A New WRF-Chem Treatment for Studying Regional Scale Impacts of Cloud-Aerosol Interactions in Parameterized Cumuli

Energy Technology Data Exchange (ETDEWEB)

Berg, Larry K.; Shrivastava, ManishKumar B.; Easter, Richard C.; Fast, Jerome D.; Chapman, Elaine G.; Liu, Ying

2015-01-01

A new treatment of cloud-aerosol interactions within parameterized shallow and deep convection has been implemented in WRF-Chem that can be used to better understand the aerosol lifecycle over regional to synoptic scales. The modifications to the model to represent cloud-aerosol interactions include treatment of the cloud dropletnumber mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. Thesechanges have been implemented in both the WRF-Chem chemistry packages as well as the Kain-Fritsch cumulus parameterization that has been modified to better represent shallow convective clouds. Preliminary testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS) as well as a high-resolution simulation that does not include parameterized convection. The simulation results are used to investigate the impact of cloud-aerosol interactions on the regional scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column integrated BC can be as large as -50% when cloud-aerosol interactions are considered (due largely to wet removal), or as large as +35% for sulfate in non-precipitating conditions due to the sulfate production in the parameterized clouds. The modifications to WRF-Chem version 3.2.1 are found to account for changes in the cloud drop number concentration (CDNC) and changes in the chemical composition of cloud-drop residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to WRF-Chem version 3.5, and it is anticipated that they

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...

Air pollution modeling over very complex terrain: An evaluation of WRF-Chem over Switzerland for two 1-year periods

Science.gov (United States)

Ritter, Mathias; Müller, Mathias D.; Tsai, Ming-Yi; Parlow, Eberhard

2013-10-01

The fully coupled chemistry module (WRF-Chem) within the Weather Research and Forecasting (WRF) model has been implemented over a Swiss domain for the years 2002 and 1991. The very complex terrain requires a high horizontal resolution (2 × 2 km2), which is achieved by nesting the Swiss domain into a coarser European one. The temporal and spatial distribution of O3, NO2 and PM10 as well as temperature and solar radiation are evaluated against ground-based measurements. The model performs well for the meteorological parameters with Pearson correlation coefficients of 0.92 for temperature and 0.88-0.89 for solar radiation. Temperature has root mean square errors (RMSE) of 3.30 K and 3.51 K for 2002 and 1991 and solar radiation has RMSEs of 122.92 and 116.35 for 2002 and 1991, respectively. For the modeled air pollutants, a multi-linear regression post-processing was used to eliminate systematic bias. Seasonal variations of post-processed air pollutants are represented correctly. However, short-term peaks of several days are not captured by the model. Averaged daily maximum and daily values of O3 achieved Pearson correlation coefficients of 0.69-0.77 whereas averaged NO2 and PM10 had the highest correlations for yearly average values (0.68-0.78). The spatial distribution reveals the importance of PM10 advection from the Po valley to southern Switzerland (Ticino). The absolute errors are ranging from - 10 to 15 μg/m3 for ozone, - 9 to 3 μg/m3 for NO2 and - 4 to 3 μg/m3 for PM10. However, larger errors occur along heavily trafficked roads, in street canyons or on mountains. We also compare yearly modeled results against a dedicated Swiss dispersion model for NO2 and PM10. The dedicated dispersion model has a slightly better statistical performance, but WRF-Chem is capable of computing the temporal evolution of three-dimensional data for a variety of air pollutants and meteorological parameters. Overall, WRF-Chem with the application of post-processing algorithms can

Validating the WRF-Chem model for wind energy applications using High Resolution Doppler Lidar data from a Utah 2012 field campaign

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Mitchell, M. J.; Pichugina, Y. L.; Banta, R. M.

2015-12-01

Models are important tools for assessing potential of wind energy sites, but the accuracy of these projections has not been properly validated. In this study, High Resolution Doppler Lidar (HRDL) data obtained with high temporal and spatial resolution at heights of modern turbine rotors were compared to output from the WRF-chem model in order to help improve the performance of the model in producing accurate wind forecasts for the industry. HRDL data were collected from January 23-March 1, 2012 during the Uintah Basin Winter Ozone Study (UBWOS) field campaign. A model validation method was based on the qualitative comparison of the wind field images, time-series analysis and statistical analysis of the observed and modeled wind speed and direction, both for case studies and for the whole experiment. To compare the WRF-chem model output to the HRDL observations, the model heights and forecast times were interpolated to match the observed times and heights. Then, time-height cross-sections of the HRDL and WRF-Chem wind speed and directions were plotted to select case studies. Cross-sections of the differences between the observed and forecasted wind speed and directions were also plotted to visually analyze the model performance in different wind flow conditions. A statistical analysis includes the calculation of vertical profiles and time series of bias, correlation coefficient, root mean squared error, and coefficient of determination between two datasets. The results from this analysis reveals where and when the model typically struggles in forecasting winds at heights of modern turbine rotors so that in the future the model can be improved for the industry.

Dust modeling over East Asia during the summer of 2010 using the WRF-Chem model

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Zhang, B.; Huang, J.; Chen, S.

2017-12-01

An intense summer dust storm over East Asia during June 24-27, 2010, was systematically analyzed using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and a variety of in situ measurements and satellite retrievals. The results showed that the WRF-Chem model captured the spatial and temporal distributions of meteorological factors and dust aerosols over East Asia. This summer dust storm was initiated by the approach of a transverse trough in the northwestern Xinjiang. Because of the passage of the cutoff-low, a large amount of cold air was transported southward and further enhanced in the narrow valleys of the Altai and Tianshan Mountains, which resulted in higher wind speeds and huge dust emissions over the Taklimakan Desert (TD). Dust emission fluxes over the TD were as high as 54 μg m-2 s-1 on June 25th. The dust aerosols from the TD then swept across Inner Mongolia, Ningxia and Mongolia, and some were also transported eastward to Beijing, Tianjin, the Hebei region, and even South Korea and Japan. The simulations further showed that summer dust over East Asia exerts an important influence on the radiation budget in the Earth-atmosphere system. Dust heat the atmosphere at a maximum heating rate of 0.14 k day-1, effectively changing the vertical stability of the atmosphere and affecting climate change at regional and even global scales. The dust event-averaged direct radiative forcing induced by dust particles over the TD at all-sky was -6.0, -16.8 and 10.8 W m-2 at the top of the atmosphere, the surface, and in the atmosphere, respectively.

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

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Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.; Berg, Larry K.; Fast, Jerome D.; Easter, Richard C.; Shrivastava, Manish; Thomas, Jennie L.

2017-10-01

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain-Fritsch + Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.

Tropospheric ozone using an emission tagging technique in the CAM-Chem and WRF-Chem models

Science.gov (United States)

Lupascu, A.; Coates, J.; Zhu, S.; Butler, T. M.

2017-12-01

Tropospheric ozone is a short-lived climate forcing pollutant. High concentration of ozone can affect human health (cardiorespiratory and increased mortality due to long-term exposure), and also it damages crops. Attributing ozone concentrations to the contributions from different sources would indicate the effects of locally emitted or transported precursors on ozone levels in specific regions. This information could be used as an important component of the design of emissions reduction strategies by indicating which emission sources could be targeted for effective reductions, thus reducing the burden of ozone pollution. Using a "tagging" approach within the CAM-Chem (global) and WRF-Chem (regional) models, we can quantify the contribution of individual emission of NOx and VOC precursors on air quality. Hence, when precursor emissions of NOx are tagged, we have seen that the largest contributors on ozone levels are the anthropogenic sources, while in the case of precursor emissions of VOCs, the biogenic sources and methane account for more than 50% of ozone levels. Further, we have extended the NOx tagging method in order to investigate continental source region contributions to concentrations of ozone over various receptor regions over the globe, with a zoom over Europe. In general, summertime maximum ozone in most receptor regions is largely attributable to local emissions of anthropogenic NOx and biogenic VOC. During the rest of the year, especially during springtime, ozone in most receptor regions shows stronger influences from anthropogenic emissions of NOx and VOC in remote source regions.

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

Directory of Open Access Journals (Sweden)

L. Marelle

2017-10-01

Full Text Available In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols (1 a correction to the sedimentation of aerosols, (2 dimethyl sulfide (DMS oceanic emissions and gas-phase chemistry, (3 an improved representation of the dry deposition of trace gases over seasonal snow, and (4 an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5 correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6 couple and further test the recent KF-CuP (Kain–Fritsch + Cumulus Potential cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC, sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone, the improved surface temperatures over sea ice (surface ozone, BC, and sulfate, and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone. DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.

Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts

Directory of Open Access Journals (Sweden)

G. Grell

2011-06-01

Full Text Available A plume rise algorithm for wildfires was included in WRF-Chem, and applied to look at the impact of intense wildfires during the 2004 Alaska wildfire season on weather simulations using model resolutions of 10 km and 2 km. Biomass burning emissions were estimated using a biomass burning emissions model. In addition, a 1-D, time-dependent cloud model was used online in WRF-Chem to estimate injection heights as well as the vertical distribution of the emission rates. It was shown that with the inclusion of the intense wildfires of the 2004 fire season in the model simulations, the interaction of the aerosols with the atmospheric radiation led to significant modifications of vertical profiles of temperature and moisture in cloud-free areas. On the other hand, when clouds were present, the high concentrations of fine aerosol (PM_2.5 and the resulting large numbers of Cloud Condensation Nuclei (CCN had a strong impact on clouds and cloud microphysics, with decreased precipitation coverage and precipitation amounts during the first 12 h of the integration. During the afternoon, storms were of convective nature and appeared significantly stronger, probably as a result of both the interaction of aerosols with radiation (through an increase in CAPE as well as the interaction with cloud microphysics.

Operational forecast products and applications based on WRF/Chem

Science.gov (United States)

Hirtl, Marcus; Flandorfer, Claudia; Langer, Matthias; Mantovani, Simone; Olefs, Marc; Schellander-Gorgas, Theresa

2015-04-01

The responsibilities of the national weather service of Austria (ZAMG) include the support of the federal states and the public in questions connected to the protection of the environment in the frame of advisory and counseling services as well as expert opinions. The ZAMG conducts daily Air-Quality forecasts using the on-line coupled model WRF/Chem. The mother domain expands over Europe, North Africa and parts of Russia. The nested domain includes the alpine region and has a horizontal resolution of 4 km. Local emissions (Austria) are used in combination with European inventories (TNO and EMEP) for the simulations. The modeling system is presented and the results from the evaluation of the assimilation of pollutants using the 3D-VAR software GSI is shown. Currently observational data (PM10 and O3) from the Austrian Air-Quality network and from European stations (EEA) are assimilated into the model on an operational basis. In addition PM maps are produced using Aerosol Optical Thickness (AOT) observations from MODIS in combination with model data using machine learning techniques. The modeling system is operationally evaluated with different data sets. The emphasis of the application is on the forecast of pollutants which are compared to the hourly values (PM10, O3 and NO2) of the Austrian Air-Quality network. As the meteorological conditions are important for transport and chemical processes, some parameters like wind and precipitation are automatically evaluated (SAL diagrams, maps, …) with other models (e.g. ECMWF, AROME, …) and ground stations via web interface. The prediction of the AOT is also important for operators of solar power plants. In the past Numerical Weather Prediction (NWP) models were used to predict the AOT based on cloud forecasts at the ZAMG. These models do not consider the spatial and temporal variation of the aerosol distribution in the atmosphere with a consequent impact on the accuracy of forecasts especially during clear-sky days

Photochemical Pollution Modeling of Ozone at Metropolitan Area of Porto Alegre - RS/Brazil using WRF/Chem

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Cuchiara, G. C.; Carvalho, J.

2013-05-01

One of the main problems related to air pollution in urban areas is caused by photochemical oxidants, particularly troposphere ozone (O3), which is considered a harmful substance. The O3 precursors (carbon monoxide CO, nitrogen oxides NOx and hydrocarbons HCs) are predominantly of anthropogenic origin in these areas, and vehicles are the main emission sources. Due to the increased urbanization and industrial development in recent decades, air pollutant emissions have increased likewise, mainly by mobile sources in the highly urbanized and developed areas, such as the Metropolitan Area of Porto Alegre-RS (MAPA). According to legal regulations implemented in Brazil in 2005, which aimed at increasing the fraction of biofuels in the national energy matrix, 2% biodiesel were supposed to be added to the fuel mixture within three years, and up to 5% after eight years of implementation of these regulations. Our work performs an analysis of surface concentrations for O3, NOx, CO, and HCs through numerical simulations with WRF/Chem (Weather Research and Forecasting model with Chemistry). The model is validated against observational data obtained from the local urban air quality network for the period from January 5 to 9, 2009 (96 hours). One part of the study focused on the comparison of simulated meteorological variables, to observational data from two stations in MAPA. The results showed that the model simulates well the diurnal evolution of pressure and temperature at the surface, but is much less accurate for wind speed. Another part included the evaluation of model results of WRF/Chem for O3 versus observed data at air quality stations Esteio and Porto Alegre. Comparisons between simulated and observed O3 revealed that the model simulates well the evolution of the observed values, but on many occasions the model did not reproduce well the maximum and minimum concentrations. Finally, a preliminary quantitative sensitivity study on the impact of biofuel on the

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.

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

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

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

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

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

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

Is ozone model bias driven by errors in cloud predictions? A quantitative assessment using satellite cloud retrievals in WRF-Chem

Science.gov (United States)

Ryu, Y. H.; Hodzic, A.; Barré, J.; Descombes, G.; Minnis, P.

2017-12-01

Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much of the bias in O3 predictions is caused by inaccurate cloud predictions. This study quantifies the errors in surface O3 predictions associated with clouds in summertime over CONUS using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Cloud fields used for photochemistry are corrected based on satellite cloud retrievals in sensitivity simulations. It is found that the WRF-Chem model is able to detect about 60% of clouds in the right locations and generally underpredicts cloud optical depths. The errors in hourly O3 due to the errors in cloud predictions can be up to 60 ppb. On average in summertime over CONUS, the errors in 8-h average O3 of 1-6 ppb are found to be attributable to those in cloud predictions under cloudy sky conditions. The contribution of changes in photolysis rates due to clouds is found to be larger ( 80 % on average) than that of light-dependent BVOC emissions. The effects of cloud corrections on O­3 are about 2 times larger in VOC-limited than NOx-limited regimes, suggesting that the benefits of accurate cloud predictions would be greater in VOC-limited than NOx-limited regimes.

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

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

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

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.

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

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

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....

Assessing regional scale predictions of aerosols, marine stratocumulus, and their interactions during VOCALS-REx using WRF-Chem

Directory of Open Access Journals (Sweden)

Q. Yang

2011-12-01

Full Text Available This study assesses the ability of the recent chemistry version (v3.3 of the Weather Research and Forecasting (WRF-Chem model to simulate boundary layer structure, aerosols, stratocumulus clouds, and energy fluxes over the Southeast Pacific Ocean. Measurements from the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx and satellite retrievals (i.e., products from the MODerate resolution Imaging Spectroradiometer (MODIS, Clouds and Earth's Radiant Energy System (CERES, and GOES-10 are used for this assessment. The Morrison double-moment microphysics scheme is newly coupled with interactive aerosols in the model. The 31-day (15 October–16 November 2008 WRF-Chem simulation with aerosol-cloud interactions (AERO hereafter is also compared to a simulation (MET hereafter with fixed cloud droplet number concentrations in the microphysics scheme and simplified cloud and aerosol treatments in the radiation scheme. The well-simulated aerosol quantities (aerosol number, mass composition and optical properties, and the inclusion of full aerosol-cloud couplings lead to significant improvements in many features of the simulated stratocumulus clouds: cloud optical properties and microphysical properties such as cloud top effective radius, cloud water path, and cloud optical thickness. In addition to accounting for the aerosol direct and semi-direct effects, these improvements feed back to the simulation of boundary-layer characteristics and energy budgets. Particularly, inclusion of interactive aerosols in AERO strengthens the temperature and humidity gradients within the capping inversion layer and lowers the marine boundary layer (MBL depth by 130 m from that of the MET simulation. These differences are associated with weaker entrainment and stronger mean subsidence at the top of the MBL in AERO. Mean top-of-atmosphere outgoing shortwave fluxes, surface latent heat, and surface downwelling longwave fluxes are in better agreement with

Simulations of the Holuhraun eruption 2014 with WRF-Chem and evaluation with satellite and ground based SO2 measurements

Science.gov (United States)

Hirtl, Marcus; Arnold-Arias, Delia; Flandorfer, Claudia; Maurer, Christian; Mantovani, Simone; Natali, Stefano

2016-04-01

Volcanic eruptions, with gas or/and particle emissions, directly influence our environment, with special significance when they either occur near inhabited regions or are transported towards them. In addition to the well-known affectation of air traffic, with large economic impacts, the ground touching plumes can lead directly to an influence of soil, water and even to a decrease of air quality. The eruption of Holuhraun in August 2014 in central Iceland is the country's largest lava and gas eruption since the Lakagígar eruption in 1783. Nevertheless, very little volcanic ash was produced. The main atmospheric threat from this event was the SO2 pollution that frequently violated the Icelandic National Air Quality Standards in many population centers. However, the SO2 affectation was not limited to Iceland but extended to mainland Europe. The on-line coupled model WRF-Chem is used to simulate the dispersion of SO2 for this event that affected the central European regions. The volcanic emissions are considered in addition to the anthropogenic and biogenic ground sources at European scale. A modified version of WRF-Chem version 4.1 is used in order to use time depending injection heights and mass fluxes which were obtained from in situ observations. WRF-Chem uses complex gas- (RADM2) and aerosol- (MADE-SORGAM) chemistry and is operated on a European domain (12 km resolution), and a nested grid covering the Alpine region (4 km resolution). The study is showing the evaluation of the model simulations with satellite and ground based measurement data of SO2. The analysis is conducted on a data management platform, which is currently developed in the frame of the ESA-funded project TAMP "Technology and Atmospheric Mission Platform": it provides comprehensive functionalities to visualize and numerically compare data from different sources (model, satellite and ground-measurements).

A statistical downscaling approach for roadside NO2 concentrations: Application to a WRF-Chem study for Berlin

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Kuik, Friderike; Lauer, Axel; von Schneidemesser, Erika; Butler, Tim

2017-04-01

Many European cities continue to struggle with meeting the European air quality limits for NO2. In Berlin, Germany, most of the exceedances in NO2 recorded at monitoring sites near busy roads can be largely attributed to emissions from traffic. In order to assess the impact of changes in traffic emissions on air quality at policy relevant scales, we combine the regional atmosphere-chemistry transport model WRF-Chem at a resolution of 1kmx1km with a statistical downscaling approach. Here, we build on the recently published study evaluating the performance of a WRF-Chem setup in representing observed urban background NO2 concentrations from Kuik et al. (2016) and extend this setup by developing and testing an approach to statistically downscale simulated urban background NO2 concentrations to street level. The approach uses a multilinear regression model to relate roadside NO2 concentrations observed with the municipal monitoring network with observed NO2 concentrations at urban background sites and observed traffic counts. For this, the urban background NO2 concentrations are decomposed into a long term, a synoptic and a diurnal component using the Kolmogorov-Zurbenko filtering method. We estimate the coefficients of the regression model for five different roadside stations in Berlin representing different street types. In a next step we combine the coefficients with simulated urban background concentrations and observed traffic counts, in order to estimate roadside NO2 concentrations based on the results obtained with WRF-Chem at the five selected stations. In a third step, we extrapolate the NO2 concentrations to all major roads in Berlin. The latter is based on available data for Berlin of daily mean traffic counts, diurnal and weekly cycles of traffic as well as simulated urban background NO2 concentrations. We evaluate the NO2 concentrations estimated with this method at street level for Berlin with additional observational data from stationary measurements and

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

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

(WRFDA) for WRF non-hydrostatic mesoscale model

Indian Academy of Sciences (India)

Sujata Pattanayak

2018-05-22

May 22, 2018 ... Keywords. WRF-NMM; WRFDA; single observation test; eigenvalues; eigenvector; correlation; tropical .... The per- turbation variables here are defined as deviations ..... Synop, Sound, Metar, Pilot, Buoy, Ships, Airep,. Geoamv ...

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.

A framework for WRF to WRF-IBM grid nesting to enable multiscale simulations

Energy Technology Data Exchange (ETDEWEB)

Wiersema, David John [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Univ. of California, Berkeley, CA (United States); Lundquist, Katherine A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Chow, Fotini Katapodes [Univ. of California, Berkeley, CA (United States)

2016-09-29

With advances in computational power, mesoscale models, such as the Weather Research and Forecasting (WRF) model, are often pushed to higher resolutions. As the model’s horizontal resolution is refined, the maximum resolved terrain slope will increase. Because WRF uses a terrain-following coordinate, this increase in resolved terrain slopes introduces additional grid skewness. At high resolutions and over complex terrain, this grid skewness can introduce large numerical errors that require methods, such as the immersed boundary method, to keep the model accurate and stable. Our implementation of the immersed boundary method in the WRF model, WRF-IBM, has proven effective at microscale simulations over complex terrain. WRF-IBM uses a non-conforming grid that extends beneath the model’s terrain. Boundary conditions at the immersed boundary, the terrain, are enforced by introducing a body force term to the governing equations at points directly beneath the immersed boundary. Nesting between a WRF parent grid and a WRF-IBM child grid requires a new framework for initialization and forcing of the child WRF-IBM grid. This framework will enable concurrent multi-scale simulations within the WRF model, improving the accuracy of high-resolution simulations and enabling simulations across a wide range of scales.

A high resolution WRF model for wind energy forecasting

Science.gov (United States)

Vincent, Claire Louise; Liu, Yubao

2010-05-01

The increasing penetration of wind energy into national electricity markets has increased the demand for accurate surface layer wind forecasts. There has recently been a focus on forecasting the wind at wind farm sites using both statistical models and numerical weather prediction (NWP) models. Recent advances in computing capacity and non-hydrostatic NWP models means that it is possible to nest mesoscale models down to Large Eddy Simulation (LES) scales over the spatial area of a typical wind farm. For example, the WRF model (Skamarock 2008) has been run at a resolution of 123 m over a wind farm site in complex terrain in Colorado (Liu et al. 2009). Although these modelling attempts indicate a great hope for applying such models for detailed wind forecasts over wind farms, one of the obvious challenges of running the model at this resolution is that while some boundary layer structures are expected to be modelled explicitly, boundary layer eddies into the inertial sub-range can only be partly captured. Therefore, the amount and nature of sub-grid-scale mixing that is required is uncertain. Analysis of Liu et al. (2009) modelling results in comparison to wind farm observations indicates that unrealistic wind speed fluctuations with a period of around 1 hour occasionally occurred during the two day modelling period. The problem was addressed by re-running the same modelling system with a) a modified diffusion constant and b) two-way nesting between the high resolution model and its parent domain. The model, which was run with horizontal grid spacing of 370 m, had dimensions of 505 grid points in the east-west direction and 490 points in the north-south direction. It received boundary conditions from a mesoscale model of resolution 1111 m. Both models had 37 levels in the vertical. The mesoscale model was run with a non-local-mixing planetary boundary layer scheme, while the 370 m model was run with no planetary boundary layer scheme. It was found that increasing the

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)

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.

Operational on-line coupled chemical weather forecasts for Europe with WRF/Chem

Science.gov (United States)

Hirtl, Marcus; Mantovani, Simone; Krüger, Bernd C.; Flandorfer, Claudia; Langer, Matthias

2014-05-01

Air quality is a key element for the well-being and quality of life of European citizens. Air pollution measurements and modeling tools are essential for the assessment of air quality according to EU legislation. The responsibilities of ZAMG as the national weather service of Austria include the support of the federal states and the public in questions connected to the protection of the environment in the frame of advisory and counseling services as well as expert opinions. ZAMG conducts daily Air-Quality forecasts using the on-line coupled model WRF/Chem. Meteorology is simulated simultaneously with the emissions, turbulent mixing, transport, transformation, and fate of trace gases and aerosols. The emphasis of the application is on predicting pollutants over Austria. Two domains are used for the simulations: the mother domain covers Europe with a resolution of 12 km, the inner domain includes the alpine region with a horizontal resolution of 4 km; 45 model levels are used in the vertical direction. The model runs 2 times per day for a period of 72 hours and is initialized with ECMWF forecasts. On-line coupled models allow considering two-way interactions between different atmospheric processes including chemistry (both gases and aerosols), clouds, radiation, boundary layer, emissions, meteorology and climate. In the operational set-up direct-, indirect and semi-direct effects between meteorology and air chemistry are enabled. The model is running on the HPCF (High Performance Computing Facility) of the ZAMG. In the current set-up 1248 CPUs are used. As the simulations need a big amount of computing resources, a method to safe I/O-time was implemented. Every MPI task writes all its output into the shared memory filesystem of the compute nodes. Once the WRF/Chem integration is finished, all split NetCDF-files are merged and saved on the global file system. The merge-routine is based on parallel-NetCDF. With this method the model runs about 30% faster on the SGI

Comparative Evaluation of the Impact of WRF-NMM and WRF-ARW Meteorology on CMAQ Simulations for O3 and Related Species During the 2006 TexAQS/GoMACCS Campaign

Science.gov (United States)

In this paper, impact of meteorology derived from the Weather, Research and Forecasting (WRF)– Non–hydrostatic Mesoscale Model (NMM) and WRF–Advanced Research WRF (ARW) meteorological models on the Community Multiscale Air Quality (CMAQ) simulations for ozone and its related prec...

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.

Quantifying sources of elemental carbon over the Guanzhong Basin of China: A consistent network of measurements and WRF-Chem modeling

International Nuclear Information System (INIS)

Li, Nan; He, Qingyang; Tie, Xuexi; Cao, Junji; Liu, Suixin; Wang, Qiyuan; Li, Guohui; Huang, Rujin; Zhang, Qiang

2016-01-01

We conducted a year-long WRF-Chem (Weather Research and Forecasting Chemical) model simulation of elemental carbon (EC) aerosol and compared the modeling results to the surface EC measurements in the Guanzhong (GZ) Basin of China. The main goals of this study were to quantify the individual contributions of different EC sources to EC pollution, and to find the major cause of the EC pollution in this region. The EC measurements were simultaneously conducted at 10 urban, rural, and background sites over the GZ Basin from May 2013 to April 2014, and provided a good base against which to evaluate model simulation. The model evaluation showed that the calculated annual mean EC concentration was 5.1 μgC m −3 , which was consistent with the observed value of 5.3 μgC m −3 . Moreover, the model result also reproduced the magnitude of measured EC in all seasons (regression slope = 0.98–1.03), as well as the spatial and temporal variations (r = 0.55–0.78). We conducted several sensitivity studies to quantify the individual contributions of EC sources to EC pollution. The sensitivity simulations showed that the local and outside sources contributed about 60% and 40% to the annual mean EC concentration, respectively, implying that local sources were the major EC pollution contributors in the GZ Basin. Among the local sources, residential sources contributed the most, followed by industry and transportation sources. A further analysis suggested that a 50% reduction of industry or transportation emissions only caused a 6% decrease in the annual mean EC concentration, while a 50% reduction of residential emissions reduced the winter surface EC concentration by up to 25%. In respect to the serious air pollution problems (including EC pollution) in the GZ Basin, our findings can provide an insightful view on local air pollution control strategies. - Highlights: • A yearlong WRF-Chem simulation is conducted to identify sources of the EC pollution. • A network of

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.

Spatio-temporal variability of CO and O3 in Hyderabad (17°N, 78°E, central India, based on MOZAIC and TES observations and WRF-Chem and MOZART-4 models

Directory of Open Access Journals (Sweden)

Varun Sheel

2016-05-01

Full Text Available This article is based on the study of the seasonal and interannual variability of carbon monoxide (CO and ozone (O3 at different altitudes of the troposphere over Hyderabad, India, during 2006–2010 using Measurement of OZone and water vapour by Airbus In-Service Aircraft (MOZAIC and observation from Tropospheric Emission Spectrometer (TES aboard NASA's Aura satellite. The MOZAIC observations show maximum seasonal variability in both CO and O3 during winter and pre-monsoon season, with CO in the range (100–200±13 ppbv and O3 in the range (50–70±9 ppbv. The time-series of MOZAIC data shows a significant increase of 4.2±1.3 % in the surface CO and 6.7±1.3 % in the surface O3 during 2006–2010 in Hyderabad. From MOZAIC observations, we identify CO and O3 profiles that are anomalous with respect to the monthly mean and compare those with Weather Research Forecast model coupled with Chemistry (WRF-Chem and Model for OZone and Related Tracers, version 4 profiles for the same day. The anomalous profiles of WRF-Chem are simulated using three convection schemes. The goodness of comparison depends on the convection scheme and the altitude region of the troposphere.

A WRF-Chem model study of the impact of VOCs emission of a huge petro-chemical industrial zone on the summertime ozone in Beijing, China

Science.gov (United States)

Wei, Wei; Lv, Zhao Feng; Li, Yue; Wang, Li Tao; Cheng, Shuiyuan; Liu, Huan

2018-02-01

In China, petro-chemical manufacturing plants generally gather in the particular industrial zone defined as PIZ in some cities, and distinctly influence the air quality of these cities for their massive VOCs emissions. This study aims to quantify the local and regional impacts of PIZ VOCs emission and its relevant reduction policy on the surface ozone based on WRF-Chem model, through the case study of Beijing. Firstly, the model simulation under the actual precursors' emissions over Beijing region for July 2010 is conducted and evaluated, which meteorological and chemical predictions both within the thresholds for satisfactory model performance. Then, according to simulated H2O2/HNO3 ratio, the nature of photochemical ozone formation over Beijing is decided, the VOCs-sensitive regime over the urban areas, NOx-sensitive regime over the northern and western rural areas, and both VOCssbnd and NOx-mixed sensitive regime over the southern and eastern rural areas. Finally, a 30% VOCs reduction scenario (RS) and a 100% VOCs reduction scenario (ZS) for Beijing PIZ are additional simulated by WRF-Chem. The sensitivity simulations imply that the current 30% reduction policy would bring about an O3 increase in the southern and western areas (by +4.7 ppb at PIZ site and +2.1 ppb at LLH station), and an O3 decrease in the urban center (by -1.7 ppb at GY station and -2.5 ppb at DS station) and in the northern and eastern areas (by -1.2 ppb at MYX station), mainly through interfering with the circulation of atmospheric HOx radicals. While the contribution of the total VOCs emission of PIZ to ozone is greatly prominent in the PIZ and its surrounding areas along south-north direction (12.7% at PIZ site on average), but slight in the other areas of Beijing (<3% in other four stations on average).

Comparison of Thunderstorm Simulations from WRF-NMM and WRF-ARW Models over East Indian Region

Directory of Open Access Journals (Sweden)

A. J. Litta

2012-01-01

Full Text Available The thunderstorms are typical mesoscale systems dominated by intense convection. Mesoscale models are essential for the accurate prediction of such high-impact weather events. In the present study, an attempt has been made to compare the simulated results of three thunderstorm events using NMM and ARW model core of WRF system and validated the model results with observations. Both models performed well in capturing stability indices which are indicators of severe convective activity. Comparison of model-simulated radar reflectivity imageries with observations revealed that NMM model has simulated well the propagation of the squall line, while the squall line movement was slow in ARW. From the model-simulated spatial plots of cloud top temperature, we can see that NMM model has better captured the genesis, intensification, and propagation of thunder squall than ARW model. The statistical analysis of rainfall indicates the better performance of NMM than ARW. Comparison of model-simulated thunderstorm affected parameters with that of the observed showed that NMM has performed better than ARW in capturing the sharp rise in humidity and drop in temperature. This suggests that NMM model has the potential to provide unique and valuable information for severe thunderstorm forecasters over east Indian region.

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.

Radiative effects of black carbon aerosols on Indian monsoon: a study using WRF-Chem model

Science.gov (United States)

Soni, Pramod; Tripathi, Sachchida Nand; Srivastava, Rajesh

2018-04-01

The Weather Research and Forecasting model with Chemistry (WRF-Chem) is utilized to examine the radiative effects of black carbon (BC) aerosols on the Indian monsoon, for the year 2010. Five ensemble simulations with different initial conditions (1st to 5th December, 2009) were performed and simulation results between 1st January, 2010 to 31st December, 2010 were used for analysis. Most of the BC which stays near the surface during the pre-monsoon season gets transported to higher altitudes with the northward migration of the Inter Tropical Convergence Zone (ITCZ) during the monsoon season. In both the seasons, strong negative SW anomalies are present at the surface along with positive anomalies in the atmosphere, which results in the surface cooling and lower tropospheric heating, respectively. During the pre-monsoon season, lower troposphere heating causes increased convection and enhanced meridional wind circulation, bringing moist air from Indian Ocean and Bay of Bengal to the North-East India, leading to increased rainfall there. However, during the monsoon season, along with cooling over the land regions, a warming over the Bay of Bengal is simulated. This differential heating results in an increased westerly moisture flux anomaly over central India, leading to increased rainfall over northern parts of India but decreased rainfall over southern parts. Decreased rainfall over southern India is also substantiated by the presence of increased evaporation over Bay of Bengal and decrease over land regions.

Modeling regional air quality and climate: improving organic aerosol and aerosol activation processes in WRF/Chem version 3.7.1

Science.gov (United States)

Yahya, Khairunnisa; Glotfelty, Timothy; Wang, Kai; Zhang, Yang; Nenes, Athanasios

2017-06-01

Air quality and climate influence each other through the uncertain processes of aerosol formation and cloud droplet activation. In this study, both processes are improved in the Weather, Research and Forecasting model with Chemistry (WRF/Chem) version 3.7.1. The existing Volatility Basis Set (VBS) treatments for organic aerosol (OA) formation in WRF/Chem are improved by considering the following: the secondary OA (SOA) formation from semi-volatile primary organic aerosol (POA), a semi-empirical formulation for the enthalpy of vaporization of SOA, and functionalization and fragmentation reactions for multiple generations of products from the oxidation of VOCs. Over the continental US, 2-month-long simulations (May to June 2010) are conducted and results are evaluated against surface and aircraft observations during the Nexus of Air Quality and Climate Change (CalNex) campaign. Among all the configurations considered, the best performance is found for the simulation with the 2005 Carbon Bond mechanism (CB05) and the VBS SOA module with semivolatile POA treatment, 25 % fragmentation, and the emissions of semi-volatile and intermediate volatile organic compounds being 3 times the original POA emissions. Among the three gas-phase mechanisms (CB05, CB6, and SAPRC07) used, CB05 gives the best performance for surface ozone and PM2. 5 concentrations. Differences in SOA predictions are larger for the simulations with different VBS treatments (e.g., nonvolatile POA versus semivolatile POA) compared to the simulations with different gas-phase mechanisms. Compared to the simulation with CB05 and the default SOA module, the simulations with the VBS treatment improve cloud droplet number concentration (CDNC) predictions (normalized mean biases from -40.8 % to a range of -34.6 to -27.7 %), with large differences between CB05-CB6 and SAPRC07 due to large differences in their OH and HO2 predictions. An advanced aerosol activation parameterization based on the Fountoukis and Nenes

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....

Impact of vehicular emissions on the formation of fine particles in the Sao Paulo Metropolitan Area: a numerical study with the WRF-Chem model

Directory of Open Access Journals (Sweden)

A. Vara-Vela

2016-01-01

Full Text Available The objective of this work is to evaluate the impact of vehicular emissions on the formation of fine particles (PM2.5;  ≤  2.5 µm in diameter in the Sao Paulo Metropolitan Area (SPMA in Brazil, where ethanol is used intensively as a fuel in road vehicles. The Weather Research and Forecasting with Chemistry (WRF-Chem model, which simulates feedbacks between meteorological variables and chemical species, is used as a photochemical modelling tool to describe the physico-chemical processes leading to the evolution of number and mass size distribution of particles through gas-to-particle conversion. A vehicular emission model based on statistical information of vehicular activity is applied to simulate vehicular emissions over the studied area. The simulation has been performed for a 1-month period (7 August–6 September 2012 to cover the availability of experimental data from the NUANCE-SPS (Narrowing the Uncertainties on Aerosol and Climate Changes in Sao Paulo State project that aims to characterize emissions of atmospheric aerosols in the SPMA. The availability of experimental measurements of atmospheric aerosols and the application of the WRF-Chem model made it possible to represent some of the most important properties of fine particles in the SPMA such as the mass size distribution and chemical composition, besides allowing us to evaluate its formation potential through the gas-to-particle conversion processes. Results show that the emission of primary gases, mostly from vehicles, led to a production of secondary particles between 20 and 30 % in relation to the total mass concentration of PM2.5 in the downtown SPMA. Each of PM2.5 and primary natural aerosol (dust and sea salt contributed with 40–50 % of the total PM10 (i.e. those  ≤  10 µm in diameter concentration. Over 40 % of the formation of fine particles, by mass, was due to the emission of hydrocarbons, mainly aromatics. Furthermore, an increase in the

Impact of vehicular emissions on the formation of fine particles in the Sao Paulo Metropolitan Area: a numerical study with the WRF-Chem model

Science.gov (United States)

Vara-Vela, A.; Andrade, M. F.; Kumar, P.; Ynoue, R. Y.; Muñoz, A. G.

2016-01-01

The objective of this work is to evaluate the impact of vehicular emissions on the formation of fine particles (PM2.5; ≤ 2.5 µm in diameter) in the Sao Paulo Metropolitan Area (SPMA) in Brazil, where ethanol is used intensively as a fuel in road vehicles. The Weather Research and Forecasting with Chemistry (WRF-Chem) model, which simulates feedbacks between meteorological variables and chemical species, is used as a photochemical modelling tool to describe the physico-chemical processes leading to the evolution of number and mass size distribution of particles through gas-to-particle conversion. A vehicular emission model based on statistical information of vehicular activity is applied to simulate vehicular emissions over the studied area. The simulation has been performed for a 1-month period (7 August-6 September 2012) to cover the availability of experimental data from the NUANCE-SPS (Narrowing the Uncertainties on Aerosol and Climate Changes in Sao Paulo State) project that aims to characterize emissions of atmospheric aerosols in the SPMA. The availability of experimental measurements of atmospheric aerosols and the application of the WRF-Chem model made it possible to represent some of the most important properties of fine particles in the SPMA such as the mass size distribution and chemical composition, besides allowing us to evaluate its formation potential through the gas-to-particle conversion processes. Results show that the emission of primary gases, mostly from vehicles, led to a production of secondary particles between 20 and 30 % in relation to the total mass concentration of PM2.5 in the downtown SPMA. Each of PM2.5 and primary natural aerosol (dust and sea salt) contributed with 40-50 % of the total PM10 (i.e. those ≤ 10 µm in diameter) concentration. Over 40 % of the formation of fine particles, by mass, was due to the emission of hydrocarbons, mainly aromatics. Furthermore, an increase in the number of small particles impaired the

North Pacific Mesoscale Coupled Air-Ocean Simulations Compared with Observations

Energy Technology Data Exchange (ETDEWEB)

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

2014-11-14

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

Assessing the Impact of Oil and Natural Gas Activities on Regional Air Quality in the Colorado Northern Front Range using WRF-Chem

Science.gov (United States)

Abdioskouei, M.; Carmichael, G. R.

2017-12-01

Recent increases in the Natural Gas (NG) production through hydraulic fracturing have questioned the climate benefit of switching from coal-fired to natural gas-fired power plants. Higher than expected levels of methane, VOCs, and NOx have been observed in areas close to oil and NG (OnG) operation facilities. High uncertainty in the OnG emission inventories and methane budget challenge the assessment of OnG impact on air quality and climate and consequently development of effective mitigation policies and control regulations. In this work, we focus on reducing the uncertainties around the OnG emissions by using high resolution (4x4 km2) WRF-Chem simulations coupled with detailed observation from the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ 2014) field campaign. First, we identified the optimal WRF-Chem configurations in the NFR area. We compared the performance of local and non-local Planetary Boundary Layer (PBL) schemes in predicting the PBL height and vertical mixing in the domain. We evaluated the impact of different meteorological and chemical initial and boundary conditions on the model performance. Next, simulations based on optimal configurations were used to assess the performance of the emission inventory (NEI-2011v2). To evaluate the impact of OnG emission on regional air quality and performance of NEI-2011 we tested the sensitivity of the model to the OnG emission. Comparison between simulated values and ground-based and airborne measurements shows a low bias of OnG emission in NEI-2011. Finally, inverse modeling techniques based on emission sensitivity simulations are being used to optimal scaling the OnG emission from the NEI-2011.

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

Science.gov (United States)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Eastman, Joseph L.; Tao, Wei-Kuo

2007-01-01

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

Mesoscale modeling of smoke radiative feedback over the Sahel region

Science.gov (United States)

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

2013-12-01

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

Modeling regional air quality and climate: improving organic aerosol and aerosol activation processes in WRF/Chem version 3.7.1

Directory of Open Access Journals (Sweden)

K. Yahya

2017-06-01

Full Text Available Air quality and climate influence each other through the uncertain processes of aerosol formation and cloud droplet activation. In this study, both processes are improved in the Weather, Research and Forecasting model with Chemistry (WRF/Chem version 3.7.1. The existing Volatility Basis Set (VBS treatments for organic aerosol (OA formation in WRF/Chem are improved by considering the following: the secondary OA (SOA formation from semi-volatile primary organic aerosol (POA, a semi-empirical formulation for the enthalpy of vaporization of SOA, and functionalization and fragmentation reactions for multiple generations of products from the oxidation of VOCs. Over the continental US, 2-month-long simulations (May to June 2010 are conducted and results are evaluated against surface and aircraft observations during the Nexus of Air Quality and Climate Change (CalNex campaign. Among all the configurations considered, the best performance is found for the simulation with the 2005 Carbon Bond mechanism (CB05 and the VBS SOA module with semivolatile POA treatment, 25 % fragmentation, and the emissions of semi-volatile and intermediate volatile organic compounds being 3 times the original POA emissions. Among the three gas-phase mechanisms (CB05, CB6, and SAPRC07 used, CB05 gives the best performance for surface ozone and PM2. 5 concentrations. Differences in SOA predictions are larger for the simulations with different VBS treatments (e.g., nonvolatile POA versus semivolatile POA compared to the simulations with different gas-phase mechanisms. Compared to the simulation with CB05 and the default SOA module, the simulations with the VBS treatment improve cloud droplet number concentration (CDNC predictions (normalized mean biases from −40.8 % to a range of −34.6 to −27.7 %, with large differences between CB05–CB6 and SAPRC07 due to large differences in their OH and HO2 predictions. An advanced aerosol activation

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.

