the first decade omi near uv aerosol observations:
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The first decade OMI Near UV aerosol observations: An A-train algorithm Assessment of AOD and SSA The long-term OMAERUV record - PowerPoint PPT PresentationTRANSCRIPT
The first decade OMI Near UV aerosol observations: An A-train algorithm Assessment of AOD and SSA The long-term OMAERUV record
Omar Torres, Changwoo Ahn, Hiren Jehva NASA,GSFC/SSAI/GESTAR-USRA
The 18th OMI Science Team Meeting De Bilt, Holland March 11-13, 2014
- Torres, O., C. Ahn, and Z. Chen, Improvements to the OMI Near UV aerosol algorithm using A-train CALIOP and AIRS observations, Atmos. Meas. Tech., 6, 3257-3270, 2013
OMICALIOP
AIRS
Combined use of OMI, CALIOP and AIRS observations in OMAERUV Aerosol RetrievalOMAERUV uses a CALIOP-based Aerosol Layer Height Climatology and real-time AIRS carbon monoxide data for aerosol type identification [Torres et al., 2013]
The combined use of AI and CO allows the identification of smoke layers over arid areas. AIRS CO allows the identification of heavy aerosol
loads over China, and other regions, otherwise undistinguishable from cloud contamination.
AOD June 2007 Monthly average
Without CO
With CO
Ahn, C., O. Torres, and H. Jethva, Assessment of OMI Near UV Aerosol Optical Depth over land, JG R, accepted, 2014
Global Validation of OMAERUV Aerosol Optical Depth
OMI 388 nm AOD retrievals were compared to AERONET observations at 44 sitesrepresentative of the most commonly observed aerosol types: desert dust, carbonaceous, and urban-industrial particulate.
OMAERUV AOD validation: Comparison at representative locations
Desert Dust Carbonaceous Aerosols Urban Industrial Aerosols
OMAERUV AOD Validation: The Global Picture
Number of pairs per 0.02 AOD bin. Maximum pair density (50 to 110) shown in pink.
OMAERUV AOD Validation: The long-term record at selected sites
Long-term OMAERUV and AERONET AOD records shows no obvious trends
Aero
sol O
ptica
l Dep
thGSFC
Alta Floresta
Dakar
IER_Cinzana
Xiang He
OMAERUV AERONET
OMAERUV AOD Validation: The long-term sensor stability
The lack of temporal trend highlights OMI sensor long-term stability
How does OMAERUV perform in relation to other algorithms?
OMAERUV MISR
MODIS-DB OMAERO
Simultaneous comparison to AERONET in arid & semi-arid environments
-Jethva, H., O. Torres, and C. Ahn, Global Assessment of OMI Aerosol single-scattering albedo in relation to Ground-based AERONET Inversion, J. Geophys. Res., submitted, 2014
Comparison of OMAERUV Single Scattering Albedo to AERONET Observations
Unadjusted for wavelength difference Adjusted for wavelength difference
OMAERUV SSA assessment: Comparison at selected AERONET sites
OMAERUV SSA assessment: Summary of results
SSA difference decreases with aerosol optical depth
SSA difference decreases rapidly with AI, close to zero for AI >2.0
OMAERUV SSA evaluation using SKYNET observations (new results!)
SKYNET is a Japanese sky radiometer network (Chiba University) that uses sky-radiance measurements to derive aerosol particle size and optical properties (similar to AERONET).
Aerosol absorption properties are derived at 340, 380, 400, 500, 670, 1020 nm.
Observing sites in Japan, China, Thailand, Mongolia, South Korea, India, Europe.
OMAERUV – SKYNET SSA COMPARISON (2006-2008)
Preliminary comparison results are encouraging
Nine-year Global record of OMI Aerosol Absorption Optical Depth
Jethva, H., O. Torres, F. Waquet, D. Chand, and Y. Hu., How do A-train sensors inter-compare in the retrieval of above cloud aerosol optical depth? A case study assessment, Geophys. Res, Lett., 41, 186-192, 2014
OMI Retrieval of Aerosols above clouds: Multi-sensor comparison
Concluding Remarks
OMAERUV AOD/SSA products have been evaluated by comparison to independentground-based and satellite observations.
On average 65% of evaluated AOD results agree with AERONET within 0.1 or 30%, yielding0.81 corr. coef., 0.1 y-intercept, and rms 0.16
OMI retrieved SSA is quantitatively consistent with AERONET and SKYNET ground based observations.
The correlative analysis with ground-based observations over the OMI sensor lifetime showsremarkable longterm stability.
Future work includes the combined use of Aqua-MODIS and OMI for improved cloud contamination screening.
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