scholarly journals Inline Coupling of WRF–HYSPLIT: Model Development and Evaluation Using Tracer Experiments

2015 ◽  
Vol 54 (6) ◽  
pp. 1162-1176 ◽  
Author(s):  
Fong Ngan ◽  
Ariel Stein ◽  
Roland Draxler
Keyword(s):  
Complex Terrain ◽  
Dispersion Model ◽  
Meteorological Data ◽  
Temporal Frequency ◽  
Regional Scale ◽  
Grid Spacing ◽  
Hysplit Model ◽  
Meteorological Model ◽  
Vertical Coordinate ◽  
Tracer Experiments

AbstractThe Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), a Lagrangian dispersion model, has been coupled (inline) to the the Weather Research and Forecasting (WRF) Model meteorological model in such a way that the HYSPLIT calculation is run as part of the WRF-ARW prediction calculation. This inline version of HYSPLIT takes advantage of the higher temporal frequency of WRF-ARW variables relative to what would be available for the offline approach. Furthermore, the dispersion calculation uses the same vertical coordinate system as WRF-ARW, resulting in a more consistent depiction of the state of the atmosphere and the dispersion simulation. Both inline and the offline HYSPLIT simulations were conducted for two tracer experiments at quite different model spatial resolutions: the Cross Appalachian Tracer Experiment (CAPTEX) in regional scale (at 9-km grid spacing) and the Atmospheric Studies in Complex Terrain (ASCOT) in finescale (at 333.3-m grid spacing). A comparison of the model with the measured values showed that the results of the two approaches were very similar for all six releases in CAPTEX. For the ASCOT experiments, the cumulative statistical score of the inline simulations was better than or equal to offline runs in four of five releases. Although the use of the inline approach did not provide any advantage over the offline method for the regional spatial scale and medium-range temporal scale represented by the CAPTEX experiment, the inline HYSPLIT was able to improve the simulation of the dispersion when compared with the offline version for the fine spatial and temporal resolutions over the complex-terrain area represented by ASCOT. The improvement of the inline over the offline calculation is attributed to the elimination of temporal and vertical interpolation of the meteorological data as compared with the offline version.

scholarly journals A Long-Term WRF Meteorological Archive for Dispersion Simulations: Application to Controlled Tracer Experiments

2017 ◽  
Vol 56 (8) ◽  
pp. 2203-2220 ◽  
Author(s):  
Fong Ngan ◽  
Ariel F. Stein
Keyword(s):  
Dispersion Model ◽  
Meteorological Data ◽  
Atmospheric Dispersion ◽  
Wrf Model ◽  
Tracer Experiment ◽  
Limited Information ◽  
Hysplit Model ◽  
The North ◽  
Tracer Experiments

AbstractA long-term archive of meteorological data using the Weather Research and Forecasting (WRF) Model was created to provide data that are compatible with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) dispersion model and to serve as initial and boundary conditions for simulations at a finer resolution. On the basis of these WRF data, generated with a variety of planetary boundary layer (PBL) schemes and nudging options, the HYSPLIT model was run to simulate four controlled tracer experiments—the Cross Appalachian Tracer Experiment (CAPTEX), the Across North America Tracer Experiment (ANATEX), a 1980 release in Oklahoma City, Oklahoma (OKC80), and the Metropolitan Tracer Experiment (METREX)—covering different time periods with diverse durations, including a summer day, several days in autumn, three months during winter, and one full year, respectively. The evaluation of the WRF results utilizing conventional observations showed a similar statistical performance for the different PBL schemes. Given the limited information the meteorological evaluation alone can provide, the authors used the dispersion evaluation with measurements from multiple tracer experiments to gain further insight into the most appropriate WRF configuration to generate reasonable data for dispersion applications. The dispersion simulations that were based on WRF data generated equal or slightly better statistical performance than did those driven by the North American Regional Reanalysis (NARR) dataset. The statistical comparison showed a mixed impact for the dispersion results driven by the nonnudged and nudged WRF data. The main advantage of the WRF data is the availability of hourly meteorological data from 1980 to the present and the inclusion of additional variables that are relevant to atmospheric dispersion and are not available from NARR. This WRF dataset will be accessible online, providing additional capabilities for using different meteorological inputs and a variety of options to compute the HYSPLIT mixing parameters.

