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DEVELOPMENT OF A REMOTE-SENSING TESTBEDFOR TROPOSPHERIC AIR QUALITY AND WINDS
Working Group on Space-Based Lidar Winds
Key West, Florida, January 17-20, 2006
University of Alabama in HuntsvilleMike Newchurch, David Bowdle, John Mecikalski,
Walt Petersen, Kevin Knupp, Dick McNider
Simpson Weather AssociatesDave Emmitt
NOAA Earth Systems Research LaboratoryMike Hardesty
NASA Marshall Space Flight CenterSteve Johnson
Huntsville/Madison Urban Corridorand Redstone ArsenalIn Northern Alabama
*Walter D. Bach Jr., Program Manager, Environmental Sciences Division, U.S. Army Research Office
CoChair: OFCM Joint Action Group for Atmospheric Transport and Diffusion Modeling (Research and Development Plan)
Modeling Challenge #1:Multiple Coupled Scales*
Adapted from:
Modeling Challenge #2: Multiple Coupled Nonlinear Processes
PBL dynamics
gas chemistry thermodynamics
aerosol processes
MICROSCALElower troposphere
MESOSCALEfull troposphere
METEOROLOGY(MM5 with 4DDA)
sfc energy balance
radiation
PBL and cloud dynamics
thermodynamics
AIR QUALITY(Models-3/CMAQ)
trace gasemission transportchemistry
aerosol processes cloud processes
initial conditions & boundary conditions
LARGE EDDYSIMULATION
(LES)
SATELLITEDATA
ASSIMILATION
with
clouds J*
clouds sfc
merge
IC BC
CLOUD dynamics
microphysics thermodynamics
chemistry
operational models
needed
Lightn
ing
Strat/T
rop
PBL/Fre
e Tro
p
Modeling Challenge #3:Multiple Applications and Stakeholders
For example,
• air quality model validation
• air pollution assessments and forecasts
• source attribution; regulatory/economic impact
• ground-truth for satellite-based sensors
• urban- to regional-scale climate modeling
• regional- to global-scale climate modeling
• tactical-scale tracer models for national security
INADEQUATE WIND DATA
and
complex terrain with diverse land usage
Modeling Challenge #4:
www.ofcm.gov/r23/r23-2004/fcm-r23.htm
Federal Air Quality Modeling Needs
Establish ATD Test beds
Participating Federal agencies establisha multi-agency testbed authority
to oversee the development and operationof multiple test beds for urban and complex-
environments,in locations selected for national and/or R&D priorities
Documentation
Implementation Recommendation #2
Implementation Recommendation #6
Bridge the Scale Gap
Address difficulties in interfacing models at different scales
Keystone Recommendations Interpret uncertainty
ATD modeling systems should routinely quantifythe uncertainties in their results
Quantify uncertainty
ATD modeling R&D community work with representative users
to determine effective meansto quantify and communicate uncertainties.
INFORMATION CONTENTIntelligent assimilation of multi-scale multi-variate atmospheric data• improved atmospheric modeling on ~20-meter to ~20 kilometer scales• improved atmospheric measurements for point and standoff detection• improved understanding and quantification of atmospheric uncertainties
INFORMATION APPLICATIONIntelligent transformation of complex atmospheric data into usableinformation for civil and military decision-makers on tactical time scales• improved sensor webs to capture critical information and initiate responses• improved information display formats, including uncertainties & implications
INFORMATION EFFECTIVENESSIntelligent expansion of atmospheric information management systems• Flexible, responsive, scalable, transferable, evolvable – and marketable• Requires open architecture with national standards
*Walter D. Bach Jr., Program Manager, Environmental Sciences Division, U.S. Army Research OfficeCoChair: OFCM Joint Action Group for Atmospheric Transport and Diffusion Modeling (Research and Development Plan)
Air Quality Information Needs
Expanded from:
OUTER NEST• NWS WSR-88D radar: Columbus, MS; Nashville, TN; Birmingham, AL; Hytop, AL (~75 km NE
of Huntsville);• C-band dual-polarization Doppler radar: (ARMOR, at Huntsville airport)• Real-time satellite downlink (GOES & MODIS); Land-surface characterization from satellites;• Remote sensing-based land-surface flux modeling, disaggregating to <100 m resolutions;• Surface weather instrumentation, real-time satellite data• Lightning Mapping Array• High-resolution Regional Modeling, coupled to LES simulations
INNER NEST• Regional Atmospheric Profiling Center for Discovery (RAPCD): 2.1 micron scanning Doppler
wind lidar, 0.532 micron scanning aerosol lidar, UV DIAL for vertical ozone profiles• Mobile Integrated Profiling System (MIPS): 915 MHz wind profiler, Radio Acoustic Sounding
System (RASS), 2 kHz Doppler sodar (two locations), 0.905 micron ceilometer, 12-channel microwave profiling radiometer (MPR); mobile X-band radar (pending)
Research ApproachEvolving Even as We Speak!
