showing the close relationship between the Azores front meander and the occurrence of Mediterranean water lenses (meddies, and the shift between the Azores current frontal signature at the surface and within the thermocline. Using drifting buoys and ship data in the upper ocean, the gap between the scales of the atmospheric forcing and the oceanic variability was made evident. A 2 °C decrease and a 40-m deepening of the mixed layer were measured within the IOP, associated with a heating loss of about 100 W m^-2. This evolution was shown to be strongly connected to the occurrence of storms at the beginning and the end of October. Above the surface, turbulent measurements from ship and aircraft were analyzed across the surface thermal front, showing a 30% difference in heat fluxes between both sides during a 4-day period, and the respective contributions of the wind and the surface temperature were evaluated. The

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

International Nuclear Information System (INIS)

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

2011-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

1997-12-31

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

Investigating the Potential Impact of the Surface Water and Ocean Topography (SWOT) Altimeter on Ocean Mesoscale Prediction

Science.gov (United States)

Carrier, M.; Ngodock, H.; Smith, S. R.; Souopgui, I.

2016-02-01

NASA's Surface Water and Ocean Topography (SWOT) satellite, scheduled for launch in 2020, will provide sea surface height anomaly (SSHA) observations with a wider swath width and higher spatial resolution than current satellite altimeters. It is expected that this will help to further constrain ocean models in terms of the mesoscale circulation. In this work, this expectation is investigated by way of twin data assimilation experiments using the Navy Coastal Ocean Model Four Dimensional Variational (NCOM-4DVAR) data assimilation system using a weak constraint formulation. Here, a nature run is created from which SWOT observations are sampled, as well as along-track SSHA observations from simulated Jason-2 tracks. The simulated SWOT data has appropriate spatial coverage, resolution, and noise characteristics based on an observation-simulator program provided by the SWOT science team. The experiment is run for a three-month period during which the analysis is updated every 24 hours and each analysis is used to initialize a 96 hour forecast. The forecasts in each experiment are compared to the available nature run to determine the impact of the assimilated data. It is demonstrated here that the SWOT observations help to constrain the model mesoscale in a more consistent manner than traditional altimeter observations. The findings of this study suggest that data from SWOT may have a substantial impact on improving the ocean model analysis and forecast of mesoscale features and surface ocean transport.

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

Science.gov (United States)

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

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

Science.gov (United States)

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

2012-12-01

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

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

Directory of Open Access Journals (Sweden)

Jing Lu

2014-11-01

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

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

Science.gov (United States)

Gross, N. A.; Hughes, W.

2011-12-01

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

Multi-sensor in situ observations to resolve the sub-mesoscale features in the stratified Gulf of Finland, Baltic Sea

Science.gov (United States)

Lips, Urmas; Kikas, Villu; Liblik, Taavi; Lips, Inga

2016-05-01

High-resolution numerical modeling, remote sensing, and in situ data have revealed significant role of sub-mesoscale features in shaping the distribution pattern of tracers in the ocean's upper layer. However, in situ measurements are difficult to conduct with the required resolution and coverage in time and space to resolve the sub-mesoscale, especially in such relatively shallow basins as the Gulf of Finland, where the typical baroclinic Rossby radius is 2-5 km. To map the multi-scale spatiotemporal variability in the gulf, we initiated continuous measurements with autonomous devices, including a moored profiler and Ferrybox system, which were complemented by dedicated research-vessel-based surveys. The analysis of collected high-resolution data in the summers of 2009-2012 revealed pronounced variability at the sub-mesoscale in the presence of mesoscale upwelling/downwelling, fronts, and eddies. The horizontal wavenumber spectra of temperature variance in the surface layer had slopes close to -2 between the lateral scales from 10 to 0.5 km. Similar tendency towards the -2 slopes of horizontal wavenumber spectra of temperature variance was found in the seasonal thermocline between the lateral scales from 10 to 1 km. It suggests that the ageostrophic sub-mesoscale processes could contribute considerably to the energy cascade in such a stratified sea basin. We showed that the intrusions of water with different salinity, which indicate the occurrence of a layered flow structure, could appear in the process of upwelling/downwelling development and relaxation in response to variable wind forcing. We suggest that the sub-mesoscale processes play a major role in feeding surface blooms in the conditions of coupled coastal upwelling and downwelling events in the Gulf of Finland.

Weather forecast

CERN Document Server

Courtier, P

1994-02-07

Weather prediction is performed using the numerical model of the atmosphere evolution.The evolution equations are derived from the Navier Stokes equation for the adiabatic part but the are very much complicated by the change of phase of water, the radiation porocess and the boundary layer.The technique used operationally is described. Weather prediction is an initial value problem and accurate initial conditions need to be specified. Due to the small number of observations available (105 ) as compared to the dimension of the model state variable (107),the problem is largely underdetermined. Techniques of optimal control and inverse problems are used and have been adapted to the large dimension of our problem. our problem.The at mosphere is a chaotic system; the implication for weather prediction is discussed. Ensemble prediction is used operationally and the technique for generating initial conditions which lead to a numerical divergence of the subsequent forecasts is described.

Graphical tools for TV weather presentation

Science.gov (United States)

Najman, M.

2010-09-01

Contemporary meteorology and its media presentation faces in my opinion following key tasks: - Delivering the meteorological information to the end user/spectator in understandable and modern fashion, which follows industry standard of video output (HD, 16:9) - Besides weather icons show also the outputs of numerical weather prediction models, climatological data, satellite and radar images, observed weather as actual as possible. - Does not compromise the accuracy of presented data. - Ability to prepare and adjust the weather show according to actual synoptic situtation. - Ability to refocus and completely adjust the weather show to actual extreme weather events. - Ground map resolution weather data presentation need to be at least 20 m/pixel to be able to follow the numerical weather prediction model resolution. - Ability to switch between different numerical weather prediction models each day, each show or even in the middle of one weather show. - The graphical weather software need to be flexible and fast. The graphical changes nee to be implementable and airable within minutes before the show or even live. These tasks are so demanding and the usual original approach of custom graphics could not deal with it. It was not able to change the show every day, the shows were static and identical day after day. To change the content of the weather show daily was costly and most of the time impossible with the usual approach. The development in this area is fast though and there are several different options for weather predicting organisations such as national meteorological offices and private meteorological companies to solve this problem. What are the ways to solve it? What are the limitations and advantages of contemporary graphical tools for meteorologists? All these questions will be answered.