Satellite Aerosol Detection in the NPOESS Era

Leslie O. BelsmaThe Aerospace Corporation

Leslie.belsma@aero.org

310-336-3040

Agenda

Background Satellite Sensors

Current National Polar-orbiting Operational Environment

Satellite System (NPOESS) Data Assimilation Conclusions

Background - Need for Detection and Prediction

Air quality Visual air quality Health effect

Visibility Military operations Civilian and defense aviation

Climatic impact – global warming

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

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

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

Qualitative: Wildfire Smoke

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

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,

Satellite Sensors Categories

Visible IR solar backscatter sensors Ozone sensors that detect solar UV absorption

and backscatter Polarimeters Active Lidar

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

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

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

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

http://idea.ssec.wisc.edu/index.php

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

Vis - IR backscatter sensors – SeaWiFS, MISR

NASA’s 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

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

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

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

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.

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

Aerosol Polarimetry

POLDER (POlarization and Directionality of the Earth’s 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 NASA’s Earth System Science Pathfinder (ESSP) program

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

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

GLAS Layer Heights Data Product Example

Aerosol Product Summary Sensor Satellite Retrieved Grid Near Ocean Land Day 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 TypesAdditional AerosolProducts from ASDC

SEAWifs SEAWifs AOT 9 km Yes No YesAngC

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 AngESSA 17.6 km Beta Beta BetaAPSASD

PBL&ALayer HT 7/28 km

GLAS ICESat BSctrCS Yes Yes Yes Yes QuicklookAExtC Vertical AvailableAOT 76.8 m

AOT = Aerosol Optical ThicknessAIndex = Aerosol IndesAngC/E = Angstron Coefficient or ExponentASP = Aerosol Size ParameterType = Aerosol Type

ASD = Aerosol Size DistributionSSA = Singel Scatter AlbedoRelVD = Relative Vertical DistributionPBL&AlayrerHT = Planetary Boundary andAerosol Layer Heights

BsctrCS = Backscatter Cross SectionAextC = Aerosol Extinction Cross Section

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

1. Sense Phenomena2. Downlink Raw

Data3. Transport Data to

Centrals for Processing

5. Monitor and Control Satellites and Ground Elements

4. Process Raw data into EDRs and Deliver to Centrals

Full Processing Capability at each Central: NESDIS, AFWA, FNMOC, NAVO

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Global fiber network connects 15 receptors to Centrals

MMC (Suitland)

Schriever MMC

NPOESS - CONOPS

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

NPOESS- VIIRS Visible/Infrared Imager Radiometer Suite

0.4 km imaging and 0.8 km radiometer resolution 22 spectral bands covering 0.4 to 12.5 m 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

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

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

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 m)

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

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

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

NPOESS Aerosol Related Sensors and Data Products

Sensor Satellite Processed Latency Ocean Land Day Night CommentsProducts 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 28 min 5 km 5 km Yes No 5 km, APS/VIIRS

1 orbit SM 28 min TBD product can beARI, SSA, Sh 90 min finer resolution

OMPS NPOESS SO2 28 min 50 km 50 km1 orbit Aindex 28 min

AOT = Aerosol Optical ThicknessASP = Aerosol Size ParameterSM = Suspended Matter

ARI = Aerosol Refractive IndexSSA = Single-Scattering AlbedoSH = Shape

No

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

Application of Satellite AOT to PM

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

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)

http://idea.ssec.wisc.edu/

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)

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

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

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 today’s 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.

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 User’s 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