Potential improvements of aerosols algorithms for future climate-oriented satellites such as the coming Global Change Observation Mission Climate/Second generation Global Imager (GCOM-C/SGLI) are discussed based on a validation study of three years’ (2008–2010) daily aerosols properties, that is, the aerosol optical thickness (AOT) and the ？ngstr？m exponent (AE) retrieved from two MODIS algorithms. The ground-truth data used for this validation study are aerosols measurements from 3 SKYNET ground sites. The results obtained show a good agreement between the ground-truth data AOT and that of one of the satellites’ algorithms, then a systematic overestimation (around 0.2) by the other satellites’ algorithm. The examination of the AE shows a clear underestimation (by around 0.2–0.3) by both satellites’ algorithms. The uncertainties explaining these ground-satellites’ algorithms discrepancies are examined: the cloud contamination affects differently the aerosols properties (AOT and AE) of both satellites’ algorithms due to the retrieval scale differences between these algorithms. The deviation of the real part of the refractive index values assumed by the satellites’ algorithms from that of the ground tends to decrease the accuracy of the AOT of both satellites’ algorithms. The asymmetry factor (AF) of the ground tends to increase the AE ground-satellites discrepancies as well. 1. Introduction The determination of the optical properties of aerosols and their size distribution around the globe has been a significant contemporary research effort of late [1]. Some of the major factors that have enabled this progress are the better spectral and spatial capacities of satellites and ground-based radiometers, the improvement of the aerosol signal filtering methods, the better knowledge of the aerosols particles’ shapes, and so forth. The qualitative and quantitative importance of the data collected through the continuous monitoring of aerosols and their daily global coverage, by various satellites, has permitted a better characterization of the role of the aerosols in the climate dynamics and the understanding of their temporal and local variation. The most common aerosols optical and physical properties used for this characterization are the AOT, the AE, the particle size distribution, the single scattering albedo (SSA), the aerosol phase function, the asymmetry factor (AF), the refractive index (RI), and so forth. To obtain these aerosols characteristics from satellites’ observations, a detailed model of the aerosols properties is required [2]. The increasing
References
[1]
K. N. Liou, An Introduction to Atmospheric Radiation, Academic Press, 2nd edition, 2002.
[2]
G. A. d'Almeida, P. Koepke, and E. P. Shettle, Atmospheric Aerosols, Global Climatology and Radiative Characteristics, Deepak, Hampton, Va, USA, 1991.
[3]
L. A. Remer, D. Tanré, Y. J. Kaufman et al., “Validation of MODIS aerosol retrieval over ocean,” Geophysical Research Letters, vol. 29, no. 12, pp. MOD3-1–MOD3-4, 2002.
[4]
D. A. Chu, Y. J. Kaufman, C. Ichoku, L. A. Remer, D. Tanré, and B. N. Holben, “Validation of MODIS aerosol optical depth retrieval over land,” Geophysical Research Letters, vol. 29, no. 12, pp. MOD2-1–MOD2-4, 2002.
[5]
C. Ichoku, D. Allen Chu, S. Mattoo et al., “A spatio-temporal approach for global validation and analysis of MODIS aerosol products,” Geophysical Research Letters, vol. 29, no. 12, pp. 1–4, 2002.
[6]
A. Ignatov, L. Stowe, R. Singh, S. Sakerin, D. Kabanov, and I. Dergileva, “Validation of NOAA/AVHRR aerosol retrievals using sun-photometer measurements from R/V akademik vernadsky in 1991,” Advances in Space Research, vol. 16, no. 10, pp. 95–98, 1995.
[7]
M. Riffler, C. Popp, A. Hauser, F. Fontana, and S. Wunderle, “Validation of a modified AVHRR aerosol optical depth retrieval algorithm over Central Europe,” Atmospheric Measurement Techniques, vol. 3, no. 5, pp. 1255–1270, 2010.
[8]
P. Goloub, D. Tanré, J. L. Deuze, M. Herman, A. Marchand, and F. Breon, “Validation of the first algorithm applied for deriving the aerosol properties over the ocean using the POLDER/ADEOS measurements,” IEEE Transactions on Geoscience and Remote Sensing, vol. 37, no. 3, pp. 1586–1596, 1999.
[9]
L. A. Remer, Y. J. Kaufman, D. Tanré et al., “The MODIS aerosol algorithm, products, and validation,” Journal of the Atmospheric Sciences, vol. 62, no. 4, pp. 947–973, 2005.
