Vol. 34, issue 10, article # 6

Zhuravleva T. B., Nasrtdinov I. M. Impact of microstructure and horizontal heterogeneity of broken cirrus clouds on mean solar radiation fluxes in the visible spectral region: results of numerical simulation. // Optika Atmosfery i Okeana. 2021. V. 34. No. 10. P. . DOI: 10.15372/AOO20211006 [in Russian].
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The results of statistical simulation of the albedo and diffuse transmission of the atmosphere in the visible region in the presence of overcast and broken cirrus clouds are presented. The main numerical experiments were performed using the third version of the model proposed by a group of authors consisting of B.A. Baum, P. Yang, A.J. Heymsfield et al. (a mixture of particles of different shapes and sizes with a rough surface). To assess the effect of random geometry of clouds on the solar radiation transfer in the atmosphere, G.A. Titov method of closed equations, developed within the framework of a model based on Poisson fluxes of points on straight lines, was used. Analysis of the influence of the microstructure of cirrus clouds on the mean albedo and diffuse transmission at average cloud fraction showed that the average value of the uncertainty due to the lack of information on the particle shape and size is within ~ ± 2%. This value is comparable to the effect of random geometry effects in optically thin clouds, while in optically dense clouds the range of errors caused by ignoring the horizontal heterogeneity increases and is ~ ± 5% in albedo calculations with an underestimation of the diffuse transmission by ~ 10–20%.


cirrus cloud models, Monte Carlo method, effects of random geometry of clouds, Poisson model, solar radiation fluxes in the visible spectral region


  1. Liou K.N. Influence of cirrus clouds on weather and climate processes – A global perspective // Mon. Weather Rev. 1986. V. 114. P. 1167–1199.
  2. Baran A.J. From the single-scattering properties of ice crystals to climate prediction: A way forward // Atmos. Res. 2012. V. 112. P. 45–69.
  3. Zhang M.H., Lin W.Y., Klein S.A., Bacmeister J.T., Bony S., Cederwall R.T., Del Genio A.D., Hack J.J., Loeb N.G., Lohmann U., Minnis P., Musat I., Pincus R., Stier P., Suarez M.J., Webb M.J., Wu J.B., Xie S.C., Yao M.-S., Zhang J.H. Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements // J. Geophys. Res. 2005. V. 110. P. D15S02.
  4. Loeb N.G., Coakley J.A. Inference of marine stratus cloud optical depths from satellite measurements: Does 1D theory apply? // J. Clim. 1998. V. 11, iss. 2. P. 215–233.
  5. Várnai T., Marshak A. Statistical analysis of the uncertainties in cloud optical depth retrievals caused by three-dimensional radiative effects // J. Atmos. Sci. 2001. V. 58, N 12. P. 1540–1548.
  6. Iwabuchi H., Hayasaka T. Effects of cloud horizontal inhomogeneity on the optical thickness retrieved from moderate-resolution satellite data // J. Atmos. Sci. 2002. V. 59, iss. 14. P. 2227–2242.
  7. Zinner T., Mayer B. Remote sensing of stratocumulus clouds: Uncertainties and biases due to inhomogeneity // J. Geophys. Res. 2006. V. 111. P. D14209.
  8. Marshak A., Platnick S., Várnai T., Wen G., Cahalan R.F. Impact of 3D radiative effects on satellite retrievals of cloud droplet sizes // J. Geophys. Res. 2006. V. 111. P. DO9207.
  9. Cornet C., Davies R. Use of MISR measurements to study the radiative transfer of an isolated convective cloud: Implications for cloud optical thickness retrieval // J. Geophys. Res. 2008. V. 113. P. D04202.
  10. Zhou Y., Sun X., Zhang R., Zhang C., Li H., Zhou J., Li S. Influences of cloud heterogeneity on cirrus optical properties retrieved from the visible and near-infrared channels of MODIS/SEVIRI for flat and optically thick cirrus clouds // J. Quant. Spectrosc. Radiat. Transfer. 2017. V. 187. P. 232–246.
  11. Fauchez T., Platnick S., Várnai T., Meyer K., Cornet C., Szczap F. Scale dependence of cirrus heterogeneity effects. Part II: MODIS NIR and SWIR channels // Atmos. Chem. Phys. 2018. V. 18. P. 12105–12121.
  12. Kalesse H. Influence of ice crystal habit and cirrus spatial inhomogeneities on the retrieval of cirrus optical thickness and effective radius: Ph.D. thesis. Mainz, Germany: Johannes Gutenberg University. 2009. P. 65–85.
  13. Chen T., Rossow W.B., Zhang Y. Radiative effects of cloud-type variations // J. Clim. 2000. V. 13, iss. 1. P. 264–286.
  14. Zhang Y., Macke A., Albers F. Effect of crystal size spectrum and crystal shape on stratiform cirrus radiative forcing // Atmos. Res. 1999. V. 52. P. 59–75.
