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1. DEVELOPMENT OF A REMOTE-SENSING TESTBED FOR TROPOSPHERIC AIR QUALITY AND WINDS University of Alabama in Huntsville Mike Newchurch, David Bowdle, John Mecikalski, Walt Petersen, Kevin Knupp, Dick McNider Simpson Weather Associates Dave Emmitt NOAA Earth Systems Research Laboratory Mike Hardesty NASA Marshall Space Flight Center Steve Johnson pseudo-true color image false-color land use image Working Group on Space-Based Lidar Winds Key West, Florida, January 17-20, 2006 Huntsville/Madison Urban Corridor and Redstone Arsenal In Northern Alabama

2. Modeling Challenge #1: Multiple Coupled Scales* Adapted from: *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)

3. initial conditions & boundary conditions Modeling Challenge #2: Multiple Coupled Nonlinear Processes • operational models • needed MICROSCALE lower troposphere MESOSCALE full troposphere Lightning Strat/Trop PBL/Free Trop with LARGE EDDY SIMULATION (LES) SATELLITE DATA ASSIMILATION • clouds • sfc • clouds • J* • merge PBL • dynamics • gas chemistry • thermodynamics • aerosol processes CLOUD • dynamics • microphysics • thermodynamics • chemistry • METEOROLOGY • (MM5 with 4DDA) • sfc energy balance • radiation • PBL and cloud • dynamics • thermodynamics • AIR QUALITY • (Models-3/CMAQ) • trace gas • emission • transport • chemistry • aerosol processes • cloud processes • IC • BC

4. 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

5. Modeling Challenge #4: INADEQUATE WIND DATA and complex terrain with diverse land usage

6. Federal Air Quality Modeling Needs • Documentation • Keystone Recommendations • Interpret uncertainty • ATD modeling systems should routinely quantify • the uncertainties in their results • Quantify uncertainty • ATD modeling R&D community work with representative users • to determine effective means • to quantify and communicate uncertainties. • Implementation Recommendation #2 • Establish ATD Test beds • Participating Federal agencies establish • a multi-agency testbed authority • to oversee the development and operation • of multiple test beds for urban and complex-environments, • in locations selected for national and/or R&D priorities • Implementation Recommendation #6 • Bridge the Scale Gap • Address difficulties in interfacing models at different scales www.ofcm.gov/r23/r23-2004/fcm-r23.htm

7. Air Quality Information Needs • INFORMATION CONTENT • Intelligent 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 APPLICATION • Intelligent transformation of complex atmospheric data into usable • information 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 EFFECTIVENESS • Intelligent expansion of atmospheric information management systems • Flexible, responsive, scalable, transferable, evolvable – and marketable • Requires open architecture with national standards Expanded from: *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)

8. Research Approach Evolving Even as We Speak! Continuous Long-Term Nested Observations and Modeling: Clear AirConvective InitiationStorms 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)

9. AmOR Dome Shutters Applied Microparticle Optics and Radiometry Locked at zenith Dome Ozone Lidar Doppler Lidar Scanner 2.1-micron Doppler wind/aerosol lidar Chimney 5 Solar FTIR Chimney 4 Dome Floor Horizontal FTIR Chimney 3 Railing Lid Open Lid Open Dome Sidewall Lid Closed Chimney 2 Lid Closed Grating Top Dome Floor Chimney 1 Dome Legs Roof Top NSSTC Regional Atmospheric Profiling Center for DiscoveryRAPCD Elevation of roof plan 1-micron scanning aerosol lidar on loan from Herman and Labow/GSFC

10. Surface instr. MIPS Components Satellite comm. 2 kHz Doppler sodar Ceilometer 915 MHz profiler Electric Field Mill 12-channel Microwave Profiling Radiometer Not shown: 2 raingages and disdrometer

11. 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

12. ARMOR Remote Sensing and Hydrometeorology • Boundary Layer Forcing • Convective Initiation • Cloud Physics 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

13. Research Radar Scanning Flexibility Will allow for high temporal resolution tracer Studies Chaff Plume (Tracer) Browns Ferry Plume Clear Air Use diagnosed winds and backscatter for both validation and initialization- in clear air AND precipitating conditions!

14. RAPCD DWL, Ozone (fixed site) Citizens DWL (option 1) 10-km Citizens DWL (option 2) Army DWL (fixed site) Embedded Sensor Networks CHARM STORMNET existing Cooperative Huntsville Area Rainfall Measurements POTENTIAL DOPPLER LIDAR COVERAGE (topographic obscuration not shown) DWL IOP concepts

15. GOES Data Assimilation Process:Multiple Instrument Platforms Methods H Operator maps/grids, relates & interprets Lidars & Radars 3D-Var 4D-Var O/I Filters SCM data from observation space to model grid H Disparate Data/Observations Model Grid Bottom Line: All radar winds are treated as unique data, mapped through the assimilation system

16. Heterogeneous sensor network Airborne Satellite Decision Support Tools In-Situ monitors Bio/Chem/Rad Detectors Surveillance • sparse • disparate • mobile/in-situ • extensible Sensor Web Enablement • discovery • access • tasking • alert notification • web services and encodings based on Open Standards • (OGC, ISO, OASIS, IEEE) Models and Simulations • vendor neutral • extensive • - flexible • adaptable • nested • national, regional, urban • adaptable • data assimilation Sensor Web Enablement Framework M. Botts -2004

17. 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 • …

18. Development of a Remote Sensing Testbed For Tropospheric Air Quality and Winds Summary • Multiple parameters observed by complementary sensors • Frequent operation of stationary sensors over extended periods • Wide range of weather conditions and airmass types • Interaction with end users in a simulated operational setting • Infrastructure to accommodate guest investigators • Occasional multi-institutional intensive operational periods • Funding/participation from multiple agencies and organizations • Invite further discussions with interested parties mike.newchurch@nsstc.uah.edu