NYC Urban Atmospheric Observatory UAO:

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NYC Urban Atmospheric Observatory (UAO) Overview
and Current Projects
Presented to the 2004 Annual Meeting of Technical
Panel 9 (TP9) of The Technical Cooperation
Program (TTCP) Chemical, Biological and
Radiological Defense (CBD) Group 9 Feb 2004
R. Michael Reynolds Brookhaven National
Laboratory, Upton, NY 11973 Bob Bornstein Dept
of Meteorology, SJSU pblmodel_at_hotmail
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URBAN ATMOSPHERIC OBSERVATORY (UAO) RESPONSE TO A
NATIONAL NEED
UAO INTERAGENCY INITIATIVE MISSION
STATEMENT gt Create permanent, real-time, NYC
facility to support research in urban
atmospheric sciences gt Provide testbed for
development and validation of technologies for
emergency management and anti-terrorism with
real-time information. STRONG SCIENTIFIC AND
TECHNICAL INPUT REAL-TIME PERMANENT
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BALANCE BETWEEN EMERGENCY MANAGEMENT AND SCIENCE
Real-time component is essential Data
Assimilation is essential to program.
SCIENCE URBAN METEOROLOGY SYNOPTIC
INTERACTIONS FRONTS SEABREEZES CONVECTION TURBULEN
CE DIURNAL STABILITY STREAMING FLOW BOUNDARY
LAYER HEAT ISLAND BUILDING VORTEX CANYON
CIRCULATION INTERSECTION EXCHANGE TRANSPORT DISPER
SION DATA ASSIMILATION SUBWAY DISPERSAL BUILDING
INTERIOR CIRC.
PREPAREDNESS EVACUATION LETHAL DOSE SUBWAY
EXCHANGE SUBWAY DISPERSAL BUILDING
EVACUATION CBNR TERRORIST FIRST RESPONDERS EVENT
PLANNING HEAT STRESS CLIMATE CHANGE PUBLIC
HEALTH CHRONIC POLLUTION
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UAO COLLABORATIVE EFFORT
PARTNERSHIP DOE - BROOKHAVEN NATIONAL LABORATORY
(R. MICHAEL REYNOLDS) NOAA AIR RESOURCES
LABORATORY (BRUCE HICKS) NYC - OFFICE OF
EMERGENCY MANAGEMENT (EDDIE GABRIEL, KEVIN
CLARK) DHS ENVIRONMENTAL MEASUREMENTS
LABORATORY ( HSI-NA LEE) DTRA DEFENSE THREAT
REDUCTION AGENCY (RICK FRY)
SCIENCE TEAM ROBERT BORNSTEIN - San Jose State
Univ. (Chief Scientist) STEVE HANNA Harvard
School of Public Health ALAN HUBER -
NOAA/EPA MIKE BROWN Los Alamos National Lab
COLLABORATORS LABS NCAR LLNL LANL BOTH
NASA /GODDARDs USArmy EPA/RTP ANL
ORNL BATTELLE DCNET FAA LBNL COMPANIES
IBM VAISALA WEATHER2000 STETSON
BAXTER UNIVERSITIES CUNY COLUMBIA RUTGERS
MIT/LL SUNY/SB UofO UofU
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UAO ORGANIZATION
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UAO PARADIGM
REGIONAL MESONET CENTRAL TESTBED
INTENSIVE STUDIES Continuous facility
Permanent communications backbone Integrated
into NYC Office of Emergency Management (OEM)
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GIS-REMOTE SENSING DATA

• NYC DATA
• BUILDING HEIGHT
• LAND USE
• VEGETATION
• URBAN HEAT ISLAND
• SURFACE PARAMETERS

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MESOSCALE ROOFTOP AND PBL

• ROOFTOP MESOMET NET
• PBL RADARS, LIDARS, SODARS,
• 4DDA SYSTEMS (NCAR, FAA,)
• URBANIZED MESOMET MODELS
• MM5
• RAMS

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MESOSCALE NETWORK URBAN MODELING DATA
ASSIMILATION
The Challenge Assimilate existing and new
observations into a predictive urban mesoscale
model and provide high-resolution (100 m),
one-hour forecasts over the urban region.
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REMOTE SENSING FOR HIGH-RESOLUTION MESONET
ASSIMILATION
Lidar and/or radar hold the promise of providing
needed resolution to define the wind predictions
over the city. The CCNY location is perfect for
covering all of Manhattan below approx. 130th
Street.
Doppler-Lidar The doppler-Lidar is an off the
shelf, turn-key system. It has a volumn scan
operation mode. 1-min per horizontal sweep x 5
elevations gt 5-min volumn update. Wind radials
at 60 m resolution. Range depends on aerosol
content but in NYC we should see 12-15 Km range.
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MESOSCALE URBAN PBL MODELS

