Number range CHAPTER

FEDERAL COMMITTEE FOR

METEOROLOGICAL SERVICES AND SUPPORTING RESEARCH

(FCMSSR)

*WORKING GROUP FOR*

*URBAN METEOROLOGY (WG/UM)*

**[JOINT ACTION GROUP FOR JOINT URBAN TEST BEDS
(JAG/JUTB)]{.underline}**

## RECORD OF ACTIONS FOR MEETING 2006-2

March 1-2, 2006

**Attendees:**

  ---------------------------------- ------------------------------------
  Dr. Walter Bach, Army/ARO (CCH)    Ms. Jocelyn Mitchell, NRC (M)

  Mr. Will Pendergrass, NOAA/ARL     Ms. Maria Pirone, AER (SME)
  (CCH)                              

  Mr. Jeff McQueen, NOAA/NWS/NCEP    Dr. Paul Bieringer, MIT Lincoln Lab
  (M)                                (SME)

  Mr. Rich Jesuroga, NOAA/OAR/ESRL   Dr. David Bacon, SAIC (SME)
  (A)                                

  Dr. Paula Davidson, NOAA/NWS/OS&T  Dr. Robert Bornstein, San Jose State
                                     University (SME)

  Mr. Andrew Noel, NOAA/NWS/OCWWS    Dr. Rama Tangirala, DC DOH (SME)
  (A)                                

  Mr. Rick Fry, DOD/DTRA (M)         Ms. Suzanne Condon, Massachusetts
                                     DPH (SME)

  Mr. Kim Curry, Navy (M)            Ms. Margaret Round, Massachusetts
                                     DPH (SME) -- by phone

  LtCol Mark Zettlemoyer, USAF, Air  Mr. Raymond Rogers, UMBC (O)
  Force (M)                          

  Dr. Dennis Garvey, Army ARL (M)    Dr. David McLaughlin, UMASS-CASA
                                     (SME)

  Mr. Donny Storwold, Army DPG (A)   Dr. David Kingsmill, NOAA ESRL (SME)
  -- by phone                        

  Ms. Vickie Boothe, DDHS/CDC/NCEH   Mr. Jay Titlow, WeatherFlow Inc.
  (M)                                (SME)

  Ms. Julie Thomas, DOI/NPS (M)      Mr. Mark Nilles, DOI /USGS (SME)

  Mr. Dirk Herkhof, DOI/MMS (M)      Mr. Jim McNitt, OFCM/STC (ES)

  Mr. Pat Kennedy, DOT/FHWA (A)      Mr. Robert Dumont, OFCM

  Dr. Michael F. Jasinski, NASA (M)) Ms. Margaret McCalla, OFCM

  Dr. Jason Ching, EPA (A) -- by     
  phone                              
  ---------------------------------- ------------------------------------

The following summarizes the presentations, discussions, and outcomes
that resulted from the meeting. The presentations are available for
viewing on the OFCM ftp site.

1.  **Opening remarks**. Mr. Bob Dumont, welcomed the participants on
    behalf of Mr. Samuel P. Williamson, the Federal Coordinator for
    Meteorology.

2.  **Opening Remarks**. Dr. Walter Bach (Army/ARO) and Mr. Will
    Pendergrass (NOAA/ARL), the JAG/JUTB Cochairs, opened the meeting
    with a review of the draft terms of reference (TOR) drafted by the
    OFCM staff.