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.

Coupling of WRF and Building-resolved CFD Simulations for Greenhouse Gas Transport and Dispersion

Science.gov (United States)

Prasad, K.; Hu, H.; McDermott, R.; Lopez-Coto, I.; Davis, K. J.; Whetstone, J. R.; Lauvaux, T.

2014-12-01

The Indianapolis Flux Experiment (INFLUX) aims to use a top-down inversion methodology to quantify sources of Greenhouse Gas (GHG) emissions over an urban domain with high spatial and temporal resolution. Atmospheric transport of tracer gases from an emission source to a tower mounted receptor are usually conducted using the Weather Research and Forecasting (WRF) model. WRF is used extensively in the atmospheric community to simulate mesoscale atmospheric transport. For such simulations, WRF employs a parameterized turbulence model and does not resolve the fine scale dynamics that are generated by the flow around buildings and communities that are part of a large city. Since the model domain includes the city of Indianapolis, much of the flow of interest is over an urban topography. The NIST Fire Dynamics Simulator (FDS) is a computational fluid dynamics model to perform large eddy simulations of flow around buildings, but it has not been nested within a larger-scale atmospheric transport model such as WRF. FDS has the potential to evaluate the impact of complex urban topography on near-field dispersion and mixing that cannot be simulated with a mesoscale atmospheric model, and which may be important to determining urban GHG emissions using atmospheric measurements. A methodology has been developed to run FDS as a sub-grid scale model within a WRF simulation. The coupling is based on nudging the FDS flow field towards the one computed by WRF, and is currently limited to one way coupling performed in an off-line mode. Using the coupled WRF / FDS model, NIST will investigate the effects of the urban canopy at horizontal resolutions of 2-10 m. The coupled WRF-FDS simulations will be used to calculate the dispersion of tracer gases in an urban domain and to evaluate the upwind areas that contribute to tower observations, referred to in the inversion community as influence functions. Predicted mixing ratios will be compared with tower measurements and WRF simulations

Application of WRF/Chem over the Continental U.S. under the AQMEII Phase II: Part 2. Evaluation of 2010 Application and Responses of Air Quality and Meteorology-Chemistry Interactions to Changes in Emissions and Meteorology from 2006 to 2010

Science.gov (United States)

The Weather Research and Forecasting model with Chemistry (WRF/Chem) simulation with the 2005 Carbon Bond (CB05) gas-phase mechanism coupled to the Modal for Aerosol Dynamics for Europe (MADE) and the Volatility Basis Set (VBS) approach for secondary organic aerosol (SOA) (MADE/V...

Mesoscale wind fluctuations over Danish waters

Energy Technology Data Exchange (ETDEWEB)

Vincent, C.L.

2010-12-15

mesoscale fluctuations in a mesoscale model is then examined using the weather research and forecasting (WRF) model. A set of case studies demonstrate that realistic hour-scale wind fluctuations and open cellular convection patterns develop in WRF simulations with 2 km horizontal grid spacing. The atmospheric conditions during one of the case studies are then used to initialise a simplified version of the model that has no large scale weather forcing, topography or surface inhomogeneties. Using the simplified model, the sensitivity of the modelled open cellular convection to choices in model setup and to aspects of the environmental forcing are tested. Finally, the cell-scale kinetic energy budget of the modelled cells is calculated, and it is shown that the buoyancy and pressure balance terms are important for cell maintenance. It is explained that the representation of mesoscale convection in a mesoscale model is not only important to end users such as wind farm operators, but to the treatment of energy transport within the boundary layer. (Author)

Evaluation of the WRF model for precipitation downscaling on orographic complex islands

Science.gov (United States)

Díaz, Juan P.; González, Albano; Expósito, Francisco; Pérez, Juan C.

2010-05-01

General Circulation Models (GCMs) have proven to be an effective tool to simulate many aspects of large-scale and global climate. However, their applicability to climate impact studies is limited by their capabilities to resolve regional scale situations. In this sense, dynamical downscaling techniques are an appropriate alternative to estimate high resolution regional climatologies. In this work, the Weather Research and Forecasting model (WRF) has been used to simulate precipitations over the Canary Islands region during 2009. The precipitation patterns over Canary Islands, located at North Atlantic region, show large gradients over a relatively small geographical area due to large scale factors such as Trade Winds regime predominant in the area and mesoscale factors mainly due to the complex terrain. Sensitivity study of simulated WRF precipitations to variations in model setup and parameterizations was carried out. Thus, WRF experiments were performed using two way nesting at 3 km horizontal grid spacing and 28 vertical levels in the Canaries inner domain. The initial and lateral and lower boundary conditions for the outer domain were provided at 6 hourly intervals by NCEP FNL (Final) Operational Global Analysis data on 1.0x1.0 degree resolution interpolated onto the WRF model grid. Numerous model options have been tested, including different microphysics schemes, cumulus parameterizations and nudging configuration Positive-definite moisture advection condition was also checked. Two integration approaches were analyzed: a 1-year continuous long-term integration and a consecutive short-term monthly reinitialized integration. To assess the accuracy of our simulations, model results are compared against observational datasets obtained from a network of meteorological stations in the region. In general, we can observe that the regional model is able to reproduce the spatial distribution of precipitation, but overestimates rainfall, mainly during strong

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-Chem

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

NARCIS (Netherlands)

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

2014-01-01

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

Optimizing zonal advection of the Advanced Research WRF (ARW) dynamics for Intel MIC

Science.gov (United States)

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

2014-10-01

The Weather Research and Forecast (WRF) model is the most widely used community weather forecast and research model in the world. There are two distinct varieties of WRF. The Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we will use Intel Intel Many Integrated Core (MIC) architecture to substantially increase the performance of a zonal advection subroutine for optimization. It is of the most time consuming routines in the ARW dynamics core. Advection advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 2.4x.

A WRF/Chem sensitivity study using ensemble modelling for a high ozone episode in Slovenia and the Northern Adriatic area

Science.gov (United States)

Žabkar, Rahela; Koračin, Darko; Rakovec, Jože

2013-10-01

A high ozone (O3) concentrations episode during a heat wave event in the Northeastern Mediterranean was investigated using the WRF/Chem model. To understand the major model uncertainties and errors as well as the impacts of model inputs on the model accuracy, an ensemble modelling experiment was conducted. The 51-member ensemble was designed by varying model physics parameterization options (PBL schemes with different surface layer and land-surface modules, and radiation schemes); chemical initial and boundary conditions; anthropogenic and biogenic emission inputs; and model domain setup and resolution. The main impacts of the geographical and emission characteristics of three distinct regions (suburban Mediterranean, continental urban, and continental rural) on the model accuracy and O3 predictions were investigated. In spite of the large ensemble set size, the model generally failed to simulate the extremes; however, as expected from probabilistic forecasting the ensemble spread improved results with respect to extremes compared to the reference run. Noticeable model nighttime overestimations at the Mediterranean and some urban and rural sites can be explained by too strong simulated winds, which reduce the impact of dry deposition and O3 titration in the near surface layers during the nighttime. Another possible explanation could be inaccuracies in the chemical mechanisms, which are suggested also by model insensitivity to variations in the nitrogen oxides (NOx) and volatile organic compounds (VOC) emissions. Major impact factors for underestimations of the daytime O3 maxima at the Mediterranean and some rural sites include overestimation of the PBL depths, a lack of information on forest fires, too strong surface winds, and also possible inaccuracies in biogenic emissions. This numerical experiment with the ensemble runs also provided guidance on an optimum model setup and input data.

Modeling mesoscale eddies

Science.gov (United States)

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

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

Simulation of Mexico City plumes during the MIRAGE-Mex field campaign using the WRF-Chem model

Directory of Open Access Journals (Sweden)

X. Tie

2009-07-01

Full Text Available The quantification of tropospheric O₃ production in the downwind of the Mexico City plume is a major objective of the MIRAGE-Mex field campaign. We used a regional chemistry-transport model (WRF-Chem to predict the distribution of O₃ and its precursors in Mexico City and the surrounding region during March 2006, and compared the model with in-situ aircraft measurements of O₃, CO, VOCs, NO_x, and NO_y concentrations. The comparison shows that the model is capable of capturing the timing and location of the measured city plumes, and the calculated variability along the flights is generally consistent with the measured results, showing a rapid increase in O₃ and its precursors when city plumes are detected. However, there are some notable differences between the calculated and measured values, suggesting that, during transport from the surface of the city to the outflow plume, ozone mixing ratios are underestimated by about 0–25% during different flights. The calculated O₃-NO_x, O₃-CO, and O₃-NO_z correlations generally agree with the measured values, and the analyses of these correlations suggest that photochemical O₃ production continues in the plume downwind of the city (aged plume, adding to the O₃ already produced in the city and exported with the plume. The model is also used to quantify the contributions to OH reactivity from various compounds in the aged plume. This analysis suggests that oxygenated organics (OVOCs have the highest OH reactivity and play important roles for the O₃ production in the aging plume. Furthermore, O₃ production per NO_x molecule consumed (O₃ production efficiency is more efficient in the aged plume than in the young plume near the city. The major contributor to the high O₃ production efficiency in the aged plume is the

Coupling spectral-bin cloud microphysics with the MOSAIC aerosol model in WRF-Chem: Methodology and results for marine stratocumulus clouds

Science.gov (United States)

Gao, Wenhua; Fan, Jiwen; Easter, R. C.; Yang, Qing; Zhao, Chun; Ghan, Steven J.

2016-09-01

Aerosol-cloud interaction processes can be represented more physically with bin cloud microphysics relative to bulk microphysical parameterizations. However, due to computational power limitations in the past, bin cloud microphysics was often run with very simple aerosol treatments. The purpose of this study is to represent better aerosol-cloud interaction processes in the Chemistry version of Weather Research and Forecast model (WRF-Chem) at convection-permitting scales by coupling spectral-bin cloud microphysics (SBM) with the MOSAIC sectional aerosol model. A flexible interface is built that exchanges cloud and aerosol information between them. The interface contains a new bin aerosol activation approach, which replaces the treatments in the original SBM. It also includes the modified aerosol resuspension and in-cloud wet removal processes with the droplet loss tendencies and precipitation fluxes from SBM. The newly coupled system is evaluated for two marine stratocumulus cases over the Southeast Pacific Ocean with either a simplified aerosol setup or full-chemistry. We compare the aerosol activation process in the newly coupled SBM-MOSAIC against the SBM simulation without chemistry using a simplified aerosol setup, and the results show consistent activation rates. A longer time simulation reinforces that aerosol resuspension through cloud drop evaporation plays an important role in replenishing aerosols and impacts cloud and precipitation in marine stratocumulus clouds. Evaluation of the coupled SBM-MOSAIC with full-chemistry using aircraft measurements suggests that the new model works realistically for the marine stratocumulus clouds, and improves the simulation of cloud microphysical properties compared to a simulation using MOSAIC coupled with the Morrison two-moment microphysics.

URBAN EFFICIENT ENERGY EVALUATION IN HIGH RESOLUTION URBAN AREAS BY USING ADAPTED WRF-UCM AND MICROSYS CFD MODELS

Science.gov (United States)

San Jose, R.; Perez, J. L.; Gonzalez, R. M.

2009-12-01

Urban metabolism modeling has advanced substantially during the last years due to the increased detail in mesoscale urban parameterization in meteorological mesoscale models and CFD numerical tools. Recently the implementation of the “urban canopy model” (UCM) into the WRF mesoscale meteorological model has produced a substantial advance on the understanding of the urban atmospheric heat flux exchanges in the urban canopy. The need to optimize the use of heat energy in urban environment has produced a substantial increase in the detailed investigation of the urban heat flux exchanges. In this contribution we will show the performance of using a tool called MICROSYS (MICRO scale CFD modelling SYStem) which is an adaptation of the classical urban canopy model but on a high resolution environment by using a classical CFD approach. The energy balance in the urban system can be determined in a micrometeorologicl sense by considering the energy flows in and out of a control volume. For such a control volume reaching from ground to a certain height above buildings, the energy balance equation includes the net radiation, the anthropogenic heat flux, the turbulent sensible heat flux, the turbulent latent heat flux, the net storage change within the control volume, the net advected flux and other sources and sinks. We have applied the MICROSYS model to an area of 5 km x 5 km with 200 m spatial resolution by using the WRF-UCM (adapted and the MICROSYS CFD model. The anthropogenic heat flux has been estimated by using the Flanner M.G. (2009) database and detailed GIS information (50 m resolution) of Madrid city. The Storage energy has been estimated by calculating the energy balance according to the UCM procedure and implementing it into the MICROSYS tool. Results show that MICROSYS can be used as an energy efficient tool to estimate the energy balance of different urban areas and buildings.

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...

Optimizing meridional advection of the Advanced Research WRF (ARW) dynamics for Intel Xeon Phi coprocessor

Science.gov (United States)

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

2015-05-01

The most widely used community weather forecast and research model in the world is the Weather Research and Forecast (WRF) model. Two distinct varieties of WRF exist. The one we are interested is the Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we optimize a meridional (north-south direction) advection subroutine for Intel Xeon Phi coprocessor. Advection is of the most time consuming routines in the ARW dynamics core. It advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 1.2x.

Contributions of mobile, stationary and biogenic sources to air pollution in the Amazon rainforest: a numerical study with the WRF-Chem model

Science.gov (United States)

Abou Rafee, Sameh A.; Martins, Leila D.; Kawashima, Ana B.; Almeida, Daniela S.; Morais, Marcos V. B.; Souza, Rita V. A.; Oliveira, Maria B. L.; Souza, Rodrigo A. F.; Medeiros, Adan S. S.; Urbina, Viviana; Freitas, Edmilson D.; Martin, Scot T.; Martins, Jorge A.

2017-06-01

This paper evaluates the contributions of the emissions from mobile, stationary and biogenic sources on air pollution in the Amazon rainforest by using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. The analyzed air pollutants were CO, NOx, SO2, O3, PM2. 5, PM10 and volatile organic compounds (VOCs). Five scenarios were defined in order to evaluate the emissions by biogenic, mobile and stationary sources, as well as a future scenario to assess the potential air quality impact of doubled anthropogenic emissions. The stationary sources explain the highest concentrations for all air pollutants evaluated, except for CO, for which the mobile sources are predominant. The anthropogenic sources considered resulted an increasing in the spatial peak-temporal average concentrations of pollutants in 3 to 2780 times in relation to those with only biogenic sources. The future scenario showed an increase in the range of 3 to 62 % in average concentrations and 45 to 109 % in peak concentrations depending on the pollutant. In addition, the spatial distributions of the scenarios has shown that the air pollution plume from the city of Manaus is predominantly transported west and southwest, and it can reach hundreds of kilometers in length.

Contributions of mobile, stationary and biogenic sources to air pollution in the Amazon rainforest: a numerical study with the WRF-Chem model

Directory of Open Access Journals (Sweden)

S. A. Abou Rafee

2017-06-01

Full Text Available This paper evaluates the contributions of the emissions from mobile, stationary and biogenic sources on air pollution in the Amazon rainforest by using the Weather Research and Forecasting with Chemistry (WRF-Chem model. The analyzed air pollutants were CO, NOx, SO2, O3, PM2. 5, PM10 and volatile organic compounds (VOCs. Five scenarios were defined in order to evaluate the emissions by biogenic, mobile and stationary sources, as well as a future scenario to assess the potential air quality impact of doubled anthropogenic emissions. The stationary sources explain the highest concentrations for all air pollutants evaluated, except for CO, for which the mobile sources are predominant. The anthropogenic sources considered resulted an increasing in the spatial peak-temporal average concentrations of pollutants in 3 to 2780 times in relation to those with only biogenic sources. The future scenario showed an increase in the range of 3 to 62 % in average concentrations and 45 to 109 % in peak concentrations depending on the pollutant. In addition, the spatial distributions of the scenarios has shown that the air pollution plume from the city of Manaus is predominantly transported west and southwest, and it can reach hundreds of kilometers in length.

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

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...

Meteorological Modeling Using the WRF-ARW Model for Grand Bay Intensive Studies of Atmospheric Mercury

Directory of Open Access Journals (Sweden)

Fong Ngan

2015-02-01

Full Text Available Measurements at the Grand Bay National Estuarine Research Reserve support a range of research activities aimed at improving the understanding of the atmospheric fate and transport of mercury. Routine monitoring was enhanced by two intensive measurement periods conducted at the site in summer 2010 and spring 2011. Detailed meteorological data are required to properly represent the weather conditions, to determine the transport and dispersion of plumes and to understand the wet and dry deposition of mercury. To describe the mesoscale features that might influence future plume calculations for mercury episodes during the Grand Bay Intensive campaigns, fine-resolution meteorological simulations using the Weather Research and Forecasting (WRF model were conducted with various initialization and nudging configurations. The WRF simulations with nudging generated reasonable results in comparison with conventional observations in the region and measurements obtained at the Grand Bay site, including surface and sounding data. The grid nudging, together with observational nudging, had a positive effect on wind prediction. However, the nudging of mass fields (temperature and moisture led to overestimates of precipitation, which may introduce significant inaccuracies if the data were to be used for subsequent atmospheric mercury modeling. The regional flow prediction was also influenced by the reanalysis data used to initialize the WRF simulations. Even with observational nudging, the summer case simulation results in the fine resolution domain inherited features of the reanalysis data, resulting in different regional wind patterns. By contrast, the spring intensive period showed less influence from the reanalysis data.

DART: New Research Using Ensemble Data Assimilation in Geophysical Models

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Hoar, T. J.; Raeder, K.

2015-12-01

The Data Assimilation Research Testbed (DART) is a community facilityfor ensemble data assimilation developed and supported by the NationalCenter for Atmospheric Research. DART provides a comprehensive suite of software, documentation, and tutorials that can be used for ensemble data assimilation research, operations, and education. Scientists and software engineers at NCAR are available to support DART users who want to use existing DART products or develop their own applications. Current DART users range from university professors teaching data assimilation, to individual graduate students working with simple models, through national laboratories doing operational prediction with large state-of-the-art models. DART runs efficiently on many computational platforms ranging from laptops through thousands of cores on the newest supercomputers.This poster focuses on several recent research activities using DART with geophysical models.Using CAM/DART to understand whether OCO-2 Total Precipitable Water observations can be useful in numerical weather prediction.Impacts of the synergistic use of Infra-red CO retrievals (MOPITT, IASI) in CAM-CHEM/DART assimilations.Assimilation and Analysis of Observations of Amazonian Biomass Burning Emissions by MOPITT (aerosol optical depth), MODIS (carbon monoxide) and MISR (plume height).Long term evaluation of the chemical response of MOPITT-CO assimilation in CAM-CHEM/DART OSSEs for satellite planning and emission inversion capabilities.Improved forward observation operators for land models that have multiple land use/land cover segments in a single grid cell,Simulating mesoscale convective systems (MCSs) using a variable resolution, unstructured grid in the Model for Prediction Across Scales (MPAS) and DART.The mesoscale WRF+DART system generated an ensemble of year-long, real-time initializations of a convection allowing model over the United States.Constraining WACCM with observations in the tropical band (30S-30N) using DART

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...

WRF Model Output

Data.gov (United States)

U.S. Environmental Protection Agency — This dataset contains WRF model output. There are three months of data: July 2012, July 2013, and January 2013. For each month, several simulations were made: A...

Sensitivity of an Integrated Mesoscale Atmosphere and Agriculture Land Modeling System (WRF/CMAQ-EPIC) to MODIS Vegetation and Lightning Assimilation

Science.gov (United States)

The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteo...

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.

Sensitivity of an Integrated Mesoscale Atmosphere and Agriculture Land Modeling System (WRF/CMAQ-EPIC) to MODIS Vegetation and Lightning Assimilation

Science.gov (United States)

Ran, L.; Cooter, E. J.; Gilliam, R. C.; Foroutan, H.; Kang, D.; Appel, W.; Wong, D. C.; Pleim, J. E.; Benson, V.; Pouliot, G.

2017-12-01

The combined meteorology and air quality modeling system composed of the Weather Research and Forecast (WRF) model and Community Multiscale Air Quality (CMAQ) model is an important decision support tool that is used in research and regulatory decisions related to emissions, meteorology, climate, and chemical transport. The Environmental Policy Integrated Climate (EPIC) is a cropping model which has long been used in a range of applications related to soil erosion, crop productivity, climate change, and water quality around the world. We have integrated WRF/CMAQ with EPIC using the Fertilizer Emission Scenario Tool for CMAQ (FEST-C) to estimate daily soil N information with fertilization for CMAQ bi-directional ammonia flux modeling. Driven by the weather and N deposition from WRF/CMAQ, FEST-C EPIC simulations are conducted on 22 different agricultural production systems ranging from managed grass lands (e.g. hay and alfalfa) to crop lands (e.g. corn grain and soybean) with rainfed and irrigated information across any defined conterminous United States (U.S.) CMAQ domain and grid resolution. In recent years, this integrated system has been enhanced and applied in many different air quality and ecosystem assessment projects related to land-water-atmosphere interactions. These enhancements have advanced this system to become a valuable tool for integrated assessments of air, land and water quality in light of social drivers and human and ecological outcomes. This presentation will focus on evaluating the sensitivity of precipitation and N deposition in the integrated system to MODIS vegetation input and lightning assimilation and their impacts on agricultural production and fertilization. We will describe the integrated modeling system and evaluate simulated precipitation and N deposition along with other weather information (e.g. temperature, humidity) for 2011 over the conterminous U.S. at 12 km grids from a coupled WRF/CMAQ with MODIS and lightning assimilation

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

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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''

Impact of MODIS High-Resolution Sea-Surface Temperatures on WRF Forecasts at NWS Miami, FL

Science.gov (United States)

Case, Jonathan L.; LaCasse, Katherine M.; Dembek, Scott R.; Santos, Pablo; Lapenta, William M.

2007-01-01

Over the past few years,studies at the Short-term Prediction Research and Transition (SPoRT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) composite sea-surface temperature (SST) products in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. The recent paper by LaCasse et al. (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPoRT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The scientific hypothesis being tested is: More accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running the WRF system in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software; The EMS is a standalone modeling system capable of downloading the necessary daily datasets, and initializing, running and displaying WRF forecasts in the NWS Advanced Weather Interactive Processing System (AWIPS) with little intervention required by forecasters. Twenty-seven hour forecasts are run daily with start times of 0300,0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and the far

Air quality modelling in the summer over the eastern Mediterranean using WRF-Chem: chemistry and aerosol mechanism intercomparison

Science.gov (United States)

Georgiou, George K.; Christoudias, Theodoros; Proestos, Yiannis; Kushta, Jonilda; Hadjinicolaou, Panos; Lelieveld, Jos

2018-02-01

We employ the WRF-Chem model to study summertime air pollution, the intense photochemical activity and their impact on air quality over the eastern Mediterranean. We utilize three nested domains with horizontal resolutions of 80, 16 and 4 km, with the finest grid focusing on the island of Cyprus, where the CYPHEX campaign took place in July 2014. Anthropogenic emissions are based on the EDGAR HTAP global emission inventory, while dust and biogenic emissions are calculated online. Three simulations utilizing the CBMZ-MOSAIC, MOZART-MOSAIC, and RADM2-MADE/SORGAM gas-phase and aerosol mechanisms are performed. The results are compared with measurements from a dense observational network of 14 ground stations in Cyprus. The model simulates T2 m, Psurf, and WD10 m accurately, with minor differences in WS10 m between model and observations at coastal and mountainous stations attributed to limitations in the representation of the complex topography in the model. It is shown that the south-eastern part of Cyprus is mostly affected by emissions from within the island, under the dominant (60 %) westerly flow during summertime. Clean maritime air from the Mediterranean can reduce concentrations of local air pollutants over the region during westerlies. Ozone concentrations are overestimated by all three mechanisms (9 % ≤ NMB ≤ 23 %) with the smaller mean bias (4.25 ppbV) obtained by the RADM2-MADE/SORGAM mechanism. Differences in ozone concentrations can be attributed to the VOC treatment by the three mechanisms. The diurnal variability of pollution and ozone precursors is not captured (hourly correlation coefficients for O3 ≤ 0.29). This might be attributed to the underestimation of NOx concentrations by local emissions by up to 50 %. For the fine particulate matter (PM2.5), the lowest mean bias (9 µg m-3) is obtained with the RADM2-MADE/SORGAM mechanism, with overestimates in sulfate and ammonium aerosols. Overestimation of sulfate aerosols by this mechanism may be

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.

Dynamical Downscaling of NASA/GISS ModelE: Continuous, Multi-Year WRF Simulations

Science.gov (United States)

Otte, T.; Bowden, J. H.; Nolte, C. G.; Otte, M. J.; Herwehe, J. A.; Faluvegi, G.; Shindell, D. T.

2010-12-01

The WRF Model is being used at the U.S. EPA for dynamical downscaling of the NASA/GISS ModelE fields to assess regional impacts of climate change in the United States. The WRF model has been successfully linked to the ModelE fields in their raw hybrid vertical coordinate, and continuous, multi-year WRF downscaling simulations have been performed. WRF will be used to downscale decadal time slices of ModelE for recent past, current, and future climate as the simulations being conducted for the IPCC Fifth Assessment Report become available. This presentation will focus on the sensitivity to interior nudging within the RCM. The use of interior nudging for downscaled regional climate simulations has been somewhat controversial over the past several years but has been recently attracting attention. Several recent studies that have used reanalysis (i.e., verifiable) fields as a proxy for GCM input have shown that interior nudging can be beneficial toward achieving the desired downscaled fields. In this study, the value of nudging will be shown using fields from ModelE that are downscaled using WRF. Several different methods of nudging are explored, and it will be shown that the method of nudging and the choices made with respect to how nudging is used in WRF are critical to balance the constraint of ModelE against the freedom of WRF to develop its own fields.

WRF4G project: Adaptation of WRF Model to Distributed Computing Infrastructures

Science.gov (United States)

Cofino, Antonio S.; Fernández Quiruelas, Valvanuz; García Díez, Markel; Blanco Real, Jose C.; Fernández, Jesús

2013-04-01

Nowadays Grid Computing is powerful computational tool which is ready to be used for scientific community in different areas (such as biomedicine, astrophysics, climate, etc.). However, the use of this distributed computing infrastructures (DCI) is not yet common practice in climate research, and only a few teams and applications in this area take advantage of this infrastructure. Thus, the first objective of this project is to popularize the use of this technology in the atmospheric sciences area. In order to achieve this objective, one of the most used applications has been taken (WRF; a limited- area model, successor of the MM5 model), that has a user community formed by more than 8000 researchers worldwide. This community develop its research activity on different areas and could benefit from the advantages of Grid resources (case study simulations, regional hind-cast/forecast, sensitivity studies, etc.). The WRF model is been used as input by many energy and natural hazards community, therefore those community will also benefit. However, Grid infrastructures have some drawbacks for the execution of applications that make an intensive use of CPU and memory for a long period of time. This makes necessary to develop a specific framework (middleware). This middleware encapsulates the application and provides appropriate services for the monitoring and management of the jobs and the data. Thus, the second objective of the project consists on the development of a generic adaptation of WRF for Grid (WRF4G), to be distributed as open-source and to be integrated in the official WRF development cycle. The use of this WRF adaptation should be transparent and useful to face any of the previously described studies, and avoid any of the problems of the Grid infrastructure. Moreover it should simplify the access to the Grid infrastructures for the research teams, and also to free them from the technical and computational aspects of the use of the Grid. Finally, in order to

Hydrological Modeling in Alaska with WRF-Hydro

Science.gov (United States)

Elmer, N. J.; Zavodsky, B.; Molthan, A.

2017-12-01

The operational National Water Model (NWM), implemented in August 2016, is an instantiation of the Weather Research and Forecasting hydrological extension package (WRF-Hydro). Currently, the NWM only covers the contiguous United States, but will be expanded to include an Alaska domain in the future. It is well known that Alaska presents several hydrological modeling challenges, including unique arctic/sub-arctic hydrological processes not observed elsewhere in the United States and a severe lack of in-situ observations for model initialization. This project sets up an experimental version of WRF-Hydro in Alaska mimicking the NWM to gauge the ability of WRF-Hydro to represent hydrological processes in Alaska and identify model calibration challenges. Recent and upcoming launches of hydrology-focused NASA satellite missions such as the Soil Moisture Active Passive (SMAP) and Surface Water Ocean Topography (SWOT) expand the spatial and temporal coverage of observations in Alaska, so this study also lays the groundwork for assimilating these NASA datasets into WRF-Hydro in the future.

Using WRF-Chem to investigate the impact of night time nitrate radical chemistry and N2O5 heterogeneous chemistry on the chemical composition of the UK troposphere.

Science.gov (United States)

Archer-Nicholls, S.; Lowe, D.; Utembe, S.; McFiggans, G.

2012-04-01

It is believed that NO3 is the primary oxidant at night time, significantly impacting ozone formation, rain acidification and the formation and transformation of aerosols, particularly through the formation of the ammonium nitrate particulate (Allan et. al., 2000). However, many of the basic chemical processes controlling the formation and removal of NO3, in particular, the N2O5 heterogeneous reactions, are often not represented in models, although general parameterisations have been developed (c.f. Bertram & Thornton, 2009). The ROle of Night time chemistry in controlling the Oxidising Capacity of the atmOsphere (RONOCO) campaign is a project being funded by NERC and being carried out by a collaboration of UK Universities. It aims to better understand the role of the NO3 radical on the chemistry of the night time atmosphere, its oxidation capacity and thus its overall effects on the composition of the troposphere. The Weather Research and Forecasting model with Chemistry (WRF-Chem) is a state of the art regional climate model with fully coupled online air quality and meteorological components allowing for better resolution of aerosol and gas-phase chemistry (Grell et. al., 2005). It has been extended to include the Common Representative Intermediates scheme (CRIv2-R5) (Watson et. al., 2008), a reduced chemical scheme designed to simulate the atmospheric degradation of 220 species of hydrocarbons and VOCs. The MOSAIC aerosol scheme (Zaveri et. al., 2008), has been extended to include a reduced complexity condensed organic phase consisting of 13 semi-volatile and 2 involatile species (Topping et. al., 2012), as well as the N2O5 heterogeneous reaction scheme of Bertram & Thornton (2009). We aim to use WRF-Chem to compare the oxidation capacity of nighttime NO3 chemistry with that of daytime OH chemistry. The model was run using two nested grids: a 15km resolution domain over western Europe, containing a 5km resolution domain over the UK. The RONOCO campaign consisted

Implementation of a WRF-CMAQ Air Quality Modeling System in Bogotá, Colombia

Science.gov (United States)

Nedbor-Gross, R.; Henderson, B. H.; Pachon, J. E.; Davis, J. R.; Baublitz, C. B.; Rincón, A.

2014-12-01

Due to a continuous economic growth Bogotá, Colombia has experienced air pollution issues in recent years. The local environmental authority has implemented several strategies to curb air pollution that have resulted in the decrease of PM10 concentrations since 2010. However, more activities are necessary in order to meet international air quality standards in the city. The University of Florida Air Quality and Climate group is collaborating with the Universidad de La Salle to prioritize regulatory strategies for Bogotá using air pollution simulations. To simulate pollution, we developed a modeling platform that combines the Weather Research and Forecasting Model (WRF), local emissions, and the Community Multi-scale Air Quality model (CMAQ). This platform is the first of its kind to be implemented in the megacity of Bogota, Colombia. The presentation will discuss development and evaluation of the air quality modeling system, highlight initial results characterizing photochemical conditions in Bogotá, and characterize air pollution under proposed regulatory strategies. The WRF model has been configured and applied to Bogotá, which resides in a tropical climate with complex mountainous topography. Developing the configuration included incorporation of local topography and land-use data, a physics sensitivity analysis, review, and systematic evaluation. The threshold, however, was set based on synthesis of model performance under less mountainous conditions. We will evaluate the impact that differences in autocorrelation contribute to the non-ideal performance. Air pollution predictions are currently under way. CMAQ has been configured with WRF meteorology, global boundary conditions from GEOS-Chem, and a locally produced emission inventory. Preliminary results from simulations show promising performance of CMAQ in Bogota. Anticipated results include a systematic performance evaluation of ozone and PM10, characterization of photochemical sensitivity, and air

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...

Evaluation of Optimized WRF Precipitation Forecast over a Complex Topography Region during Flood Season

Directory of Open Access Journals (Sweden)

Yuan Li

2016-11-01

Full Text Available In recent years, the Weather Research and Forecast (WRF model has been utilized to generate quantitative precipitation forecasts with higher spatial and temporal resolutions. However, factors including horizontal resolution, domain size, and the physical parameterization scheme have a strong impact on the dynamic downscaling ability of the WRF model. In this study, the influence of these factors has been analyzed in precipitation forecasting for the Xijiang Basin, southern China—a region with complex topography. The results indicate that higher horizontal resolutions always result in higher Critical Success Indexes (CSI, but higher biases as well. Meanwhile, the precipitation forecast skills are also influenced by the combination of microphysics parameterization scheme and cumulus convective parameterization scheme. On the basis of these results, an optimized configuration of the WRF model is built in which the horizontal resolution is 10 km, the microphysics parameterization is the Lin scheme, and the cumulus convective parameterization is the Betts–Miller–Janjic scheme. This configuration is then evaluated by simulating the daily weather during the 2013–2014 flood season. The high Critical Success Index scores and low biases at various thresholds and lead times confirm the high accuracy of the optimized WRF model configuration for Xijiang Basin. However, the performance of the WRF model varies from different sub-basins due to the complexity of the mesoscale convective system (MCS over this region.

Coupling aerosol-cloud-radiative processes in the WRF-Chem model: Investigating the radiative impact of elevated point sources

Directory of Open Access Journals (Sweden)

E. G. Chapman

2009-02-01

Full Text Available The local and regional influence of elevated point sources on summertime aerosol forcing and cloud-aerosol interactions in northeastern North America was investigated using the WRF-Chem community model. The direct effects of aerosols on incoming solar radiation were simulated using existing modules to relate aerosol sizes and chemical composition to aerosol optical properties. Indirect effects were simulated by adding a prognostic treatment of cloud droplet number and adding modules that activate aerosol particles to form cloud droplets, simulate aqueous-phase chemistry, and tie a two-moment treatment of cloud water (cloud water mass and cloud droplet number to precipitation and an existing radiation scheme. Fully interactive feedbacks thus were created within the modified model, with aerosols affecting cloud droplet number and cloud radiative properties, and clouds altering aerosol size and composition via aqueous processes, wet scavenging, and gas-phase-related photolytic processes. Comparisons of a baseline simulation with observations show that the model captured the general temporal cycle of aerosol optical depths (AODs and produced clouds of comparable thickness to observations at approximately the proper times and places. The model overpredicted SO₂ mixing ratios and PM_2.5 mass, but reproduced the range of observed SO₂ to sulfate aerosol ratios, suggesting that atmospheric oxidation processes leading to aerosol sulfate formation are captured in the model. The baseline simulation was compared to a sensitivity simulation in which all emissions at model levels above the surface layer were set to zero, thus removing stack emissions. Instantaneous, site-specific differences for aerosol and cloud related properties between the two simulations could be quite large, as removing above-surface emission sources influenced when and where clouds formed within the modeling domain. When summed spatially over the finest

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

Mitigating Satellite-Based Fire Sampling Limitations in Deriving Biomass Burning Emission Rates: Application to WRF-Chem Model Over the Northern sub-Saharan African Region

Science.gov (United States)

Wang, Jun; Yue, Yun; Wang, Yi; Ichoku, Charles; Ellison, Luke; Zeng, Jing

2018-01-01

Largely used in several independent estimates of fire emissions, fire products based on MODIS sensors aboard the Terra and Aqua polar-orbiting satellites have a number of inherent limitations, including (a) inability to detect fires below clouds, (b) significant decrease of detection sensitivity at the edge of scan where pixel sizes are much larger than at nadir, and (c) gaps between adjacent swaths in tropical regions. To remedy these limitations, an empirical method is developed here and applied to correct fire emission estimates based on MODIS pixel level fire radiative power measurements and emission coefficients from the Fire Energetics and Emissions Research (FEER) biomass burning emission inventory. The analysis was performed for January 2010 over the northern sub-Saharan African region. Simulations from WRF-Chem model using original and adjusted emissions are compared with the aerosol optical depth (AOD) products from MODIS and AERONET as well as aerosol vertical profile from CALIOP data. The comparison confirmed an 30-50% improvement in the model simulation performance (in terms of correlation, bias, and spatial pattern of AOD with respect to observations) by the adjusted emissions that not only increases the original emission amount by a factor of two but also results in the spatially continuous estimates of instantaneous fire emissions at daily time scales. Such improvement cannot be achieved by simply scaling the original emission across the study domain. Even with this improvement, a factor of two underestimations still exists in the modeled AOD, which is within the current global fire emissions uncertainty envelope.

WRF-Chem model simulations of a dust outbreak over the central Mediterranean and comparison with multi-sensor desert dust observations

Science.gov (United States)

Rizza, Umberto; Barnaba, Francesca; Marcello Miglietta, Mario; Mangia, Cristina; Di Liberto, Luca; Dionisi, Davide; Costabile, Francesca; Grasso, Fabio; Gobbi, Gian Paolo

2017-01-01

In this study, the Weather Research and Forecasting model with online coupled chemistry (WRF-Chem) is applied to simulate an intense Saharan dust outbreak event that took place over the Mediterranean in May 2014. Comparison of a simulation using a physics-based desert dust emission scheme with a numerical experiment using a simplified (minimal) emission scheme is included to highlight the advantages of the former. The model was found to reproduce well the synoptic meteorological conditions driving the dust outbreak: an omega-like pressure configuration associated with a cyclogenesis in the Atlantic coasts of Spain. The model performances in reproducing the atmospheric desert dust load were evaluated using a multi-platform observational dataset of aerosol and desert dust properties, including optical properties from satellite and ground-based sun photometers and lidars, plus in situ particulate matter mass concentration (PM) data. This comparison allowed us to investigate the model ability in reproducing both the horizontal and the vertical displacement of the dust plume, as well as its evolution in time. The comparison with satellite (MODIS-Terra) and sun photometers (AERONET) showed that the model is able to reproduce well the horizontal field of the aerosol optical depth (AOD) and its evolution in time (temporal correlation coefficient with AERONET of 0.85). On the vertical scale, the comparison with lidar data at a single site (Rome, Italy) confirms that the desert dust advection occurs in several, superimposed "pulses" as simulated by the model. Cross-analysis of the modeled AOD and desert dust emission fluxes further allowed for the source regions of the observed plumes to be inferred. The vertical displacement of the modeled dust plume was in rather good agreement with the lidar soundings, with correlation coefficients among aerosol extinction profiles up to 1 and mean discrepancy of about 50 %. The model-measurement comparison for PM10 and PM2.5 showed a

Sources and characteristics of summertime organic aerosol in the Colorado Front Range: perspective from measurements and WRF-Chem modeling

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R. Bahreini

2018-06-01

Full Text Available The evolution of organic aerosols (OAs and their precursors in the boundary layer (BL of the Colorado Front Range during the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ, July–August 2014 was analyzed by in situ measurements and chemical transport modeling. Measurements indicated significant production of secondary OA (SOA, with enhancement ratio of OA with respect to carbon monoxide (CO reaching 0.085±0.003 µg m−3 ppbv−1. At background mixing ratios of CO, up to  ∼  1.8 µg m−3 background OA was observed, suggesting significant non-combustion contribution to OA in the Front Range. The mean concentration of OA in plumes with a high influence of oil and natural gas (O&G emissions was  ∼  40 % higher than in urban-influenced plumes. Positive matrix factorization (PMF confirmed a dominant contribution of secondary, oxygenated OA (OOA in the boundary layer instead of fresh, hydrocarbon-like OA (HOA. Combinations of primary OA (POA volatility assumptions, aging of semi-volatile species, and different emission estimates from the O&G sector were used in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem simulation scenarios. The assumption of semi-volatile POA resulted in greater than a factor of 10 lower POA concentrations compared to PMF-resolved HOA. Including top-down modified O&G emissions resulted in substantially better agreements in modeled ethane, toluene, hydroxyl radical, and ozone compared to measurements in the high-O&G-influenced plumes. By including emissions from the O&G sector using the top-down approach, it was estimated that the O&G sector contributed to  <  5 % of total OA, but up to 38 % of anthropogenic SOA (aSOA in the region. The best agreement between the measured and simulated median OA was achieved by limiting the extent of biogenic hydrocarbon aging and consequently biogenic SOA (bSOA production. Despite a lower production of bSOA in

Ultrafine particles from power plants: Evaluation of WRF-Chem simulations with airborne measurements

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Forkel, Renate; Junkermann, Wolfgang

2017-04-01

Ultrafine particles (UFP, particles with a diameter risk to human health and have a potential effect on climate as their presence affects the number concentration of cloud condensation nuclei. Despite of the possibly hazardous effects no regulations exist for this size class of ambient air pollution particles. While ground based continuous measurements of UFP are performed in Germany at several sites (e.g. the German Ultrafine Aerosol Network GUAN, Birmili et al. 2016, doi:10.5194/essd-8-355-2016) information about the vertical distribution of UFP within the atmospheric boundary layer is only scarce. This gap has been closed during the last years by regional-scale airborne surveys for UFP concentrations and size distributions over Germany (Junkermann et al., 2016, doi: 10.3402/tellusb.v68.29250) and Australia (Junkermann and Hacker, 2015, doi: 10.3402/tellusb.v67.25308). Power stations and refineries have been identified as a major source of UFP in Germany with observed particle concentrations > 50000 particles cm-3 downwind of these elevated point sources. Nested WRF-Chem simulations with 2 km grid width for the innermost domain are performed with UFP emission source strengths derived from the measurements in order to study the advection and vertical exchange of UFP from power plants near the Czech and Polish border and their impact on planetary boundary layer particle patterns. The simulations are evaluated against the airborne observations and the downward mixing of the UFP from the elevated sources is studied.

