AMT Atmospheric Measurement Techniques AMT Atmos. Meas. Tech. 1867-8548 Copernicus Publications Göttingen, Germany 10.5194/amt-7-2839-2014 Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms Hamann U. https://orcid.org/0000-0001-8091-722X 1 2 Walther A. 3 Baum B. https://orcid.org/0000-0002-7193-2767 3 Bennartz R. https://orcid.org/0000-0001-7133-9659 3 4 Bugliaro L. https://orcid.org/0000-0003-4793-0101 5 Derrien M. 6 Francis P. N. https://orcid.org/0000-0002-5869-803X 7 Heidinger A. 8 Joro S. 9 Kniffka A. 10 Le Gléau H. 6 Lockhoff M. 10 Lutz H.-J. 9 Meirink J. F. 1 Minnis P. https://orcid.org/0000-0002-4733-6148 11 Palikonda R. 12 Roebeling R. 9 Thoss A. 14 Platnick S. https://orcid.org/0000-0003-3964-3567 13 Watts P. 9 Wind G. https://orcid.org/0000-0002-1001-3724 13 Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands MeteoSwiss, Locarno, Switzerland University of Wisconsin, Madison, WI, USA Vanderbilt University, Nashville, TN, USA Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany Météo-France, Lannion, France Met Office, Exeter, UK Center for Satellite Applications and Research, NESDIS, NOAA, Madison, WI, USA EUMETSAT, Darmstadt, Germany Deutscher Wetterdienst (DWD), Offenbach, Germany NASA Langley Research Center, Hampton, VA, USA Science Systems and Applications, Inc., Hampton, VA, USA NASA Goddard Space Flight Center, Greenbelt, MD, USA Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, Sweden 09 09 2014 7 9 2839 2867 Copyright: © 2014 U. Hamann et al. 2014 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://amt.copernicus.org/articles/7/2839/2014/amt-7-2839-2014.html The full text article is available as a PDF file from https://amt.copernicus.org/articles/7/2839/2014/amt-7-2839-2014.pdf

The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) – a crucial parameter to estimate the thermal cloud radiative forcing – can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. <br><br> In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer to the CPR measurements than to CALIOP measurements. The biases between SEVIRI and CPR retrievals range from −0.8 km to 0.6 km. The correlation coefficients of CPR and SEVIRI observations vary between 0.82 and 0.89. To discuss the origin of the CTH deviation, we investigate three cloud categories: optically thin and thick single layer as well as multi-layer clouds. For optically thick clouds the correlation coefficients between the SEVIRI and the reference data sets are usually above 0.95. For optically thin single layer clouds the correlation coefficients are still above 0.92. For this cloud category the SEVIRI algorithms yield CTHs that are lower than CALIOP and similar to CPR observations. Most challenging are the multi-layer clouds, where the correlation coefficients are for most algorithms between 0.6 and 0.8. Finally, we evaluate the performance of the SEVIRI retrievals for boundary layer clouds. While the CTH retrieval for this cloud type is relatively accurate, there are still considerable differences between the algorithms. These are related to the uncertainties and limited vertical resolution of the assumed temperature profiles in combination with the presence of temperature inversions, which lead to ambiguities in the CTH retrieval. Alternative approaches for the CTH retrieval of low clouds are discussed.