Continuous Long-Term Nested Observations and Modeling:Clear AirConvective InitiationStorms
NSSTC Regional Atmospheric Profiling Center
for DiscoveryRAPCD
Doppler lidar bench
FTIR benchtrop aerosol lidar bench
strat /trop lidar bench
~NORTH
horizontalsky-view
Janu ary 10, 2001each f loorspace square i s 2 f t x 2 f t; each laboratory fl oorspace is 20 ft E to W x 22.5 f t N to S
white c ircles wi th soli d borders show posi tions of l ight chi mneys, accurate to 1/2 i nch, and interior diametersfaded blue blocks around light chimneys show opt ical benches in laboratories below
cherry pi cker boom circle indicates minim um boom length
scanner
FTIR LAB ROOF PLANLIDAR LAB ROOF PLAN
ped estal
on roo f for
5 ft cherry
picker
48”30”
30” 30”
semi-t ransparent green bl ock shows elevatedscanner platform on roof,
15 ft E to W and 26 ft N to S
approx 2 f t c learance on outer walkway
9’
13’
17’
13’ 9”
13’
11’
8’ 3”
13’ 9”
26’
21’ 8”
support pi llar
approx
16 feet center to center
approx
20 feet center to center8 foot
Dopplerlidarscancircle
ped estal
on roo f for
7 ft cherry
picker
ped estal
on roo f for
7 ft cherry
picker
30” 30”
30” 30”
7 footrooflidar
domeon
8 footbase
8’ 3”
Acrobat Document Ozone Lidar
Doppler Lidar Scanner
Lockedat zenith
Grating TopDome Floor
Roof Top
DomeSidewall
RailingHorizontal FTIR
Solar FTIR
Lid Closed
Lid Closed
Lid
Op
en
Lid
Op
en
Dome Floor
Chimney 2
Chimney 4
Chimney 5
Chimney 1
Dome Legs
Dome Shutters
Dome
Chimney 3
1-micron scanning aerosol lidar on loan from Herman and Labow/GSFC
Elevation of roof plan
2.1-micron Doppler wind/aerosol lidar
AOR
Applied Microparticle Optics and Radiometry
MIPS Components
915 MHz profiler
Electric Field Mill
12-channel Microwave Profiling Radiometer
Ceilometer
2 kHz Doppler sodar
Surface instr.Satellite comm.
Not shown: 2 raingages and disdrometer
Afternoon Clear Air/Cumulus: Within 50 km of ARMOR and in the planetary boundary layer (PBL)
ARMOR tracks individual PBL structures (refractive index gradients, biological flyers) and directly measures radial wind.
ARMOR wind measurements can be transformed to Cartesian grid at “modeling gap” resolutions (e.g., 1 km). using combined sensors in STORMnet (e.g., MIPS and KHTX NEXRAD Doppler Radar) to retrieve wide-area u, v wind components
ARMOR Remote Sensing and Hydrometeorology
• Convective Initiation • Cloud Physics• Boundary Layer Forcing
Combined (lightning mapping, wind profiler) high resolution studies of summer thunderstorms and interactions with the convective boundary layer
Example: Short-lived summer convection; can exert an immediate impact on operations: wind, heavy rain, hail, flash flooding and lightning
•Goals:
• Improved hydrometeorological threat detection for decision support
• Process study-based Improvements in predictive capability
Dual-polarimetric radar is better able to characterize the particle types, sizes and shapes in precipitation
Research Radar Scanning Flexibility Will allow for high temporal resolution tracer Studies
Chaff Plume (Tracer)
Clear Air
Browns Ferry Plume
Use diagnosed winds and backscatter for both validation and initialization- in clear air AND precipitating conditions!
Embedded Sensor Networks
10-km
RAPCDDWL, Ozone(fixed site)
Citizens DWL(option 2)
Army DWL(fixed site)
Citizens DWL(option 1)
STORMNET CHARM
Cooperative Huntsville Area Rainfall Measurements
DWL IOP
existing
concepts
POTENTIAL DOPPLER LIDAR COVERAGE(topographic obscuration not shown)
Data Assimilation Process:Multiple Instrument Platforms
GOES
Model Grid Disparate
Data/Observations
H Operatormaps/grids,relates &interpretsdata fromobservationspace tomodel grid
3D-Var4D-VarO/I
FiltersSCM
Methods
Bottom Line:All radar winds are treated as unique data,mapped through the assimilation system
Lidars & Radars
HH
Decision Support Tools
- vendor neutral- extensive
- flexible- adaptable
Heterogeneous sensor network
In-Situ monitors
Bio/Chem/RadDetectorsSurveillance
AirborneSatellite
- sparse- disparate
- mobile/in-situ- extensible
Models and Simulations
- nested- national, regional, urban- adaptable- data assimilation
M. Botts -2004
Sensor Web Enablement
- discovery- access- tasking- alert notification
web services and encodings based on Open
Standards(OGC, ISO, OASIS, IEEE)
Sensor Web Enablement Framework
Current and Prospective Partners
Academia• University of Alabama in Huntsville (lead)
• Arizona State University
• …
Private Industry• Simpson Weather Associates
• …
Federal Agencies and National Laboratories• NASA MSFC/…
• NOAA NESDIS/NSSL/ESRL/NWS/IPO…
• US Army: RSA, BED, WSMR, Dugway, Yuma, …
• Other DOD (Navy: NPS/CIRPAS, Air Force: Hanscom AFB)
• DOE: PNNL/BNL/ORNL
• NCAR, EPA, TVA
• …
Development of a Remote Sensing TestbedFor Tropospheric Air Quality and Winds
Summary
1. Multiple parameters observed by complementary sensors
2. Frequent operation of stationary sensors over extended periods
3. Wide range of weather conditions and airmass types
4. Interaction with end users in a simulated operational setting
5. Infrastructure to accommodate guest investigators
6. Occasional multi-institutional intensive operational periods
7. Funding/participation from multiple agencies and organizations
8. Invite further discussions with interested parties
mike.newchurch@nsstc.uah.edu