Sensitivity of the Community Multiscale Air Quality (CMAQ model v4.7 results for the eastern United States to MM5 and WRF meteorological drivers

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K. W. Appel

2010-02-01

Full Text Available This paper presents a comparison of the operational performances of two Community Multiscale Air Quality (CMAQ model v4.7 simulations that utilize input data from the 5th-generation Mesoscale Model (MM5 and the Weather Research and Forecasting (WRF meteorological models. Two sets of CMAQ model simulations were performed for January and August 2006. One set utilized MM5 meteorology (MM5-CMAQ and the other utilized WRF meteorology (WRF-CMAQ, while all other model inputs and options were kept the same. For January, predicted ozone (O₃ mixing ratios were higher in the Southeast and lower Mid-west regions in the WRF-CMAQ simulation, resulting in slightly higher bias and error as compared to the MM5-CMAQ simulations. The higher predicted O₃ mixing ratios are attributed to less dry deposition of O₃ in the WRF-CMAQ simulation due to differences in the calculation of the vegetation fraction between the MM5 and WRF models. The WRF-CMAQ results showed better performance for particulate sulfate (SO₄²⁻, similar performance for nitrate (NO₃⁻, and slightly worse performance for nitric acid (HNO₃, total carbon (TC and total fine particulate (PM_2.5 mass than the corresponding MM5-CMAQ results. For August, predictions of O₃ were notably higher in the WRF-CMAQ simulation, particularly in the southern United States, resulting in increased model bias. Concentrations of predicted particulate SO₄²⁻ were lower in the region surrounding the Ohio Valley and higher along the Gulf of Mexico in the WRF-CMAQ simulation, contributing to poorer model performance. The primary causes of the differences in the MM5-CMAQ and WRF-CMAQ simulations appear to be due to differences in the calculation of wind speed, planetary boundary layer height, cloud cover and the friction velocity (u_∗ in the MM5 and WRF model simulations, while

Evaluating transport in the WRF model along the California coast

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C. E. Yver

2013-02-01

Full Text Available This paper presents a step in the development of a top-down method to complement the bottom-up inventories of halocarbon emissions in California using high frequency observations, forward simulations and inverse methods. The Scripps Institution of Oceanography high-frequency atmospheric halocarbons measurement sites are located along the California coast and therefore the evaluation of transport in the chosen Weather Research Forecast (WRF model at these sites is crucial for inverse modeling. The performance of the transport model has been investigated by comparing the wind direction and speed and temperature at four locations using aircraft weather reports as well at all METAR weather stations in our domain for hourly variations. Different planetary boundary layer (PBL schemes, horizontal resolutions (achieved through nesting and two meteorological datasets have been tested. Finally, simulated concentration of an inert tracer has been briefly investigated. All the PBL schemes present similar results that generally agree with observations, except in summer when the model sea breeze is too strong. At the coarse 12 km resolution, using ERA-interim (ECMWF Re-Analysis as initial and boundary conditions leads to improvements compared to using the North American Model (NAM dataset. Adding higher resolution nests also improves the match with the observations. However, no further improvement is observed from increasing the nest resolution from 4 km to 0.8 km. Once optimized, the model is able to reproduce tracer measurements during typical winter California large-scale events (Santa Ana. Furthermore, with the WRF/CHEM chemistry module and the European Database for Global Atmospheric Research (EDGAR version 4.1 emissions for HFC-134a, we find that using a simple emission scaling factor is not sufficient to infer emissions, which highlights the need for more complex inversions.

Wind farm efficiency assessed by WRF with a statistical-dynamical approach

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....

Wake modelling combining mesoscale and microscale models

DEFF Research Database (Denmark)

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

2013-01-01

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

Sensitivity of simulated convection-driven stratosphere-troposphere exchange in WRF-Chem to the choice of physical and chemical parameterization

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Phoenix, Daniel B.; Homeyer, Cameron R.; Barth, Mary C.

2017-08-01

Tropopause-penetrating convection is capable of rapidly transporting air from the lower troposphere to the upper troposphere and lower stratosphere (UTLS), where it can have important impacts on chemistry, the radiative budget, and climate. However, obtaining in situ measurements of convection and convective transport is difficult and such observations are historically rare. Modeling studies, on the other hand, offer the advantage of providing output related to the physical, dynamical, and chemical characteristics of storms and their environments at fine spatial and temporal scales. Since these characteristics of simulated convection depend on the chosen model design, we examine the sensitivity of simulated convective transport to the choice of physical (bulk microphysics or BMP and planetary boundary layer or PBL) and chemical parameterizations in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). In particular, we simulate multiple cases where in situ observations are available from the recent (2012) Deep Convective Clouds and Chemistry (DC3) experiment. Model output is evaluated using ground-based radar observations of each storm and in situ trace gas observations from two aircraft operated during the DC3 experiment. Model results show measurable sensitivity of the physical characteristics of a storm and the transport of water vapor and additional trace gases into the UTLS to the choice of BMP. The physical characteristics of the storm and transport of insoluble trace gases are largely insensitive to the choice of PBL scheme and chemical mechanism, though several soluble trace gases (e.g., SO2, CH2O, and HNO3) exhibit some measurable sensitivity.

Development of the WRF-CO2 4D-Var assimilation system v1.0

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Zheng, Tao; French, Nancy H. F.; Baxter, Martin

2018-05-01

Regional atmospheric CO2 inversions commonly use Lagrangian particle trajectory model simulations to calculate the required influence function, which quantifies the sensitivity of a receptor to flux sources. In this paper, an adjoint-based four-dimensional variational (4D-Var) assimilation system, WRF-CO2 4D-Var, is developed to provide an alternative approach. This system is developed based on the Weather Research and Forecasting (WRF) modeling system, including the system coupled to chemistry (WRF-Chem), with tangent linear and adjoint codes (WRFPLUS), and with data assimilation (WRFDA), all in version 3.6. In WRF-CO2 4D-Var, CO2 is modeled as a tracer and its feedback to meteorology is ignored. This configuration allows most WRF physical parameterizations to be used in the assimilation system without incurring a large amount of code development. WRF-CO2 4D-Var solves for the optimized CO2 flux scaling factors in a Bayesian framework. Two variational optimization schemes are implemented for the system: the first uses the limited memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) minimization algorithm (L-BFGS-B) and the second uses the Lanczos conjugate gradient (CG) in an incremental approach. WRFPLUS forward, tangent linear, and adjoint models are modified to include the physical and dynamical processes involved in the atmospheric transport of CO2. The system is tested by simulations over a domain covering the continental United States at 48 km × 48 km grid spacing. The accuracy of the tangent linear and adjoint models is assessed by comparing against finite difference sensitivity. The system's effectiveness for CO2 inverse modeling is tested using pseudo-observation data. The results of the sensitivity and inverse modeling tests demonstrate the potential usefulness of WRF-CO2 4D-Var for regional CO2 inversions.

Development of the WRF-CO2 4D-Var assimilation system v1.0

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T. Zheng

2018-05-01

Full Text Available Regional atmospheric CO2 inversions commonly use Lagrangian particle trajectory model simulations to calculate the required influence function, which quantifies the sensitivity of a receptor to flux sources. In this paper, an adjoint-based four-dimensional variational (4D-Var assimilation system, WRF-CO2 4D-Var, is developed to provide an alternative approach. This system is developed based on the Weather Research and Forecasting (WRF modeling system, including the system coupled to chemistry (WRF-Chem, with tangent linear and adjoint codes (WRFPLUS, and with data assimilation (WRFDA, all in version 3.6. In WRF-CO2 4D-Var, CO2 is modeled as a tracer and its feedback to meteorology is ignored. This configuration allows most WRF physical parameterizations to be used in the assimilation system without incurring a large amount of code development. WRF-CO2 4D-Var solves for the optimized CO2 flux scaling factors in a Bayesian framework. Two variational optimization schemes are implemented for the system: the first uses the limited memory Broyden–Fletcher–Goldfarb–Shanno (BFGS minimization algorithm (L-BFGS-B and the second uses the Lanczos conjugate gradient (CG in an incremental approach. WRFPLUS forward, tangent linear, and adjoint models are modified to include the physical and dynamical processes involved in the atmospheric transport of CO2. The system is tested by simulations over a domain covering the continental United States at 48 km  ×  48 km grid spacing. The accuracy of the tangent linear and adjoint models is assessed by comparing against finite difference sensitivity. The system's effectiveness for CO2 inverse modeling is tested using pseudo-observation data. The results of the sensitivity and inverse modeling tests demonstrate the potential usefulness of WRF-CO2 4D-Var for regional CO2 inversions.

WRF-Chem simulations in the Amazon region during wet and dry season transitions: evaluation of methane models and wetland inundation maps

Science.gov (United States)

Beck, V.; Gerbig, C.; Koch, T.; Bela, M. M.; Longo, K. M.; Freitas, S. R.; Kaplan, J. O.; Prigent, C.; Bergamaschi, P.; Heimann, M.

2013-08-01

The Amazon region, being a large source of methane (CH4), contributes significantly to the global annual CH4 budget. For the first time, a forward and inverse modelling framework on regional scale for the purpose of assessing the CH4 budget of the Amazon region is implemented. Here, we present forward simulations of CH4 as part of the forward and inverse modelling framework based on a modified version of the Weather Research and Forecasting model with chemistry that allows for passive tracer transport of CH4, carbon monoxide, and carbon dioxide (WRF-GHG), in combination with two different process-based bottom-up models of CH4 emissions from anaerobic microbial production in wetlands and additional datasets prescribing CH4 emissions from other sources such as biomass burning, termites, or other anthropogenic emissions. We compare WRF-GHG simulations on 10 km horizontal resolution to flask and continuous CH4 observations obtained during two airborne measurement campaigns within the Balanço Atmosférico Regional de Carbono na Amazônia (BARCA) project in November 2008 and May 2009. In addition, three different wetland inundation maps, prescribing the fraction of inundated area per grid cell, are evaluated. Our results indicate that the wetland inundation maps based on remote-sensing data represent the observations best except for the northern part of the Amazon basin and the Manaus area. WRF-GHG was able to represent the observed CH4 mixing ratios best at days with less convective activity. After adjusting wetland emissions to match the averaged observed mixing ratios of flights with little convective activity, the monthly CH4 budget for the Amazon basin obtained from four different simulations ranges from 1.5 to 4.8 Tg for November 2008 and from 1.3 to 5.5 Tg for May 2009. This corresponds to an average CH4 flux of 9-31 mg m-2 d-1 for November 2008 and 8-36 mg m-2 d-1 for May 2009.

WRF model for precipitation simulation and its application in real-time flood forecasting in the Jinshajiang River Basin, China

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Zhou, Jianzhong; Zhang, Hairong; Zhang, Jianyun; Zeng, Xiaofan; Ye, Lei; Liu, Yi; Tayyab, Muhammad; Chen, Yufan

2017-07-01

An accurate flood forecasting with long lead time can be of great value for flood prevention and utilization. This paper develops a one-way coupled hydro-meteorological modeling system consisting of the mesoscale numerical weather model Weather Research and Forecasting (WRF) model and the Chinese Xinanjiang hydrological model to extend flood forecasting lead time in the Jinshajiang River Basin, which is the largest hydropower base in China. Focusing on four typical precipitation events includes: first, the combinations and mode structures of parameterization schemes of WRF suitable for simulating precipitation in the Jinshajiang River Basin were investigated. Then, the Xinanjiang model was established after calibration and validation to make up the hydro-meteorological system. It was found that the selection of the cloud microphysics scheme and boundary layer scheme has a great impact on precipitation simulation, and only a proper combination of the two schemes could yield accurate simulation effects in the Jinshajiang River Basin and the hydro-meteorological system can provide instructive flood forecasts with long lead time. On the whole, the one-way coupled hydro-meteorological model could be used for precipitation simulation and flood prediction in the Jinshajiang River Basin because of its relatively high precision and long lead time.

A spatio-temporal evaluation of the WRF physical parameterisations for numerical rainfall simulation in semi-humid and semi-arid catchments of Northern China

Science.gov (United States)

Tian, Jiyang; Liu, Jia; Wang, Jianhua; Li, Chuanzhe; Yu, Fuliang; Chu, Zhigang

2017-07-01

Mesoscale Numerical Weather Prediction systems can provide rainfall products at high resolutions in space and time, playing an increasingly more important role in water management and flood forecasting. The Weather Research and Forecasting (WRF) model is one of the most popular mesoscale systems and has been extensively used in research and practice. However, for hydrologists, an unsolved question must be addressed before each model application in a different target area. That is, how are the most appropriate combinations of physical parameterisations from the vast WRF library selected to provide the best downscaled rainfall? In this study, the WRF model was applied with 12 designed parameterisation schemes with different combinations of physical parameterisations, including microphysics, radiation, planetary boundary layer (PBL), land-surface model (LSM) and cumulus parameterisations. The selected study areas are two semi-humid and semi-arid catchments located in the Daqinghe River basin, Northern China. The performance of WRF with different parameterisation schemes is tested for simulating eight typical 24-h storm events with different evenness in space and time. In addition to the cumulative rainfall amount, the spatial and temporal patterns of the simulated rainfall are evaluated based on a two-dimensional composed verification statistic. Among the 12 parameterisation schemes, Scheme 4 outperforms the other schemes with the best average performance in simulating rainfall totals and temporal patterns; in contrast, Scheme 6 is generally a good choice for simulations of spatial rainfall distributions. Regarding the individual parameterisations, Single-Moment 6 (WSM6), Yonsei University (YSU), Kain-Fritsch (KF) and Grell-Devenyi (GD) are better choices for microphysics, planetary boundary layers (PBL) and cumulus parameterisations, respectively, in the study area. These findings provide helpful information for WRF rainfall downscaling in semi-humid and semi

WRF-Chem simulated surface ozone over south Asia during the pre-monsoon: effects of emission inventories and chemical mechanisms

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A. Sharma

2017-12-01

Full Text Available We evaluate numerical simulations of surface ozone mixing ratios over the south Asian region during the pre-monsoon season, employing three different emission inventories in the Weather Research and Forecasting model with Chemistry (WRF-Chem with the second-generation Regional Acid Deposition Model (RADM2 chemical mechanism: the Emissions Database for Global Atmospheric Research – Hemispheric Transport of Air Pollution (EDGAR-HTAP, the Intercontinental Chemical Transport Experiment phase B (INTEX-B and the Southeast Asia Composition, Cloud, Climate Coupling Regional Study (SEAC4RS. Evaluation of diurnal variability in modelled ozone compared to observational data from 15 monitoring stations across south Asia shows the model ability to reproduce the clean, rural and polluted urban conditions over this region. In contrast to the diurnal average, the modelled ozone mixing ratios during noontime, i.e. hours of intense photochemistry (11:30–16:30 IST – Indian Standard Time – UTC +5:30, are found to differ among the three inventories. This suggests that evaluations of the modelled ozone limited to 24 h average are insufficient to assess uncertainties associated with ozone buildup. HTAP generally shows 10–30 ppbv higher noontime ozone mixing ratios than SEAC4RS and INTEX-B, especially over the north-west Indo-Gangetic Plain (IGP, central India and southern India. The HTAP simulation repeated with the alternative Model for Ozone and Related Chemical Tracers (MOZART chemical mechanism showed even more strongly enhanced surface ozone mixing ratios due to vertical mixing of enhanced ozone that has been produced aloft. Our study indicates the need to also evaluate the O3 precursors across a network of stations and the development of high-resolution regional inventories for the anthropogenic emissions over south Asia accounting for year-to-year changes to further reduce uncertainties in modelled ozone over this region.

WRF-Chem simulated surface ozone over south Asia during the pre-monsoon: effects of emission inventories and chemical mechanisms

Science.gov (United States)

Sharma, Amit; Ojha, Narendra; Pozzer, Andrea; Mar, Kathleen A.; Beig, Gufran; Lelieveld, Jos; Gunthe, Sachin S.

2017-12-01

We evaluate numerical simulations of surface ozone mixing ratios over the south Asian region during the pre-monsoon season, employing three different emission inventories in the Weather Research and Forecasting model with Chemistry (WRF-Chem) with the second-generation Regional Acid Deposition Model (RADM2) chemical mechanism: the Emissions Database for Global Atmospheric Research - Hemispheric Transport of Air Pollution (EDGAR-HTAP), the Intercontinental Chemical Transport Experiment phase B (INTEX-B) and the Southeast Asia Composition, Cloud, Climate Coupling Regional Study (SEAC4RS). Evaluation of diurnal variability in modelled ozone compared to observational data from 15 monitoring stations across south Asia shows the model ability to reproduce the clean, rural and polluted urban conditions over this region. In contrast to the diurnal average, the modelled ozone mixing ratios during noontime, i.e. hours of intense photochemistry (11:30-16:30 IST - Indian Standard Time - UTC +5:30), are found to differ among the three inventories. This suggests that evaluations of the modelled ozone limited to 24 h average are insufficient to assess uncertainties associated with ozone buildup. HTAP generally shows 10-30 ppbv higher noontime ozone mixing ratios than SEAC4RS and INTEX-B, especially over the north-west Indo-Gangetic Plain (IGP), central India and southern India. The HTAP simulation repeated with the alternative Model for Ozone and Related Chemical Tracers (MOZART) chemical mechanism showed even more strongly enhanced surface ozone mixing ratios due to vertical mixing of enhanced ozone that has been produced aloft. Our study indicates the need to also evaluate the O3 precursors across a network of stations and the development of high-resolution regional inventories for the anthropogenic emissions over south Asia accounting for year-to-year changes to further reduce uncertainties in modelled ozone over this region.

Sensitivity Studies on the Influence of Aerosols on Cloud and Precipitation Development Using WRF Mesoscale Model Simulations

Science.gov (United States)

Thompson, G.; Eidhammer, T.; Rasmussen, R.

2011-12-01

Using the WRF model in simulations of shallow and deep precipitating cloud systems, we investigated the sensitivity to aerosols initiating as cloud condensation and ice nuclei. A global climatological dataset of sulfates, sea salts, and dust was used as input for a control experiment. Sensitivity experiments with significantly more polluted conditions were conducted to analyze the resulting impacts to cloud and precipitation formation. Simulations were performed using the WRF model with explicit treatment of aerosols added to the Thompson et al (2008) bulk microphysics scheme. The modified scheme achieves droplet formation using pre-tabulated CCN activation tables provided by a parcel model. The ice nucleation is parameterized as a function of dust aerosols as well as homogeneous freezing of deliquesced aerosols. The basic processes of aerosol activation and removal by wet scavenging are considered, but aerosol characteristic size or hygroscopicity does not change due to evaporating droplets. In other words, aerosol processing was ignored. Unique aspects of this study include the usage of one to four kilometer grid spacings and the direct parameterization of ice nucleation from aerosols rather than typical temperature and/or supersaturation relationships alone. Initial results from simulations of a deep winter cloud system and its interaction with significant orography show contrasting sensitivities in regions of warm rain versus mixed liquid and ice conditions. The classical view of higher precipitation amounts in relatively clean maritime clouds with fewer but larger droplets is confirmed for regions dominated by the warm-rain process. However, due to complex interactions with the ice phase and snow riming, the simulations revealed the reverse situation in high terrain areas dominated by snow reaching the surface. Results of other cloud systems will be summarized at the conference.

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.

Effects of biomass smoke from southern Africa on stratocumulus over southeastern Atlantic Ocean based on satellite observations and WRF-Chem model simulations

Science.gov (United States)

Lu, Z.; Liu, X.; Zhang, Z.; Zhao, C.; Meyer, K.; Rajapakshe, C.; Wu, C.; Yang, Z.; Penner, J.

2017-12-01

Each year, large amount of biomass burning (BB) aerosols are emitted over southern Africa, and transported by the predominant circulation to the southeastern Atlantic Ocean (SEA), where they overly and potentially interact with the semi-permanent stratocumulus deck in the marine boundary layer (MBL). Many previous studies suggested that the aerosol plumes are well separated from the MBL clouds, and only focused on the radiative effects of BB aerosols (direct + semi-direct radiative effects); however, as shown in several recent satellite observational studies, BB aerosols are able to be frequently entrained into the underlying clouds, function as cloud condensation nuclei (CCN), and potentially cause microphysical effects. Based on satellite observations from CATS, we found that the mixing frequencies between above-cloud aerosols and MBL clouds are very high ( 50%) over both coastal and remote regions, suggesting that BB aerosols may likely contact MBL cloud top and function as CCN quickly after they are transported over SEA. Despite the potential importance of the microphysical effect of BB aerosols over SEA, its magnitude is not fully assessed by modeling studies. In this study, we employ WRF-Chem model to study the impacts of BB aerosols on MBL stratocumulus clouds over SEA during the fire season of 2014. By designing three cases, we are able to quantitatively determine the relative importance of microphysical and radiative effects of BB aerosols. Our modeling results show that, by serving as CCN, BB aerosols are able to alter cloud properties of stratocumulus (e.g. higher cloud droplet number concentration [CDNC], higher cloud liquid water path [LWP], and larger cloud fraction [CF] before noon) and exert significant cooling effect at TOA (-8.05 Wm-2) over SEA. The cooling is primarily caused by higher CDNC (the Twomey effect), and secondarily by the changes in LWP and CF (the cloud lifetime effect). The semi-direct effect estimated in this study is smaller in

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

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.

Application of Weather Research and Forecasting Model with Chemistry (WRF/Chem) over northern China: Sensitivity study, comparative evaluation, and policy implications

Science.gov (United States)

Wang, Litao; Zhang, Yang; Wang, Kai; Zheng, Bo; Zhang, Qiang; Wei, Wei

2016-01-01

An extremely severe and persistent haze event occurred over the middle and eastern China in January 2013, with the record-breaking high concentrations of fine particulate matter (PM2.5). In this study, an online-coupled meteorology-air quality model, the Weather Research and Forecasting Model with Chemistry (WRF/Chem), is applied to simulate this pollution episode over East Asia and northern China at 36- and 12-km grid resolutions. A number of simulations are conducted to examine the sensitivities of the model predictions to various physical schemes. The results show that all simulations give similar predictions for temperature, wind speed, wind direction, and humidity, but large variations exist in the prediction for precipitation. The concentrations of PM2.5, particulate matter with aerodynamic diameter of 10 μm or less (PM10), sulfur dioxide (SO2), and nitrogen dioxide (NO2) are overpredicted partially due to the lack of wet scavenging by the chemistry-aerosol option with the 1999 version of the Statewide Air Pollution Research Center (SAPRC-99) mechanism with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) and the Volatility Basis Set (VBS) for secondary organic aerosol formation. The optimal set of configurations with the best performance is the simulation with the Gorddard shortwave and RRTM longwave radiation schemes, the Purdue Lin microphysics scheme, the Kain-Fritsch cumulus scheme, and a nudging coefficient of 1 × 10-5 for water vapor mixing ratio. The emission sensitivity simulations show that the PM2.5 concentrations are most sensitive to nitrogen oxide (NOx) and SO2 emissions in northern China, but to NOx and ammonia (NH3) emissions in southern China. 30% NOx emission reductions may result in an increase in PM2.5 concentrations in northern China because of the NH3-rich and volatile organic compound (VOC) limited conditions over this area. VOC emission reductions will lead to a decrease in PM2.5 concentrations in eastern China

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.

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

Science.gov (United States)

Hyde, Peter; Mahalov, Alex; Li, Jialun

2018-03-01

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

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...

Radiative effects of light-absorbing particles deposited in snow over Himalayas using WRF-Chem simulations

Science.gov (United States)

Sarangi, C.; Qian, Y.; Painter, T. H.; Liu, Y.; Lin, G.; Wang, H.

2017-12-01

Radiative forcing induced by light-absorbing particles (LAP) deposited on snow is an important surface forcing. It has been debated that an aerosol-induced increase in atmospheric and surface warming over Tibetan Plateau (TP) prior to the South Asian summer monsoon can have a significant effect on the regional thermodynamics and South Asian monsoon circulation. However, knowledge about the radiative effects due to deposition of LAP in snow over TP is limited. In this study we have used a high-resolution WRF-Chem (coupled with online chemistry and snow-LAP-radiation model) simulations during 2013-2014 to estimate the spatio-temporal variation in LAP deposition on snow, specifically black carbon (BC) and dust particles, in Himalayas. Simulated distributions in meteorology, aerosol concentrations, snow albedo, snow grain size and snow depth are evaluated against satellite and in-situ measurements. The spatio-temporal change in snow albedo and snow grain size with variation in LAP deposition is investigated and the resulting shortwave LAP radiative forcing at surface is calculated. The LAP-radiative forcing due to aerosol deposition, both BC and dust, is higher in magnitude over Himalayan slopes (terrain height below 4 km) compared to that over TP (terrain height above 4 km). We found that the shortwave aerosol radiative forcing efficiency at surface due to increase in deposited mass of BC particles in snow layer ( 25 (W/m2)/ (mg/m2)) is manifold higher than the efficiency of dust particles ( 0.1 (W/m2)/ (mg/m2)) over TP. However, the radiative forcing of dust deposited in snow is similar in magnitude (maximum 20-30 W/m2) to that of BC deposited in snow over TP. This is mainly because the amount of dust deposited in snow over TP can be about 100 times greater than the amount of BC deposited in snow during polluted conditions. The impact of LAP on surface energy balance, snow melting and atmospheric thermodynamics is also examined.

Simulations of organic aerosol concentrations in Mexico City using the WRF-CHEM model during the MCMA-2006/MILAGRO campaign

Directory of Open Access Journals (Sweden)

G. Li

2011-04-01

Full Text Available Organic aerosol concentrations are simulated using the WRF-CHEM model in Mexico City during the period from 24 to 29 March in association with the MILAGRO-2006 campaign. Two approaches are employed to predict the variation and spatial distribution of the organic aerosol concentrations: (1 a traditional 2-product secondary organic aerosol (SOA model with non-volatile primary organic aerosols (POA; (2 a non-traditional SOA model including the volatility basis-set modeling method in which primary organic components are assumed to be semi-volatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. The MCMA (Mexico City Metropolitan Area 2006 official emission inventory is used in simulations and the POA emissions are modified and distributed by volatility based on dilution experiments for the non-traditional SOA model. The model results are compared to the Aerosol Mass Spectrometry (AMS observations analyzed using the Positive Matrix Factorization (PMF technique at an urban background site (T0 and a suburban background site (T1 in Mexico City. The traditional SOA model frequently underestimates the observed POA concentrations during rush hours and overestimates the observations in the rest of the time in the city. The model also substantially underestimates the observed SOA concentrations, particularly during daytime, and only produces 21% and 25% of the observed SOA mass in the suburban and urban area, respectively. The non-traditional SOA model performs well in simulating the POA variation, but still overestimates during daytime in the urban area. The SOA simulations are significantly improved in the non-traditional SOA model compared to the traditional SOA model and the SOA production is increased by more than 100% in the city. However, the underestimation during daytime is still salient in the urban area and the non-traditional model also fails to reproduce the high level of SOA concentrations in the

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

Observation of a tropopause fold by MARA VHF wind-profiler radar and ozonesonde at Wasa, Antarctica: comparison with ECMWF analysis and a WRF model simulation

Directory of Open Access Journals (Sweden)

M. Mihalikova

2012-09-01

Full Text Available Tropopause folds are one of the mechanisms of stratosphere–troposphere exchange, which can bring ozone rich stratospheric air to low altitudes in the extra-tropical regions. They have been widely studied at northern mid- or high latitudes, but so far almost no studies have been made at mid- or high southern latitudes. The Moveable Atmospheric Radar for Antarctica (MARA, a 54.5 MHz wind-profiler radar, has operated at the Swedish summer station Wasa, Antarctica (73° S, 13.5° W during austral summer seasons from 2007 to 2011 and has observed on several occasions signatures similar to those caused by tropopause folds at comparable Arctic latitudes. Here a case study is presented of one of these events when an ozonesonde successfully sampled the fold. Analysis from European Center for Medium Range Weather Forecasting (ECMWF is used to study the circumstances surrounding the event, and as boundary conditions for a mesoscale simulation using the Weather Research and Forecasting (WRF model. The fold is well resolved by the WRF simulation, and occurs on the poleward side of the polar jet stream. However, MARA resolves fine-scale layering associated with the fold better than the WRF simulation.

The Transition of High-Resolution NASA MODIS Sea Surface Temperatures into the WRF Environmental Modeling System

Science.gov (United States)

Case, Jonathan L.; Jedlove, Gary J.; Santos, Pablo; Medlin, Jeffrey M.; Rozumalski, Robert A.

2009-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data

Sensitivity analysis of WRF model PBL schemes in simulating boundary-layer variables in southern Italy: An experimental campaign

DEFF Research Database (Denmark)

Avolio, E.; Federico, S.; Miglietta, M.

2017-01-01

the surface, where the model uncertainties are, usually, smaller than at the surface. A general anticlockwise rotation of the simulated flow with height is found at all levels. The mixing height is overestimated by all schemes and a possible role of the simulated sensible heat fluxes for this mismatching......The sensitivity of boundary layer variables to five (two non-local and three local) planetary boundary-layer (PBL) parameterization schemes, available in the Weather Research and Forecasting (WRF) mesoscale meteorological model, is evaluated in an experimental site in Calabria region (southern...... is investigated. On a single-case basis, significantly better results are obtained when the atmospheric conditions near the measurement site are dominated by synoptic forcing rather than by local circulations. From this study, it follows that the two first order non-local schemes, ACM2 and YSU, are the schemes...

The Community WRF-Hydro Modeling System Version 4 Updates: Merging Toward Capabilities of the National Water Model

Science.gov (United States)

McAllister, M.; Gochis, D.; Dugger, A. L.; Karsten, L. R.; McCreight, J. L.; Pan, L.; Rafieeinasab, A.; Read, L. K.; Sampson, K. M.; Yu, W.

2017-12-01

The community WRF-Hydro modeling system is publicly available and provides researchers and operational forecasters a flexible and extensible capability for performing multi-scale, multi-physics options for hydrologic modeling that can be run independent or fully-interactive with the WRF atmospheric model. The core WRF-Hydro physics model contains very high-resolution descriptions of terrestrial hydrologic process representations such as land-atmosphere exchanges of energy and moisture, snowpack evolution, infiltration, terrain routing, channel routing, basic reservoir representation and hydrologic data assimilation. Complementing the core physics components of WRF-Hydro are an ecosystem of pre- and post-processing tools that facilitate the preparation of terrain and meteorological input data, an open-source hydrologic model evaluation toolset (Rwrfhydro), hydrologic data assimilation capabilities with DART and advanced model visualization capabilities. The National Center for Atmospheric Research (NCAR), through collaborative support from the National Science Foundation and other funding partners, provides community support for the entire WRF-Hydro system through a variety of mechanisms. This presentation summarizes the enhanced user support capabilities that are being developed for the community WRF-Hydro modeling system. These products and services include a new website, open-source code repositories, documentation and user guides, test cases, online training materials, live, hands-on training sessions, an email list serve, and individual user support via email through a new help desk ticketing system. The WRF-Hydro modeling system and supporting tools which now include re-gridding scripts and model calibration have recently been updated to Version 4 and are merging toward capabilities of the National Water Model.

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.

Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

Science.gov (United States)

Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

2018-02-01

Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation

Evaluation of the atmospheric model WRF on the Qatar peninsula for a converging sea-breeze event

Science.gov (United States)

Balan Sobhana, Sandeepan; Nayak, Sashikant; Panchang, Vijay

2016-04-01

Qatar, a narrow peninsula covering an area of 11437 sq km, extends northwards into the Arabian Gulf for about 160km and has a maximum width of 88km. The convex shape of the coast-line and narrowness of the peninsula results in the Qatar region experiencing complex wind patterns. The geometry is favorable for formation of the land-sea breeze from both coastal sides of the peninsula. This can lead to the development of sea breeze convergence zones in the middle of the country. Although circulations arising from diurnal thermal contrast of land and water are amongst most intensively studied meteorological phenomena, there is no reported study for the Qatar peninsula and very few studies are reported for the Arabian Gulf region as whole. It is necessary to characterize the wind field for applications such as assessing air pollution, renewable energy etc. A non-hydrostatic mesoscale model, Weather Research and Forecast (WRF) with a nested high resolution grid permits the investigation of such fine scale phenomena. Data from eighteen land based Automated Weather Stations (AWS) and two offshore buoys deployed and maintained by the Qatar Meteorological Department were analyzed. Based on the analysis a clear case of sea breeze convergence were seen on 18 September 2015. Model simulations were used to investigate the synoptic conditions associated with the formation of this event. The season is characterized by week ambient north westerly wind over the Arabian Gulf. The WRF model performance is validated using observed in-situ data. Model simulations show that vertical extent of sea breeze cell was up to 1 km and the converging sea breeze regions were characterized with high vertical velocities. The WRF simulation also revealed that with high resolution, the model is capable of reproducing the fine scale patterns accurately. The error of predictions in the inner domain (highest resolution) are found to be relatively lower than coarse resolution domain. The maximum wind speed

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

Science.gov (United States)

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

2015-12-01

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

WRF-Fire Applied in Bulgaria

OpenAIRE

Dobrinkova, Nina; Jordanov, Georgi; Mandel, Jan

2010-01-01

WRF-Fire consists of the WRF (Weather Research and Forecasting Model) coupled with a fire spread model, based on the level-set method. We describe a preliminary application of WRF-Fire to a forest fire in Bulgaria, oportunities for research of forest fire models for Bulgaria, and plans for the development of an Environmental Decision Support Systems which includes computational modeling of fire behavior.

Regional and urban downscaling of global climate scenarios for health impact assessments

Energy Technology Data Exchange (ETDEWEB)

San Jose, R.; Perez, J.L.; Perez, L.; Gonzalez, R.M.; Pecci, J.; Garzon, A.; Palacios, M.

2015-07-01

In this contribution we have used global climate RCP IPCC scenarios to produce climate and air pollution maps at regional (25 km resolution) and urban scale with 200 m spatial resolution over Europe and five European cities in order to investigate the impact on meteorological variables and pollutant concentrations . We have used the very well known mesoscale meeorological model WRF-Chem (NOAA, US). We have used 2011 as control past year and two RCP scenarios from CCSM global climate model with 4.5 W/m2 and 8.5 W/m2 for 2030, 2050 and 2100 years. After running WRF-Chem model, using the boundary conditions provided by RCP scenarios with the emissions of 2011, we have performed a detailed downscaling process using CALMET diagnostic model to obtain a full 200 m spatial resolution map of five European cities (London, Antwerp, Madrid, Milan, and Helsinki). We will show the results and the health impacts for future RCP IPCC climate scenarios in comparison with the 2011 control year information for climate and health indicators. Finnally, we have also investigated the impact of the aerosol effects in the short wave radiation mean value. Two simulations with the WRF-Chem model have been performed over Europe in 2010. A baseline simulation without any feedback effects and a second simulation including the direct effects affecting the solar radiation reaching the surface as well as the indirect aerosol effect with potential impacts on increasing or decreasing the precipitation rates. Aerosol effects produce an increase of incoming radiation over Atlantic Ocean (up to 70%) because the prescribed aerosol concentrations in the WRF-Chem without feedbacks is substantially higher than the aerosol concentrations produced when we activate the feedback effects. The decrease in solar radiation in the Sahara area (10%) is found to be produced because the prescribed aerosol concentration in the {sup n}o feedback{sup s}imulation is lower than when we activate the feedback effects. (Author)

Regional and urban down scaling of global climate scenarios for health impact assessments

Energy Technology Data Exchange (ETDEWEB)

San Jose, R.; Perez, J. L.; Perez, L.; Gonzalez, R. M.; Pecci, J.; Garzon, A.; Palacios, M.

2015-07-01

In this contribution we have used global climate RCP IPCC scenarios to produce climate and air pollution maps at regional (25 km resolution) and urban scale with 200 m spatial resolution over Europe and five European cities in order to investigate the impact on meteorological variables and pollutant concentrations . We have used the very well known mesoscale meteorological model WRF-Chem (NOAA, US). We have used 2011 as control past year and two RCP scenarios from CCSM global climate model with 4.5 W/m2 and 8.5 W/m2 for 2030, 2050 and 2100 years. After running WRF-Chem model, using the boundary conditions provided by RCP scenarios with the emissions of 2011, we have performed a detailed down scaling process using CALMET diagnostic model to obtain a full 200 m spatial resolution map of five European cities (London, Antwerp, Madrid, Milan, and Helsinki). We will show the results and the health impacts for future RCP IPCC climate scenarios in comparison with the 2011 control year information for climate and health indicators. Finally, we have also investigated the impact of the aerosol effects in the short wave radiation mean value. Two simulations with the WRF-Chem model have been performed over Europe in 2010. A baseline simulation without any feedback effects and a second simulation including the direct effects affecting the solar radiation reaching the surface as well as the indirect aerosol effect with potential impacts on increasing or decreasing the precipitation rates. Aerosol effects produce an increase of incoming radiation over Atlantic Ocean (up to 70%) because the prescribed aerosol concentrations in the WRF-Chem without feedbacks is substantially higher than the aerosol concentrations produced when we activate the feedback effects. The decrease in solar radiation in the Sahara area (10%) is found to be produced because the prescribed aerosol concentration in the no feedback simulation is lower than when we activate the feedback effects. (Author)

A Dynamical Downscaling study over the Great Lakes Region Using WRF-Lake: Historical Simulation

Science.gov (United States)

Xiao, C.; Lofgren, B. M.

2014-12-01

As the largest group of fresh water bodies on Earth, the Laurentian Great Lakes have significant influence on local and regional weather and climate through their unique physical features compared with the surrounding land. Due to the limited spatial resolution and computational efficiency of general circulation models (GCMs), the Great Lakes are geometrically ignored or idealized into several grid cells in GCMs. Thus, the nested regional climate modeling (RCM) technique, known as dynamical downscaling, serves as a feasible solution to fill the gap. The latest Weather Research and Forecasting model (WRF) is employed to dynamically downscale the historical simulation produced by the Geophysical Fluid Dynamics Laboratory-Coupled Model (GFDL-CM3) from 1970-2005. An updated lake scheme originated from the Community Land Model is implemented in the latest WRF version 3.6. It is a one-dimensional mass and energy balance scheme with 20-25 model layers, including up to 5 snow layers on the lake ice, 10 water layers, and 10 soil layers on the lake bottom. The lake scheme is used with actual lake points and lake depth. The preliminary results show that WRF-Lake model, with a fine horizontal resolution and realistic lake representation, provides significantly improved hydroclimates, in terms of lake surface temperature, annual cycle of precipitation, ice content, and lake-effect snowfall. Those improvements suggest that better resolution of the lakes and the mesoscale process of lake-atmosphere interaction are crucial to understanding the climate and climate change in the Great Lakes region.

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.

Anthropogenic and volcanic emission impacts on SO2 dynamics and acid rain profiles. Numerical study using WRF-Chem in a high-resolution modeling

Science.gov (United States)

Vela, A. V.; González, C. M.; Ynoue, R.; Rojas, N. Y.; Aristizábal, B. H.; Wahl, M.