 References Avery, M., Winker, D., Heymsfield, A., Vaughan, M., Young, S., Hu, Y., and Trepte, C.: Cloud ice water content retrieved from the CALIOP space-based lidar, Geophys. Res. Lett., 39, L05808, <a href="http://dx.doi.org/10.1029/2011GL050545">https://doi.org/10.1029/2011GL050545</a>, 2012. Baum, B. A. and Wielicki, B. A.: Cirrus cloud retrieval using infrared sounding data: Multilevel cloud errors, J. Appl. Meteorol., 33, 107–117, 1994. Baum, B., Heymsfield, A., Yang, P., and Bedka, S.: Bulk scattering models for the remote sensing of ice clouds. Part 1: Microphysical data and models, J. Appl. Meteorol., 44, 1885–1895, 2005. Baum, B., Yang, P., Heymsfield, A., Platnick, S., King, M., Hu, Y.-X., and Bedka, S.: Bulk scattering models for the remote sensing of ice clouds. Part 2: Narrowband models, J. Appl. Meteorol., 44, 1896–1911, 2005. Baum, B., Yang, P., Nasiri, S., Heidinger, A., Heymsfield, A., and Li, J.: Bulk scattering properties for the remote sensing of ice clouds. Part 3: High resolution spectral models from 100 to 3250 <abbr>cm-1</abbr>, J. Appl. Meteorol., 46, 423–434, 2007. Baum, B. A., Menzel, W. P., Frey, R. A., Tobin, D. C., Holz, R. E., Ackerman, S. A., Heidinger, A. K., and Yang, P.: MODIS cloud-top property refinements for Collection 6, J. Appl. Meteorol. Clim., 51, 1145–1163, 2012. Banks, J. R. and Brindley, H. E.: Evaluation of MSG-SEVIRI mineral dust retrieval products over North Africa and the Middle East, Remote Sens. Env., 128, 58–73, 2013. Bennartz, R., Fell, F., and Walther, A.: AVAC-S: A-Train Validation of Aerosol and Cloud properties from SEVIRI, EUMETSAT document, 2010. Bodas-Salcedo, A., Webb, M., Bony, S., Chepfer, H., Dufresne, J.-L., Klein, S., Zhang, Y., Marchand, R., Haynes, J., Pincus, R., and John, V. O.: COSP: satellite simulation software for model assessment, B. Am. Meteorol. Soc., 92, 1023–1043, 2011. Boucher, O.: Air traffic may increase cirrus cloudiness, Nature, 397, 30–31, 1999. Breon, F.-M., Vermeulen, A., and Descloitres, J.: An evaluation of satellite aerosol products against sunphotometer measurements, Remote Sens. Environ., 115, 12, 3102–3111, 2011. Brindley, H. E. and Russell, J. E.: Improving GERB scene identification using SEVIRI: infrared dust detection strategy, Remote Sens. Env., 104, 426–446, 2006. Brindley, H., Knippertz, P., Ryder, C., and Ashpole, I.: A critical evaluation of the ability of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) thermal infrared red-green-blue rendering to identify dust events: Theoretical analysis, J. Geophys. Res., 117, D07201, <a href="http://dx.doi.org/10.1029/2011JD017326">https://doi.org/10.1029/2011JD017326</a>, 2012. 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, <a href="http://dx.doi.org/10.5194/acp-11-5603-2011">https://doi.org/10.5194/acp-11-5603-2011</a>, 2011. Cavia, F. and Tomassini, C.: Détermination de la température des cirrus semi-transparents, La Météorologie, 6, 63–67, 1978. Cess, R. D., Potter, G., Blanchet, J., Boer, G., Ghan, S., Kiehl, J., Le Treut, H., Li, Z.-X., Liang, X.-Z., Mitchell, J., Morcrette, J.-J., Randall, D. A., Riches, M. R., Roeckner, E., Schlese, U., Slingo, A., Taylor, K. E., Washington, W. M., Wetherald, R. T., and Yagai, I.: Interpretation of cloud-climate feedback as produced by 14 atmospheric general circulation models, Science, 245, 513–516, 1989. Chahine, M. T.: Remote sounding of cloudy atmospheres, I. The single cloud layer, J. Atmos. Sci., 31, 233–243, 1974. Chang, F.-L. and Li, Z.: A near-global climatology of single-layer and overlapped clouds and their optical properties retrieved from Terra/MODIS data using a new algorithm, J. Climate, 18, 4752–4771, 2005a. Chang, F.-L. and Li, Z.: A new method for detection of cirrus overlapping water clouds and determination of their optical properties, J. Atmos. Sci., 62, 3993–4009, 2005b. Chang, F.