3.  **Presentation:** Homeland Security Infrastructure Program (HSIP) -
    Urban Area Orthoimagery (30 mins). Mr. David Roberts, Aerial
    Photography and Orthoimagery Project Manager, DOI/USGS described the
    Homeland Security Infrastructure Program Memorandum of Understanding
    which was signed July 2002 by DOD/National Geospatial-Intelligence
    Agency (NGA), DOI/USGS, and the Federal Geographic Data Committee
    (FGDC)[^1]. The HSIP was formed after 9/11 to provide the data
    layers required for homeland security. The focus is to gather data
    layers from diverse sources and to develop two accessible data
    bases, one that is unclassified and the other that is classified.
    The public data is available through the Seamless Data Distribution
    System (SDDS) at the Earth Resources Observation Systems (EROS) Data
    Center (EDC) NGA and USGS meet regularly to determine requirements
    and to acquire funding. Imagery data are the most dynamic of the
    data collected in the program. Other data layers are less dynamic
    and some are static. USGS relies on partnerships, including
    partnerships with state, local, and city governments, to fund the
    program. USGS State Liaisons help to facilitate these partnerships.
    The HISP supports National Special Security Events (NSSE) \-- NGA
    identifies the customer requirements and passes the requirements to
    USGS. USGS brokers the acquisition of vector data and imagery from
    local sources in a short time-frame and the local partner then sends
    imagery and data to NGA. USGS offers the following in-kind services:
    liaison staff, contract support, data QA/QC, technical services from
    EROS, data hosting, data archive, and data delivery. As of 2005, the
    status of the HSIP is:

-   131 Urban Areas with first coverage

-   2 Urban Areas remaining

-   49 Urban Areas with second coverage

-   13 Urban Areas with third coverage

-   More than 70 partnerships established with States, counties, cities

-   Contract experience on CSC, GGI

-   Contract purchases on CRSDC, both aerial and satellite

**Discussion:** The group discussed the Homeland Infrastructure
Foundation Level Data (HIFLD) efforts. More information on HIFLD is
available at: <http://www.hifldwg.org/>.

4.  **Presentation: The Hydrometeorology Testbed**. Dr. David Kingsmill,
    University of Colorado CIRES and NOAA ESRL. The Hydrometeorology
    Testbed (HMT) concept began with meetings in the 1990s at NOAA NWS.
    During the early planning meetings information and capability gaps
    were identified. These gaps included: quantitative precipitation
    estimates (QPE) and quantitative precipitation forecasts (QPF),
    hydrologic forecasting of high resolution flood warnings, and
    probabilistic warnings.

    a.  The Science Technology Infusion Program (STIP) Integrated
        product Team (IPT) for Hydrologic Services compiled a list of
        R&D needs and recommendations, that included: develop QPE
        techniques that optimally blend next-generation radar, satellite
        (e.g, GPM), and rain gauge data, improve short-term
        radar-satellite precipitation nowcasting techniques blended with
        NWP forecasts, develop high resolution hydrologic forecast
        models of water excess-deficit at ungauged locations, develop
        ensemble NWP and hydrologic model forecasts with associated
        reliability information, improve NWP model physics and increase
        assimilation of existing observational datasets, and implement
        hydrometeorological testbeds to demonstrate and evaluate
        next-generation datasets, forecast techniques, and models.

    b.  The HMT accelerates the infusion of new technologies, models,
        and scientific results from the research community into daily
        forecasting operations of NOAA NWS and its River Forecast
        Centers (RFC). Transition from research to operations needs
        resources for development and needs to have systems in operation
        for extended periods of time for testing and evaluation---the
        test bed is the intersection of the two domains.

    c.  Feedback from users is critical. The primary goals of the HMT
        are:

        1.  Systematically evaluate promising new methods that can
            influence both NWP and nowcasting using the man-machine mix
            forecasting paradigm,

        2.  Assess their value in terms of improved regional performance
            on Flood/Flash Flood Warning and QPF GPRA measures, and

        3.  Use these results as an objective basis for decisions on
            transitions to operations both in the test region and
            nationally.

5.  **Panel Session and Discussion: Users' Needs for Urban
    Meteorological Information Moderator:** Mr. Will Pendergrass,
    Cochair.

    a.  Ms. Suzanne K. Condon, Associate Commissioner, Center for
        Environmental Health and Interim Director, Center for Emergency
        Preparedness, Massachusetts Department of Public Health.
        Presentation is on the OFCM ftp site.

        1.  Ms. Condon described the roles and responsibilities of the
            Massachusetts Center for Environmental Health (CEH). CEH has
            a broad mission of protecting the public health from a
            variety of environmental exposures. CEH responds to
            environmental health concerns and provides communities with
            epidemiologic and toxicological health assessments. She also
            described the importance of environmental public health
            tracking.