2017-12-01

Eulerian 3-D chemistry transport models (CTM) have been widely used for the study of air quality in urban environments, becoming an essential tool for studying the impacts and dynamics of gases and aerosols on air quality. However, their use in Colombia is scarce, especially in medium-sized cities, which are experimenting a fast urban growth, increasing the risk associated with possible air pollution episodes. In the densely populated medium-sized Andean city of Manizales, Colombia - a city located on the western slopes of the central range of the Andes (urban population 368000; 2150 m.a.s.l), there is an influence of the active Nevado del Ruiz volcano, located 28 km to the southwest. This natural source emits daily gas and particle fluxes, which could influence the atmospheric chemistry of the city and neighboring towns. Hence, the zone presents a unique combination of anthropogenic and volcanic sulfur gas emissions, which affects SO2 dynamics in the urban area, influencing also in the formation of acid rain phenomenon in the city. Therefore, studies analyzing the relative contribution of anthropogenic and volcanic emission could contribute with a deep understanding about causes and dynamics of both acid rain phenomenon and ambient SO2 levels in Manizales. This work aimed to analyze the influence of anthropogenic (on-road vehicular and industrial point-sources) and volcanic sulfur emissions in SO2 atmospheric chemistry dynamics, evaluating its possible effects on acid rain profiles. Ambient SO2 levels and day-night rain samples were measured and used to analyze results obtained from the application of the fully-coupled on-line WRF-Chem model. Two high-resolution simulations were performed during two dry and wet one-week periods in 2015. Analysis of SO2 dispersion patterns and comparison with SO2 observations in the urban area were performed for three different scenarios in which natural and anthropogenic emissions were simulated separately. Results suggest that

WRF-based fire risk modelling and evaluation for years 2010 and 2012 in Poland

Science.gov (United States)

Stec, Magdalena; Szymanowski, Mariusz; Kryza, Maciej

2016-04-01

Wildfires are one of the main ecosystems' disturbances for forested, seminatural and agricultural areas. They generate significant economic loss, especially in forest management and agriculture. Forest fire risk modeling is therefore essential e.g. for forestry administration. In August 2015 a new method of forest fire risk forecasting entered into force in Poland. The method allows to predict a fire risk level in a 4-degree scale (0 - no risk, 3 - highest risk) and consists of a set of linearized regression equations. Meteorological information is used as predictors in regression equations, with air temperature, relative humidity, average wind speed, cloudiness and rainfall. The equations include also pine litter humidity as a measure of potential fuel characteristics. All these parameters are measured routinely in Poland at 42 basic and 94 auxiliary sites. The fire risk level is estimated for a current (basing on morning measurements) or next day (basing on midday measurements). Entire country is divided into 42 prognostic zones, and fire risk level for each zone is taken from the closest measuring site. The first goal of this work is to assess if the measurements needed for fire risk forecasting may be replaced by the data from mesoscale meteorological model. Additionally, the use of a meteorological model would allow to take into account much more realistic spatial differentiation of weather elements determining the fire risk level instead of discrete point-made measurements. Meteorological data have been calculated using the Weather Research and Forecasting model (WRF). For the purpose of this study the WRF model is run in the reanalysis mode allowing to estimate all required meteorological data in a 5-kilometers grid. The only parameter that cannot be directly calculated using WRF is the litter humidity, which has been estimated using empirical formula developed by Sakowska (2007). The experiments are carried out for two selected years: 2010 and 2012. The

Effects of Initial Drivers and Land Use on WRF Modeling for Near-Surface Fields and Atmospheric Boundary Layer over the Northeastern Tibetan Plateau

Directory of Open Access Journals (Sweden)

Junhua Yang

2016-01-01

Full Text Available To improve the simulation performance of mesoscale models in the northeastern Tibetan Plateau, two reanalysis initial datasets (NCEP FNL and ERA-Interim and two MODIS (Moderate-Resolution Imaging Spectroradiometer land-use datasets (from 2001 and 2010 are used in WRF (Weather Research and Forecasting modeling. The model can reproduce the variations of 2 m temperature (T2 and 2 m relative humidity (RH2, but T2 is overestimated and RH2 is underestimated in the control experiment. After using the new initial drive and land use data, the simulation precision in T2 is improved by the correction of overestimated net energy flux at surface and the RH2 is improved due to the lower T2 and larger soil moisture. Due to systematic bias in WRF modeling for wind speed, we design another experiment that includes the Jimenez subgrid-scale orography scheme, which reduces the frequency of low wind speed and increases the frequency of high wind speed and that is more consistent with the observation. Meanwhile, the new drive and land-use data lead to lower boundary layer height and influence the potential temperature and wind speed in both the lower atmosphere and the upper layer, while the impact on water vapor mixing ratio is primarily concentrated in the lower atmosphere.

Contribution of ship emissions to the concentration of PM2.5: A comprehensive study using AIS data and WRF/Chem model in Bohai Rim Region, China.

Science.gov (United States)

Chen, Dongsheng; Zhao, Na; Lang, Jianlei; Zhou, Ying; Wang, Xiaotong; Li, Yue; Zhao, Yuehua; Guo, Xiurui

2018-01-01

Compared with on-road vehicles, emission from ships is one of the least-regulated anthropogenic emission sources and non-negligible source of primary aerosols and gas-phase precursors of PM 2.5 . The Bohai Rim Region in China hosts dozens of large ports, two of which ranked among the top ten ports in the world. To determine the impact of ship emissions on the PM 2.5 concentrations over this region, two parts of works have been conducted in this study. First, a detailed ship emission inventory with high spatiotemporal resolution was developed based on Automatic Identification System (AIS) data. Then the WRF/Chem model was applied to modeling the impact of ship emissions by comparing two scenarios: with and without ship emissions. The results indicate that the total estimated ship emissions of SO 2 , NO X , PM 10 , PM 2.5 , CO, HC, and CO 2 from Bohai Rim Region in 2014 are 1.9×10 5 , 2.9×10 5 , 2.6×10 4 , 2.4×10 4 , 2.5×10 4 , 1.2×10 4 , and 1.3×10 7 tonnes, respectively. The modeling results indicate that the annual PM 2.5 concentrations increased by 5.9% on land areas of Bohai Rim Region (the continent within 115.2°E-124.3°E and 36.1°N-41.6°N) due to ship emissions. The contributions show distinctive seasonal variations of contributions, presenting highest in summer (12.5%) followed by spring (6.9%) and autumn (3.3%), and lowest in winter (0.9%). The contribution reaches up to 10.7% along the shoreline and down to 1.0% 200km inland. After examining the statistics of the modeling results during heavy and non-heavy haze days in July, it was found that 6 out of 9 cities around the Bohai Rim Region were observed with higher contributions from ship emissions during heavy haze days compared with non-heavy haze days. These results indicate that the impacts of ship emissions on the ambient PM 2.5 are non-negligible, especially for heavy haze days for most coastal cities in the Bohai Rim Region. Copyright © 2017 Elsevier B.V. All rights reserved.

An Iberian climatology of solar radiation obtained from WRF regional climate simulations for 1950-2010 period

Science.gov (United States)

Perdigão, João; Salgado, Rui; Magarreiro, Clarisse; Soares, Pedro M. M.; Costa, Maria João; Dasari, Hari Prasad

2017-12-01

The mesoscale Weather Research and Forecasting (WRF) Model is used over the Iberian Peninsula to generate 60 years (1950-2010) of climate data, at 5 km resolution, in order to evaluate and characterize the incident shortwave downward radiation at the surface (SW ↓), in present climate. The simulated values of SW ↓ in the period 2000-2009 were compared with data measured in Spanish and Portuguese meteorological stations before and a statistical BIAS correction was applied using data from Clouds and the Earth's Radiant Energy System (CERES), on board four different satellites. The spatial and temporal comparison between WRF results and observations show a good agreement for the analyzed period, although the model overestimates observations. This overestimation has a mean normalized bias of about 7% after BIAS correction (or 17% for original WRF output). Additionally, the present simulation was confronted against another previously validated WRF simulation performed with different resolution and set of parametrizations, showing comparable results. WRF adequately reproduces the observational features of SW ↓ with correlation coefficients above 0.8 in annual and seasonal basis. 60 years of simulated SW ↓ over the Iberian Peninsula were produced, which showed annual mean values that range from 130 W/m2, in the northern regions, to a maximum of around 230 W/m2 in the southeast of the Iberian Peninsula (IP). SW ↓ over IP shows a positive gradient from north to south and from west to east, with local effects influenced by topography and distance to the coast. The analysis of the simulated cloud fraction indicates that clear sky days are found in > 30% of the period at the southern area of IP, particularly in the Algarve (Portugal) and Andalusia (Spain), and this value increases significantly in the summer season for values above 80%.

Cold Outbreaks at the Mesoscale in the Western Mediterranean Basin: From Raincells to Rainbands

Directory of Open Access Journals (Sweden)

Jordi Mazon

2017-01-01

Full Text Available This paper investigates cold outbreaks that form offshore density currents within the whole mesoscale over the Western Mediterranean basin. Reflectivity radar and satellite images are used to detect clouds and precipitation that are associated with these density currents in the meso-α, meso-β, and meso-γ over the Western Mediterranean basin (WMB. Version 3.3 of the WRF-ARW model is used to describe the formation and evolution of these density currents and to estimate their lifetime as well as horizontal and vertical scales. Based on the observations and simulations, this paper suggests that a new perspective could effectively be adopted regarding the WMB region delineated by the Balearic Islands, the northeastern Iberian Peninsula, and the Gulf of Lion, where inland cold outbreaks develop into density currents that move offshore and can produce precipitation ranging from raincells to rainbands at the whole mesoscale.

Impacts of aerosols on seasonal precipitation and snowpack in California based on convection-permitting WRF-Chem simulations

Science.gov (United States)

Wu, Longtao; Gu, Yu; Jiang, Jonathan H.; Su, Hui; Yu, Nanpeng; Zhao, Chun; Qian, Yun; Zhao, Bin; Liou, Kuo-Nan; Choi, Yong-Sang

2018-04-01

A version of the WRF-Chem model with fully coupled aerosol-meteorology-snowpack is employed to investigate the impacts of various aerosol sources on precipitation and snowpack in California. In particular, the impacts of locally emitted anthropogenic and dust aerosols, and aerosols transported from outside California are studied. We differentiate three pathways of aerosol effects: aerosol-radiation interaction (ARI), aerosol-snow interaction (ASI), and aerosol-cloud interaction (ACI). The convection-permitting model simulations show that precipitation, snow water equivalent (SWE), and surface air temperature averaged over the whole domain (34-42° N, 117-124° W, not including ocean points) are reduced when aerosols are included, therefore reducing large biases in these variables due to the absence of aerosol effects in the model. Aerosols affect California water resources through the warming of mountaintops and the reduction of precipitation; however, different aerosol sources play different roles in changing surface temperature, precipitation, and snowpack in California by means of various weights of the three pathways. ARI by all aerosols mainly cools the surface, leading to slightly increased SWE over the mountains. Locally emitted dust aerosols warm the surface of mountaintops through ASI, in which the reduced snow albedo associated with dusty snow leads to more surface absorption of solar radiation and reduced SWE. Transported aerosols and local anthropogenic aerosols play a dominant role in increasing nonprecipitating clouds but reducing precipitation through ACI, leading to reduced SWE and runoff on the Sierra Nevada, as well as the warming of mountaintops associated with decreased SWE and hence lower surface albedo. The average changes in surface temperature from October 2012 to June 2013 are about -0.19 and 0.22 K for the whole domain and over mountaintops, respectively. Overall, the averaged reduction during October to June is about 7 % for precipitation

WRF-Chem model predictions of the regional impacts of N2O5 heterogeneous processes on night-time chemistry over north-western Europe

Directory of Open Access Journals (Sweden)

D. Lowe

2015-02-01

Full Text Available Chemical modelling studies have been conducted over north-western Europe in summer conditions, showing that night-time dinitrogen pentoxide (N2O5 heterogeneous reactive uptake is important regionally in modulating particulate nitrate and has a~modest influence on oxidative chemistry. Results from Weather Research and Forecasting model with Chemistry (WRF-Chem model simulations, run with a detailed volatile organic compound (VOC gas-phase chemistry scheme and the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC sectional aerosol scheme, were compared with a series of airborne gas and particulate measurements made over the UK in July 2010. Modelled mixing ratios of key gas-phase species were reasonably accurate (correlations with measurements of 0.7–0.9 for NO2 and O3. However modelled loadings of particulate species were less accurate (correlation with measurements for particulate sulfate and ammonium were between 0.0 and 0.6. Sulfate mass loadings were particularly low (modelled means of 0.5–0.7 μg kg−1air, compared with measurements of 1.0–1.5 μg kg−1air. Two flights from the campaign were used as test cases – one with low relative humidity (RH (60–70%, the other with high RH (80–90%. N2O5 heterogeneous chemistry was found to not be important in the low-RH test case; but in the high-RH test case it had a strong effect and significantly improved the agreement between modelled and measured NO3 and N2O5. When the model failed to capture atmospheric RH correctly, the modelled NO3 and N2O5 mixing ratios for these flights differed significantly from the measurements. This demonstrates that, for regional modelling which involves heterogeneous processes, it is essential to capture the ambient temperature and water vapour profiles. The night-time NO3 oxidation of VOCs across the whole region was found to be 100–300 times slower than the daytime OH oxidation of these compounds. The difference in contribution was less

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.

Implementation of a gust front head collapse scheme in the WRF numerical model

Science.gov (United States)

Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje

2018-05-01

Gust fronts are thunderstorm-related phenomena usually associated with severe winds which are of great importance in theoretical meteorology, weather forecasting, cloud dynamics and precipitation, and wind engineering. An important feature of gust fronts demonstrated through both theoretical and observational studies is the periodic collapse and rebuild of the gust front head. This cyclic behavior of gust fronts results in periodic forcing of vertical velocity ahead of the parent thunderstorm, which consequently influences the storm dynamics and microphysics. This paper introduces the first gust front pulsation parameterization scheme in the WRF-ARW model (Weather Research and Forecasting-Advanced Research WRF). The influence of this new scheme on model performances is tested through investigation of the characteristics of an idealized supercell cumulonimbus cloud, as well as studying a real case of thunderstorms above the United Arab Emirates. In the ideal case, WRF with the gust front scheme produced more precipitation and showed different time evolution of mixing ratios of cloud water and rain, whereas the mixing ratios of ice and graupel are almost unchanged when compared to the default WRF run without the parameterization of gust front pulsation. The included parameterization did not disturb the general characteristics of thunderstorm cloud, such as the location of updraft and downdrafts, and the overall shape of the cloud. New cloud cells in front of the parent thunderstorm are also evident in both ideal and real cases due to the included forcing of vertical velocity caused by the periodic collapse of the gust front head. Despite some differences between the two WRF simulations and satellite observations, the inclusion of the gust front parameterization scheme produced more cumuliform clouds and seem to match better with real observations. Both WRF simulations gave poor results when it comes to matching the maximum composite radar reflectivity from radar

An Iberian climatology of solar radiation obtained from WRF regional climate simulations for 1950–2010 period

KAUST Repository

Perdigão, João

2017-08-15

The mesoscale Weather Research and Forecasting (WRF) Model is used over the Iberian Peninsula to generate 60years (1950–2010) of climate data, at 5km resolution, in order to evaluate and characterize the incident shortwave downward radiation at the surface (SW↓), in present climate.The simulated values of SW↓ in the period 2000–2009 were compared with data measured in Spanish and Portuguese meteorological stations before and a statistical BIAS correction was applied using data from Clouds and the Earth\\'s Radiant Energy System (CERES), on board four different satellites. The spatial and temporal comparison between WRF results and observations show a good agreement for the analyzed period, although the model overestimates observations. This overestimation has a mean normalized bias of about 7% after BIAS correction (or 17% for original WRF output). Additionally, the present simulation was confronted against another previously validated WRF simulation performed with different resolution and set of parametrizations, showing comparable results. WRF adequately reproduces the observational features of SW↓ with correlation coefficients above 0.8 in annual and seasonal basis.60years of simulated SW↓ over the Iberian Peninsula were produced, which showed annual mean values that range from 130W/m2, in the northern regions, to a maximum of around 230W/m2 in the southeast of the Iberian Peninsula (IP). SW↓ over IP shows a positive gradient from north to south and from west to east, with local effects influenced by topography and distance to the coast.The analysis of the simulated cloud fraction indicates that clear sky days are found in >30% of the period at the southern area of IP, particularly in the Algarve (Portugal) and Andalusia (Spain), and this value increases significantly in the summer season for values above 80%.

An Iberian climatology of solar radiation obtained from WRF regional climate simulations for 1950–2010 period

KAUST Repository

Perdigã o, Joã o; Salgado, Rui; Magarreiro, Clarisse; Soares, Pedro M.M.; Costa, Maria Joã o; Dasari, Hari Prasad

2017-01-01

The mesoscale Weather Research and Forecasting (WRF) Model is used over the Iberian Peninsula to generate 60years (1950–2010) of climate data, at 5km resolution, in order to evaluate and characterize the incident shortwave downward radiation at the surface (SW↓), in present climate.The simulated values of SW↓ in the period 2000–2009 were compared with data measured in Spanish and Portuguese meteorological stations before and a statistical BIAS correction was applied using data from Clouds and the Earth's Radiant Energy System (CERES), on board four different satellites. The spatial and temporal comparison between WRF results and observations show a good agreement for the analyzed period, although the model overestimates observations. This overestimation has a mean normalized bias of about 7% after BIAS correction (or 17% for original WRF output). Additionally, the present simulation was confronted against another previously validated WRF simulation performed with different resolution and set of parametrizations, showing comparable results. WRF adequately reproduces the observational features of SW↓ with correlation coefficients above 0.8 in annual and seasonal basis.60years of simulated SW↓ over the Iberian Peninsula were produced, which showed annual mean values that range from 130W/m2, in the northern regions, to a maximum of around 230W/m2 in the southeast of the Iberian Peninsula (IP). SW↓ over IP shows a positive gradient from north to south and from west to east, with local effects influenced by topography and distance to the coast.The analysis of the simulated cloud fraction indicates that clear sky days are found in >30% of the period at the southern area of IP, particularly in the Algarve (Portugal) and Andalusia (Spain), and this value increases significantly in the summer season for values above 80%.

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...

WRF model sensitivity to choice of parameterization: a study of the `York Flood 1999'

Science.gov (United States)

Remesan, Renji; Bellerby, Tim; Holman, Ian; Frostick, Lynne

2015-10-01

Numerical weather modelling has gained considerable attention in the field of hydrology especially in un-gauged catchments and in conjunction with distributed models. As a consequence, the accuracy with which these models represent precipitation, sub-grid-scale processes and exceptional events has become of considerable concern to the hydrological community. This paper presents sensitivity analyses for the Weather Research Forecast (WRF) model with respect to the choice of physical parameterization schemes (both cumulus parameterisation (CPSs) and microphysics parameterization schemes (MPSs)) used to represent the `1999 York Flood' event, which occurred over North Yorkshire, UK, 1st-14th March 1999. The study assessed four CPSs (Kain-Fritsch (KF2), Betts-Miller-Janjic (BMJ), Grell-Devenyi ensemble (GD) and the old Kain-Fritsch (KF1)) and four MPSs (Kessler, Lin et al., WRF single-moment 3-class (WSM3) and WRF single-moment 5-class (WSM5)] with respect to their influence on modelled rainfall. The study suggests that the BMJ scheme may be a better cumulus parameterization choice for the study region, giving a consistently better performance than other three CPSs, though there are suggestions of underestimation. The WSM3 was identified as the best MPSs and a combined WSM3/BMJ model setup produced realistic estimates of precipitation quantities for this exceptional flood event. This study analysed spatial variability in WRF performance through categorical indices, including POD, FBI, FAR and CSI during York Flood 1999 under various model settings. Moreover, the WRF model was good at predicting high-intensity rare events over the Yorkshire region, suggesting it has potential for operational use.

Evaluation of a multi-scale WRF-CAM5 simulation during the 2010 East Asian Summer Monsoon

Energy Technology Data Exchange (ETDEWEB)

Campbell, Patrick; Zhang, Yang; Wang, Kai; Leung, Ruby; Fan, Jiwen; Zheng, Bo; Zhang, Qiang; He, Kebin

2017-11-01

The Weather Research and Forecasting model with Chemistry (WRF-Chem) with the physics package of the Community Atmosphere Model Version 5 (CAM5) has been applied at multiple scales over Eastern China (EC) and the Yangtze River Delta (YRD) to evaluate how increased horizontal resolution with physics designed for a coarser resolution climate model impacts aerosols and clouds, and the resulting precipitation characteristics and performance during the 2010 East Asian Summer Monsoon (EASM). Despite large underpredictions in surface aerosol concentrations and aerosol optical depth, there is good spatial agreement with surface observations of chemical predictions, and increasing spatial resolution tends to improve performance. Model bias and normalized root mean square values for precipitation predictions are relatively small, but there are significant differences when comparing modeled and observed probability density functions for precipitation in EC and YRD. Increasing model horizontal resolution tends to reduce model bias and error for precipitation predictions. The surface and column aerosol loading is maximized between about 32N and 42N in early to mid-May during the 2010 EASM, and then shifts north while decreasing in magnitude during July and August. Changing model resolution moderately changes the spatiotemporal relationships between aerosols, cloud properties, and precipitation during the EASM, thus demonstrating the importance of model grid resolution in simulating EASM circulation and rainfall patterns over EC and the YRD. Results from this work demonstrate the capability and limitations in the aerosol, cloud, and precipitation representation of WRF-CAM5 for regional-scale applications down to relatively fine horizontal resolutions. Further WRF-CAM5 model development and application in this area is needed.

Impacts of aerosols on seasonal precipitation and snowpack in California based on convection-permitting WRF-Chem simulations

Energy Technology Data Exchange (ETDEWEB)

Wu, Longtao; Gu, Yu; Jiang, Jonathan; Su, Hui; Yu, Nanpeng; Zhao, Chun; Qian, Yun; Zhao, Bin; Liou, K. N.; Choi, Yong-Sang

2018-04-23

A version of the WRF-Chem model with fully coupled aerosol–meteorology–snowpack is employed to investigate the impacts of various aerosol sources on precipitation and snowpack in California. In particular, the impacts of locally emitted anthropogenic and dust aerosols, and aerosols transported from outside California are studied. We differentiate three pathways of aerosol effects: aerosol–radiation interaction (ARI), aerosol–snow interaction (ASI), and aerosol–cloud interaction (ACI). The convection-permitting model simulations show that precipitation, snow water equivalent (SWE), and surface air temperature averaged over the whole domain (34–42° N, 117–124° W, not including ocean points) are reduced when aerosols are included, therefore reducing large biases in these variables due to the absence of aerosol effects in the model. Aerosols affect California water resources through the warming of mountaintops and the reduction of precipitation; however, different aerosol sources play different roles in changing surface temperature, precipitation, and snowpack in California by means of various weights of the three pathways. ARI by all aerosols mainly cools the surface, leading to slightly increased SWE over the mountains. Locally emitted dust aerosols warm the surface of mountaintops through ASI, in which the reduced snow albedo associated with dusty snow leads to more surface absorption of solar radiation and reduced SWE. Transported aerosols and local anthropogenic aerosols play a dominant role in increasing nonprecipitating clouds but reducing precipitation through ACI, leading to reduced SWE and runoff on the Sierra Nevada, as well as the warming of mountaintops associated with decreased SWE and hence lower surface albedo. The average changes in surface temperature from October 2012 to June 2013 are about −0.19 and 0.22 K for the whole domain and over mountaintops, respectively. Overall, the averaged reduction during October to June is about

Model representations of aerosol layers transported from North America over the Atlantic Ocean during the Two-Column Aerosol Project

Energy Technology Data Exchange (ETDEWEB)

Fast, Jerome D.; Berg, Larry K.; Zhang, Kai; Easter, Richard C.; Ferrare, Richard A.; Hair, John; Hostetler, Chris A.; Liu, Ying; Ortega, Ivan; Sedlacek, Art; Shilling, John E.; Shrivastava, ManishKumar B.; Springston, Stephen R.; Tomlinson, Jason M.; Volkamer, Rainer M.; Wilson, Jacqueline M.; Zaveri, Rahul A.; Zelenyuk-Imre, Alla

2016-08-22

The ability of the Weather Research and Forecasting model with chemistry (WRF-Chem) version 3.7 and the Community Atmosphere Model version 5.3 (CAM5) in simulating profiles of aerosol properties is quantified using extensive in situ and remote sensing measurements from the Two Column Aerosol Project (TCAP) conducted during July of 2012. TCAP was supported by the U.S. Department of Energy’s Atmospheric Radiation Measurement program and was designed to obtain observations within two atmospheric columns; one fixed over Cape Cod, Massachusetts and the other several hundred kilometers over the ocean. The performance is quantified using most of the available aircraft and surface measurements during July, and two days are examined in more detail to identify the processes responsible for the observed aerosol layers. The higher resolution WRF-Chem model produced more aerosol mass in the free troposphere than the coarser resolution CAM5 model so that the fraction of aerosol optical thickness above the residual layer from WRF-Chem was more consistent with lidar measurements. We found that the free troposphere layers are likely due to mean vertical motions associated with synoptic-scale convergence that lifts aerosols from the boundary layer. The vertical displacement and the time period associated with upward transport in the troposphere depend on the strength of the synoptic system and whether relatively high boundary layer aerosol concentrations are present where convergence occurs. While a parameterization of subgrid scale convective clouds applied in WRF-Chem modulated the concentrations of aerosols aloft, it did not significantly change the overall altitude and depth of the layers.

WRF nested large-eddy simulations of deep convection during SEAC4RS

Science.gov (United States)

Heath, Nicholas K.; Fuelberg, Henry E.; Tanelli, Simone; Turk, F. Joseph; Lawson, R. Paul; Woods, Sarah; Freeman, Sean

2017-04-01

Large-eddy simulations (LES) and observations are often combined to increase our understanding and improve the simulation of deep convection. This study evaluates a nested LES method that uses the Weather Research and Forecasting (WRF) model and, specifically, tests whether the nested LES approach is useful for studying deep convection during a real-world case. The method was applied on 2 September 2013, a day of continental convection that occurred during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. Mesoscale WRF output (1.35 km grid length) was used to drive a nested LES with 450 m grid spacing, which then drove a 150 m domain. Results reveal that the 450 m nested LES reasonably simulates observed reflectivity distributions and aircraft-observed in-cloud vertical velocities during the study period. However, when examining convective updrafts, reducing the grid spacing to 150 m worsened results. We find that the simulated updrafts in the 150 m run become too diluted by entrainment, thereby generating updrafts that are weaker than observed. Lastly, the 450 m simulation is combined with observations to study the processes forcing strong midlevel cloud/updraft edge downdrafts that were observed on 2 September. Results suggest that these strong downdrafts are forced by evaporative cooling due to mixing and by perturbation pressure forces acting to restore mass continuity around neighboring updrafts. We conclude that the WRF nested LES approach, with further development and evaluation, could potentially provide an effective method for studying deep convection in real-world cases.

Improved cyberinfrastructure for integrated hydrometeorological predictions within the fully-coupled WRF-Hydro modeling system

Science.gov (United States)

gochis, David; hooper, Rick; parodi, Antonio; Jha, Shantenu; Yu, Wei; Zaslavsky, Ilya; Ganapati, Dinesh

2014-05-01

The community WRF-Hydro system is currently being used in a variety of flood prediction and regional hydroclimate impacts assessment applications around the world. Despite its increasingly wide use certain cyberinfrastructure bottlenecks exist in the setup, execution and post-processing of WRF-Hydro model runs. These bottlenecks result in wasted time, labor, data transfer bandwidth and computational resource use. Appropriate development and use of cyberinfrastructure to setup and manage WRF-Hydro modeling applications will streamline the entire workflow of hydrologic model predictions. This talk will present recent advances in the development and use of new open-source cyberinfrastructure tools for the WRF-Hydro architecture. These tools include new web-accessible pre-processing applications, supercomputer job management applications and automated verification and visualization applications. The tools will be described successively and then demonstrated in a set of flash flood use cases for recent destructive flood events in the U.S. and in Europe. Throughout, an emphasis on the implementation and use of community data standards for data exchange is made.

A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model

Science.gov (United States)

Capecchi, V.; Gozzini, B.

2012-04-01

The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently

Extending flood forecasting lead time in a large watershed by coupling WRF QPF with a distributed hydrological model

Science.gov (United States)

Li, Ji; Chen, Yangbo; Wang, Huanyu; Qin, Jianming; Li, Jie; Chiao, Sen

2017-03-01

Long lead time flood forecasting is very important for large watershed flood mitigation as it provides more time for flood warning and emergency responses. The latest numerical weather forecast model could provide 1-15-day quantitative precipitation forecasting products in grid format, and by coupling this product with a distributed hydrological model could produce long lead time watershed flood forecasting products. This paper studied the feasibility of coupling the Liuxihe model with the Weather Research and Forecasting quantitative precipitation forecast (WRF QPF) for large watershed flood forecasting in southern China. The QPF of WRF products has three lead times, including 24, 48 and 72 h, with the grid resolution being 20 km  × 20 km. The Liuxihe model is set up with freely downloaded terrain property; the model parameters were previously optimized with rain gauge observed precipitation, and re-optimized with the WRF QPF. Results show that the WRF QPF has bias with the rain gauge precipitation, and a post-processing method is proposed to post-process the WRF QPF products, which improves the flood forecasting capability. With model parameter re-optimization, the model's performance improves also. This suggests that the model parameters be optimized with QPF, not the rain gauge precipitation. With the increasing of lead time, the accuracy of the WRF QPF decreases, as does the flood forecasting capability. Flood forecasting products produced by coupling the Liuxihe model with the WRF QPF provide a good reference for large watershed flood warning due to its long lead time and rational results.

Modelling regional climate change and urban planning scenarios and their impacts on the urban environment in two cities with WRF-ACASA

Science.gov (United States)

Falk, M.; Pyles, R. D.; Marras, S.; Spano, D.; Paw U, K. T.

2011-12-01

The number of urban metabolism studies has increased in recent years, due to the important impact that energy, water and carbon exchange over urban areas have on climate change. Urban modeling is therefore crucial in the future design and management of cities. This study presents the ACASA model coupled to the Weather Research and Forecasting (WRF-ARW) mesoscale model to simulate urban fluxes at a horizontal resolution of 200 meters for urban areas of roughly 100 km^2. As part of the European Project "BRIDGE", these regional simulations were used in combination with remotely sensed data to provide constraints on the land surface types and the exchange of carbon and energy fluxes from urban centers. Surface-atmosphere exchanges of mass and energy were simulated using the Advanced Canopy Atmosphere Soil Algorithm (ACASA). ACASA is a multi-layer high-order closure model, recently modified to work over natural, agricultural as well as urban environments. In particular, improvements were made to account for the anthropogenic contribution to heat and carbon production. For two cities four climate change and four urban planning scenarios were simulated: The climate change scenarios include a base scenario (Sc0: 2008 Commit in IPCC), a medium emission scenario (Sc1: IPCC A2), a worst case emission scenario (Sce2: IPCC A1F1) and finally a best case emission scenario (Sce3: IPCC B1). The urban planning scenarios include different development scenarios such as smart growth. The two cities are a high latitude city, Helsinki (Finland) and an historic city, Florence (Italy). Helsinki is characterized by recent, rapid urbanization that requires a substantial amount of energy for heating, while Florence is representative of cities in lower latitudes, with substantial cultural heritage and a comparatively constant architectural footprint over time. In general, simulated fluxes matched the point observations well and showed consistent improvement in the energy partitioning over

Application of WRF - SWAT OpenMI 2.0 based models integration for real time hydrological modelling and forecasting

Science.gov (United States)

Bugaets, Andrey; Gonchukov, Leonid

2014-05-01

Intake of deterministic distributed hydrological models into operational water management requires intensive collection and inputting of spatial distributed climatic information in a timely manner that is both time consuming and laborious. The lead time of the data pre-processing stage could be essentially reduced by coupling of hydrological and numerical weather prediction models. This is especially important for the regions such as the South of the Russian Far East where its geographical position combined with a monsoon climate affected by typhoons and extreme heavy rains caused rapid rising of the mountain rivers water level and led to the flash flooding and enormous damage. The objective of this study is development of end-to-end workflow that executes, in a loosely coupled mode, an integrated modeling system comprised of Weather Research and Forecast (WRF) atmospheric model and Soil and Water Assessment Tool (SWAT 2012) hydrological model using OpenMI 2.0 and web-service technologies. Migration SWAT into OpenMI compliant involves reorganization of the model into a separate initialization, performing timestep and finalization functions that can be accessed from outside. To save SWAT normal behavior, the source code was separated from OpenMI-specific implementation into the static library. Modified code was assembled into dynamic library and wrapped into C# class implemented the OpenMI ILinkableComponent interface. Development of WRF OpenMI-compliant component based on the idea of the wrapping web-service clients into a linkable component and seamlessly access to output netCDF files without actual models connection. The weather state variables (precipitation, wind, solar radiation, air temperature and relative humidity) are processed by automatic input selection algorithm to single out the most relevant values used by SWAT model to yield climatic data at the subbasin scale. Spatial interpolation between the WRF regular grid and SWAT subbasins centroid (which are

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-07-01

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

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.

Megacity impacts on regional ozone formation: observations and WRF-Chem modeling for the MIRAGE-Shanghai field campaign

Directory of Open Access Journals (Sweden)

X. Tie

2013-06-01

Full Text Available The MIRAGE-Shanghai experiment was designed to characterize the factors controlling regional air pollution near a Chinese megacity (Shanghai and was conducted during September 2009. This paper provides information on the measurements conducted for this study. In order to have some deep analysis of the measurements, a regional chemical/dynamical model (version 3 of Weather Research and Forecasting Chemical model – WRF-Chemv3 is applied for this study. The model results are intensively compared with the measurements to evaluate the model capability for calculating air pollutants in the Shanghai region, especially the chemical species related to ozone formation. The results show that the model is able to calculate the general distributions (the level and the variability of air pollutants in the Shanghai region, and the differences between the model calculation and the measurement are mostly smaller than 30%, except the calculations of HONO (nitrous acid at PD (Pudong and CO (carbon monoxide at DT (Dongtan. The main scientific focus is the study of ozone chemical formation not only in the urban area, but also on a regional scale of the surrounding area of Shanghai. The results show that during the experiment period, the ozone photochemical formation was strongly under the VOC (volatile organic compound-limited condition in the urban area of Shanghai. Moreover, the VOC-limited condition occurred not only in the city, but also in the larger regional area. There was a continuous enhancement of ozone concentrations in the downwind of the megacity of Shanghai, resulting in a significant enhancement of ozone concentrations in a very large regional area in the surrounding region of Shanghai. The sensitivity study of the model suggests that there is a threshold value for switching from VOC-limited condition to NOx (nitric oxide and nitrogen dioxide-limited condition. The threshold value is strongly dependent on the emission ratio of NOx / VOCs. When the

Impact of Asian Aerosols on Precipitation Over California: An Observational and Model Based Approach

Science.gov (United States)

Naeger, Aaron R.; Molthan, Andrew L.; Zavodsky, Bradley T.; Creamean, Jessie M.

2015-01-01

Dust and pollution emissions from Asia are often transported across the Pacific Ocean to over the western United States. Therefore, it is essential to fully understand the impact of these aerosols on clouds and precipitation forming over the eastern Pacific and western United States, especially during atmospheric river events that account for up to half of California's annual precipitation and can lead to widespread flooding. In order for numerical modeling simulations to accurately represent the present and future regional climate of the western United States, we must account for the aerosol-cloud-precipitation interactions associated with Asian dust and pollution aerosols. Therefore, we have constructed a detailed study utilizing multi-sensor satellite observations, NOAA-led field campaign measurements, and targeted numerical modeling studies where Asian aerosols interacted with cloud and precipitation processes over the western United States. In particular, we utilize aerosol optical depth retrievals from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS), NOAA Geostationary Operational Environmental Satellite (GOES-11), and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT) to effectively detect and monitor the trans-Pacific transport of Asian dust and pollution. The aerosol optical depth (AOD) retrievals are used in assimilating the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in order to provide the model with an accurate representation of the aerosol spatial distribution across the Pacific. We conduct WRF-Chem model simulations of several cold-season atmospheric river events that interacted with Asian aerosols and brought significant precipitation over California during February-March 2011 when the NOAA CalWater field campaign was ongoing. The CalWater field campaign consisted of aircraft and surface measurements of aerosol and precipitation processes that help extensively validate our WRF-Chem

WRF Simulation over the Eastern Africa by use of Land Surface Initialization

Science.gov (United States)

Sakwa, V. N.; Case, J.; Limaye, A. S.; Zavodsky, B.; Kabuchanga, E. S.; Mungai, J.

2014-12-01

The East Africa region experiences severe weather events associated with hazards of varying magnitude. It receives heavy precipitation which leads to wide spread flooding and lack of sufficient rainfall in some parts results into drought. Cases of flooding and drought are two key forecasting challenges for the Kenya Meteorological Service (KMS). The source of heat and moisture depends on the state of the land surface which interacts with the boundary layer of the atmosphere to produce excessive precipitation or lack of it that leads to severe drought. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Improved modeling capabilities within the region have the potential to enhance forecast guidance in support of daily operations and high-impact weather over East Africa. KMS currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Non-hydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over Eastern Africa.SPoRT and SERVIR provide land surface initialization datasets and model verification tool. The NASA Land Information System (LIS) provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Model verification is done using the Model Evaluation Tools (MET) package, in order

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.

Water resources management using the WRF-Hydro modelling system: Case-study of the Tono dam in West Africa

Directory of Open Access Journals (Sweden)

E. Naabil

2017-08-01

Full Text Available Water resources are a major source of economic development for most West African (WA countries. There is, however inadequate information on these resources for the purposes of planning, decision-making and management. This paper explores the potential for using a state of the art hydrological model (WRF-Hydro in a fully coupled (i.e. land surface hydrology-atmosphere mode to assess these water resources, particularly the Tono basin in Ghana. The WRF-Hydro model is an enhanced version of the Weather Research and Forecasting model (WRF which allows simulating river discharge. A 2-domain configuration is chosen: an outer domain at 25 km horizontal resolution encompassing the West African Region and an inner domain at 5 km horizontal resolution centered on the Tono basin. The infiltration partition parameter and Manning’s roughness parameter were calibrated to fit the WRF-Hydro simulated discharge with the observed data. The simulations were done from 1999 to 2003, using 1999 as a spin-up period. The results were compared with TRMM precipitation, CRU temperature and available observed hydrological data. The WRF-Hydro model captured the attributes of the “observed” streamflow estimate; with Nash-Sutcliff efficiency (NSE of 0.78 and Pearson’s correlation of 0.89. Further validation of model results is based on using the output from the WRF-Hydro model as input into a water balance model to simulate the dam levels. WRF-Hydro has shown the potential for use in water resource planning (i.e. with respect to streamflow and dam level estimation. However, the model requires further improvement with respect to calibration of model parameters (e.g. baseflow and saturated hydraulic conductivity considering the effect of the accumulation of model bias in dam level estimation.

NASA SPoRT Modeling and Data Assimilation Research and Transition Activities Using WRF, LIS and GSI

Science.gov (United States)

Case, Jonathan L.; Blankenship, Clay B.; Zavodsky, Bradley T.; Srikishen, Jayanthi; Berndt, Emily B.

2014-01-01

weather research and forecasting ===== The NASA Short-term Prediction Research and Transition (SPoRT) program has numerous modeling and data assimilation (DA) activities in which the WRF model is a key component. SPoRT generates realtime, research satellite products from the MODIS and VIIRS instruments, making the data available to NOAA/NWS partners running the WRF/EMS, including: (1) 2-km northwestern-hemispheric SST composite, (2) daily, MODIS green vegetation fraction (GVF) over CONUS, and (3) NASA Land Information System (LIS) runs of the Noah LSM over the southeastern CONUS. Each of these datasets have been utilized by specific SPoRT partners in local EMS model runs, with select offices evaluating the impacts using a set of automated scripts developed by SPoRT that manage data acquisition and run the NCAR Model Evaluation Tools verification package. SPoRT is engaged in DA research with the Gridpoint Statistical Interpolation (GSI) and Ensemble Kalman Filter in LIS for soil moisture DA. Ongoing DA projects using GSI include comparing the impacts of assimilating Atmospheric Infrared Sounder (AIRS) radiances versus retrieved profiles, and an analysis of extra-tropical cyclones with intense non-convective winds. As part of its Early Adopter activities for the NASA Soil Moisture Active Passive (SMAP) mission, SPoRT is conducting bias correction and soil moisture DA within LIS to improve simulations using the NASA Unified-WRF (NU-WRF) for both the European Space Agency's Soil Moisture Ocean Salinity and upcoming SMAP mission data. SPoRT has also incorporated real-time global GVF data into LIS and WRF from the VIIRS product being developed by NOAA/NESDIS. This poster will highlight the research and transition activities SPoRT conducts using WRF, NU-WRF, EMS, LIS, and GSI.

GPU-Accelerated Stony-Brook University 5-class Microphysics Scheme in WRF

Science.gov (United States)

Mielikainen, J.; Huang, B.; Huang, A.

2011-12-01

The Weather Research and Forecasting (WRF) model is a next-generation mesoscale numerical weather prediction system. Microphysics plays an important role in weather and climate prediction. Several bulk water microphysics schemes are available within the WRF, with different numbers of simulated hydrometeor classes and methods for estimating their size fall speeds, distributions and densities. Stony-Brook University scheme (SBU-YLIN) is a 5-class scheme with riming intensity predicted to account for mixed-phase processes. In the past few years, co-processing on Graphics Processing Units (GPUs) has been a disruptive technology in High Performance Computing (HPC). GPUs use the ever increasing transistor count for adding more processor cores. Therefore, GPUs are well suited for massively data parallel processing with high floating point arithmetic intensity. Thus, it is imperative to update legacy scientific applications to take advantage of this unprecedented increase in computing power. CUDA is an extension to the C programming language offering programming GPU's directly. It is designed so that its constructs allow for natural expression of data-level parallelism. A CUDA program is organized into two parts: a serial program running on the CPU and a CUDA kernel running on the GPU. The CUDA code consists of three computational phases: transmission of data into the global memory of the GPU, execution of the CUDA kernel, and transmission of results from the GPU into the memory of CPU. CUDA takes a bottom-up point of view of parallelism is which thread is an atomic unit of parallelism. Individual threads are part of groups called warps, within which every thread executes exactly the same sequence of instructions. To test SBU-YLIN, we used a CONtinental United States (CONUS) benchmark data set for 12 km resolution domain for October 24, 2001. A WRF domain is a geographic region of interest discretized into a 2-dimensional grid parallel to the ground. Each grid point has

Coupling of Large Eddy Simulations with Meteorological Models to simulate Methane Leaks from Natural Gas Storage Facilities

Science.gov (United States)

Prasad, K.

