AERONET Inversions: Progress and Perspectives

1. AERONET Inversions: Progress and Perspectives Oleg Dubovik (NASA / GSFC) Alexander Sinyuk (NASA / GSFC) Tatyana Lapyonok (NASA / GSFC) Brent Holben (NASA / GSFC) Tom Eck (NASA / GSFC) Alexander Smirnov (NASA / GSFC) Anne Vermeulen (NASA / GSFC) Teruyuki Nakajima (CCSR, Tokyo, Japan) Takashi Nakajima (CCSR, Tokyo, Japan) Charles Gatebe (NASA / GSFC) Michael King (NASA / GSFC) Francois-Marie Breon (CEA/DSM/LSCE, France) Michael Sorokin (NASA / GSFC) Ilya Slutsker (NASA / GSFC) AERONET/PHOTON… (Word-Wide)

2. Retrieval scheme: Forward model: -Spectral and angular scattering by particles with different sizes, compositions and shapes - Accounting for multiple scattering in atmosphere • (Dubovik and King, JGR, 2000) Numerical inversion: -Accounting for noise -Solving Ill-posed problem - Setting a priori constraints Observations aerosol particle sizes, refractive index, single scattering albedo, etc.

3. Multiple Scattering Multiple Scattering Multiple scattering effects are accounted by solving scalar radiative transfer equation with assuming Lambertian ground reflectance (Nakajima – Tanaka code) Aerosol scattering Gaseous absorption Surface reflection Molecular scattering

4. Single Scattering Single Scattering by Single Particle Scattering and Absorptionis modeled assuming aerosol particle as homogeneoussphere with spectrally dependent complex refractive index ( m(l)= n(l) - i k(l)) - “Mie particles” Iscat() m(l) Radius I0() Itrans() P(Q)-Phase Function; 0(l) -single scattering albedo (l) - extinction optical thickness; (l)0(l) absorptionoptical thickness

5. AERONET model of aerosol AERONET model of aerosol spherical: Randomly oriented spheroids : (Mishchenko et al., 1997)

6. Inversion • Statistically optimized fitting: • (Dubovik and King, 2000) weighting Lagrange parameters • Measurements: • i=1 - optical thickness • i=2 - sky radiances • their covariances • (should depend on l and Q) • -lognormal error distributions a priori restrictions on norms of derivatives of: i=3 -size distr. variability; i=4 -n spectral variability; i=5 -k spectral variability; consistency Indicator

7. Fitting as a retrieval strategy

8. The averaged optical properties of various aerosol types (Dubovik et al., 2002, JAS) _ +

9. AERONET inversion developments • Forward model: • accounting for particle shape • - using non-lambertian surface • modeling polarization • Output improvements: • detailed phase function • degree of polarization • flexible separation of modes • - fluxes and forcing • details of fitting (biases and random) • Retrieval flexibility: • additional spectral channels • different geometries • Errors estimation: • for individual retrieval • for absorption optical thickness • for phase functions, etc. • Inversion of combined data: • different geometries • combining with satellite • - combining with aircraft • Perspectives: • assuming bi-component aerosols • combining with polarimetric • satellite observations • - retrieval of shape distribution

10. AERONET inversion scenarios • Almucantar: • t(l), I(l,Q) • = 0.38, 0.44, 0.5, 0.67, 0.87, 1.02, 1.64, mm Inversion Products: dV/dln(ri) n(l) k(l) BRDF errors spheres Principal Plane: t(l), I(l,Q) l = 0.38, 0.44, 0.5, 0.67, 0.87, 1.02, 1.64, mm spheroids Polarized Principal Plane: t(l), I(l,Q),P(l,Q) l = 0.87mm w0(l) P11(l), P12(l), ... fine & coarse fluxes, … satellite, aircraft, etc.

11. Utilizing additional spectral channels • Almucantar: • t(l), I(l,Q) • = 0.44, 0.67,0.87, 1.02, 1.64, mm Potential enhancement of information Increased calibration efforts Desert Dust (Dhabi, UAI) dV/dln(ri) n(l) w0(l)

12. Utilizing additional spectral channels • Almucantar: • t(l), I(l,Q) • = 0.38, 0.44, 0.67, 0.87, 1.02, mm Potential enhancement of information Increased calibration efforts GSFC aerosol dV/dln(ri) n(l) w0(l)

13. Fitting additional spectral channels GSFC aerosol Dhabi dust + 1.64 mm + 0.5, 1.64 mm + 0.38 mm + 0.02 - 0.02 ??? water vapor ? fine ?

14. Utilizing principal plane Principal Plane: t(l), I(l,Q) l = 0.44, 0.67, 0.87, 1.02, 1.64, mm Enhanced range of scattering angles Sensitivity to vertical structure of aerosol Challenging cloud screening Desert Dust (Dhabi, UAI) dV/dln(ri) n(l) w0(l)

15. Utilizing principal plane Principal Plane: t(l), I(l,Q) l = 0.44, 0.5, 0.67, 0.87,1.02, 1.64, mm Enhanced range of scattering angles Sensitivity to vertical structure of aerosol Challenging cloud screening GSFC aerosol dV/dln(ri) n(l) w0(l)

16. AERONET Polarized Inversion Forward Model: Single Scat: Multiple Scat: DEUZE JL, HERMAN M, SANTER R, JQSRT, 1989 Successive Orders of Scattering Code t(l), I(l,Q),P(l,Q) Numerical inversion: -Accounting for uncertainty (F11; -F12/F11 !!!) - Setting a priori constraints aerosol particle sizes, refractive index, single scattering albedo