  15. Loeb N.G., Yang P., Rose F.G., Hong G., Sun-Mack S., Minnis P., Kato S., Ham S.-H., Smith W.L.Jr., Hioki S., Tang G. Impact of ice cloud microphysics on satellite cloud retrievals and broadband flux radiative transfer model calculations // J. Clim. 2018. V. 31, iss. 5. P. 1851–1864.
  16. Buschmann N., McFarquhar G.M., Heymsfield A.J. Effects of observed horizontal inhomogeneities within cirrus clouds on solar radiative transfer // J. Geophys. Res. D. 2002. V. 107, N 20. P. 4445.
  17. Carlin B., Fu Q., Lohmann U., Mace G.G., Sassen K., Comstock J.M. High-cloud horizontal inhomogeneity and solar albedo bias // J. Clim. 2002. V. 15, iss. 17. P. 2321–2339.
  18. Schlimme I., Macke A., Reichardt J. The impact of ice crystal shapes, size distributions, and spatial structures of cirrus clouds on solar radiative fluxes // J. Atmos. Sci. 2005. V. 62, N 7. P. 2274–2283.
  19. Szczap F., Gour Y., Fauchez T., Cornet C., Faure T., Jourdan O., Penide G., Dubuisson P. A flexible three-dimensional stratocumulus, cumulus and cirrus cloud generator (3DCLOUD) based on drastically simplified atmospheric equations and the Fourier transform framework // Geosci. Model Dev. 2014. V. 7. P. 1779–1801.
  20. Schäfer M., Bierwirth E., Ehrlich A., Jäkel E., Werner F., Wendisch M. Directional, horizontal inhomogeneities of cloud optical thickness fields retrieved from ground-based and airbornespectral imaging // Atmos. Chem. Phys. 2017. V. 17. P. 2359–2372.
  21. Fauchez T., Platnick S., Meyer K., Cornet C., Szczap F., Várnai T. Scale dependence of cirrus horizontal heterogeneity effects on TOA measurements – Part I: MODIS brightness temperatures in the thermal infrared // Atmos. Chem. Phys. 2017. V. 17. P. 8489–8508.
  22. Zuev V.E., Titov G.A. Optika atmosfery i klimat. Tomsk: Spektr, 1996. 271 p.
  23. Marchuk G.I., Mihajlov G.A., Nazaraliev M.A., Darbinyan R.A., Kargin B.A., Elepov B.S. Metod Monte-Karlo v atmosfernoj optike. Novosibirsk: Nauka, 1976. 280 p.
  24. Zhuravleva T.B. Modelirovanie perenosa solnechnogo izlucheniya v razlichnyh atmosfernyh usloviyah. Part I: Determinirovannaya atmosfera // Optika atmosf. i okeana. 2008. V. 21, N 2. P. 99–114.
  25. Oblaka i oblachnaya atmosfera. Spravochnik / pod red. I.P. Mazina i A.H. Hrgiana. L.: Gidrometeoizdat, 1989. 647 p.
  26. Prigarin S.M., Zhuravleva T.B., Volikova P.V. Puassonovskaya model' mnogoslojnoj razorvannoj oblachnosti // Optika atmosf. i okeana. 2002. V. 15, N 10. P. 917–924.
  27. Hess M., Koepke P., Schult I. Optical properties of aerosols and clouds: The software package OPAC // Bull. Am. Meteorol. Soc. 1998. V. 79. P. 831–844.
  28. Kneizys F.X., Robertson D.S., Abreu L.W., Acharya P., Anderson G.P., Rothman L.S., Chetwynd J.H., Selby J.E.A., Shetle E.P., Gallery W.O., Berk A., Clough S.A., Bernstein L.S. The MODTRAN 2/3 report and LOWTRAN 7 Model. Hanscom, MA: Phillips Laboratory, Geophysics Directorate. Hanscom AFB, MA 01731-3010. 1996. 260 p.
  29. Hook S.J. ASTER Spectral Library: Johns Hopkins University (JHU) spectral library; Jet Propulsion Laboratory (JPL) spectral library; The United States Geological Survey (USGS-Reston) spectral library [Electron resource]. 1998 (CD-ROM).
  30. Mazin I.P., Shmeter S.M. Oblaka, stroenie i fizika obrazovaniya. L.: Gidrometeoizdat, 1983. 279 p.
  31. Baum B.A., Heymsfield A.J., Yang P., Bedka S.T. Bulk scattering models for the remote sensing of ice clouds. Part 1: Microphysical data and models // J. Appl. Meteor. 2005. V. 44, iss. 12. P. 1885–1895.
  32. Heymsfield A.J., Schmitt C., Bansemer A. Ice cloud particle size distributions and pressure dependent terminal velocities from in situ observations at temperatures from 0° to -86 °C // J. Atmos. Sci. 2013. V. 70. P. 4123–4154.