scholarly journals Association between the Occurrence of Primary Hypothyroidism and the Exposure of the Population Near to Industrial Pollutants in São Paulo State, Brazil

2019 ◽  
Vol 16 (18) ◽  
pp. 3464 ◽  
Author(s):  
Maria Angela Zaccarelli-Marino ◽  
Rudá Alessi ◽  
Thalles Zaccarelli Balderi ◽  
Marco Antonio Garcia Martins
Keyword(s):  
Dispersion Model ◽  
Meteorological Data ◽  
Primary Hypothyroidism ◽  
Atmospheric Pollutants ◽  
Meteorological Model ◽  
Pollutant Concentrations ◽  
Influence Area ◽  
Home Based ◽  
Environmental Agents ◽  
Multiple Levels

Background: Environmental agents interfere with thyroid function at multiple levels. This study was to investigate the association between pollutant concentrations and the primary hypothyroidism (PH) occurrence odds in residents living in the Capuava Petrochemical Complex (CPC) influence area. Methods: This area was evaluated with the combination of the AERMOD dispersion model with the Weather Research Forecast (WRF) meteorological model (2016). The concentration of atmospheric pollutants were analyzed in 2017 using meteorological data on the period from 2005 to 2009, correlating this data with the research done in 2003 to 2005. A home-based questionnaire was applied to evaluate 2004 residents, of both sexes, aged from 8 to 72 years, based on their proximity to the industrial areas; were select residents with PH. Results: Volatile organic compounds (VOCs), carbon monoxide (CO), and nitrogen dioxide (NO2) concentrations presented the highest correlations between the PH odds and pollutant concentrations. Conclusion: Air pollution associated with the presence of the CPC is an important environmental factor contributing to the development of PH in the nearby population. As the first study showing this association in Brazil, research should be continued to better understand the mechanisms and to find ways to compensate for or remedy to avoid health impacts in future populations.

scholarly journals The Use of Global and Mesoscale Meteorological Model Data to Predict the Transport and Dispersion of Tracer Plumes over Washington, D.C.

2006 ◽  
Vol 21 (3) ◽  
pp. 383-394 ◽  
Author(s):  
Roland R. Draxler
Keyword(s):  
Mesoscale Model ◽  
Dispersion Model ◽  
Meteorological Data ◽  
Model Performance ◽  
Reanalysis Data ◽  
Urban Environments ◽  
Model Data ◽  
Meteorological Model ◽  
Model Calculations ◽  
Comparable Performance

Abstract The data from a yearlong tracer dispersion experiment over Washington, D.C., in 1984 were used to evaluate Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) dispersion model calculations using coarse global meteorological reanalysis data [NCEP–NCAR and 40-Yr ECMWF Re-Analysis (ERA-40)] and calculations using meteorological data fields created by running a high-resolution meteorological model [fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5)]. None of the meteorological models were optimized for urban environments. The dispersion calculation using the ERA-40 data showed better performance than those using the NCEP–NCAR data and comparable performance to those using MM5 data fields. Calculations with MM5 data that used shorter-period forecasts were superior to calculations that used forecast data that extended beyond 24 h. Daytime dispersion model calculations using the MM5 data showed an underprediction bias not evident in calculations using the ERA-40 data or for nighttime calculations using either meteorological dataset. It was found that small changes in the wind direction for all meteorological model data resulted in dramatic improvements in dispersion model performance. All meteorological data modeled plume directions were biased 10°–20° clockwise to the measured plume direction. This bias was greatest when using the global meteorological data. A detailed analysis of the wind observations during the November intensive, which had the greatest difference between the model and measured plume directions, showed that only the very lowest level of observed winds could account for the transport direction of the measured plume. In the Northern Hemisphere, winds tend to turn clockwise with height resulting in positive directional transport bias if the lowest-level winds are not represented in sufficient detail by the meteorological model.

