Satellite Aerosol Detection in the NPOESS Era

1
Satellite Aerosol Detection in the NPOESS Era

• Leslie O. BelsmaThe Aerospace Corporation
• Leslie.belsma_at_aero.org
• 310-336-3040

2
Agenda

• Background
• Satellite Sensors
• Current
• National Polar-orbiting Operational Environment
  Satellite System (NPOESS)
• Data Assimilation
• Conclusions

3
Background - Need for Detection and Prediction

• Air quality
• Visual air quality
• Health effect
• Visibility
• Military operations
• Civilian and defense aviation
• Climatic impact global warming

4
Surface Networks

• Visibility, PM, and aerosol properties have
  traditionally been measured from ground based
  networks such as
• SLAMS - State and Local Air Monitoring Stations
• NAMS - National Ambient Monitoring Stations
• SPMS - Special Purpose Monitoring Stations
• PAMS - Photochemical Assessment Monitoring
  Stations
• IMPROVE - Interagency Monitoring of Protected
  Visual Environment
• NASA AERONET (AErosol RObotic NETwork) passive
  aerosol measurements using sun photometers
• Sparsity of ground-based measurements limits
  their utility in understanding climate impact,
  the transport of aerosols, or ambient detection
  for operational applications

5
Needs for Satellite Aerosol Detection

• Space-based Aerosol Detection is a valuable tool
  to augment ground measurements
• Spatial and temporal heterogeneity of aerosols
• Provides coverage in data sparse and rural
  regions where it might be the only source of data
  
• Large spatial domains allows tracking aerosol
  transport

6
Space Based Data

• A variety of aerosol properties can be retrieved
  from satellites
• Aerosol Optical Thickness AOT Aerosol Index
• Angstrom Coefficient
• Single Scatter Albedo
• Size Distribution Information
• Aerosol Type
• Aerosol Shape
• Relative Vertical Distribution
• Aerosol Layer Height
• Backscatter Extinction CrossSection
• Data can be used qualitatively
• Imagery and visualizations to provide a regional
  view of aerosol transport
• Data can be used Quantitatively
• Initialize and validate weather, climate, and air
  quality models

7
Qualitative Wildfire Smoke

• Wildfire Smoke plumes evident in both DMSP OLS
  (Left) and EOS MODIS (Right)

8
Qualitative Dust storm
Air Force Special Operations Command feedback
(Operation Iraqi Freedom) Approximately 20
instances where dust and sand storms were
identified in the DMSP imagery with the lack of
ground obs, DMSP became more important than ever
Ref Lanicci, Polar Max 2004 Conference, Los
Angeles,
9
Satellite Sensors Categories

• Visible IR solar backscatter sensors
• Ozone sensors that detect solar UV absorption and
  backscatter
• Polarimeters
• Active Lidar

10
Visible IR backscatter retrievals

• Backscattered solar radiation over dark surfaces
  mainly varies with aerosol type and concentration
• Aerosols backscatter solar radiation in
  proportion to Aerosol Optical Thickness (AOT) and
  aerosol single scatter phase function
• To retrieve AOT, phase function must be known
• Phase function depends on aerosol size
  distribution and composition
• Aerosol models used with satellite radiances to
  retrieve AOT
• Simplified over ocean because of low and constant
  albedo
• More difficult over land complex and variable
  albedo

11
Visible IR backscatter sensors - AVHRR

• NOAA Advanced Very High Resolution Radiometer
  (AVHRR)
• Polar orbiting
• Operational single-channel algorithm for Aerosol
  AOT retrieval over oceans from radiances in
  channel 1 (0.63 µm)
• Aerosol records spanning over two decades
• NESDIS generates global daytime cloud-free AOT
  over oceans
• Daily, Weekly, Monthly 1 deg maps

http//www.osdpd.noaa.gov/PSB/EPS/Aerosol/Aerosol.
html
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Visible IR backscatter sensors- GOES

• GOES Imager
• Geostationary orbit more frequent data
• Collaborating with EPA, NOAA/NESDIS recently
  implemented operational aerosol retrievals over
  land
• Use GOES visible channel to produce AOT
• 30 minute intervals with a 4km spatial resolution
• Daytime cloud-free conditions

http//www.ssd.noaa.gov/PS/FIRE/GASP/gasp.html
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Visible IR backscatter sensors -MODIS