-L., Minnis, P., Lin, B., Khaiyer, M. M., Palikonda, R., and Spangenberg, D. A.: A modified method for inferring upper troposphere cloud top height using the GOES 12 imager 10.7 and 13.3 <abbr>\mu</abbr>m data, J. Geophys. Res., 115, D06208, <a href="http://dx.doi.org/10.1029/2009JD012304">https://doi.org/10.1029/2009JD012304</a>, 2010. Cox, C. and Munk, W.: Measurement of the roughness of the sea surface from photographs of the sun's glitter, J. Optical Soc. Am., 44, 838–850, 1954. Cox, C. and Munk, W.: Statistics of the sea surface derived from sun glitter, J. Marine Res., 13, 198–227, 1954. Delanoë, J. and Hogan, R. J.: A variational scheme for retrieving ice cloud properties from combined radar, lidar, and infrared radiometer, J. Geophys. Res.-Atmos., 113, D07204, <a href="http://dx.doi.org/10.1029/2007JD009000">https://doi.org/10.1029/2007JD009000</a>, 2008. Delanoë, J. and Hogan, R. J.: Combined CloudSat-CALIPSO-MODIS retrievals of the properties of ice clouds, J. Geophys. Res.-Atmos., 115, D00H29, <a href="http://dx.doi.org/10.1029/2009JD012346">https://doi.org/10.1029/2009JD012346</a>, 2010. De Pape, B. and Dewitte, S.: Dust aerosol optical depth retrieval over a desert surface using the SEVIRI window channels, J. Atmos. Oceanic. Technol., 26, 704–718, 2008. Derrien, M. and Le Gléau, H.: MSG/SEVIRI cloud mask and type from SAFNWC, Int. J. Remote Sens., 26, 4707–4732, 2005. Derrien, M. and Le Gléau, H.: Improvement of cloud detection near sunrise and sunset by temporal-differencing and region-growing techniques with real-time SEVIRI, Int. J. Remote Sens., 31, 1765–1780, 2010. Derrien, M. and Le Gléau, H.: Algorithm Theoretical Basis Document for "Cloud Products" (CMa-PGE01 v3.2, CT-PGE02 v2.2 & CTTH-PGE03 v2.2), NWC SAF document: SAF/NWC/CDOP/MFL/SCI/ATBD/01, 2013. Dong, X., Minnis, P., Xi, B., Sun-Mack, S., and Chen, Y.: Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site, J. Geophys. Res.-Atmos., 113, D03204, <a href="http://dx.doi.org/10.1029/2007JD008438">https://doi.org/10.1029/2007JD008438</a>, 2008. Ewald, F., Bugliaro, L., Mannstein, H., and Mayer, B.: An improved cirrus detection algorithm MeCiDA2 for SEVIRI and its evaluation with MODIS, Atmos. Meas. Tech., 6, 309–322, <a href="http://dx.doi.org/10.5194/amt-6-309-2013">https://doi.org/10.5194/amt-6-309-2013</a>, 2013. Eyre, J. R. and Menzel, W. P.: Retrieval of cloud parameters from satellite sounder data: A simulation study., J. Appl. Meteorol., 28, 267–275, 1989. Francis, P. N., Hocking, J. A., and Saunders, R. W.: Improved diagnosis of low-level cloud from MSG SEVIRI data for assimilation into Met Office limited area models, Proceedings of the 2008 EUMETSAT Meteorological Satellite Conference, Darmstadt, 2008. Govaerts, Y., Arriaga, A., and Schmetz, J.: Operational vicarious calibration of the MSG/SEVIRI solar channels, Adv. Space Res., 28, 21–30, 2001. Heidinger, A. K. and Pavolonis, M. J.: Gazing at cirrus clouds for 25 years through a split window, Part I: Methodology, J. Appl. Meteorol. Clim., 48, 1100–1116, 2009. Heidinger, A., Pavolonis, M., Holz, R., Baum, B. A., and Berthier, S.: Using CALIPSO to explore the sensitivity to cirrus height in the infrared observations from NPOESS/VIIRS and GOES-R/ABI, J. Geophys. Res.