        2.  The environmental public health tracking (EPHT) program is
            the ongoing collection, integration, analysis, and
            interpretation of surveillance data about the following
            factors: environmental hazards, exposure to environmental
            hazards, and health effects potentially related to exposure
            to environmental hazards. She described the importance of
            surveillance. The goal of EPHT is to protect communities by
            providing information to federal, state, and local agencies.
            The Health Insurance Portability and Accountability Act
            (HIPAA) and Family Educational Rights and Privacy Act
            (FERPA) made the collection of data more challenging, but
            Massachusetts law requires reporting of communicable
            diseases upon request. These agencies, in turn, will use
            this information to plan, apply, and evaluate public health
            actions to prevent and control environmentally related
            diseases. Health outcomes of concern (and the associated
            pollutants/ sources of concern) include: pediatric asthma
            (VOCs/HAPs, PM, SO2, NO2, and Ozone), developmental
            disabilities (Mercury, PCBs, and Lead), cancer (Air
            pollution sources, Contaminated drinking water, VOCs/HAPs,
            and Metals), and birth defects (contaminated drinking water,
            VOCs/HAPs, and Metals). Other health outcomes of concern
            include: Temperature-related morbidity and mortality,
            Vector-borne diseases, West Nile Virus, "Triple E" --
            Eastern Equine Encephalitis, Microbial agents in waterborne
            (e.g., drinking water) and food borne (e.g., seafood, fresh
            produce) diseases, and Red tide.

        3.  CEH analyses are inherently spatial \-- CEH's GIS Center
            provides ability to integrate robust databases: surveillance
            data from EPHT (pediatric asthma, childhood cancer;
            childhood lead poisoning; Lupus; Vital records (e.g.,
            births, deaths)), geopolitical boundaries, key
            infrastructure (e.g., hospitals, Community Health Centers),
            demographic data from Census (e.g., sensitive receptors),
            and environmental locations (e.g., water supplies, DEP
            Hazardous Waste Sites).

        4.  Exposure to Environmental Pollutants. Typically,
            environmental data are not available and surrogates for
            exposure are used (e.g., proximity to source). When
            available, modeling and monitoring data are used to improve
            exposure estimates by quantifying the spatial and temporal
            distribution of ground-level concentrations of pollutants
            across study area. The goal is to incorporate the
            distribution of pollutant exposures across a geographic area
            as spatially-continuous GIS data layers. Appropriate
            geographic resolution is the key. For example: 36-km
            modeling domain would not be useful for public health
            linkage. Need the distribution of ground-level
            concentrations with confidence intervals to characterize
            exposure gradients (i.e., high, medium, low).

        5.  **In summary**: EPHT data is being generated and
            simultaneously spatially organized in GIS; use of GIS layers
            being developed has great promise for both environmental
            health and preparedness/response; integrating ATD modeling
            data into GIS can provide more precise estimates of
            population exposure both temporally and spatially; data
            access and sharing is critical; and a mechanism for
            providing feedback from public health community on
            pollutants of concern and modeling capabilities as new
            health information becomes available is critical. Ms. Condon
            requested assistance from the JAG/JUTB in helping to satisfy
            the following needs:

            a.  Air quality: EPHT linkage requires ground-level
                pollutant concentration data that are spatially and
                temporally relevant

            b.  Water quality: Deposition modeling data can assist EPHT
                efforts by identifying impacted water bodies (e.g.
                mercury/developmental disabilities)

            c.  Emergency Preparedness: Deposition modeling data can be
                used in event of airborne releases and for
                decision-making in emergency response. Identify impacted
                areas for evacuation, prophylaxis, etc. Determine likely
                impacts from deposition to water supply. Identify areas
                not impacted.