scholarly journals Air-Quality Challenges of Prescribed Fire in the Complex Terrain and Wildland Urban Interface Surrounding Bend, Oregon

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 515 ◽  
Author(s):  
Colton Miller ◽  
Susan O’Neill ◽  
Miriam Rorig ◽  
Ernesto Alvarado
Keyword(s):  
Complex Terrain ◽  
Dispersion Model ◽  
Weather Data ◽  
Dispersion Modeling ◽  
Prescribed Fires ◽  
National Forest ◽  
Modeling Framework ◽  
Wildland Urban Interface ◽  
Meteorological Model ◽  
Smoke Dispersion

Prescribed fires in forest ecosystems can negatively impact human health and safety by transporting smoke downwind into nearby communities. Smoke transport to communities is known to occur around Bend, Oregon, United States of America (USA), where burning at the wildland–urban interface in the Deschutes National Forest resulted in smoke intrusions into populated areas. The number of suitable days for prescribed fires is limited due to the necessity for moderate weather conditions, as well as wind directions that do not carry smoke into Bend. To better understand the conditions leading to these intrusions and to assess predictions of smoke dispersion from prescribed fires, we collected data from an array of weather and particulate monitors over the autumn of 2014 and spring of 2015 and historical weather data from nearby remote automated weather stations (RAWS). We characterized the observed winds to compare with meteorological and smoke dispersion models using the BlueSky smoke modeling framework. The results from this study indicated that 1–6 days per month in the spring and 2–4 days per month in the fall met the general meteorological prescription parameters for conducting prescribed fires in the National Forest. Of those, 13% of days in the spring and 5% of days in the fall had “ideal” wind patterns, when north winds occurred during the day and south winds did not occur at night. The analysis of smoke intrusions demonstrated that dispersion modeling can be useful for anticipating the timing and location of smoke impacts, but substantial errors in wind speed and direction of the meteorological models can lead to mischaracterizations of intrusion events. Additionally, for the intrusion event modeled using a higher-resolution 1-km meteorological and dispersion model, we found improved predictions of both the timing and location of smoke delivery to Bend compared with the 4-km meteorological model. The 1-km-resolution model prediction fell within 1 h of the observed event, although with underpredicted concentrations, and demonstrated promise for high-resolution modeling in areas of complex terrain.

scholarly journals Parameterization of Convective Transport in a Lagrangian Particle Dispersion Model and Its Evaluation

2007 ◽  
Vol 46 (4) ◽  
pp. 403-422 ◽  
Author(s):  
Caroline Forster ◽  
Andreas Stohl ◽  
Petra Seibert
Keyword(s):  
Dispersion Model ◽  
Meteorological Data ◽  
Relative Difference ◽  
Particle Dispersion ◽  
Convective Transport ◽  
Tracer Transport ◽  
Convection Scheme ◽  
Lagrangian Particle ◽  
Mass Fluxes ◽  
Tracer Experiments

Abstract This paper presents the revision and evaluation of the interface between the convective parameterization by Emanuel and Živković-Rothman and the Lagrangian particle dispersion model “FLEXPART” based on meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The convection scheme relies on the ECMWF grid-scale temperature and humidity and provides a matrix necessary for the vertical convective particle displacement. The benefits of the revised interface relative to its previous version are presented. It is shown that, apart from minor fluctuations caused by the stochastic convective redistribution of the particles, the well-mixed criterion is fulfilled in simulations that include convection. Although for technical reasons the calculation of the displacement matrix differs somewhat between the forward and the backward simulations in time, the mean relative difference between the convective mass fluxes in forward and backward simulations is below 3% and can therefore be tolerated. A comparison of the convective mass fluxes and precipitation rates with those archived in the 40-yr ECMWF Reanalysis (ERA-40) data reveals that the convection scheme in FLEXPART produces upward mass fluxes and precipitation rates that are generally smaller by about 25% than those from ERA-40. This result is interpreted as positive, because precipitation is known to be overestimated by the ECMWF model. Tracer transport simulations with and without convection are compared with surface and aircraft measurements from two tracer experiments and to 222Rn measurements from two aircraft campaigns. At the surface no substantial differences between the model runs with and without convection are found, but at higher altitudes the model runs with convection produced better agreement with the measurements in most of the cases and indifferent results in the others. However, for the tracer experiments only few measurements at higher altitudes are available, and for the aircraft campaigns the 222Rn emissions are highly uncertain. Other datasets better suitable for the validation of convective transport in models are not available. Thus, there is a clear need for reliable datasets suitable to validate vertical transport in models.

