operational urban mesonet-driven model for homeland defense applications situational awareness for...
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Operational Urban Mesonet-Driven Model for Homeland Defense Applications
Situational Awareness for Emergency Services ...
“Accurate environmental information is critical to operational success”
Mark C. Beaubien, Sr. Engineer
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The Problem
• Weather conditions affect plume dispersion
• Metropolitan scale met prediction capability limited both in training and real time data
• Real time data not in a usable format for command and control purposes (METAR)
• Legacy weather systems inadequate for real time decision making (e.g. evacuation)
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Current Situation: Insufficient granularity of measurements
2D Satellite Data feeds 3D Numerical Weather Models“sparse matrix problem, poorly bounded”
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Multi-Sensor Real Time Profiling of the Battlespace Atmosphere
GPS radiosonde•upper air winds•PTU•1000-100,000’
Total Sky Imager•cloud motion•% cloud cover •visibility•500-5000’
Wind Lidar •surface winds•outside wake•0-1000’
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Weather Web Core Sensor Technology
Joint Battlespace Infosphere “Sensor Cloud”
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YESDAQ
Fixed-Base Network of Multiple Sensor Types
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Weather Web Network Data Architecture
Application-Specific Sensors Deployed in the field
ACQUIRE
Remote Database Stores in the Field Provide Redundancy
STORE
Data Links to Numerical Weather Prediction and other Downstream Command and
Decision ApplicationsDECIDE AND ACT
Centralized Replicated Database at Command Center
COMMUNICATE
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Logistics for Metropolitan Scale Networks
Who are the data stakeholders?
Who owns the site real estate?
Who owns the equipment?
Who maintains the equipment?
Who physically controls the sites?
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Planning the Network
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Weather Web Test Bed - 2000
Mt Greylock3491 ft
S1
S2
High School925 ft
S2
Taconic SP1540 ft
S2
Mt Ramier2560 ft
S2Landfill610 ft
S2
Clarksburg SF2283 ft
Hariman-WestAirport653 ft
S1
S2
Notch Road1870 ft
Adams
North Adams
Williamstown
SouthWilliamstown
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Met Sensor Node - 2001
YES TSI-880
Sonic Anemometer
YES MET-2010DCsupply
(Present weather,sky, precip, visibility)
(PTH)
(Surface winds)
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Sensor Node 2004
CPUEEPROM A/D Converter
FM FSK transmitter
RF Amplifier
Xmit RF Antenna
Wind speeddirectionSensor
Pressure,Temperature, %Humidity,Sensors
GPS Engine(time/position)
GPS Satellites
1.5 GHz GPS recv Antenna
Optional RAD-7001 Nuclear Radiation Detector
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TMS-7200
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Real Time Display
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Total Sky Imager
Animated Panoramic Horizon View
Animation Controls
Raw Image View
National Weather ServiceNational Weather ServiceAlbany, NYAlbany, NY
Model TSI-880 imager
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Inferring winds from cloud motion
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ASRC “REAL TIME” MOHAWK
0:00
0:01
0:02
0:03
1 mile separation
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ASRC “TIME SHIFT -3 min” MOHAWK
0:00
0:01
0:02
0:03
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In-situ Upper Air GPS Radiosonde
MERV ARL “FORCE PROTECTION”
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Optical Fiber Wind Lidar
Lidar: Light Detection and Ranging– Same as Radar only done at Light frequencies
– Light Source is typically a monochromatic Laser
– When Sensing Environmental Parameters: LIDAR
– When Sensing or Imaging “Hard Targets”: LADAR(Laser Detection and Ranging)
Laser Light Source
EnvironmentalElement (Smoke, Cloud, etc.)
"Hard Target"
Scattered/Reflected Light
Optics(Telescope)
OpticalDetector
ElectronicAmplification
Data Reduction and Display
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Soft Target Tracking: Vector-Resolved Winds
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1 4 7
10 13
16
19
22
25S
1 S5 S
9 S13 S
17 S21 S
25 S29 S
33-0.01
-0.005
0
0.005
0.01
0.015
0.02
0.025
0.03
Time, minutes
Signal Intensity
Time Evolution of Small Agricultural Fire3/26/02
0.025-0.03
0.02-0.025
0.015-0.02
0.01-0.015
0.005-0.01
0-0.005
-0.005-0
-0.01--0.005
Range, ft
1800ft
2400ft
Fire Center at a range of 2160ft
Hard Target Tracking: of Smoke Plumes
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Lidar Data: Hard and Soft Target Data Examples
Target Returns, Diode/EDFA MOPA120ns Nominal Pulse Width, 7.5KHz PRF
Peak Pulse Power 5 - 10 W
Range, relative units
Sign
al A
mpl
itud
e, r
elat
ive
unit
s
100m Deep Cloud Layer Centered at 150m150m
1.8km2.04km
Light Pole behind Bush
House thru Tree Screen2.1km
Power Wire over Hillside Grass306m
486m
Double Pulse WaveformTwo Tree Lines
2.1km1.2km
Tree Covered Mountain Top 4.32km
Smoke Column fromAgricultural Fire
585m 830m
Aluminum Calibration Target873m
Field Treeline
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Lidar Data: Tracking Precipitation and Hydrosols
Snow Velocity TrackFalling Snow 0.25in/hr, Vertical Axis, 14 ft Range, 10mw
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
0 50 100 150 200 250 300
Time, s
Fa
ll V
elo
cit
y, m
/s
Frozen Precipitation Velocity Spectra, Time History - 2/14/03, Corrected to Vertical
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0.045
0.05
0.055
0 1 2 3 4 5 6 7 8
Velocity, m/s
Rel
ativ
e S
pec
tral
Inte
nsi
ty, v
olt
s
Snowflake, 02:36:35.20PMSnow Column, 02:45:50.38PMMixed Fog-Frozen Precipitation, 03:00:45.29PMMixed Fog-Frozen Precipitation, 03:00:48.29PMMixed Frozen Precipitation, 03:10:52.09PM
1.5-2mm Snow Flakes, <1in/hr
Fine Snow/Sleet
Fog/Frozen Fog
Raindrop Spectra 1mw laser, 14ft Range, Rain Rate < 0.25in/hr (light and variable)
-0.005
-0.003
-0.001
0.001
0.003
0.005
0.007
0.009
0.011
0.013
0.00E+00 1.00E+00 2.00E+00 3.00E+00 4.00E+00 5.00E+00 6.00E+00 7.00E+00 8.00E+00Velocity, m/s
Inte
ns
ity, re
lati
ve
sc
ale
10:43:26.10AM11:04:07.79AM11:04:08.34AM11:05:25.17AM11:10:11.26AM11:12:01.50AM
Spectral Signature Extraction & Distribution Analysis
Fog/Drizzle/Rain Snow/Sleet
Vertical Velocity - Mixed Drizzle/Fog
0
0.5
1
1.5
2
2.5
3
3.5
0 50 100 150 200 250
Time, s
Velo
city
, m/s
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RF link advantages vs. telco
• Rapid setup
• No long term recurring costs
• Reliability
• Flexibility if stations must move
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Summary
•Yankee develops and produces precision
meteorological instrumentation and systems
•Weather Web - A rapidly deployable network of
expendable meteorological sensors
•Weather Web Test Successful in Boston @DNC
•TMS Met sensor linked with HPAC
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Single Point Access to Environmental Data