• URBANIZED
• PROVIDE
• ROOFTOP FLOWS WITH URBAN INFLUENCES
• ROOFTOP DISPERSION
• UPPER BC FOR MICROSCALE MODELS

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From Masson (2000)
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WTC Plume Dispersion Modeling Employing the
Mesoscale Prognostic RAMS/HYPACT Platform, 3-D
Animation(Georgopoulos et al., 2003)
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MICROSCALE STREET-CANYON OBSERVATIONAL STUDIES

• LONG TERM MET AND TURBULENCE
• REAL TIME
• DATA ARCHIVE
• SITES EML, MSG
• INTENSIVE TRACER RELEASES
• OUTDOOR-INDOOR, SUBWAY
• HEALTH IMPACTS

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THE DHS/EML AND KING STREET CANYON PILOT STUDY
Long data set NOAA Rooftop 3/2003
permanent BNL 1 Rooftop, 2 Canyon Stations
4/2003 to 2/2004 EPA/BNL SODAR 7/2003 -
3/2004 Support data SUNYSB MM5, daily
run, 4 km resolution GIS data bases AWS,
ASOS, NCEP products
h/w6, h55m, gap for south winds, typical
highly varigated
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PROPOSED HARDWARE FOR UAOCOMS-2004
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UAOCOMS-2004 A Design for 2004 Activities
Wireless LAN (Wi-Fi) in canyons to access
point, line of sight. Access Point collects
all data, science and real-time, stores data
locally. Central Access Point in a tall
building (e.g. Empire State Building) collects
data from distributed access points. UHF radio
link to BNL. RT data are transmitted to the BNL
90-m tower by direct, error-free, encrypted, UHF
link. Satellite uplink at each access point
allows removes single point of failure. This
link will automatically begin when the RF
connection fails. Science data collection will
not be in real time, but will be timely. We will
use internet where possible, but can also use a
mobile Wi-Fi van or we can manually burn DVDs.
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MESOSCALE NETWORK URBAN MODELING DATA
ASSIMILATION
The Challenge Assimilate existing and new
observations into a predictive urban mesoscale
model and provide high-resolution (100 m),
one-hour forecasts over the urban region.
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EMERGENCY RESPONSEINFO REQUIRED (IN 20-30 MIN)

• WHAT IT IS
• WHAT IS ITS CONCENTRATION
• WHERE IS ITS SOURCE
• WHERE WILL IT GO
• WHAT ARE ITS FUTURE CONCENTRATION PATTERNS

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REAL-TIME FORECASTS REQUIRE

• FAST CPU
• GOOD LARGE-SCALE WX-MODEL RESULTS
• GOOD URBAN-CANYON MODULES IN MESO-MODELS
• GOOD MESOSCALE (SFC UPPER AIR) OBS NETWORKS
• REAL-TIME COMMUNICATIONS
• SIMPLE MODELS FOR EMERGENCY RESPONCE

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NEIGHBORHOOD-SCALE RESEARCH MODELS

• TYPES
• EPA WIND TUNNEL
• NOAA CFD (FLUENT)
• INDOOR-OUTDOOR EXCHANGE
• USES
• SCIENTIFIC UNDERSTANDING
• DEVELOP PARAMETERIZATIONS FOR RAPID RESPONSE
  MODELS

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RAPID ER MODELS

• NARAC ROOFTOP
• HPAC-URBAN
• DCNET
• QUIC

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QUIC Simulation WD 215
wind vectors at 5 m height
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What is QUIC?
Bio Agent transport through downtown Salt Lake
City
Isosurface
release location
Downtown SLC simulation, SE inflow
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SUMMARY

• UAO follows series of US and international
  dispersion studies (OKC, DAPPLE, SLC, etc.) and
  extends them to deep urban canyons.
• UAO is unique as it combines science and model
  development with long-term real-time support of
  NYC emergency management.
• UAO will encompass observations, real-time data
  collection, data assimilation, and model
  development on different scales.
• The DHS/EML pilot study has shown feasibility of
  long-term urban canyon turbulence measurements,
  rooftop SODAR, and wireless technologies.
• The 2004 Madison Square Garden intensive study
  begins series of focused studies with specific
  research goals. This case focuses on observed
  rapid vertical dispersion in vicinity of singular
  tall buildings.
• Development of rapid-response models with
  high-resolution data ingest and reliable
  statistically relevant concentration and dosage
  estimates is the long-term UAO goal.

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