-Atmos., 115, D00H20, <a href="http://dx.doi.org/10.1029/2009JD012152">https://doi.org/10.1029/2009JD012152</a>, 2010. Hewison, T. J. and Müller, J.: Ice Contamination of Meteosat/SEVIRI Implied by Intercalibration Against Metop/IASI, IEEE Trans. Geosci. Remote Sens., 51, 3, 1182–1186, <a href="http://dx.doi.org/10.1109/TGRS.2012.2236335">https://doi.org/10.1109/TGRS.2012.2236335</a>, 2013. Holz, R. E., Ackerman, S., Antonelli, P., Nagle, F., Knuteson, R. O., McGill, M., Hlavka, D. L., and Hart, W. D.: An improvement to the high-spectral-resolution CO<sub>2</sub>-slicing cloud-top altitude retrieval, J. Atmos. Ocean Tech., 23, 653–670, 2006. Holz, R., Ackerman, S., Nagle, F., Frey, R., Dutcher, S., Kuehn, R., Vaughan, M., and Baum, B.: Global Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection and height evaluation using CALIOP, J. Geophys. Res.-Atmos., 113, D00A19, <a href="http://dx.doi.org/10.1029/2008JD009837">https://doi.org/10.1029/2008JD009837</a>, 2008. Hostetler, C., Liu, Z., Reagan, J., Vaughan, M., Winker, D., Osborn, M., Hunt, W., Powell, K., and Trepte, C.: CALIOP Algorithm Theoretical Basis Document – Part 1: Calibration and Level 1 Data Products, Doc. PC-SCI, 201, 2006. Hu, Y. X. and Stamnes, K.: An accurate parameterization of the radiative properties of water clouds suitable for use in climate models, J. Climate, 6, 728–742, 1993. Hurley, J., Dudhia, A., and Grainger, R. G.: Retrieval of macrophysical cloud parameters from MIPAS: algorithm description, Atmos. Meas. Tech., 4, 683–704, <a href="http://dx.doi.org/10.5194/amt-4-683-2011">https://doi.org/10.5194/amt-4-683-2011</a>, 2011. Joiner, J., Vasilkov, A. P., Bhartia, P. K., Wind, G., Platnick, S., and Menzel, W. P.: Detection of multi-layer and vertically-extended clouds using A-train sensors, Atmos. Meas. Tech., 3, 233–247, <a href="http://dx.doi.org/10.5194/amt-3-233-2010">https://doi.org/10.5194/amt-3-233-2010</a>, 2010. Karlsson, K-G., and E. Johansson: On the optimal method for evaluating cloud products from passive satellite imagery using CALIPSO-CALIOP data: example investigating the CM SAF CLARA-A1 dataset, Atmos. Meas. Tech., 6, 1271–1286, <a href="http://dx.doi.org/10.5194/amt-6-1271-2013">https://doi.org/10.5194/amt-6-1271-2013</a>, 2013. King, M. D., Platnick, S., Hubanks, P. A., Arnold, G. T., Moody, E. G., Wind, G., and Wind, B.: Collection 005 change summary for the MODIS cloud optical property (06_OD) algorithm, MODIS Atmosphere, 8 pp., 2006. Li, J., Zhang, P., Schmit, T. J., Schmetz, J., and Menzel, W. P.: Quantitative monitoring of a Saharan dust event with SEVIRI on Meteosat-8, Int. J. Remote Sens., 28, 2181–2186, 2007. Lindstrot, R., Preusker, R., and Fischer, J.: Remote sensing of multilayer cloud-top pressure using combined measurements of MERIS and AATSR on board Envisat, J. Appl. Meteorol. Clim., 49, 1191–1204, 2010. Liou, K.-N.: Influence of cirrus clouds on weather and climate processes: a global perspective, Mon. Weather Rev., 114, 1167–1199, 1986. Liou, K.-N.: An Introduction to Atmospheric Radiation, vol. 84, access online via Elsevier, 2002. Liu, Z., Omar, A., Hu, Y., Vaughan, M., Winker, D., Poole, L., and Kovacs, T.: CALIOP algorithm theoretical basis document, Part 3: Scene classification algorithms, NASA-CNES document PC-SCI-203, 2005. Lutz, H.