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N.A. Krotkov, Goddard Earth Sciences and Technology Center /UMBC and NASA/GSFC PowerPoint Presentation
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N.A. Krotkov, Goddard Earth Sciences and Technology Center /UMBC and NASA/GSFC

N.A. Krotkov, Goddard Earth Sciences and Technology Center /UMBC and NASA/GSFC

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N.A. Krotkov, Goddard Earth Sciences and Technology Center /UMBC and NASA/GSFC

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  1. Measuring aerosol single scattering albedo in UV by combining use of shadowband and almucantar techniques N.A. Krotkov, Goddard Earth Sciences and Technology Center /UMBC and NASA/GSFC P.K.Bhartia, J. Herman, NASA/GSFC, Jim Slusser, Gwen Scott, USDA UVB Monitoring network G. Labow, A.Vasilkov, SSAI T. Eck, O. Dubovik, GEST/UMBC and B. Holben, NAS A/GSFC

  2. Why is aerosol UV absorption important ? Aerosol effects on UV trends may enhance reduce, or reverse effects of stratospheric O3 change TOMS overestimationof surface UV irradiance 22 21 + 10%-20% 23 3) Aerosol effects on photochemical smog production: aerosol scattering increases photolysis rates; while aerosol absorption decreases it: Change in BL ozone mixing ratios as a result of direct aerosol forcing: +20ppb ( =0.95) -24ppb ( =0.75)

  3. why NASA? July 15 2004 TOMS SSA at 380nm

  4. Possibility exist to derive column aerosol absorption from the ground by measuring: • (2) Diffuse sky radiation ~ aerosol scattering  • (1) Direct sun radiation ~ aerosol extinction () • Combining (1) and (2) measurements and assuming surface albedo allows measuring  (Q) • Assuming horizontal homogeneity one can separate (Q) and aerosolsingle scattering albedo:  …

  5. Measurements :t(l) and Diffuse sky Irradiance: E=I(l,Q)dQ (1) Angular averaging (Diffuse-to-Direct irradiance ratio): Inversion: Fitting of DD(t,g, )=E/e-t to infer with assumedt, g=< >Q[B.Herman et al JAS 1975; King 1979; Eck et al JGR 2003; Tarasova et al FAO 2004] (2) Angular Resolved techniques (Almucantar, PP ): Measurements :t(l) and I(l,Q) l = 0.44, 0.67, 0.87, 1.02 mm 2o ≤ Q≤ 150o (up to 30 angles) Inversion:statistically optimized fitting of I(l,Q)and t(l) with the microphysical-RT model to infer PSD,  (l,Q),n(l) , k(l) -> (l)[Dubovik and King 2000]

  6. Both techniques are more accurate for large aerosol loadings … … for the same aerosol loading UV spectral region offers potentially more accurate retrievals for small particles (pollution, smoke aerosols ) Extrapolating AERONET SSA [Dubovik et al 2002] assuming constant refractive index

  7. Both techniques are more accurate for small surface albedo … Surface albedo ~ 0.02 –0.03 in UV We consider it fixed in all retrievals

  8. only Diffuse-To-Direct Irradiance technique has been tried also in UV [Wenny et al 1998, Petters et al JGR, 2003; Wetzel et al 2003; C.Goering, et al. 2004] So far … The measurements are sparse … and have not been validated

  9. USDA UV-B Monitoring and Research Program operates US network of UV MultiFilter Rotating Shadowband Radiometers (UV-MFRSR) UV-MFRSR was continuously operated at NASA/GSFC since October 2002 3 min measurements of total and diffuse irradiance measurements at 300, 305, 311, 117, 325, 332, 368nm • Characterized and monitored by UVB USDA network

  10. UV-MFRSR: corrections for systematic errors 1) Forward scattering correction 2) Cosine correction was interpolated according to solar elevation and azimuth Cosine correction for diffuse irradiance fD~0.99 3) Dark current correction 4) Temperature stabilization and monitoring: <T>=41.7C (s =0.2C)

  11. UV-MFRSR voltage and calibration errors at 368nm

  12.  extinction in UV Mauna Loa solar calibration Daily Vo Calibration Transfer Brewer ozone measurements UV-MFRSR cosine corrected direct-normal voltage Interpolated CIMEL a corrected for pressure

  13. UV-MFRSR spectral band characterization MFRSR spectral band model takes into account actual UV-MFRSR spectral response functions (SRF) as well as spectral variation of the solar flux and atmospheric extinction within each filter bandpass of the instrument.

  14. Spectral interpolating AERONET AOT AERONET direct sun aerosol extinction optical thickness at 340nm, 380nm, 440nm, and 500nm normalized by (380). Extrapolation to longer UV-MFRSR channels using quadratic least squares fit of ln() versus ln() [Eck et al 2003] compared to the linear extrapolation from 340nm and 380nm. The difference in ext between quadratic and linear interpolation methods is typically less than 0.005 at 368nm.

  15. Daily <ln(V0)> AOT comparisons

  16. Long-term changes in UV-MFRSR Vo calibration

  17. Aerosol Extinction  in UV • by shadowband technique Daily t extinction optical thickness rms differences between UV-MFRSR and AERONET CIMEL measurements at 368nm: • s  < 0.01 for  < 0.4 • s  < 0.02 for all clear sky days

  18. 2. Aerosol single scattering albedo in UV by combining shadowband and almucantar techniques • What is known: • Extinction t at 368nm (error < 0.01) ! • Surface albedo at 368 nm (0.02 in UV, error <0.01) ! • Particle size distribution (from AERONET) ! • Refractive index (m=n-ik from AERONET at 440nm) ! • 2 aerosol parameters are unknown in UV: • Asymmetry parameter of the phase function gUV=<cosQ> ? • Single scattered albedo, w in UV ?

