Larissa Nazarenko, Masato Shiotani, Jason N. S. Cole, Jie Zhang, William G. Read, Luis Millán, Nathaniel J. Livesey, Charles J. Seman, Anthony D. Del Genio, T. Janice Shen, Chengxing Zhai, Jonathan H. Jiang, Tsuyoshi Koshiro, Hui Su, Hideaki Kawai, Knut von Salzen, Masahiro Watanabe, Tongwen Wu, Y. Kasai, Andrew Gettelman, Cyril J. Morcrette, Leo J. Donner, Jean-Louis Dufresne, Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), China Meteorological Administration (CMA), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Atmosphere and Ocean Research Institute [Kashiwa-shi] (AORI), The University of Tokyo (UTokyo), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), National Center for Atmospheric Research [Boulder] (NCAR), National Institute of Information and Communications Technology [Tokyo, Japan] (NICT), Research Institute for Sustainable Humanosphere (RISH), Kyoto University [Kyoto], Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), and Kyoto University more...
Upper-tropospheric ice cloud measurements from the Superconducting Submillimeter Limb Emission Sounder (SMILES) on the International Space Station (ISS) are used to study the diurnal cycle of upper-tropospheric ice cloud in the tropics and midlatitudes (40°S–40°N) and to quantitatively evaluate ice cloud diurnal variability simulated by 10 climate models. Over land, the SMILES-observed diurnal cycle has a maximum around 1800 local solar time (LST), while the model-simulated diurnal cycles have phases differing from the observed cycle by −4 to 12 h. Over ocean, the observations show much smaller diurnal cycle amplitudes than over land with a peak at 1200 LST, while the modeled diurnal cycle phases are widely distributed throughout the 24-h period. Most models show smaller diurnal cycle amplitudes over ocean than over land, which is in agreement with the observations. However, there is a large spread of modeled diurnal cycle amplitudes ranging from 20% to more than 300% of the observed over both land and ocean. Empirical orthogonal function (EOF) analysis on the observed and model-simulated variations of ice clouds finds that the first EOF modes over land from both observation and model simulations explain more than 70% of the ice cloud diurnal variations and they have similar spatial and temporal patterns. Over ocean, the first EOF from observation explains 26.4% of the variance, while the first EOF from most models explains more than 70%. The modeled spatial and temporal patterns of the leading EOFs over ocean show large differences from observations, indicating that the physical mechanisms governing the diurnal cycle of oceanic ice clouds are more complicated and not well simulated by the current climate models. more...