Vol. 32, issue 08, article # 7

Abstract:

The algorithm for determining cloud optical depth and cloud particle effective radii from MSU-MR daytime measurements on-board the Russian meteorological satellite Meteor-M No. 2 is presented. It is based on the physical principles of using the reflectance at 1.6 and 3.7 mm. The algorithm results are compared with the results of the algorithm developed for the AVHRR radiometer. The comparison shows that the cloud parameters retrieved with the algorithm suggested are within the acceptable limits of accuracy.

Keywords:

MSU-MR, optical depth, effective radius, cloud phase, cloudiness

References:

1. Hansen J.E., Pollack J.B. Near-infrared light scattering by terrestrial clouds // J. Atmos. Sci. Rev. 1970. V. 16. P. 527–610.
2. King M.D. Determination of the scaled optical thickness of clouds from reflected solar radiation measurements // J. Atmos. Sci. 1987. V. 44. P. 1734–1751.
3. Arking A., Childs J.D. Retrieval of cloud cover parameters from multispectral satellite images // J. Clim. Appl. Meteorol. 1985. V. 24. P. 322–333.
4. Nakajima T., King M.D. Determination of the optical-thickness and effective particle radius of clouds from reflected solar-radiation measurements. 1. Theory // J. Atmos. Sci. 1990. V. 47, N 15. P. 1878–1893.
5. Rossow W.B., Schiffer R.A. Advances in understanding clouds from ISCCP // Bull. Am. Meteorol. Soc. 1999. V. 80. P. 2261–2287.
6. Мазин И.П., Хргиан А.Х. Облака и облачная атмосфера. Справочник. Л.: Гидрометиздат, 1989. 647 c.
7. Buras R., Dowling T., Emde C. New secondary-scattering correction in DISORT with increased efficiency for forward scattering // J. Quant. Spectrosc. Radiat. Transfer. 2011. V. 112, N 12. P. 2028–2034.
8. Mayer B., Kylling A., Emde C., Buras R., Hamann U., Gasteiger J., Rnichter B. LibRadtran User’s Guide. 2017. 155 p. [Electronic resource]. URL: http://www.libradtran. org/doc/libRadtran.pdf (last access: 16.04.2019).
9. Baum B.A., Heymsfield A.J., Yang P., Bedka S.T. Bulk scattering models for the remote sensing of ice clouds. Part I: Microphysical data and models // J. Appl. Meteorol. Climatol. 2005. V. 44. P. 1885–1895.
10. Baum B.A., Yang P., Heymsfield A.J., Platnick S., King M.D., Hu Y-X., Bedka S.T. Bulk scattering models for the remote sensing of ice clouds. Part II: Narrowband models // J. Appl. Meteorol. Climatol. 2005. V. 44. P. 1896–1911.
11. Hu Y.X., Stamnes K. An accurate parameterization of the radiative properties of water clouds suitable for use in climate models // J. Climate. 1993. V. 6. P. 728–742.
12. Gasteiger J., Emde C., Mayer B., Buras R., Buehler S.A., Lemke O. Representative wavelengths absorption parameterization applied to satellite channels and spectral bands // J. Quant. Spectrosc. Radiat. Transfer. 2014. V. 148. P. 99–115.
13. Wolter A., Heidinger K. Algorithm Theoretical Basis Document for Daytime Cloud Optical and Microphysical Properties (DCOMP). 2016. 67 p. [Electronic resource]. URL: https://www.star.nesdis.noaa.gov/ jpss/ documents/ATBD/ATBD_EPS_Cloud_DCOMP_v1.1.pdf (last access: 16.04.2019).
14. Wats P.D., Mutlow C.T., Baran A.J., Zavody A.M. Study on Cloud Properties derived from Meteosat Second Generation Observations, EUMETSAT report. Rutherford Appleton Laboratory, 1998. V. 97/181. 344 p.