            d.  Needs/Concerns Over Data/Access:

                i.  ATD modeling data need to be spatially and
                    temporally compatible with health outcome data for
                    appropriate use in decision making

                ii. Pollutants need to be relevant to public health

                iii. Strengths and limitations of the model need to be
                     transparent for the users

                iv. Need to understand QA/QC of data to ensure use of
                    validated data

                v.  Need to have modeling data reported in a
                    geo-referenced grid format using any GIS industry
                    standard

                vi. Need to have infrastructure in place at CEH to
                    collect, analyze, and manage data

    b.  Dr. Rama S. Tangirala, Air Quality Division, Bureau of
        Environmental Quality, District of Columbia Department of
        Health. Boundary layer profilers have been useful, and DC would
        like to have profiler data available for operational air quality
        forecasting (to verify the mixed layer height in the prognostic
        models). Near-term goals and mandates must be met by 2010. The
        biggest gaps and greatest hurdles include accurate boundary
        layer heights.

6.  **Presentation:** FAA Sponsored Boundary Layer Wind Sensing and
    Analysis Activities, Dr. Paul E. Bieringer, Weather Sensing Group,
    MIT Lincoln Laboratory. Boundary layer sensing networks include:
    operational and prototype weather sensor integration systems,
    Integrated Terminal Weather System (ITWS), Corridor Integrated
    Weather System (CIWS), gridded wind analysis prototypes, and wind
    analysis and post-processing research. Atmospheric boundary layer
    sensing from ASOS, AWOS, and TDWR can provide data for transport and
    dispersion, including: winds, direction, speed, turbulence/velocity
    variability, boundary layer characteristics, and stability class.
    Conclusions: FAA operates an extensive network of weather sensors
    that could provide measurements for transport and dispersion
    applications over most major metropolitan areas.

    a.  Doppler radar winds (WSR-88D, TDWR, ASR-9 WSP)

    b.  High temporal resolution surface observations

    c.  Boundary layer depth (WSR-88D and TDWR)

    d.  FAA sensor integration systems are a potential portal to raw
        data and derived weather products

    e.  Integrated Terminal Weather System (ITWS)

    f.  Corridor Integrated Weather System (CIWS)

    g.  Gridded wind analysis systems are now being developed and run in
        real-time

    h.  Temporal filtering techniques show considerable promise

    i.  Identification and tracking of atmospheric phenomena in gridded
        wind analyses

    j.  Opens the door to short-term, extrapolation-based forecasts

7.  **Presentation: USGS National Atmospheric Deposition Program**, Mr.
    Mark Nilles, DOI/USGS

    a.  National Atmospheric Deposition Program (NADP) Networks provide
        long-term multi-decade monitoring, multi-tiered support
        (Federal, state, private, academic & tribal), sites are
        typically regionally representative, identical sampling
        equipment and methods are used within each network, single
        analytical laboratory, Rigorous field and laboratory QA/QC, and
        open availability of all data via the Internet. NADP includes
        the National Trends Network and Mercury Deposition Network:

        1.  National Trends Network (NTN), begun in 1978, monitors
            acidity, nutrients and base stations at \~250 sites across
            the U.S.

        2.  Mercury Deposition Network (MDN), begun in 1995, the
            monitors for total mercury at nearly100 sites and
            methyl-mercury at about 20 sites in the U.S. and Canada.

    b.  All NADP Networks have the following attributes:

        1.  Long-term multi-decade monitoring

        2.  Multi-tiered support

        3.  Federal, state, private, academic & tribal

        4.  Sites are typically regionally representative

        5.  Identical sampling equipment and methods are used within
            each network

        6.  Single analytical laboratory

        7.  Rigorous field and laboratory QA/QC

        8.  Open availability of all data via the Internet

    c.  On-line Resources are:

        1.  <http://nadp.sws.uiuc.edu/> Weekly, monthly, seasonal and
            annual averages for U.S. wet deposition and U.S. maps of
            deposition patterns

        2.  <http://water.usgs.gov/ntn> On-line reports for trends and
            environmental effects research

        3.  <http://www.epa.gov/castnet/> Data for a 70 site wet + dry
            deposition network

8.  **Presentation: Collaborative Adaptive Sensing of the Atmosphere
    (CASA) Update: program status and plans.** Dr. David J. McLaughlin,
    Professor and Director NSF Engineering Research Center for
    Collaborative Adaptive Sensing of the Atmosphere (CASA), Department
    of Electrical and Computer Engineering, University of Massachusetts.