-J., Wilson, H. K., Heinemann, T., Samain, O., Gustafsson, J., Holmlund, K., and de Smet, A.: MSG Meteorological Products Extraction Facility Algorithm Specification Document, EUMETSAT Document Nr. EUM/MSG/SPE/022, 2011. Masuda, K., Takashima, T., and Takayama, Y.: Emissivity of pure and sea waters for the model sea surface in the infrared window regions, Remote Sens. Environ., 24, 313–329, 1988. Meerkötter, R. and Bugliaro, L.: Diurnal evolution of cloud base heights in convective cloud fields from MSG/SEVIRI data, Atmos. Chem. Phys., 9, 1767–1778, <a href="http://dx.doi.org/10.5194/acp-9-1767-2009">https://doi.org/10.5194/acp-9-1767-2009</a>, 2009. Meirink, J. F., Roebeling, R. A., and Stammes, P.: Inter-calibration of polar imager solar channels using SEVIRI, Atmos. Meas. Tech., 6, 2495–2508, <a href="http://dx.doi.org/10.5194/amt-6-2495-2013">https://doi.org/10.5194/amt-6-2495-2013</a>, 2013. Menzel, W., Smith, W., and Stewart, T.: Improved cloud motion wind vector and altitude assignment using VAS, J. Clim. Appl. Meteorol., 22, 377–384, 1983. Menzel, W. P., Frey, R. A., Zhang, H., Wylie, D. P., Moeller, C. C., Holz, R. E., Maddux, B., Baum, B. A., Strabala, K. I., and Gumley, L. E.: MODIS global cloud-top pressure and amount estimation: algorithm description and results, J. Appl. Meteorol. Clim., 47, 1175–1198, 2008. Meyer, R., Mannstein, H., Meerkötter, R., Schumann, U., and Wendling, P.: Regional radiative forcing by line-shaped contrails derived from satellite data, J. Geophys. Res., 107, ACL-1–ACL-17, <a href="http://dx.doi.org/10.1029/2001JD00426">https://doi.org/10.1029/2001JD00426</a>, 2002. Minnis, P. and Harrison, E. F.: Diurnal variability of regional cloud and clear-sky radiative parameters derived from GOES data, Part II: November 1978 cloud distributions, J. Clim. Appl. Meteorol., 23, 1012–1031, 1984. Minnis, P., Heck, P. W., Young, D. F., Fairall, C., and Snider, J.: Stratocumulus cloud properties derived from simultaneous satellite and island-based instrumentation during FIRE, J. Appl. Meteorol., 31, 317–339, 1992. Minnis, P., Nguyen, L., Doelling, D. R., Young, D. F., Miller, W. F., and Kratz, D. P.: Rapid calibration of operational and research meteorological satellite imagers, Part I: Evaluation of research satellite visible channels as references, J. Atmos. Oceanic Technol., 19, 1233–1249, 2002. Minnis, P., Nguyen, L., Doelling, D. R., Young, D. F., Miller, W. F., and Kratz, D. P.: Rapid calibration of operational and research meteorological satellite imagers, Part II: Comparison of infrared channels, J. Atmos. Oceanic Technol., 19, 1250–1266, 2002. Minnis, P., Huang, J., Lin, B., Yi, Y., Arduini, R. F., Fan, T.-F., Ayers, J. K., and Mace, G. G.: Ice cloud properties in ice-over-water cloud systems using Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and TRMM Microwave Imager data, J. Geophys. Res.-Atmos., 112, D06206, <a href="http://dx.doi.org/10.1029/2006JD007626">https://doi.org/10.1029/2006JD007626</a>, 2007. Minnis, P., Trepte, Q. Z., Sun-Mack, S., Chen, Y., Doelling, D. R., Young, D. F., Spangenberg, D. A., Miller, W. F., Wielicki, B. A., Brown, R. R., Gibson, S. C., and Geier, E. B.: Cloud detection in nonpolar regions for CERES using TRMM VIRS and Terra and Aqua MODIS data, IEEE T. Geosci. Remote, 46, 3857–3884, 2008a. Minnis, P., Yost, C. R., Sun-Mack, S., and Chen, Y.: Estimating the top altitude of optically thick ice clouds from thermal infrared satellite observations using CALIPSO data, Geophys. Res. Lett., 35, L12801, <a href="http://dx.doi.org/10.1029/2008GL033947">https://doi.org/10.1029/2008GL033947</a>, 2008b. Minnis, P., Sun-Mack, S., Trepte, Q. Z., Chang, F.-L., Heck, P. W., Chen, Y., Yi, Y., Arduini, R. F., Ayers, K., Bedka, K., Bedka, S., Brown, R., Gibson, S., Heckert, E., Hong, G., Jin, Z., Palikonda, R., Smith, R., Smith, W. L. J., Spangenberg, D. A., Yang, P., Yost, C. R., and Xie, Y.: CERES Edition 3 Cloud Retrievals, AMS 13th Conf. Atmos. Rad. 2010, Portland, 2010. 