Global observations and spectral characteristics of desert dust and biomass burning aerosols

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1 Global observations and spectral characteristics of desert dust and biomass burning aerosols M. de Graaf & P. Stammes Royal Netherlands Meteorological Institute (KNMI) P.O. Box 201, 3730 AE De Bilt, The Netherlands. Abstract A technique that has gained considerable interest over the last years to monitor aerosol distributions and characterise aerosol source regions has been the use of the Absorbing Aerosol Index (AAI). It has been used extensively to monitor ultraviolet (UV) absorbing aerosols, mainly desert dust and biomass burning aerosols. The AAI is not an aerosol quantity, but a radiation difference in the UV. Its main advantages are its insensitivity to scattering aerosols and clouds, which makes it suitable for global monitoring of absorbing aerosols with sensors with large footprints, and its insensitivity to surface type, which makes it suitable for monitoring aerosols over both sea and land and to study the source regions of UV-absorbing aerosols, which are mainly over land. The European spectrometers GOME and SCIAMACHY have been used to produce daily AAI distributions. GOME data (July December 2000) have been used to validate the TOMS AAI distributions and complement the TOMS data set in the period July 1995 October 1996, when no TOMS data are available. SCIAMACHY has been measuring from July 2002 to present. The spectrometers measure the entire spectrum from about 240 nm to about 800 nm (GOME) or about 2400 nm (SCIAMACHY). These instruments are used to characterise the spectra of desert dust and biomass burning aerosols scenes. The spectra are used to discriminate between these aerosol types using direct measurements, which can be useful for aerosol retrieval algorithms which at present use aerosol composition climatologies. I. INTRODUCTION One of the key issues in climate physics today is the effect of aerosols on the global energy budget. The amount and sign of the effect of aerosols on the incoming solar radiation are unknown and produce a large uncertainty in the quantification of the total energy budget of the Earth [1]. There is a great effort in quantifying the global distribution of atmospheric aerosols and understanding their effect on the radiation budget. Because aerosols are intrinsically shortlived, their removal from the atmosphere often is contingent and because aerosol sources are restricted to localised areas with different areas for different aerosols, the temporal and spacial distribution of aerosols is very heterogeneous. This has hampered a satisfactory quantification of global aerosol distributions. Much improvement in our understanding of the global aerosol budget was gained from linkage of ground based measurements and space-borne measurements. Space-borne measurements have the advantage of monitoring of the global atmosphere. The disadvantage is often a poor spacial resolution and interference of sub-pixel clouds. For instruments which have a high spacial resolution these disadvantages are less severe, but there is a trade-off with a poorer global coverage. Usually space-borne instruments measure one quantity, which means that only one aerosol quantity can be derived. As aerosols need to be characterised by four or more quantities, this means that models retrieving aerosol information need a priori information on the other aerosol quantities. Also, most algorithms are restricted to areas over either land or sea surfaces. In this paper the method of using the Absorbing Aerosol Index (AAI) is discussed. Because of its insensitivity to clouds and scattering aerosols, the AAI can be used by instruments with large footprints. Moreover, the AAI uses reflectances in the ultraviolet (UV), a spectral region in which almost all surface types are dark, which makes it potentially suitable for retrieval of aerosol distributions over both land and ocean. It turns out, however, that the crucial surface condition for the method to work is not that the surface needs to be dark, i.e. having a low reflectivity at a certain wavelength, but grey, i.e. having a reflectivity independent of wavelength in a certain wavelength interval. It has been shown that this is true not only for land and sea surfaces, but also for snow and ice surfaces [2], [3]. The AAI is not an aerosol quantity, but a radiation difference in the UV. Traditionally, it uses two measured reflectances, so at most two pieces of information can be gained from one measured scene. Sensitivity studies show a strong dependence of the AAI on aerosol optical thickness (τ), aerosol single scattering albedo (ω 0 ) and aerosol layer height [2]. The AAI has been used to quantify aerosol absorption and aerosol optical thickness [4], [5], but the dependence on aerosol layer height is an unwelcome complication. The current study focuses on the unique character of the spectrometer SCIAMACHY [6] to measure an entire spectrum and to use this information for the characterisation of different UV-absorbing aerosol scenes. Measured backscattered spectral characteristics of scenes with atmospheres laden with different aerosol types might be used to further the development of aerosol retrieval algorithms. It can improve aerosol climatologies, help retrieval algorithms to distinguish between aerosol types without geographical and climatological information,

2 and improve general knowledge of atmospheric aerosols. This paper continues with a brief summary of the theory behind the AAI and a short review of its most important sensitivities (section II). Some results from SCIAMACHY will illustrate its use (section III). Then, some spectra of biomass burning aerosol scenes, desert dust scenes, and other selected scenes, will hint to new possibilities in passive remote sensing of atmospheric aerosols (section IV). II. DERIVATION OF THE AAI The AAI separates the spectral contrast, at two wavelengths in the UV, of the atmosphere caused by aerosol absorption from that of other effects, including molecular Rayleigh scattering, surface reflection, gaseous absorption, and aerosol and cloud scattering, using the reflectance of a simulated Rayleigh atmosphere. It is derived from the residue. The residue r is a wavelength-dependent variable that can be defined as [7] { 10 r λ = 100 log( R λ ) meas 10 log( R } λ ) Ray, (1) R λ0 R λ0 where R λ is the reflectance at a wavelength λ. The superscript meas refers to the measured reflectance in the atmosphere with aerosols, as opposed to a calculated reflectance in an aerosol-free atmosphere with only Rayleigh scattering and absorption by molecules and surface reflection and absorption. The latter is referred to as Ray. The reflectance is defined as R = πi/(µ 0 E 0 ), where I is the radiance at the top of the atmosphere (TOA), E 0 is the solar irradiance at TOA perpendicular to the direction of the incident sunlight and µ 0 is the cosine of the solar zenith angle θ 0. So µ 0 E 0 is the solar irradiance at TOA incident on a horizontal surface unit. If the surface albedo A s for the Rayleigh atmosphere calculation is chosen so that R meas λ 0 = R Ray λ 0 (A s ), (2) where λ 0 is a reference wavelength, (1) can be reduced to r λ = log( Rmeas λ R Ray λ ), (3) where R Ray λ is calculated for surface albedo A s (λ 0 ), so the surface albedo is assumed to be constant in the range [λ, λ 0 ]. Traditionally, λ = 340 nm and λ 0 = 380 nm. Equation (2) involves finding a surface albedo for which the measured reflectance at the reference wavelength is equal to the reflectance of a pure Rayleigh atmosphere with all scattering and absorption effects accounted for in the surface albedo. This inversion process is performed with Lookup Tables (LUTs) of the reflectances, which is the core of the residue method algorithm. On the assumption that the atmosphere is bounded from below by a Lambertian surface, which reflects incident radiation uniformly and unpolarised in all directions, the surface contribution to the reflectance at TOA can be separated from that of the atmosphere [8]: R(λ, µ, µ 0, φ φ 0, A s ) = R 0 (λ, µ, µ 0, φ φ 0 )+ A st(λ) 1 A s s (λ). (4) The first term, R 0, is the path radiance, which is the atmospheric contribution to the reflectance. The second term is the contribution of the surface with an albedo A s. T = t(µ)t(µ 0 ), where t is the total atmospheric transmission, dependent on µ, the cosine of the viewing zenith angle θ, and µ 0, s is the spherical albedo of the atmosphere for illumination from below, and φ φ 0 is the relative azimuth angle. The path radiance can be expanded in a Fourier series. For a Rayleigh atmosphere the expansion is exact with only