17. Utilizing polarization Principal Plane: t(l), I(l,Q) l = 0.44, 0.5, 0.67, 0.87,1.02, 1.64, mm Polarization : t(l), I(l,Q),P(l,Q) l = 0.87mm Enhanced range of scattering angles Sensitivity to vertical structure of aerosol Challenging cloud screening Calibration verification Cape Verde aerosol dV/dln(ri) n(l) w0(l)

18. Fitting polarization Principal Plane: t(l), I(l,Q) l =0.87mm Polarization : t(l), I(l,Q),P(l,Q) l = 0.87mm Enhanced range of scattering angles Sensitivity to vertical structure of aerosol Challenging cloud screening Calibration verification Cape Verde aerosol Radiance Linear Polarizartion

19. Fine and Coarse modes separations Beijing aerosol Radiance 0.45mm Flexible separation between fine and coarse modes (curently: ~0.6 mm)

20. Retrieval using combinations of up-looking Ground-based and down-looking satellite observations Retrieved: Aerosol Properties: - size distribution - real ref. ind. - imag. ref. ind (AERONET sky channels) • Surface Parameters: • BRDF (MISR channels) • Albedo (MODIS IR channels)

21. AERONET / POLDER-2 retrieval Biomass burning Mongu, Zambia, June, 2003 POLDER-2 fit Size distribution BRDF

22. AERONET/ MISR/ MODIS retrieval • AERONET Ground-based Sun-sky radiometer: - t(l) ± 0.02 at 6 channels: 0.34, 0.38, 0.44, 0.67, 0.87, 1.02, 1.65mm • I(l,Q) ± 0.05% at 4 channels: 0.38, 0.44, 0.67, 0.87, 1.02, 1.65mm 3° ≤ scattering angles ≤ ~70° • P(l,Q) ± 0.02% at 0.87 • MISR Reflectance at 4 channels: 0.45, 0.55, 0.67, 0.87 mm 9 viewing angles: ±70.5o, ± 60o,± 45.6o, ± 26.1o, 0o • MODIS Reflectance at 7 channels: 0.47, 0.55, 0.66, 0.87,1.2, 1.6, 2.1

23. Retrieval using combinations of up- and down-looking observations Retrieved: Aerosol above plane: - size distribution - real ref. ind. - imag. ref. ind Aerosol below plane: - size distribution - real ref. ind. - imag. ref. ind Surface Parameters: - BRDF, albedo, etc.

24. Univ. of Washington CV-580 CAR - Cloud Absorption Radiometer Flown by CV-580 aircraft at ~ 700 m above ground 8 spectral channels: 0.34, 0.38, 0.47, 0.68, 0.87, 1.03, 1.19, 1.27mm Measures radiation transmitted* and reflected: 0° ≤ Obs. Zenith ≤ 180° 0° ≤ Obs. Azimuth ≤ 360° *Stray light problems for scattering angles ≤ 10°

25. Optical thickness t(l)on September 6, 2000 AERONET daily variations AATS-14 versusAERONET

26. Aerosol retrieved from combinedCAR - AERONET - AATS-14 obs.

27. Comparison of model retrieved BRDFwith corrected direct BRDF BRDF constrains model: - positive and smooth; - PP symmetrical Gatebe et al. 2003

28. Mongu, Zambia Comparison of retrieved surface reflectance with other observations Lambertian approximation Mongu, September 6, 2000

29. New Inversion Options: • Almucatars (any numbers of spectral channels) • Principal planes (any numbers of spectral channels) • Polarized Principle Planes (0.87 mm) • Combined Principle Planes: Polarized (0.87 mm) + Regular (0.44 - 1.02mm) • Other Combined Cimel Data: • Almucantar + Principle Plane (?) • Several Almucantars + Principle Planes (??) • AERONET + satellite data (MODIS, MISR, POLDER …) • AERONET + aircraft (CAR) + …satellite • Spherical & Nonspherical model (for all retrievals) • Perspectives: • assuming bi-component aerosols • combining with polarimetric satellite observations • - retrieval of shape distribution

30. Offsets Sensitivity to instrumental offsets Offsets were considered in: - optical thickness: - sky-channel calibration: - azimuth angle pointing: - assumed ground reflectance: Aerosol models considered(bi - modal log-normal): - Water-soluble aerosol for 0.05 ≤ t(440) ≤ 1; - Desert dust for 0.5 ≤ t(440) ≤ 1; - Biomass burning for 0.5 ≤ t(440) ≤ 1; Results summary: - t(440) ≤ 0.2 - dV/dlnr (+), n(l) (-), k(l) (-), w0(l) (-) - t(440) > 0.2- dV/dlnr (+), n(l) (+), k(l) (+), w0(l) (+) - Angular pointing accuracy is critical for dV/dlnr of dust (+) CAN BEretrieved (-) CAN NOT BE retrieved

31. Dt bias influence at Dw0 Dt bias: Sky Radiance bias:

32. Random ERRORS in AERONET retrievals ASSUMPTIONS: - measurements have Normal Noise: - optical thickness: s = 0.01 - sky-radiances: s = 5% • CONCLUSIONS: • the retrievals stable • important tendencies • outlined

33. Rigorous ERRORS estimates:General case: large number of unknowns and redundant measurements U - matrix of partial derivatives in the vicinity of solution Above is valid: - in linear approximation - for Normal Noise - no a priori constraints

34. ERRORS estimates with a priori constraints ISSUES: - in linear approximation - for Normal Noise - strongly dependent on a priori constraints - very challenging in most interesting cases

35. ERROR Factors: Important Factors: - Aerosol Loading - Scattering Angle Range - Number of Angles (homogeneity) - Aerosol Type etc.

36. Examples of error estimates high loading low loading

37. ABSORPTION of SMOKE flaming combustion Rio Branco, Brazil smoldering combustionQuebec fires, July 2002