ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-12-10957-2012 A fast SEVIRI simulator for quantifying retrieval uncertainties in the CM SAF cloud physical property algorithm Jonkheid B. J. 1 Roebeling R. A. 1 2 van Meijgaard E. 1 Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Darmstadt, Germany 20 11 2012 12 22 10957 10969 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys.net/12/10957/2012/acp-12-10957-2012.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/12/10957/2012/acp-12-10957-2012.pdf

The uncertainties in the cloud physical properties derived from satellite observations make it difficult to interpret model evaluation studies. In this paper, the uncertainties in the cloud water path (CWP) retrievals derived with the cloud physical properties retrieval algorithm (CPP) of the climate monitoring satellite application facility (CM SAF) are investigated. To this end, a numerical simulator of MSG-SEVIRI observations has been developed that calculates the reflectances at 0.64 and 1.63 &mu;m for a wide range of cloud parameter values, satellite viewing geometries and surface albedos using a plane-parallel radiative transfer model. The reflectances thus obtained are used as input to CPP, and the retrieved values of CWP are compared to the original input of the simulator. Cloud parameters considered in this paper refer to e.g. sub-pixel broken clouds and the simultaneous occurrence of ice and liquid water clouds within one pixel. These configurations are not represented in the CPP algorithm and as such the associated retrieval uncertainties are potentially substantial. <br><br> It is shown that the CWP retrievals are very sensitive to the assumptions made in the CPP code. The CWP retrieval errors are generally small for unbroken single-layer clouds with COT > 10, with retrieval errors of ~3% for liquid water clouds to ~10% for ice clouds. In a multi-layer cloud, when both liquid water and ice clouds are present in a pixel, the CWP retrieval errors increase dramatically; depending on the cloud, this can lead to uncertainties of 40–80%. CWP retrievals also become more uncertain when the cloud does not cover the entire pixel, leading to errors of ~50% for cloud fractions of 0.75 and even larger errors for smaller cloud fractions. Thus, the satellite retrieval of cloud physical properties of broken clouds as well as multi-layer clouds is complicated by inherent difficulties, and the proper interpretation of such retrievals requires extra care.

 References Ackerman, S., Strabala, K., Menzel, W., Frey, R., Moeller, C., and Gumley, L.: Discriminating clear sky from clouds with MODIS, J. Geophys. Res., 103, 32141–32157, 1998. Anderson, G., Clough, S., Kneizys, F., Chetwynd, J., and Shettle, E.: AFGL atmospheric constituent profiles (0–120 km), Tech. Rep. AFGL-TR-86-0110, Air Force Geophysics Laboratory, 1986. Berk, A., Anderson, G., Acharya, P., Chetwynd, J., Bernstein, L., Shettle, E., Matthew, M., and Adler-Golden, S.: MODTRAN4 Version 2 Users Manual, Tech. Rep., Air Force Research Laboratory, 2000. Bodas-Salcedo, A., Webb, M J., Bony, S., Chepfer, H., Dufresne, J.-L., Klein, S., Zhang, Y., Marchand, R., Haynes, J M., \mboxPincus, R., and John, V O.: COSP: Satellite simulation software for model assessment, B. Am. Meteorol. Soc., 92, 1023–1043, 2011. Bugliaro, L., Zinner, T., Keil, C., Mayer, B., Hollmann, R., Reuter, M., and Thomas, W.: Validation of cloud property retrievals with simulated satellite radiances: a case study for SEVIRI, Atmos. Chem. Phys., 11, 5603–5624, http://dx.doi.org/10.5194/acp-11-5603-2011doi:10.5194/acp-11-5603-2011, 2011. Chandrasekhar, S.: Radiative Transfer, Dover Publications, 1960. Coakley, J., Friedman, M., and Tahnk, W.: Retrieval of cloud properties for partly cloudy imager pixels, J. Atmos. Ocean. Tech., 22, 3–17, 2005. de Bruijn, E. and van Meijgaard, E.: Verification of HIRLAM with ECMWF physics compared with HIRLAM reference versions, HIRLAM Tech. Rep 63, available from SMHI, S-601 76 Norrköping, Sweden, 2005. Donovan, D., Voors, R., van Zadelhoff, G.-J., and Acarreta, J.: ECSIM Models and Algorithms Document, Tech. Rep., 2008. Frey, R., Ackerman, S., Liu, Y., Strabala, K., Zhang, H., Key, J., and Wang, X.: Cloud detection with MODIS. Part I: Improvements in the MODIS Cloud Mask for Collection 5, J. Atmos. Ocean. Tech., 25, 1057–1072, 2008. Greuell, W., van Meijgaard, E., Meirink, J., and Clerbaux, N.: Evaluation of model predicted top-of-atmosphere radiation and cloud parameters over Africa with observations from GERB and SEVIRI, J. Climate, 24, 4015–4036, 2011. Hess, M., Koelemeijer, R., and Stammes, P.: Scattering matrices of imperfect hexagonal crystals, J. Quant. Spectrosc. Ra., 60, 301–308, 1998. Klein, S. and Jakob, C.: Validation and sensitivities of frontal clouds simulated by the ECMWF model, Month. Weather Rev., 127, 2514–2531, 1999. Mayer, B. and Kylling, A.: Technical note: The libRadtran software package for radiative transfer calculations – description and examples of use, Atmos. Chem. Phys., 5, 1855–1877, http://dx.doi.org/10.5194/acp-5-1855-2005doi:10.5194/acp-5-1855-2005, 2005. Meirink, J., Roebeling, R., and van Meijgaard, E.: Atmospheric correction for the KNMI cloud physical properties retrieval algorithm, Tech. Rep. TR-304, KNMI, 2009. Molders, N., Laube, M., and Raschke, E.: Evaluation of model generated cloud cover by means of satellite data, Atmos. Res., 39, 91–111, 1995. Moody, E., King, M., Schaaf, C., and Platnick, S.: MODIS-Derived Spatially Complete Surface Albedo Products: Spatial and Temporal Pixel Distribution and Zonal Averages, J. Appl. Meteor. Climatol., 47, 2879–2894, 2008. Nakajima, T. and King, M.: Determination of the Optical Thickness and Effective Particle Radius of Clouds from Reflected Solar Radiation Measurements. Part 1: Theory, J. Atmos. Sci., 47, 1878–1893, 1990. Pincus, R., McFarlane, S., and Klein, S.: Albedo bias and the horizontal variability of clouds in subtropical marine boundary layers: Observations from ships and satellites, J. Geophys. Res., 104, 6183–6191, 1999. Platnick, S.: Vertical photon transport in cloud remote sensing problems, J. Geophys. Res., 105, 22919–22935, 2000. Platnick, S., King, M., Ackerman, S., Menzel, W., Baum, B., Riedi, J., and Frey, R.: The MODIS cloud products: algorithms and examples from Terra, IEEE T. Geosci. Remote Sens., 41, 459–473, 2003. Räisänen, P., Barker, H., Khairoutdinov, M., Li, J., and Randall, D.: Stochastic generation of subgrid-scale cloudy columns for large-scale models, Q. J. Roy. Meteor. Soc., 130, 2047–2067, 2004. Roebeling, R. and van Meijgaard, E.: Evaluation of the daylight cycle of model predicted cloud amount and condensed water path over Europe with observations from MSG-SEVIRI, J. Climate, 22, 1749–1766, 2009. Roebeling, R., Feijt, A., and Stammes, P.: Cloud property retrievals for climate monitoring: implications of differences between Spinning Enhanced Visible and Infrared Imager (SEVIRI) on METEOSAT-8 and Advanced Very High Resolution Radiometer (AVHRR) on NOAA-17, J. Geophys. Res., 111, D20210, http://dx.doi.org/10.1029/2005JD006990doi:10.1029/2005JD006990, 2006. Roebeling, R., Deneke, H., and Feijt, A.: Validation of cloud liquid water path retrievals from SEVIRI using one year of CLOUDNET observations, J. Appl. Meteor. Climatol., 47, 206–222, 2008. Rossow, W. and Garder, L.: Cloud detection using satellite measurements of infrared and visible radiances from ISCCP, J. Climate, 6, 2341–2369, 1993. Rossow, W. and Schiffer, R.: Advances in understanding clouds from ISCCP, B. Am. Meteorol. Soc., 80, 2261–2287, 1999. Stammes, P.: Spectral radiance modeling in the UV-Visible range, in: IRS 2000: current problems in atmospheric radiation, edited by: Smith, W. and Timofeyev, Y., A. Deepak Publ., Hampton, Va, 385–388, 2001. Tselioudis, G. and Jakob, C.: Evaluation of midlatitude cloud properties in a weather and a climate model: dependence on dynamical regime and spatial resolution, J. Geophys. Res., 107, 4781, http://dx.doi.org/10.1029/2002JD002259doi:10.1029/2002JD002259, 2002. van Meijgaard, E., van Ulft, L., van de Berg, W., Bosveld, F C., van den Hurk, B., Lenderink, G., and Siebesma, A.: The KNMI regional atmospheric climate model RACMO version 2.1, Tech. Rep. TR-302, KNMI, 2008. Várnai, T. and Marshak, A.: View angle dependence of cloud optical thickness retrieved by MODIS, J. Geophys. Res., 112, D06203, http://dx.doi.org/10.1029/2005JD006912doi:10.1029/2005JD006912, 2007. Voors, R., Donovan, D., Acarreta, J., Eisinger, M., Franco, R., Lajas, D., Moyano, R., Pirondini, F., Ramos, J., and Wehr, T.: ECSIM: the simulator framework for EarthCARE, in: Proc. SPIE 6744, 2007. Webb, M., Senior, C., Bony, S., and Morcrette, J.-J.: Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models, Clim. Dynam, 17, 905–922, 2001. Wolters, E., Roebeling, R., and Feijt, A.: Evaluation of cloud-phase retrieval methods for SEVIRI on Meteosat-8 using ground-based lidar and cloud radar data, J. Appl. Meteor. Climatol., 47, 1723–1738, 2008. Wolters, E., Deneke, H., van der Hurk, B., Meirink, J., and Roebeling, R.: Broken and inhomogeneous cloud impact on satellite cloud particle effective radius and cloud-phase retrievals, J. Geophys. Res., 115, D10214, http://dx.doi.org/10.1029/2009JD012205doi:10.1029/2009JD012205, 2010. Zhang, Z. and Platnick, S.: An assessment of differences between cloud effective particle radius retrievals for marine water clouds from three MODIS spectral bands, J. Geophys. Res., 116, D20215, http://dx.doi.org/10.1029/2011JD016216doi:10.1029/2011JD016216, 2011. Zinner, T. and Mayer, B.: Remote sensing of stratocumulus clouds: Uncertainties and biases due to inhomogeneity, J. Geophys. Res., 111, D14209, http://dx.doi.org/10.1029/2005JD006955doi:10.1029/2005JD006955, 2006.