Prognostic Meteorological Models and Their Use in Dispersion Modelling
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This document discusses prognostic meteorological models and their use in dispersion modelling. It focuses on the Weather Research and Forecasting (WRF) model. It describes WRF's development and capabilities, and provides an example of its use in an air quality modelling case study in the Middle East. The key findings are that WRF can simulate source location meteorology with relative accuracy compared to observations, provides upper-air data at source locations, and is an alternative source of meteorological data for locations without observation systems. The document questions WRF's potential application in the UK.
Prognostic Meteorological Models and Their Use in Dispersion Modelling
- 1. Trinity Consultants Inc. 2018 PROGNOSTIC METEOROLOGICAL MODELS AND THEIR USE IN DISPERSION MODELLING DMUG 2018 LONDON, UNITED KINGDOM ARUN KANCHAN TRINITY CONSULTANTS, INC. APRIL 19, 2018
- 2. Trinity Consultants Inc. 2018 Prognostic Meteorological Models and their Use in Dispersion Modelling AGENDA 1. INTRODUCTION 2. PROGNOSTIC MODEL OF FOCUS: WEATHER RESEARCH AND FORECASTING (WRF) MODEL 3. CASE STUDY: APPLICATION OF WRF FOR AQM IN THE MIDDLE-EAST 4. FINDINGS AND CONCLUSIONS
- 3. Trinity Consultants Inc. 2018 INTRODUCTION
- 4. Trinity Consultants Inc. 2018 Meteorological Input Types Used in Dispersion Modeling Site-Specific Installed meteorological observation tower Most accurate meteorological data at the source location Installation/maintenance costs and data handling/quality control procedures National Weather Service / Met Office Routinely available Generally not at the source location May not be the most adequately representative data (e.g. complex terrain, distance, etc.) Prognostic Meteorological Data Three-dimensional mesoscale computer models: MM5 and WRF
- 5. Trinity Consultants Inc. 2018 Discontinuance of MM5 and Advent of WRF
- 6. Trinity Consultants Inc. 2018 PROGNOSTIC MODEL OF FOCUS: WEATHER RESEARCH AND FORECASTING (WRF) MODEL
- 7. Trinity Consultants Inc. 2018 WRF Developed in the U.S. by National Center for Atmospheric Research (NCAR) Primary meteorological tool used by U.S. EPA Continuous updates Supported across a broad community Modeling across multiple scales
- 8. Trinity Consultants Inc. 2018 WRF: Visualization
- 9. Trinity Consultants Inc. 2018 Mesoscale Met Data “Mesoscale” is that domain of atmospheric physics that takes place on the order of approximately 100 km and about 1 hour Weather forecast models operate by computing mesoscale physical parameters at hourly time steps over the entire depth of the atmosphere Parameters are computed over a three- dimensional grid that covers the globe and multiple (approximately 30) levels of the atmosphere
- 10. Trinity Consultants Inc. 2018 Mesoscale Met Data MM data are used as an “initial guess” wind field input to CALMET From this wind field, terrain effects and slope flow are computed This wind field is then supplemented with interpolated observations from surface and upper air stations and smoothed to create the final wind field
- 11. Trinity Consultants Inc. 2018 Mesoscale Met Data MM data are compiled for each hour of the analysis, at each MM grid point selected for the following surface parameters Date and time Grid cell indices Surface pressure Past hour rainfall
- 12. Trinity Consultants Inc. 2018 Mesoscale Met Data MM data are compiled for each hour of the analysis, at each MM grid point selected for the following upper air parameters at each mandatory level (including surface) and additional significant levels Pressure Elevation Temperature/Dew point depression Wind direction and speed
- 13. Trinity Consultants Inc. 2018 WRF Guidance from U.S. EPA* Domain Selection Large enough to capture meteorological phenomena and topographic features that impact source location Resolution Typically two-way nesting method: parent and nest domains Complex terrain of land/water interface: 4 km (or finer) nest domain, 12 km for the parent *Modeling Guidance for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5 and Regional Haze, 2014
- 14. Trinity Consultants Inc. 2018 Data Set Prepared for WRF Processing Surface weather reports operationally collected by the National Centers for Environmental Prediction (NCEP) NCEP FNL (Final) Operational Global Analysis data which are on 1-degree by 1-degree grids prepared operationally every six hours Global Upper Air Observational Weather Data which are collected by the NCEP A daily, high-resolution, real-time, global, sea surface temperature (RTG_SST) analysis developed by the NCEP and Modeling and Analysis Branch (MMAB).
- 15. Trinity Consultants Inc. 2018 WRF Data Inputs
- 16. Trinity Consultants Inc. 2018
- 17. Trinity Consultants Inc. 2018 CASE STUDY: APPLICATION OF WRF FOR AQM IN THE MIDDLE-EAST
- 18. Trinity Consultants Inc. 2018 Modeling Approach – Puff Model Propagation Hour 1 Hour 2 Hour 3 Hour 4 Hour 1 Hour 2 Hour 3 Hour 4 Plume Dispersion Local Winds Source Three dimensional advection and dispersion simulated + Chemistry • Surface Data • Upper Air Data • Overwater Data 4 km Variable
- 19. Trinity Consultants Inc. 2018 FINDINGS AND CONCLUSIONS
- 20. Trinity Consultants Inc. 2018 CONCLUSION Prognostic Models simulate the source location with relative accuracy Retrospective application grounded by actual observations through four- dimensional data assimilation Improved representativeness relative to NWS data Provides upper-air data at source location Studies validate modeled data to be well correlated to balloon observations Alternative source of met information for locations where observation systems are not available Higher density of data for models such as CALPUFF
- 21. Trinity Consultants Inc. 2018 APPLICATION IN THE U.K. ?
- 22. Trinity Consultants Inc. 2018 Thank you!