2017-12-01

Atmospheric transport is usually performed with weather models, e.g., the Weather Research and Forecasting (WRF) model that employs a parameterized turbulence model and does not resolve the fine scale dynamics generated by the flow around buildings and features comprising a large city. The NIST Fire Dynamics Simulator (FDS) is a computational fluid dynamics model that utilizes large eddy simulation methods to model flow around buildings at length scales much smaller than is practical with models like WRF. FDS has the potential to evaluate the impact of complex topography on near-field dispersion and mixing that is difficult to simulate with a mesoscale atmospheric model. A methodology has been developed to couple the FDS model with WRF mesoscale transport models. The coupling is based on nudging the FDS flow field towards that computed by WRF, and is currently limited to one way coupling performed in an off-line mode. This approach allows the FDS model to operate as a sub-grid scale model with in a WRF simulation. To test and validate the coupled FDS - WRF model, the methane leak from the Aliso Canyon underground storage facility was simulated. Large eddy simulations were performed over the complex topography of various natural gas storage facilities including Aliso Canyon, Honor Rancho and MacDonald Island at 10 m horizontal and vertical resolution. The goal of these simulations included improving and validating transport models as well as testing leak hypotheses. Forward simulation results were compared with aircraft and tower based in-situ measurements as well as methane plumes observed using the NASA Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) and the next generation instrument AVIRIS-NG. Comparison of simulation results with measurement data demonstrate the capability of the coupled FDS-WRF models to accurately simulate the transport and dispersion of methane plumes over urban domains. Simulated integrated methane enhancements will be presented and

A Comparison of HWRF, ARW and NMM Models in Hurricane Katrina (2005 Simulation

Directory of Open Access Journals (Sweden)

Anjaneyulu Yerramilli

2011-06-01

Full Text Available The life cycle of Hurricane Katrina (2005 was simulated using three different modeling systems of Weather Research and Forecasting (WRF mesoscale model. These are, HWRF (Hurricane WRF designed specifically for hurricane studies and WRF model with two different dynamic cores as the Advanced Research WRF (ARW model and the Non-hydrostatic Mesoscale Model (NMM. The WRF model was developed and sourced from National Center for Atmospheric Research (NCAR, incorporating the advances in atmospheric simulation system suitable for a broad range of applications. The HWRF modeling system was developed at the National Centers for Environmental Prediction (NCEP based on the NMM dynamic core and the physical parameterization schemes specially designed for tropics. A case study of Hurricane Katrina was chosen as it is one of the intense hurricanes that caused severe destruction along the Gulf Coast from central Florida to Texas. ARW, NMM and HWRF models were designed to have two-way interactive nested domains with 27 and 9 km resolutions. The three different models used in this study were integrated for three days starting from 0000 UTC of 27 August 2005 to capture the landfall of hurricane Katrina on 29 August. The initial and time varying lateral boundary conditions were taken from NCEP global FNL (final analysis data available at 1 degree resolution for ARW and NMM models and from NCEP GFS data at 0.5 degree resolution for HWRF model. The results show that the models simulated the intensification of Hurricane Katrina and the landfall on 29 August 2005 agreeing with the observations. Results from these experiments highlight the superior performance of HWRF model over ARW and NMM models in predicting the track and intensification of Hurricane Katrina.

Assessment of the turbulence parameterization schemes for the Martian mesoscale simulations

Science.gov (United States)

Temel, Orkun; Karatekin, Ozgur; Van Beeck, Jeroen

2016-07-01

Turbulent transport within the Martian atmospheric boundary layer (ABL) is one of the most important physical processes in the Martian atmosphere due to the very thin structure of Martian atmosphere and super-adiabatic conditions during the diurnal cycle [1]. The realistic modeling of turbulent fluxes within the Martian ABL has a crucial effect on the many physical phenomena including dust devils [2], methane dispersion [3] and nocturnal jets [4]. Moreover, the surface heat and mass fluxes, which are related with the mass transport within the sub-surface of Mars, are being computed by the turbulence parameterization schemes. Therefore, in addition to the possible applications within the Martian boundary layer, parameterization of turbulence has an important effect on the biological research on Mars including the investigation of water cycle or sub-surface modeling. In terms of the turbulence modeling approaches being employed for the Martian ABL, the "planetary boundary layer (PBL) schemes" have been applied not only for the global circulation modeling but also for the mesoscale simulations [5]. The PBL schemes being used for Mars are the variants of the PBL schemes which had been developed for the Earth and these schemes are either based on the empirical determination of turbulent fluxes [6] or based on solving a one dimensional turbulent kinetic energy equation [7]. Even though, the Large Eddy Simulation techniques had also been applied with the regional models for Mars, it must be noted that these advanced models also use the features of these traditional PBL schemes for sub-grid modeling [8]. Therefore, assessment of these PBL schemes is vital for a better understanding the atmospheric processes of Mars. In this framework, this present study is devoted to the validation of different turbulence modeling approaches for the Martian ABL in comparison to Viking Lander [9] and MSL [10] datasets. The GCM/Mesoscale code being used is the PlanetWRF, the extended version

Ensemble using different Planetary Boundary Layer schemes in WRF model for wind speed and direction prediction over Apulia region

Science.gov (United States)

Tateo, Andrea; Marcello Miglietta, Mario; Fedele, Francesca; Menegotto, Micaela; Monaco, Alfonso; Bellotti, Roberto

2017-04-01

The Weather Research and Forecasting mesoscale model (WRF) was used to simulate hourly 10 m wind speed and direction over the city of Taranto, Apulia region (south-eastern Italy). This area is characterized by a large industrial complex including the largest European steel plant and is subject to a Regional Air Quality Recovery Plan. This plan constrains industries in the area to reduce by 10 % the mean daily emissions by diffuse and point sources during specific meteorological conditions named wind days. According to the Recovery Plan, the Regional Environmental Agency ARPA-PUGLIA is responsible for forecasting these specific meteorological conditions with 72 h in advance and possibly issue the early warning. In particular, an accurate wind simulation is required. Unfortunately, numerical weather prediction models suffer from errors, especially for what concerns near-surface fields. These errors depend primarily on uncertainties in the initial and boundary conditions provided by global models and secondly on the model formulation, in particular the physical parametrizations used to represent processes such as turbulence, radiation exchange, cumulus and microphysics. In our work, we tried to compensate for the latter limitation by using different Planetary Boundary Layer (PBL) parameterization schemes. Five combinations of PBL and Surface Layer (SL) schemes were considered. Simulations are implemented in a real-time configuration since our intention is to analyze the same configuration implemented by ARPA-PUGLIA for operational runs; the validation is focused over a time range extending from 49 to 72 h with hourly time resolution. The assessment of the performance was computed by comparing the WRF model output with ground data measured at a weather monitoring station in Taranto, near the steel plant. After the analysis of the simulations performed with different PBL schemes, both simple (e.g. average) and more complex post-processing methods (e.g. weighted average

Monitoring Air Quality over China: Evaluation of the modeling system of the PANDA project

Science.gov (United States)

Bouarar, Idir; Katinka Petersen, Anna; Brasseur, Guy; Granier, Claire; Xie, Ying; Wang, Xuemei; Fan, Qi; Wang, Lili

2015-04-01

Air pollution has become a pressing problem in Asia and specifically in China due to rapid increase in anthropogenic emissions related to growth of China's economic activity and increasing demand for energy in the past decade. Observed levels of particulate matter and ozone regularly exceed World Health Organization (WHO) air quality guidelines in many parts of the country leading to increased risk of respiratory illnesses and other health problems. The EU-funded project PANDA aims to establish a team of European and Chinese scientists to monitor air pollution over China and elaborate air quality indicators in support of European and Chinese policies. PANDA combines state-of-the-art air pollution modeling with space and surface observations of chemical species to improve methods for monitoring air quality. The modeling system of the PANDA project follows a downscaling approach: global models such as MOZART and MACC system provide initial and boundary conditions to regional WRF-Chem and EMEP simulations over East Asia. WRF-Chem simulations at higher resolution (e.g. 20km) are then performed over a smaller domain covering East China and initial and boundary conditions from this run are used to perform simulations at a finer resolution (e.g. 5km) over specific megacities like Shanghai. Here we present results of model simulations for January and July 2010 performed during the first year of the project. We show an intercomparison of the global (MACC, EMEP) and regional (WRF-Chem) simulations and a comprehensive evaluation with satellite measurements (NO2, CO) and in-situ data (O3, CO, NOx, PM10 and PM2.5) at several surface stations. Using the WRF-Chem model, we demonstrate that model performance is influenced not only by the resolution (e.g. 60km, 20km) but also the emission inventories used (MACCity, HTAPv2), their resolution and diurnal variation, and the choice of initial and boundary conditions (e.g. MOZART, MACC analysis).

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)

Wind waves modelling on the water body with coupled WRF and WAVEWATCH III models

Science.gov (United States)

Kuznetsova, Alexandra; Troitskaya, Yuliya; Kandaurov, Alexander; Baydakov, Georgy; Vdovin, Maxim; Papko, Vladislav; Sergeev, Daniil

2015-04-01

Simulation of ocean and sea waves is an accepted instrument for the improvement of the weather forecasts. Wave modelling, coupled models modelling is applied to open seas [1] and is less developed for moderate and small inland water reservoirs and lakes, though being of considerable interest for inland navigation. Our goal is to tune the WAVEWATCH III model to the conditions of the inland reservoir and to carry out the simulations of surface wind waves with coupled WRF (Weather Research and Forecasting) and WAVEWATCH III models. Gorky Reservoir, an artificial lake in the central part of the Volga River formed by a hydroelectric dam, was considered as an example of inland reservoir. Comparing to [2] where moderate constant winds (u10 is up to 9 m/s) of different directions blowing steadily all over the surface of the reservoir were considered, here we apply atmospheric model WRF to get wind input to WAVEWATCH III. WRF computations were held on the Yellowstone supercomputer for 4 nested domains with minimum scale of 1 km. WAVEWATCH III model was tuned for the conditions of the Gorky Reservoir. Satellite topographic data on altitudes ranged from 56,6° N to 57,5° N and from 42.9° E to 43.5° E with increments 0,00833 ° in both directions was used. 31 frequencies ranged from 0,2 Hz to 4 Hz and 30 directions were considered. The minimal significant wave height was changed to the lower one. The waves in the model were developing from some initial seeding spectral distribution (Gaussian in frequency and space, cosine in direction). The range of the observed significant wave height in the numerical experiment was from less than 1 cm up to 30 cm. The field experiments were carried out in the south part of the Gorky reservoir from the boat [2, 3]. 1-D spectra of the field experiment were compared with those obtained in the numerical experiments with different parameterizations of flux provided in WAVEWATCH III both with constant wind input and WRF wind input. For all the

Land use and topography influence in a complex terrain area: A high resolution mesoscale modelling study over the Eastern Pyrenees using the WRF model

Science.gov (United States)

Jiménez-Esteve, B.; Udina, M.; Soler, M. R.; Pepin, N.; Miró, J. R.

2018-04-01

Different types of land use (LU) have different physical properties which can change local energy balance and hence vertical fluxes of moisture, heat and momentum. This in turn leads to changes in near-surface temperature and moisture fields. Simulating atmospheric flow over complex terrain requires accurate local-scale energy balance and therefore model grid spacing must be sufficient to represent both topography and land-use. In this study we use both the Corine Land Cover (CLC) and United States Geological Survey (USGS) land use databases for use with the Weather Research and Forecasting (WRF) model and evaluate the importance of both land-use classification and horizontal resolution in contributing to successful modelling of surface temperatures and humidities observed from a network of 39 sensors over a 9 day period in summer 2013. We examine case studies of the effects of thermal inertia and soil moisture availability at individual locations. The scale at which the LU classification is observed influences the success of the model in reproducing observed patterns of temperature and moisture. Statistical validation of model output demonstrates model sensitivity to both the choice of LU database used and the horizontal resolution. In general, results show that on average, by a) using CLC instead of USGS and/or b) increasing horizontal resolution, model performance is improved. We also show that the sensitivity to these changes in the model performance shows a daily cycle.

Intercomparison of Streamflow Simulations between WRF-Hydro and Hydrology Laboratory-Research Distributed Hydrologic Model Frameworks

Science.gov (United States)

KIM, J.; Smith, M. B.; Koren, V.; Salas, F.; Cui, Z.; Johnson, D.

2017-12-01

The National Oceanic and Atmospheric Administration (NOAA)-National Weather Service (NWS) developed the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) framework as an initial step towards spatially distributed modeling at River Forecast Centers (RFCs). Recently, the NOAA/NWS worked with the National Center for Atmospheric Research (NCAR) to implement the National Water Model (NWM) for nationally-consistent water resources prediction. The NWM is based on the WRF-Hydro framework and is run at a 1km spatial resolution and 1-hour time step over the contiguous United States (CONUS) and contributing areas in Canada and Mexico. In this study, we compare streamflow simulations from HL-RDHM and WRF-Hydro to observations from 279 USGS stations. For streamflow simulations, HL-RDHM is run on 4km grids with the temporal resolution of 1 hour for a 5-year period (Water Years 2008-2012), using a priori parameters provided by NOAA-NWS. The WRF-Hydro streamflow simulations for the same time period are extracted from NCAR's 23 retrospective run of the NWM (version 1.0) over CONUS based on 1km grids. We choose 279 USGS stations which are relatively less affected by dams or reservoirs, in the domains of six different RFCs. We use the daily average values of simulations and observations for the convenience of comparison. The main purpose of this research is to evaluate how HL-RDHM and WRF-Hydro perform at USGS gauge stations. We compare daily time-series of observations and both simulations, and calculate the error values using a variety of error functions. Using these plots and error values, we evaluate the performances of HL-RDHM and WRF-Hydro models. Our results show a mix of model performance across geographic regions.

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

Development of a source oriented version of the WRF/Chem model and its application to the California regional PM10 / PM2.5 air quality study

Directory of Open Access Journals (Sweden)

H. Zhang

2014-01-01

Full Text Available A source-oriented version of the Weather Research and Forecasting model with chemistry (SOWC, hereinafter was developed. SOWC separately tracks primary particles with different hygroscopic properties rather than instantaneously combining them into an internal mixture. This approach avoids artificially mixing light absorbing black + brown carbon particles with materials such as sulfate that would encourage the formation of additional coatings. Source-oriented particles undergo coagulation and gas-particle conversion, but these processes are considered in a dynamic framework that realistically "ages" primary particles over hours and days in the atmosphere. SOWC more realistically predicts radiative feedbacks from anthropogenic aerosols compared to models that make internal mixing or other artificial mixing assumptions. A three-week stagnation episode (15 December 2000 to 6 January 2001 in the San Joaquin Valley (SJV during the California Regional PM10 / PM2.5 Air Quality Study (CRPAQS was chosen for the initial application of the new modeling system. Primary particles emitted from diesel engines, wood smoke, high-sulfur fuel combustion, food cooking, and other anthropogenic sources were tracked separately throughout the simulation as they aged in the atmosphere. Differences were identified between predictions from the source oriented vs. the internally mixed representation of particles with meteorological feedbacks in WRF/Chem for a number of meteorological parameters: aerosol extinction coefficients, downward shortwave flux, planetary boundary layer depth, and primary and secondary particulate matter concentrations. Comparisons with observations show that SOWC predicts particle scattering coefficients more accurately than the internally mixed model. Downward shortwave radiation predicted by SOWC is enhanced by ~1% at ground level chiefly because diesel engine particles in the source-oriented mixture are not artificially coated with material that

Adaptation of Mesoscale Weather Models to Local Forecasting

Science.gov (United States)

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

2003-01-01

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

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...

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

DEFF Research Database (Denmark)

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

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

Examining Interior Grid Nudging Techniques Using Two-Way Nesting in the WRF Model for Regional Climate Modeling

Science.gov (United States)

This study evaluates interior nudging techniques using the Weather Research and Forecasting (WRF) model for regional climate modeling over the conterminous United States (CONUS) using a two-way nested configuration. NCEP–Department of Energy Atmospheric Model Intercomparison Pro...

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.

Comparison of Two Grid Refinement Approaches for High Resolution Regional Climate Modeling: MPAS vs WRF

Science.gov (United States)

Leung, L.; Hagos, S. M.; Rauscher, S.; Ringler, T.

2012-12-01

This study compares two grid refinement approaches using global variable resolution model and nesting for high-resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales (MPAS), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context with a focus on the spatial and temporal characteristics of tropical precipitation simulated by the models using the same physics package from the Community Atmosphere Model (CAM4). For MPAS, simulations have been performed with a quasi-uniform resolution global domain at coarse (1 degree) and high (0.25 degree) resolution, and a variable resolution domain with a high-resolution region at 0.25 degree configured inside a coarse resolution global domain at 1 degree resolution. Similarly, WRF has been configured to run on a coarse (1 degree) and high (0.25 degree) resolution tropical channel domain as well as a nested domain with a high-resolution region at 0.25 degree nested two-way inside the coarse resolution (1 degree) tropical channel. The variable resolution or nested simulations are compared against the high-resolution simulations that serve as virtual reality. Both MPAS and WRF simulate 20-day Kelvin waves propagating through the high-resolution domains fairly unaffected by the change in resolution. In addition, both models respond to increased resolution with enhanced precipitation. Grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. However, there are important differences between the anomalous patterns in MPAS and WRF due to differences in the grid refinement approaches and sensitivity of model physics to grid resolution. This study highlights the need for "scale aware" parameterizations in variable resolution and nested regional models.

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

Indian Academy of Sciences (India)

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

Atmospheric stability and turbulence fluxes at Horns Rev—an intercomparison of sonic, bulk and WRF model data

DEFF Research Database (Denmark)

Pena Diaz, Alfredo; Hahmann, Andrea N.

2012-01-01

anemometer at 15 m height and potential temperature differences between the water and the air above. Surface flux estimations from the advanced weather research and forecast (WRF) model are also validated against the sonic and bulk data. The correlation between the sonic and bulk estimates of friction...... to the surface, not only from a systematic bulk and WRF under‐prediction of the friction velocity when compared with the sonic value but also because of the lower magnitude of the sonic heat flux compared with that from the WRF simulations. Although they are not measured but parameterized or estimated, the bulk......–WRF comparisons of friction velocity and 10 m wind speed show good agreement. It is also shown that on a long‐term basis, the WRF and bulk estimates of stability are nearly equal and that a correction towards a slightly stable atmospheric condition has to be applied to the long‐term wind profile at Horns Rev...

Wind Farm parametrization in the mesoscale model WRF

DEFF Research Database (Denmark)

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

2012-01-01

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

Quantitative precipitation estimation based on high-resolution numerical weather prediction and data assimilation with WRF – a performance test

Directory of Open Access Journals (Sweden)

Hans-Stefan Bauer

2015-04-01

Full Text Available Quantitative precipitation estimation and forecasting (QPE and QPF are among the most challenging tasks in atmospheric sciences. In this work, QPE based on numerical modelling and data assimilation is investigated. Key components are the Weather Research and Forecasting (WRF model in combination with its 3D variational assimilation scheme, applied on the convection-permitting scale with sophisticated model physics over central Europe. The system is operated in a 1-hour rapid update cycle and processes a large set of in situ observations, data from French radar systems, the European GPS network and satellite sensors. Additionally, a free forecast driven by the ECMWF operational analysis is included as a reference run representing current operational precipitation forecasting. The verification is done both qualitatively and quantitatively by comparisons of reflectivity, accumulated precipitation fields and derived verification scores for a complex synoptic situation that developed on 26 and 27 September 2012. The investigation shows that even the downscaling from ECMWF represents the synoptic situation reasonably well. However, significant improvements are seen in the results of the WRF QPE setup, especially when the French radar data are assimilated. The frontal structure is more defined and the timing of the frontal movement is improved compared with observations. Even mesoscale band-like precipitation structures on the rear side of the cold front are reproduced, as seen by radar. The improvement in performance is also confirmed by a quantitative comparison of the 24-hourly accumulated precipitation over Germany. The mean correlation of the model simulations with observations improved from 0.2 in the downscaling experiment and 0.29 in the assimilation experiment without radar data to 0.56 in the WRF QPE experiment including the assimilation of French radar data.

Investigating fire emissions and smoke transport during the Summer of 2013 using an operational smoke modeling system and chemical transport model

Science.gov (United States)

ONeill, S. M.; Chung, S. H.; Wiedinmyer, C.; Larkin, N. K.; Martinez, M. E.; Solomon, R. C.; Rorig, M.

2014-12-01

Emissions from fires in the Western US are substantial and can impact air quality and regional climate. Many methods exist that estimate the particulate and gaseous emissions from fires, including those run operationally for use with chemical forecast models. The US Forest Service Smartfire2/BlueSky modeling framework uses satellite data and reported information about fire perimeters to estimate emissions of pollutants to the atmosphere. The emission estimates are used as inputs to dispersion models, such as HYSPLIT, and chemical transport models, such as CMAQ and WRF-Chem, to assess the chemical and physical impacts of fires on the atmosphere. Here we investigate the use of Smartfire2/BlueSky and WRF-Chem to simulate emissions from the 2013 fire summer fire season, with special focus on the Rim Fire in northern California. The 2013 Rim Fire ignited on August 17 and eventually burned more than 250,000 total acres before being contained on October 24. Large smoke plumes and pyro-convection events were observed. In this study, the Smartfire2/BlueSky operational emission estimates are compared to other estimation methods, such as the Fire INventory from NCAR (FINN) and other global databases to quantify variations in emission estimation methods for this wildfire event. The impact of the emissions on downwind chemical composition is investigated with the coupled meteorology-chemistry WRF-Chem model. The inclusion of aerosol-cloud and aerosol-radiation interactions in the model framework enables the evaluation of the downwind impacts of the fire plume. The emissions and modeled chemistry can also be evaluated with data collected from the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) aircraft field campaign, which intersected the fire plume.

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

Science.gov (United States)

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

2012-12-01

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

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 ...

for WRF Non-hydrostatic Mesoscale Model

Indian Academy of Sciences (India)

8

School of Earth Ocean and Climate Sciences,. Indian Institute of Technology, Bhubaneswar. Toshali Bhavan, Satya Nagar, Bhubaneswar-751007. INDIA .... vertically propagating sound waves, Adams-Bashforth scheme for horizontal advection, ... (refractivity & radial velocity), GPS (refractivity & Total Zenith delay) data.

Exploiting PubChem for Virtual Screening.

Science.gov (United States)

Xie, Xiang-Qun

2010-12-01

IMPORTANCE OF THE FIELD: PubChem is a public molecular information repository, a scientific showcase of the NIH Roadmap Initiative. The PubChem database holds over 27 million records of unique chemical structures of compounds (CID) derived from nearly 70 million substance depositions (SID), and contains more than 449,000 bioassay records with over thousands of in vitro biochemical and cell-based screening bioassays established, with targeting more than 7000 proteins and genes linking to over 1.8 million of substances. AREAS COVERED IN THIS REVIEW: This review builds on recent PubChem-related computational chemistry research reported by other authors while providing readers with an overview of the PubChem database, focusing on its increasing role in cheminformatics, virtual screening and toxicity prediction modeling. WHAT THE READER WILL GAIN: These publicly available datasets in PubChem provide great opportunities for scientists to perform cheminformatics and virtual screening research for computer-aided drug design. However, the high volume and complexity of the datasets, in particular the bioassay-associated false positives/negatives and highly imbalanced datasets in PubChem, also creates major challenges. Several approaches regarding the modeling of PubChem datasets and development of virtual screening models for bioactivity and toxicity predictions are also reviewed. TAKE HOME MESSAGE: Novel data-mining cheminformatics tools and virtual screening algorithms are being developed and used to retrieve, annotate and analyze the large-scale and highly complex PubChem biological screening data for drug design.

PENGGUNAAN SKEMA KONVEKTIF MODEL CUACA WRF (BETTS MILLER JANJIC, KAIN FRITSCH DAN GRELL 3D ENSEMBLE (Studi kasus: Surabaya dan Jakarta

Directory of Open Access Journals (Sweden)

Roni Kurniawan

2015-01-01

Full Text Available Pada kajian ini dilakukan evaluasi penggunaan beberapa skema konvektif pada model WRF (Weather Research and Forecasting untuk prediksi cuaca di wilayah Indonesia. Terdapat tiga skema konvektif yang akan dievaluasi yaitu; skema konvektif cumulus BMJ (Betts Miller Janjic, KF (Kain Fritsch, dan GD (Grell 3D ensemble. Data yang digunakan untuk evaluasi adalah data curah hujan per 3 jam dan data angin per 12 jam (level ketinggian; permukaan, 850, 500, 250 mb dari hasil pengolahan model WRF dan observasi selama periode bulan Agustus 2011 dan Februari 2012 di stasiun Juanda-Surabaya dan Cengkareng-Jakarta. Hasil verifikasi dari tiga skema konvektif pada model WRF terhadap data observasi menunjukkan bahwa untuk prakiraan curah hujan, penggunaan skema konvektif BMJ lebih baik dari skema KF dan GD, dan untuk prakiraan arah dan kecepatan angin skema BMJ dan GD relatif lebih baik dari skema KF. Berdasarkan analisis hasil verifikasi yang diperoleh, pemilihan skema konvektif cumulus BMJ cenderung lebih baik dari skema konvektif KF dan GD untuk di aplikasikan pada model WRF.   In this study, the use of some convective schemes on the model WRF (Weather Research and Forecasting for weather prediction in Indonesian region has been evaluated. There are two models evaluated; BMJ cumulus convective scheme (Betts Miller Janjic, KF (Kain Fritsch, and GD (Grell 3D ensemble. The data used in the evaluation are the 3 hourly rainfall data, and the 12 hourly wind data (level height; surface, 850, 500, 250mb from the WRF models and observation processing during August 2011 and February 2012 period at the Juanda-Surabaya and Cengkareng-Jakarta stations. The results of the verification of the three convective schemes in WRF models against observation data indicate that for precipitation forecasts, the application of the BMJ convective scheme is better than the KF and GD schemes, and for direction and wind speed forecast, BMJ and GD schemes is relatively better than the KF

MPAS Atmospheric Boundary Layer Simulation under Selected Stability Conditions: Evaluation Using the SWIFT Datasen

Energy Technology Data Exchange (ETDEWEB)

Kotamarthi, V. Rao [Argonne National Lab. (ANL), Argonne, IL (United States); Feng, Yan [Argonne National Lab. (ANL), Argonne, IL (United States)

2016-10-12

Modeling the transition from mesoscale to microscale is necessary in order to model different processes that affect a wind farm and to develop forecasting tools that operate at the farm scale. The mesoscale-to-microscale coupling (MMC) project is an A2e (Atmosphere-toelectrons) coordinated activity for developing modeling capabilities at the wind farm scale. By moving the focus of the research from a single wind turbine to the collection of turbines that comprise a wind farm, A2e extends the range of spatial and timescales that need representation in a model from tens of meters to hundreds of kilometers and timescales from a few seconds to days (Bokharaie et al. 2016). In the atmosphere, these scales are represented by mesoscale-tomicroscale models. The modeling available at these scales has differed in its representation of various physical processes. The MMC group is responsible for evaluating existing models at these scales and recommending a set of options for coupling the mesoscale and microscale with the best-performing models. The group was organized in 2015 and will explore options for coupling strategies with real-world test problems in fiscal year (FY) 2017. The model of choice for this exercise is WRF (Weather Research Forecasting) for mesoscale and WRF-LES (Large Eddy Simulation) for microscale simulations. The MPAS (Model Prediction Across Scales) variable mesh model that can be continuously refined; it has dynamic core and physics options adopted from WRF, which offer an alternative platform for modeling the mesoscale.

Improved meteorology from an updated WRF/CMAQ modeling system with MODIS vegetation and albedo

Science.gov (United States)

Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Qual...

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.

Characterizing the degree of convective clustering using radar reflectivity and its application to evaluating model simulations

Science.gov (United States)

Cheng, W. Y.; Kim, D.; Rowe, A.; Park, S.

2017-12-01

Despite the impact of mesoscale convective organization on the properties of convection (e.g., mixing between updrafts and environment), parameterizing the degree of convective organization has only recently been attempted in cumulus parameterization schemes (e.g., Unified Convection Scheme UNICON). Additionally, challenges remain in determining the degree of convective organization from observations and in comparing directly with the organization metrics in model simulations. This study addresses the need to objectively quantify the degree of mesoscale convective organization using high quality S-PolKa radar data from the DYNAMO field campaign. One of the most noticeable aspects of mesoscale convective organization in radar data is the degree of convective clustering, which can be characterized by the number and size distribution of convective echoes and the distance between them. We propose a method of defining contiguous convective echoes (CCEs) using precipitating convective echoes identified by a rain type classification algorithm. Two classification algorithms, Steiner et al. (1995) and Powell et al. (2016), are tested and evaluated against high-resolution WRF simulations to determine which method better represents the degree of convective clustering. Our results suggest that the CCEs based on Powell et al.'s algorithm better represent the dynamical properties of the convective updrafts and thus provide the basis of a metric for convective organization. Furthermore, through a comparison with the observational data, the WRF simulations driven by the DYNAMO large-scale forcing, similarly applied to UNICON Single Column Model simulations, will allow us to evaluate the ability of both WRF and UNICON to simulate convective clustering. This evaluation is based on the physical processes that are explicitly represented in WRF and UNICON, including the mechanisms leading to convective clustering, and the feedback to the convective properties.

Multi-scale Modeling of Power Plant Plume Emissions and Comparisons with Observations

Science.gov (United States)

Costigan, K. R.; Lee, S.; Reisner, J.; Dubey, M. K.; Love, S. P.; Henderson, B. G.; Chylek, P.

2011-12-01

The Remote Sensing Verification Project (RSVP) test-bed located in the Four Corners region of Arizona, Utah, Colorado, and New Mexico offers a unique opportunity to develop new approaches for estimating emissions of CO2. Two major power plants located in this area produce very large signals of co-emitted CO2 and NO2 in this rural region. In addition to the Environmental Protection Agency (EPA) maintaining Continuous Emissions Monitoring Systems (CEMS) on each of the power plant stacks, the RSVP program has deployed an array of in-situ and remote sensing instruments, which provide both point and integrated measurements. To aid in the synthesis and interpretation of the measurements, a multi-scale atmospheric modeling approach is implemented, using two atmospheric numerical models: the Weather Research and Forecasting Model with chemistry (WRF-Chem; Grell et al., 2005) and the HIGRAD model (Reisner et al., 2003). The high fidelity HIGRAD model incorporates a multi-phase Lagrangian particle based approach to track individual chemical species of stack plumes at ultra-high resolution, using an adaptive mesh. It is particularly suited to model buoyancy effects and entrainment processes at the edges of the power plant plumes. WRF-Chem is a community model that has been applied to a number of air quality problems and offers several physical and chemical schemes that can be used to model the transport and chemical transformation of the anthropogenic plumes out of the local region. Multiple nested grids employed in this study allow the model to incorporate atmospheric variability ranging from synoptic scales to micro-scales (~200 m), while including locally developed flows influenced by the nearby complex terrain of the San Juan Mountains. The simulated local atmospheric dynamics are provided to force the HIGRAD model, which links mesoscale atmospheric variability to the small-scale simulation of the power plant plumes. We will discuss how these two models are applied and

Assessment of the aerosol optics component of the coupled WRF-CMAQ model using CARES field campaign data and a single column model

Science.gov (United States)

Gan, Chuen Meei; Binkowski, Francis; Pleim, Jonathan; Xing, Jia; Wong, David; Mathur, Rohit; Gilliam, Robert

2015-08-01

The Carbonaceous Aerosols and Radiative Effects Study (CARES), a field campaign held in central California in June 2010, provides a unique opportunity to assess the aerosol optics modeling component of the two-way coupled Weather Research and Forecasting (WRF) - Community Multiscale Air Quality (CMAQ) model. This campaign included comprehensive measurements of aerosol composition and optical properties at two ground sites and aloft from instrumentation on-board two aircraft. A single column model (SCM) was developed to evaluate the accuracy and consistency of the coupled model using both observation and model information. Two cases (June 14 and 24, 2010) are examined in this study. The results show that though the coupled WRF-CMAQ estimates of aerosol extinction were underestimated relative to these measurements, when measured concentrations and characteristics of ambient aerosols were used as input to constrain the SCM calculations, the estimated extinction profiles agreed well with aircraft observations. One of the possible causes of the WRF-CMAQ extinction errors is that the simulated sea-salt (SS) in the accumulation mode in WRF-CMAQ is very low in both cases while the observations indicate a considerable amount of SS. Also, a significant amount of organic carbon (OC) is present in the measurement. However, in the current WRF-CMAQ model all OC is considered to be insoluble whereas most secondary organic aerosol is water soluble. In addition, the model does not consider external mixing and hygroscopic effects of water soluble OC which can impact the extinction calculations. In conclusion, the constrained SCM results indicate that the scattering portion of the aerosol optics calculations is working well, although the absorption calculation could not be effectively evaluated. However, a few factors such as greatly underestimated accumulation mode SS, misrepresentation of water soluble OC, and incomplete mixing state representation in the full coupled model

Sensitivity analysis of ground level ozone in India using WRF-CMAQ models

NARCIS (Netherlands)

Sharma, Sumit; Chatani, Satoru; Mahtta, Richa; Goel, Anju; Kumar, Atul

2016-01-01

Ground level ozone is emerging as a pollutant of concern in India. Limited surface monitoring data reveals that ozone concentrations are well above the prescribed national standards. This study aims to simulate the regional and urban scale ozone concentrations in India using WRF-CMAQ models.

Recent Advances in Modeling of the Atmospheric Boundary Layer and Land Surface in the Coupled WRF-CMAQ Model

Science.gov (United States)

Advances in the land surface model (LSM) and planetary boundary layer (PBL) components of the WRF-CMAQ coupled meteorology and air quality modeling system are described. The aim of these modifications was primarily to improve the modeling of ground level concentrations of trace c...

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

Statistical Studies of Mesoscale Forecast Models MM5 and WRF

National Research Council Canada - National Science Library

Henmi, Teizi

2004-01-01

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

How reliable is the offline couple of WRF and VIC model? And how does high quality land cover data impact the VIC model simulation?

Science.gov (United States)

Tang, C.; Dennis, R. L.

2012-12-01

First, the ability of the offline coupling of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model to produce hydrological and climate variables was evaluated. The performance of the offline couple of WRF and VIC was assessed with respect to key simulated variables through a comparison with the calibrated VIC model simulation. A spatiotemporal comparison of the simulated evaporation (ET), soil moisture (SM), runoff, and baseflow produced by the VIC calibrated run (base data) and by the offline coupling run was conducted. The results showed that the offline couple of VIC with WRF was able to achieve good agreement in the simulation of monthly and daily soil moisture, and monthly evaporation. This suggests the VIC coupling should function without causing a large change in the moisture budget. However, the offline coupling showed most disagreement in daily and monthly runoff, and baseflow which is related to errors in WRF precipitation. Second, the sensitivity of the VIC model to the land cover was assessed by performing a sensitivity simulation using the National Land Cover Database (NLCD) instead of the older NLDAS/AVHRR data. Improved land cover is shown to achieve more accurate simulation of the streamflow.

Modelling the urban air quality in Hamburg with the new city-scale chemistry transport model CityChem

Science.gov (United States)

Karl, Matthias; Ramacher, Martin; Aulinger, Armin; Matthias, Volker; Quante, Markus

2017-04-01

Air quality modelling plays an important role by providing guidelines for efficient air pollution abatement measures. Currently, most urban dispersion models treat air pollutants as passive tracer substances or use highly simplified chemistry when simulating air pollutant concentrations on the city-scale. The newly developed urban chemistry-transport model CityChem has the capability of modelling the photochemical transformation of multiple pollutants along with atmospheric diffusion to produce pollutant concentration fields for the entire city on a horizontal resolution of 100 m or even finer and a vertical resolution of 24 layers up to 4000 m height. CityChem is based on the Eulerian urban dispersion model EPISODE of the Norwegian Institute for Air Research (NILU). CityChem treats the complex photochemistry in cities using detailed EMEP chemistry on an Eulerian 3-D grid, while using simple photo-stationary equilibrium on a much higher resolution grid (receptor grid), i.e. close to industrial point sources and traffic sources. The CityChem model takes into account that long-range transport contributes to urban pollutant concentrations. This is done by using 3-D boundary concentrations for the city domain derived from chemistry-transport simulations with the regional air quality model CMAQ. For the study of the air quality in Hamburg, CityChem was set-up with a main grid of 30×30 grid cells of 1×1 km2 each and a receptor grid of 300×300 grid cells of 100×100 m2. The CityChem model was driven with meteorological data generated by the prognostic meteorology component of the Australian chemistry-transport model TAPM. Bottom-up inventories of emissions from traffic, industry, households were based on data of the municipality of Hamburg. Shipping emissions for the port of Hamburg were taken from the Clean North Sea Shipping project. Episodes with elevated ozone (O3) were of specific interest for this study, as these are associated with exceedances of the World

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.

Forest fire forecasting tool for air quality modelling systems

International Nuclear Information System (INIS)

San Jose, R.; Perez, J. L.; Perez, L.; Gonzalez, R. M.; Pecci, J.; Palacios, M.

2015-01-01

Adverse effects of smoke on air quality are of great concern; however, even today the estimates of atmospheric fire emissions are a key issue. It is necessary to implement systems for predicting smoke into an air quality modelling system, and in this work a first attempt towards creating a system of this type is presented. Wild land fire spread and behavior are complex phenomena due to both the number of involved physic-chemical factors, and the nonlinear relationship between variables. WRF-Fire was employed to simulate spread and behavior of some real fires occurred in South-East of Spain and North of Portugal. The use of fire behavior models requires the availability of high resolution environmental and fuel data. A new custom fuel moisture content model has been developed. The new module allows each time step to calculate the fuel moisture content of the dead fuels and live fuels. The results confirm that the use of accurate meteorological data and a custom fuel moisture content model is crucial to obtain precise simulations of fire behavior. To simulate air pollution over Europe, we use the regional meteorological-chemistry transport model WRF-Chem. In this contribution, we show the impact of using two different fire emissions inventories (FINN and IS4FIRES) and how the coupled WRF-Fire- Chem model improves the results of the forest fire emissions and smoke concentrations. The impact of the forest fire emissions on concentrations is evident, and it is quite clear from these simulations that the choice of emission inventory is very important. We conclude that using the WRF-fire behavior model produces better results than using forest fire emission inventories although the requested computational power is much higher. (Author)

Forest fire forecasting tool for air quality modelling systems

Energy Technology Data Exchange (ETDEWEB)

San Jose, R.; Perez, J.L.; Perez, L.; Gonzalez, R.M.; Pecci, J.; Palacios, M.

2015-07-01

Adverse effects of smoke on air quality are of great concern; however, even today the estimates of atmospheric fire emissions are a key issue. It is necessary to implement systems for predicting smoke into an air quality modelling system, and in this work a first attempt towards creating a system of this type is presented. Wildland fire spread and behavior are complex Phenomena due to both the number of involved physic-chemical factors, and the nonlinear relationship between variables. WRF-Fire was employed to simulate spread and behavior of some real fires occurred in South-East of Spain and North of Portugal. The use of fire behavior models requires the availability of high resolution environmental and fuel data. A new custom fuel moisture content model has been developed. The new module allows each time step to calculate the fuel moisture content of the dead fuels and live fuels. The results confirm that the use of accurate meteorological data and a custom fuel moisture content model is crucial to obtain precise simulations of fire behavior. To simulate air pollution over Europe, we use the regional meteorological-chemistry transport model WRF-Chem. In this contribution, we show the impact of using two different fire emissions inventories (FINN and IS4FIRES) and how the coupled WRF-FireChem model improves the results of the forest fire emissions and smoke concentrations. The impact of the forest fire emissions on concentrations is evident, and it is quite clear from these simulations that the choice of emission inventory is very important. We conclude that using the WRF-fire behavior model produces better results than using forest fire emission inventories although the requested computational power is much higher. (Author)

Forest fire forecasting tool for air quality modelling systems

Energy Technology Data Exchange (ETDEWEB)

San Jose, R.; Perez, J. L.; Perez, L.; Gonzalez, R. M.; Pecci, J.; Palacios, M.

2015-07-01

Adverse effects of smoke on air quality are of great concern; however, even today the estimates of atmospheric fire emissions are a key issue. It is necessary to implement systems for predicting smoke into an air quality modelling system, and in this work a first attempt towards creating a system of this type is presented. Wild land fire spread and behavior are complex phenomena due to both the number of involved physic-chemical factors, and the nonlinear relationship between variables. WRF-Fire was employed to simulate spread and behavior of some real fires occurred in South-East of Spain and North of Portugal. The use of fire behavior models requires the availability of high resolution environmental and fuel data. A new custom fuel moisture content model has been developed. The new module allows each time step to calculate the fuel moisture content of the dead fuels and live fuels. The results confirm that the use of accurate meteorological data and a custom fuel moisture content model is crucial to obtain precise simulations of fire behavior. To simulate air pollution over Europe, we use the regional meteorological-chemistry transport model WRF-Chem. In this contribution, we show the impact of using two different fire emissions inventories (FINN and IS4FIRES) and how the coupled WRF-Fire- Chem model improves the results of the forest fire emissions and smoke concentrations. The impact of the forest fire emissions on concentrations is evident, and it is quite clear from these simulations that the choice of emission inventory is very important. We conclude that using the WRF-fire behavior model produces better results than using forest fire emission inventories although the requested computational power is much higher. (Author)

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.

Evaluating transport in the WRF model along the California coast

OpenAIRE

C. E. Yver; H. D. Graven; D. D. Lucas; P. J. Cameron-Smith; R. F. Keeling; R. F. Weiss

2013-01-01

This paper presents a step in the development of a top-down method to complement the bottom-up inventories of halocarbon emissions in California using high frequency observations, forward simulations and inverse methods. The Scripps Institution of Oceanography high-frequency atmospheric halocarbons measurement sites are located along the California coast and therefore the evaluation of transport in the chosen Weather Research Forecast (WRF) model at these sites is crucial fo...

How reliable is the offline linkage of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model?

Science.gov (United States)

The aim for this research is to evaluate the ability of the offline linkage of Weather Research & Forecasting Model (WRF) and Variable Infiltration Capacity (VIC) model to produce hydrological, e.g. evaporation (ET), soil moisture (SM), runoff, and baseflow. First, the VIC mo...

