Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-10T20:39:29.018Z Has data issue: false hasContentIssue false

References

Published online by Cambridge University Press:  18 September 2020

A. Pier Siebesma
Affiliation:
Royal Netherlands Meteorological Institute
Sandrine Bony
Affiliation:
Laboratoire de Meteorologie Dynamique, Paris
Christian Jakob
Affiliation:
Monash University, Victoria
Bjorn Stevens
Affiliation:
Max-Planck-Institut für Meteorologie, Hamburg
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Clouds and Climate
Climate Science's Greatest Challenge
, pp. 389 - 400
Publisher: Cambridge University Press
Print publication year: 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abercromby, R. 1888. Cloud-land in folk-lore and in science. The Folk-Lore Journal, 6(21), https://books.google.com.au/books?id=FwgNAQA.CrossRefGoogle Scholar
Ackerman, A. S., Kirkpatrick, M. P., Stevens, D. E., and Toon, O. B. 2004. The impact of humidity above stratiform clouds on indirect aerosol climate forcing. Nature, 432, 1014–17.Google Scholar
Ackerman, Thomas P., and Stokes, Gerald M. 2003. The atmospheric radiation measurement program. Physics Today, 56(1), 38.Google Scholar
Adams, J. 2010. Vegetation-Climate Interaction, How Plants Make the Global Environment. Springer.Google Scholar
Allan, Richard P., Liu, Chunlei, Zahn, Matthias, et al. 2014. Physically consistent responses of the global atmospheric hydrological cycle in models and observations. Surveys in Geophysics, 35(3), 533–52.Google Scholar
Andrews, Timothy, Gregory, Jonathan M., Webb, Mark J., and Taylor, Karl E. 2012. Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models. Geophysical Research Letters, 39(9), L09712.CrossRefGoogle Scholar
Arakawa, Akio. 1969. Parameterization of cumulus convection. Pages 1–6 of: Proc. WMO/IUGG Symp. Numerical Weather Prediction.Google Scholar
Arakawa, Akio. 2004. The cumulus parameterization problem: past, present, and future. Journal of Climate, 17(13), 2493–525.2.0.CO;2>CrossRefGoogle Scholar
Arakawa, Akio., and Schubert, H. 1974. Interaction of a cumulus cloud ensemble with the large-scale environment. Part I. Theoretical formulation and sensitivity tests. Journal of the Atmospheric Sciences, 31, 674701.Google Scholar
Arakawa, Akio, and Wu, Chien-Ming. 2013. A unified representation of deep moist convection in numerical modeling of the atmosphere. Part I. Journal of the Atmospheric Sciences, 70(7), 1977–92.Google Scholar
Arora, V. 2002. Modeling vegetation as a dynamic component in soil– vegetation–atmosphere transfer schemes and hydrological models. Reviews of Geophysics, 40, 126.CrossRefGoogle Scholar
Arrhenius, S. 1896. On the influence of carbonic acid in the air upon the temperature of the ground. Philosophical Magazine and Journal of Science, 41, 237–76.CrossRefGoogle Scholar
Asai, T., and Kasahara, A. 1967. A theoretical study of the compensating downward motions associated with cumulus clouds. Journal of the Atmospheric Sciences, 24, 467–96.Google Scholar
Augstein, E., Riehl, Herbert, Ostapoff, F., and Wagner, V. 1973. Mass and energy transports in an undisturbed Atlantic trade-wind flow. Monthly Weather Review, 101(2), 101–11.2.3.CO;2>CrossRefGoogle Scholar
Bailey, M., and Hallett, J. 2009. A comprehensive habit diagram for atmospheric ice crystals: confirmation from the laboratory, AIRS II, and other field studies. Journal of the Atmospheric Sciences, 66(9), 2888–9, https://dx.doi.org/10.1175/2009jas2883.1.Google Scholar
Bannon, P. R. 2002. Theoretical foundations for models of moist convection. Journal of the Atmospheric Sciences, 59(12), 1967–82.Google Scholar
Barenblatt, G. I. 1996. Scaling, Self Similarity, and Intermediate Asymptotics. Cambridge University Press.Google Scholar
Bauer, M. P., Tselioudis, G., and Rossow, W. B. 2016. A new climatology for investigating storm influences in and on the extratropics. Journal of Applied Meteorology and Climatology, 55, 1287–303.Google Scholar
Beard, K. V. 1977. Terminal velocity adjustment for cloud and precipitation drops aloft. Journal of the Atmospheric Sciences, 34, 1293–8.Google Scholar
Bellon, G., and Sobel, A. H. 2010. Multiple equilibria of the Hadley circulation in an intermediate-complexity axisymmetric model. Journal of Climate, 23, 1760–78.Google Scholar
Bellouin, N., Jones, A., Haywood, J., and Christopher, S. A. 2008. Updated estimate of aerosol direct radiative forcing from satellite observations and comparison against the Hadley Centre climate model. Journal of Geophysical Research, 113, D10205.Google Scholar
Bellouin, N., Quaas, J., Morcrette, J.-J., and Boucher, O. 2013. Estimates of aerosol radiative forcing from the MACC re-analysis. Atmospheric Chemistry and Physics, 13, 2045–62.Google Scholar
Bender, F. A-M., Ramanathan, V., and Tselioudis, G. 2012. Changes in extratropical storm track cloudiness 1983–2008: observational support for a poleward shift. Climate Dynamics, 38, 2037–53.Google Scholar
Betts, A. K., and Ridgway, W. 1988. Coupling of the radiative, convective, and surface fluxes over the Equatorial Pacific. Journal of the Atmospheric Sciences, 45(3), 522–36.Google Scholar
Betts, A. K., and Ridgway, W. 1989. Climatic equilibrium of the atmospheric convective boundary layer over a tropical ocean. Journal of the Atmospheric Sciences, 46(17), 2621–41.Google Scholar
Bjerknes, Jakob. 1969. Atmospheric teleconnections from the equatorial Pacific. Monthly Weather Review, 97(3), 163–72.Google Scholar
Bjerknes, Jakob., and Solberg, H. 1922. Life cycle of cyclones and the polar front theory of atmospheric circulation. Geophysisks Publikationer, 3, 318.Google Scholar
Bodas-Salcedo, A., Webb, M. J., Bony, S., et al. 2011. COSP: satellite simulation software for model assessment. Bulletin of the American Meteorological Society, 92(8), 1023–43.Google Scholar
Bodas-Salcedo, A., Williams, K. D., Field, P. R., and Lock, A. P. 2012. The surface downwelling solar radiation surplus over the Southern Ocean in the Met Office model: the role of midlatitude cyclone clouds. Journal of Climate, 25(21), 7467–86.Google Scholar
Bodas-Salcedo, A., Williams, K. D., Ringer, M. A., et al. 2014. Origins of the solar radiation biases over the Southern Ocean in CFMIP2 models. Journal of Climate, 27, 4156.Google Scholar
Boers, R., de Haij, M. J., Wauben, W. M. F., et al. 2010. Optimized fractional cloudiness determination from five ground-based remote sensing techniques. Journal of Geophysical Research, 115(D24), D24116.CrossRefGoogle Scholar
Bohren, Craig F. 1987. Multiple scattering of light and some of its observable consequences. American Journal of Physics, 55(6), 524–33.Google Scholar
Bohren, Craig F., and Clothiaux, Eugene E. 2006. Fundamentals of Atmospheric Radiation. John Wiley and Sons.CrossRefGoogle Scholar
Böing, Steven J., Siebesma, A. P, Korpershoek, J. D., and Jonker, Harm J. J. 2012. Detrainment in deep convection. Geophysical Research Letters, 39, 2030.Google Scholar
Böing, Steven J., Jonker, Harm J. J., Nawara, Witek A., and Siebesma, A. Pier. 2014. On the deceiving aspects of mixing diagrams of deep cumulus convection. Journal of the Atmospheric Sciences, 71(1), 5668.Google Scholar
Bollasina, M., Ming, Y., and Ramaswamy, V. 2011. Anthropogenic aerosols and the weakening of the South Asian summer monsoon. Science, 334, 502–5.Google Scholar
Bolton, David. 1980. The computation of equivalent potential temperature. Monthly Weather Review, 108(7), 1046–53.2.0.CO;2>CrossRefGoogle Scholar
Bony, Sandrine, Bellon, Gilles, Klocke, Daniel, et al. 2013a. Robust direct effect of carbon dioxide on tropical circulation and regional precipitation. Nature Geoscience, 6(6), 447–51.CrossRefGoogle Scholar
Bony, Sandrine, Colman, Robert, Kattsov, Vladimir M., et al. 2006. How well do we understand and evaluate climate change feedback processes? Journal of Climate, 19(15), 3445–82.Google Scholar
Bony, Sandrine, Dufresne, J.-L., Le Treut, H., Morcrette, J.-J., and Senior, C. 2004. On dynamic and thermodynamic components of cloud changes. Climate Dynamics, 22(2–3), 7186.Google Scholar
Bony, Sandrine, Stevens, B., Held, I., et al. 2013b. Carbon Dioxide and Climate: Perspectives on a Scientific Assessment. In Climate Science for Serving Society: Research, Modeling and Prediction Priorities. Springer. Pages 391413.Google Scholar