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, W. L., Ayers, J. K., Gibson, S. C., Miller, W. F., Chakrapani, V., Takano, Y., Liou, K.-N., Xie, Y., and Yang, P.: CERES edition-2 cloud property retrievals using TRMM VIRS and Terra and Aqua MODIS data, Part I: Algorithms, IEEE T. Geosci. Remote, 49, 4374–4400, 2011. Moseley, S.: Changes to the Nimrod cloud top height diagnosis, Met Office Forecasting Research Technical Report, 424, 2003. Painemal, D., Minnis, P., and O'Neill, L.: The diurnal cycle of boundary layer height and cloud cover over the Southeast Pacific as observed by GOES-10, J. Atmos. Sci., 70, 2393–2408, 2013. Parajuli, S. P., Gherboudj, I., and Ghedira, H: The effect of soil moisture and wind speed on aerosol optical thickness retrieval in a desert environment using SEVIRI thermal channels, Int. J. Remote Sens., 34, 14, 5054–5071, 2013. Pavolonis, M. J. and Heidinger, A. K.: Daytime cloud overlap detection from AVHRR and VIIRS, J. Appl. Meteorol., 43, 762–778, 2004. Platnick, S., King, M. D., Ackerman, S. A., Menzel, W. P., Baum, B. A., Riédi, J. C., and Frey, R. A.: The MODIS cloud products: algorithms and examples from Terra, IEEE T. Geosci. Remote, 41, 459–473, 2003. Poulsen, C. A., Siddans, R., Thomas, G. E., Sayer, A. M., Grainger, R. G., Campmany, E., Dean, S. M., Arnold, C., and Watts, P. D.: Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR, Atmos. Meas. Tech., 5, 1889–1910, <a href="http://dx.doi.org/10.5194/amt-5-1889-2012">https://doi.org/10.5194/amt-5-1889-2012</a>, 2012. Ray, P. S.: Broadband complex refractive indices of ice and water, Applied Optics, 11, 8, 1836–1844; <a href="http://dx.doi.org/10.1364/AO.11.001836">https://doi.org/10.1364/AO.11.001836</a>, 1972. Rodgers, C. D.: Inverse Methods for Atmospheric Sounding: Theory and Practice, Series on Atmospheric, Ocean. Planet. Phys., 2, World Scentic, Singapore, 238 pp., 2000. Roebeling, R.: Cloud Physical Properties Retrieval for Climate Studies using SEVIRI and AVHRR data, Ph.D. thesis, Wageningen University, the Netherlands, 2008. 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.-Atmos., 111, D20210, <a href="http://dx.doi.org/10.1029/2005JD006990">https://doi.org/10.1029/2005JD006990</a>, 2006. Roebeling, R., Baum, B., Bennartz, R., Hamann, U., Heidinger, A., Thoss, A., and Walther, A.: Evaluating and improving cloud parameter retrievals, B. Am. Meteorol. Soc., 94, ES41–ES44, 2012. Romano, F., Ricciardelli, E., Cimini, D., Di Paola, F., and Viggiano, M.: Dust Detection and Optical Depth Retrieval Using MSG SEVIRI Data, Atmosphere, 4, 35–47, <a href="http://dx.doi.org/10.3390/atmos4010035">https://doi.org/10.3390/atmos4010035</a>, 2013. Rossow, W. B. and Schiffer, R. A.: Advances in understanding clouds from ISCCP, B. Am. Meteorol. Soc., 80, 2261–2287, 1999. Rossow, W., Mosher, F., Kinsella, E., Arking, A., Desbois, M., Harrison, E., Minnis, P., Ruprecht, E., Seze, G., Simmer, C., and Smith, E.: ISCCP cloud algorithm intercomparison, J. Clim. Appl. Meteorol., 24, 877–903, 1985. Salisbury, J. W. and D'Aria, D. M.: Emissivity of terrestrial materials in the 8-14 <abbr>\mu</abbr>m atmospheric window, Remote Sens. Environ., 42, 83–106, 1992. Sannazzaroa, F., Filizzolab, C., Marcheseb, F., Corradoa, R., Paciellob, R., Mazzeob, G., Pergolab, N., and Tramutolia, V.: Identification of dust outbreaks on infrared MSG-SEVIRI data by using a Robust Satellite Technique (RST), Acta Astronautica, 93, 64–70, 2014. Saunders, R., Francis, R., Francis, P., Crawford, J., Smith, A., Brown, I., Taylor, R., Forsythe, M., Doutriaux-Boucher, M., and Millington, S.: The