• Moderate Resolution Imaging Spectroradiometer
  (MODIS)
• 36 well-calibrated bands with spatial resolution
  ranging from 250-1000m
• Daytime cloud-free detection of aerosols with
  high accuracy
• Aerosol retrieval uses seven well-calibrated
  channels from VIS to SWIR
• Global coverage over ocean and nearly global over
  land at 10km res

• Near Real Time access through new EPA-NASA-NOAA
  Collaboration (IDEA-Infusing satellite Data into
  Environmental Applications)

http//idea.ssec.wisc.edu/index.php
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Vis - IR backscatter sensors SeaWiFS, MISR

• NASAs Sea-viewing Wide Field-of-view Sensor
  (SeaWiFS)
• Primary mission ocean color bio-optical
  properties
• AOT at 865nm over oceans is a by-product of
  atmospheric correction
• Routinely produced for the past seven years
• Daily, Weekly, Seasonal at 9km resolution
• Terra Multi-angle Imaging Spectro-Radiometer
  (MISR)
• Measures solar reflectance in four spectral bands
  (red, blue, green, and near infrared)
• Nine widely spaced viewing angles simultaneously
• Allows distinguishing different types of aerosols
  and land surface covers
• AOT over water and dark surfaces composition
  products mapped to a 17.6km grid
• Beta products AOT over other surfaces, Ang Exp,
  Single Scatter Albedo, size, shape, and
  fractional amounts

15
UV Absorption/Backscatter Sensors

• Multispectral bands in near UV detect
  UV-absorbing tropospheric aerosols over both land
  and ocean
• UV aerosol retrieval is fundamentally different
  from VIS/SWIR
• Strong Rayleigh scattering signature
• Reduced, less variable surface reflectivity
• Enables detection of aerosols over more land
  surfaces
• Capability to separate aerosol absorption from
  scattering allows identification of aerosol types
• Less spatial resolution

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UV Absorption/Backscatter Sensors - TOMS

• Total Ozone Mapping Spectrometer (TOMS)
• First instrument to allow observation of aerosols
  as they cross the land/sea boundary
• 50 km footprint
• Aerosol Index product that is related to optical
  depth, is routinely generated
• Earthprobe TOMS Aerosol Index is in terms of
  the differences between measurements at 331 and
  360 nm

17
UV Absorption/Backscatter Sensors

• Other ozone monitors
• GOME (Global Ozone Monitoring Experiment) flying
  on the European Space Agency (ESA) Environmental
  Research Satellite (ERS2)
• SCIAMACHY (SCanning Imaging Absorption
  spectroMeter for Atmospheric CHartographY) flying
  on the ESA ENVISAT launched Oct. 01
• OMI (Ozone Monitoring Instrument flying on the
  NASA Earth Observing System (EOS) Aura mission)
• HIRDLS (High Resolution Dynamics Limb Sounder),
  another NASA Aura mission

18
Aerosol Retrieval Coverage

• MODIS provides aerosol data with high accuracy
  and spatial resolution over most of the globe,
  but challenges in retrieving AOT over highly
  reflective land surfaces results in regional
  coverage that must be filled by other means.

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Aerosol Polarimetry

• Observations of solar reflectance with polarizing
  filters at multiple angles and wavelengths
• Correction for ground reflectance (polarization
  insensitive to wavelength)
• Enables derivation of several aerosol properties
• NASA Research Scanning Polarimeter (RSP)
• Airborne sensor successfully demonstrated the
  capability
• Paving the way for a new generation of
  space-based aerosol sensors

20
Aerosol Polarimetry

• POLDER (POlarization and Directionality of the
  Earths Reflectances)
• Launched Japanese Advanced Earth Observing
  Satellite (ADEOS I II) missions, both of which
  suffered premature deaths.
• Planned as the main payload on future French
  space agency microsatellite PARASOL to complement
  NASAs Earth System Science Pathfinder (ESSP)
  program

21
LIDAR Sensors

• Multi-wavelength Lidar uses the
  wavelength-dependent absorption of atmosphere
  constituents to measure their range-resolved
  concentration
• Provides information on the vertical distribution
  of the aerosols
• Retrieval of aerosol information both night and
  day
• Demonstrated through measurements campaigns with
  NOAA Ozone Airborne Lidar - NOAL(formerly
  UV-DIAL)
• Measures vertical profiles of ozone and aerosols
  from near the surface to the upper troposphere
  along the flight track

