Producing Meteorological Fields for Local Scale Pollutant Transport and Dispersion Estimates 1)Using the CALPUFF modeling system. 2)The model system produces.

Slides:



Advertisements
Similar presentations
A numerical simulation of urban and regional meteorology and assessment of its impact on pollution transport A. Starchenko Tomsk State University.
Advertisements

A thermodynamic model for estimating sea and lake ice thickness with optical satellite data Student presentation for GGS656 Sanmei Li April 17, 2012.
ANALYSIS OF TRACER DATA FROM URBAN DISPERSION EXPERIMENTS Akula Venkatram and Vlad Isakov  Motivation for Field Experiments  Field Studies Conducted.
Setting Acceptable Odor Criteria Using Steady-state and Variable Weather Data Z. Yu 1, H. Guo 2, C. Lague 3 1.Division of Environmental Engineering, University.
Coupled NMM-CALMET Meteorology Development for the CALPUFF Air Dispersion Modelling in Complex Terrain and Shoreline Settings Presented at: European Geoscience.
EPA PM2.5 Modeling Guidance for Attainment Demonstrations Brian Timin EPA/OAQPS February 20, 2007.
Meteorological Data Issues for Class II Increment Analysis.
Weather and X/Q 1 Impact Of Weather Changes On TVA Nuclear Plant Chi/Q (  /Q) Kenneth G. Wastrack Doyle E. Pittman Jennifer M. Call Tennessee Valley Authority.
The Use of High Resolution Mesoscale Model Fields with the CALPUFF Dispersion Modelling System in Prince George BC Bryan McEwen Master’s project
Assessing PM 2.5 Background Levels and Local Add-On Prepared by Bryan Lambeth, PE Field Operations Support Division Texas Commission on Environmental Quality.
Acknowledgments Jennifer Fowler, University of Montana, Flight Director UM-BOREALIS Roger DesJardins, Canadian East Fire Region, Incident Meteorologist.
Distribution of NO 2 concentrations over shooting (400 µg/m 3 per 1 hour) calculated with POLAIR dispersion model using (2004) NO 2 concentrations from.
For the Lesson: Eta Characteristics, Biases, and Usage December 1998 ETA-32 MODEL CHARACTERISTICS.
Chapter 3 Space, Time, and Motion. (1) Wind Observations Vectors have both magnitude and direction. Wind is a vector quantity. The components of wind.
Chapter 1 Ways of Seeing. Ways of Seeing the Atmosphere The behavior of the atmosphere is very complex. Different ways of displaying the characteristics.
Princeton University Global Evaluation of a MODIS based Evapotranspiration Product Eric Wood Hongbo Su Matthew McCabe.
1 Modelled Meteorology - Applicability to Well-test Flaring Assessments Environment and Energy Division Alex Schutte Science & Community Environmental.
Monitoring and Pollutant Load Estimation. Load = the mass or weight of pollutant that passes a cross-section of the river in a specific amount of time.
Derivation of the Gaussian plume model Distribution of pollutant concentration c in the flow field (velocity vector u ≡ u x, u y, u z ) in PBL can be generally.
fluidyn – PANAIR Fluidyn-PANAIR
Jenny Stocker, Christina Hood, David Carruthers, Martin Seaton, Kate Johnson, Jimmy Fung The Development and Evaluation of an Automated System for Nesting.
1 icfi.com | 1 HIGH-RESOLUTION AIR QUALITY MODELING OF NEW YORK CITY TO ASSESS THE EFFECTS OF CHANGES IN FUELS FOR BOILERS AND POWER GENERATION 13 th Annual.
Understanding Air Pressure
Earth Science 17.3 Temperature Controls
For the lack of ground data the verification of the TRMM performance could not be checked for the entire catchments, however it has been tested over Bangladesh.
Air Quality Modeling.
Identifying Non-Linear Flow for Modeling of Routine Releases from TVA Nuclear Facilities Toree M. Cook Kenneth G. Wastrack Doyle E. Pittman Tennessee Valley.
Development of WRF-CMAQ Interface Processor (WCIP)
AMBIENT AIR CONCENTRATION MODELING Types of Pollutant Sources Point Sources e.g., stacks or vents Area Sources e.g., landfills, ponds, storage piles Volume.
Lecture 4 Transport Network and Flows. Mobility, Space and Place Transport is the vector by which movement and mobility is facilitated. It represents.