Characterization of down-valley winds in stable stratification from the KASCADE field campaign and WRF mesoscale simulations

International Nuclear Information System (INIS)

Duine, Gert-Jan

2015-01-01

and Durance down-valley (CDV and DDV, respectively) winds are both dominating flows during the period of investigation. Once stable stratification has set around sunset, CDV wind continuously grows and thickens. The profile forms in a jet which is mostly observed at around 30 m agl with 2 - 3 m s -1 . CDV wind is a thermally driven flow, which persists regularly throughout the night and disappears in the early morning alongside stable stratification. Though the Cadarache current observational network lacks means of measurement for inside CDV wind, this work shows that it can be now forecasted from available meteorological tower observations. Although the forecast of CDV wind is out of reach of mesoscale modeling on a kilometer-scale resolution, the now casting methodology developed here could be used to forecast it by means of a combination of dynamical and statistical down-scaling. The DDV wind has been investigated by means of observations and modeling - all IOPs were simulated with an optimized WRF configuration at a 1-km horizontal grid spacing. The DDV wind has been recognized as down-valley oriented, and strongly related to stability at a regional scale, as it exists only after sunset when synoptic forcing is very weak. On the one hand, though highly variable, the DDV wind arrival at Cadarache is mostly observed 6 to 9 hours after sunset. On the other hand, it is dominantly present around sunrise, when convectively driven processes are not yet established. Jets are observed mostly at around 175 - 225 m agl with wind speeds between 4 and 8 m s -1 . DDV wind depth appears to be closely related to valley depth, which varies throughout the DV. Some deficiencies of the simulations are found, including underestimations of diurnal temperature ranges, overestimations of atmospheric turbulent fluxes, too early timing for onset and cessation of DDV wind. Despite these, the DDV wind is simulated close to reality thanks to the 1-km resolution allowing a correct

West-WRF Sensitivity to Sea Surface Temperature Boundary Condition in California Precipitation Forecasts of AR Related Events

Science.gov (United States)

Zhang, X.; Cornuelle, B. D.; Martin, A.; Weihs, R. R.; Ralph, M.

2017-12-01

We evaluated the merit in coastal precipitation forecasts by inclusion of high resolution sea surface temperature (SST) from blended satellite and in situ observations as a boundary condition (BC) to the Weather Research and Forecast (WRF) mesoscale model through simple perturbation tests. Our sensitivity analyses shows that the limited improvement of watershed scale precipitation forecast is credible. When only SST BC is changed, there is an uncertainty introduced because of artificial model state equilibrium and the nonlinear nature of the WRF model system. With the change of SST on the order of a fraction of a degree centigrade, we found that the part of random perturbation forecast response is saturated after 48 hours when it reaches to the order magnitude of the linear response. It is important to update the SST at a shorter time period, so that the independent excited nonlinear modes can cancel each other. The uncertainty in our SST configuration is quantitatively equivalent to adding to a spatially uncorrelated Guasian noise of zero mean and 0.05 degree of standard deviation to the SST. At this random noise perturbation magnitude, the ensemble average behaves well within a convergent range. It is also found that the sensitivity of forecast changes in response to SST changes. This is measured by the ratio of the spatial variability of mean of the ensemble perturbations over the spatial variability of the corresponding forecast. The ratio is about 10% for surface latent heat flux, 5 % for IWV, and less than 1% for surface pressure.

Evaluating transport in the WRF model along the California coast

OpenAIRE

C. Yver; H. Graven; D. D. Lucas; P. Cameron-Smith; R. Keeling; R. Weiss

2012-01-01

This paper presents a step in the development of a top-down method to complement the bottom-up inventories of halocarbon emissions in California using high frequency observations, forward simulations and inverse methods. The Scripps Institution of Oceanography high-frequency atmospheric halocarbon measurement sites are located along the California coast and therefore the evaluation of transport in the chosen Weather Research Forecast (WRF) model at these sites is crucial for inverse mo...

The Comparison of Point Data Models for the Output of WRF Hydro Model in the IDV

Science.gov (United States)

Ho, Y.; Weber, J.

2017-12-01

WRF Hydro netCDF output files contain streamflow, flow depth, longitude, latitude, altitude and stream order values for each forecast point. However, the data are not CF compliant. The total number of forecast points for the US CONUS is approximately 2.7 million and it is a big challenge for any visualization and analysis tool. The IDV point cloud display shows point data as a set of points colored by parameter. This display is very efficient compared to a standard point type display for rendering a large number of points. The one problem we have is that the data I/O can be a bottleneck issue when dealing with a large collection of point input files. In this presentation, we will experiment with different point data models and their APIs to access the same WRF Hydro model output. The results will help us construct a CF compliant netCDF point data format for the community.

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)

Combined impacts of nitrous acid and nitryl chloride on lower-tropospheric ozone: new module development in WRF-Chem and application to China

Science.gov (United States)

Zhang, Li; Li, Qinyi; Wang, Tao; Ahmadov, Ravan; Zhang, Qiang; Li, Meng; Lv, Mengyao

2017-08-01

Nitrous acid (HONO) and nitryl chloride (ClNO2) - through their photolysis - can have profound effects on the nitrogen cycle and oxidation capacity of the lower troposphere. Previous numerical studies have separately considered and investigated the sources/processes of these compounds and their roles in the fate of reactive nitrogen and the production of ozone (O3), but their combined impact on the chemistry of the lower part of the troposphere has not been addressed yet. In this study, we updated the WRF-Chem model with the currently known sources and chemistry of HONO and chlorine in a new chemical mechanism (CBMZ_ReNOM), and applied it to a study of the combined effects of HONO and ClNO2 on summertime O3 in the boundary layer over China. We simulated the spatial distributions of HONO, ClNO2, and related compounds at the surface and within the lower troposphere. The results showed that the modeled HONO levels reached up to 800-1800 ppt at the surface (0-30 m) over the North China Plain (NCP), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) regions and that HONO was concentrated within a 0-200 m layer. In comparison, the simulated surface ClNO2 mixing ratio was around 800-1500 ppt over the NCP, YRD, and central China regions and was predominantly present in a 0-600 m layer. HONO enhanced daytime ROx (OH + HO2 + RO2) and O3 at the surface (0-30 m) by 2.8-4.6 ppt (28-37 %) and 2.9-6.2 ppb (6-13 %), respectively, over the three most developed regions, whereas ClNO2 increased surface O3 in the NCP and YRD regions by 2.4-3.3 ppb (or 5-6 %) and it also had a significant impact (3-6 %) on above-surface O3 within 200-500 m. The combined effects increased surface O3 by 11.5, 13.5, and 13.3 % in the NCP, YRD, and PRD regions, respectively. Over the boundary layer (0-1000 m), the HONO and ClNO2 enhanced O3 by up to 5.1 and 3.2 %, respectively, and their combined effect increased O3 by 7.1-8.9 % in the three regions. The new module noticeably improved O3

Numerical simulations of an advection fog event over Shanghai Pudong International Airport with the WRF model

Science.gov (United States)

Lin, Caiyan; Zhang, Zhongfeng; Pu, Zhaoxia; Wang, Fengyun

2017-10-01

A series of numerical simulations is conducted to understand the formation, evolution, and dissipation of an advection fog event over Shanghai Pudong International Airport (ZSPD) with the Weather Research and Forecasting (WRF) model. Using the current operational settings at the Meteorological Center of East China Air Traffic Management Bureau, the WRF model successfully predicts the fog event at ZSPD. Additional numerical experiments are performed to examine the physical processes associated with the fog event. The results indicate that prediction of this particular fog event is sensitive to microphysical schemes for the time of fog dissipation but not for the time of fog onset. The simulated timing of the arrival and dissipation of the fog, as well as the cloud distribution, is substantially sensitive to the planetary boundary layer and radiation (both longwave and shortwave) processes. Moreover, varying forecast lead times also produces different simulation results for the fog event regarding its onset and duration, suggesting a trade-off between more accurate initial conditions and a proper forecast lead time that allows model physical processes to spin up adequately during the fog simulation. The overall outcomes from this study imply that the complexity of physical processes and their interactions within the WRF model during fog evolution and dissipation is a key area of future research.

The WRF model forecast-derived low-level wind shear climatology over the United States great plains

Energy Technology Data Exchange (ETDEWEB)

Storm, B. [Wind Science and Engineering Research Center, Texas Tech University, Lubbock, TX (United States); Basu, S. [Atmospheric Science Group, Department of Geosciences, Texas Tech University, Lubbock, TX (United States)

2010-07-01

For wind resource assessment projects, it is common practice to use a power-law relationship (U(z) {proportional_to} z{sup {alpha}}) and a fixed shear exponent ({alpha} = 1/7) to extrapolate the observed wind speed from a low measurement level to high turbine hub-heights. However, recent studies using tall-tower observations have found that the annual average shear exponents at several locations over the United States Great Plains (USGP) are significantly higher than 1/7. These findings highlight the critical need for detailed spatio-temporal characterizations of wind shear climatology over the USGP, where numerous large wind farms will be constructed in the foreseeable future. In this paper, a new generation numerical weather prediction model - the Weather Research and Forecasting (WRF) model, a fast and relatively inexpensive alternative to time-consuming and costly tall-tower projects, is utilized to determine whether it can reliably estimate the shear exponent and the magnitude of the directional shear at any arbitrary location over the USGP. Our results indicate that the WRF model qualitatively captures several low-level wind shear characteristics. However, there is definitely room for physics parameterization improvements for the WRF model to reliably represent the lower part of the atmospheric boundary layer. (author)

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

DEFF Research Database (Denmark)

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

2014-01-01

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

High resolution dynamical downscaling of air temperature and relative humidity: performance assessment of WRF for Portugal

Science.gov (United States)

Menezes, Isilda; Pereira, Mário; Moreira, Demerval; Carvalheiro, Luís; Bugalho, Lourdes; Corte-Real, João

2017-04-01

Air temperature and relative humidity are two of the atmospheric variables with higher impact on human and natural systems, contributing to define the stress/comfortable conditions, affecting the productivity and health of the individuals as well as diminishing the resilience to other environmental hazards. Atmospheric regional models, driven by large scale forecasts from global circulation models, are the best way to reproduce such environmental conditions in high space-time resolution. This study is focused on the performance assessment of the WRF mesoscale model to perform high resolution dynamical downscaling for Portugal with three two-way nested grids, at 60 km, 20 km and 5 km horizontal resolution. The simulations of WRF models were produced with different initial and boundary forcing conditions. The NCEP-FNL Operational Global Analysis data available on 1-degree by 1-degree grid every six hours and ERA-Interim reanalyses dataset were used to drive the models. Two alternative configurations of the WRF model, including planetary boundary, layer schemes, microphysics, land-surface models, radiation schemes, were used and tested within the 5 km spatial resolution domain. Simulations of air temperature and relative humidity were produced for January and July of 2016 and compared with the observed datasets provided by the Instituto Português do Mar e da Atmosfera (IPMA) for 83 weather stations. Different performance measures of bias, precision, and accuracy were used, namely normalized bias, standard deviation, mean absolute error, root mean square error, bias of root mean square error as well as correlation based measures (e.g., coefficient of determination) and goodness of fit measures (index of agreement). Main conclusions from the obtained results reveal: (i) great similarity between the spatial patterns of the simulated and observed fields; (ii) only small differences between simulations produced with ERA-Interim and NCEP-FNL, in spite of some differences

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

Forecasting Lightning Threat Using WRF Proxy Fields

Science.gov (United States)

McCaul, E. W., Jr.

2010-01-01

Objectives: Given that high-resolution WRF forecasts can capture the character of convective outbreaks, we seek to: 1. Create WRF forecasts of LTG threat (1-24 h), based on 2 proxy fields from explicitly simulated convection: - graupel flux near -15 C (captures LTG time variability) - vertically integrated ice (captures LTG threat area). 2. Calibrate each threat to yield accurate quantitative peak flash rate densities. 3. Also evaluate threats for areal coverage, time variability. 4. Blend threats to optimize results. 5. Examine sensitivity to model mesh, microphysics. Methods: 1. Use high-resolution 2-km WRF simulations to prognose convection for a diverse series of selected case studies. 2. Evaluate graupel fluxes; vertically integrated ice (VII). 3. Calibrate WRF LTG proxies using peak total LTG flash rate densities from NALMA; relationships look linear, with regression line passing through origin. 4. Truncate low threat values to make threat areal coverage match NALMA flash extent density obs. 5. Blend proxies to achieve optimal performance 6. Study CAPS 4-km ensembles to evaluate sensitivities.

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-06-01

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

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.

Comparison of Hourly Solar Radiation from a Ground–Based Station, Remote Sensing and Weather Forecast Models at a Coastal Site of South Italy (Lamezia Terme)

DEFF Research Database (Denmark)

Feudo, Teresa Lo; Avolio, Elenio; Gullì, Daniel

2015-01-01

The solar radiation is a critical input parameter when working with solar energy and radiation dependent surface processes. In this study, we present preliminary results from an inter-comparison between hourly values from a pyranometer, MSG-SEVIRI sensor and two meso-scale models, WRF and RAMS, i...

Updated vegetation information in high resolution WRF simulations

DEFF Research Database (Denmark)

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

2013-01-01

modify the energy distribution at the land surface. In weather and climate models it is important to represent the vegetation variability accurately to obtain reliable results. The weather research and forecasting (WRF) model uses green vegetation fraction (GVF) time series to represent vegetation...... seasonality. The GVF of each grid cell is additionally used to scale other parameters such as LAI, roughness, emissivity and albedo within predefined intervals. However, the default GYP used by WRF does not reflect recent climatic changes or change in management practices since it was derived more than 20...

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

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.

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

Science.gov (United States)

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

2015-10-01

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

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

CHEM2D-OPP: A new linearized gas-phase ozone photochemistry parameterization for high-altitude NWP and climate models

Directory of Open Access Journals (Sweden)

J. P. McCormack

2006-01-01

Full Text Available The new CHEM2D-Ozone Photochemistry Parameterization (CHEM2D-OPP for high-altitude numerical weather prediction (NWP systems and climate models specifies the net ozone photochemical tendency and its sensitivity to changes in ozone mixing ratio, temperature and overhead ozone column based on calculations from the CHEM2D interactive middle atmospheric photochemical transport model. We evaluate CHEM2D-OPP performance using both short-term (6-day and long-term (1-year stratospheric ozone simulations with the prototype high-altitude NOGAPS-ALPHA forecast model. An inter-comparison of NOGAPS-ALPHA 6-day ozone hindcasts for 7 February 2005 with ozone photochemistry parameterizations currently used in operational NWP systems shows that CHEM2D-OPP yields the best overall agreement with both individual Aura Microwave Limb Sounder ozone profile measurements and independent hemispheric (10°–90° N ozone analysis fields. A 1-year free-running NOGAPS-ALPHA simulation using CHEM2D-OPP produces a realistic seasonal cycle in zonal mean ozone throughout the stratosphere. We find that the combination of a model cold temperature bias at high latitudes in winter and a warm bias in the CHEM2D-OPP temperature climatology can degrade the performance of the linearized ozone photochemistry parameterization over seasonal time scales despite the fact that the parameterized temperature dependence is weak in these regions.

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

Science.gov (United States)

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

2011-12-01

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

WRF added value to capture the spatio-temporal drought variability

Science.gov (United States)

García-Valdecasas Ojeda, Matilde; Quishpe-Vásquez, César; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

Regional Climate Models (RCM) has been widely used as a tool to perform high resolution climate fields in areas with high climate variability such as Spain. However, the outputs provided by downscaling techniques have many sources of uncertainty associated at different aspects. In this study, the ability of the Weather Research and Forecasting (WRF) model to capture drought conditions has been analyzed. The WRF simulation was carried out for a period that spanned from 1980 to 2010 over a domain centered in the Iberian Peninsula with a spatial resolution of 0.088°, and nested in the coarser EURO-CORDEX domain (0.44° spatial resolution). To investigate the spatiotemporal drought variability, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) has been computed at two different timescales: 3- and 12-months due to its suitability to study agricultural and hydrological droughts. The drought indices computed from WRF outputs were compared with those obtained from the observational (MOTEDAS and MOPREDAS) datasets. In order to assess the added value provided by downscaled fields, these indices were also computed from the ERA-Interim Re-Analysis database, which provides the lateral and boundary conditions of the WRF simulations. Results from this study indicate that WRF provides a noticeable benefit with respect to ERA-Interim for many regions in Spain in terms of drought indices, greater for SPI than for SPEI. The improvement offered by WRF depends on the region, index and timescale analyzed, being greater at longer timescales. These findings prove the reliability of the downscaled fields to detect drought events and, therefore, it is a remarkable source of knowledge for a suitable decision making related to water-resource management. Keywords: Drought, added value, Regional Climate Models, WRF, SPEI, SPI. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and

Evaluation of the WRF-Urban Modeling System Coupled to Noah and Noah-MP Land Surface Models Over a Semiarid Urban Environment

Science.gov (United States)

Salamanca, Francisco; Zhang, Yizhou; Barlage, Michael; Chen, Fei; Mahalov, Alex; Miao, Shiguang

2018-03-01

We have augmented the existing capabilities of the integrated Weather Research and Forecasting (WRF)-urban modeling system by coupling three urban canopy models (UCMs) available in the WRF model with the new community Noah with multiparameterization options (Noah-MP) land surface model (LSM). The WRF-urban modeling system's performance has been evaluated by conducting six numerical experiments at high spatial resolution (1 km horizontal grid spacing) during a 15 day clear-sky summertime period for a semiarid urban environment. To assess the relative importance of representing urban surfaces, three different urban parameterizations are used with the Noah and Noah-MP LSMs, respectively, over the two major cities of Arizona: Phoenix and Tucson metropolitan areas. Our results demonstrate that Noah-MP reproduces somewhat better than Noah the daily evolution of surface skin temperature and near-surface air temperature (especially nighttime temperature) and wind speed. Concerning the urban areas, bulk urban parameterization overestimates nighttime 2 m air temperature compared to the single-layer and multilayer UCMs that reproduce more accurately the daily evolution of near-surface air temperature. Regarding near-surface wind speed, only the multilayer UCM was able to reproduce realistically the daily evolution of wind speed, although maximum winds were slightly overestimated, while both the single-layer and bulk urban parameterizations overestimated wind speed considerably. Based on these results, this paper demonstrates that the new community Noah-MP LSM coupled to an UCM is a promising physics-based predictive modeling tool for urban applications.

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...

Interactive Gaussian Graphical Models for Discovering Depth Trends in ChemCam Data

Science.gov (United States)

Oyen, D. A.; Komurlu, C.; Lanza, N. L.

2018-04-01

Interactive Gaussian graphical models discover surface compositional features on rocks in ChemCam targets. Our approach visualizes shot-to-shot relationships among LIBS observations, and identifies the wavelengths involved in the trend.

Prediction of Aerosol Optical Depth in West Asia: Machine Learning Methods versus Numerical Models

Science.gov (United States)

Omid Nabavi, Seyed; Haimberger, Leopold; Abbasi, Reyhaneh; Samimi, Cyrus

2017-04-01

Dust-prone areas of West Asia are releasing increasingly large amounts of dust particles during warm months. Because of the lack of ground-based observations in the region, this phenomenon is mainly monitored through remotely sensed aerosol products. The recent development of mesoscale Numerical Models (NMs) has offered an unprecedented opportunity to predict dust emission, and, subsequently Aerosol Optical Depth (AOD), at finer spatial and temporal resolutions. Nevertheless, the significant uncertainties in input data and simulations of dust activation and transport limit the performance of numerical models in dust prediction. The presented study aims to evaluate if machine-learning algorithms (MLAs), which require much less computational expense, can yield the same or even better performance than NMs. Deep blue (DB) AOD, which is observed by satellites but also predicted by MLAs and NMs, is used for validation. We concentrate our evaluations on the over dry Iraq plains, known as the main origin of recently intensified dust storms in West Asia. Here we examine the performance of four MLAs including Linear regression Model (LM), Support Vector Machine (SVM), Artificial Neural Network (ANN), Multivariate Adaptive Regression Splines (MARS). The Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) and the Dust REgional Atmosphere Model (DREAM) are included as NMs. The MACC aerosol re-analysis of European Centre for Medium-range Weather Forecast (ECMWF) is also included, although it has assimilated satellite-based AOD data. Using the Recursive Feature Elimination (RFE) method, nine environmental features including soil moisture and temperature, NDVI, dust source function, albedo, dust uplift potential, vertical velocity, precipitation and 9-month SPEI drought index are selected for dust (AOD) modeling by MLAs. During the feature selection process, we noticed that NDVI and SPEI are of the highest importance in MLAs predictions. The data set was divided

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.

Study of atmospheric condition during the heavy rain event in Bojonegoro using weather research and forecasting (WRF) model: case study 9 February 2017

Science.gov (United States)

Saragih, I. J. A.; Meygatama, A. G.; Sugihartati, F. M.; Sidauruk, M.; Mulsandi, A.

2018-03-01

During 2016, there are frequent heavy rains in the Bojonegoro region, one of which is rain on 9 February 2016. The occurrence of heavy rainfall can cause the floods that inundate the settlements, rice fields, roads, and public facilities. This makes it important to analyze the atmospheric conditions during the heavy rainfall events in Bojonegoro. One of the analytical methods that can be used is using WRF-Advanced Research WRF (WRF-ARW) model. This study was conducted by comparing the rain analysis from WRF-ARW model with the Himawari-8 satellite imagery. The data used are Final Analysis (FNL) data for the WRF-ARW model and infrared (IR) channel for Himawari-8 satellite imagery. The data are processed into the time-series images and then analyzed descriptively. The meteorological parameters selected to be analyzed are relative humidity, vortices, divergences, air stability index, and precipitation. These parameters are expected to indicate the existence of a convective activity in Bojonegoro during the heavy rainfall event. The Himawari-8 satellite imagery shows that there is a cluster of convective clouds in Bojonegoro during the heavy rainfall event. The lowest value of the cloud top temperature indicates that the cluster of convective clouds is a cluster of Cumulonimbus cloud (CB).

Development and Performance of the Modularized, High-performance Computing and Hybrid-architecture Capable GEOS-Chem Chemical Transport Model

Science.gov (United States)

Long, M. S.; Yantosca, R.; Nielsen, J.; Linford, J. C.; Keller, C. A.; Payer Sulprizio, M.; Jacob, D. J.

2014-12-01

The GEOS-Chem global chemical transport model (CTM), used by a large atmospheric chemistry research community, has been reengineered to serve as a platform for a range of computational atmospheric chemistry science foci and applications. Development included modularization for coupling to general circulation and Earth system models (ESMs) and the adoption of co-processor capable atmospheric chemistry solvers. This was done using an Earth System Modeling Framework (ESMF) interface that operates independently of GEOS-Chem scientific code to permit seamless transition from the GEOS-Chem stand-alone serial CTM to deployment as a coupled ESM module. In this manner, the continual stream of updates contributed by the CTM user community is automatically available for broader applications, which remain state-of-science and directly referenceable to the latest version of the standard GEOS-Chem CTM. These developments are now available as part of the standard version of the GEOS-Chem CTM. The system has been implemented as an atmospheric chemistry module within the NASA GEOS-5 ESM. The coupled GEOS-5/GEOS-Chem system was tested for weak and strong scalability and performance with a tropospheric oxidant-aerosol simulation. Results confirm that the GEOS-Chem chemical operator scales efficiently for any number of processes. Although inclusion of atmospheric chemistry in ESMs is computationally expensive, the excellent scalability of the chemical operator means that the relative cost goes down with increasing number of processes, making fine-scale resolution simulations possible.

Assessment of the Effects of Various Precipitation Forcings on Flood Forecasting Potential Using WRF-Hydro Modeling

Science.gov (United States)

Zhang, J.; Fang, N. Z.

2017-12-01

A potential flood forecast system is under development for the Upper Trinity River Basin (UTRB) in North Central of Texas using the WRF-Hydro model. The Routing Application for the Parallel Computation of Discharge (RAPID) is utilized as channel routing module to simulate streamflow. Model performance analysis was conducted based on three quantitative precipitation estimates (QPE): the North Land Data Assimilation System (NLDAS) rainfall, the Multi-Radar Multi-Sensor (MRMS) QPE and the National Centers for Environmental Prediction (NCEP) quality-controlled stage IV estimates. Prior to hydrologic simulation, QPE performance is assessed on two time scales (daily and hourly) using the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) and Hydrometeorological Automated Data System (HADS) hourly products. The calibrated WRF-Hydro model was then evaluated by comparing the simulated against the USGS observed using various QPE products. The results imply that the NCEP stage IV estimates have the best accuracy among the three QPEs on both time scales, while the NLDAS rainfall performs poorly because of its coarse spatial resolution. Furthermore, precipitation bias demonstrates pronounced impact on flood forecasting skills, as the root mean squared errors are significantly reduced by replacing NLDAS rainfall with NCEP stage IV estimates. This study also demonstrates that accurate simulated results can be achieved when initial soil moisture values are well understood in the WRF-Hydro model. Future research effort will therefore be invested on incorporating data assimilation with focus on initial states of the soil properties for UTRB.

Development of a Grid-Independent Geos-Chem Chemical Transport Model (v9-02) as an Atmospheric Chemistry Module for Earth System Models

Science.gov (United States)

Long, M. S.; Yantosca, R.; Nielsen, J. E; Keller, C. A.; Da Silva, A.; Sulprizio, M. P.; Pawson, S.; Jacob, D. J.

2015-01-01

The GEOS-Chem global chemical transport model (CTM), used by a large atmospheric chemistry research community, has been re-engineered to also serve as an atmospheric chemistry module for Earth system models (ESMs). This was done using an Earth System Modeling Framework (ESMF) interface that operates independently of the GEOSChem scientific code, permitting the exact same GEOSChem code to be used as an ESM module or as a standalone CTM. In this manner, the continual stream of updates contributed by the CTM user community is automatically passed on to the ESM module, which remains state of science and referenced to the latest version of the standard GEOS-Chem CTM. A major step in this re-engineering was to make GEOS-Chem grid independent, i.e., capable of using any geophysical grid specified at run time. GEOS-Chem data sockets were also created for communication between modules and with external ESM code. The grid-independent, ESMF-compatible GEOS-Chem is now the standard version of the GEOS-Chem CTM. It has been implemented as an atmospheric chemistry module into the NASA GEOS- 5 ESM. The coupled GEOS-5-GEOS-Chem system was tested for scalability and performance with a tropospheric oxidant-aerosol simulation (120 coupled species, 66 transported tracers) using 48-240 cores and message-passing interface (MPI) distributed-memory parallelization. Numerical experiments demonstrate that the GEOS-Chem chemistry module scales efficiently for the number of cores tested, with no degradation as the number of cores increases. Although inclusion of atmospheric chemistry in ESMs is computationally expensive, the excellent scalability of the chemistry module means that the relative cost goes down with increasing number of cores in a massively parallel environment.

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.

High-Resolution WRF Forecasts of Lightning Threat

Science.gov (United States)

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

2007-01-01

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

Prediction of tropical cyclone over North Indian Ocean using WRF model: sensitivity to scatterometer winds, ATOVS and ATMS radiances

KAUST Repository

Dodla, Venkata B.

2016-05-03

Tropical cyclone prediction, in terms of intensification and movement, is important for disaster management and mitigation. Hitherto, research studies were focused on this issue that lead to improvement in numerical models, initial data with data assimilation, physical parameterizations and application of ensemble prediction. Weather Research and Forecasting (WRF) model is the state-of-art model for cyclone prediction. In the present study, prediction of tropical cyclone (Phailin, 2013) that formed in the North Indian Ocean (NIO) with and without data assimilation using WRF model has been made to assess impacts of data assimilation. WRF model was designed to have nested two domains of 15 and 5 km resolutions. In the present study, numerical experiments are made without and with the assimilation of scatterometer winds, and radiances from ATOVS and ATMS. The model performance was assessed in respect to the movement and intensification of cyclone. ATOVS data assimilation experiment had produced the best prediction with least errors less than 100 km up to 60 hours and producing pre-deepening and deepening periods accurately. The Control and SCAT wind assimilation experiments have shown good track but the errors were 150-200 km and gradual deepening from the beginning itself instead of sudden deepening.

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

A comparison study of convective and microphysical parameterization schemes associated with lightning occurrence in southeastern Brazil using the WRF model

Science.gov (United States)

Zepka, G. D.; Pinto, O.

2010-12-01

The intent of this study is to identify the combination of convective and microphysical WRF parameterizations that better adjusts to lightning occurrence over southeastern Brazil. Twelve thunderstorm days were simulated with WRF model using three different convective parameterizations (Kain-Fritsch, Betts-Miller-Janjic and Grell-Devenyi ensemble) and two different microphysical schemes (Purdue-Lin and WSM6). In order to test the combinations of parameterizations at the same time of lightning occurrence, a comparison was made between the WRF grid point values of surface-based Convective Available Potential Energy (CAPE), Lifted Index (LI), K-Index (KI) and equivalent potential temperature (theta-e), and the lightning locations nearby those grid points. Histograms were built up to show the ratio of the occurrence of different values of these variables for WRF grid points associated with lightning to all WRF grid points. The first conclusion from this analysis was that the choice of microphysics did not change appreciably the results as much as different convective schemes. The Betts-Miller-Janjic parameterization has generally worst skill to relate higher magnitudes for all four variables to lightning occurrence. The differences between the Kain-Fritsch and Grell-Devenyi ensemble schemes were not large. This fact can be attributed to the similar main assumptions used by these schemes that consider entrainment/detrainment processes along the cloud boundaries. After that, we examined three case studies using the combinations of convective and microphysical options without the Betts-Miller-Janjic scheme. Differently from the traditional verification procedures, fields of surface-based CAPE from WRF 10 km domain were compared to the Eta model, satellite images and lightning data. In general the more reliable convective scheme was Kain-Fritsch since it provided more consistent distribution of the CAPE fields with respect to satellite images and lightning data.

Quantifying the effects of LUCCs on local temperatures, precipitation, and wind using the WRF model.

Science.gov (United States)

Lian, Lishu; Li, Baofu; Chen, Yaning; Chu, Cuicui; Qin, Yanhua

2017-09-11

Land use/cover changes (LUCCs) are an important cause of regional climate changes, but the contribution of LUCCs to regional climate changes is not clear. In this study, the Weather Research and Forecasting (WRF) model and statistical methods were used to investigate changes in meteorologic variables in January, April, July, and October 2013 due to local LUCCs from 1990 to 2010 in southern Shandong province, China. The results indicate that the WRF model simulates temperatures in the region well, with high correlation coefficients (0.86-0.97, p wind speed and direction substantially during these four months: average wind speeds increased by 0.02 and 0.01 m/s in January and October, respectively, and decreased by 0.02 and 0.05 m/s in April and July, respectively. Overall, The LUCCs affected spring temperatures the least and summer precipitation the most.

South Baltic Wind Atlas

DEFF Research Database (Denmark)

Pena Diaz, Alfredo; Hahmann, Andrea N.; Hasager, Charlotte Bay

A first version of a wind atlas for the South Baltic Sea has been developed using the WRF mesoscale model and verified by data from tall Danish and German masts. Six different boundary-layer parametrization schemes were evaluated by comparing the WRF results to the observed wind profiles at the m...

Application and evaluation of the WRF-CMAQ modeling system to the 2011 DISCOVER-AQ Baltimore-Washington D.C. study

Science.gov (United States)

Appel, W.; Gilliam, R. C.; Pouliot, G. A.; Godowitch, J. M.; Pleim, J.; Hogrefe, C.; Kang, D.; Roselle, S. J.; Mathur, R.

2013-12-01

The DISCOVER-AQ project (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality), is a joint collaboration between NASA, U.S. EPA and a number of other local organizations with the goal of characterizing air quality in urban areas using satellite, aircraft, vertical profiler and ground based measurements (http://discover-aq.larc.nasa.gov). In July 2011, the DISCOVER-AQ project conducted intensive air quality measurements in the Baltimore, MD and Washington, D.C. area in the eastern U.S. To take advantage of these unique data, the Community Multiscale Air Quality (CMAQ) model, coupled with the Weather Research and Forecasting (WRF) model is used to simulate the meteorology and air quality in the same region using 12-km, 4-km and 1-km horizontal grid spacings. The goal of the modeling exercise is to demonstrate the capability of the coupled WRF-CMAQ modeling system to simulate air quality at fine grid spacings in an urban area. Development of new data assimilation techniques and the use of higher resolution input data for the WRF model have been implemented to improve the meteorological results, particularly at the 4-km and 1-km grid resolutions. In addition, a number of updates to the CMAQ model were made to enhance the capability of the modeling system to accurately represent the magnitude and spatial distribution of pollutants at fine model resolutions. Data collected during the 2011 DISCOVER-AQ campaign, which include aircraft transects and spirals, ship measurements in the Chesapeake Bay, ozonesondes, tethered balloon measurements, DRAGON aerosol optical depth measurements, LIDAR measurements, and intensive ground-based site measurements, are used to evaluate results from the WRF-CMAQ modeling system for July 2011 at the three model grid resolutions. The results of the comparisons of the model results to these measurements will be presented, along with results from the various sensitivity simulations

Short-Term Forecasts Using NU-WRF for the Winter Olympics 2018

Science.gov (United States)

Srikishen, Jayanthi; Case, Jonathan L.; Petersen, Walter A.; Iguchi, Takamichi; Tao, Wei-Kuo; Zavodsky, Bradley T.; Molthan, Andrew

2017-01-01

The NASA Unified-Weather Research and Forecasting model (NU-WRF) will be included for testing and evaluation in the forecast demonstration project (FDP) of the International Collaborative Experiment -PyeongChang 2018 Olympic and Paralympic (ICE-POP) Winter Games. An international array of radar and supporting ground based observations together with various forecast and now-cast models will be operational during ICE-POP. In conjunction with personnel from NASA's Goddard Space Flight Center, the NASA Short-term Prediction Research and Transition (SPoRT) Center is developing benchmark simulations for a real-time NU-WRF configuration to run during the FDP. ICE-POP observational datasets will be used to validate model simulations and investigate improved model physics and performance for prediction of snow events during the research phase (RDP) of the project The NU-WRF model simulations will also support NASA Global Precipitation Measurement (GPM) Mission ground-validation physical and direct validation activities in relation to verifying, testing and improving satellite-based snowfall retrieval algorithms over complex terrain.

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

Science.gov (United States)

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

2006-01-01

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

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.

The 2010 Pakistan floods: high-resolution simulations with the WRF model

Science.gov (United States)

Viterbo, Francesca; Parodi, Antonio; Molini, Luca; Provenzale, Antonello; von Hardenberg, Jost; Palazzi, Elisa

2013-04-01

Estimating current and future water resources in high mountain regions with complex orography is a difficult but crucial task. In particular, the French-Italian project PAPRIKA is focused on two specific regions in the Hindu-Kush -- Himalaya -- Karakorum (HKKH)region: the Shigar basin in Pakistan, at the feet of K2, and the Khumbu valley in Nepal, at the feet of Mount Everest. In this framework, we use the WRF model to simulate precipitation and meteorological conditions with high resolution in areas with extreme orographic slopes, comparing the model output with station and satellite data. Once validated the model, we shall run a set of three future time-slices at very high spatial resolution, in the periods 2046-2050, 2071-2075 and 2096-2100, nested in different climate change scenarios (EXtreme PREcipitation and Hydrological climate Scenario Simulations -EXPRESS-Hydro project). As a prelude to this study, here we discuss the simulation of specific, high-intensity rainfall events in this area. In this paper we focus on the 2010 Pakistan floods which began in late July 2010, producing heavy monsoon rains in the Khyber Pakhtunkhwa, Sindh, Punjab and Balochistan regions of Pakistan and affecting the Indus River basin. Approximately one-fifth of Pakistan's total land area was underwater, with a death toll of about 2000 people. This event has been simulated with the WRF model (version 3.3.) in cloud-permitting mode (d01 14 km and d02 3.5 km): different convective closures and microphysics parameterization have been used. A deeper understanding of the processes responsible for this event has been gained through comparison with rainfall depth observations, radiosounding data and geostationary/polar satellite images.

A parallel calibration utility for WRF-Hydro on high performance computers

Science.gov (United States)

Wang, J.; Wang, C.; Kotamarthi, V. R.

2017-12-01

A successful modeling of complex hydrological processes comprises establishing an integrated hydrological model which simulates the hydrological processes in each water regime, calibrates and validates the model performance based on observation data, and estimates the uncertainties from different sources especially those associated with parameters. Such a model system requires large computing resources and often have to be run on High Performance Computers (HPC). The recently developed WRF-Hydro modeling system provides a significant advancement in the capability to simulate regional water cycles more completely. The WRF-Hydro model has a large range of parameters such as those in the input table files — GENPARM.TBL, SOILPARM.TBL and CHANPARM.TBL — and several distributed scaling factors such as OVROUGHRTFAC. These parameters affect the behavior and outputs of the model and thus may need to be calibrated against the observations in order to obtain a good modeling performance. Having a parameter calibration tool specifically for automate calibration and uncertainty estimates of WRF-Hydro model can provide significant convenience for the modeling community. In this study, we developed a customized tool using the parallel version of the model-independent parameter estimation and uncertainty analysis tool, PEST, to enabled it to run on HPC with PBS and SLURM workload manager and job scheduler. We also developed a series of PEST input file templates that are specifically for WRF-Hydro model calibration and uncertainty analysis. Here we will present a flood case study occurred in April 2013 over Midwest. The sensitivity and uncertainties are analyzed using the customized PEST tool we developed.

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

Performance Assessment of New Land-Surface and Planetary Boundary Layer Physics in the WRF-ARW

Science.gov (United States)

The Pleim-Xiu land surface model, Pleim surface layer scheme, and Asymmetric Convective Model (version 2) are now options in version 3.0 of the Weather Research and Forecasting model (WRF) Advanced Research WRF (ARW) core. These physics parameterizations were developed for the f...

On the Dependence of Cloud Feedbacks on Physical Parameterizations in WRF Aquaplanet Simulations

Science.gov (United States)

Cesana, Grégory; Suselj, Kay; Brient, Florent

2017-10-01

We investigate the effects of physical parameterizations on cloud feedback uncertainty in response to climate change. For this purpose, we construct an ensemble of eight aquaplanet simulations using the Weather Research and Forecasting (WRF) model. In each WRF-derived simulation, we replace only one parameterization at a time while all other parameters remain identical. By doing so, we aim to (i) reproduce cloud feedback uncertainty from state-of-the-art climate models and (ii) understand how parametrizations impact cloud feedbacks. Our results demonstrate that this ensemble of WRF simulations, which differ only in physical parameterizations, replicates the range of cloud feedback uncertainty found in state-of-the-art climate models. We show that microphysics and convective parameterizations govern the magnitude and sign of cloud feedbacks, mostly due to tropical low-level clouds in subsidence regimes. Finally, this study highlights the advantages of using WRF to analyze cloud feedback mechanisms owing to its plug-and-play parameterization capability.

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

Seasonal Characteristics of Widespread Ozone Pollution in China and India: Current Model Capabilities and Source Attributions

Science.gov (United States)

Gao, M.; Song, S.; Beig, G.; Zhang, H.; Hu, J.; Ying, Q.; McElroy, M. B.

2017-12-01

Fast urbanization and industrialization in China and India have led to severe ozone pollution, threatening public health in these densely populated countries. We show the spatial and seasonal characteristics of ozone concentrations using nation-wide observations for these two countries in 2013. We used the Weather Research and Forecasting model coupled to chemistry (WRF-Chem) to conduct one-year simulations and to evaluate how current models capture the important photochemical processes using the exhaustive available datasets in China and India, including surface measurements, ozonesonde data and satellite retrievals. We also employed the factor separation approach to distinguish the contributions of different sectors to ozone during different seasons. The back trajectory model FLEXPART was applied to investigate the role of transport in highly polluted regions (e.g., North China Plain, Yangtze River delta, and Pearl River Delta) during different seasons. Preliminary results indicate that the WRF-Chem model provides a satisfactory representation of the temporal and spatial variations of ozone for both China and India. The factor separation approach offers valuable insights into relevant sources of ozone for both countries providing valuable guidance for policy options designed to mitigate the related problem.

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...

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...

Analysis of Hurricane Irene’s Wind Field Using the Advanced Research Weather Research and Forecast (WRF-ARW Model

Directory of Open Access Journals (Sweden)

Alfred M. Klausmann

2014-01-01

Full Text Available Hurricane Irene caused widespread and significant impacts along the U.S. east coast during 27–29 August 2011. During this period, the storm moved across eastern North Carolina and then tracked northward crossing into Long Island and western New England. Impacts included severe flooding from the mid-Atlantic states into eastern New York and western New England, widespread wind damage and power outages across a large portion of southern and central New England, and a major storm surge along portions of the Long Island coast. The objective of this study was to conduct retrospective simulations using the Advanced Research Weather Research and Forecast (WRF-ARW model in an effort to reconstruct the storm’s surface wind field during the period of 27–29 August 2011. The goal was to evaluate how to use the WRF modeling system as a tool for reconstructing the surface wind field from historical storm events to support storm surge studies. The results suggest that, with even modest data assimilation applied to these simulations, the model was able to resolve the detailed structure of the storm, the storm track, and the spatial surface wind field pattern very well. The WRF model shows real potential for being used as a tool to analyze historical storm events to support storm surge studies.

Urban Heat Island Simulations in Guangzhou, China, Using the Coupled WRF/UCM Model with a Land Use Map Extracted from Remote Sensing Data

Directory of Open Access Journals (Sweden)

Guang Chen

2016-07-01

Full Text Available The Weather Research and Forecasting (WRF model coupled with an Urban Canopy Model (UCM was used for studying urban environmental issues. Because land use data employed in the WRF model do not agree with the current situation around Guangzhou, China, the performance of WRF/UCM with new land-use data extracted from Remote Sensing (RS data was evaluated in early August 2012. Results from simulations reveal that experiments with the extracted data are capable of reasonable reproductions of the majority of the observed temporal characteristics of the 2-m temperature, and can capture the characteristics of Urban Heat Island (UHI. The “UCM_12” simulation, which employed the extracted land-use data with the WRF/UCM model, provided the best reproduction of the 2-m temperature data evolution and the smallest minimum absolute average error when compared with the other two experiments without coupled UCM. The contributions of various factors to the UHI effect were analyzed by comparing the energy equilibrium processes of “UCM_12” in urban and suburban areas. Analysis revealed that energy equilibrium processes with new land use data can explain the diurnal character of the UHI intensity variation. Furthermore, land use data extracted from RS can be used to simulate the UHI.