Bony, Sandrine, Stevens, Bjorn, Coppin, David, et al. 2016. Thermodynamic control of anvil cloud amount. Proceedings of the National Academy of Sciences of the United States of America, 113(32), 8927–32.Google Scholar
Bony, Sandrine, Stevens, Bjorn, Frierson, Dargan M. W., et al. 2015. Clouds, circulation and climate sensitivity. Nature Geoscience, 8(4), 261–8.Google Scholar
Booth, B. B. B., Dunstone, N. J., Halloran, P. R., Andrews, T., and Bellouin, N. 2012. Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability. Nature, 484, 228–32.Google Scholar
Booth, J. F., Wang, S., and Polvani, L. M. 2013. Midlatitude storms in a moister world: lessons from idealized baroclinic life cycle experiments. Climate Dynamics, 41, 787802.Google Scholar
Boucher, O. 2015. Atmospheric Aerosols: Properties and Climate Impacts. Springer.Google Scholar
Boucher, O., Randall, D., Artaxo, P., et al. 2013. Clouds and Aerosols. In Climate Change 2013: The Physical Science Basis. Cambridge University Press. Pages 571657.Google Scholar
Boutle, I. A., Eyre, J. E. J., and Lock, A. P. 2014. Seamless stratocumulus simulation across the turbulent gray zone. Monthly Weather Review, 142(4), 1655–68.Google Scholar
Bras, R. L. 1990. Hydrology: An Introduction to Hydrologic Science. Addison-Wesley.Google Scholar
Bretherton, Christopher S. 2015. Insights into low-latitude cloud feedbacks from high-resolution models. Philosophical Transactions of the Royal Society A, 373(2054).Google Scholar
Bretherton, Christopher, S., Blossey, P. N., and Khairoutdinov, M. 2005. An energy-balance analysis of deep convective self-aggregation above uniform SST. Journal of the Atmospheric Sciences, 62, 4273–92.Google Scholar
Bretherton, Christopher, S., Blossey, P. N., and Uchida, J. 2007. Cloud droplet sedimentation, entrainment efficiency, and subtropical stratocumulus albedo. Geophysical Research Letters, 34.CrossRefGoogle Scholar
Bretherton, Christopher S., and Park, Sungsu. 2009. A new moist turbulence parameterization in the community atmosphere model. Journal of Climate, 22(12), 3422–48.Google Scholar
Bretherton, Christopher, S., and Wyant, M. C. 1997. Moisture transport, lower-tropospheric stability, and decoupling of cloud-topped boundary layers. Journal of the Atmospheric Sciences, 54, 148–67.Google Scholar
Brient, Florent, and Bony, Sandrine. 2013. Interpretation of the positive low-cloud feedback predicted by a climate model under global warming. Climate Dynamics, 40, 2415–31.Google Scholar
Brooks, C. E. P. 1927. The mean cloudiness over the earth. Memoirs of the Royal Meteorological Society, 1(10), 127–38.Google Scholar
Butler, A. H., Thompson, D. W. J., and Heikes, R. 2010. The steady-state atmospheric circulation response to climate change-like thermal forcings in a simple general circulation model. Journal of Climate, 23, 3274–496.Google Scholar
Buizza, R. and Miller, M. and Palmer, T.N. 2007. Stochastic representation of model uncertainties in the ECMWF ensemble prediction system. Quarterly Journal of the Royal Meteorological Society, 125(560), 28872908.CrossRefGoogle Scholar
Byers, H. R., and Braham, R. R. Jr 1949. The Thunderstorm: Final Report of the Thunderstorm Project. US Government Printing Office.Google Scholar
Caldwell, P., Zhang, Y., and Klein, S. 2013. CMIP3 subtropical stratocumulus cloud feedback interpreted through a mixed-layer model. Journal of Climate, 26, 1607–25.Google Scholar
Callen, Herbert B. 1985. Thermodynamics, and an Introduction to Thermostatics. John Wiley & Sons.Google Scholar
Capderou, Michel. 2014. Handbook of Satellite Orbits: From Kepler to GPS. Springer.Google Scholar
Carlson, T. N. 1998. Mid-Latitude Weather Systems. American Meteorological Society.Google Scholar
Ceppi, Paulo, Brient, Florent, Zelinka, Mark D., and Hartmann, Dennis L. 2017. Cloud feedback mechanisms and their representation in global climate models. Wiley Interdisciplinary Reviews: Climate Change, 8(4), e465.Google Scholar
Ceppi, Paulo, and Hartmann, D. L. 2015. Connections between clouds, radiation, and midlatitude dynamics: a review. Current Climate Change Reports, 1, 94102.Google Scholar
Ceppi, Paulo, and Hartmann, D. L. 2016. Clouds and the atmospheric circulation response to warming. Journal of Climate, 29, 783–99.Google Scholar
Cesana, G., Kay, J. E., Chepfer, H., English, J. M., and de Boer, G. 2012. Ubiquitous low-level liquid-containing Arctic clouds: new observations and climate model constraints from CALIPSO-GOCCP. Geophysical Research Letters, 39(20), L20804.Google Scholar
Cess, R. D. 1976. Climate change: an appraisal of atmospheric feedback mechanisms employing zonal climatology. Journal of the Atmospheric Sciences, 33(10), 1831–43.Google Scholar
Cess, R. D., Potter, G. L., Blanchet, J. P., et al. 1990. Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. Journal of Geophysical Research, 95(D10), 16601–15.Google Scholar
Chang, E. K. M., Guo, Y., and Xia, X.. 2012. CMIP5 multimodel ensemble projection of storm track change under global warming. Journal of Geophysical Research: Atmospheres, 117, D23118, 10.1029/2012JD018578.Google Scholar
Charlson, R., Lovelock, J., Andreae, M., and Warren, S. 1987. Oceanic phytoplankton, atmospheric sulphur, cloud albedo and climate. Nature, 326, 655–61.CrossRefGoogle Scholar
Charney, J. G. 1963. A note on large-scale motions in the tropics. Journal of the Atmospheric Sciences, 20(6), 607–9.Google Scholar
Charney, J. G. 1979. Carbon Dioxide and Climate: A Scientific Assessment. National Academy Press.Google Scholar
Chen, Yi-Chun, Christensen, Matthew W., Stephens, Graeme L., and Seinfeld, John H. 2014. Satellite-based estimate of global aerosol-cloud radiative forcing by marine warm clouds. Nature Geoscience, 7(9), 643–6.Google Scholar
Cherian, R., Quaas, J., Salzmann, M., and Wild, M. 2014. Pollution trends over Europe constrain global aerosol forcing as simulated by climate models. Geophysical Research Letters, 41, 2176–81.Google Scholar
Chou, Chia, and Neelin, J. David. 2004. Mechanisms of global warming impacts on regional tropical precipitation. Journal of Climate, 17(13), 2688–701.Google Scholar
Christensen, M. W., Suzuki, K., Zambri, B., and Stephens, G. L. 2014. Ship track observations of a reduced shortwave aerosol indirect effect in mixed-phase clouds. Geophysical Research Letters, 41, 6970–77.Google Scholar
Clarke, Allan J. 2008. An Introduction to the Dynamics of El Niño and the Southern Oscillation. Academic Press.Google Scholar
Claussen, M., Dallmeyer, A., and Bader, J. 2017. Theory and modeling of the African Humid Period and the Green Sahara. In Oxford Research Encyclopedias, Climate Science, Regional and Local Climates, Climate Change. Oxford University Press.Google Scholar
Connolly, P. J., Möhler, O., Field, P. R., et al. 2009. Studies of heterogeneous freezing by three different desert dust samples. Atmospheric Chemistry and Physics, 9, 2805–24.Google Scholar
Conover, J. H. 1966. Anomalous cloud lines. Journal of the Atmospheric Sciences, 23, 778–85.Google Scholar
Cotton, W. R., Bryan, G., and van den Heever, S. 2010. Storm and Cloud Dynamics, 2nd Edition. Vol. 99. Academic Press.Google Scholar
Cox, P. M., Huntingford, C., and Williamson, M. S. 2018. Emergent constraint on equilibrium climate sensitivity from global temperature variability. Nature, 553, 319.Google Scholar
Cronin, T. W., and Jansen, M. F. 2016. Analytic radiative-advective equilibrium as a model for high-latitude climate. Geophysical Research Letters, 43(1), 449–57.Google Scholar
Cronin, T. W., and Tziperman, E. 2015. Low clouds suppress Arctic air formation and amplify high-latitude continental winter warming. Proceedings of the National Academy of Sciences of the United States of America, 112(37), 11490–5.Google Scholar
Crosman, E. T., and Horel, J. D. 2010. Sea and lake breezes: a review of numerical studies. Boundary-Layer Meteorology, 137, 129.Google Scholar
Curry, Judith. 1983. On the formation of continental polar air. Journal of the Atmospheric Sciences, 40(9), 2278–92.Google Scholar
Curry, Judith., and Webster, P. J. 1999. Thermodynamics of Atmospheres & Oceans. Academic Press.Google Scholar
Cuxart, J., Bougeault, P., and Redelsperger, J.-L. 2000. A turbulence scheme allowing for mesoscale and large-eddy simulations. Quarterly Journal of the Royal Meteorological Society, 126(562), 130.Google Scholar
Dal Gesso, S., and Neggers, R. A. J. 2017. Can we use single-column models for understanding the boundary-layer cloud-climate feedback? Journal of Advances in Modeling Earth Systems, 10(2), 245–61.Google Scholar