    a.  In September 2003, the National Science Foundation established
        the Engineering Research Center for Collaborative Adaptive
        Sensing of the Atmosphere (CASA). It is a collaborative effort
        of 19 separate organizations.

    b.  CASA\'s vision is to revolutionize the ability to observe,
        understand, and predict weather hazards by creating Distributed
        Collaborative Adaptive Sensing (DCAS) networks that sample the
        atmosphere where and when end user needs are greatest. This \$40
        million Center brings together a multidisciplinary group of
        engineers, computer scientists, meteorologists, sociologists,
        graduate and undergraduate students, and industry and government
        representatives to conduct fundamental research, develop
        enabling technology, and deploy prototype engineering systems
        based on a new paradigm (i.e., DCAS networks).

    c.  DCAS weather-sensing networks could save lives and property by
        detecting the region of the lower atmosphere currently below
        conventional radar range - mapping storms, winds, rain,
        temperature, humidity, airborne hazards, and other thermodynamic
        conditions. The radars will communicate with one another and
        adjust their sensing strategies in direct response to the
        evolving weather and changing user needs - a dramatic change
        from current technology. A new generation of meteorological
        software will use this radar data to support organizations that
        need weather data for decision making: government, emergency
        managers, and private industry.

    d.  CASA seeks to advance fundamental knowledge - of the
        troposphere, of application driven, cross-layer, resource
        allocation, and of electromagnetic wave-atmosphere interaction
        for networked remote sensing - and to apply this knowledge in
        concert with academic, industrial, and end user partners, to
        both advance the enabling technology base and to create
        field-scale DCAS system-level test beds. Through these test
        beds, CASA aims to understand and demonstrate the potential of
        the DCAS paradigm to benefit society by saving lives and
        property through improved understanding, detection, prediction,
        and warning of atmospheric events.

9.  **Panel Session:** Role of Multi-sector Partnerships in Test Beds.
    **Moderator**: Dr. Walter Bach, Cochair.

    a.  Ms. Maria A. Pirone, Vice President, Commercial Division,
        Atmospheric and Environmental Research (AER), Inc. Ms. Pirone
        listed some successful test beds: the Joint Hurricane Test Bed
        (JHT) and New England High Resolution Temperature (NEHRT) Test
        Bed. The lessons learned are: close association with users of
        the information speeds up the transfer of research to operations
        and partnering with academia (JHT), and industry proved
        beneficial (NEHRT). Everyone will have a role in the systems
        engineering required to develop an urban test bed. A broad
        spectrum of needs, sensors, and algorithms requires a systems
        engineering approach. Systems engineering tasks include:
        defining user needs, systematic selection and location of
        sensors, near real-time data collection, assessment and
        dissemination via an integrated network, and documentation for
        usability of data among existing and new partners. The efficient
        cycling of ideas and strategies using simulation toolkit will be
        critical. A simulation toolkit would provide an efficient,
        high-fidelity, GIS-based software tool that defines the location
        and types of sensors for live test bed. Test bed results provide
        information to validate the tool. The tool then provides
        uncertainty bounds for a broad range of scenarios.

    b.  Dr. David Bacon, Director, Center for Atmospheric Physics,
        Science Applications International Corporation (SAIC). Cities
        have a major effect (locally) on the atmospheric circulation. In
        addition to the mechanical effect for mixing of the boundary
        layer (urban canyon), there is also a thermal effect (building
        morphology and sun angle). There are multiple users involved.
        For emergency response, the decision maker needs to know the
        impact on the population, and the modeler needs the wind
        direction and speed where the people are.

        1.  There are a number of challenges that must be faced to
            successfully simulate urban dispersion, including: what and
            where to measure, remote sensing, surface and atmospheric
            properties, quality control (QC), analysis schemes (need to
            convert bits into information into knowledge and need tools
            to provide binary, graphic, and text output), and data
            transfer

        2.  Micrometeorology -- especially for hazardous dispersion -
            involves many intertwined factors including data collection,
            data assimilation, modeling, and data dissemination. Cannot
            measure everywhere -- so we need to know how to analyze what
            we do measure properly.