exploitation of Meteosat Second Generation Data in the Met Office, Proceedings of the 2006 EUMETSAT Meteorological Satellite Conference, Helsinki, 2006. Schepanski, K., Tegen, I., and Macke, A.: Comparison of satellite based observations of Saharan dust source areas, Remote Sens. Environ., 123, 90–97, 2012. Schmetz, J., Holmlund, K., Hoffman, J., Strauss, B., Mason, B., Gaertner, V., Koch, A., and Van De Berg, L.: Operational cloud-motion winds from Meteosat infrared images, J. Appl. Meteorol., 32, 1206–1225, 1993. Schmetz, J., Pili, P., Tjemkes, S., Just, D., Kerkmann, J., Rota, S., and Ratier, A.: An introduction to Meteosat second generation (MSG), B. Am. Meteorol. Soc., 83, 977–992, 2002. Schumann, U., Mayer, B., Graf, K., and Mannstein, H.: A parametric radiative forcing model for contrail cirrus, J. Appl. Meteorol. Clim., 51, 1391–1406, 2012. Seemann, S. W., Borbas, E. E., Knuteson, R. O., Stephenson, G. R., and Huang, H.-L.: Development of a global infrared land surface emissivity database for application to clear sky sounding retrievals from multispectral satellite radiance measurements, J. Appl. Meteorol. Clim., 47, 108–123, 2008. Sherwood, S. C., Chae, J.-H., Minnis, P., and McGill, M.: Underestimation of deep convective cloud tops by thermal imagery, Geophys. Res. Lett., 31, L11102, <a href="http://dx.doi.org/10.1029/2004GL019699">https://doi.org/10.1029/2004GL019699</a>, 2004. Shettle, E.: Models of aerosols, clouds and precipitation for atmospheric propagation studies, Atmospheric propagation in the UV, visible, IR and <abbr>mm</abbr>-region and related system aspects, no. 454 in AGARD Conference Proceedings, 1989. Smith, W. L. and Frey, R.: On cloud altitude determinations from high resolution interferometer sounder (HIS) observations, J. Appl. Meteorol., 29, 658–664, 1990. Smith, W. and Platt, C.: Comparison of satellite-deduced cloud heights with indications from radiosonde and ground-based laser measurements, J. Appl. Meteorol., 17, 1796–1802, 1978. Smith, W. L. and Frey, R.: On cloud altitude determinations from high resolution interferometer sounder (HIS) observations, J. Appl. Meteorol., 29, 658–662, 1990. Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., Sassen, K., Wang, Z., Illingworth, A. J., O'Connor, E. J., Rossow, W. B., Durden, S. L., Miller, S. D., Austin, R. T., Benedetti, A., Mitrescu, C., and The CloudSat Science Team: The CloudSat mission and the A-Train: a new dimension of space-based observations of clouds and precipitation, B. Am. Meteorol. Soc., 83, 1771–1790, 2002. Stephens, G. L., Vane, D. G., Tanelli, S., Im, E., Durden, S., Rokey, M., Reinke, D., Partain, P., Mace, G. G., Austin, R., L'Ecuyer, T., Haynes, J., Lebsock, M., Suzuki, K., Waliser, D., Wu, D., Kay, J., Gettelman, A., Wang, Z., and Marchand, R.: CloudSat mission: performance and early science after the first year of operation, J. Geophys. Res., 113, D00A18, <a href="http://dx.doi.org/10.1029/2008JD009982">https://doi.org/10.1029/2008JD009982</a>, 2008. Stubenrauch, C., Rossow, W., Kinne, S., Ackerman, S., Cesana, G., Chepfer, H., Di Girolamo, L., Getzewich, B., Guignard, A., Heidinger, A. Maddux, B. C., Menzel, W. P., Minnis, P., Pearl, C., Platnick, S., Poulsen, C., Riedi, J., Sun-Mack, S., Walther, A., Winker, D., Zeng, S., and Zhao, G.: Assessment of global cloud datasets from satellites: project and database initiated by the GEWEX Radiation Panel, B. Am. Meteorol. Soc., 94, 1031–1049, <a href="http://dx.doi.org/10.1175/BAMS-D-12-00117">https://doi.org/10.1175/BAMS-D-12-00117</a>, 