Dawe, J. T., and Austin, P. H. 2011. Interpolation of LES cloud surfaces for use in direct calculations of entrainment and detrainment. Monthly Weather Review, 139, 444–56.Google Scholar
de Roode, S. R., and Duynkerke, P. G. 1997. Observed Lagrangian transition of stratocumulus into cumulus during ASTEX: mean state and turbulence structure. Journal of the Atmospheric Sciences, 54, 2157–73.Google Scholar
de Roode, S. R., Duynkerke, P. G., and Jonker, H. J. J. 2004. Large eddy simulation: how large is large enough? Journal of the Atmospheric Sciences, 61, 403–21.Google Scholar
de Roode, S. R, Sandu, I., van der Dussen, J. J., et al. 2016. Large eddy simulations of EUCLIPSE/GASS Lagrangian stratocumulus to cumulus transitions: mean state, turbulence, and decoupling. Journal of the Atmospheric Sciences, 73, 2485–508.Google Scholar
de Roode, S. R., Siebesma, A. P., Dal Gesso, S., et al. 2014. A mixed-layer model study of the stratocumulus response to changes in large-scale conditions. Journal of Advances in Modeling Earth Systems, 6(4), 1256–70.Google Scholar
de Roode, S. R., Siebesma, A. P., Jonker, H. J. J., and de Voogd, Y. 2012. Parameterization of the vertical velocity equation for shallow cumulus clouds. Monthly Weather Review, 140, 2424–36.Google Scholar
de Rooy, Wim C., Bechtold, Peter, Fröhlich, Kristina, et al. 2013. Entrainment and detrainment in cumulus convection: an overview. Quarterly Journal of the Royal Meteorological Society, 139(670), 119.Google Scholar
de Rooy, Wim C., and Siebesma, A. Pier. 2008. A simple parameterization for detrainment in shallow cumulus. Monthly Weather Review, 136(2), 560–76.Google Scholar
Delworth, T. L., and Manabe, S. 1988. The influence of potential evaporation on the variabilities of simulated soil wetness and climate. Journal of Climate, 1, 523–47.2.0.CO;2>CrossRefGoogle Scholar
Diaz, Henry F., and Bradley, Raymond S. 2004. The Hadley Circulation: Present, Past, and Future. Springer.Google Scholar
Dirmeyer, P. A., and Brubaker, K. L. 2007. Characterization of the global hydrologic cycle from a back-trajectory analysis of atmospheric water vapor. Journal of Hydrometeorology, 8, 2037.Google Scholar
Dorrestijn, Jesse, Crommelin, Daan T., Siebesma, A. Pier, Jonker, Harmen J. J., and Selten, Frank. 2016. Stochastic convection parameterization with Markov chains in an intermediate-complexity GCM. Journal of the Atmospheric Sciences, 73(3), 1367–82.Google Scholar
Dufresne, Jean-Louis, and Bony, Sandrine. 2008. An assessment of the primary sources of spread of global warming estimates from coupled atmosphere–ocean models. Journal of Climate, 21(19), 5135–44.Google Scholar
Dufresne, Jean-Louis, and Saint-Lu, Marion. 2016. Positive feedback in climate: stabilization or runaway, illustrated by a simple experiment. Bulletin of the American Meteorological Society, 97(5), 755–65.Google Scholar
Dunstone, N. J., Smith, D. M., Booth, B. B. B., Hermanson, L., and Eade, R. 2013. Anthropogenic aerosol forcing of Atlantic tropical storms. Nature Geoscience, 6, 534–9.Google Scholar
Durant, A. J., and Shaw, A. 2005. Evaporation freezing by contact nucleation inside-out. Geophysical Research Letters, 32.Google Scholar
Duynkerke, P. G., de Roode, S. R., van Zanten, M. C., et al. 2004. Observations and numerical simulations of the diurnal cycle of the EUROCS stratocumulus case. Quarterly Journal of the Royal Meteorological Society, 130, 3269–96.CrossRefGoogle Scholar
Duynkerke, P. G., Zhang, H.-Q., and Jonker, P. J. 1995. Microphysical and turbulent structure of nocturnal stratocumulus as observed during ASTEX. Journal of the Atmospheric Sciences, 52, 2763–77.Google Scholar
Ek, M., and Mahrt, L. 1994. Daytime evolution of relative humidity at the boundary layer top. Monthly Weather Review, 122, 2709–21.Google Scholar
Emanuel, Kerry. 1994. Atmospheric Convection. Oxford University Press.Google Scholar
Emanuel, Kerry. 2003. Tropical cyclones. Annual Review of Earth and Planetary Sciences, 31(1), 75104.Google Scholar
Faloona, I., Lenschow, D. H., Campos, T., et al. 2005. Observations of entrainment in eastern Pacific marine stratocumulus using three conserved scalars. Journal of the Atmospheric Sciences, 62, 3268–85.Google Scholar
Fang, Ming, and Tung, Ka Kit. 1996. A simple model of nonlinear Hadley circulation with an ITCZ: analytic and numerical solutions. Journal of the Atmospheric Sciences, 53(9), 1241–61.Google Scholar
Feng, Y., and Ramanathan, V. 2010. Investigation of aerosol-cloud interactions using a chemical transport model constrained by satellite observations. Tellus, 62B, 6986.Google Scholar
Fermi, E. 1956. Thermodynamics. Dover Publications.Google Scholar
Field, P. R., Heymsfield, A. J., Bansemer, A. R., and Twohy, C. H. 2008. Determination of the combined ventilation factor and capacitance for ice crystal aggregates from airborne observations in a tropical anvil cloud. Journal of the Atmospheric Sciences, 65, 376–91.Google Scholar
Field, P. R., and Wood, R. 2007. Precipitation and cloud structure in midlatitude cyclones. Journal of Climate, 20, 233–54.Google Scholar
Findell, K. L., and Eltahir, E. A. B. 2003. Atmospheric controls on soil moisture-boundary layer interactions. Part I: framework development. Journal of Hydrometeorology, 4, 552–69.Google Scholar
Fischer, E. M., Seneviratne, S. I., Vidale, P. L., Lüthi, D., and Schär, C. 2007. Soil moisture–atmosphere interactions during the 2003 European summer heat wave. Journal of Climate, 20, 5081–99.Google Scholar
Flato, G. M., Marotzke, J., Abiodun, B., et al. 2013. Evaluation of Climate Models. In Climate Change 2013: The Physical Science Basis. On Climate Change, Panel, Intergovernmental (ed.) Cambridge University Press. Pages 741866.Google Scholar
Forster, Piers M. 2016. Inference of climate sensitivity from analysis of Earth’s energy budget. Annual Review of Earth and Planetary Sciences, 44(1), 85106.Google Scholar
Freud, E., and Rosenfeld, D. 2012. Linear relation between convective cloud drop number concentration and depth for rain initiation. Journal of Geophysical Research, 117, D02207.Google Scholar
Frisch, Uriel. 1996. Turbulence, the Legacy of A. N. Kolmogorov. Cambridge University Press.Google Scholar
Garcia-Herrera, R., Diaz, J., Trigo, R. M., Luterbacher, J., and Fischer, E. M. 2010. A review of the European summer heat wave of 2003. Critical Reviews in Environmental Science and Technology, 40, 267306.Google Scholar
Geoffroy, O., Saint-Martin, D., Olivié, D. J. L., et al. 2013. Transient climate response in a two-layer energy-balance model. Part I: analytical solution and parameter calibration using CMIP5 AOGCM experiments. Journal of Climate, 26(6), 1841–57.Google Scholar
Gerst, Alexander. 2017. Astro Alex. www.flickr.com/photos/astro_alex/. Accessed: 15/01/2017.Google Scholar
Gill, Adrian E. 1980. Some simple solutions for heat-induced tropical circulation. Quarterly Journal of the Royal Meteorological Society, 106(449), 447–62.Google Scholar
Gill, Adrian E. 1982. Atmosphere–Ocean Dynamics. Elsevier.Google Scholar
Gleckler, P. J., Taylor, K. E., and Doutriaux, C. 2008. Performance metrics for climate models. Journal of Geophysical Research, 113(D6), D06104.Google Scholar
Golaz, Jean-Christophe, Larson, Vincent E., and Cotton, William R. 2002. A PDF-based model for boundary layer clouds. Part I: method and model description. Journal of the Atmospheric Sciences, 59(24), 3540–51.Google Scholar
Gordon, Neil D., and Klein, Stephen A. 2014. Low-cloud optical depth feedback in climate models. Journal of Geophysical Research, 119(10), 6052–65.Google Scholar
Goren, T., and Rosenfeld, D. 2014. Decomposing aerosol cloud radiative effects into cloud cover, liquid water path and Twomey components in marine stratocumulus. Atmospheric Research, 138, 378–93.Google Scholar
Govekar, Pallavi D., Jakob, Christian, and Catto, Jennifer. 2014. The relationship between clouds and dynamics in southern hemisphere extratropical cyclones in the real world and a climate model. Journal of Geophysical Research: Atmospheres, 119(11), 6609–28.Google Scholar
Grabowski, Wojciech W., and Smolarkiewicz, Piotr K. 1999. CRCP: a cloud resolving convection parameterization for modeling the tropical convecting atmosphere. Physica D: Nonlinear Phenomena, 133(1), 171–8.CrossRefGoogle Scholar
Grabowski, Wojciech W., and Wang, L. P. 2013. Growth of cloud droplets in a turbulent environment. Annual Review of Fluid Mechanics, 45, 293324.Google Scholar