Combined impacts of nitrous acid and nitryl chloride on lower-tropospheric ozone: new module development in WRF-Chem and application to China

Directory of Open Access Journals (Sweden)

L. Zhang

2017-08-01

Full Text Available Nitrous acid (HONO and nitryl chloride (ClNO2 – through their photolysis – can have profound effects on the nitrogen cycle and oxidation capacity of the lower troposphere. Previous numerical studies have separately considered and investigated the sources/processes of these compounds and their roles in the fate of reactive nitrogen and the production of ozone (O3, but their combined impact on the chemistry of the lower part of the troposphere has not been addressed yet. In this study, we updated the WRF-Chem model with the currently known sources and chemistry of HONO and chlorine in a new chemical mechanism (CBMZ_ReNOM, and applied it to a study of the combined effects of HONO and ClNO2 on summertime O3 in the boundary layer over China. We simulated the spatial distributions of HONO, ClNO2, and related compounds at the surface and within the lower troposphere. The results showed that the modeled HONO levels reached up to 800–1800 ppt at the surface (0–30 m over the North China Plain (NCP, the Yangtze River Delta (YRD, and the Pearl River Delta (PRD regions and that HONO was concentrated within a 0–200 m layer. In comparison, the simulated surface ClNO2 mixing ratio was around 800–1500 ppt over the NCP, YRD, and central China regions and was predominantly present in a 0–600 m layer. HONO enhanced daytime ROx (OH + HO2 + RO2 and O3 at the surface (0–30 m by 2.8–4.6 ppt (28–37 % and 2.9–6.2 ppb (6–13 %, respectively, over the three most developed regions, whereas ClNO2 increased surface O3 in the NCP and YRD regions by 2.4–3.3 ppb (or 5–6 % and it also had a significant impact (3–6 % on above-surface O3 within 200–500 m. The combined effects increased surface O3 by 11.5, 13.5, and 13.3 % in the NCP, YRD, and PRD regions, respectively. Over the boundary layer (0–1000 m, the HONO and ClNO2 enhanced O3 by up to 5.1 and 3.2 %, respectively, and their combined effect increased O

Joint atmospheric-terrestrial water balances for East Africa: a WRF-Hydro case study for the upper Tana River basin

Science.gov (United States)

Kerandi, Noah; Arnault, Joel; Laux, Patrick; Wagner, Sven; Kitheka, Johnson; Kunstmann, Harald

2018-02-01

For an improved understanding of the hydrometeorological conditions of the Tana River basin of Kenya, East Africa, its joint atmospheric-terrestrial water balances are investigated. This is achieved through the application of the Weather Research and Forecasting (WRF) and the fully coupled WRF-Hydro modeling system over the Mathioya-Sagana subcatchment (3279 km2) and its surroundings in the upper Tana River basin for 4 years (2011-2014). The model setup consists of an outer domain at 25 km (East Africa) and an inner one at 5-km (Mathioya-Sagana subcatchment) horizontal resolution. The WRF-Hydro inner domain is enhanced with hydrological routing at 500-m horizontal resolution. The results from the fully coupled modeling system are compared to those of the WRF-only model. The coupled WRF-Hydro slightly reduces precipitation, evapotranspiration, and the soil water storage but increases runoff. The total precipitation from March to May and October to December for WRF-only (974 mm/year) and coupled WRF-Hydro (940 mm/year) is closer to that derived from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data (989 mm/year) than from the TRMM (795 mm/year) precipitation product. The coupled WRF-Hydro-accumulated discharge (323 mm/year) is close to that observed (333 mm/year). However, the coupled WRF-Hydro underestimates the observed peak flows registering low but acceptable NSE (0.02) and RSR (0.99) at daily time step. The precipitation recycling and efficiency measures between WRF-only and coupled WRF-Hydro are very close and small. This suggests that most of precipitation in the region comes from moisture advection from the outside of the analysis domain, indicating a minor impact of potential land-precipitation feedback mechanisms in this case. The coupled WRF-Hydro nonetheless serves as a tool in quantifying the atmospheric-terrestrial water balance in this region.

A Step towards a Sharable Community Knowledge Base for WRF Settings -Developing a WRF Setting Methodology based on a case study in a Torrential Rainfall Event

Science.gov (United States)

CHU, Q.; Xu, Z.; Zhuo, L.; Han, D.

2016-12-01

Increased requirements for interactions between different disciplines and readily access to the numerical weather forecasting system featured with portability and extensibility have made useful contribution to the increases of downstream model users in WRF over recent years. For these users, a knowledge base classified by the representative events would be much helpful. This is because the determination of model settings is regarded as the most important steps in WRF. However, such a process is generally time-consuming, even if with a high computational platform. As such, we propose a sharable proper lookup table on WRF domain settings and corresponding procedures based on a representative torrential rainfall event in Beijing, China. It has been found that WRF's simulations' drift away from the input lateral boundary conditions can be significantly reduced with the adjustment of the domain settings. Among all the impact factors, the placement of nested domain can not only affect the moving speed and angle of the storm-center, but also the location and amount of heavy-rain-belt which can only be detected with adjusted spatial resolutions. Spin-up time is also considered in the model settings, which is demonstrated to have the most obvious influence on the accuracy of the simulations. This conclusion is made based on the large diversity of spatial distributions of precipitation, in terms of the amount of heavy rain varied from -30% to 58% among each experiment. After following all the procedures, the variations of domain settings have minimal effect on the modeling and show the best correlation (larger than 0.65) with fusion observations. So the model settings, including domain size covering the greater Beijing area, 1:5:5 downscaling ratio, 57 vertical levels with top of 50hpa and 60h spin-up time, are found suitable for predicting the similar convective torrential rainfall event in Beijing area. We hope that the procedure for building the community WRF knowledge

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

Simulation of the effects of aerosol on mixed-phase orographic clouds using the WRF model with a detailed bin microphysics scheme

Science.gov (United States)

Xiao, Hui; Yin, Yan; Jin, Lianji; Chen, Qian; Chen, Jinghua

2015-08-01

The Weather Research Forecast (WRF) mesoscale model coupled with a detailed bin microphysics scheme is used to investigate the impact of aerosol particles serving as cloud condensation nuclei and ice nuclei on orographic clouds and precipitation. A mixed-phase orographic cloud developed under two scenarios of aerosol (a typical continental background and a relatively polluted urban condition) and ice nuclei over an idealized mountain is simulated. The results show that, when the initial aerosol condition is changed from the relatively clean case to the polluted scenario, more droplets are activated, leading to a delay in precipitation, but the precipitation amount over the terrain is increased by about 10%. A detailed analysis of the microphysical processes indicates that ice-phase particles play an important role in cloud development, and their contribution to precipitation becomes more important with increasing aerosol particle concentrations. The growth of ice-phase particles through riming and Wegener-Bergeron-Findeisen regime is more effective under more polluted conditions, mainly due to the increased number of droplets with a diameter of 10-30 µm. Sensitivity tests also show that a tenfold increase in the concentration of ice crystals formed from ice nucleation leads to about 7% increase in precipitation, and the sensitivity of the precipitation to changes in the concentration and size distribution of aerosol particles is becoming less pronounced when the concentration of ice crystals is also increased.

Downscaling with a nested regional climate model in near-surface fields over the contiguous United States: WRF dynamical downscaling

Energy Technology Data Exchange (ETDEWEB)

Wang, Jiali [Environmental Science Division, Argonne National Laboratory, Argonne Illinois USA; Kotamarthi, Veerabhadra R. [Environmental Science Division, Argonne National Laboratory, Argonne Illinois USA

2014-07-27

The Weather Research and Forecasting (WRF) model is used for dynamic downscaling of 2.5 degree National Centers for Environmental Prediction-U.S. Department of Energy Reanalysis II (NCEP-R2) data for 1980-2010 at 12 km resolution over most of North America. The model's performance for surface air temperature and precipitation is evaluated by comparison with high-resolution observational data sets. The model's ability to add value is investigated by comparison with NCEP-R2 data and a 50 km regional climate simulation. The causes for major model bias are studied through additional sensitivity experiments with various model setup/integration approaches and physics representations. The WRF captures the main features of the spatial patterns and annual cycles of air temperature and precipitation over most of the contiguous United States. However, simulated air temperatures over the south central region and precipitation over the Great Plains and the Southwest have significant biases. Allowing longer spin-up time, reducing the nudging strength, or replacing the WRF Single-Moment 6-class microphysics with Morrison microphysics reduces the bias over some subregions. However, replacing the Grell-Devenyi cumulus parameterization with Kain-Fritsch shows no improvement. The 12 km simulation does add value above the NCEP-R2 data and the 50 km simulation over mountainous and coastal zones.

Literature information in PubChem: associations between PubChem records and scientific articles.

Science.gov (United States)

Kim, Sunghwan; Thiessen, Paul A; Cheng, Tiejun; Yu, Bo; Shoemaker, Benjamin A; Wang, Jiyao; Bolton, Evan E; Wang, Yanli; Bryant, Stephen H

2016-01-01

PubChem is an open archive consisting of a set of three primary public databases (BioAssay, Compound, and Substance). It contains information on a broad range of chemical entities, including small molecules, lipids, carbohydrates, and (chemically modified) amino acid and nucleic acid sequences (including siRNA and miRNA). Currently (as of Nov. 2015), PubChem contains more than 150 million depositor-provided chemical substance descriptions, 60 million unique chemical structures, and 225 million biological activity test results provided from over 1 million biological assay records. Many PubChem records (substances, compounds, and assays) include depositor-provided cross-references to scientific articles in PubMed. Some PubChem contributors provide bioactivity data extracted from scientific articles. Literature-derived bioactivity data complement high-throughput screening (HTS) data from the concluded NIH Molecular Libraries Program and other HTS projects. Some journals provide PubChem with information on chemicals that appear in their newly published articles, enabling concurrent publication of scientific articles in journals and associated data in public databases. In addition, PubChem links records to PubMed articles indexed with the Medical Subject Heading (MeSH) controlled vocabulary thesaurus. Literature information, both provided by depositors and derived from MeSH annotations, can be accessed using PubChem's web interfaces, enabling users to explore information available in literature related to PubChem records beyond typical web search results. Graphical abstractLiterature information for PubChem records is derived from various sources.

Study of local winds over Tehran using WRF in ideal conditions

Directory of Open Access Journals (Sweden)

I Soltanzadeh

2011-09-01

Full Text Available   Wind is the carrier of pollutants and any other gaseous or particle matters in the atmosphere. Stable atmosphere with low wind provides favourable conditions for high contamination of pollutants in urban areas. The importance of mesoscale atmospheric flows in air pollution dispersion has been recognized in the past three decades and has been the focus of intensive research; both observational and numerical. Mesoscale or local scale circulations are more prominent when the synoptic pressure gradients are weak, allowing horizontal temperature contrasts to develop, which in turn lead to mesoscale pressure perturbations. Tehran, a city which is situated at the southern foothills of the Alborz Mountain chain has an average elevation of 1500m, and covers an area of 864 km2. Alborz Mountains have a significant influence on the dynamics and thermodynamic modification of wind regime over the city. At the same time, the Urban Heat Island effect (UHI can cause its own mesoscale flow, complicating an already complex local scale flow. The topography and the urban fabric can cause slope flows, mountain flows, and valley flows amongst many other factors. Th is paper focuses on the use of state-of-the-art atmospheric numerical model – The Weather Research and Forecasting (WRF – in an ideal situation to study the characteristics of the mesoscale flow systems that prevail over Tehran when air quality is unfavourable. So average sound of Radiosonde at Mehrabad station, for almost all the fair days of cold seasons from 2005 to 2008 was selected as an ideal initial condition and boundary condition with 10 × 10 km spatial and 12-hour temporal resolution. The simulations were carried out for a 3-day period in December 2005 when an aircraft , due to low visibility caused by high concentration of air pollution, crashed 2 miles away from the end of runway into an inhabited area. Three simulations were prepared. For the first experiment, called control run, we

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.

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.

Development of a methodology for probable maximum precipitation estimation over the American River watershed using the WRF model

Science.gov (United States)

Tan, Elcin

A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the

Hydrologic Modeling at the National Water Center: Operational Implementation of the WRF-Hydro Model to support National Weather Service Hydrology

Science.gov (United States)

Cosgrove, B.; Gochis, D.; Clark, E. P.; Cui, Z.; Dugger, A. L.; Fall, G. M.; Feng, X.; Fresch, M. A.; Gourley, J. J.; Khan, S.; Kitzmiller, D.; Lee, H. S.; Liu, Y.; McCreight, J. L.; Newman, A. J.; Oubeidillah, A.; Pan, L.; Pham, C.; Salas, F.; Sampson, K. M.; Smith, M.; Sood, G.; Wood, A.; Yates, D. N.; Yu, W.; Zhang, Y.

2015-12-01

The National Weather Service (NWS) National Water Center(NWC) is collaborating with the NWS National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) to implement a first-of-its-kind operational instance of the Weather Research and Forecasting (WRF)-Hydro model over the Continental United States (CONUS) and contributing drainage areas on the NWS Weather and Climate Operational Supercomputing System (WCOSS) supercomputer. The system will provide seamless, high-resolution, continuously cycling forecasts of streamflow and other hydrologic outputs of value from both deterministic- and ensemble-type runs. WRF-Hydro will form the core of the NWC national water modeling strategy, supporting NWS hydrologic forecast operations along with emergency response and water management efforts of partner agencies. Input and output from the system will be comprehensively verified via the NWC Water Resource Evaluation Service. Hydrologic events occur on a wide range of temporal scales, from fast acting flash floods, to long-term flow events impacting water supply. In order to capture this range of events, the initial operational WRF-Hydro configuration will feature 1) hourly analysis runs, 2) short-and medium-range deterministic forecasts out to two day and ten day horizons and 3) long-range ensemble forecasts out to 30 days. All three of these configurations are underpinned by a 1km execution of the NoahMP land surface model, with channel routing taking place on 2.67 million NHDPlusV2 catchments covering the CONUS and contributing areas. Additionally, the short- and medium-range forecasts runs will feature surface and sub-surface routing on a 250m grid, while the hourly analyses will feature this same 250m routing in addition to nudging-based assimilation of US Geological Survey (USGS) streamflow observations. A limited number of major reservoirs will be configured within the model to begin to represent the first-order impacts of

The SPoRT-WRF: Evaluating the Impact of NASA Datasets on Convective Forecasts

Science.gov (United States)

Zavodsky, Bradley; Kozlowski, Danielle; Case, Jonathan; Molthan, Andrew

2012-01-01

Short-term Prediction Research and Transition (SPoRT) seeks to improve short-term, regional weather forecasts using unique NASA products and capabilities SPoRT has developed a unique, real-time configuration of the NASA Unified Weather Research and Forecasting (WRF)WRF (ARW) that integrates all SPoRT modeling research data: (1) 2-km SPoRT Sea Surface Temperature (SST) Composite, (2) 3-km LIS with 1-km Greenness Vegetation Fraction (GVFs) (3) 45-km AIRS retrieved profiles. Transitioned this real-time forecast to NOAA's Hazardous Weather Testbed (HWT) as deterministic model at Experimental Forecast Program (EFP). Feedback from forecasters/participants and internal evaluation of SPoRT-WRF shows a cool, dry bias that appears to suppress convection likely related to methodology for assimilation of AIRS profiles Version 2 of the SPoRT-WRF will premier at the 2012 EFP and include NASA physics, cycling data assimilation methodology, better coverage of precipitation forcing, and new GVFs

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

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)

Dynamical downscaling of ERA-40 in complex terrain using the WRF regional climate model

Energy Technology Data Exchange (ETDEWEB)

Heikkilae, U. [Bjerknes Centre for Climate Research, Uni Bjerknes Centre, Bergen (Norway); Sandvik, A. [Bjerknes Centre for Climate Research, Institute for Marine Research (IMR), Bergen (Norway); Sorteberg, A. [University of Bergen, Geophysical Institute, Bergen (Norway)

2011-10-15

Results from a first-time employment of the WRF regional climate model to climatological simulations in Europe are presented. The ERA-40 reanalysis (resolution 1 ) has been downscaled to a horizontal resolution of 30 and 10 km for the period of 1961-1990. This model setup includes the whole North Atlantic in the 30 km domain and spectral nudging is used to keep the large scales consistent with the driving ERA-40 reanalysis. The model results are compared against an extensive observational network of surface variables in complex terrain in Norway. The comparison shows that the WRF model is able to add significant detail to the representation of precipitation and 2-m temperature of the ERA-40 reanalysis. Especially the geographical distribution, wet day frequency and extreme values of precipitation are highly improved due to the better representation of the orography. Refining the resolution from 30 to 10 km further increases the skill of the model, especially in case of precipitation. Our results indicate that the use of 10-km resolution is advantageous for producing regional future climate projections. Use of a large domain and spectral nudging seems to be useful in reproducing the extreme precipitation events due to the better resolved synoptic scale features over the North Atlantic, and also helps to reduce the large regional temperature biases over Norway. This study presents a high-resolution, high-quality climatological data set useful for reference climate impact studies. (orig.)

Mechanisms and Effects of Summertime Transport of African Dust Through the Tokar Mountain Gap to the Red Sea and Arabian Peninsula

Science.gov (United States)

Kalenderski, S.; Stenchikov, G. L.

2015-12-01

Very high dust loading over the Red Sea region in summer strongly affects the nutrition balance and thermal and dynamic regimes of the sea. The observations suggest that small-scale local dynamic and orographic effects, from both the Arabian and African sides, strongly contribute to dust plume formation. To better understand and quantify these processes we present here the first high resolution modeling study of the dust outbreak phenomena in June 2012 over East Africa, the Red Sea, and the Arabian Peninsula using the WRF-Chem model. We identified several dust generating dynamical processes that range from convective to synoptic scales, including: synoptic cyclones, nocturnal low-level jets, and cold pools of mesoscale convective systems. The simulations reveal an eastward transport of African dust across the Red Sea. Over the northern part of the Red Sea most of the dust transport occurs beyond 2 km above ground level and is strengthened by a pressure gradient formed by low pressure over the eastern Mediterranean and high pressure over the Arabian Peninsula. Across the central and southern parts of the Red Sea dust is mostly transported below 2 km height. During the study period dust is a dominant contributor (87%) to aerosol optical depth (AOD), producing a domain average cooling effect of -12.1 W m-2 at surface, a warming of 7.1 W m-2 in the atmosphere, and a residual cooling of -4.9 W m-2 at the top of the atmosphere. WRF-Chem simulations demonstrate that both dry and wet deposition processes contribute significantly to dust removal from the atmosphere. During the dust outbreak 49.2 Tg of dust deposits within the calculation domain, which is approximately 90% of the total dust emission of 54.5 Tg. Model results compare well with available ground-based and satellite observations but generally underestimate the observed AOD maximum values.

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.

Urban Flow and Pollutant Dispersion Simulation with Multi-scale coupling of Meteorological Model with Computational Fluid Dynamic Analysis

Science.gov (United States)

Liu, Yushi; Poh, Hee Joo

2014-11-01

The Computational Fluid Dynamics analysis has become increasingly important in modern urban planning in order to create highly livable city. This paper presents a multi-scale modeling methodology which couples Weather Research and Forecasting (WRF) Model with open source CFD simulation tool, OpenFOAM. This coupling enables the simulation of the wind flow and pollutant dispersion in urban built-up area with high resolution mesh. In this methodology meso-scale model WRF provides the boundary condition for the micro-scale CFD model OpenFOAM. The advantage is that the realistic weather condition is taken into account in the CFD simulation and complexity of building layout can be handled with ease by meshing utility of OpenFOAM. The result is validated against the Joint Urban 2003 Tracer Field Tests in Oklahoma City and there is reasonably good agreement between the CFD simulation and field observation. The coupling of WRF- OpenFOAM provide urban planners with reliable environmental modeling tool in actual urban built-up area; and it can be further extended with consideration of future weather conditions for the scenario studies on climate change impact.

Assessment of the Aerosol Optics Component of the Coupled WRF-CMAQ Model usingCARES Field Campaign data and a Single Column Model

Science.gov (United States)

The Carbonaceous Aerosols and Radiative Effects Study (CARES), a field campaign held in central California in June 2010, provides a unique opportunity to assess the aerosol optics modeling component of the two-way coupled Weather Research and Forecasting (WRF) – Community Multisc...

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.

High-resolution dynamical downscaling of re-analysis data over the Kerguelen Islands using the WRF model

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Fonseca, Ricardo; Martín-Torres, Javier

2018-03-01

We have used the Weather Research and Forecasting (WRF) model to simulate the climate of the Kerguelen Islands (49° S, 69° E) and investigate its inter-annual variability. Here, we have dynamically downscaled 30 years of the Climate Forecast System Reanalysis (CFSR) over these islands at 3-km horizontal resolution. The model output is found to agree well with the station and radiosonde data at the Port-aux-Français station, the only location in the islands for which observational data is available. An analysis of the seasonal mean WRF data showed a general increase in precipitation and decrease in temperature with elevation. The largest seasonal rainfall amounts occur at the highest elevations of the Cook Ice Cap in winter where the summer mean temperature is around 0 °C. Five modes of variability are considered: conventional and Modoki El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Subtropical IOD (SIOD) and Southern Annular Mode (SAM). It is concluded that a key mechanism by which these modes impact the local climate is through interaction with the diurnal cycle in particular in the summer season when it has a larger magnitude. One of the most affected regions is the area just to the east of the Cook Ice Cap extending into the lower elevations between the Gallieni and Courbet Peninsulas. The WRF simulation shows that despite the small annual variability, the atmospheric flow in the Kerguelen Islands is rather complex which may also be the case for the other islands located in the Southern Hemisphere at similar latitudes.

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

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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.

The Sensitivity of WRF Daily Summertime Simulations over West Africa to Alternative Parameterizations. Part 1: African Wave Circulation

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Noble, Erik; Druyan, Leonard M.; Fulakeza, Matthew

2014-01-01

The performance of the NCAR Weather Research and Forecasting Model (WRF) as a West African regional-atmospheric model is evaluated. The study tests the sensitivity of WRF-simulated vorticity maxima associated with African easterly waves to 64 combinations of alternative parameterizations in a series of simulations in September. In all, 104 simulations of 12-day duration during 11 consecutive years are examined. The 64 combinations combine WRF parameterizations of cumulus convection, radiation transfer, surface hydrology, and PBL physics. Simulated daily and mean circulation results are validated against NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and NCEP/Department of Energy Global Reanalysis 2. Precipitation is considered in a second part of this two-part paper. A wide range of 700-hPa vorticity validation scores demonstrates the influence of alternative parameterizations. The best WRF performers achieve correlations against reanalysis of 0.40-0.60 and realistic amplitudes of spatiotemporal variability for the 2006 focus year while a parallel-benchmark simulation by the NASA Regional Model-3 (RM3) achieves higher correlations, but less realistic spatiotemporal variability. The largest favorable impact on WRF-vorticity validation is achieved by selecting the Grell-Devenyi cumulus convection scheme, resulting in higher correlations against reanalysis than simulations using the Kain-Fritch convection. Other parameterizations have less-obvious impact, although WRF configurations incorporating one surface model and PBL scheme consistently performed poorly. A comparison of reanalysis circulation against two NASA radiosonde stations confirms that both reanalyses represent observations well enough to validate the WRF results. Validation statistics for optimized WRF configurations simulating the parallel period during 10 additional years are less favorable than for 2006.

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

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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

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

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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 Atmospheric InfraRed Sounder (AIRS) Profiles using WRF-Var

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Zavodsky, Brad; Jedlovec, Gary J.; Lapenta, William

2008-01-01

The Weather Research and Forecasting (WRF) model contains a three-dimensional variational (3DVAR) assimilation system (WRF-Var), which allows a user to join data from multiple sources into one coherent analysis. WRF-Var combines observations with a background field traditionally generated using a previous model forecast through minimization of a cost function. In data sparse regions, remotely-sensed observations may be able to improve analyses and produce improved forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The combined AIRS/AMSU system provides radiance measurements used as input to a sophisticated retrieval scheme which has been shown to produce temperature profiles with an accuracy of 1 K over 1 km layers and humidity profiles with accuracy of 15% in 2 km layers in both clear and partly cloudy conditions. The retrieval algorithm also provides estimates of the accuracy of the retrieved values at each pressure level, allowing the user to select profiles based on the required error tolerances of the application. The purpose of this paper is to describe a procedure to optimally assimilate high-resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type using gen_be and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics in the WRF-Var. The AIRS thermodynamic profiles are obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators are used to select the highest quality temperature and moisture

Short-term Wind Forecasting at Wind Farms using WRF-LES and Actuator Disk Model

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Kirkil, Gokhan

2017-04-01

Short-term wind forecasts are obtained for a wind farm on a mountainous terrain using WRF-LES. Multi-scale simulations are also performed using different PBL parameterizations. Turbines are parameterized using Actuator Disc Model. LES models improved the forecasts. Statistical error analysis is performed and ramp events are analyzed. Complex topography of the study area affects model performance, especially the accuracy of wind forecasts were poor for cross valley-mountain flows. By means of LES, we gain new knowledge about the sources of spatial and temporal variability of wind fluctuations such as the configuration of wind turbines.

Preliminary validation of WRF model in two Arctic fjords, Hornsund and Porsanger

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Aniskiewicz, Paulina; Stramska, Małgorzata

2017-04-01

Our research is focused on development of efficient modeling system for arctic fjords. This tool should include high-resolution meteorological data derived using downscaling approach. In this presentation we have focused on modeling, with high spatial resolution, of the meteorological conditions in two Arctic fjords: Hornsund (H), located in the western part of Svalbard archipelago and Porsanger (P) located in the coastal waters of the Barents Sea. The atmospheric downscaling is based on The Weather Research and Forecasting Model (WRF, www.wrf-model.org) with polar stereographic projection. We have created two parent domains with grid point distances of about 3.2 km (P) and 3.0 km (H) and with nested domains (almost 5 times higher resolution than parent domains). We tested what is the impact of the spatial resolution of the model on derived meteorological quantities. For both fjords the input topography data resolution is 30 sec. To validate the results we have used meteorological data from the Norwegian Meteorological Institute for stations Lakselv (L) and Honningsvåg (Ho) located in the inner and outer parts of the Porsanger fjord as well as from station in the outer part of the Hornsund fjord. We have estimated coefficients of determination (r2), statistical errors (St) and systematic errors (Sy) between measured and modelled air temperature and wind speed at each station. This approach will allow us to create high resolution spatially variable meteorological fields that will serve as forcing for numerical models of the fjords. We will investigate the role of different meteorological quantities (e. g. wind, solar insolation, precipitation) on hydrohraphic processes in fjords. The project has been financed from the funds of the Leading National Research Centre (KNOW) received by the Centre for Polar Studies for the period 2014-2018. This work was also funded by the Norway Grants (NCBR contract No. 201985, project NORDFLUX). Partial support comes from the

A Study of the Oklahoma City Urban Heat Island Effect Using a WRF/Single-Layer Urban Canopy Model, a Joint Urban 2003 Field Campaign, and MODIS Satellite Observations

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Hengyue Zhang

2017-09-01

Full Text Available The urban heat island effect (UHI for inner land regions was investigated using satellite data, ground observations, and simulations with an Single-Layer Urban Canopy Parameterization (SLUCP coupled into the regional Weather Research Forecasting model (WRF, http://wrf-model.org/index.php. Specifically, using the satellite-observed surface skin temperatures (Tskin, the intensity of the UHI was first compared for two inland cities (Xi’an City, China, and Oklahoma City (OKC, which have different city populations and building densities. The larger population density and larger building density in Xi’an lead to a stronger skin-level UHI by 2 °C. However, the ground observed 2 m surface air temperature (Tair observations showed an urban cooling island effect (UCI over the downtown region in OKC during the daytime of 19 July 2003, from a DOE field campaign (Joint Urban 2003. To understand this contrast between satellite-based Tskin and ground-based Tair, a sensitivity study using WRF/SLUCP was analyzed. The model reproduced a UCI in OKC. Furthermore, WRF/Noah/SLUCM simulations were also compared with the Joint Urban 2003 ground observations, including wind speeds, wind directions, and energy fluxes. Although the WRF/SLUCM model failed to simulate these variables accurately, it reproduced the diurnal variations of surface temperatures, wind speeds, wind directions, and energy fluxes reasonably well.

Case Study of the California Low Level Coastal Jet Comparisons Between Observed and Model-Estimated Winds and Temperatures using WRF and COAMPS

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Tomé, Ricardo; Semedo, Alvaro; Ranjha, Raza; Tjernström, Michael; Svensson, Gunilla

2010-05-01

A low level coastal jet (LLCJ) is a low-troposphereic wind feature driven by the pressure gradient produced by a sharp contrast between high temperatures over land and lower temperatures over sea. This feature has been identified and studied in several areas of the world, where such a land-sea temperature contrast exist: off the coast of Somalia, near Lima, Peru, off the Mediterranean coast of Spain, in the Southwest coast of Africa, or in the South China Sea coast. Nevertheless, the California LLCJ is probably the most studied coastal jet in the world, with several studies available in the literature. Coastal jets have a notorious impact on coastal areas. Climatologically they are associated with coastal upwelling processes. The major coastal fishing grounds in the world are usually in areas of upwelling, and the abundance of fish at the surface is supported by the upwelled nutrient-rich waters from deeper levels. The effect of this upwelled water to the fishing industry and to the habitat of an enormous diversity of marine life is of paramount importance, and has led to numerous studies in this field. Littoral areas are usually densely populated, and often airports are built in areas where a LLCJ may occur. Thus, aviation operations are deeply influenced by this weather feature, which has a significant impact on the takeoff and landing of airplanes. Therefore the forecasting of LLCJ features is very important for several reasons.The forecasting skills of mesoscale models, while challenging in any region, become particularly complex near coastlines, where processes associated with the coastal boundary add additional complexity: interaction of the flow with the coastal orography, sharp sea-land temperature gradients, highly baroclinic environment, complex air-sea exchanging processes, etc. The purpose of this study is to assess the forecasting skills of the limited-area models WRF (Weather Research and Forecasting) and COAMPS® (Coupled Ocean-Atmosphere Mesoscale

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

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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.

AutoClickChem: click chemistry in silico.

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Jacob D Durrant

Full Text Available Academic researchers and many in industry often lack the financial resources available to scientists working in "big pharma." High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu.

AutoClickChem: click chemistry in silico.

Science.gov (United States)

Durrant, Jacob D; McCammon, J Andrew

2012-01-01

Academic researchers and many in industry often lack the financial resources available to scientists working in "big pharma." High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu.

Simulated cold bias being improved by using MODIS time-varying albedo in the Tibetan Plateau in WRF model

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Meng, X.; Lyu, S.; Zhang, T.; Zhao, L.; Li, Z.; Han, B.; Li, S.; Ma, D.; Chen, H.; Ao, Y.; Luo, S.; Shen, Y.; Guo, J.; Wen, L.

2018-04-01

Systematic cold biases exist in the simulation for 2 m air temperature in the Tibetan Plateau (TP) when using regional climate models and global atmospheric general circulation models. We updated the albedo in the Weather Research and Forecasting (WRF) Model lower boundary condition using the Global LAnd Surface Satellite Moderate-Resolution Imaging Spectroradiometer albedo products and demonstrated evident improvement for cold temperature biases in the TP. It is the large overestimation of albedo in winter and spring in the WRF model that resulted in the large cold temperature biases. The overestimated albedo was caused by the simulated precipitation biases and over-parameterization of snow albedo. Furthermore, light-absorbing aerosols can result in a large reduction of albedo in snow and ice cover. The results suggest the necessity of developing snow albedo parameterization using observations in the TP, where snow cover and melting are very different from other low-elevation regions, and the influence of aerosols should be considered as well. In addition to defining snow albedo, our results show an urgent call for improving precipitation simulation in the TP.

A methodology for the design and testing of atmospheric boundary layer models for wind energy applications

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J. Sanz Rodrigo

2017-02-01

Full Text Available The GEWEX Atmospheric Boundary Layer Studies (GABLS 1, 2 and 3 are used to develop a methodology for the design and testing of Reynolds-averaged Navier–Stokes (RANS atmospheric boundary layer (ABL models for wind energy applications. The first two GABLS cases are based on idealized boundary conditions and are suitable for verification purposes by comparing with results from higher-fidelity models based on large-eddy simulation. Results from three single-column RANS models, of 1st, 1.5th and 2nd turbulence closure order, show high consistency in predicting the mean flow. The third GABLS case is suitable for the study of these ABL models under realistic forcing such that validation versus observations from the Cabauw meteorological tower are possible. The case consists on a diurnal cycle that leads to a nocturnal low-level jet and addresses fundamental questions related to the definition of the large-scale forcing, the interaction of the ABL with the surface and the evaluation of model results with observations. The simulations are evaluated in terms of surface-layer fluxes and wind energy quantities of interest: rotor equivalent wind speed, hub-height wind direction, wind speed shear and wind direction veer. The characterization of mesoscale forcing is based on spatially and temporally averaged momentum budget terms from Weather Research and Forecasting (WRF simulations. These mesoscale tendencies are used to drive single-column models, which were verified previously in the first two GABLS cases, to first demonstrate that they can produce similar wind profile characteristics to the WRF simulations even though the physics are more simplified. The added value of incorporating different forcing mechanisms into microscale models is quantified by systematically removing forcing terms in the momentum and heat equations. This mesoscale-to-microscale modeling approach is affected, to a large extent, by the input uncertainties of the mesoscale

Offshore Wind Resources Assessment from Multiple Satellite Data and WRF Modeling over South China Sea

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Rui Chang

2015-01-01

Full Text Available Using accurate inputs of wind speed is crucial in wind resource assessment, as predicted power is proportional to the wind speed cubed. This study outlines a methodology for combining multiple ocean satellite winds and winds from WRF simulations in order to acquire the accurate reconstructed offshore winds which can be used for offshore wind resource assessment. First, wind speeds retrieved from Synthetic Aperture Radar (SAR and Scatterometer ASCAT images were validated against in situ measurements from seven coastal meteorological stations in South China Sea (SCS. The wind roses from the Navy Operational Global Atmospheric Prediction System (NOGAPS and ASCAT agree well with these observations from the corresponding in situ measurements. The statistical results comparing in situ wind speed and SAR-based (ASCAT-based wind speed for the whole co-located samples show a standard deviation (SD of 2.09 m/s (1.83 m/s and correlation coefficient of R 0.75 (0.80. When the offshore winds (i.e., winds directed from land to sea are excluded, the comparison results for wind speeds show an improvement of SD and R, indicating that the satellite data are more credible over the open ocean. Meanwhile, the validation of satellite winds against the same co-located mast observations shows a satisfactory level of accuracy which was similar for SAR and ASCAT winds. These satellite winds are then assimilated into the Weather Research and Forecasting (WRF Model by WRF Data Assimilation (WRFDA system. Finally, the wind resource statistics at 100 m height based on the reconstructed winds have been achieved over the study area, which fully combines the offshore wind information from multiple satellite data and numerical model. The findings presented here may be useful in future wind resource assessment based on satellite data.

Future Midwest Heat Waves in WRF

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Huber, M.; Buzan, J. R.; Yoo, J.

2017-12-01

We present heat stress results for the upper Midwest derived from convection resolving Weather Research and Forecasting (WRF) model simulations carried out for the RCP 8.5 Scenario and driven by Community Earth System Model (CESM) boundary conditions as part of the Indiana Climate Change Assessment. Using this modeling system we find widespread and severe increases in moist heat stress metrics in the Midwest by end of century. We detail scaling arguments that suggest our results are robust and not model dependent and describe potential health, welfare, and productivity implications of these results.

A multi-model approach to monitor emissions of CO2 and CO from an urban–industrial complex

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I. Super

2017-11-01

Full Text Available Monitoring urban–industrial emissions is often challenging because observations are scarce and regional atmospheric transport models are too coarse to represent the high spatiotemporal variability in the resulting concentrations. In this paper we apply a new combination of an Eulerian model (Weather Research and Forecast, WRF, with chemistry and a Gaussian plume model (Operational Priority Substances – OPS. The modelled mixing ratios are compared to observed CO2 and CO mole fractions at four sites along a transect from an urban–industrial complex (Rotterdam, the Netherlands towards rural conditions for October–December 2014. Urban plumes are well-mixed at our semi-urban location, making this location suited for an integrated emission estimate over the whole study area. The signals at our urban measurement site (with average enhancements of 11 ppm CO2 and 40 ppb CO over the baseline are highly variable due to the presence of distinct source areas dominated by road traffic/residential heating emissions or industrial activities. This causes different emission signatures that are translated into a large variability in observed ΔCO : ΔCO2 ratios, which can be used to identify dominant source types. We find that WRF-Chem is able to represent synoptic variability in CO2 and CO (e.g. the median CO2 mixing ratio is 9.7 ppm, observed, against 8.8 ppm, modelled, but it fails to reproduce the hourly variability of daytime urban plumes at the urban site (R2 up to 0.05. For the urban site, adding a plume model to the model framework is beneficial to adequately represent plume transport especially from stack emissions. The explained variance in hourly, daytime CO2 enhancements from point source emissions increases from 30 % with WRF-Chem to 52 % with WRF-Chem in combination with the most detailed OPS simulation. The simulated variability in ΔCO :  ΔCO2 ratios decreases drastically from 1.5 to 0.6 ppb ppm−1, which agrees

A multi-model approach to monitor emissions of CO2 and CO from an urban-industrial complex

Science.gov (United States)

Super, Ingrid; Denier van der Gon, Hugo A. C.; van der Molen, Michiel K.; Sterk, Hendrika A. M.; Hensen, Arjan; Peters, Wouter

2017-11-01

Monitoring urban-industrial emissions is often challenging because observations are scarce and regional atmospheric transport models are too coarse to represent the high spatiotemporal variability in the resulting concentrations. In this paper we apply a new combination of an Eulerian model (Weather Research and Forecast, WRF, with chemistry) and a Gaussian plume model (Operational Priority Substances - OPS). The modelled mixing ratios are compared to observed CO2 and CO mole fractions at four sites along a transect from an urban-industrial complex (Rotterdam, the Netherlands) towards rural conditions for October-December 2014. Urban plumes are well-mixed at our semi-urban location, making this location suited for an integrated emission estimate over the whole study area. The signals at our urban measurement site (with average enhancements of 11 ppm CO2 and 40 ppb CO over the baseline) are highly variable due to the presence of distinct source areas dominated by road traffic/residential heating emissions or industrial activities. This causes different emission signatures that are translated into a large variability in observed ΔCO : ΔCO2 ratios, which can be used to identify dominant source types. We find that WRF-Chem is able to represent synoptic variability in CO2 and CO (e.g. the median CO2 mixing ratio is 9.7 ppm, observed, against 8.8 ppm, modelled), but it fails to reproduce the hourly variability of daytime urban plumes at the urban site (R2 up to 0.05). For the urban site, adding a plume model to the model framework is beneficial to adequately represent plume transport especially from stack emissions. The explained variance in hourly, daytime CO2 enhancements from point source emissions increases from 30 % with WRF-Chem to 52 % with WRF-Chem in combination with the most detailed OPS simulation. The simulated variability in ΔCO :  ΔCO2 ratios decreases drastically from 1.5 to 0.6 ppb ppm-1, which agrees better with the observed standard

Atmospheric Turbulence Estimates from a Pulsed Lidar

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Pruis, Matthew J.; Delisi, Donald P.; Ahmad, Nash'at N.; Proctor, Fred H.

2013-01-01

Estimates of the eddy dissipation rate (EDR) were obtained from measurements made by a coherent pulsed lidar and compared with estimates from mesoscale model simulations and measurements from an in situ sonic anemometer at the Denver International Airport and with EDR estimates from the last observation time of the trailing vortex pair. The estimates of EDR from the lidar were obtained using two different methodologies. The two methodologies show consistent estimates of the vertical profiles. Comparison of EDR derived from the Weather Research and Forecast (WRF) mesoscale model with the in situ lidar estimates show good agreement during the daytime convective boundary layer, but the WRF simulations tend to overestimate EDR during the nighttime. The EDR estimates from a sonic anemometer located at 7.3 meters above ground level are approximately one order of magnitude greater than both the WRF and lidar estimates - which are from greater heights - during the daytime convective boundary layer and substantially greater during the nighttime stable boundary layer. The consistency of the EDR estimates from different methods suggests a reasonable ability to predict the temporal evolution of a spatially averaged vertical profile of EDR in an airport terminal area using a mesoscale model during the daytime convective boundary layer. In the stable nighttime boundary layer, there may be added value to EDR estimates provided by in situ lidar measurements.

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)

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

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.

Evaluation and Improvement of Polar WRF simulations using the observed atmospheric profiles in the Arctic seasonal ice zone

Science.gov (United States)

Liu, Z.; Schweiger, A. J. B.