three terms in φ φ 0, because of the cosine-squared scattering angle dependence: R 0 (λ, µ, µ 0, φ φ 0 ) = a 0 (λ)+ 2 2a i (λ, µ, µ 0 ) cos i(φ φ 0 ). i=1 (5) R 0 is calculated with LUTs of a i (µ, µ 0 ), t(µ, µ 0 ) and s for all wavelengths used. Then the surface albedo A s in equation (2) can be found from A s = (R 0 ) λ0 T λ0 + s λ 0 (Rλ meas 0 (R 0 ) λ0 ). (6) R meas λ 0 Note that this equation allows negative surface albedos, which occurs for highly absorbing (aerosol) layers. Sensitivity of the residue To find the sensitivity of the residue on the measured reflectances, the residue is expressed as a function of these reflectances. To do this, the expression for A s in (6) is substituted in (4) to find the Rayleigh reflectance at wavelength λ, R Ray λ, R Ray T λ (Rλ meas λ = (R 0 ) λ + 0 (R 0 ) λ0 ) T λ0 + (s λ 0 s λ )(Rmeas λ 0 (R 0 ) λ0 ). (7) This can be substituted in Equation (3) to get ( ) R meas r λ = λ log, (8) (R 0 ) λ + c a where c a = T λ ( (s λ 0 s λ ) + T λ0 R meas (R 0 ) λ0 λ 0 ) 1 (9) is the contribution of the corrected surface albedo. Equation (8) shows that the residue increases when λ becomes smaller: due to the strong inverse dependence of the reflectance on wavelength in the UV, where Rayleigh scattering is dominant, the reflectance increases when the wavelength decreases. This will increase the residue. Changing the reference wavelength λ 0 can have nonlinear effects, as the sensitivity of the residue on the reflectance at λ 0 is in the denominator of the argument of the logarithm in (8), due to

3 in [12] and D3 is the large mode dust aerosol model as defined by [12], with the updated imaginary part of the refractive index of [13]. The top panel of Fig. 1 shows the dependence of the residue on the aerosol optical thickness τ for Mie aerosol models C2 and D3. The residue is zero for zero optical thickness as expected; a Rayleigh atmosphere produces zero residue by construction. As the aerosol optical thickness increases, Rayleigh scattering is suppressed and more radiation is absorbed. Therefore less radiation will emerge at TOA and the deviation from the clear sky radiation increases, yielding a higher residue. This is the basis for the detection of absorbing aerosols. The figure also shows that the increase is larger for the larger D3 aerosols, compared to the C2 aerosols, because the single scattering albedo of the D3 aerosols is smaller, increasing the residue. This dependence on single scattering albedo has been shown before [2], [7], [12]. The residue increases linearly with aerosol layer altitude (lower panel of Fig. 1). For aerosols with a wavelength Fig. 1. Dependence of the residue on aerosol optical thickness τ (top panel) and height of the aerosol layer z (lower panel), for the carbonaceous smoke model C2 and the large mode dust model D3. the connection via the adjusted surface albedo. These effects are confirmed by numerical simulations [2]. The basic sensitivities of the residue are shown in Fig. 1. These figures were created with radiative transfer model calculations, using the polarised doubling-adding method [9], with a plane-parallel standard Mid-Latitude Summer (MLS) atmosphere [10]. The surface albedo was 0.05, the viewing angle θ was zero and the solar zenith angle θ 0 varied between zero and sixty degrees. An aerosol layer of Henyey-Greenstein (HG) aerosols [11] or Mie aerosols could be introduced in the atmosphere to simulate aerosol effects. The default altitude of the bottom of this one kilometre thick layer was three kilometres (see [2] for details). HG aerosols typically have wavelength-independent ( grey ) refractive indices and can be used to separate the effects of the single scattering albedo and the asymmetry parameter of the aerosols. Mie aerosol phase functions were used to model more realistic aerosols. Two types of aerosols were used, a carbonaceous aerosol model (C2) and a large mode dust aerosol model (D3). C2 is a smoke model with wavelength independent refractive index defined Fig. 2. Residue calculations in an atmosphere with absorbing aerosols (top panel) and scattering aerosols (lower panel). Solar zenith angle θ 0 is 30, viewing zenith angle θ is 0. HG aerosols are present between 3 and 4 km, the optical thickness τ is 2.0, the aerosol single scattering albedo ω 0 is 0.75 for absorbing aerosols and 1.0 for scattering aerosols.