Grant, A. L. M., and Brown, A. R. 1999. A similarity hypothesis for shallow-cumulus transports. Quarterly Journal of the Royal Meteorological Society, 125(558), 1913–36.Google Scholar
Gregory, Jonathan M., Andrews, Timothy, and Good, Peter. 2015. The inconstancy of the transient climate response parameter under increasing CO2. Philosophical Transactions of the Royal Society A, 373(2054), pii: 20140417.Google Scholar
Gregory, Jonathan M., Ingram, W. J., Palmer, M. A., et al. 2004. A new method for diagnosing radiative forcing and climate sensitivity. Geophysical Research Letters, 31(3), L03205.CrossRefGoogle Scholar
Grise, K. M., and Medeiros, B. 2016. Understanding the varied influence of midlatitude jet position on clouds and cloud radiative effects in observations and global climate models. Journal of Climate, 29, 9005–25.Google Scholar
Gunn, R., and Kinzer, G. D. 1949. The terminal velocity of fall for water droplets in stagnant air. Journal of the Atmospheric Sciences, 6, 243–48.Google Scholar
Hagemann, S. 2002. An improved land surface parameter dataset for global and regional climate models. Max Planck Institute for Meteorology Report No 336.Google Scholar
Hagos, Samson, Zhang, Chidong, Tao, Wei-Kuo, et al. 2010. Estimates of tropical diabatic heating profiles: commonalities and uncertainties. Journal of Climate, 23(3), 542–58.Google Scholar
Hahn, C. J., and Warren, S. G. 2007. A Gridded Climatology of Clouds over Land (1971–96) and Ocean (1954–97) from Surface Observations Worldwide. Numeric Data Package NDP-026E. CDIAC, Department of Energy.Google Scholar
Halley, E. 1686. An historical account of the trade winds and monsoons, observable in the seas between and near the tropics, with an attempt to assign the physical cause of the said winds. Philosophical Transactions of the Royal Society, 16, 153–68.Google Scholar
Hartmann, Dennis. 2016. Global Physical Climatology, 2nd Edition. Elsevier Science.Google Scholar
Hartmann, Dennis L., and Larson, Kristin. 2002. An important constraint on tropical cloud – climate feedback. Geophysical Research Letters, 29(20), 12-1-12-4.Google Scholar
Haynes, John M., Jakob, Christian, Rossow, William B., Tselioudis, George, and Brown, Josephine. 2011. Major characteristics of southern ocean cloud regimes and their effects on the energy budget. Journal of Climate, 24(19), 5061–80.Google Scholar
Hazeleger, W., Severijns, C., Semmler, T., et al. 2010. EC-Earth, a seamless earth-system prediction approach in action. Bulletin of the American Meteorological Society, 91, 1357–63.Google Scholar
Held, Isaac M., and Hou, Arthur Y. 1980. Nonlinear axially symmetric circulations in a nearly inviscid atmosphere. Journal of the Atmospheric Sciences, 37(3), 515–33.Google Scholar
Held, Isaac M., and Soden, Brian J. 2006. Robust responses of the hydrological cycle to global warming. Journal of Climate, 19(21), 5686–99.Google Scholar
Hogan, Robin J., and Illingworth, Anthony J. 2000. Deriving cloud overlap statistics from radar. Quarterly Journal of the Royal Meteorological Society, 126(569), 2903–9.Google Scholar
Hogstrom, U. 1996. Review of some basic characteristics of the atmospheric surface layer. Boundary Layer Meteorology, 78, 215–46.Google Scholar
Hohenegger, C., Brockhaus, P., Bretherton, C. S., and Schär, C. 2009. The soil moisture-precipitation feedback in simulations with explicit and parameterized convection. Journal of Climate, 22, 5003–20.Google Scholar
Holton, J. R., and Hakim, G. J. 2013. An Introduction to Dynamic Meteorology, 5th Edition. Academic Press.Google Scholar
Holtslag, A. A. M., and Duynkerke, P. G. 1998. Clear and cloudy boundary layers. Proceedings of the Colloquium ‘Clear and Cloudy Boundary Layers’, Amsterdam, 26–9 August 1997. Verhandelingen der Koninklijke Nederlandse Akademie van Wetenschappen, Afd. Natuurkunde: Eerste reeks. Royal Netherlands Academy of Arts and Sciences.Google Scholar
Hoskins, B. J., and Hodges, K. I. 2002. New perspectives on the northern hemisphere winter storm tracks. Journal of the Atmospheric Sciences, 59, 1041–61.Google Scholar
Hourdin, Frederic, Mauritsen, Thorsten, Gettelman, Andrew, et al. 2017. The art and science of climate model tuning. Bulletin of the American Meteorological Society, 98(3), 589602.Google Scholar
Houze, R. A. Jr and Betts, A. K. 1981. Convection in GATE. Reviews of Geophysics and Space Physics, 19, 541–76.Google Scholar
Houze, Robert A. 1993. Cloud Dynamics. Vol. 53. Academic Press.Google Scholar
Houze, Robert A. 2004. Mesoscale convective systems. Reviews of Geophysics, 42(4).Google Scholar
Howard, L. 1865. Essay on the Modification of Clouds. https://books.google.com.au/books?id=HvADAAAAQAAJ&printsec=frontcover& source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false. Accessed 14/01/2020.Google Scholar
Howell, Wallace E. 1949. The growth of cloud drops in uniformly cooled air. Journal of Meteorology, 6(2), 134–49.2.0.CO;2>CrossRefGoogle Scholar
Hughes, N. A. 1984. Global cloud climatologies: a historical review. Journal of Applied Meteorology and Climatology, 23, 724–51.Google Scholar
Iribarne, J. V., and Godson, W. L. 1981. Atmospheric Thermodynamics. D. Reidel.Google Scholar
Jakob, Christian, and Tselioudis, George. 2003. Objective identification of cloud regimes in the Tropical Western Pacific. Geophysical Research Letters, 30(21), 2082.CrossRefGoogle Scholar
Jiang, Jonathan H., Su, Hui, Zhai, Chengxing, et al. 2012. Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA “ATrain” satellite observations. Journal of Geophysical Research, 117(D14), D14105.Google Scholar
Johnson, Richard H., Rickenbach, Thomas M., Rutledge, Steven A., Ciesielski, Paul E., and Schubert, Wayne H. 1999. Trimodal characteristics of tropical convection. Journal of Climate, 12(8), 2397–418.2.0.CO;2>CrossRefGoogle Scholar
Kahn, B. H., Teixeira, J., Fetzer, E. J., et al. 2011. Temperature and water vapor variance scaling in global models: comparisons to satellite and aircraft data. Journal of the Atmospheric Sciences, 68(9), 2156–68.Google Scholar
Kain, J. S., and Frisch, J. M. 1990. A one-dimensional entraining/ detraining plume model and its application in convective parameterization. Journal of the Atmospheric Sciences, 479, 2784–802.Google Scholar
Kamae, Youichi, and Watanabe, Masahiro. 2013. Tropospheric adjustment to increasing CO2 : its timescale and the role of land–sea contrast. Climate Dynamics, 41(11), 3007–24.Google Scholar
Kärcher, B., and Lohmann, U. 2003. A parameterization of cirrus cloud formation: heterogeneous freezing. Journal of Geophysical Research, 108, 4402.Google Scholar
Karlsson, K.-G., and Dybbroe, A. 2010. Evaluation of Arctic cloud products from the EUMETSAT Climate Monitoring Satellite Application Facility based on CALIPSO-CALIOP observations. Atmospheric Chemistry and Physics, 10(4), 1789–807.Google Scholar
Kay, Jennifer E., L’Ecuyer, Tristan, Chepfer, Helene, et al. 2016. Recent advances in Arctic cloud and climate research. Current Climate Change Reports, 2(4), 159–69.Google Scholar
Kessler, E. 1995. On the continuity and distribution of water substance in atmospheric circulations. Atmospheric Research, 38(1–4), 109–45.Google Scholar
Khouider, B., Biello, J., and Majda, A. J. 2010. A stochastic multicloud model for tropical convection. Communications in Mathematical Sciences, 8(1), 187216.Google Scholar
Khvorostyanov, V. I., and Curry, J. A. 2006. Aerosol size spectra and CCN activity spactra: reconciling the lognormal, algebraic, and power lows. Journal of Geophysical Research, 111(D12).Google Scholar
Kiladis, George N., Wheeler, Matthew C., Haertel, Patrick T., Straub, Katherine H., and Roundy, Paul E. 2009. Convectively coupled equatorial waves. Reviews of Geophysics, 47(2).Google Scholar
Kinne, S., O’Donnell, D., Stier, P., et al. 2013. MAC-v1: a new global aerosol climatology for climate studies. Journal of Advances in Modeling Earth Systems, 5, 704–40.Google Scholar
Kleidon, A., and Renner, M. 2013. A simple explanation for the sensitivity of the hydrologic cycle to surface temperature and solar radiation and its implications for global climate change. Earth System Dynamics, 4(2), 455–65.Google Scholar
Klein, Rupert. 2010. Scale-dependent models for atmospheric flows. Annual Review of Fluid Mechanics, 42(1), 249–74.Google Scholar