2013. Sun-Mack, S., Minnis, P., Chen, Y., Kato, S., Yi, Y., Gibson, S., Heck, P. W., and Winker, D.: Regional Apparent Boundary Layer Lapse Rates Determined from CALIPSO and MODIS Data for Cloud-Height Determination, J. Appl. Meteorol. Clim., 53, 4, 990–1011, 2014. Tanelli, S., Durden, S. L., Im, E., Pak, K. S., Reinke, D. G., Partain, P., Haynes, J. M., and Marchand, R. T.: CloudSat's cloud profiling radar after two years in orbit: performance, calibration, and processing, IEEE T. Geosci. Remote, 46, 3560–3573, 2008. Taylor, K. E.: Summarizing multiple aspects of model performance in a single diagram, J. Geophys. Res.-Atmos., 106, 7183–7192, 2001. Vaughan, M., Winker, D. M., and Powell, K.: CALIOP algorithm theoretical basis document, Part 2: Feature detection and layer properties algorithms, Rep. PC-SCI-202, Release 1.01, 87 pp., 2005. Walther, A. and Heidinger, A. K.: Implementation of the daytime cloud optical and microphysical properties algorithm (DCOMP) in PATMOS-x, J. Appl. Meteorol. Clim., 51, 1371–1390, 2012. Watts, P., Bennartz, R., and Fell, F.: Retrieval of two-layer cloud properties from multispectral observations using optimal estimation, J. Geophys. Res.-Atmos., 116, , D16203, <a href="http://dx.doi.org/10.1029/2011JD015883">https://doi.org/10.1029/2011JD015883</a>, 2011. Wielicki, B. A. and Coakley Jr., J. A.: Cloud retrieval using infrared sounder data: error analysis, J. Appl. Meteorol., 20, 157–169, 1981. Wielicki, B. A., Harrison, E. F., Cess, R. D., King, M. D., and Randall, D. A.: Mission to planet Earth: role of clouds and radiation in climate, B. Am. Meteorol. Soc., 76, 2125–2153, 1995. Wind, G., Platnick, S., King, M. D., Hubanks, P. A., Pavolonis, M. J., Heidinger, A. K., Yang, P., and Baum, B. A.: Multilayer cloud detection with the MODIS near-infrared water vapor absorption band, J. Appl. Meteorol. Clim., 49, 2315–2333, 2010. Winker, D. M., Pelon, J., and McCormick, M. P.: The CALIPSO mission: spaceborne lidar for observation of aerosols and clouds, in: Proc. Spie, vol. 4893, 11 pp., 2003. Winker, D. M., Hunt, W. H., and McGill, M. J.: Initial performance assessment of CALIOP, Geophys. Res. Lett., 34, 19, L19803, <a href="http://dx.doi.org/10.1029/2007GL030135">https://doi.org/10.1029/2007GL030135</a>, 2007. Winker, D., Pelon, J., Coakley Jr, J., Ackerman, S., Charlson, R., Colarco, P., Flamant, P., Fu, Q., Hoff, R., Kittaka, C., Kubar, T. L., Le Treut, H., McCormick, M. P., Megie, G., Poole, L., Powell, K., Trepte, C., Vaughan, M. A., and Wielicki, B. A.: The CALIPSO mission: a global 3-D view of aerosols and clouds, Faculty Research Publications (College of Earth, Ocean, and Atmospheric Sciences), 2010. Wu, D., Hu, Y., McCormick, M. P., Xu, K.-M., Liu, Z., Smith, B., Omar, A. H., and Chang, F.-L.: Deriving marine-boundary-layer lapse rate from collocated CALIPSO, MODIS, and AMSR-E data to study global low-cloud height statistics, IEEE Geosci. Remote Sens. Lett., 5, 649–652, 2008. Wylie, D. P. and Menzel, W.: Two years of cloud cover statistics using VAS, J. Climate, 2, 380–392, 1989. Zhang, H. and Menzel, W. P.: Improvement in thin cirrus retrievals using an emissivity-adjusted CO<sub>2</sub> slicing algorithm, J. Geophys. Res.-Atmos., 107, 4327, <a href="http://dx.doi.org/10.1029/2001JD001037">https://doi.org/10.1029/2001JD001037</a>, 2002. Zinner, T. and Mayer, B.: Remote sensing of stratocumulus clouds: uncertainties and biases due to inhomogeneity, J. Geophys. Res., 111, D14209, <a href="http://dx.doi.org/10.1029/2005JD006955">https://doi.org/10.1029/2005JD006955</a>, 2006.