  33. Fridlind A.M., Atlas R., van Diedenhoven B., Um J., McFarquhar G.M., Ackerman A.S., Moyer E.J., Lawso R.P. Derivation of physical and optical properties of mid-latitude cirrus ice crystals for a size-resolved cloud microphysics model // Atmos. Chem. Phys. 2016. V. 16. P. 7251–7283.
  34. Platnick S., Meyer K.G., King M.D., Wind G., Amarasinghe N., Marchant B., Arnold G.T., Zhang Z., Hubanks P.A., Holz R.E., Yang P., Ridgway W.L., Riedi J. The MODIS Cloud optical and microphysical products: collection 6 updates and examples from terra and aqua // IEEE Trans. Geosci. Rem. Sens. 2017. V. 55, N 1. P. 502–525.
  35. Yang P., Hioki S., Saito M., Kuo C.-P., Baum B., Liou K.-N. A Review of ice cloud optical property models for passive satellite remote sensing // Atmosphere. 2018. V. 9, N 12. P. 499.
  36. Minnis P., Sun-Mack S., Young D.F., Heck P.W., Garber D.P., Chen Y., Spangenberg D.A., Arduini R.F., Trepte Q.Z., Smith Jr., Ayers J.K., Gibson S.C., Miller W.F., Hong G., Chakrapani V., Takano Y., Liou K.-N., Xie Y., Yang P. CERES Edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data, Part I: Algorithms // IEEE Trans. Geosci. Remote Sens. 2011. V. 49. P. 4374–4400.
  37. Zhang Z., Yang P., Kattawar G.W., Riedi J., Labonnote C.-L., Baum B.A., Platnick S., Huang H.-L. Influence of ice particle model on satellite ice cloud retrieval: Lessons learned from MODIS and POLDER cloud product comparison // Atmos. Chem. Phys. 2009. V. 9. P. 7115–7129.
  38. Labonnote C.-L., Brogniez G., Buriez J.C., Doutriaux-Boucher M. Polarized light scattering by inhomogeneous hexagonal monocrystals: Validation with ADEOS-POLDER measurements // J. Geophys. Res. 2001. V. 106. P. 12139–12153.
  39. Cole B.H., Yang P., Baum B.A., Riedi J., Labonnote C.-L., Thieuleux F., Platnick S. Comparison of PARASOL observations with polarized reflectances simulated using different ice habit mixtures // J. Appl. Meteorol. Climatol. 2013. V. 52. P. 186–196.
  40. Cole B.H., Yang P., Baum B.A., Riedi J., Labonnote C.-L. Ice particle habit and surface roughness derived from PARASOL polarization measurements // Atmos. Chem. Phys. 2014. V. 14. P. 3739–3750.
  41. Baum B.A., Yang P., Heymsfield A.J., Platnick S., King M.D., Hu Y.-X., Bedka S.T. Bulk scattering properties for the remote sensing of ice clouds. Part II: Narrowband models // J. Appl. Meteorol. 2005. V. 44, iss. 12. P. 1896–1911.
  42. Baum B.A., Yang P., Heymsfield A.J., Bansemer A., Merrelli A., Schmitt C., Wang C. Ice cloud bulk single-scattering property models with the full phase matrix at wavelengths from 0.2 to 100 mm // J. Quant. Spectrosc. Radiant. Transfer. 2014. V. 146. P. 123–139.
  43. Zhuravleva T.B. Vliyanie formy i razmerov kristallicheskih chastits na uglovye raspredeleniya propushchennoj solnechnoj radiatsii v dvuh geometricheskih skhemah zondirovaniya: rezul'taty chislennogo modelirovaniya // Optika atmosf. i okeana. 2020. V. 33, N 10. P. 798–804; Zhuravleva T.B. Effect of shape and sizes of crystal particles on angular distributions of transmitted solar radiation in two sensing geometries: Results of numerical simulation // Atmos. Ocean. Opt. 2021. V. 34, N 1. P. 50–60.
  44. Sassen K., Wang Z., Liu D. Global distribution of cirrus clouds from CloudSat/Cloud-Aerosol lidar and infrared pathfinder satellite observations (CALIPSO) measurements // J. Geophys. Res. D. 2008. V. 113, N 8. P. 347–348.
  45. Macke A., Francis P.N., McFarquhar G.M., Kinne S. The role of ice particle shapes and size distributions in the single scattering properties of cirrus clouds // J. Atmos. Sci. 1998. V. 55, N 17. P. 2874–2883.
  46. Skorinov V.N., Titov G.A. O tochnosti odnogo priblizheniya metoda rascheta luchistyh potokov pri razorvannoj oblachnosti // Izv. AN SSSR. Ser. Fizika atmosf. i okeana. 1984. V. 20, N 3. P. 263–270.