The Application of the Micro-Siting Technique in Tioman Island, Malaysia Using the RIAM-COMPACT Software

2014 ◽  
Vol 660 ◽  
pp. 745-749
Author(s):  
Rosly Nurhayati ◽  
Mohd Sofian
Keyword(s):  
Complex Terrain ◽  
Meteorological Data ◽  
Computational Prediction ◽  
Applied Mechanics ◽  
Eddy Simulation ◽  
Turbine Generators ◽  
Wind Turbine Generators ◽  
Large Eddy ◽  
Asean Countries ◽  
Wind Resources

ASEAN (Association of Southeast Asian Nations) countries may have a huge potential for utilizing wind energy as it requires little in the way of land. Land in these countries is very fertile and is used by other alternatives, therefore reducing its conduciveness for developing solar energy. The wind resources map is widely available for Laos, Vietnam, Thailand, Cambodia and Philippines but there is not much information about other ASEAN countries. Based on meteorological data, Tioman Island was selected as the area that had the best potential for installing wind turbines in Malaysia. A more detailed study was conducted using a CFD model for unsteady flow, known as the Research Institute for Applied Mechanics, Kyushu University, COMputational Prediction of Airflow over Complex Terrain (RIAM-COMPACT®) which is based on the Large-Eddy Simulation (LES) technique. Micro-siting technique is used as a tool for selecting appropriate point and an inappropriate point for locating wind turbine generators (WTGs) at Tioman Island, Malaysia. The suggested points for locating WTGs were shown based on the numerical results obtained from the calculation.

Simulation of the wind fields over complex terrain with coupling of CFD and WRF

2021 ◽  
pp. 1-12
Author(s):  
Xiaoyu Luo ◽  
Yiwen Cao
Keyword(s):  
Wind Speed ◽  
Wind Field ◽  
Complex Terrain ◽  
Civil Engineering ◽  
Meteorological Data ◽  
Mass Conservation ◽  
Coupling Method ◽  
Wind Fields ◽  
Civil Structures ◽  
Civil Engineers

In the field of civil engineering, the meteorological data available usually do not have the detailed information of the wind near a certain site. However, the detailed information of the wind field during typhoon is important for the wind-resistant design of civil structures. Furthermore, the resolution of the meteorological data available by the civil engineers is too coarse to be applicable. Therefore it is meaningful to obtain the detailed information of the wind fields based on the meteorological data provided by the meteorological department. Therefore, in the present study, a one-way coupling method between WRF and CFD is adopted and a method to keep the mass conservation during the simulation in CFD is proposed. It is found that using the proposed one-way coupling method, the predicted wind speed is closer to the measurement. And the curvature of the wind streamline during typhoon is successfully reproduced.

scholarly journals Using the significant dust deposition event on the glaciers of Mt. Elbrus, Caucasus Mountains, Russia on 5 May 2009 to develop a method for dating and "provenancing" of desert dust events recorded in snow pack

2013 ◽  
Vol 13 (4) ◽  
pp. 1797-1808 ◽  
Author(s):  
M. Shahgedanova ◽  
S. Kutuzov ◽  
K. H. White ◽  
G. Nosenko
Keyword(s):  
Eastern Mediterranean ◽  
Meteorological Data ◽  
Source Region ◽  
Secondary Source ◽  
Snow Pack ◽  
Dust Deposition ◽  
Hysplit Model ◽  
Pressure System ◽  
Desert Dust ◽  
Caucasus Mountains