        3.  Requirements for urban simulations include:

            a.  Information on the larger scale wind field

            b.  Data is not sufficient as all data is not equivalent

            c.  Wind observation far upwind of a city may be accurate

            d.  Wind observation upwind, but close to the city, may
                reflect the effect of the city bow wave

            e.  Wind observations within / above the city canopy are
                contaminated by the presence of the buildings

            f.  Wind observations downwind of, but close to, the city
                may reflect the entrainment zone

            g.  Wind observations far downwind of the city may be
                accurate

            h.  ***Metadata is essential for unfolding the data.***

        4.  An Urban Data Assimilation System is required. Data
            assimilation is the process of fusing known isolated data
            points into a physically consistent representation of the
            three-dimensional state of the atmosphere. Consistency
            requires recognition of the strong forcing of the boundary
            conditions -- a difficult problem in a complex urban
            setting. Traditional data assimilation systems are not
            geared to ensuring physical consistency in complex
            geometries. The collection and use of metadata are critical
            to urban test beds.

        5.  Urban circulations are highly constrained by the geometry --
            but -- urban circulations are highly dependent on the
            initial / boundary conditions. The result is that the
            circulation tends to jump from one well-characterized flow
            solution to another with sharp discontinuities. Variability
            and uncertainty in an urban setting are greater -- and
            lesser -- than the extra-urban world. Building geometry
            constraints are a help. Increased turbulence and
            anthropogenic activity is a hindrance. We need to understand
            the scope of the solution space. To understand the impacts,
            we need to specify the problem.

        6.  Dr. Bacon concluded by stating that dispersion depends on
            the details and in an urban environment, the details can
            mount quickly, and time is of the essence. We need to
            understand the type of problem that is being addressed if we
            want to have a hope of understanding the important factors
            in dispersion in urban environments. A new class of data
            assimilation system -- including enhanced accumulation of
            metadata -- is necessary to support urban simulation

    c.  Mr. Jay Titlow, Senior Meteorologist, WeatherFlow Inc described
        the WeatherFlow products and business model. WeatherFlow is
        providing valued information: augmenting "incomplete" data
        collection, understanding of meteorological processes, and
        increasing accuracy and verifying forecasts. It is producing
        products that address the end-user's needs: delivering quality
        reliably, translating information into end user's language, and
        delivering information in a timely manner. Building a
        cost-effective and sustainable system by constructing via
        practical requirements, not theoretical, sharing costs among
        users, and exploiting existing infrastructure. WeatherFlow
        commercial web sites combined memberships approaching 100,000
        users.

10. **Panel Session: Research and Operational Needs.** Moderator: Mr.
    Jeff McQueen, NOAA NWS NCEP.

    a.  **Air Quality Needs** -- Dr. Paula Davidson, NOAA NWS OS&T. Dr.
        Davidson provided an overview of the NOAA NWS current air
        quality forecasting capability and described both near-term and
        longer-term improvements.

        1.  The initial operational capability (IOC) provided a 1-day
            forecast guidance for ozone and was deployed in the
            Northeastern U.S. in September 2004. That deployment was
            expanded to cover the Eastern U.S. (east of the Rockies) in
            August 2005. Near-term plans include converting the
            meteorological model input from Eta to WRF in the Spring of
            2006 and conducting an experiment to test the ozone guidance
            product over the continental U.S. during the Summer of 2006
            with plans to deploy it nationwide (AK and HI) by 2009.
            Longer range (within 10 years) improvements that are planned
            incude the following:

            a.  Develop and implement capability to forecast particulate
                matter (PM)

            b.  Particulate size \< 2.5 microns

            c.  Data assimilation for air quality

            d.  Extend air quality forecast range to 48-72 hours

            e.  Include broader range of significant pollutants

        2.  Model Components include: a linked numerical prediction
            system (the NWS mesoscale NWP model, Eta-12 and the NOAA/EPA
            community model for AQ, CMAQ is operationally integrated on
            NCEP's supercomputer), observational data input, and the EPA
            emissions inventory. Model outputs include gridded forecast
            guidance products that are delivered to NWS
            Telecommunications Gateway and EPA for users to pull twice
            daily. Forecasts are verified with data from EPA
            ground-level observations and ozone observations.