Klein, Stephen A., and Jakob, C. 1999. Validation and sensitivities of frontal clouds simulated by the ECMWF model. Monthly Weather Review, 127, 2514–31.Google Scholar
Klein, Stephen A., Pincus, Robert, Hannay, Cecile, and Xu, Kuan-Man. 2005. How might a statistical cloud scheme be coupled to a mass-flux convection scheme? Journal of Geophysical Research: Atmospheres, 110(D15), 1015.Google Scholar
Klocke, Daniel, Pincus, Robert, and Quaas, Johannes. 2011. On constraining estimates of climate sensitivity with present-day observations through model weighting. Journal of Climate, 24(23), 6092–9.CrossRefGoogle Scholar
Knutti, Reto, and Sedlá˜cek, Jan. 2013. Robustness and uncertainties in the new CMIP5 climate model projections. Nature Climate Change, 369(3).Google Scholar
Kolmogorov, A. N. 1941. The local structure of turbulence in incompressible viscous fluid for very large Reynolds’ numbers. Doklady Akademiia Nauk SSSR, 30, 301–5.Google Scholar
Koster, R. D., and Suarez, M. J. 2001. Soil moisture memory in climate models. Journal of Hydrometeorology, 2, 559–70.Google Scholar
Kuang, Zhiming. 2008. Modeling the interaction between cumulus convection and linear gravity waves using a limited-domain cloud system-resolving model. Journal of the Atmospheric Sciences, 65(2), 576–91.Google Scholar
Kuhlmann, J., and Quaas, J. 2010. How can aerosols affect the Asian summer monsoon? Assessment during three consecutive pre-monsoon seasons from CALIPSO satellite data. Atmospheric Chemistry and Physics, 10, 4673–88.Google Scholar
Kulmala, M., Suni, T., Lehtinen, K. E. J., et al. 2004. A new feedback mechanism linking forests, aerosols, and climate. Atmospheric Chemistry and Physics, 4, 557–62.Google Scholar
Kundu, Pijush K., and Cohen, Ira M. 2002. Fluid Mechanics. 2nd Edition. Academic Press.Google Scholar
Lamarque, J.-F., Bond, T. C., Eyring, V., et al. 2010. Historical (1850– 2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmospheric Chemistry and Physics, 10, 7017–39.Google Scholar
Lamb, D., and Verlinde, J. 2011. Physics and Chemistry of Clouds. Cambridge University Press.Google Scholar
Lappen, Cara-Lyn, and Randall, David A. 2001. Toward a unified parameterization of the boundary layer and moist convection. Part I: a new type of mass-flux model. Journal of the Atmospheric Sciences, 58(15), 2021–36.Google Scholar
Lau, N.-C., and Crane, M. W. 1997. Comparing satellite and surface observations of cloud patterns in synoptic-scale circulation systems. Monthly Weather Review, 125, 3172–89.Google Scholar
Lau, William K.-M., and Waliser, Duane E. 2011. Intraseasonal Variability in the Atmosphere–Ocean Climate System. Springer.Google Scholar
L’Ecuyer, Tristan S., Beaudoing, H. K., Rodell, M., et al. 2015. The observed state of the energy budget in the early twenty-first century. Journal of Climate, 28(21), 8319–46.Google Scholar
Lenderink, G., and Holtslag, A. A. M. 2000. Evaluation of the kinetic energy approach for modeling turbulent fluxesin stratocumulus. Monthly Weather Review, 128(1), 244–58.Google Scholar
Lenoble, Jacqueline. 1993. Atmospheric Radiative Transfer. Studies in Geophysical Optics and Remote Sensing. A. Deepak Publishing.Google Scholar
Li, Ying, Thompson, David W. J., and Bony, Sandrine. 2015. The influence of atmospheric cloud radiative effects on the largescale atmospheric circulation. Journal of Climate, 28(18), 7263–78.Google Scholar
Liepert, B., Feichter, J., Lohmann, U., and Roeckner, E. 2004. Can aerosols spin down the hydrological cycle in a moister and warmer world? Geophysical Research Letters, 31, L06207.Google Scholar
Lindzen, R. S., and Farrell, B. 1980. A simple approximate result for the maximum growth rate of baroclinic instabilities. Journal of the Atmospheric Sciences, 37, 1648–54.Google Scholar
Loeb, N. G., and Wielicki, B. A. 2015. Earth’s Radiation Budget. In Encyclopedia of Atmospheric Sciences. 2nd Edition. North, Gerald R., Pyle, John, and Zhang, Fuqing (eds). Academic Press. Pages 6776.Google Scholar
Lohmann, U. 2002. A glaciation indirect aerosol effect caused by soot aerosols. Geophysical Research Letters, 29, 1052.Google Scholar
Lohmann, U., and Feichter, J. 2005. Global indirect aerosol effects: a review. Atmospheric Chemistry and Physics, 5, 715–37.Google Scholar
Lohmann, U., Lüönd, F., and Mahrt, F. 2016. An Introduction to Clouds: From the Microscale to Climate. Cambridge University Press.Google Scholar
Lohmann, U., Quaas, J., Kinne, S., and Feichter, J. 2007. Different approaches for constraining global climate models of the anthropogenic indirect aerosol effect. Bulletin of the American Meteorological Society, 88, 243–9.Google Scholar
Long, Alexis B. 1974. Solutions to the droplet collection equation for polynomial kernels. Journal of the Atmospheric Sciences, 31(4), 1040–52.Google Scholar
Lorenz, D. J., and Hartmann, D. L. 2001. Eddy-zonal flow feedback in the southern hemisphere. Journal of the Atmospheric Sciences, 58, 3312–27.Google Scholar
Madden, Roland A., and Julian, Paul R. 1972. Description of global-scale circulation cells in the tropics with a 40–50 day period. Journal of the Atmospheric Sciences, 29(6), 1109–23.Google Scholar
Mahmood, R., Pielke, Sr, Hubbard, R. A. K. G., et al. 2014. Land cover changes and their biogeophysical effects on climate. International Journal of Climatology, 34, 929–53.Google Scholar
Malkus, Joanne, and Scorer, R. S. 1955. The erosion of cumulus towers. Journal of Meteorology, 12(1), 4357.Google Scholar
Malkus, Joanne S., Scorer, R. S., Ludlam, F. H., and Bjorgum, O. 1953. Correspondence – bubble theory of penetrative convection. Quarterly Journal of the Royal Meteorological Society, 79, 288–93.Google Scholar
Manabe, S., Smagorinsky, J., and Strickler, R. F. 1965. Simulated climatology of a general circulation model with a hydrological cycle. Monthly Weather Review, 93, 769–98.Google Scholar
Manabe, S., and Wetherald, R. T. 1967. Thermal equilibrium of the atmosphere with a given distribution of relative humidity. Journal of the Atmospheric Sciences, 24(3), 241–59.Google Scholar
Mapes, Brian, Tulich, Stefan, Lin, Jialin, and Zuidema, Paquita. 2006. The mesoscale convection life cycle: building block or prototype for large-scale tropical waves? Dynamics of Atmospheres and Oceans, 42(1), 329.Google Scholar
Marquet, Pascal. 2011. Definition of a moist entropy potential temperature: application to FIRE-I data flights. Quarterly Journal of the Royal Meteorological Society, 137(656), 768–91.Google Scholar
Marquet, Pascal. 2017. A third-law isentropic analysis of a simulated hurricane. Journal of the Atmospheric Sciences, 74(10), 3451–71.Google Scholar
Martin, G. M., Johnson, D. W., and Spice, S. 1994. The measurement and parameterization of effective radius of droplets in warm stratocumulus clouds. Journal of the Atmospheric Sciences, 51, 1823–42.Google Scholar
Mason, B. J. 1971. The Physics of Clouds. Clarendon Press. Page 671.Google Scholar
Mason, Shannon, Fletcher, Jennifer K., Haynes, John M., et al. 2015. A hybrid cloud regime methodology used to evaluate Southern Ocean cloud and shortwave radiation errors in ACCESS. Journal of Climate, 28(15), 6001–18.Google Scholar
Matsuno, Taroh. 1966. Quasi-geostrophic motions in the equatorial area. Journal of the Meteorological Society of Japan. Ser. II, 44(1), 2543.Google Scholar
Mauritsen, T., Sedlar, J., Tjernström, M., et al. 2011. An Arctic CCN-limited cloud-aerosol regime. Atmospheric Chemistry and Physics, 11(1), 165–73.Google Scholar
McDonald, James E. 1958. The physics of cloud modification. Advances in Geophysics, 5, 223303.Google Scholar
McDonald, James E. 1963. Use of the electrostatic analogy in studies of ice crystal growth. Zeitschrift für Angewandte Mathematik und Physik, 14(5), 610–20.Google Scholar
Medeiros, Brian, and Stevens, Bjorn. 2011. Revealing differences in GCM representations of low clouds. Climate Dynamics, 36(1), 385–99.Google Scholar
Mellado, Juan Pedro. 2010. The evaporatively driven cloud-top mixing layer. Journal of Fluid Mechanics, 660(Oct.), 536.Google Scholar
Mellado, Juan Pedro. 2017. Cloud-top entrainment in stratocumulus clouds. Annual Review of Fluid Mechanics, 49(Jan.), 145–69.Google Scholar
Mellor, George L. 1977. The Gaussian cloud model relations. Journal of the Atmospheric Sciences, 34(2), 356–58.Google Scholar
Ming, Y., Ramaswamy, V., and Persad, G. 2010. Two opposing effects of absorbing aerosols on global-mean precipitation. Geophysical Research Letters, 37, L13701.Google Scholar
