# Presentation: 690921

## OFCM Special Session on Research Needs

***OFCM Special Session on Research Needs***
***19 Jun 03***

***John Pace***
***Operational Applications Division***
***Technology Development Directorate***
***Defense Threat Reduction Agency***

## Two Research Areas of Particular Interest

-   Urban winds, turbulence, and dispersion
-   Integration of agent sensor data with dispersion models

## Urban Winds, Turbulence, and Dispersion

-   Increasing awareness of importance of urban dispersion for emergency response, military operations, and others
-   Previous urban dispersion studies: helpful, incomplete
-   Some old studies, but these lack comprehensive data
-   Some recent studies, but these don’t answer all the relevant questions
-   Planned studies will approach needs in various ways
-   The primary requirement is to obtain data to improve *model performance *and* scientific understanding *in urban situations

## Model Development and Validation

-   Many models for urban effects are available
-   Wide range of approaches and applications
-   Parameterization of urban effects in mesoscale models
-   Fast-response urban dispersion models
-   Quick-response urban wind models
-   CFD wind and dispersion models
-   Requirement:  Acquire data suitable for validation and evaluation of all types of models
-   Requires variety of experiments

## Scientific Understanding of Urban Boundary Layer

-   Study urban boundary layer structure and development
-   Both daytime and nighttime studies
-   Range of wind conditions
-   Interaction between scales
-   Long-term statistics for model parameterizations

## Future Urban Studies

-   Joint Urban 2003 in Oklahoma City
-   Limited-duration (one month)
-   Abundant equipment to study scale interactions, detailed flow and dispersion in various parts of city
-   DCNet in Washington DC
-   Long-term (plan for several years)
-   Multiple sensors across DC region
-   Urban Atmospheric Observatory in New York City
-   Long-term (plan for several years)
-   Dense network in limited area of downtown NYC
-   UMPIRE on Penn State campus (proposed)
-   Study wind flow around buildings

## Sensor Data Integration

-   Becoming an actively discussed topic
-   Several approaches have been proposed
-   It’s usually possible to think of reasons they won’t work in certain situations
-   This is NOT a reason not to proceed—optimists needed

## Sensor Data Integration

-   Variety of objectives
-   Look *backward* to determine source characteristics (particularly location)
-   Look *forward* to predict what happens to observed material—use sensor reading as source term
-   Combine sensor data with dispersion calculations
-   My favorite analogy is with weather observations combined with weather model output as first guess—resulting blended analysis is better (more accurate, more complete) than either alone
-   Help identify false positives or calibration errors
-   *Get the most complete depiction of situation*

## Sensor Data Integration Research

-   Mathematical consideration of problem
-   Fuzzy logic?
-   Other approaches?
-   Incorporate false positives, false negatives, multiple releases at different times, moving releases...
-   Lab and field studies
-   Probably need very dense network of samplers, high resolution models to give detailed picture of releases
-   Need to know ground truth (remote sensing?)
-   See if selected special observations can reveal true pattern

## Sensor Data Integration Research

-   Tech Panels 9 and 10 of The Technical Cooperation Program will host a combined meeting to discuss sensor data integration in Sep 03 in Salt Lake City
-   Propose lab or field studies then