Meteorological Modeling & Analysis

Exponent has strong capabilities and deep experience in using state of the science numerical weather prediction and diagnostic meteorological models for a variety of applications. Exponent’s meteorological modeling and analysis experience includes:


  • Meteorological Modeling for Air Quality Analysis
  • Forensic Meteorology
  • Severe Storm Impacts and Analysis
  • Atmospheric Boundary Layer studies
  • Real-Time Numerical Meteorological and Air Quality Forecasting
  • Model Evaluation Studies

Numerical Weather Prediction Modeling with WRF and MM5

Numerical weather prediction models are prognostic models that can simulate the evolution of atmospheric circulation systems at a range of scales. Both the Penn State Fifth Generation Mesoscale Model (MM5) and the Weather Research and Forecast Model (WRF) are non-hydrostatic numerical models capable of simulating such phenomena as severe convective storms, tropical and extra-tropical cyclones, sea-land breeze circulations, and mountain-valley wind systems. Very often observational data is of insufficient spatial or temporal resolution or is non-existent making it difficult or impossible to adequately represent the structure and evolution of important meteorological features.

Exponent scientists have conducted numerous meteorological simulations worldwide with MM5 and WRF to depict fine scale topographically forced flow features as well as detailed meteorological structures associated with severe storms such as hurricanes.

Using Observational Data and Numerical Meteorological Models

Exponent scientists use a combination of available observational data and numerical modeling to perform a variety of meteorological analyses. Exponent uses sophisticated data assimilation methods such as four dimensional data assimilation (FDDA) known as nudging in performing multi-year retrospective simulations to develop three-dimensional gridded meteorological analyses. Numerical simulations using FDDA involve adjustments to the model predictions at regular intervals during the simulation to constrain the model predictions toward observations while maintaining dynamically balanced meteorological fields.

Diagnostic Modeling with CALMET

Diagnostic models such as the CALMET model, developed by Exponent scientists, are useful tools to develop very high-resolution meteorological fields using a variety of data. Diagnostic meteorological models can ingest both meteorological observations and gridded meteorological data from numerical weather prediction models and are often used as a way to enhance three-dimensional wind fields by making adjustments using higher resolution topographic and land use data and incorporating representative surface and upper air observations. The CALMET model is part of the CALPUFF modeling system.

Exponent scientists have extensive experience conducting multi-year retrospective FDDA simulations with MM5 and WRF to develop high-resolution three-dimensional gridded meteorological data that can be used to drive air quality models such as the CALPUFF modeling system. Such data sets can also be used for meteorological analysis over specific regions where observational data networks are not adequate.

Exponent has specialized high capacity computing capabilities specifically configured for advanced numerical weather modeling studies. This includes a 120-processor Linux cluster computer which is dedicated exclusively to meteorological and air quality modeling.

Meteorological Conditions Associated with Tropical Storms or Flash Flood Events

Exponent scientists have used a variety of available observational data to perform an analysis of meteorological conditions associated with such phenomena as tropical storms or flash flood events. These datasets include meteorological observations, radar data, satellite imagery, buoy data, three-dimensional regional and global analysis fields, and high resolution terrain and land use data. When observational data are not available or do not have sufficient resolution to resolve meteorological conditions, Exponent uses numerical meteorological models and data assimilation techniques to reconstruct winds and precipitation from high impact weather events. Numerical meteorological modeling is used to develop a high spatial and temporal resolution analysis of meteorological fields during the storm event such as surface winds and precipitation amounts that can be used to perform storm damage assessments. Exponent scientists have coupled numerical meteorological model output with Computational Fluid Dynamics (CFD) models to determine the pressure forces on building structures and thus assess if structural damage is due to a particular storm event.