Mironov, Dmitrii V. 2008. Turbulence in the Lower Troposphere: Second-Order Closure and Mass-Flux Modelling Frameworks. Springer.Google Scholar
Mishchenko, Michael I., Hovenier, Joop W., and Travis, Larry D. (eds). 2000. Light Scattering by Nonspherical Particles: Theory, Measurements, and Applications. Academic Press.Google Scholar
Mitchell, D. L., and Heymsfield, A. J. 2005. Refinements in the treatment of ice particle terminal velocities, highlighting aggregates. Journal of the Atmospheric Sciences, 62, 1637–44.Google Scholar
Mitchell, J. F. B., Wilson, C. A., and Cunnington, W. M. 1987. On CO2 climate sensitivity and model dependence of results. Quarterly Journal of the Royal Meteorological Society, 113(475), 293322.Google Scholar
Möhler, O., Field, P. R., Connolly, P., et al. 2006. Efficiency of the deposition mode ice nucleation on mineral dust particles. Atmospheric Chemistry and Physics, 6, 3007–21.Google Scholar
Morrison, Hugh, de Boer, Gijs, Feingold, Graham, et al. 2012. Resilience of persistent Arctic mixed-phase clouds. Nature Geoscience, 5(1), 1117.CrossRefGoogle Scholar
Muller, Caroline J., and Held, Isaac M. 2012. Detailed investigation of the self-aggregation of convection in cloud-resolving simulations. Journal of the Atmospheric Sciences, 69(8), 2551–65.Google Scholar
Murphy, D. M., and Koop, T. 2005. Review of the vapour pressures of ice and supercooled water for atmospheric applications. Quarterly Journal of the Royal Meteorological Society, 131(608), 1539–65.Google Scholar
Neelin, J. David, and Held, Isaac M. 1987. Modeling tropical convergence based on the moist static energy budget. Monthly Weather Review, 115(1), 312.Google Scholar
Neelin, J. David, and Zeng, N. 2000. A quasi-equilibrium tropical circulation model-formulation. Journal of the Atmospheric Sciences, 57(11), 1741–66.Google Scholar
Neggers, R. A. J. 2015. Exploring bin-macrophysics models for moist convective transport and clouds. Journal of Advances in Modeling Earth Systems, 7(4), 2079–104.Google Scholar
Neggers, R. A. J., Neelin, J. D., and Stevens, B. 2007. Impact mechanisms of shallow cumulus convection on tropical climate dynamics. Journal of Climate, 20(11), 2623–42.Google Scholar
Nicholls, S., and Turton, J. D. 1986. An observational study of the structure of stratiform cloud sheets: part II. entrainment. Quarterly Journal of the Royal Meteorological Society, 112, 461–80.Google Scholar
Norris, J., and Slingo, A. 2009. Trends in Observed Cloudiness and Earth’s Radiation Budget. In Clouds in the Perturbed Climate System: Their Relationship to Energy Balance, Atmospheric Dynamics, and Precipitation. Heintzenberg, J., and Charlson, Robert J. (eds). The MIT Press. Pages 1736.Google Scholar
O’Gorman, Paul A., Allan, Richard P., Byrne, Michael P., and Previdi, Michael. 2012. Energetic constraints on precipitation under climate change. Surveys in Geophysics, 33(3), 585608.Google Scholar
Otto, A., Otto, F. E. L., Boucher, O., et al. 2013. Energy budget constraints on climate response. Nature Geoscience, 6(6), 415–16.Google Scholar
Oueslati, Boutheina, and Bellon, Gilles. 2015. The double ITCZ bias in CMIP5 models: interaction between SST, large-scale circulation and precipitation. Climate Dynamics, 44(3–4), 585607.Google Scholar
Park, S., Leovy, C. B., and Rozendaal, M. A. 2004. A new heuristic Lagrangian marine boundary layer cloud model. Journal of the Atmospheric Sciences, 61, 3002–24.Google Scholar
Pauluis, Olivier, and Held, I. M. 2002a. Entropy budget of an atmosphere in radiative-convective equilibrium. Part I: maximum work and frictional dissipation. Journal of the Atmospheric Sciences, 59(2), 125–39.Google Scholar
Pauluis, Olivier, and Held, I. M. 2002b. Entropy budget of an atmosphere in radiative-convective equilibrium. Part II: latent heat transport and moist processes. Journal of the Atmospheric Sciences, 59(2), 140–9.Google Scholar
Pawlowska, H., Grabowski, W. W., and Brenguier, J.-L. 2006. Observations of the width of cloud droplet spectra in stratocumulus. Geophysical Research Letters, 33, L19810.Google Scholar
Perovich, Don K., Andreas, E. L., Curry, J. A., et al. 1999. Year on ice gives climate insights. Eos, Transactions American Geophysical Union, 80(41), 481–6.Google Scholar
Persson, P. Ola, G., Shupe, Matthew D., Perovich, Don, and Solomon, Amy. 2016. Linking atmospheric synoptic transport, cloud phase, surface energy fluxes, and sea-ice growth: observations of midwinter SHEBA conditions. Climate Dynamics, 49(4), 1341–64.Google Scholar
Peters, Karsten, Crueger, Traute, Jakob, Christian, and Mobis, Benjamin. 2017. Improved MJO-simulation in ECHAM6.3 by coupling a stochastic multicloud model to the convection scheme. Journal of Advances in Modeling Earth Systems, 9(1), 193219.Google Scholar
Petters, M. D., and Kreidenweis, S. M. 2007. A single parameter representation of hygroscopic growth and cloud condensation nuclei activity. Atmospheric Chemistry and Physics, 7, 1961–71.Google Scholar
Petty, Grant W. 2006. A First Course in Atmospheric Radiation. 2nd Edition. Sundog Publishing.Google Scholar
Pierrehumbert, R. T. 1995. Thermostats, radiator fins, and the local runaway greenhouse. Journal of Atmospheric Sciences, 52(10), 17841806.Google Scholar
Pierrehumbert, R. T., and Yang, H. 1993. Global chaotic mixing on isentropic surfaces. Journal of Atmospheric Sciences, 50(15), 2462–80.Google Scholar
Pincus, Robert, Batstone, Crispian P., Hofmann, Robert J. Patrick, Taylor, Karl E., and Glecker, Peter J. 2008. Evaluating the present-day simulation of clouds, precipitation, and radiation in climate models. Journal of Geophysical Research, 113(D14), D14209.Google Scholar
Pincus, Robert, Platnick, Steven, Ackerman, Steven A., Hemler, Richard S., and Hofmann, Patrick, Robert, J. 2012. Reconciling simulated and observed views of clouds: MODIS, ISCCP, and the limits of instrument simulators. Journal of Climate, 25(13), 4699–720.Google Scholar
Pino, D., Vilà-Guerau de Arellano, J., and Duynkerke, P. G. 2003. The contribution of shear to the evolution of a convective boundary layer. Journal of Atmospheric Sciences, 60(16), 1913–26.Google Scholar
Pithan, Felix, Medeiros, Brian, and Mauritsen, Thorsten. 2014. Mixed-phase clouds cause climate model biases in Arctic wintertime temperature inversions. Climate Dynamics, 43(1), 289303.Google Scholar
Plant, Robert S., and Yano, Jun-Ichi. 2015. Parameterization of Atmospheric Convection. Imperial College Press.Google Scholar
Plant, R. S., and Craig, George C. 2008. A stochastic parameterization for deep convection based on equilibrium statistics. Journal of Atmospheric Sciences, 65(1), 87105.Google Scholar
Pope, Stephen B. 2000. Turbulent Flows. Cambridge University Press.Google Scholar
Posselt, D. J., Stephens, G. L., and Miller, M. 2008. CloudSat: adding a new dimension to a classical view of extratropical cyclones. Bulletin of the American Meteorological Society, 89, 599609.Google Scholar
Pruppacher, H. R., and Klett, J. D. 2010. Microphysics of Clouds and Precipitation. Atmospheric and Oceanographic Sciences Library. Springer.Google Scholar
Quaas, Johannes. 2012. Evaluating the “critical relative humidity” as a measure of subgrid-scale variability of humidity in general circulation model cloud cover parameterizations using satellite data. Journal of Geophysical Research: Atmospheres, 117(D9).Google Scholar
Quaas, Johannes. 2015. Approaches to observe effects of anthropogenic aerosols on clouds and radiation. Current Climate Change Reports, 1, 297304.Google Scholar
Quaas, Johannes., Bony, S., Collins, W. D., et al. 2009. Current Understanding and Quantification of Clouds in the Changing Climate System and Strategies for Reducing Critical Uncertainties. MIT Press. Pages 557–73.Google Scholar
Quaas, Johannes., Stevens, B., Lohmann, U., and Stier, P. 2010. Interpreting the cloud cover – aerosol optical depth relationship found in satellite data using a general circulation model. Atmospheric Chemistry and Physics, 10, 6129–135.Google Scholar
Ramage, Colin S. 1971. Monsoon Meteorology. International Geophysics Series. Vol. 15. Academic Press.Google Scholar
Ramanathan, V., Cess, R. D., Harrison, E. F., et al. 1989. Cloud-radiative forcing and climate: results from the Earth radiation budget experiment. Science, 243(4887), 5763.Google Scholar
Randall, David A. 1980. Conditional instability of the first kind upside downocument. Journal of Atmospheric Sciences, 37, 125–30.Google Scholar