22
LIDAR Sensors

• GLAS (NASA Geoscience Laser Altimeter System)
• Launched in Jan 2003 aboard ICESat
• Retrieves ice, cloud, and aerosol properties both
  day and night
• 1064 and 532 nm channels provide atmospheric
  backscatter profiles
• 1064 nm provides height and vertical distribution
  of dense aerosols (and clouds)
• 532 nm provides vertical distribution of
  optically thin aerosols
• 75 m vertical and 175 m horizontal resolution
• Products include Aerosol Layer Height,
  Backscatter crossSection, Extinction Coefficient,
  AOT
• Reliability of two of three GLAS lasers was much
  less than planned and NASA is currently operating
  the system on an intermittent schedule

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GLAS Layer Heights Data Product Example
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Aerosol Product Summary

• Sensor Satellite Retrieved Grid Near Ocean Land Da
  y Night Comments Parameter Size RealTime
• OLS DMSP N/A Imagery only
• AVHRR POES AOT 1 Deg No Yes Rsch Yes Daily,
  Weekly/Monthly
• VISSR GOES AOT 4 km Yes Yes Yes Yes
• AOT Yes Some Yes AOT is for DarkMODIS Aqua
  ASD 10 km Yes No Yes Vegetation Rsch
  Alg Terra Type No Yes Yes for other Land
  Types Additional Aerosol Product
  s from ASDC
• SEAWifs SEAWifs AOT 9 km Yes No Yes AngC
• TOMS Earthprobe Aindex 50 km Yes Yes Yes No
• AOT 13x24km Launch Jul 2004
  OMI Aura SSA Yes Yes Yes Products not
  SO2 available yet
• AOT No Yes Some Yes Rsch over
  homogeneous Sfcs
• MISR Terra AngE SSA 17.6 km Beta Beta Beta AP
  S ASD
• PBLA Layer HT 7/28 kmGLAS ICESat BSctrCS Y
  es Yes Yes Yes Quicklook AExtC Vertical Ava
  ilable AOT 76.8 m

AOT Aerosol Optical Thickness AIndex Aerosol
Indes AngC/E Angstron Coefficient or
Exponent ASP Aerosol Size Parameter Type
Aerosol Type
ASD Aerosol Size Distribution SSA Singel
Scatter Albedo RelVD Relative Vertical
Distribution PBLAlayrerHT Planetary Boundary
andAerosol Layer Heights
BsctrCS Backscatter Cross Section AextC
Aerosol Extinction Cross Section
25
NPOESS

• National Polar-orbiting Operational Environmental
  Satellite System
• 5.6B NPOESS system marks a new era
• Converges operational DoD and NOAA environmental
  satellites with new NASA technologies
• Three orbital planes provide frequent
  data-refresh
• 56 Data Products 21 Enhancement Products
• Rapid-downlink delivers products in 28 minutes
• First launch in 2009

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NPOESS - CONOPS
2. Downlink Raw Data
3. Transport Data to Centrals for Processing
1. Sense Phenomena
Global fiber network connects 15 receptors to
Centrals
4. Process Raw data into EDRs and Deliver to
Centrals
5. Monitor and Control Satellites and Ground
Elements
Full Processing Capability at each Central
NESDIS, AFWA, FNMOC, NAVO
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NPOESS Aerosol Capabilities

• 3 of 11 NPOESS sensors will provide data related
  to aerosols
• VIIRS (Visible Infrared Imaging Radiometer Suite)
• MODIS-like fire, smoke, and aerosol products
• APS (Aerosol Polarimetry Sensor)
• Dedicated to aerosol detection
• OMPS (Ozone Mapping and Profiler Suite)
• Aerosol Index Interim Product
• APS and OMPS will fly in only one of the NPOESS
  orbit planes, while VIIRS will fly on all three
• VIIRS, and OMPS first fly in 2006 on NPOESS
  Preparatory Project (NPP) risk reduction mission

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NPOESS- VIIRS Visible/Infrared Imager
Radiometer Suite

• Merges attributes of the current operational DMSP
  OLS and POES AVHRR sensors with state of the art
  spectro-radiomometer capabilities of the NASA
  MODIS sensor

