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TEMPO Aerosols Workshop Need for TEMPO-ABI Synergy

TEMPO Aerosols Workshop Need for TEMPO-ABI Synergy. Omar Torres, Hiren Jethva, Changwoo Ahn NASA-Goddard Space Flight Center Greenbelt, MD, 20771, USA. September 11, 2017. Use of near UV Satellite Observations for retrieving aerosol properties.

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TEMPO Aerosols Workshop Need for TEMPO-ABI Synergy

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  1. TEMPO Aerosols Workshop Need for TEMPO-ABI Synergy Omar Torres, Hiren Jethva, Changwoo Ahn NASA-Goddard Space Flight Center Greenbelt, MD, 20771, USA September 11, 2017

  2. Use of near UV Satellite Observations for retrieving aerosol properties • Observations in the 340-400 nm range can be used to derive aerosol properties • Advantages: • Low surface albedo at all terrestrial surfaces (.01 to .03 for vegetation; .08 - .12 deserts) • Sensitivity to aerosol absorption. • Negligible gas absorption interference. • Disadvantages: • Ocean color interference • Aerosol absorption detection is aerosol layer height sensitive. • Historically, near UV measurements have been associated with coarse spatial resolution sensors (TOMS, OMI) primarily designed for trace gas retrieval. • Although TEMPO’s 2.1x4.7 km resolution is unprecedented for hyper-spectral near UV sensors, it is still too coarse for accurate aerosol retrieval. • The associated sub-pixel cloud contamination (SCC) results in low yield and low accuracy AOD retrievals.

  3. Advanced Baseline Imager • ABI channels: • Visible: 0.47, 0.64 μm • Near IR: 0.86, 1.37, 1.6 μm • SWIR/Thermal IR: 2.2, 3.9, 6.2, 6.9, 7.3, 8.4, 9.6, 10.3, 11.2,12.3, 13.3 μm • Spatial Resolution • 0.47 μm 1.0 km • 0.64 μm 0.5 km • > 2.0 μm 2.0 km • Spatial Coverage • Full Disk: 4 per hour • CONUS: 12 per hour • Mesoscale: 30 or 60 sec • Satellite: GOES-16 • Launch date: November 19, 2016 ABI’s much higher spatial resolution measurements allow the application of spatial homogeneity and spectral techniques for cloud masking. Availability of SWIR and thermal IR channels may contribute to aerosol type determination.

  4. Effects of sub-pixel cloud contamination -Reduces the availability of scenes for retrieval. - AOD retrieval contamination in large pixels considered clear Pixel resolution 30 m, 15% CF Pixel resolution 960 m, 25% CF Koren et al, how small is a small cloud?, ACP, 2008 Remer et al., Retrieving aerosol in a cloudy environment: aerosol product availability as a function of spatial resolution, AMT, 2012

  5. Cloud masking Analysis (1) • Observation resolution: 1.0x1.0 km (0.47 μm) • Sample size for cloud detection: 2X2 pixels: 2x2 km at 0.47 μm • Observation resolution: 4.0x2.0 km (0.47 μm) • Sample size for cloud detection: 2X2 pixels: 8x4 km at 0.47 μm Cloud mask criteria Abs. ref. (470 nm)<0.4 2x2 pixels spatial std. dev<0.0025 Product Resolution: 8x8 km

  6. Cloud Masking Analysis (2) Jan 3, 2012 Apr 10, 2012 Jul 1, 2012 Sept 25, 2012 34% 29% 32% 36% 16% 13% 16% 16% At the TEMPO resolution the number of retrieval opportunities reduces by 50% in relation to a MODIS-like sensor.

  7. Using TEMPO and ABI observations • Use TEMPO near UV algorithm to retrieve AOD and SSA from near UV observations • Use an algorithm (DT, MAIAC) on ABI observations to retrieve AOD from VIS-near IR observations • Use collocated TEMPO ABI to retrieve AOD and SSA from near UV observations using ABI cloud mask • Use collocated TEMPO -ABI observations to retrieve AOD from visible observations and • SSA and either Absorption Angstrom Exponent (AAE) or aerosol layer height (ZAE) from near UV observations

  8. The use of ABI 0.5 km observations (0.64μm) for cloud-masking would result in an improved product spatial resolution (a factor of 8)

  9. Combined VIS-UV retrieval of aerosol properties Independently measured AOD in the visible can be extrapolated to the near UV, and combined with near-UV measured radiances to improve aerosol characterization. For elevated aerosols, retrieve SSA and ZAE For BL aerosols, retrieve, SSA and AAE (or SSA at two near UV channels) Sources of Uncertainty of Independently measured AOD -Sensor Calibration -Surface Characterization -Aerosol Model (SSA and PSD) -Cloud Contamination -Extrapolation Error In the following sensitivity analysis combined uncertainties of 10%, 15% and 20% are assumed.

  10. Simultaneous retrieval of aerosol layer height and single scattering albedo

  11. Sensitivity of retrieved SSA and ZAE to AOD Accuracy AOD uncertainties: 10%, 15%, 20%

  12. Application to collocated OMI – Aqua-MODIS observations OMI-MODIS Derived Height Gasso and Torres, AMT, 2016 (Satheesh et al, JGR, 2009) Layer Height (Airborne Lidar) (km) Comparison of retrieved aerosol layer height to lidar observations

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