Randall, David. A. 2000. General Circulation Model Development: Past, Present, and Future. International Geophysics. Elsevier Science.Google Scholar
Randall, David. 2012. Atmosphere, Clouds and Climate. Princeton University Press.Google Scholar
Randall, David, DeMott, Charlotte, Stan, Cristiana, et al. 2016. Simulations of the tropical general circulation with a multiscale global model. Meteorological Monographs, 56, 15.1–15.15.Google Scholar
Randall, David A., Krueger, S. K., Bretherton, C. S., et al. 2003. Confronting models with data – The GEWEX Cloud Systems Study. Bulletin of the American Meteorological Society, 84, 455–69.Google Scholar
Randall, David A., Shao, Qingqiu, and Moeng, Chin-Hoh. 1992. A second-order bulk boundary-layer model. Journal of the Atmospheric Sciences, 49(20), 1903–23.Google Scholar
Raymond, David J., Sessions, Sharon L., Sobel, Adam H., and Fuchs, Željka. 2009. The mechanics of gross moist stability. Journal of Advances in Modeling Earth Systems, 1(3).Google Scholar
Rieck, M., Nuijens, L., and Stevens, B. 2012. Marine boundary layer cloud feedbacks in a constant relative humidity atmosphere. Journal of Atmospheric Sciences, 69(Aug.), 2538–50.Google Scholar
Riehl, H. 1954. Tropical Meteorology. McGraw-Hill.Google Scholar
Riehl, H., and Malkus, J. S. 1957. On the heat balance and maintenance of circulation in the trades. Quarterly Journal of the Royal Meteorological Society, 83, 21–9.CrossRefGoogle Scholar
Riehl, H., and Malkus, J. S. 1958. On the heat balance in the equatorial trough zone. Geophysica, 6(3–4), 503–37.Google Scholar
Riley, Emily M., Mapes, Brian E., and Tulich, Stefan N. 2011. Clouds associated with the Madden-Julian oscillation: a new perspective from CloudSat. Journal of the Atmospheric Sciences, 68(12), 3032–51.Google Scholar
Rogers, R. R., and Yau, M. K. 1996. A Short Course in Cloud Physics. Butterworth Heinemann. Page 290.Google Scholar
Romps, D. 2010. A direct measurement of entrainment. Journal of Atmospheric Sciences, 67, 1908–27.Google Scholar
Rosenfeld, D., Lohmann, U., Raga, G. B., et al. 2008. Flood or drought: how do aerosols affect precipitation? Science, 321, 1309–13.Google Scholar
Rossow, W. B., and Schiffer, R. A. 1999. Advances in understanding clouds from ISCCP. Bulletin of the American Meteorological Society, 80(11), 2261–87.Google Scholar
Rotstayn, L. D., and Lohmann, U. 2002. Tropical rainfall trends and the indirect aerosol effect. Journal of Climate, 15, 2103–16.Google Scholar
Society, Royal. 2009. Geoengineering the Climate – Science, Governance and Uncertainty. Royal Society Policy document.Google Scholar
Sakradzija, Mirjana, Seifert, Axel, and Heus, Thijs. 2015. Fluctuations in a quasi-stationary shallow cumulus cloud ensemble. Nonlinear Processes in Geophysics, 22(1), 6585.Google Scholar
Sanchez-Lorenzo, A., Laux, P., Hendricks-Franssen, H.-J., et al. 2012. Assessing large-scale weekly cycles in meteorological variables: a review. Atmospheric Chemistry and Physics, 12, 5755–71.Google Scholar
SCEP Study of Critical Environmental Problems. 1970. Man’s Impact on the Global Environment. The MIT Press.Google Scholar
Schalkwijk, J., Jonker, H. J. J., and Siebesma, A. P. 2013. Simple solutions to steady-state cumulus regimes in the convective boundary layer. Journal of Atmospheric Sciences, 70, 3656–72.Google Scholar
Schalkwijk, J., Jonker, H. J. J., Siebesma, A. P., and Van Meijgaard, E. 2015. Weather forecasting using GPU-based large-eddy simulations. Bulletin of the American Meteorological Society, 96, 715–23.Google Scholar
Schär, C., Vidale, P. L., Lüthi, D., et al. 2004. The role of increasing temperature variability in European summer heatwaves. Nature, 427, 332–6.Google Scholar
Schemann, Vera, Stevens, Bjorn, Grutzun, Verena, and Quaas, Johannes. 2013. Scale dependency of total water variance and its implication for cloud parameterizations. Journal of the Atmospheric Sciences, 70(11), 3615–30.Google Scholar
Schneider, S. H. 1972. Cloudiness as a global climate feedback mechanisms: the effects on the radiation balance and surface temperature of variations in cloudiness. Journal of Atmospheric Sciences, 29, 1413–22.2.0.CO;2>CrossRefGoogle Scholar
Schneider, Tapio, and Sobel, Adam H. 2007. The Global Circulation of the Atmosphere. Princeton University Press.Google Scholar
Schulz, J., Albert, P., Behr, H.-D., et al. 2009. Operational climate monitoring from space: the EUMETSAT Satellite Application Facility on Climate Monitoring (CM-SAF). Atmospheric Chemistry and Physics, 9(5), 1687–709.Google Scholar
Schumacher, Courtney, Zhang, Minghua H., and Ciesielski, Paul E. 2007. Heating structures of the TRMM field campaigns. Journal of the Atmospheric Sciences, 64(7), 2593–610.Google Scholar
Schwartz, Stephen E. 2011. Feedback and sensitivity in an electrical circuit: an analog for climate models. Climatic Change, 106(2), 315–26.Google Scholar
Schwartz, Stephen E. 2012. Determination of Earth’s transient and equilibrium climate sensitivities from observations over the twentieth century: strong dependence on assumed forcing. Surveys in Geophysics, 33, 745–77.Google Scholar
Seneviratne, S. I., Nicholls, N., Easterling, D., et al. 2012. Changes in Climate Extremes and Their Impacts on the Natural Physical Environment. In Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. Field, C. B., Barros, V., Stocker, T. F., et al. (eds). A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC). Cambridge University Press. Pages 109–230.Google Scholar
Seneviratne, S. I., Wilhelm, M., Stanelle, T., et al. 2013. Impact of soil moisture-climate feedbacks on CMIP5 projections: first results from the GLACE-CMIP5 experiment. Geophysical Research Letters, 40, 5212–17.Google Scholar
Shaw, T. A., Baldwin, M., Barnes, E. A., et al. 2016. Storm track processes and the opposing influences of climate change. Nature Geoscience, 9, 656–64.Google Scholar
Sherwood, Steven C., Bony, Sandrine, Boucher, Olivier, et al. 2015. Adjustments in the forcing-feedback framework for understanding climate change. Bulletin of the American Meteorological Society, 96(2), 217–28.Google Scholar
Sherwood, Steven C., Bony, Sandrine, and Dufresne, Jean-Louis. 2014. Spread in model climate sensitivity traced to atmospheric convective mixing. Nature, 505, 3742.Google Scholar
Shupe, M. D., Persson, P. O. G., Brooks, I. M., et al. 2013. Cloud and boundary layer interactions over the Arctic sea ice in late summer. Atmospheric Chemistry and Physics, 13(18), 9379–99.Google Scholar
Siebesma, A. Pier, Bretherton, C. S., Brown, A., et al. 2003. A large eddy simulation intercomparison study of shallow cumulus convection. Journal of the Atmospheric Sciences, 60(10), 1201–19.Google Scholar
Siebesma, A. Pier, and Cuijpers, J. W. M. 1995. Evaluation of parametric assumptions for shallow cumulus convection. Journal of Atmospheric Sciences, 52, 650–66.Google Scholar
Siebesma, A. Pier, Soares, Pedro M. M., and Teixeira, Joao. 2007. A combined eddy-diffusivity mass-flux approach for the convective boundary layer. Journal of the Atmospheric Sciences, 64(4), 1230–48.Google Scholar
Simmons, A. J., and Hollingsworth, A. 2002. Some aspects of the improvement in skill of numerical weather prediction. Quarterly Journal of the Royal Meteorological Society, 128(580), 647–77.Google Scholar
Simpson, J. 1973. The Global Energy Budget and the Role of Cumulus Clouds. NOAA Technical Memorandum ERL WMPO-8, Boulder, Colorado. ftp://ftp.library.noaa.gov/noaa_documents.lib/OAR/ERL_WMPO/TM_ERL_WMPO_8.pdf. Accessed 14/01/2020.Google Scholar
Smythe, W. R. 1962. Charged right circular cylinder. Journal of Applied Physics, 33(10), 2966.Google Scholar
Sobel, Adam H., and Bretherton, Christopher S. 2000. Modeling tropical precipitation in a single column. Journal of Climate, 13(24), 4378–92.Google Scholar
Soden, B. J., and Held, I. M. 2006. An assessment of climate feedbacks in coupled ocean-atmosphere models. Journal of Climate, 19(14), 3354–60.Google Scholar
Soden, Brian J., Held, Isaac M., Colman, Robert, et al. 2008. Quantifying Climate Feedbacks Using Radiative Kernels. Journal of Climate, 21(14), 3504–20.Google Scholar
Sommeria, G., and Deardorff, J. W. 1977. Subgrid-scale condensation in models of nonprecipitating clouds. Journal of the Atmospheric Sciences, 34(2), 344–55.Google Scholar