2016-12-01

We use the Polar Weather Research and Forecasting (WRF) model to simulate atmospheric conditions during the Seasonal Ice Zone Reconnaissance Survey (SIZRS) over the Beaufort Sea in the summer since 2013. With the 119 SIZRS dropsondes in the18 cross sections along the 150W and 140W longitude lines, we evaluate the performance of WRF simulations and two forcing data sets, the ERA-Interim reanalysis and the Global Forecast System (GFS) analysis, and explore the improvement of the Polar WRF performance when the dropsonde data are assimilated using observation nudging. Polar WRF, ERA-Interim, and GFS can reproduce the general features of the observed mean atmospheric profiles, such as low-level temperature inversion, low-level jet (LLJ) and specific humidity inversion. The Polar WRF significantly improves the mean LLJ, with a lower and stronger jet and a larger turning angle than the forcing, which is likely related to the lower values of the boundary layer diffusion in WRF than in the global models such as ECMWF and GFS. The Polar WRF simulated relative humidity closely resembles the forcing datasets while having large biases compared to observations. This suggests that the performance of Polar WRF and its forecasts in this region are limited by the quality of the forcing dataset and that the assimilation of more and better-calibrated observations, such as humidity data, is critical for their improvement. We investigate the potential of assimilating the SIZRS dropsonde dataset in improving the weather forecast over the Beaufort Sea. A simple local nudging approach is adopted. Along SIZRS flight cross sections, a set of Polar WRF simulations are performed with varying number of variables and dropsonde profiles assimilated. Different model physics are tested to examine the sensitivity of different aspects of model physics, such as boundary layer schemes, cloud microphysics, and radiation parameterization, to data assimilation. The comparison of the Polar WRF runs with

The Impact of Microphysics on Intensity and Structure of Hurricanes

Science.gov (United States)

Tao, Wei-Kuo; Shi, Jainn; Lang, Steve; Peters-Lidard, Christa

2006-01-01

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. WFW 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. WFW 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 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 WW to examine the impact of six different cloud microphysical schemes on hurricane track, intensity and rainfall forecast. We are also performing the inline tracer calculation to comprehend the physical processes @e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes.

North Pacific Mesoscale Coupled Air-Ocean Simulations Compared with Observations

Energy Technology Data Exchange (ETDEWEB)

Koracin, Darko; Cerovecki, Ivana; Vellore, Ramesh; Mejia, John; Hatchett, Benjamin; McCord, Travis; McLean, Julie; Dorman, Clive

2013-04-11

Executive summary The main objective of the study was to investigate atmospheric and ocean interaction processes in the western Pacific and, in particular, effects of significant ocean heat loss in the Kuroshio and Kuroshio Extension regions on the lower and upper atmosphere. It is yet to be determined how significant are these processes are on climate scales. The understanding of these processes led us also to development of the methodology of coupling the Weather and Research Forecasting model with the Parallel Ocean Program model for western Pacific regional weather and climate simulations. We tested NCAR-developed research software Coupler 7 for coupling of the WRF and POP models and assessed its usability for regional-scale applications. We completed test simulations using the Coupler 7 framework, but implemented a standard WRF model code with options for both one- and two-way mode coupling. This type of coupling will allow us to seamlessly incorporate new WRF updates and versions in the future. We also performed a long-term WRF simulation (15 years) covering the entire North Pacific as well as high-resolution simulations of a case study which included extreme ocean heat losses in the Kuroshio and Kuroshio Extension regions. Since the extreme ocean heat loss occurs during winter cold air outbreaks (CAO), we simulated and analyzed a case study of a severe CAO event in January 2000 in detail. We found that the ocean heat loss induced by CAOs is amplified by additional advection from mesocyclones forming on the southern part of the Japan Sea. Large scale synoptic patterns with anomalously strong anticyclone over Siberia and Mongolia, deep Aleutian Low, and the Pacific subtropical ridge are a crucial setup for the CAO. It was found that the onset of the CAO is related to the breaking of atmospheric Rossby waves and vertical transport of vorticity that facilitates meridional advection. The study also indicates that intrinsic parameterization of the surface fluxes

Analysis of the ozone profile specifications in the WRF-ARW model and their impact on the simulation of direct solar radiation

Directory of Open Access Journals (Sweden)

A. Montornès

2015-03-01

Full Text Available Although ozone is an atmospheric gas with high spatial and temporal variability, mesoscale numerical weather prediction (NWP models simplify the specification of ozone concentrations used in their shortwave schemes by using a few ozone profiles. In this paper, a two-part study is presented: (i an evaluation of the quality of the ozone profiles provided for use with the shortwave schemes in the Advanced Research version of the Weather Research and Forecasting (WRF-ARW model and (ii an assessment of the impact of deficiencies in those profiles on the performance of model simulations of direct solar radiation. The first part compares simplified data sets used to specify the total ozone column in six schemes (i.e., Goddard, New Goddard, RRTMG, CAM, GFDL and Fu–Liou–Gu with the Multi-Sensor Reanalysis data set during the period 1979–2008 examining the latitudinal, longitudinal and seasonal limitations in the ozone profile specifications of each parameterization. The results indicate that the maximum deviations are over the poles and show prominent longitudinal patterns in the departures due to the lack of representation of the patterns associated with the Brewer–Dobson circulation and the quasi-stationary features forced by the land–sea distribution, respectively. In the second part, the bias in the simulated direct solar radiation due to these deviations from the simplified spatial and temporal representation of the ozone distribution is analyzed for the New Goddard and CAM schemes using the Beer–Lambert–Bouguer law and for the GFDL using empirical equations. For radiative applications those simplifications introduce spatial and temporal biases with near-zero departures over the tropics throughout the year and increasing poleward with a maximum in the high middle latitudes during the winter of each hemisphere.

Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

Science.gov (United States)

Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

2018-03-01

Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF

Modeling studies on the formation of Hurricane Helene: the impact of GPS dropwindsondes from the NAMMA 2006 field campaign

Science.gov (United States)

Folmer, Michael J.; Pasken, Robert W.; Chiao, Sen; Dunion, Jason; Halverson, Jeffrey

2016-12-01

Numerical simulations, using the weather research and forecasting (WRF) model in concert with GPS dropwindsondes released during the NASA African Monsoon Multidisciplinary Analyses 2006 Field Campaign, were conducted to provide additional insight on SAL-TC interaction. Using NCEP Final analysis datasets to initialize the WRF, a sensitivity test was performed on the assimilated (i.e., observation nudging) GPS dropwindsondes to understand the effects of individual variables (i.e., moisture, temperature, and winds) on the simulation and determine the extent of improvement when compared to available observations. The results suggested that GPS dropwindsonde temperature data provided the most significant difference in the simulated storm organization, storm strength, and synoptic environment, but all of the variables assimilated at the same time give a more representative mesoscale and synoptic picture.

Evaluation of Extratropical Cyclone Precipitation in the North Atlantic Basin: An analysis of ERA-Interim, WRF, and two CMIP5 models.

Science.gov (United States)

Booth, James F; Naud, Catherine M; Willison, Jeff

2018-03-01

The representation of extratropical cyclones (ETCs) precipitation in general circulation models (GCMs) and a weather research and forecasting (WRF) model is analyzed. This work considers the link between ETC precipitation and dynamical strength and tests if parameterized convection affects this link for ETCs in the North Atlantic Basin. Lagrangian cyclone tracks of ETCs in ERA-Interim reanalysis (ERAI), the GISS and GFDL CMIP5 models, and WRF with two horizontal resolutions are utilized in a compositing analysis. The 20-km resolution WRF model generates stronger ETCs based on surface wind speed and cyclone precipitation. The GCMs and ERAI generate similar composite means and distributions for cyclone precipitation rates, but GCMs generate weaker cyclone surface winds than ERAI. The amount of cyclone precipitation generated by the convection scheme differs significantly across the datasets, with GISS generating the most, followed by ERAI and then GFDL. The models and reanalysis generate relatively more parameterized convective precipitation when the total cyclone-averaged precipitation is smaller. This is partially due to the contribution of parameterized convective precipitation occurring more often late in the ETC life cycle. For reanalysis and models, precipitation increases with both cyclone moisture and surface wind speed, and this is true if the contribution from the parameterized convection scheme is larger or not. This work shows that these different models generate similar total ETC precipitation despite large differences in the parameterized convection, and these differences do not cause unexpected behavior in ETC precipitation sensitivity to cyclone moisture or surface wind speed.

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 Polar WRF Downscaled Historical and Projected Twenty-First Century Climate for the Coast and Foothills of Arctic Alaska

Directory of Open Access Journals (Sweden)

Lei Cai

2018-01-01

Full Text Available Climate change is most pronounced in the northern high latitude region. Yet, climate observations are unable to fully capture regional-scale dynamics due to the sparse weather station coverage, which limits our ability to make reliable climate-based assessments. A set of simulated data products was therefore developed for the North Slope of Alaska through a dynamical downscaling approach. The polar-optimized Weather Research and Forecast (Polar WRF model was forced by three sources: The ERA-interim reanalysis data (for 1979–2014, the Community Earth System Model 1.0 (CESM1.0 historical simulation (for 1950–2005, and the CESM1.0 projected (for 2006–2100 simulations in two Representative Concentration Pathways (RCP4.5 and RCP8.5 scenarios. Climatic variables were produced in a 10-km grid spacing and a 3-h interval. The ERA-interim forced WRF (ERA-WRF proves the value of dynamical downscaling, which yields more realistic topographical-induced precipitation and air temperature, as well as corrects underestimations in observed precipitation. In summary, dry and cold biases to the north of the Brooks Range are presented in ERA-WRF, while CESM forced WRF (CESM-WRF holds wet and warm biases in its historical period. A linear scaling method allowed for an adjustment of the biases, while keeping the majority of the variability and extreme values of modeled precipitation and air temperature. CESM-WRF under RCP 4.5 scenario projects smaller increase in precipitation and air temperature than observed in the historical CESM-WRF product, while the CESM-WRF under RCP 8.5 scenario shows larger changes. The fine spatial and temporal resolution, long temporal coverage, and multi-scenario projections jointly make the dataset appropriate to address a myriad of physical and biological changes occurring on the North Slope of Alaska.

The polar WRF downscaled historical and projected 21st century climate for the coast and foothills of Arctic Alaska

Science.gov (United States)

Cai, Lei; Alexeev, Vladimir A.; Arp, Christopher D.; Jones, Benjamin M.; Liljedahl, Anna K.; Gädeke, Anne

2018-01-01

Climate change is most pronounced in the northern high latitude region. Yet, climate observations are unable to fully capture regional-scale dynamics due to the sparse weather station coverage, which limits our ability to make reliable climate-based assessments. A set of simulated data products was therefore developed for the North Slope of Alaska through a dynamical downscaling approach. The polar-optimized Weather Research & Forecast (Polar WRF) model was forced by three sources: The ERA-interim reanalysis data (for 1979-2014), the Community Earth System Model 1.0 (CESM1.0) historical simulation (for 1950-2005), and the CESM1.0 projected (for 2006-2100) simulations in two Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios. Climatic variables were produced in a 10-km grid spacing and a 3-hour interval. The ERA-interim forced WRF (ERA-WRF) proves the value of dynamical downscaling, which yields more realistic topographical-induced precipitation and air temperature, as well as corrects underestimations in observed precipitation. In summary, dry and cold biases to the north of the Brooks Range are presented in ERA-WRF, while CESM forced WRF (CESM-WRF) holds wet and warm biases in its historical period. A linear scaling method allowed for an adjustment of the biases, while keeping the majority of the variability and extreme values of modeled precipitation and air temperature. CESM-WRF under RCP 4.5 scenario projects smaller increase in precipitation and air temperature than observed in the historical CESM-WRF product, while the CESM-WRF under RCP8.5 scenario shows larger changes. The fine spatial and temporal resolution, long temporal coverage, and multi-scenario projections jointly make the dataset appropriate to address a myriad of physical and biological changes occurring on the North Slope of Alaska.

Impact of spectral nudging on regional climate simulation over CORDEX East Asia using WRF

Science.gov (United States)

Tang, Jianping; Wang, Shuyu; Niu, Xiaorui; Hui, Pinhong; Zong, Peishu; Wang, Xueyuan

2017-04-01

In this study, the impact of the spectral nudging method on regional climate simulation over the Coordinated Regional Climate Downscaling Experiment East Asia (CORDEX-EA) region is investigated using the Weather Research and Forecasting model (WRF). Driven by the ERA-Interim reanalysis, five continuous simulations covering 1989-2007 are conducted by the WRF model, in which four runs adopt the interior spectral nudging with different wavenumbers, nudging variables and nudging coefficients. Model validation shows that WRF has the ability to simulate spatial distributions and temporal variations of the surface climate (air temperature and precipitation) over CORDEX-EA domain. Comparably the spectral nudging technique is effective in improving the model's skill in the following aspects: (1), the simulated biases and root mean square errors of annual mean temperature and precipitation are obviously reduced. The SN3-UVT (spectral nudging with wavenumber 3 in both zonal and meridional directions applied to U, V and T) and SN6 (spectral nudging with wavenumber 6 in both zonal and meridional directions applied to U and V) experiments give the best simulations for temperature and precipitation respectively. The inter-annual and seasonal variances produced by the SN experiments are also closer to the ERA-Interim observation. (2), the application of spectral nudging in WRF is helpful for simulating the extreme temperature and precipitation, and the SN3-UVT simulation shows a clear advantage over the other simulations in depicting both the spatial distributions and inter-annual variances of temperature and precipitation extremes. With the spectral nudging, WRF is able to preserve the variability in the large scale climate information, and therefore adjust the temperature and precipitation variabilities toward the observation.

Identification of wind fields for wave modeling near Qatar

Science.gov (United States)

Nayak, Sashikant; Balan Sobhana, Sandeepan; Panchang, Vijay

2016-04-01

Due to the development of coastal and offshore infrastructure in and around the Arabian Gulf, a large semi-enclosed sea, knowledge of met-ocean factors like prevailing wind systems, wind generated waves, and currents etc. are of great importance. Primarily it is important to identify the wind fields that are used as forcing functions for wave and circulation models for hindcasting and forecasting purposes. The present study investigates the effects of using two sources of wind-fields on the modeling of wind-waves in the Arabian Gulf, in particular near the coastal regions of Qatar. Two wind sources are considered here, those obtained from ECMWF and those generated by us using the WRF model. The wave model SWAN was first forced with the 6 hourly ERA Interim daily winds (from ECMWF) having spatial resolution of 0.125°. For the second option, wind fields were generated by us using the mesoscale wind model (WRF) with a high spatial resolution (0.1°) at every 30 minute intervals. The simulations were carried out for a period of two months (7th October-7th December, 2015) during which measurements were available from two moored buoys (deployed and operated by the Qatar Meteorological Department), one in the north of Qatar ("Qatar North", in water depth of 58.7 m) and other in the south ("Shiraouh Island", in water depth of 16.64 m). This period included a high-sea event on 11-12th of October, recorded by the two buoys where the significant wave heights (Hs) reached as high as 2.9 m (i.e. max wave height H ~ 5.22 m) and 1.9 (max wave height H ~ 3.4 m) respectively. Model results were compared with the data for this period. The scatter index (SI) of the Hs simulated using the WRF wind fields and the observed Hs was found to be about 30% and 32% for the two buoys (total period). The observed Hs were generally reproduced but there was consistent underestimation. (Maximum 27% for the high-sea event). For the Hs obtained with ERA interim wind fields, the underestimation was

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.

Numerical simulation of rainfall and temperature over Kenya using weather research and forecasting-environmental modelling system (WRF-EMS

Directory of Open Access Journals (Sweden)

Sagero Obaigwa Philip

2016-01-01

Full Text Available This paper focuses on one of the high resolution models used for weather forecasting at Kenya Meteorological Department (KMD. It reviews the skill and accuracy of the Weather Research and Forecasting (WRF - Environmental Modeling System (EMS model, in simulating weather over Kenya. The study period was March to May 2011, during the rainy season over Kenya. The model output was compared with the observed data from 27 synoptic stations spread over the study area, to determine the performance of the model in terms of its skill and accuracy in forecasting. The spatial distribution of rainfall and temperature showed that the WRF model was capable of reproducing the observed general pattern especially for temperature. The model has skill in forecasting both rainfall and temperature over the study area. However, the model may underestimate rainfall of more than 10 mm/day and displace its location and overestimate rainfall of less than 1 mm/day. Therefore, during the period of enhanced rainfall especially in the month of April and part of May the model forecast needs to be complemented by other models or forecasting methods before giving a forecast. There is need to improve its performance over the domain through review of the parameterization of small scale physical processes and more observed data need to be simulated into the model.

Assessment of the ARW-WRF model over complex terrain: the case of the Stellenbosch Wine of Origin district of South Africa

Science.gov (United States)

Soltanzadeh, Iman; Bonnardot, Valérie; Sturman, Andrew; Quénol, Hervé; Zawar-Reza, Peyman

2017-08-01

Global warming has implications for thermal stress for grapevines during ripening, so that wine producers need to adapt their viticultural practices to ensure optimum physiological response to environmental conditions in order to maintain wine quality. The aim of this paper is to assess the ability of the Weather Research and Forecasting (WRF) model to accurately represent atmospheric processes at high resolution (500 m) during two events during the grapevine ripening period in the Stellenbosch Wine of Origin district of South Africa. Two case studies were selected to identify areas of potentially high daytime heat stress when grapevine photosynthesis and grape composition were expected to be affected. The results of high-resolution atmospheric model simulations were compared to observations obtained from an automatic weather station (AWS) network in the vineyard region. Statistical analysis was performed to assess the ability of the WRF model to reproduce spatial and temporal variations of meteorological parameters at 500-m resolution. The model represented the spatial and temporal variation of meteorological variables very well, with an average model air temperature bias of 0.1 °C, while that for relative humidity was -5.0 % and that for wind speed 0.6 m s-1. Variation in model performance varied between AWS and with time of day, as WRF was not always able to accurately represent effects of nocturnal cooling within the complex terrain. Variations in performance between the two case studies resulted from effects of atmospheric boundary layer processes in complex terrain under the influence of the different synoptic conditions prevailing during the two periods.

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.

An evaluation of WRF's ability to reproduce the surface wind over complex terrain based on typical circulation patterns.

NARCIS (Netherlands)

Jiménez, P.A.; Dudhia, J.; González-Rouco, J.F.; Montávez, J.P.; Garcia-Bustamante, E.; Navarro, J.; Vilà-Guerau de Arellano, J.; Munoz-Roldán, A.

2013-01-01

[1] The performance of the Weather Research and Forecasting (WRF) model to reproduce the surface wind circulations over complex terrain is examined. The atmospheric evolution is simulated using two versions of the WRF model during an over 13¿year period (1992 to 2005) over a complex terrain region

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

Science.gov (United States)

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

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)

Effect of land cover on atmospheric processes and air quality over the continental United States – a NASA Unified WRF (NU-WRF model study

Directory of Open Access Journals (Sweden)

Z. Tao

2013-07-01

Full Text Available The land surface plays a crucial role in regulating water and energy fluxes at the land–atmosphere (L–A interface and controls many processes and feedbacks in the climate system. Land cover and vegetation type remains one key determinant of soil moisture content that impacts air temperature, planetary boundary layer (PBL evolution, and precipitation through soil-moisture–evapotranspiration coupling. In turn, it will affect atmospheric chemistry and air quality. This paper presents the results of a modeling study of the effect of land cover on some key L–A processes with a focus on air quality. The newly developed NASA Unified Weather Research and Forecast (NU-WRF modeling system couples NASA's Land Information System (LIS with the community WRF model and allows users to explore the L–A processes and feedbacks. Three commonly used satellite-derived land cover datasets – i.e., from the US Geological Survey (USGS and University of Maryland (UMD, which are based on the Advanced Very High Resolution Radiometer (AVHRR, and from the Moderate Resolution Imaging Spectroradiometer (MODIS – bear large differences in agriculture, forest, grassland, and urban spatial distributions in the continental United States, and thus provide an excellent case to investigate how land cover change would impact atmospheric processes and air quality. The weeklong simulations demonstrate the noticeable differences in soil moisture/temperature, latent/sensible heat flux, PBL height, wind, NO2/ozone, and PM2.5 air quality. These discrepancies can be traced to associate with the land cover properties, e.g., stomatal resistance, albedo and emissivity, and roughness characteristics. It also implies that the rapid urban growth may have complex air quality implications with reductions in peak ozone but more frequent high ozone events.

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

Science.gov (United States)

Mielikainen, J.; Huang, B.; Huang, A. H.-L.

2014-12-01

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

Resolving vorticity-driven lateral fire spread using the WRF-Fire coupled atmosphere–fire numerical model

OpenAIRE

Simpson, C. C.; Sharples, J. J.; Evans, J. P.

2014-01-01

Fire channelling is a form of dynamic fire behaviour, during which a wildland fire spreads rapidly across a steep lee-facing slope in a direction transverse to the background winds, and is often accompanied by a downwind extension of the active flaming region and extreme pyro-convection. Recent work using the WRF-Fire coupled atmosphere-fire model has demonstrated that fire channelling can be characterised as vorticity-driven lateral fire spread (VDLS). In t...

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

Science.gov (United States)

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

2018-01-01

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

ChemAND - a system health monitor for plant chemistry

Energy Technology Data Exchange (ETDEWEB)

Turner, C.W.; Mitchel, G.R.; Tosello, G.; Balakrishnan, P.V.; McKay, G.; Thompson, M. [Atomic Energy of Canada Limited, Chalk River, Ontario (Canada); Dundar, Y.; Bergeron, M.; Laporte, R. [Hydro-Quebec, Groupe Chimie, Centrale Nucleaire Gentilly-2, Gentilly, Quebec (Canada)

2001-03-01

Effective management of plant systems throughout their lifetime requires much more than data acquisition and display - it requires that the plant's system health be continually monitored and managed. AECL has developed a System Health Monitor called ChemAND for CANDU plant chemistry. ChemAND, a Chemistry ANalysis and Diagnostic system, monitors key chemistry parameters in the heat transport system, moderator-cover gas, annulus gas, and the steam cycle during full-power operation. These parameters can be used as inputs to models that calculate the effect of current plant operating conditions on the present and future health of the system. Chemistry data from each of the systems are extracted on a regular basis from the plant's Historical Data Server and are sorted according to function, e.g., indicators for condenser in-leakage, air in-leakage, heavy water leakage into the annulus gas, fuel failure, etc. Each parameter is conveniently displayed and is trended along with its alarm limits. ChemAND currently includes two analytical models developed for the balance-of-plant. The first model, ChemSolv, calculates crevice chemistry conditions in the steam generator (SG) from either the SG blowdown chemistry conditions or from a simulated condenser leak. This information can be used by plant staff to evaluate the susceptibility of the SG tubes to crevice corrosion. ChemSolv also calculates chemistry conditions throughout the steam-cycle system as determined by the transport of volatile species such as ammonia, hydrazine, morpholine, and oxygen. The second model, SLUDGE, calculates the deposit loading and distribution in the SG as a function of time, based on concentrations of corrosion product in the final feedwater for both normal and start-up conditions. Operations personnel can use this information to predict where to inspect and when to clean. (author)

ChemAND - a system health monitor for plant chemistry

International Nuclear Information System (INIS)

Turner, C.W.; Mitchell, G.R.; Tosello, G.; Balakrishnan, P.V.; McKay, G.; Thompson, M.; Dundar, Y.; Bergeron, M.; Laporte, R.

2001-01-01

Effective management of plant systems throughout their lifetime requires much more than data acquisition and display-it requires that the plant's system health be continually monitored and managed. AECL has developed a System Health Monitor called ChemAND for CANDU plant chemistry. ChemAND, a Chemistry ANalysis and Diagnostic system, monitors key chemistry parameters in the heat transport system, moderator-cover gas, annulus gas, and the steam cycle during full-power operation. These parameters can be used as inputs to models that calculate the effect of current plant operating conditions on the present and future health of the system. Chemistry data from each of the systems are extracted on a regular basis from the plant's Historical Data Server and are sorted according to function, e.g., indicators for condenser in-leakage, air in-leakage, heavy water leakage into the annulus gas, fuel failure, etc. Each parameter is conveniently displayed and is trended along with its alarm limits. ChemAND currently includes two analytical models developed for the balance-of-plant. The first model, ChemSolv, calculates crevice chemistry conditions in the steam generator (SG) from either the SG blowdown chemistry conditions or from a simulated condenser leak. This information can be used by plant staff to evaluate the susceptibility of the SG tubes to crevice corrosion. ChemSolv also calculates chemistry conditions throughout the steam cycle system, as determined by the transport of volatile species such as ammonia, hydrazine, morpholine, and oxygen. The second model, SLUDGE, calculates the deposit loading and distribution in the SG as a function of time, based on concentrations of corrosion product in the final feedwater for both normal and start-up conditions. Operations personnel can use this information to predict where to inspect and when to clean. (author)

ChemAND - a system health monitor for plant chemistry

International Nuclear Information System (INIS)

Turner, C.W.; Mitchel, G.R.; Tosello, G.; Balakrishnan, P.V.; McKay, G.; Thompson, M.; Dundar, Y.; Bergeron, M.; Laporte, R.

2001-03-01

Effective management of plant systems throughout their lifetime requires much more than data acquisition and display - it requires that the plant's system health be continually monitored and managed. AECL has developed a System Health Monitor called ChemAND for CANDU plant chemistry. ChemAND, a Chemistry ANalysis and Diagnostic system, monitors key chemistry parameters in the heat transport system, moderator-cover gas, annulus gas, and the steam cycle during full-power operation. These parameters can be used as inputs to models that calculate the effect of current plant operating conditions on the present and future health of the system. Chemistry data from each of the systems are extracted on a regular basis from the plant's Historical Data Server and are sorted according to function, e.g., indicators for condenser in-leakage, air in-leakage, heavy water leakage into the annulus gas, fuel failure, etc. Each parameter is conveniently displayed and is trended along with its alarm limits. ChemAND currently includes two analytical models developed for the balance-of-plant. The first model, ChemSolv, calculates crevice chemistry conditions in the steam generator (SG) from either the SG blowdown chemistry conditions or from a simulated condenser leak. This information can be used by plant staff to evaluate the susceptibility of the SG tubes to crevice corrosion. ChemSolv also calculates chemistry conditions throughout the steam-cycle system as determined by the transport of volatile species such as ammonia, hydrazine, morpholine, and oxygen. The second model, SLUDGE, calculates the deposit loading and distribution in the SG as a function of time, based on concentrations of corrosion product in the final feedwater for both normal and start-up conditions. Operations personnel can use this information to predict where to inspect and when to clean. (author)

Coupling of WRF meteorological model to WAM spectral wave model through sea surface roughness at the Balearic Sea: impact on wind and wave forecasts

Science.gov (United States)

Tolosana-Delgado, R.; Soret, A.; Jorba, O.; Baldasano, J. M.; Sánchez-Arcilla, A.

2012-04-01

Meteorological models, like WRF, usually describe the earth surface characteristics by tables that are function of land-use. The roughness length (z0) is an example of such approach. However, over sea z0 is modeled by the Charnock (1955) relation, linking the surface friction velocity u*2 with the roughness length z0 of turbulent air flow, z0 = α-u2* g The Charnock coefficient α may be considered a measure of roughness. For the sea surface, WRF considers a constant roughness α = 0.0185. However, there is evidence that sea surface roughness should depend on wave energy (Donelan, 1982). Spectral wave models like WAM, model the evolution and propagation of wave energy as a function of wind, and include a richer sea surface roughness description. Coupling WRF and WAM is thus a common way to improve the sea surface roughness description of WRF. WAM is a third generation wave model, solving the equation of advection of wave energy subject to input/output terms of: wind growth, energy dissipation and resonant non-linear wave-wave interactions. Third generation models work on the spectral domain. WAM considers the Charnock coefficient α a complex yet known function of the total wind input term, which depends on the wind velocity and on the Charnock coefficient again. This is solved iteratively (Janssen et al., 1990). Coupling of meteorological and wave models through a common Charnock coefficient is operationally done in medium-range met forecasting systems (e.g., at ECMWF) though the impact of coupling for smaller domains is not yet clearly assessed (Warner et al, 2010). It is unclear to which extent the additional effort of coupling improves the local wind and wave fields, in comparison to the effects of other factors, like e.g. a better bathymetry and relief resolution, or a better circulation information which might have its influence on local-scale meteorological processes (local wind jets, local convection, daily marine wind regimes, etc.). This work, within the

Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections

Science.gov (United States)

S. Sun; Ge Sun; Erika Cohen Mack; Steve McNulty; Peter Caldwell; K. Duan; Y. Zhang

2015-01-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model)...

Evaluation of Heavy Precipitation Simulated by the WRF Model Using 4D-Var Data Assimilation with TRMM 3B42 and GPM IMERG over the Huaihe River Basin, China

Directory of Open Access Journals (Sweden)

Lu Yi

2018-04-01

Full Text Available To obtain independent, consecutive, and high-resolution precipitation data, the four-dimensional variational (4D-Var method was applied to directly assimilate satellite precipitation products into the Weather Research and Forecasting (WRF model. The precipitation products of the Tropical Rainfall Measuring Mission 3B42 (TRMM 3B42 and its successor, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM IMERG were assimilated in this study. Two heavy precipitation events that occurred over the Huaihe River basin in eastern China were studied. Before assimilation, the WRF model simulations were first performed with different forcing data to select more suitable forcing data and determine the control experiments for the subsequent assimilation experiments. Then, TRMM 3B42 and GPM IMERG were separately assimilated into the WRF. The simulated precipitation results in the outer domain (D01, with a 27-km resolution, and the inner domain (D02, with a 9-km resolution, were evaluated in detail. The assessments showed that (1 4D-Var with TRMM 3B42 or GPM IMERG could both significantly improve WRF precipitation predictions at a time interval of approximately 12 h; (2 the WRF simulated precipitation assimilated with GPM IMERG outperformed the one with TRMM 3B42; (3 for the WRF output precipitation assimilated with GPM IMERG over D02, which has spatiotemporal resolutions of 9 km and 50 s, the correlation coefficients of the studied events in August and November were 0.74 and 0.51, respectively, at the point and daily scales, and the mean Heidke skill scores for the two studied events both reached 0.31 at the grid and hourly scales. This study can provide references for the assimilation of TRMM 3B42 or GPM IMERG into the WRF model using 4D-Var, which is especially valuable for hydrological applications of GPM IMERG during the transition period from the TRMM era into the GPM era.

Full Coupling Between the Atmosphere, Surface, and Subsurface for Integrated Hydrologic Simulation

Science.gov (United States)

Davison, Jason Hamilton; Hwang, Hyoun-Tae; Sudicky, Edward A.; Mallia, Derek V.; Lin, John C.

2018-01-01

An ever increasing community of earth system modelers is incorporating new physical processes into numerical models. This trend is facilitated by advancements in computational resources, improvements in simulation skill, and the desire to build numerical simulators that represent the water cycle with greater fidelity. In this quest to develop a state-of-the-art water cycle model, we coupled HydroGeoSphere (HGS), a 3-D control-volume finite element surface and variably saturated subsurface flow model that includes evapotranspiration processes, to the Weather Research and Forecasting (WRF) Model, a 3-D finite difference nonhydrostatic mesoscale atmospheric model. The two-way coupled model, referred to as HGS-WRF, exchanges the actual evapotranspiration fluxes and soil saturations calculated by HGS to WRF; conversely, the potential evapotranspiration and precipitation fluxes from WRF are passed to HGS. The flexible HGS-WRF coupling method allows for unique meshes used by each model, while maintaining mass and energy conservation between the domains. Furthermore, the HGS-WRF coupling implements a subtime stepping algorithm to minimize computational expense. As a demonstration of HGS-WRF's capabilities, we applied it to the California Basin and found a strong connection between the depth to the groundwater table and the latent heat fluxes across the land surface.

Air quality and radiative impacts of Arctic shipping emissions in the summertime in northern Norway: from the local to the regional scale

Directory of Open Access Journals (Sweden)

L. Marelle

2016-02-01

Full Text Available In this study, we quantify the impacts of shipping pollution on air quality and shortwave radiative effect in northern Norway, using WRF-Chem (Weather Research and Forecasting with chemistry simulations combined with high-resolution, real-time STEAM2 (Ship Traffic Emissions Assessment Model version 2 shipping emissions. STEAM2 emissions are evaluated using airborne measurements from the ACCESS (Arctic Climate Change, Economy and Society aircraft campaign, which was conducted in the summer 2012, in two ways. First, emissions of nitrogen oxides (NOx and sulfur dioxide (SO2 are derived for specific ships by combining in situ measurements in ship plumes and FLEXPART-WRF plume dispersion modeling, and these values are compared to STEAM2 emissions for the same ships. Second, regional WRF-Chem runs with and without STEAM2 ship emissions are performed at two different resolutions, 3 km  ×  3 km and 15 km  ×  15 km, and evaluated against measurements along flight tracks and average campaign profiles in the marine boundary layer and lower troposphere. These comparisons show that differences between STEAM2 emissions and calculated emissions can be quite large (−57 to +148 % for individual ships, but that WRF-Chem simulations using STEAM2 emissions reproduce well the average NOx, SO2 and O3 measured during ACCESS flights. The same WRF-Chem simulations show that the magnitude of NOx and ozone (O3 production from ship emissions at the surface is not very sensitive (< 5 % to the horizontal grid resolution (15 or 3 km, while surface PM10 particulate matter enhancements due to ships are moderately sensitive (15 % to resolution. The 15 km resolution WRF-Chem simulations are used to estimate the regional impacts of shipping pollution in northern Norway. Our results indicate that ship emissions are an important source of pollution along the Norwegian coast, enhancing 15-day-averaged surface concentrations of NOx ( ∼  +80 %, SO2 (�

Ecosystem feedbacks to climate change in California: Development, testing, and analysis using a coupled regional atmosphere and land-surface model (WRF3-CLM3.5)

Energy Technology Data Exchange (ETDEWEB)

Subin, Z.M.; Riley, W.J.; Kueppers, L.M.; Jin, J.; Christianson, D.S.; Torn, M.S.

2010-11-01

A regional atmosphere model [Weather Research and Forecasting model version 3 (WRF3)] and a land surface model [Community Land Model, version 3.5 (CLM3.5)] were coupled to study the interactions between the atmosphere and possible future California land-cover changes. The impact was evaluated on California's climate of changes in natural vegetation under climate change and of intentional afforestation. The ability of WRF3 to simulate California's climate was assessed by comparing simulations by WRF3-CLM3.5 and WRF3-Noah to observations from 1982 to 1991. Using WRF3-CLM3.5, the authors performed six 13-yr experiments using historical and future large-scale climate boundary conditions from the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1). The land-cover scenarios included historical and future natural vegetation from the Mapped Atmosphere-Plant-Soil System-Century 1 (MC1) dynamic vegetation model, in addition to a future 8-million-ha California afforestation scenario. Natural vegetation changes alone caused summer daily-mean 2-m air temperature changes of -0.7 to +1 C in regions without persistent snow cover, depending on the location and the type of vegetation change. Vegetation temperature changes were much larger than the 2-m air temperature changes because of the finescale spatial heterogeneity of the imposed vegetation change. Up to 30% of the magnitude of the summer daily-mean 2-m air temperature increase and 70% of the magnitude of the 1600 local time (LT) vegetation temperature increase projected under future climate change were attributable to the climate-driven shift in land cover. The authors projected that afforestation could cause local 0.2-1.2 C reductions in summer daily-mean 2-m air temperature and 2.0-3.7 C reductions in 1600 LT vegetation temperature for snow-free regions, primarily because of increased evapotranspiration. Because some of these temperature changes are of comparable magnitude to those

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.

Numerical simulations of Aerosol and Trace Gas Emissions and Transformations over the North China Plain

Science.gov (United States)

He, H.; Ren, X.; Li, Z.; Dickerson, R. R.

2016-12-01

The North China Plain (NCP) is one of the most populated and polluted regions on Earth. In the past decades the rapid economic development has resulted in heavy atmospheric aerosol loadings in this region. The high aerosol concentrations induce severe environmental and climate problems, and aerosols can also affect human health and visibility. So there is a continued need to understand air quality in this region and transport of air pollutants from this region as populations grow, energy use increases, and industrial activity evolves. The unique mix of species over the NCP makes understanding the processes leading to transformations of primary pollutants and formation of secondary pollutants essential to predicting regional and global impacts. WRF-Chem simulations were performed for the NCP to investigate the emissions and transformations of air pollutants. MIX emission inventory of year 2010 (developed for MICS-Asia III and HTAP projects) was used to drive the WRF-Chem model. Modeling results were evaluated with observation data including OMI SO2/NO2 and MODIS AOD products to improve our knowledge of emission changes in the NCP between 2010 and 2016. We also estimated the regional transport of air pollutants from the NCP to downwind areas such as South Korea and Japan with WRF-Chem simulations constrained by these observations.

South Baltic wind atlas. South Baltic offshore wind energy regions project

Energy Technology Data Exchange (ETDEWEB)

Pena, A.; Hahmann, A.; Hasager, C.B.; Bingoel, F.; Karagali, I.; Badger, J.; Badger, M.; Clausen, Niels-Erik

2011-05-15

A first version of a wind atlas for the South Baltic Sea has been developed using the WRF mesoscale model and verified by data from tall Danish and German masts. Six different boundary-layer parametrization schemes were evaluated by comparing the WRF results to the observed wind profiles at the masts. The WRF modeling was done in a nested domain of high spatial resolution for 4 years. In addition the long-term wind statistics using the NCAR-NCEP reanalysis data were performed during 30 years to provide basis for a long-term adjustment of the results and the final WRF results include a weighting for the long-term trends variability in the South Baltic Sea. Observations from Earth observing satellites were used to evaluate the spatial resolution of the WRF model results near the surface. The QuikSCAT and the WRF results compared well whereas the Envisat ASAR mean wind map showed some variation to the others. The long-term analysis revealed that the South Baltic Sea has a spatially highly variable wind climate during the 30-years. (Author)

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

ChemSpell Web Service API

Data.gov (United States)

U.S. Department of Health & Human Services — The ChemSpell Web Service API provides chemical name spell checking and chemical name synonym look-up. ChemSpell contains more than 1.3 million chemical names...

Forecasting summertime surface temperature and precipitation in the Mexico City metropolitan area: sensitivity of the WRF model to land cover changes

Science.gov (United States)

López-Bravo, Clemente; Caetano, Ernesto; Magaña, Víctor

2018-02-01

Changes in the frequency and intensity of severe hydrometeorological events in recent decades in the Mexico City Metropolitan Area have motivated the development of weather warning systems. The weather forecasting system for this region was evaluated in sensitivity studies using the Weather Research and Forecasting Model (WRF) for July 2014, a summer time month. It was found that changes in the extent of the urban area and associated changes in thermodynamic and dynamic variables have induced local circulations that affect the diurnal cycles of temperature, precipitation, and wind fields. A newly implemented configuration (land cover update and Four-Dimensional Data Assimilation (FDDA)) of the WRF model has improved the adjustment of the precipitation field to the orography. However, errors related to the depiction of convection due to parameterizations and microphysics remains a source of uncertainty in weather forecasting in this region.

Wake Effects of Large Offshore Wind Farms - a study of the Mesoscale Atmophere

DEFF Research Database (Denmark)

Volker, Patrick

to the flow. In the past, several approaches have been introduced, ranging from surface roughness change to drag approaches which usually also add turbulence. A new scheme is implemented in the Weather Research and Forecast (WRF) model. Measurements from Horns Rev I are used to evaluate the new scheme...... together with that in the WRF model. Results show an improvement of robustness in vertical resolution dependency. Furthermore, the velocity and “turbulence kinetic energy” fields agree better to those of high resolution models. The two schemes are applied to various problems. A hypothetical offshore wind...

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...

An evaluation of the performance of a WRF multi-physics ensemble for heatwave events over the city of Melbourne in southeast Australia

Science.gov (United States)

Imran, H. M.; Kala, J.; Ng, A. W. M.; Muthukumaran, S.

2018-04-01

Appropriate choice of physics options among many physics parameterizations is important when using the Weather Research and Forecasting (WRF) model. The responses of different physics parameterizations of the WRF model may vary due to geographical locations, the application of interest, and the temporal and spatial scales being investigated. Several studies have evaluated the performance of the WRF model in simulating the mean climate and extreme rainfall events for various regions in Australia. However, no study has explicitly evaluated the sensitivity of the WRF model in simulating heatwaves. Therefore, this study evaluates the performance of a WRF multi-physics ensemble that comprises 27 model configurations for a series of heatwave events in Melbourne, Australia. Unlike most previous studies, we not only evaluate temperature, but also wind speed and relative humidity, which are key factors influencing heatwave dynamics. No specific ensemble member for all events explicitly showed the best performance, for all the variables, considering all evaluation metrics. This study also found that the choice of planetary boundary layer (PBL) scheme had largest influence, the radiation scheme had moderate influence, and the microphysics scheme had the least influence on temperature simulations. The PBL and microphysics schemes were found to be more sensitive than the radiation scheme for wind speed and relative humidity. Additionally, the study tested the role of Urban Canopy Model (UCM) and three Land Surface Models (LSMs). Although the UCM did not play significant role, the Noah-LSM showed better performance than the CLM4 and NOAH-MP LSMs in simulating the heatwave events. The study finally identifies an optimal configuration of WRF that will be a useful modelling tool for further investigations of heatwaves in Melbourne. Although our results are invariably region-specific, our results will be useful to WRF users investigating heatwave dynamics elsewhere.

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.

UPDATE ON DEVELOPMENT OF NUDGING FDDA FOR ADVANCED RESEARCH WRF

Science.gov (United States)

A nudging-based four-dimensional data assimilation (FDDA) system is being developed for the Weather Research and Forecasting (WRF) Model. This effort represents a collaboration between The Pennsylvania State University (i.e., Penn State), the National Center for Atmospheric Rese...

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.

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.

Cross-spectra over the sea from observations and mesoscale modelling

DEFF Research Database (Denmark)

Vincent, Claire Louise; Larsén, Xiaoli Guo; Larsen, Søren Ejling

2013-01-01

of the cross-correlation function and an exponentially decaying coherence function are fitted to the normalized cospectra and quadrature spectra. The expressions are shown to be a good fit to the spectra calculated from the WRF simulations and to the observed spectra for directions with a long sea-fetch, which...

The effect of stability on the coastal gradients at the Anholt wind farm

DEFF Research Database (Denmark)

Volker, Patrick; Hasager, Charlotte Bay; Badger, Merete

We use Synthetic Aperture Radar (SAR) and SCADA measurements and mesoscale model simulations from the Weather Research and Forecast (WRF) model[3] to analyse the flow conditions at the Danish offshore wind farm at Anholt. The first Danish oshore wind farms have been installed in the North Sea of ...