pseudo-true color image false-color land use image

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