[10]
A. K. Heidinger, V. R. Anne, and C. Dean, “Using MODIS to estimate cloud contamination of the AVHRR data record,” Journal of Atmospheric and Oceanic Technology, vol. 19, no. 5, pp. 586–601, 2002.
[11]
M. Jin and R. E. Treadon, “Correcting the orbit drift effect on AVHRR land surface skin temperature measurements,” International Journal of Remote Sensing, vol. 24, no. 22, pp. 4543–4558, 2003.
[12]
J. R. Dim, H. Murakami, T. Y. Nakajima, B. Nordell, A. K. Heidinger, and T. Takamura, “The recent state of the climate: driving components of cloud-type variability,” Journal of Geophysical Research D, vol. 116, no. 11, Article ID D11117, 2011.
[13]
T. Takemura, T. Nakajima, A. Higurashi, S. Ohta, and N. Sugimoto, “Aerosol distributions and radiative forcing over the Asian Pacific region simulated by Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS),” Journal of Geophysical Research D, vol. 108, no. 23, pp. 27–10, 2003.
[14]
B. C. Bush and F. P. J. Valero, “Surface aerosol radiative forcing at Gosan during the ACE-Asia campaign,” Journal of Geophysical Research, vol. 108, no. D23, p. 8660, 2003.
[15]
B. J. Huebert, T. Bates, P. B. Russell et al., “An overview of ACE Asia: strategies for quantifying the relationships between Asian aerosols and their climatic impacts,” Journal of Geophysical Research, vol. 108, no. D23, p. 8633, 2003.
[16]
I. Uno, “Regional chemical weather forecasting system CFORS: model descriptions and analysis of surface observations at Japanese island stations during the ACE-ASIA experiment,” Journal of Geophysical Research: Atmospheres, vol. 108, no. D23, 2003.
[17]
T. Nakajima, S. Yoon, V. Ramanathan et al., “Overview of the Atmospheric Brown Cloud East Asian Regional Experiment 2005 and a study of the aerosol direct radiative forcing in east Asia,” Journal of Geophysical Research D, vol. 112, no. 24, Article ID D24S91, 2007.
[18]
T. Takamura, N. Sugimoto, A. Shimizu et al., “Aerosol radiative characteristics at Gosan, Korea, during the Atmospheric Brown Cloud East Asian Regional Experiment 2005,” Journal of Geophysical Research D: Atmospheres, vol. 112, no. 22, Article ID D22S36, 2007.
[19]
I. Sano, S. Mukai, M. Yamano, T. Takamura, T. Nakajima, and B. Holben, “Calibration and validation of retrieved aerosol properties based on aeronet and skynet,” Advances in Space Research, vol. 32, no. 11, pp. 2159–2164, 2003.
[20]
T. Nakajima, G. Tonna, R. Rao, P. Boi, Y. Kaufman, and B. Holben, “Use of sky brightness measurements from ground for remote sensing of particulate polydispersions,” Applied Optics, vol. 35, no. 15, pp. 2672–2686, 1996.
[21]
Y. Liu, J. Huang, G. Shi et al., “Aerosol optical properties and radiative effect determined from sky-radiometer over Loess Plateau of Northwest China,” Atmospheric Chemistry and Physics, vol. 11, no. 22, pp. 11455–11463, 2011.
[22]
J. Bi, Y. Liu, J. Huang et al., “Characteristics of dust aerosols derived from sky-radiometer over Loess Plateau of Northwest China,” in Proceedings of the 16th CEReS International Symposium on Climate Change Studies through Activities of SKYNET and Virtual Laboratory for Climate Diagnostics, Nago, Okinawa, Japan, October 2010.
[23]
T. Nakajima and A. Higurashi, “A use of two-channel radiances for an aerosol characterization from space,” Geophysical Research Letters, vol. 25, no. 20, pp. 3815–3818, 1998.
[24]
A. Higurashi and T. Nakajima, “Detection of aerosol types over the East China Sea near Japan from four-channel satellite data,” Geophysical Research Letters, vol. 29, no. 17, pp. 17–1, 2002.
[25]
C. Ichoku, Y. J. Kaufman, L. A. Remer, and R. Levy, “Global aerosol remote sensing from MODIS,” Advances in Space Research, vol. 34, no. 4, pp. 820–827, 2004.
