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Kazuyoshi Oouchi and Masaki Satoh

work in developing and maintaining the hierarchy of SCCs. Such an investigation was attempted by Oouchi (1999) , Grabowski and Moncrieff (2001) , and Oouchi and Yamasaki (2001) , and more recently by Tulich and Mapes (2008) . As suggested by these studies, the origin of mesoscale convection, or cloud clusters in broader meaning, is the key to understanding the mechanism of tropical convection. The classification of convective regimes presented in this chapter should be based on more rigorous

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Chih-Pei Chang, Mong-Ming Lu, and Hock Lim

. J. Roy. Meteor. Soc. , 140 , 814–825 , doi: 10.1002/qj.2161 . Qian , J.-H. , A. W. Robertson , and V. Moron , 2010 : Interactions between ENSO, monsoon and diurnal cycle in rainfall variability over Java, Indonesia . J. Atmos. Sci. , 67 , 3509 – 3523 , doi: 10.1175/2010JAS3348.1 . Qian , J.-H. , A. W. Robertson , and V. Moron , 2013 : Diurnal cycle in different weather regimes and rainfall variability over Borneo associated with ENSO . J. Climate , 26 , 1772 – 1790 , doi

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Sally A. McFarlane, James H. Mather, and Eli J. Mlawer

al. (2006) , Evans et al. (2012) , and Mülmenstädt et al. (2012) use objective methodologies to classify the multiple years of observations at the SGP, Darwin, and NSA sites, respectively, into distinct meteorological regimes. At each site, significant differences in cloud properties and the associated surface radiation fields are found between the different categories, indicating the potential utility of the classification for examining how dynamics influence cloud and radiative properties in

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Matthew D. Shupe, Jennifer M. Comstock, David D. Turner, and Gerald G. Mace

. J. Geophys. Res. , 106 , 32 019 – 32 030 , doi: 10.1029/2000JD000055 . Williams , K. D. , and G. Tselioudis , 2007 : GCM intercomparison of global cloud regimes: Present-day evaluation and climate change response . Climate Dyn. , 29 , 231 – 250 , doi: 10.1007/s00382-007-0232-2 . Zhao , C. , and Coauthors , 2012 : Toward understanding of differences in current cloud retrievals of ARM ground-based measurements . J. Geophys. Res. , 117 , D10206 , doi: 10.1029/2011JD016792 . Zhao

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Sue Ellen Haupt, Branko Kosović, Scott W. McIntosh, Fei Chen, Kathleen Miller, Marshall Shepherd, Marcus Williams, and Sheldon Drobot

the world’s population. In turn, as humans change land use for agriculture, the environment is impacted, and we must understand these changes to avoid unintended consequences. This section also continues the theme of Part II of this series ( Haupt et al. 2019b ), which dealt with topics related to growing populations. Section 2 culminates with a discussion of the food–energy–water nexus and its susceptibility to a changing climate. Section 3 discusses our current understanding (and limits to

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John E. Walsh, David H. Bromwich, James. E. Overland, Mark C. Serreze, and Kevin R. Wood

.1088/1748-9326/aa7def Rodionov , S. N. , J. E. Overland , and N. A. Bond , 2005 : The Aleutian low and winter climatic conditions in the Bering Sea. Part I: Classification . J. Climate , 18 , 160 – 177 , . 10.1175/JCLI3253.1 Rusin , N. P. , 1964 : Meteorological and Radiational Regime of Antarctica. Israel Program for Scientific Translations, 355 pp. Scherhag , R. , 1936 : Eine bemerkenswerte Klimaanderung uber Nordeuropa . Ann. Hydrogr. Marit. Meteor

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M. Haeffelin, S. Crewell, A. J. Illingworth, G. Pappalardo, H. Russchenberg, M. Chiriaco, K. Ebell, R. J. Hogan, and F. Madonna

how they affect the performance in terms of cloud properties. In the NWP-Testbed, the performance of NWP models has been assessed in a much wider range of climate regimes and over longer periods compared to the original Cloudnet project. Figure 29-13 shows the time series of the symmetric extreme dependency score (SEDS) that gauges the skill of the various forecast models to predict cloud fraction above 5% in the right place at the right time. As discussed in section 3c , SEDS has the advantage

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W.-K. Tao, Y. N. Takayabu, S. Lang, S. Shige, W. Olson, A. Hou, G. Skofronick-Jackson, X. Jiang, C. Zhang, W. Lau, T. Krishnamurti, D. Waliser, M. Grecu, P. E. Ciesielski, R. H. Johnson, R. Houze, R. Kakar, K. Nakamura, S. Braun, S. Hagos, R. Oki, and A. Bhardwaj

heating profiles derived from TRMM, sounding observations, and global reanalyses, and their results are summarized here. 1) Data Time series of Q 1 estimated from radiosonde observations are available from eight field campaign networks ( Table 2-2 ). All data represent averages over areas of roughly 10 3 –10 5 km 2 in different tropical climate regimes ( Fig. 2-3 ), including open ocean with small or no islands (GATE, TOGA-COARE, KWAJEX, and MISMO), coastal and monsoon regions (SCSMEX, TWP

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Sonia M. Kreidenweis, Markus Petters, and Ulrike Lohmann

et al. 2012 ). The interactions of aerosols in the troposphere and stratosphere with incoming solar radiation had been pointed out early in the twentieth century. Charlson et al. (1992) , building on the estimates of Charlson et al. (1990) , argued that the addition of anthropogenic aerosols to the climate system constituted a significant perturbation—a climate forcing—to the natural system. Their analysis focused on sulfate aerosol, due to anthropogenic emissions that could be shown to

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J. Bühl, S. Alexander, S. Crewell, A. Heymsfield, H. Kalesse, A. Khain, M. Maahn, K. Van Tricht, and M. Wendisch

. In this case, the ice crystals become larger, at the expense of the smaller liquid water droplets. Figure 10-1b shows that the sign of net (solar plus terrestrial) radiative effect of clouds can change from warming to cooling or vice versa depending on the ice water content in the cloud. For low sun elevations [large solar zenith angle (SZA)] such as in the Arctic, the overall effect of mixed-phase clouds seems to be warming. Clouds remain a highly uncertain component of the global climate

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