Forensic Meteorology Services

Exponent atmospheric scientists use a wide range of meteorological data to reconstruct weather events. These data includes surface weather observations, upper air soundings, radar imagery, satellite imagery, three-dimensional analysis from National Weather Service meteorological models, lightning data, snow and ice cover data, and climatological data and summaries. If needed, high-resolution numerical modeling can be coupled with available data to reconstruct an event. Our forensic meteorological services include evaluating the following meteorological conditions:


  • Wind, temperature, humidity, visibility, and precipitation
  • Ice or snow cover, snow melt and refreezing
  • Heat waves and cold waves
  • Fogging and visibility
  • Air pollution and odors

Severe weather events often can result in litigation. Exponent can analyze severe weather events including:


  • Hurricanes and tropical storms
  • Winter storms
  • High wind events
  • Flooding events
  • Severe Thunderstorms
  • Lightning
  • Wind versus water damage

Exponent’s atmospheric scientists have performed a range of forensic meteorological services for clients. For example, Exponent scientists performed a detailed meteorological analysis of a flash flood event in the New York region. They performed high-resolution numerical modeling of Hurricane Katrina to evaluate the surface wind field of the storm as it made landfall near New Orleans to evaluate wind versus water damage to building structures.

Wind Maps to Assist in Micrositing of Wind Turbines

Another application for numerical meteorological models is to develop high resolution wind maps to assist in micrositing of wind turbines. Both MM5 and the WRF models have been used to provide a refined site specific independent analysis of wind characteristics that can be used to supplement existing wind maps and provide detailed guidance when siting wind turbines. The WRF model is capable of being run at sub-kilometer resolutions making it attractive for developing limited area fine-scale wind maps for wind turbine siting applications.

Atmospheric Boundary Layer Studies for Renewable Energy, Aviation, and Agriculture  

Exponent scientists perform customized meteorological studies of atmospheric boundary layer flow to examine wind and turbulence characteristics that impact wind farms, aviation operations, agricultural operations such as pesticide and herbicide spraying, and urban planning. We perform these using observational data, numerical modeling with the Weather Research and Forecast model and Computational Fluid Dynamics (CFD) modeling. Exponent scientists also use the NOAA Rapid Refresh (RAP) three-dimensional hourly analysis data and the High-Resolution Rapid Refresh (HRRR) analyses to develop boundary layer profiles of wind and temperature for evaluating wind shear and turbulence characteristics. These tools are used to develop guidance information and real-time customized forecast systems for various weather sensitive operations within the atmospheric boundary layer including but not limited to:


  • Wind shear and turbulence for wind energy and aviation
  • Meteorological studies for aviation and agriculture
  • Real-time air quality forecast systems for agricultural spraying and mining operations
  • Rainfall forecasting guidance for storm water sampling programs
  • Building structure induced wind flows for industrial sites and urban planning studies

Exponent scientists recently performed a complex study of the atmospheric boundary layer to examine low level jet flows and thunderstorm outflow boundaries and the impact on wind turbine operations at several wind farms. We have developed and continuously maintain a real-time air quality forecast system for mining operations in Chile. Exponent scientists have also conducted CFD modeling studies to support offshore oil and gas operations.

Air Quality Forecast Systems for Industry

Exponent has coupled numerical weather prediction forecast models with the CALPUFF dispersion modeling system for international industrial clients in the mining and metals industries. The turn-key air quality forecast systems developed by Exponent predict air concentrations of various pollutants emitted during facility operations.

Meteorological Sensitive Activities Including Sailing

A customized real-time meteorological forecast system can also be developed to provide guidance for meteorological sensitive activities. For example, Exponent meteorologists have provided support to a U.S. sailing team at the America’s Cup races in New Zealand and for a team in the around-the-world Volvo Ocean race.

References 

Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Wang W, Powers JG. A description of the Advanced Research WRF Version 2. NCAR/TN-408+STR, 2006 (last revised Jan 2007). 

Scire JS, Strimaitis D, Yamartino RJ. A user's guide for the CALPUFF dispersion model (Version 5). 2000. 

Scire JS, Robe FR, Strimaitis D. A user's guide for the CALMET meteorological model (Version 5). 2000. 

Grell G, Dudhia J, Stauffer DA. Description of the fifth generation Penn State/NCAR mesoscale model (MM5). NCAR/TN-398+STR, December 1994.

Professionals

Knowledge