Earth System Sciences, LLC Suggested Analyses of WRAP Drilling Rig Databases Doug Blewitt, CCM 1.
Russ Bullock 11 th Annual CMAS Conference October 17, 2012 Development of Methodology to Downscale Global Climate Fields to 12km Resolution.
Understanding the USEPA’s AERMOD Modeling System for Environmental Managers Ashok Kumar Abhilash Vijayan Kanwar Siddharth Bhardwaj University of Toledo.
June 19, 2007 GRIDDED MOS STARTS WITH POINT (STATION) MOS STARTS WITH POINT (STATION) MOS –Essentially the same MOS that is in text bulletins –Number and.
Dataset Development within the Surface Processes Group David I. Berry and Elizabeth C. Kent.
The Earth © Lisa Michalek.
Impact Of Surface State Analysis On Estimates Of Long Term Variability Of A Wind Resource Dr. Jim McCaa
The Semivariogram in Remote Sensing: An Introduction P. J. Curran, Remote Sensing of Environment 24: (1988). Presented by Dahl Winters Geog 577,
Meteorology of Winter Air Pollution In Fairbanks.
Accounting for Uncertainties in NWPs using the Ensemble Approach for Inputs to ATD Models Dave Stauffer The Pennsylvania State University Office of the.
An air quality information system for cities with complex terrain based on high resolution NWP Viel Ødegaard, r&d department.
DRAINMOD APPLICATION ABE 527 Computer Models in Environmental and Natural Resources.
Ice Cover in New York City Drinking Water Reservoirs: Modeling Simulations and Observations NIHAR R. SAMAL, Institute for Sustainable Cities, City University.
Regional Modeling Joseph Cassmassi South Coast Air Quality Management District USA.
Introduction to Modeling – Part II
Lagrangian particle models are three-dimensional models for the simulation of airborne pollutant dispersion, able to account for flow and turbulence space-time.
Types of Models Marti Blad Northern Arizona University College of Engineering & Technology.
© Crown copyright Met Office Downscaling ability of the HadRM3P model over North America Wilfran Moufouma-Okia and Richard Jones.
Boundary layer depth verification system at NCEP M. Tsidulko, C. M. Tassone, J. McQueen, G. DiMego, and M. Ek 15th International Symposium for the Advancement.
Page 1© Crown copyright Modelling the stable boundary layer and the role of land surface heterogeneity Anne McCabe, Bob Beare, Andy Brown EMS 2005.
Impact of Temporal Fluctuations in Power Plant Emissions on Air Quality Forecasts Prakash Doraiswamy 1, Christian Hogrefe 1,2, Eric Zalewsky 2, Winston.
Instruments. In Situ In situ instruments measure what is occurring in their immediate proximity. E.g., a thermometer or a wind vane. Remote sensing uses.
The application of Models-3 in national policy Samantha Baker Air and Environment Quality Division, Defra.
Statistical Evaluation of High-resolution WRF Model Forecasts Near the SF Bay Peninsula By Ellen METR 702 Prof. Leonard Sklar Fall 2014 Research Advisor:
7. Air Quality Modeling Laboratory: individual processes Field: system observations Numerical Models: Enable description of complex, interacting, often.
Comparisons of CALPUFF and AERMOD for Vermont Applications Examining differing model performance for a 76 meter and 12 meter (stub) stack with emission.
of Temperature in the San Francisco Bay Area
A.Liudchik, V.Pakatashkin, S.Umreika, S.Barodka
The Earth © Lisa Michalek.
Meteorological Site Representativeness and AERSURFACE Issues
Maj Dan Pawlak Air Force Liaison to NCEP
  Robert Gibson1, Douglas Drob2 and David Norris1 1BBN Technologies
WindNinja Model Domain/Objective
of Temperature in the San Francisco Bay Area
Chapter 10 Verification and Validation of Simulation Models
Suggested Analyses of WRAP Drilling Rig Databases
PAPER 3: Geographical Applications
Introduction to Modeling – Part II
REGIONAL AND LOCAL-SCALE EVALUATION OF 2002 MM5 METEOROLOGICAL FIELDS FOR VARIOUS AIR QUALITY MODELING APPLICATIONS Pat Dolwick*, U.S. EPA, RTP, NC, USA.
Data Assimilation of TEMPO NO2: Winds, Emissions and PBL mixing
Presentation transcript:

Producing Meteorological Fields for Local Scale Pollutant Transport and Dispersion Estimates 1)Using the CALPUFF modeling system. 2)The model system produces gridded meteorological fields that allow the puff transport and dispersion simulations (eg of benzene). These fields are produced by interpolating measured meteorological inputs as well as simulating local scale geographical effects.

Primary Needs to Produce Accurate Meteorological Fields for the Burlington Area. 1)Establish horizontal resolution of domain. 2)Select and prepare meteorological inputs. 3)Ensure that various meteorological field quantities produced by model are reasonable. 4)Tweak CALMET option settings to allow best performance in Burlington area – involves comparing modeled to measured meteorological fields as CALMET is rerun.

Examining the domain to ensure model simulation accurate 1.inspection of the geographical characteristics of the domain is essential so that the model runs may properly simulate atmospheric flow in the situation at hand. 2.Primary Characteristics of the Domain Include :  Lake Champlain  and the terrain gently sloping downwards to the lake (westwards), over about 10 kilometers distance.

Given the domain, the wind flow characteristics to capture :  In stable conditions at the surface slope flows will affect wind speeds and lifting or wrapping phenomena will affect wind direction. For less stable and more well- mixed conditions (i.e., at higher wind speeds), the geographical effects on the surface windfield are much less significant (i.e., wind speed and direction across the domain produced by CALMET are much more uniform). Therefore this evaluation to determine sufficient horizontal grid resolution for geographical effects is based on stable conditions. Examination of the annual frequency distribution of winds for Burlington reveals that for wind speeds less then 3 meters/second greatest directional frequency occurs from the easterly sectors (i.e., downslope flows toward the lake, usually occurring overnight).

Given the domain, the wind flow characteristics to capture :  Therefore it is essential that significant terrain features be sufficiently represented for modeled flow from the east downslope to the lake. Sufficient representation must allow two different physical phenomena to be properly simulated : 1). actual average slope over distances sufficient to cause slope flows. And, 2) actual height of terrain undulations that may causing wrapping of flow.  Comparison of terrain cross section from west to east over domain at 200 meter resolution indicates slope angle or incline of major terrain features are accurately represented.

Determination of Horizontal Model Resolution

 Because the slope angles of the more significant features are retained at 200 meter resolution it is likely the slope flows and wrapping situations will be properly simulated. Test runs at 200 meter resolution for this domain indicate that computing power is sufficient for annual runs in a reasonable time frame, therefore the 200 meter horizontal resolution will be used.

CALMET output fields directly derived from the Geographical inputs for the 200 meter horizontal resolution Burlington Domain.  Once the domain resolution is chosen and the geographical inputs prepared, production of certain fields directly related to the geographical representation across the domain are automatically produced.

Meteorological Observations Used for the Burlington, Vermont Domain - Surface  For the domain for this study meteorological conditions over water (lake Champlain), and over land must be represented, because of significant differences in temperature, moisture, and winds in some situations. Over land, there are no significant orographic barriers or other geographical variations within the domain requiring more than one surface station for adequate coverage.  Therefore, at the surface, the Colchester Reef station represents over water conditions, and the Burlington Airport represents over land conditions.

Meteorological Observations Used for the Burlington, Vermont Domain – Upper Air  Two alternatives currently exist for upper air representation for this domain : 1. Utilization of radiosonde data from a remote location (Albany, NY), or, 2.Extraction of prognostic windfields from the 12 km Resolution NAM model for locations within the domain.  Which fields best for application will be examined in Validation Procedures

Meteorological Observations– Upper Air Radiosonde versus NAM fields  Examine times when the wind fields differ.  For these times, the difference in upper air representation in the two cases is because of significant differences in the upper air windfield over the New England area. Over distances of 100 km or more in New England, variations in upper air wind field may be significant (cut off lows, other phenomena caused by land – sea interface).  The NAM derived fields can simulate smaller scale spatial variations. When winds are uniform over the New England area The NAM derived fields are very similar to the radiosonde measurements. The NAM derived fields are available at a 3 hour time resolution.  the NAM derived fields will be used for the final wind field production.

Validation Procedures  The Validation procedures examine wind fields separately from other output fields, such as mixing heights and stability classifications affecting pollutant dispersion.  For output fields dependent on vertical temperature profiles, such as the mixing height, evaluation of the NAM fields used in combination with the measured surface temperature is especially critical.

Evaluation of Mixing Heights and Stability Classification  A series of CALMET runs were performed using three basic combinations of the meteorological inputs available and examining mixing heights and stability classifications produced by CALMET.  These fields were compared and evaluated for reasonableness for winter and summer episodes, for day and night time conditions.  The Figures below depict mixing heights produced by CALMET for the Burlington domain for two choices of upper air wind data.