Abstract. A significant desert dust deposition event occurred on Mt. Elbrus, Caucasus Mountains, Russia on 5 May 2009, where the deposited dust later appeared as a brown layer in the snow pack. An examination of dust transportation history and analysis of chemical and physical properties of the deposited dust were used to develop a new approach for high-resolution "provenancing" of dust deposition events recorded in snow pack using multiple independent techniques. A combination of SEVIRI red-green-blue composite imagery, MODIS atmospheric optical depth fields derived using the Deep Blue algorithm, air mass trajectories derived with HYSPLIT model and analysis of meteorological data enabled identification of dust source regions with high temporal (hours) and spatial (ca. 100 km) resolution. Dust, deposited on 5 May 2009, originated in the foothills of the Djebel Akhdar in eastern Libya where dust sources were activated by the intrusion of cold air from the Mediterranean Sea and Saharan low pressure system and transported to the Caucasus along the eastern Mediterranean coast, Syria and Turkey. Particles with an average diameter below 8 μm accounted for 90% of the measured particles in the sample with a mean of 3.58 μm, median 2.48 μm. The chemical signature of this long-travelled dust was significantly different from the locally-produced dust and close to that of soils collected in a palaeolake in the source region, in concentrations of hematite. Potential addition of dust from a secondary source in northern Mesopotamia introduced uncertainty in the "provenancing" of dust from this event. Nevertheless, the approach adopted here enables other dust horizons in the snowpack to be linked to specific dust transport events recorded in remote sensing and meteorological data archives.

Evaluation of Surface Analyses and Forecasts with a Multiscale Ensemble Kalman Filter in Regions of Complex Terrain

2011 ◽  
Vol 139 (6) ◽  
pp. 2008-2024 ◽  
Author(s):  
Brian C. Ancell ◽  
Clifford F. Mass ◽  
Gregory J. Hakim
Keyword(s):  
Kalman Filter ◽  
High Resolution ◽  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
Complex Terrain ◽  
Error Variance ◽  
Small Scale ◽  
Observation Error ◽  
Grid Spacing ◽  
Background Error

Abstract Previous research suggests that an ensemble Kalman filter (EnKF) data assimilation and modeling system can produce accurate atmospheric analyses and forecasts at 30–50-km grid spacing. This study examines the ability of a mesoscale EnKF system using multiscale (36/12 km) Weather Research and Forecasting (WRF) model simulations to produce high-resolution, accurate, regional surface analyses, and 6-h forecasts. This study takes place over the complex terrain of the Pacific Northwest, where the small-scale features of the near-surface flow field make the region particularly attractive for testing an EnKF and its flow-dependent background error covariances. A variety of EnKF experiments are performed over a 5-week period to test the impact of decreasing the grid spacing from 36 to 12 km and to evaluate new approaches for dealing with representativeness error, lack of surface background variance, and low-level bias. All verification in this study is performed with independent, unassimilated observations. Significant surface analysis and 6-h forecast improvements are found when EnKF grid spacing is reduced from 36 to 12 km. Forecast improvements appear to be a consequence of increased resolution during model integration, whereas analysis improvements also benefit from high-resolution ensemble covariances during data assimilation. On the 12-km domain, additional analysis improvements are found by reducing observation error variance in order to address representativeness error. Removing model surface biases prior to assimilation significantly enhances the analysis. Inflating surface wind and temperature background error variance has large impacts on analyses, but only produces small improvements in analysis RMS errors. Both surface and upper-air 6-h forecasts are nearly unchanged in the 12-km experiments. Last, 12-km WRF EnKF surface analyses and 6-h forecasts are shown to generally outperform those of the Global Forecast System (GFS), North American Model (NAM), and the Rapid Update Cycle (RUC) by about 10%–30%, although these improvements do not extend above the surface. Based on these results, future improvements in multiscale EnKF are suggested.

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