133
Views
19
CrossRef citations to date
0
Altmetric
Original Articles

On the observability of chemical and physical aerosol properties by optical observations: Inverse modelling with variational data assimilation

Pages 747-755 | Received 26 Mar 2009, Accepted 02 Jul 2009, Published online: 18 Jan 2017

References

  • Andersson, C., Langner, J. and Bergstrom, R. 2007. Interannual variation and trends in air pollution over Europe due to climate variability during 1958-2001 simulated with a regional CTM coupled to the ERA40 reanalysis. Tellus 59B, 77–98.
  • Benedetti, A. and Fisher, M. 2007. Background error statistics for aerosols. Q. J. R. MeteoroL Soc. 133, 391–405.
  • Berre, L. 2000. Estimation of synoptic and mesoscale forecast error covariances in a limited-area model. Mon. Wea. Rev. 128, 644–667.
  • Collins, W. D., Rasch, P. J., Eaton, B. E., Khattatov, B. V. and Lamarque, J.F. 2001. Simulating aerosols using a chemical transport model with assimilation of satellite aerosol retrievals: Methodology for INDOEX. J. Geophys. Res. 106, 7313–7336.
  • Constantinescu, E. M., Sandu, A., Chai, T. and Carmichael, G. R. 2007a. Ensemble-based chemical data assimilation. I: General approach. Q. J. Roy. Meteorol. Soc. 133, 1229–1243.
  • Constantinescu, E. M., Sandu, A., Chai, T. and Carmichael, G. R. 2007b. Ensemble-based chemical data assimilation. II: Covariance localiza-tion. Q. J. Roy. MeteoroL Soc. 133, 1245–1256.
  • Dockery, D., Pope, C., XU, X., Spengler, J., Ware, J., et al, 1993. An association between air-pollution and mortality in 6 United-States cities. N. Engl. J. Med. 329(24), 1753–1759.
  • Dusek, U., Frank, G. P., Hildebrandt, L., Curtius, J., Schneider, J., et al, 2006. Size matters more than chemistry for cloud-nucleation ability of aerosol particles. Science 312, 1375–1378.
  • Elbern, H. and Schmidt, H. 1999. A four-dimensional variational chem-istry data assimilation scheme for Eulerian chemistry transport mod-eling. J. Geophys. Res. 104, 18583–18598.
  • Elbern, H. and Schmidt, H. 2001. Ozone episode analysis by four-dimensional variational chemistry data assimilation. J. Geophys. Res. 106, 3569–3590.
  • Elbern, H., Schmidt, H. and Ebel, A. 1997. Variational data assimilation for tropospheric chemistry modeling. J. Geophys. Res. 102, 15967-15 985.
  • Elbern, H., Schmidt, H., Talagrand, O. and Ebel, A. 2000. 4D-variational data assimilation with and adjoint air quality model for emission analysis. Environ. Model. Software 15, 539–548.
  • Elbern, H., Strunk, A., Schmidt, H. and Talagrand, O. 2007. Emission rate and chemical state estimation by 4-dimensional variational inver-sion. Atmos. Chem. Phys. 7, 3749–3769.
  • Eleftheriadis, K., Colbeck, I., Housiadas, C., Lazaridis, M., Mihalopou-los, N., et al, 2006. Size distribution, composition and origin of the submicron aerosol in the marine boundary layer during the eastern mediterranean SUB-AERO experiment. Atmos. Env. 40, 6245–6260.
  • Evensen, G. 2007. Data Assimilation — the Ensemble Kalman Filter Springer, Berlin.
  • Foltescu, V, Pryor, S. C. and Bennet, C. 2005. Sea salt generation, dispersion and removal on the regional scale. Atmos. Environ. 39, 2123–2133.
  • Forster, R, Ramaswamy, V., Artaxo, P.R. Betts, T. B., Fahey, D., et al, 2007. Changes in atmospheric constituents and in radiative forcing. In: Climate Change 2007: The Physical Science Basis, (eds. S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. Averyt, M. Tignor and H. Miller), Contribution of Working Group Ito the Fourth Assessment Report of the Intergovernmetal Panel on Climate Change, Cambridge University Press, Cambridge.
  • Gustafsson, N., Berre, L., Hörnquist, S., Huang, X.-Y., Lindskog, M., et al, 2001. Three-dimensional variational data assimilation for a lim-ited area model part I: General formulation and the background error constraint. Tellus 53A, 425–446.
  • Harrison, R. and Yin, J. 2000. Particulate matter in the atmosphere: which particle properties are important for its effects on health? Sci. Total Environ. 249(1-3), 85–101.
  • Hess, M., Koepke, P. and Schuh, I. 1998. Optical properties of aerosols and clouds: The software package OPAC. Bull. Am. Met. Soc. 79, 831–844.
  • Jacobson, M. Z. 2001. Global direct radiative forcing due to multicom-ponent anthropogenic and natural aerosols. J. Geophys. Res. 106, 1551–1568.