        3.  Dr. Davidson described the AQ Focus Group that is comprised
            of State and local air quality forecasters. State and local
            air quality forecasters provide AQ forecasts for ozone at
            about 300 cities and AQ forecasts for ozone and PM at about
            100 cities. Members of the AQ Focus Group compile forecasts,
            send monitoring data to EPA's AIRNow site, and provide
            feedback on developmental real-time NOAA-EPA predictions.

        4.  Key Challenges for AQ Prediction include:

            a.  Better use of weather information in AQ predictions,
                including exploration of "on-line" predictions; and

            b.  Quantitative predictions for particulates, including:

                i.  Large episodic source inputs

                ii. Extended chemical mechanisms: rigor with speed

                iii. Real-time atm chemical data ingest; boundary
                     conditions

                iv. Improved integration with weather prediction

                v.  Building to quantitative accuracy: Diagnosing,
                    correcting inadequacies in emissions estimates,
                    reactive transport simulations

            c.  Improvements to urban-scale observations and AQ
                prediction include:

                i.  Emissions characterization:

                    1.  improves both inventories (inputs) and basis for
                        diagnostic evaluations of AQ predictions
                        (outputs)

                    2.  Very limited: speciated data, time-resolved,
                        over long periods of time; urban-scale spatial
                        variability

                    3.  Vertically resolved data generally lacking

                ii. Weather observations:

                    1.  Information that improves mesoscale weather
                        forecasts that drive AQ prediction will improve
                        AQ predictions

                    2.  Available weather datasets much richer than
                        those for emissions!

> b **The Oklahoma City Urban Micronet Project**: Transitioning From
> Vision to Reality\-- Dr. Ken Crawford, NOAA NWS OS&T. Dr. Crawford
> described the history of the Oklahoma Mesonet (1994) which is a
> statewide, mainly rural network. The successes of the Oklahoma Mesonet
> set the stage for the largest urban-scale field campaign ever
> conducted, the Joint Urban 2003 (JU-2003) conducted in Oklahoma City,
> OK. JU-2003 led to OK funding for new sensors for the Oklahoma City
> Urban Micronet.
>
> i\. The Oklahoma City Urban Micronet is a focused urban atmospheric
> monitoring project building on the Oklahoma Mesonet and JU-2003. Dr.
> Crawford described the concept of a Science, Applications, and
> Outreach (SAO) Network:

1.  Science - Specific, focused research projects developed around
    dense, research-quality observations.

2.  Application - Applying the data collected to meet the needs of a
    broad range of users.

3.  Outreach - Focused outreach to urban K-12 students, First
    Responders, etc.

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i.  Scientific Objectives are to quantify the urban heat island for OKC,
    develop new dispersion tools and technologies (e.g., simulated
    plumes, etc.), determine impact of severe weather on OKC, and sssess
    the relationship between urban atmospheric processes and public
    health.

ii. Potential applications include: improved road weather information
    for OKC, real-time diagnosis of potential flood risk areas during
    heavy precipitation events, products geared to first responders
    (dispersion maps, etc.), and improved urban forecasts (e.g., heat
    advisories).

iii. The project recently received \$250K from the State of Oklahoma for
     hardware to deploy the Urban Micronet (instruments, nuts and bolts,
     etc.) and the initial sensors and equipment have been purchased and
     tested. The use of power where needed and use of the OKC wireless
     network (utilized by the police, fire, and public works
     departments) has been arranged. The first Mesonet site has been
     chosen to be installed at OSU-OKC pending some final arrangements.
     The project team still needs to identify about 4 additional Mesonet
     site locations. No rooftop sites have been identified or chosen.
     The first site commenced operations in March 2006 and the network
     is expected to be fully operational by 1 January 2007. The
     innovations of this project include: low cost, low impact, research
     quality data; extensive coverage; 1 minute data; use of high
     bandwidth WiFi; irregular, and spider-web spaced sites on the scale
     of the atmospheric processes. Dr. Crawford recognized the
     willingness of Oklahoma City government to support this project.
     Their support and the efforts of the project team have made the
     Oklahoma City Urban Micronet a model for replication in other
     cities. Dr. Crawford welcomed the members of the JAG/JUTB to
     provide any ideas or inputs to the project team.