• 0.4 km imaging and 0.8 km radiometer resolution
• 22 spectral bands covering 0.4 to 12.5 mm
• Automatic dual VNIR and triple DNB gains
• Spectrally and radiometrically calibrated
• EDR-dependent swath widths of 1700, 2000, 3000 km
• Will deliver enhanced MODIS-like aerosol products
  
• AOT
• Size parameter
• Suspended Matter (Type)
• Product resolution at 1.6km over ocean, 9.6km
  over land

29
NPOESS-VIIRS

• VIIRS includes a Day-Night Band (DNB) for visible
  band cloud imagery with a quarter moon
  illumination
• Naval Research Laboratory investigating use of
  VIIRS DNB measurements of scattered moonlight to
  retrieve AOT at night over oceans (Shettle, 2004)
• Nighttime AOT would improve temporal coverage
• Better capture transient aerosol phenomena
• Provide information on day/night differences of
  aerosols
• Aid in understanding the impact of aerosols on
  thermal cooling at night with land/sea breezes in
  coastal regions

30
NPOESS- APS Aerosol Polarimeter Sensor

• Sensor dedicated to measuring global distribution
  of aerosols
• Polarization (all states)
• Multiangular (175 angles)
• Multispectral (nine spectral bands from 0.4 to
  2.25 mm)
• Measurements of spectral and angular polarization
  signature of solar backscatter allow unambiguous
  retrieval of aerosol amount and size
• Most benefit to retrieval of fine particulate
  data
• Wide spectral range needed to understand size
  distributions and determine fraction of aerosols
  absorbing vs reflecting
• 488 nm measures chlorophyll over-water to
  separate surface and atmospheric signals
• 910 nm band will measure water vapor
• 1378 nm will detect cirrus clouds
• Remaining bands used to fully characterize the
  aerosols

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NPOESS-APS

• APS pixel size 5 km to limit sensitivity to cloud
  cover
• APS aerosol products
• Optical thickness
• Particle size distribution
• Refractive index
• Single-scatter albedo and shape
• APS will allow accurate calibration to improve
  VIIRS aerosol retrievals

32
NPOESS-OMPS Ozone Mapping and Profiler Suite

• Includes both nadir and limb viewing systems
• Total column ozone
• High vertical resolution ozone profiles
• Aerosol correction is an interim processing step
  in the ozone retrieval
• Aerosol index, AI, defined in terms of the
  difference between the 336 and 377 nm channels,
  is an Interim Product
• OMPS sulfate detection can be used in conjunction
  with VIIRS data for Suspended Matter product

33
NPOESS Aerosol Related Sensors and Data Products

• Sensor Satellite Processed Latency Ocean Land Day
  Night Comments Products HCS HCS
• NPOESS AOT 28 min 9.6km RschVIIRS 3
  orbit ASP 28 min 1.6 km planes SM 28 min 1.6 km
• AOT 28 min APS footprint isAPS NPOESS ASP 2
  8 min 5 km 5 km Yes No 5 km, APS/VIIRS 1
  orbit SM 28 min TBD product can be ARI, SSA,
  Sh 90 min finer resolution
• OMPS NPOESS SO2 28 min 50 km 50 km 1
  orbit Aindex 28 min

No
AOT Aerosol Optical Thickness ASP Aerosol
Size Parameter SM Suspended Matter
ARI Aerosol Refractive Index SSA
Single-Scattering Albedo SH Shape
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Data Fusion

• Satellite data fusion techniques that exploit
  data from multiple future missions, both domestic
  and international, will further enhance improved
  retrievals by reducing backscatter radiance
  solution space (Labonnote, 2004)
• NASA planning formation flying among EOS
  afternoon constellation of science missions
  satellites
• Aqua
• CALIPSO
• Cloudsat
• Aura
• PARASOL (French micro-satellite containing
  POLDER)
• NPOESS continues the Initial Joint Polar
  Satellite System (IJPS) NOAA and ESA data sharing
  data sharing agreement
• ESA operational METOP will include AVHRR and GOME
  (enhanced follow-on versions) during the NPOESS
  era

35
Application of Satellite AOT to PM

• Research is underway to relate satellite derived
  aerosol optical depth to ground-based Particulate
  Matter (PM) measurements
• Comparison between the surface PM2.5 monitors and
  MODIS AOT(Kittaka, 2004)