[26]
W. A. Abdou, D. J. Diner, J. V. Martonchik et al., “Comparison of coincident Multiangle Imaging Spectroradiometer and Moderate Resolution Imaging Spectroradiometer aerosol optical depths over land and ocean scenes containing Aerosol Robotic Network sites,” Journal of Geophysical Research D, vol. 110, no. 10, pp. 1–12, 2005.
[27]
O. V. Kalashnikova and R. A. Kahn, “Mineral dust plume evolution over the Atlantic from MISR and MODIS aerosol retrievals,” Journal of Geophysical Research D, vol. 113, no. 24, Article ID D24204, 2008.
[28]
A. Higurashi and T. Nakajima, “Development of a two-channel aerosol retrieval algorithm on a global scale using NOAA AVHRR,” Journal of the Atmospheric Sciences, vol. 56, no. 7, pp. 924–941, 1999.
[29]
A. Higurashi, T. Nakajima, B. N. Holben, A. Smirnov, R. Frouin, and B. Chatenet, “A study of global aerosol optical climatology with two-channel AVHRR remote sensing,” Journal of Climate, vol. 13, no. 12, pp. 2011–2027, 2000.
[30]
Y. J. Kaufman and D. Tanré, “Algorithm for remote sensing of tropospheric aerosol from MODIS. Products: MOD04, MOD08. ATBD reference number: ATBD-MOD-02,” 1998, http://modis.gsfc.nasa.gov/data/atbd/atbd_mod02.pdf.
[31]
F. Wagner and A. M. Silva, “Some considerations about ？ngstr？m exponent distributions,” Atmospheric Chemistry and Physics, vol. 8, no. 3, pp. 481–489, 2008.
[32]
T. W. Ault, K. P. Czajkowski, T. Benko et al., “Validation of the MODIS snow product and cloud mask using student and NWS cooperative station observations in the Lower Great Lakes Region,” Remote Sensing of Environment, vol. 105, no. 4, pp. 341–353, 2006.
[33]
S. A. Ackerman, R. E. Holz, R. Frey, E. W. Eloranta, B. C. Maddux, and M. McGill, “Cloud detection with MODIS. Part II: validation,” Journal of Atmospheric and Oceanic Technology, vol. 25, no. 7, pp. 1073–1086, 2008.
[34]
R. Santer and D. Ramon, MERIS Aerosol Remote Sensing over Land ATBD, 2011.
[35]
J. N. Porter and A. D. Clarke, “Aerosol size distribution models based on in situ measurements,” Journal of Geophysical Research D, vol. 102, no. 5, pp. 6035–6045, 1997.
[36]
A. A. Kokhanovsky, J. L. Deuzé, D. J. Diner, et al., “The inter-comparison of major satellite aerosol retrieval algorithms using simulated intensity and polarization characteristics of reflected light,” Atmospheric Measurement Techniques, vol. 3, pp. 909–932, 2010.
[37]
L. Alados-Arboledas, H. Lyamani, and F. J. Olmo, “Aerosol size properties at Armilla, Granada (Spain),” Quarterly Journal of the Royal Meteorological Society, vol. 129, no. 590, pp. 1395–1413, 2003.
[38]
L. A. Remer, D. Tanré, and Y. J. Kaufman, “Algorithm for remote sensing of tropospheric aerosols from MODIS,” collection 5, 87 pp, 1998.
[39]
R. C. Levy, L. A. Remer, D. Tanré et al., “Evaluation of the MODIS retrievals of dust aerosol over the ocean during PRIDE,” J. Geophys. Res, vol. 108, no. D19, 2003.
[40]
J. B. Pollack and J. N. Cuzzi, “Scattering by nonspherical particles of size comparable to a wavelength: a new semi-empirical theory and its application to tropospheric aerosols,” Journal of the Atmospheric Sciences, vol. 37, pp. 868–881, 1980.
[41]
R. C. Levy, L. A. Remer, D. Tanré, S. Mattoo, and Y. J. Kaufman, “Algorithm for remote sensing of tropospheric aerosols over dark targets from MODIS,” Collections 005 and 051: Revision 2, Feb 2009, Product ID: MOD04/MYD04, 96 pp, 2009.
[42]
R. C. Levy, L. A. Remer, R. G. Kleidman et al., “Global evaluation of the Collection 5 MODIS dark-target aerosol products over land,” Atmospheric Chemistry and Physics, vol. 10, no. 21, pp. 10399–10420, 2010.