  19. With shadowband technique only 1 measurement is available for fitting DD=Diffuse/Direct ratio [Herman et al, 1975; King 1979] or DT= Diffuse/Total ratio (DT) [Eck et al 2003] or TR=Total /Rayleigh Transmittance [Krotkov et al 1998] The advantage of shadowband technique is that No calibration is required!

  20. We retrieve imaginary part of refractive index, k 1) All components of the Global Aerosol Data Set have spectrally flat n 2) k may increase in UV for water soluble and mineral dust components [GADS, P. Koepke, M. Hess, I. Schult and E. P. Shettle] fixed n=n440 fitted k

  21. The actual shape of the AERONET particle size distribution was used for retrievals: 1) AERONET discrete (22 points) PSD was parameterized by a bi-modal Log normal size distribution 2) For this study we used actual AERONET retrieved PSD in each case (no LUT generation)

  22. absolute radiometric calibration of sky measurements (5% error) 3-min Diffuse/Total relative measurement (2% error) DT text Fitting of DT, with UArizona RT model A-priori information Fitting of absolute sky radiances in almucantar ozone k AERONET retrievals of size distribution (PSD) and effective refractive index (real) at 440nm Mie calculations PSD = const n=n440 Imaginary refr index, k, n440 Single scattering albedo at 368nm Single scattering albedo at 440nm

  23. Error in tabs due to measurement and calibration errors at 368nm • Error due to uncertainty in size distribution and real refractive index becomes comparable to the measured uncertainties only for large aerosol loadings (ext>0.5)

  24. Siberian smoke plume on June 2, 2003 AERONET SSA UV-MFRSR AOT 368nm

  25. Diurnal 368 dependence on June 24, 2003 AERONET SSA UV-MFRSR AOT 368nm

  26. Diurnal 368 changes on August 25, 2003 AERONET SSA AOT UV-MFRSR 368nm

  27. Comparison statistics: (65 matchup cases in summer 2003) • Imaginary refractive index, k in UV: • <k368> ~0.01, k368~0.004 at 368nm • <k440> ~0.006, k440~0.003 at 440nm • Single scattering albedo,  • <368>=0.93 +/-0.02 (1) at 368nm • <440> =0.95 +/-0.02 (1) at 440nm

  28. 3. SSA spectral dependence in UV 368nm

  29. 368nm – 332nm

  30. 368nm –332nm- 325nm

  31. 368nm

  32. 368nm – 332nm

  33. 368nm – 332nm –325nm


  35. 4. Aerosol absorption optical thickness: Seasonal Dependence The absvalues show a pronounced seasonal dependence of ext with maximum values abs~0.05 at 368nm (~0.07 at 325nm) occurring in summer hazy conditions and <0.02 in winter-fall seasons, when aerosol loadings are small.

  36. W results: Seasonal Dependence No clear W seasonal dependence

  37. W results: AOT dependence The decrease of single scattering albedo with optical thickness suggests that the type of aerosol changes between summer and winter conditions.

  38. New TOMS UV database (1978-2003) 305nm 324m Erythema 380nm

  39. Maps of mean 1978-1987 daily UV irradiation (in J m-2) for August UV from pyranometers TOMS Difference(%)

  40. Theoretical parameterization of the bias agrees with the UV-MFRSR UV flux measurements The slope of the empirical fit ~3 is close to the model slope. abs

  41. Difference between TOMS UV (325nm) and UV-MFRSR at 325nm and Greenbelt, MD 20% bias

  42. Summary • The shadowband method is complementary to the AERONET almucantar retrieval of , because • retrievals are more reliable at low solar zenith angles; • absolute sky radiances calibration is not required; • The variability in aerosol size distribution and real refractive index becomes comparable to the measured uncertainties only for large aerosol loadings (ext>0.5) • Combined use of both methods allows: • Deriving complete diurnal cycle of aerosol absorption • Considering days with low aerosol loadings, thus obtaining complete seasonal cycle of aerosol absorption • Extending spectral dependence of single scattering albedo into UV wavelengths

  43. Future work • Continuing co-located measurements at GFSC location is important to improve the comparison statistics; • Extending UV-MFRSR spectral coverage to 440nm • and CIMEL almucantar retrievals to 340 and 380nm to allow for spectral overlap between 2 types of aerosol absorption measurements; • Conducting simultaneous measurements at different sites with varying background aerosol conditions.

  44. Backup

  45. SENSITIVITY OF UV-MFRSR MEASUREMENTS TO AEROSOL ABSORPTION Relationship between Rayleigh normalized total transmittance, TR and abs at 368nm, assuming fixed ext=0.167 (red) and 0.2 (purple) and o=33o,70o. Linear regression model (1) is fitted to al data points assuming variability due to size distribution as random errors

  46. UV-MFRSR on-site calibration (V0) UV-MFRSR cosine corrected direct-normal voltage UV-MFRSR spectral band model Direct pressure measurements Interpolated CIMEL a corrected for pressure Brewer/TOMS total ozone measurements Airmass factor

  47. AOT comparisons

  48. Long-term changes in UV-MFRSR Vo calibration