ACPD Atmospheric Chemistry and Physics Discussions ACPD 1680-7375 Copernicus GmbH Göttingen, Germany 10.5194/acpd-9-3367-2009 Cloud-type dependencies of MODIS and AMSR-E liquid water path differences de la Torre Juárez M. 1 Kahn B. H. 1 2 Fetzer E. J. 1 Jet Propulsion Laboratory/California Inst. of Technology, Pasadena, CA 91109–8099, USA Joint Institute for RegionalEarth System Science and Engineering, U.C.L.A., Los Angeles, CA, USA 02 02 2009 9 1 3367 3399 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-discuss.net/9/3367/2009/acpd-9-3367-2009.html The full text article is available as a PDF file from http://www.atmos-chem-phys-discuss.net/9/3367/2009/acpd-9-3367-2009.pdf

Comparisons of cloud liquid water path (LWP) retrievals are presented from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer (AMSR-E) located aboard the Aqua spacecraft. LWP differences as a function of cloud top height, cloud fraction, cloud top temperature, LWP, cloud effective radius and cloud optical thickness are quantified in most geophysical conditions. The assumption of vertically homogeneous distributions of cloud water content in the MODIS LWP retrieval yields a slightly poorer agreement than the assumption of stratified cloud liquid water. Furthermore, for a fixed cloud top pressure, the cloud top temperature can lead to sign changes in the LWP difference. In general, AMSR-E LWP is larger than MODIS for small cloud fractions, low values of LWP, and warmer cloud top temperatures. On the other hand, clouds with optical thicknesses above 20 lead to larger MODIS LWP. Using cloud optical thickness as a proxy for cloud type, deep convective clouds and stratus are shown to have the poorest agreement between AMSR-E and MODIS LWP. Particularly large differences are also found at latitudes poleward of 50°. The results of this work help characterize the scene- and cloud-dependent performance of microwave and visible/near infrared retrievals of LWP.

 References Ackerman,~S A., Strabaja,~K I., Menzel,~W., Frey,~R., Moeller,~C., and Gumley,~L.: Discriminating clear sky from clouds with MODIS,~J. Geophys. Res., 103, 32141–32157, 1998. Bennartz,~R.: Global assessment of marine boundary layer cloud droplet number concentration from satellite,~J. Geophys. Res., 112, D02201, doi:10.1029/2006JD007547, 2007. Boers,~R., Acarreta,~J R., and Gras,~J L.: Satellite monitoring of the first indirect aerosol effect: Retrieval of the droplet concentration of water clouds,~J. Geophys. Res., 111, D22208, doi:10.1029/2005JD006838, 2006. Borg,~L A. and Bennartz,~R.: Vertical structure of stratiform marine boundary layer clouds and its impact on cloud albedo, Geophys. Res. Lett., 34, L05807, doi:10.1029/2006GL028713, 2007. Chang,~F.-L. and Li,~Z.: Retrieving vertical profiles of water-cloud droplet effective radius: Algorithm modification and preliminary application, J. Geophys. Res., 108, 4763–4772, 2003. Chen,~R., Chang,~F.-L., Li,~Z., Ferraro,~R., and Weng,~F.: Impact of the vertical variation of cloud droplet size on the estimation of cloud liquid water path and rain detection,~J. Atmos. Sci., 64, 3843–3853, 2007. Greenwald,~T J., L'Ecuyer,~T S., and Christopher,~S A.: Evaluating specific error characteristics of microwave-derived cloud liquid water products, Geophys. Res. Lett., 34, L22907, doi:10.1029/2007GL031180, 2007. Horváth,~A. and Davies,~R.: Comparison of microwave and optical cloud water path estimates from TMI, MODIS and MISR,~J. Geophys. Res. Atmos., 112, D01201, doi:10.1029/2006JD007101, 2007. Horváth,~A. and Gentemann,~C.: Cloud-fraction-dependent bias in satellite liquid water path retrievals of shallow, non-precipitating marine clouds, Geophys. Res. Lett., 34, L22806, doi:10.1029/2007GL030625, 2007. Huang,~J., Minnis,~P., Lin,~B., Yi,~Y., Fan,~T.-F., Sun-Mack,~S., and Ayers, ~J.: Determination of ice water path in ice-over-water cloud systems using combined MODIS and AMSR-E measurements, Geophys. Res. Lett., 33, L21801, doi:10.1029/2006GL027038, 2006. 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, available at http://modis-atmos.gsfc.nasa.gov/products_C005update.html, 2006. Li,~Z., Chen,~R., and Chang,~F.-L.: The Impact of the Vertical Variation of Cloud Droplet Size on the Estimation of Cloud Liquid Water Path and Its Potential for Rain Detection, in: Sixteenth Arm Science Team Meeting Proceedings, 2006. Lohmann, U. and Feichter, J.: Global indirect aerosol effects: a review, Atmos. Chem. Phys., 5, 715–737, 2005. Lohman,~U., Quaas,~J., Kinne,~S., and Feichter,~J.: Different Approaches for Constraining Global Climate Models of the Anthropogenic Indirect Aerosol Effect, B. Am. Meteorol. Soc., pp. 243–250, 2007. Lohmann,~U. and Lesins,~G.: Comparing continental and oceanic cloud susceptibilities to aerosols, Geophys. Res. Lett., 30, 1791, doi:10.1029/2003GL017828, 2003. Nakajima,~T. and King,~M.: Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. Part I: Theory,~J. Atmos. Sci., 47, 1878–1893, 1990. Nasiri,~S. and Kahn,~B H.: Limitations of bispectral infrared cloud phase determination andpotential for improvement,~J. Appl. Meteor., 47, 2895–2910, doi:10.1175/2008JAMC1879.1, 2008. O'Dell,~C W., Wentz,~F J., and Bennartz,~R.: Cloud liquid water path from satellite-based passive microwave observations: a~new climatology over the global oceans,~J. Climate, 21, 1721–1739, 2008. Platnick,~S., King,~M., Ackerman,~S., Menzel,~W., Baum,~B., Riedl,~C., and Frey,~R.: The MODIS cloud products: algorithms and examples from Terra, IEEE Trans. Geosci. Rem. Sens., Aqua Special Issue, 41, 459–473, 2003. Quaas,~J., Boucher,~O., and Breon,~F.-M.: Aerosol indirect effects in POLDER satellite data and the Laboratoire de Meteorologie Dynamique-Zoom (LMDZ) general circulation model,~J. Geophys. Res., 109, D08205, doi:10.1029/2003JD004, 2004. Rossow,~W B. and Schiffer,~R A.: Advances in understanding clouds from ISCCP, B. Am. Meteorol. Soc., 80, 2261–2287, 1999. Schlosser,~C A. and Houser,~P R.: Assessing a~Satellite-Era Perspective of the Global Water Cycle,~J. Climate, 20, 1316–1338, doi:10.1175/JCLI4057.1, 2007. Stephens,~G L. and Kummerow,~C.: The remote sensing of clouds and precipitation from space: A~review,~J. Atmos. Sci., 64, 3742–3765, 2007. Wentz,~F J.: A~well-calibrated ocean algorithm for special sensor microwave/imager,~J. Geophys. Res., 102, 8703–8718, 1997. Wentz,~F J. and Meissner,~T.: Algorithm Theoretical Basis Document (ATBD). Version 2. AMSR Ocean Algorithm, Tech. Rep. RSS Tech. Proposal 121599 A-1, Remote~Sensing~Systems, 2000.