• IDEA -Infusing satellite Data into Environmental
  Applications
• Joint NASA/EPA project
• Prototype system in place
• Demonstrates use of MODIS AOT to determine
  transport of fine aerosols within the lower
  troposphere

http//idea.ssec.wisc.edu/
36
Application of Satellite AOT to PM

• Study comparing hourly PM2.5 values from a
  ground-based monitor in Houston with MODIS AOT -
  found good statistical correlation (Wang, 2004)
• Study underway in Europe to demonstrate that
  SeaWiFS and MERIS aerosol products can be
  converted into PM10 and PM2.5 (Ramon, 2003)

37
Data Assimilation

• Integration of satellite and ground measurements
  with numerical models is required to fully
  characterize large spatial and temporal
  variations of aerosols
• Space based aerosol retrievals are column
  quantities
• Data assimilation into numerical models provides
  a 3D grid of aerosol distribution
• Analysis and forecast
• Aerosol transport
• Fine particulate contribution to air pollution

38
Data Assimilation

• Study to assimilate MODIS AOT into GOCART model
  (Yu, 2003)
• Produced AOT over land in better agreement with
  ground based AERONET measurements than either the
  MODIS retrievals or the GOCART simulations alone
• Study to assimilate GOES AOT into the CSU RAMS
  for optimal characterization of the spatial and
  temporal aerosol distribution (Wang, 2004)
• Results indicated that aerosol radiative effects
  are significant in the simulation of aerosol
  transport and weather prediction

39
Conclusion

• Space-based measurements are an increasingly
  valuable tool in the detection, tracking and
  understanding of aerosols by providing
  observations over large spatial domains and where
  ground based measurements are sparse or missing.
• Numerous satellite missions flying today can
  retrieve aerosol parameters that can be related
  to PM concentrations for air quality
  applications.
• Increasingly sophisticated multi-spectral,
  multi-angle, polarization, and active sensing
  methods will be employed on future missions.
• The NPOESS program will merge the remote sensing
  technologies of todays science and operational
  environmental satellite programs to provide
  significantly improved data quality, frequent
  data refresh, and rapid ground processing to
  deliver products within operational timelines.
• Three of the 11 NPOESS sensors will provide
  aerosol data
• It is essential that air quality agencies plan
  now to procure the capability to acquire,
  display, and assimilate these valuable sources of
  data into modeling processes to improve
  particulate matter forecasting into the NPOESS
  era.

40
References

• Shettle E., NPOESS Integrated Program Office
  (IPO), Internal Government Study (IGS) Science
  Team Presentations, Silver Spring, MD, February
  24-26 and March 2-4, 2004
• Labonnote, L., Kreidenweis, S., Stephens, G.,
  Multi-Sensor Retrieval of Aerosol Properties.
  Colorado State/CIRA Annual Review 04 Poster,
  Accessed via CIRA Website Jul 2004
• Kittaka, C. j. Szykman, B. Pierce, J Al-Saadi, D.
  Neil, A.Chu, L Remer, E. Prins, J.Holdskom, 2004
  Utilizing MODIS Satellite Observations to Monitor
  and Analyze Fine Particulate Matter, PM2.5,
  Transport Event, Proceedings of the 84th AMS
  Annual Meeting, Washington State Convention and
  Trade Center, Seattle WA 11-15 Jan 2004
• Wang, J, U.S Nair, S. A Christopher., GOES-8
  Aerosol Optical Thickness Assimilation in a
  Mesoscale Model Online Integration of Aerosol
  Radiative Effects, JGR, Revised Submission
  August 5, 2004
• Ramon, D., R. Santer, J. Vidot, Determination of
  fine particulate matter from MERIS and SeaWiFS
  aerosol data, Proceedings of the ESA Envisat
  MERIS Users Workshop 10-14 Nov 03
• Yu, H., R. E Dickinson, M. Chin, Y. J Kaufman, B.
  N. Holben, I.V. Geogdzhayev, M. I Mishchenko,
  Annual cycle of global distributions of aerosol
  optical depth from integration of MODIS
  retrievals and GOCART model simulations JOURNAL
  OF GEOPHYSICAL RESEARCH, VOL. 108, NO. D3, 4128,
  14 February 2003