  • Jazwinslci, A. H. 2007. Stochastic Processes and Filtering Theory. Dover, Mineola.
  • Kahnert, F. M. 2004. Reproducing the optical properties of fine desert dust aerosols using ensembles of simple model particles. J. Quant. Spectrosc. Radiat. Transfer 85, 231–249.
  • Kahnert, M. 2008. Variational data analysis of aerosol species in a re-gional CTM: Background error covariance constraint and aerosol op-tical observation operators. Tellus 60B, 753–770.
  • Kahnert, M. and Kylling, A. 2004. Radiance and flux simulations for mineral dust aerosols: Assessing the error due to using spher-ical or spheroidal model particles. J. Geophys. Res. 109, D09203, 10.1029/2003JD004318, errata: doi:10.1029/2004JD005311.
  • Kahnert, M. and Nousiainen, T. 2006. Uncertainties in measured and modelled asymmetry parameters of mineral dust aerosols. J. Quant. Spectrosc. Radiat. Transfer 100, 173–178.
  • Kahnert, M., Nousiainen, T. and Veihelmann, B. 2005. Spherical and spheroidal model particles as an error source in aerosol climate forcing and radiance computations: A case study for feldspar aerosols. J. Geophys. Res. 110. 10.1029/2004JD005558.
  • Kahnert, M., Nousiainen, T. and Räisdnen, P. 2007. Mie simulations as an error source in mineral aerosol radiative forcing calculations. Q. J. R. Met. Soc. 133, 299–307.
  • Lohmann, U. and Lesins, G. 2002. Stronger constraints on the anthro-pogenic indirect aerosol effect. Science 298, 1012–1014.
  • Matta, E., Facchini, M., Decesari, S., Mircea, M., Cavalli, F., et al, 2003. Mass closure on the chemical species in size-segregated atmospheric aerosol collected in an urban area of the Po Valley, Italy. Atmos. Chem. Phys. 3, 623–637.
  • McFiggans, G., Artaxo, P., Baltensperger, U., Coe, H., Facchini, M. C, et al, 2006. The effect of physical and chemical aerosol properties on warm cloud droplet activation. Atmos. Chem. Phys. 6, 2593–2649.
  • Mishchenko, M. I., Cairns, B., Kopp, G., Schueler, C., Fafaul, B. A., et al, 2007. Accurate monitoring of terrestrial aerosols and total solar irradiance: Introducing the Glory mission. Bull. Am. Met. Soc. 88, 677–691.
  • Myhre, G. and Stordal, E 2001. Global sensitivity experiments of the ra-diative forcing due to mineral aerosols. J. Geophys. Res. 106, 18193–18204.
  • Nousiainen, T., Kahnert, M. and Veihelmann, B. 2006. Light scatter-ing modeling of small feldspar aerosol particles using polyhedral prisms and spheroids. J. Quant. Spectrosc. Radiat. Transfer 101, 471–487.
  • Parrish, D. F. and Derber, J. C. 1992. The National Meteorological Centre's spectral statistical interpolation analysis system. Mon. Wea. Rev. 120, 1747–1763.
  • Penner, J. E., Dong, X. and Chen, Y. 2004. Observational evidence of a change in radiative forcing due to the indirect aerosol effect. Nature 427, 231–234.
  • Pope, C. A., Ezzati, M. and Dockery, D. W. 2009. Fine-particulate air pollution and life expectancy in the United States. N. Engl. J. Med. 360(4), 376–386.
  • Robertson, L., Langner, J. and Enghardt, M. 1999. An Eulerian limited-area atmospheric transport model. J. AppL MeteoroL 38, 190–210. Rosenfeld, D. 2006. Aerosols, clouds, and climate. Science 312, 1323–1324.
  • Sandu, A., Liao, W., Henze, D. K., Carmichael G. R. and Seinfeld, J. H. 2005. Inverse modeling of aerosol dynamics using adjoints: Theoretical and numerical considerations. Aerosol Sci. TechnoL 39), 677–694.
  • Schulz, E M., Stamnes, K. and Stamnes, J. J. 1998. Modeling the radia-tive transfer properties of media containing particles of moderately and highly elongated shape. Geophys. Res. Lett. 25, 4481–4484.
  • Schulz, FM., Stamnes, K. and Stamnes, J. J. 1999. Shape-dependence of the optical properties in size-shape distributions of randomly oriented prolate spheroids, including highly elongated shapes. J. Geophys. Res. 104, 9413–9421.
  • Sokolilc, I. N. and Toon, O. B. 1999. Incorporation of mineralogical composition into models of the radiative properties of mineral aerosols from UV to IR wavelengths. J. Geophys. Res. 104, 9423–9444.
  • Stier, R, Seinfeld, J. H., Kinne, S. and Boucher, O. 2007. Aerosol absorption and radiative forcing. Atmos. Chem. Phys. 7, 5237–5261.
  • Veihelmann, B., Nousiainen, T., Kahnert, M. and van der Zande, W. 2006. Light scattering by small feldspar particles simulated using the Gaussian random sphere geometry. J. Quant. Spectrosc. Radiat. Transfer 100(1-3), 393–405.