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WP 5 : Clouds & Aerosols. Absorbing Aerosol Index (AAI). L.G. Tilstra and P. Stammes Royal Netherlands Meteorological Institute (KNMI). SCIAvisie Meeting, SRON, Utrecht, 21-09-2012. Cloud and surface albedo effects in the AAI. There are some flaws in the definition of the AAI:.
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WP 5 : Clouds & Aerosols Absorbing Aerosol Index (AAI) L.G. Tilstra and P. Stammes Royal Netherlands Meteorological Institute (KNMI) SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Cloud and surface albedo effects in the AAI There are some flaws in the definition of the AAI: • The spectral dependence of the surface albedo is not taken into account • Clouds have an (unwanted) impact on the residue Impact of (a): up to one index point (for, e.g., desert areas) Impact of (b): negative bias, can be more than one index point Reason: the simulated reference scene used in the algorithm contains only one Lambertian reflector, which makes it impossible to separate scene and surface contributions. Also, it is just not possible to have coexisting cloud and ground surfaces described properly by just one (representative) surface. Solution: work with two Lambertian reflectors instead of one. Split a partly clouded scene into a cloud-free part and a fully clouded part. SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Mix scenes adopting the Independent Pixel Approximation (IPA): 340 / 380 nm hs = surface height (ETOPO–4 database) As = surface albedo (OMI LER database) c = effective cloud fraction (retrieved at 380 nm) z = cloud height (FRESCO, or take z = hs for simplicity) Ac = cloud albedo (= 0.8) Algorithm scheme: SLER : TLER : SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Assumptions made: Ac(340) = Ac(380) = 0.8 (wavelength independent) c(340) = c(380) (wavelength independent) CHECK: retrieved cloud fraction (c) at 380 nm versus FRESCO cloud fraction: (one orbit of SCIAMACHY data) Good correlation. The wavelength dependence of effective cloud fraction is apparently small (as expected). SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Verification: simulations of cloudy, aerosol-free scenes DAK can model the Earth reflectance for clear-sky or fully clouded scenes. There are (at least) two possible ways to vary cloud parameters: • Construct partially cloud covered scenes using the Independent Pixel Approximation (IPA). One can vary the geometrical cloud fraction. • Accept that the geometrical cloud fraction in the simulations is equal to 1 and vary the cloud optical thickness (COT) in DAK (to get thin/thick clouds). Retrieve the residue for the simulated cloud reflectances and hope to find that the retrieved residues are close to zero. Mie calculations by Martin de Graaf (KNMI) SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
IPA: Dependence of residue on solar zenith angle Θ= 0° (exact nadir) As = 0.05 Reff = 8 μm COT = 16 Red : single LER (SLER) Green : modified LER (MLER) Blue : twin LER (TLER) The cloud layer is located between 1 and 2 km. The new TLER retrieval method also uses the IPA all *remaining* deviations from zero residue are caused by the Lambertian description of clouds in the TLER algorithm compared to the Mie description of clouds in the simulations. SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
IPA: Dependence of residue on geometrical cloud fraction Red : single LER (SLER) Green : modified LER (MLER) Blue : twin LER (TLER) SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Full cloud cover: Dependence of residue on solar zenith angle Θ= 0° (exact nadir) As = 0.05 Reff = 8 μm COT = 4 Red : single LER (SLER) Green : modified LER (MLER) Blue : twin LER (TLER) The cloud layer is located between 1 and 2 km. Also for this case there is quite an improvement. SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Full cloud cover: Dependence of residue on COT Θ= 0° (exact nadir) Θ0= 45° As = 0.05 Reff = 8 μm Red : single LER (SLER) Green : modified LER (MLER) Blue : twin LER (TLER) The cloud layer is located between 1 and 2 km. Conclusion: TLER approach leads to a smaller dependence of the residue on cloud presence/parameters. SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Effect on residue for SCIAMACHY Yearly mean for the year 2007 SLER: We find negative values where we expect little or no aerosols. The average should be closer to zero for these cases. SLER TLER: The average values are much closer to zero. Ok. TLER SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Histograms July–August–September 2007 SLER The histogram of “all scenes” looks weird compared to the histogram of “cloud-free scenes”. TLER The histogram of “all scenes” is similarly shaped. Ok. SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Conclusions The (unwanted) dependence of the AAI on cloud presence is strongly reduced if we make use of two Lambertian reflectors instead of one in the algorithm. This improves the quality of the AAI. The separation between cloud-free and cloud-covered parts of the scene allows the including and handling of spectrally varying surface albedo. Outlook for WP 5 • Implementation of these improvements in the scientific AAI product (SC-AAI) • Support implementation in the official L2-AAI via the SQWG: correction for cloud and surface albedo effects • Verification of (scan-angle dependent) instrument degradation for support of the SQWG SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Extra slides SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Introduction: Absorbing Aerosol Index (AAI) The AAI represents the scene colour in the UV • Definition of the residue: where the surface albedo A for the simulations is such that: (A is assumed to be wavelength independent: A340 = A380) no clouds, no aerosols : r = 0 clouds, scattering aerosols : r < 0 absorbing aerosols : r > 0 B. Definition of the AAI: AAI = residue > 0 (and the AAI is not defined where residue < 0) The AAI can be retrieved over land and sea surfaces, even in the presence of clouds. SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Example of global aerosol distribution recorded by SCIAMACHY: The “Global Dust Belt”: Desert Dust Aerosols (DDA) (dust storms, all year) Biomass Burning Aerosols (BBA) (dry season, anthropogenic) AAI from other UV satellite instruments: TOMS, GOME-1, OMI, GOME-2. Combined with SCIAMACHY there are more than three decades (1978–2012) of AAI data available for studies of trends in desert dust and biomass burning aerosol. SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
The “Global Dust Belt” SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
AAI products from GOME-1, SCIAMACHY, GOME-2, and OMI: *GOME-1: loss of global coverage on 22 June 2003 ; instrument retired on 4 July 2011 SCIAvisie Meeting, SRON, Utrecht, 21-09-2012
Residue difference (TLER-SLER) 2007 SCIAvisie Meeting, SRON, Utrecht, 21-09-2012