WP 3: Absorbing Aerosol Index (AAI) WP 10: Level-1 validation L.G. Tilstra 1, I. Aben 2, and P. Stammes 1 1 Royal Netherlands Meteorological Institute (KNMI) 2 Netherlands Institute for Space Research (SRON) SCIAvisie Meeting, SRON, Utrecht,

(2) WP3: scientific AAI (SC-AAI) and operational AAI (L2-AAI) 1) correction for calibration offset at t=0 2) correction for the obstruction in the FOV for westernmost scan mirror positions (problem affects data until April 2003) 3) correction for (scan-angle dependent) instrument degradation (on top of the standard m-factor correction) 4) look-up tables (LUTs) calculated by RTM taking polarisation into account 5) completely new algorithm approach: more accurate + allows negative albedos 6) improved surface height calculation method + database 7) proper flagging of (potential) sunglint situations 8) flagging of solar eclipse events 9) viewing and solar angles calculated w.r.t. sea-level (instead of w.r.t. 100 km) 10) ozone column dependency of AAI taken into account 11) LUTs calculated by RTM taking the atmosphere’s sphericity into account 12) O2-O2 absorption included in LUTs Algorithm improvements: SQWG YR 1/2SQWG YR 3/4

SCIAvisie Meeting, SRON, Utrecht, (3) (10) Taking ozone absorption into account in the simulated reflectances / LUTs  ozone column fixed to 334 DU Effect of neglecting ozone on the AAI  - New LUTs + ATBD + documentation sent to DLR (end of June 2009) - Total (SCIAMACHY L2) ozone columns are required (and available) as input - DLR are working on changing the algorithm code of the operational processor - Testing is needed with SC-AAI as a reference

SCIAvisie Meeting, SRON, Utrecht, (4) (11) Pseudo-spherical treatment of the atmosphere’s sphericity in the LUTs: LUTs recreated using DAK v3.1, which offers pseudo-sphericity. Improvement is relatively large for solar zenith angles above 75°. Proposed change requires modest changes in the L2-AAI retrieval code. LUTs of the reflectances at 340 and 380 nm were originally calculated for plane parallel atmospheres (using the RTM “DAK”). We proposed to improve this. Impact on the AAI:

SCIAvisie Meeting, SRON, Utrecht, (5) –non-negligible effect: 0.1–0.5 index points for thick clouds –offset of ~0.1 index points for thin/no clouds –same offset for positive residues (12) Taking O 2 –O 2 absorption into account: Effect cannot be neglected. Including O 2 –O 2 absorption in the LUTs improves matters at little or no cost. Effect of including O 2 –O 2 absorption in the AAI LUTs: [O 2 –O 2 absorption bands at 360 and 380 nm]

SCIAvisie Meeting, SRON, Utrecht, (6) Plans for WP3:  Keep improving the scientific AAI product (SC-AAI)  Assist DLR with the implementation of the proposed changes to improve the quality of the L2-AAI (“SQWG year 3/4 activities”)  Continue validation of SC-AAI and L2-AAI  Maintain SC-AAI data archive at the TEMIS site  Further study the scan-angle dependent degradation for support of WP10

SCIAvisie Meeting, SRON, Utrecht, (7) WP10: level-1 validation –comparison with radiative transfer model “DAK” (in the UV) –comparison with other satellite instruments (GOME-1, MERIS, POLDER-2, …) –qualitative analysis of the spectra (spectral properties) Validation techniques for the reflectance: calibration offset spectral features

SCIAvisie Meeting, SRON, Utrecht, (8) Validation techniques for the polarisation: –comparisons with single scattering model –validation via special geometries –comparison with POLDER-2 PMDs 1–4 improved a lot. Degradation has become a problem. Key data improvements: –SRON is working on a new set of key data which is expected to improve the radiometric calibration significantly –This should also solve the presence of spectral features in the spectra –Also polarisation key data will be improvement Validation techniques for the reflectance + polarisation will be used to study the influence of the new key data. (We are repeating the validation work for every new level-1 data version any way.)

SCIAvisie Meeting, SRON, Utrecht, (9) Degradation monitoring using the scientific AAI product: global mean AAI Without m-factors - increase of ~4 index points With m-factors

SCIAvisie Meeting, SRON, Utrecht, (10) Plans for WP10:  Verify improvement in calibration brought about by the new key data using the various tools we developed  Monitor degradation and analyse quality of applied degradation correction using the Absorbing Aerosol Index (AAI) in the UV  Monitor and validate polarisation product using special geometries  Analyse the reflectance over specific stable Earth targets

SCIAvisie Meeting, SRON, Utrecht, (11) Extra slides (R)

SCIAvisie Meeting, SRON, Utrecht, (12) R1: The “Global Dust Belt”

SCIAvisie Meeting, SRON, Utrecht, (13) R2: Introduction of the Absorbing Aerosol Index (AAI) and the residue A.Definition of the residue: where the surface albedo A for the simulations is such that: (A is assumed to be wavelength independent: A 340 = A 380 ) no clouds, no aerosols: r = 0 clouds, no absorbing 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 represents the scene colour in the UV –

SCIAvisie Meeting, SRON, Utrecht, (14) R3: Typical global aerosol distribution: The “Global Dust Belt”: Desert Dust Aerosols (DDA) (dust storms, all year) AAI from other UV satellite instruments: TOMS, GOME-1, GOME-2. Combined with SCIAMACHY there are more than three decades (1978–2009) of AAI data available for studies of trends in desert dust and biomass burning aerosol. Biomass Burning Aerosols (BBA) (dry season, anthropogenic)