> c\. **Urban Modeling Needs** \-- Dr. Robert Bornstein, San Jose State
> University. Dr. Bornstein provided a summary of progress made in
> mesoscale modeling in the past 3 decades and described the challenges
> that the modeling community faces.
>
> i\. Dr. Bornstein described the problems with existing surface cover
> and land use data bases. Other problem areas in urban mesoscale
> meteorological models include the following:

1.  PBL vs. canopy vs. canyon scales

2.  Roughness sub-layer \[u\*(z)\] vs. SBL u\* = const

3.  building-height variation (where is the lower boundary?)

4.  inhomogeneous sfc type (thermal, rad, & roughness param are f(x,y))

5.  aerosols à rad flux div à

6.  need interactive met and air-quality models à

7.  elevated urban-inversions & actinic flux (caused by photochemical
    reactions)

> ii\. Dr. Bornstein recommended the following modeling capability
> improvements:
>
> \(1\) Meso-met grid model min-spacing

-   Horizontal grid: about 0.5 km

-   Vertical urban-canopy layer grid: about 7-m

> \(2\) Meso-met model-urbanization for WRF model

-   Satellite-derived land use and surface data

-   Urban (SURFACE, SBL, and PBL) parameterizations

> \(3\) Two-way links of meso-met models with other models:

-   CFD urban-canopy

```{=html}
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-   Ozone

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```
-   Cloud/thunderstorm

    -   Hydrology

    ```{=html}
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    -   Thermal stress

> \(4\) One-way links with regional climate-change models
>
> \(5\) Urban test beds + field studies
>
> \(6\) Open urban (morphology + met) data-bases

11. **New Action Items**

**ACTION ITEM 2006-2.1:** All meeting participants and everyone on the
JAG/JUTB membership roster (attached) are invited to provide an input to
the Executive Secretary by March 31, as follows: Please provide a brief
summary of your personal perspective on each of the following seven
topics that are to be addressed within the Operational Concept for the
JUTB (the reference is the JAG/JUTB Terms of Reference which was
distributed by previous correspondence).

1\. Users\' needs

2\. Capability gaps

3\. Existing infrastructure that could be used

4\. Desired infrastructure capabilities

5\. Roles and responsibilities and a recommended management structure

6\. Criteria for optimal test bed site selection

7\. Anticipated benefits to public health, the security of the Nation's
critical infrastructure, and the economy that will be realized through
operation of the joint urban test beds

The Cochairs will review the inputs and will use the information to
prepare for the next meeting.

**Date for the Next Meeting:** The tentative date for the next meeting
is Tuesday and Wednesday, May 9-10, 2006, at the OFCM Office. This
meeting will be for JAG/JUTB Members, Alternates, and Technical
Advisors.

[^1]: The Federal Geographic Data Committee (FGDC) is an interagency
    committee that promotes the coordinated development, use, sharing,
    and dissemination of geospatial data on a national basis. This
    nationwide data publishing effort is known as the [National Spatial
    Data Infrastructure](http://www.fgdc.gov/nsdi/nsdi.html) (NSDI). The
    NSDI is a physical, organizational, and virtual network designed to
    enable the development and sharing of this nation\'s digital
    geographic information resources. FGDC activities are administered
    through the FGDC Secretariat, hosted by the [National Geospatial
    Programs Office](http://www.usgs.gov/ngpo) (NGPO) of the U.S.
    Geological Survey. The NGPO oversees other geospatial programs of
    national importance including The National Map and the Geospatial
    One-Stop activity.