4 this surface albedo (orange solid line) matches the aerosol reflectance curve much better, leading to a smaller absolute residue. The Rayleigh reflectance curve has become much flatter, because the contribution of the surface to the reflectance, which is spectrally flat, has increased. Therefore, in the case of scattering aerosols the spectral dependence of the residue is opposite to the one of absorbing aerosols, yielding a negative value (in the case shown here the residue is 1.2 at 340 nm). On the basis of the above effect, the AAI is defined as the positive part of the residue, thereby filtering clouds and scattering aerosols. Fig. 3. Mean global AAI from SCIAMACHY in July independent refractive index, like the carbonaceous aerosol model C2, the residue disappears near the surface, whereas non-grey absorbing aerosols, like the dust aerosol model D3, can be detected even very close to the surface. The behaviour of the C2 model is similar to that of HG aerosols, which have even negative residues close to the surface (not shown). To illustrate the working of the residue, consider the spectral dependence of the TOA reflectance in a Rayleigh atmosphere with no aerosols present and a surface albedo of 0.05 (blue dashed lines in Fig. 2). The reflectance of an atmosphere with an absorbing aerosol layer between 3 and 4 km is decreased for all wavelengths due to the absorption by the aerosols (light green dashed-dotted line in top panel of Fig. 2). This aerosol atmosphere is approximated by a pure Rayleigh atmosphere with a different, but wavelength independent surface albedo (red solid line in top panel of Fig. 2). Using the measured reflectance value at λ 0 = 380 nm to fix the Rayleigh case, a surface albedo A s of is found. Apparently, according to Fig. 2, a wavelength independent surface albedo does not produce a good approximation for all wavelengths for the absorbing aerosol case. The slope of the absorbing aerosol curve (light green dashed-dotted line) is decreased compared to the slope of the Rayleigh curve (blue dashed line), even if the refractive index of the aerosols is wavelength independent, because suppression of Rayleigh scattering by the absorbing aerosols is stronger with decreasing wavelength, due to the higher Rayleigh optical thickness of the atmosphere at shorter wavelength (τ Ray λ 4 ). The slope of the Rayleigh curve is increased for decreasing surface reflection (red solid line compared to the blue dashed line), because the subtracted contribution of the surface was spectrally flat. This is the essence of the residue method which is a measure of the deviation between the Rayleigh reflectance curve and the aerosol reflectance curve at a wavelength other than 380 nm. (The case shown here yields a residue r of 4.3 at 340 nm.) Now consider a case with scattering aerosols (lower panel of Fig. 2). The reflectance with the aerosol layer added (dark green dashed-dotted line) is now larger than the Rayleigh reflectance (blue dashed line), giving rise to a higher equivalent surface albedo of The Rayleigh reflectance curve for III. USE OF THE AAI The use of the SCIAMACHY AAI was demonstrated in [14] and is illustrated in Figs. 3 and 4. The first shows the mean global SCIAMACHY AAI in July In the boreal summer a lot of desert dust from the Sahara and desert regions in the Middle East can be observed over the north African continent, the Middle East and over the North Atlantic ocean, blown from the continent over the ocean. Fig. 3 shows these regions with high AAI values as a consequence of the occurrence of the mineral aerosols. Another region with high AAI values is the west African coast near Angola. Persistent wildfires cause biomass burning aerosol plumes that can be observed every year in this region. These aerosols also produce high AAIs. Another example of biomass burning aerosols was observed over Alaska and Canada. In Fig. 4 the nine-day average AAI over North America is shown. Airborne levels of smoke and pollution were high over Alaska and western Canada because of intense wildfires that burned for about two months in June and July The smoke and pollution coming out of these fires were spread all across North America and carried eastwards over the Atlantic. The biomass burning aerosol AAI over Alaska and Canada does not show in Fig. 3, because the averaging period of one month is so large that only very Fig. 4. Nine day (26 June 04 July 2004) average of SCIAMACHY AAI over North America.