Park St Fanny Allen/UVM Calahan Park Location I-89 Site ExxonMobil Site Rt. 2/Mary St Barnes School Downtown Trailer Eight Standard TO-15 Analysis Sampling Sites (24-hr Samples)

Evaluation of Mixing Heights  In comparison of these figures, it is apparent that overland daytime mixing heights for the NAM upper air run are significantly greater. It was concluded that these height were not unreasonable, and the differences between these figures occurred because the NAM upper air fields, being representative of atmospheric features 300 km north of Albany, New York, were usually colder, resulting in greater potential for thermal mixing, and represented in the greater modeled mixing heights.  For both day and night time conditions, the primary effect on mixing heights estimates in utilizing the Radiosonde upper air data from Albany, is to decrease their values, thereby increasing predicted ground level concentrations for emission scenarios near ground level.

Evaluation of Stability Classification  Of primary importance to the rate of lateral Gaussian dispersion in Calpuff’s predictive efforts is the PGT stability classification derived by CALMET.  The PGT stability calculations are directly dependent on incoming solar radiation and wind speeds, and other observations of surface weather conditions, such as cloud cover. The most accurate PGT stability calculations occur using measured surface data, and no difference in the PGT stability calculations occurs for CALMET runs with the two alternative upper air wind field input data sets, Albany upper air and NAM fields.

Choosing the Best CALMET Settings for the Burlington, Vermont Domain  In examining the accuracy of the CALMET wind fields in this study the intent was to make a domain wide assessment. After deciding that inclusion of the NAM data for upper air representation will occur, there are many parameter settings in the CALMET model that affect the model’s handling of surface terrain effects.

Choosing the Best CALMET Settings for the Burlington, Vermont Domain (Cont.)  In the CALMET runs occurring in this study many of the parameter settings cause various physical processes to be handled differently over a range of numerical settings.  For the horizontal scale of this study, 16.6 km by 16.6 km, it was considered appropriate to use only one station as an observation data point.  When the CALMET model is applied over an area of highly complex terrain, the linear interpolation of more than one observation point is only beneficial to grid wide accuracy if synoptic-scale variation is represented by the observation point wind fields.

Choosing the Best CALMET Settings for the Burlington, Vermont Domain (Cont.)  For a domain wide model validation it is necessary to rely on a set of meteorological observations not used as input to run the CALMET model. The station used in this evaluation was Essex Junction, Vermont.  The comparison between the temporally and spatially matched sets of wind vectors involved computation of error measures for both the wind speed and wind direction.  The Bias was computed as the average of the difference between modeled and measured values for each data pair accounting for the sign, where a positive value means that the direction of the predicted wind is clockwise of the observed.  The Error measure is an absolute (i.e. sign independent), measure of the average difference between modeled and measured data pairs.

Choosing the Best CALMET Settings for the Burlington, Vermont Domain – Bias and Error Estimates.  The bias can be considered a measure of error for domain wide transport, i.e., whether the average direction of puff transport is off by 15 degrees, or the average windspeed is 3 knots too low.  The error measure better addresses the degree the wind is mispredicted at any time, quantifies the ultimate predictability of the atmosphere by the model, and may effect the rate of lateral dispersion as the effect of the directional error is compounded over a puff’s travel in the CALMET windfield.

Table 1. Below lists the varied parameter settings for each of the 10 final runs that occurred.

Table 2. Results of Modeled to Measured CALMET Wind field Validation (Bias and Error Estimates).

Choosing the Best CALMET Settings for the Burlington, Vermont Domain (Cont.)  The error measures described above were compared for a multitude of CALMET runs, where for each run the parameter settings most affecting terrain handling were altered with the intent of improving overall grid accuracy of the surface windfield.  The proper scale limiting the extent of simple interpolation of measured met inputs was determined, as well as the settings dictating lifting or wrapping of flow for the domain setting.

Conclusions  The findings in this study allow us to conclude that utilization of the NAM meteorological fields is acceptable for this application of CALMET. It was necessary to demonstrate the acceptability of using upper air NAM – derived meteorological fields with measured surface data.  Examination of the CALMET wind field predictions for this high resolution domain, by comparing modeled to measured values in Essex Junction, indicate generally good model performance and allow us to choose the option settings for the final runs that will be used by CALPUFF.

Some Local – Scale Applications of Calpuff in Complex Terrain  Rutland, Vermont – To evaluate PM2.5 concentrations, primarily from residential (wood smoke), emissions.  Ticonderoga – To evaluate impacts from the IP paper mill.  White River Junction, Vermont – to evaluate PM2.5 concentrations in tight valleys with steep terrain from Outdoor wood boilers.