5 Fig. 5. Spectra of the scenes in Fig. 6. The top panel corresponds to the desert dust and clear sky scenes in the left panel of Fig. 6 and the bottom panel corresponds to the biomass burning aerosols and clear sky scenes in the right panel of Fig. 6. The aerosol scenes spectra are drawn in green, the clear sky scenes in red. The difference between the two is drawn in blue. The axis of the difference, on the right, is shifted by 0.3. The Rayleigh atmosphere reflectances at 340 nm and 380 nm are plotted as purple triangles. persistent and static aerosol sources are noticeable. IV. AEROSOL SPECTRA FROM SCIAMACHY Although the AAI seems equally sensitive to desert dust and biomass burning aerosols, the spectrum of a desert dust scene is quite different from a biomass burning scene. The spectra of typical aerosol scenes were studied with SCIAMACHY. The calibration of SCIAMACHY is still under discussion, several workers have demonstrated that SCIAMACHY underestimates the reflectance on average by about 15% (e.g. [15]). For residue calculations the reflectances at the two residue wavelengths are corrected with at 340 nm and at 380 nm. The spectra shown here were not corrected. In July 2004 desert dust plumes could be observed almost every day over the Sahara region and from there blown over the North Atlantic ocean (Fig. 3). The plumes could be detected with the SCIAMACHY AAI, having high values over both land and ocean. On 25 July 2004 a plume extended from the main land over the ocean, with dust laden pixels in one state and clear sky pixels in the next. These states are drawn in green (with dust) and red (clear sky) in the left panel of Fig. 6. From these states two areas were chosen with almost the same viewing geometry, one where the AAI was highest (green bold rectangle, residue was 3.4) and one where the AAI was low (residue was 0.18), but where there were absolutely no clouds (red bold rectangle). The latter condition

6 Fig. 6. Locations of the selected desert dust (left green rectangle) and clear sky (left red rectangle) scenes on 25 July 2004, and the selected biomass burning aerosols (right green rectangle) and clear sky (right red rectangle) scenes on 9 September was checked with SCIAMACHY Polarisation Measurement Devices (PMD) false-colour images. SCIAMACHY s broadband ( 100 nm) PMDs are high frequency measurements devices, used to correct the reflectances for polarisation effects. With footprint of about km 2, they have an eight times better spacial resolution than the spacial reflectance measurements (60 30 km 2 ). These measurements can be used to produce high spacial resolution true- and false-colour images of scenes for visual cloud detection. In the top panel of Fig. 5 the spectra of both scenes are compared. The green curve is the spectrum of the high AAI scene and the red curve is the spectrum of the clear sky ocean scene. The reflectances of several higher resolution pixels were binned to produce a complete spectrum of one second measurements. The difference between the two spectra is plotted in blue. The red curve is a typical clear sky ocean scene spectrum. In the UV the dominant effect is absorption by ozone, and Rayleigh scattering with a λ 4 wavelength dependence. The ocean is dark at visible and near infrared (IR) wavelengths, and in the IR mainly water vapour absorption bands can be observed. The green curve is the same ocean spectrum, but now attenuated by desert dust aerosols. In the UV the mineral dust aerosols absorb radiation, decreasing the reflectance at TOA. Because Rayleigh scattering increases at lower wavelengths, the aerosol layer absorbs more effectively at lower wavelength, thereby changing the slope of the reflectance spectrum. This is the basis for the detection of desert dust aerosols (see Fig. 2). In Fig. 5 the calculated reflectances in a Rayleigh atmosphere with a modified surface albedo (as used for the calculation of the residue of the high AAI scene) are plotted as purple triangles. At 380 nm the Rayleigh atmosphere reflectance is the same as the measured reflectance, as required, whereas the Rayleigh atmosphere reflectance at 340 nm is higher than that of the measured reflectance. The calculated Rayleigh atmosphere reflectances used for the calculation of the clear sky AAI are not given, but they will be almost the same for the desert dust case, because at the reference wavelength 380 nm all reflectances are almost equal. At 340 nm the Rayleigh atmosphere case is lower than the clear sky reflectance, leading to a negative residue. These cases are similar to the theoretical cases shown in Fig. 2. In the visible and the near IR the net effect of the mineral dust aerosols is not absorbing. The reflectance at TOA in these spectral regions are much higher than that of the clear sky case. This can be seen from the difference; at wavelengths higher than about 400 nm the difference is always positive, between 300 and 400 nm the difference is negative. The situation is quite different when a biomass burning scene is compared to a clear sky ocean scene (lower panel of Fig. 5). In August and September, accumulated smoke and smog are produced from seasonal agricultural burning and charcoal production in southern Africa. At that time of year, a semipermanent area of high atmospheric pressure takes up residence over that part of the continent, and the air re-circulates in a counterclockwise spin around the high. Air does escape from this spin-cycle at times to the west over the Atlantic Ocean, as it did on 9 September 2004 west of Angola. The haze, giving clouds a dirty appearance, can be detected by satellite imagers and SCIAMACHY PMDs. It was also visible as high SCIAMACHY AAIs. Again, a scene (green bold rectangle in right panel of Fig. 6) was selected in the haze where the residue was high (residue was 3.6) and one with almost the same geometry (red bold rectangle) where the residue was low (residue was 1.8) and there were no clouds. The spectra of the scenes are plotted in the lower panel of Fig. 5. Again the red curve is the clear sky ocean spectrum, which is very similar to the red curve in the top panel. The green curve is the spectrum for the biomass burning scene. The situation is entirely different from that of the desert dust scene. The net aerosol effect on the reflectance is never absorbing. In the UV the biomass burning aerosols increase the reflectance as the wavelength increases. Again, the slope of the Rayleigh atmosphere with adjusted surface albedo (shown again at 340 nm and 380 nm as purple rectangles) is less than that of the Fig. 7. Locations of a Sahara desert dust scene on 02 July 2004 (left green rectangle) and a clear sky scene on 09 July 2004 (left red rectangle), and a biomass burning aerosols scene over Brazil on 12 September 2004 (right green rectangle) and a clear sky scene on 15 September 2004 (right red rectangle).

7 Fig. 8. Spectra of the scenes in Fig. 7. The top panel corresponds to the desert dust and clear sky scenes in the left panel of Fig. 7 and the bottom panel corresponds to the biomass burning aerosols and clear sky scenes in the right panel of Fig. 7. The aerosol scenes spectra are drawn in green, the clear sky scenes in red. The difference between the two is drawn in blue. The axis of the difference, on the right, is shifted by 0.3. The Rayleigh atmosphere reflectances at 340 nm and 380 nm are plotted s purple triangles. aerosol scene, yielding a positive residue, but that is the only resemblance to the desert dust scene. The difference between the biomass burning scene and the clear sky scene, plotted in blue, is large and positive at all wavelengths greater than 300 nm. This result is in accordance with [12], who showed a possibility to separate desert dust aerosol models from biomass burning aerosol models, using the AAI and the absolute value of the reflectance at 380 nm. The spectrum of the biomass burning aerosols scene is similar to that of cloudy scenes (not shown), with a more or less wavelength independent reflectance in the region 340 nm to about 600 nm. But the absolute value of the reflectance of a cloudy scene in this wavelength region is much higher than that of the biomass burning aerosols scene. Therefore, the surface albedo adjusted Rayleigh reflectance for a cloudy scene has a spectral slope which resembles the cloudy scene reflectance better than the biomass burning aerosol scene, because the added surface reflectivity is higher and wavelength independent. The spectra of desert dust scenes and biomass burning aerosols scenes was investigated further with different underlying surfaces, the Sahara desert for desert dust scenes and the tropical forest of Brazil for biomass burning aerosols scenes (Figs. 7 and 8). In the UV the behaviour was similar to that in Fig. 5. Over

8 the Sahara desert the difference between the aerosol scene and the clear sky scene disappears around 500 nm. Over the tropical forest the clear sky scene is comparable to the ocean scene up to about 700 nm, and so is the effect of the aerosols. From about 700 nm the reflectance at TOA is almost entirely determined by the surface reflectivity for both cases. However, over the Sahara desert the desert dust aerosols are net absorbing at higher wavelengths, lowering the reflectance, whereas biomass burning aerosols are net scattering at higher wavelengths, as they are over oceans. V. CONCLUSIONS The AAI is a very useful method to detect UV-absorbing aerosol events over both land and oceans. It has been used in the past to study heavy dust and biomass burning events and investigate aerosol impact on climate. Its great advantage is that it uses wavelengths in the UV, which makes it equally suitable for application over land and ocean surfaces. The unique capability SCIAMACHY to measure the spectrum from 240 nm to about 2400 nm, can be exploited to study the possibilities to distinguish between aerosol types using measured reflectances, instead of using climatologies and geographical selection criteria. The spectra of desert dust and biomass burning aerosols scenes show distinct differences when scenes over oceans are compared. Over land surfaces the pictures is more ambiguous, because of the marked influence of the surface at higher wavelengths. The differences of the spectra can be used to improve future aerosol retrieval algorithms. REFERENCES [1] IPCC, Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge Univ. Press, Cambridge, p. 295, [2] M. De Graaf, P. Stammes, O. Torres, and R. B. A. Koelemeijer, Absorbing Aerosol Index: Sensitivity Analysis, application to GOME and comparison with TOMS, J. Geophys. Res., vol. 110, no. D01201, doi: /2004jd005178, [3] N. C. Hsu, J. R. Herman, J. F. Gleason, O. Torres, and C. J. Seftor, Satellite Detection of Smoke Aerosols Over A Snow/Ice Surface By TOMS, Geoph. Res. Lett., vol. 26, no. 8, pp , [4] O. Torres, P. K. Bhartia, J. R. Herman, A. Sinyuk, P. Ginoux, and B. Holben, A long-term record of aerosol optical depth from TOMS observations and comparison to AERONET measurements, JAS, vol. 59, no. 3, pp , [5] O. Torres, P. K. Bhartian, A. Sinyuk, and E. Welton, Total ozone mapping spectrometer measurements of aerosol absorption from space: Comparison to safari 2000 ground-based observations, J. Geophys. Res., vol. 110, no. D10S18, doi: /2004jd004611, [6] H. Bovensmann, J. P. Burrows, M. Buchwitz, J. Frerick, S. Noël, V. V. Rozanov, K. V. Chance, and A. P. H. Goede, SCIAMACHY: Mission Objectives and Measurement Modes, J. Atmos. Sci., vol. 56, no. 2, pp , [7] J. R. Herman, P. K. Bhartia, O. Torres, C. Hsu, C. Seftor, and E. A. Celarier, Global distributions of UV-absorbing aerosols from NIM- BUS 7/TOMS data, J. Geophys. Res., vol. 102, no. D14, pp. 16,911 16,922, [8] S. Chandrasekhar, Radiative Transfer. Dover, Mineola, N.Y., [9] J. F. De Haan, P. B. Bosma, and J. W. Hovenier, The adding method for multiple scattering calculations of polarized light, Astron. Astrophys., vol. 183, pp , [10] G. P. Anderson, S. A. Clough, F. X. Kneizys, J. H. Chetwynd, and E. P. Shettle, AFGL atmospheric constituent profiles, Air Force Geophysics Laboratory, Tech. Rep. AFGL-TR , [11] L. G. Henyey and J. L. Greenstein, Diffuse radiation in the galaxy, Astrophys. J., vol. 93, pp , [12] O. Torres, P. K. Bhartia, J. R. Herman, Z. Ahmad, and J. Gleason, Derivation of aerosol properties from satellite measurements of backscattered ultraviolet radiation: Theoretical basis, J. Geophys. Res., vol. 103, no. D14, pp. 17,099 17,110, [13] A. Sinyuk, O. Torres, and O. Dubovik, Combined use of satellite and surface observations to infer the imaginary part of the refractive index of Saharan dust, Geoph. Res. Lett., vol. 30, no. D2, [14] M. De Graaf and P. Stammes, SCIAMACHY Absorbing Aerosol Index. Calibration issues and global results from , Atmos. Chem. Phys. Disc. submitted, [15] J. R. Acarreta and P. Stammes, Calibration Comparison Between SCIAMACHY and MERIS Onboard ENVISAT, IEEE Geoscience and Remote Sensing Letters, vol. 2, no. 1, pp , 2005.