Stensrud, D. J. 2007. Parameterization Schemes: Keys to Understanding Numerical Weather Prediction Models. Cambridge University Press.Google Scholar
Stephens, Graeme L. 1994. Remote Sensing of the Lower Atmosphere: An Introduction. Oxford University Press.Google Scholar
Stephens, Graeme L. 2005. Cloud feedbacks in the climate system: a critical review. Journal of Climate, 18(2), 237–73.Google Scholar
Stephens, Graeme L., Brien, Denis O., Webster, Peter J., et al. 2015. The albedo of Earth. Reviews of Geophysics, 53(1), 141–63.Google Scholar
Stephens, Graeme L., Li, J., Wild, M., et al. 2012a. An update on Earth’s energy balance in light of the latest global observations. Nature Geoscience, 5, 691–6.Google Scholar
Stevens, B. 2005. Atmospheric moist convection. Annual Review of Earth and Planetary Sciences, 33(1), 605–43.Google Scholar
Stephens, Graeme L., L’Ecuyer, Tristan, Forbes, Richard, et al. 2010. Dreary state of precipitation in global models. Journal of Geophysical Research, 115(D24), D24211.Google Scholar
Stephens, Graeme L., Li, Juilin, Wild, Martin, et al. 2012b. An update on Earth’s energy balance in light of the latest global observations. Nature Geoscience, 5(10), 691–6.Google Scholar
Stevens, Bjorn. 2000. Quasi-steady analysis of a PBL model with an eddy-diffusivity profile and nonlocal fluxes. Monthly Weather Review, 128(03), 824–36.Google Scholar
Stevens, Bjorn. 2006. Bulk boundary-layer concepts for simplified models of tropical dynamics. Theoretical and Computational Fluid Dynamics, 20(5–6), 279304.Google Scholar
Stevens, Bjorn. 2007. On the growth of layers of nonprecipitating cumulus convection. Journal of Atmospheric Sciences, 64, 2916–31.Google Scholar
Stevens, Bjorn. 2015. Rethinking the lower bound on aerosol radiative forcing. Journal of Climate, 28, 4794–819.Google Scholar
Stevens, Bjorn, and Bony, Sandrine. 2013. Water in the atmosphere. Physics Today, 66(6), 29, https://doi.org/10.1063/PT.3.2009.CrossRefGoogle Scholar
Stevens, Bjorn, and Feingold, G. 2009. Untangling Aerosol Effects on Clouds and Precipitation in a Buffered System. Nature, 461, 607–13.Google Scholar
Stevens, Bjorn, Moeng, C.-H., Ackerman, A. S., et al. 2005. Evaluation of large-eddy simulations via observations of nocturnal marine stratocumulus. Monthly Weather Review, 133, 1443–62.Google Scholar
Stevens, Bjorn, and Schwartz, Stephen E. 2012. Observing and modeling Earth’s energy flows. Surveys in Geophysics, 33(3–4), 779816.Google Scholar
Stevens, Bjorn, Sherwood, Steven C., Bony, Sandrine, and Webb, Mark J. 2016. Prospects for narrowing bounds on Earth’s equilibrium climate sensitivity. Earth’s Future, 4(11), 512–22.Google Scholar
Stier, P. 2016. Limitations of passive remote sensing to constrain global cloud condensation nuclei. Atmospheric Chemistry and Physics, 16, 6595–607.Google Scholar
Stier, P., Feichter, J., Kinne, S., et al. 2005. The aerosol-climate model ECHAM5-HAM. Atmospheric Chemistry and Physics, 5, 1125–56.Google Scholar
Stohl, A., Aamaas, B., Amann, M., et al. 2015. Evaluating the climate and air quality impacts of short-lived pollutants. Atmospheric Chemistry and Physics, 15, 10529–66.Google Scholar
Straka, J. M. 2009. Cloud and Precipitation Microphysics: Principles and Parameterizations. Cambridge University Press.Google Scholar
Stubenrauch, C. J., Rossow, W. B., Kinne, S., et al. 2013. Assessment of global cloud datasets from satellites: project and database initiated by the GEWEX Radiation Panel. Bulletin of the American Meteorological Society, 94(7), 1031–49.Google Scholar
Stull, R. B. 1988. An Introduction to Boundary Layer Meteorology. Kluwer Academic Publishers.Google Scholar
Sušelj, Kay, Teixeira, João, and Chung, Daniel. 2013. A unified model for moist convective boundary layers based on a stochastic eddy-diffusivity/mass-flux parameterization. Journal of Atmospheric Sciences, 70(7), 1929–53.Google Scholar
Suzuki, K., Stephens, G., van den Heever, S., and Nakajima, T. 2011. Diagnosis of the warm rain process in cloud-resolving models using joint CloudSat and MODIS observations. Journal of Atmospheric Sciences, 68, 2655–70.Google Scholar
Tao, W.-K., and Adler, R. 2013. Cloud Systems, Hurricanes, and the Tropical Rainfall Measuring Mission (TRMM): A Tribute to Joanne Simpson. Meteorological Monographs. Vol. 29. American Meteorological Society.Google Scholar
Tao, W.-K., Chen, J.-P., Li, Z., Wang, C., and Zhang, C. 2012. Impact of aerosols on convective clouds and precipitation. Reviews of Geophysics, 50, RG2001.Google Scholar
Tawfik, A. B., and Dirmeyer, P. A. 2014. A process-based framework for quantifying the atmospheric preconditioning of surface-triggered convection. Geophysical Research Letters, 41, 173–8.Google Scholar
Taylor, K. E. 2001. Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research, 106, 7183–92.Google Scholar
Teixeira, J., Cardoso, S., Bonazzola, M., et al. 2011. Tropical and subtropical cloud transitions in weather and climate prediction models: the GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI). Journal of Climate, 24(20), 5223–56.Google Scholar
Tennekes, H. 1973. A model for the dynamics of the inversion above a convective layer. Journal of Atmospheric Sciences, 30, 558–67.Google Scholar
Thorsen, Tyler J., Fu, Qiang, and Comstock, Jennifer M. 2013. Cloud effects on radiative heating rate profiles over Darwin using ARM and A-train radar/lidar observations. Journal of Geophysical Research: Atmospheres, 118(11), 5637–54.Google Scholar
Tiedtke, M. 1989. A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Monthly Weather Review, 117(8), 17791800.Google Scholar
Tiedtke, M. 1993. Representation of clouds in large-scale models. Monthly Weather Review, 121(11), 3040–61.Google Scholar
Tjernström, M., Leck, C., Birch, C. E., et al. 2014. The Arctic Summer Cloud Ocean Study (ASCOS): overview and experimental design. Atmospheric Chemistry and Physics, 14(6), 2823–69.Google Scholar
Tomita, H., Miura, H., Iga, S., Nasuno, T., and Satoh, M. 2005. A global cloud-resolving simulation: preliminary results from an aqua planet experiment. Geophysical Research Letters, 32(8), L08805.Google Scholar
Tompkins, A. M. 2002. A prognostic parameterization for the subgrid-scale variability of water vapor and clouds in largescale models and its use to diagnose cloud cover. Journal of Atmospheric Sciences, 59, 1917–42.Google Scholar
Trenberth, K. E., and Fasullo, J. T. 2010. Simulation of present-day and twenty-first century energy budgets of the Southern Ocean. Journal of Climate, 23, 440–54.Google Scholar
Trenberth, Kevin E., Fasullo, John T., and Kiehl, Jeffrey. 2009. Earth’s global energy budget. Bulletin of the American Meteorological Society, 90(3), 311–23.Google Scholar
Troen, I. B., and Mahrt, L. 1986. A simple model of the atmospheric boundary layer; sensitivity to surface evaporation. Boundary-Layer Meteorology, 37(1), 129–48.Google Scholar
Tselioudis, George, and Jakob, C. 2002. Evaluation of midlatitude cloud properties in a weather and a climate model: dependence on dynamic regime and spatial resolution. Journal of Geophysical Research, 107(D24), 4781.Google Scholar
Tselioudis, George, Lipat, B. R., Konsta, D., Grise, K. M., and Polvani, L. M. 2016. Midlatitude cloud shifts, their primary link to the Hadley cell, and their diverse radiative effects. Geophysical Research Letters, 43, 4594–601.Google Scholar
Tselioudis, George, and Rossow, W. B. 2006. Climate feedback implied by observed radiation and precipitation changes with midlatitude storm strength and frequency. Geophysical Research Letters, 33, L02704.Google Scholar
Tselioudis, George, Rossow, William, Zhang, Yuanchong, and Konsta, Dimitra. 2013. Global weather states and their properties from passive and active satellite cloud retrievals. Journal of Climate, 26(19), 7734–46.Google Scholar
Tselioudis, George, Zhang, Y., and Rossow, W. B. 2000. Cloud and radiation variations associated with northern midlatitude low and high sea level pressure regimes. Journal of Climate, 13, 312–27.Google Scholar
Twomey, S. 1974. Pollution and the planetary albdeo. Atmospheric Environment, 8, 1251–8.Google Scholar
Twomey, S. 1977. The influence of pollution on the shortwave albedo of clouds. Journal of Atmospheric Sciences, 34, 1149–52.Google Scholar
Uttal, Taneil, Curry, Judith A., Mcphee, Miles G., et al. 2002. Surface heat budget of the Arctic Ocean. Bulletin of the American Meteorological Society, 83(2), 255–75.Google Scholar
Vallis, Geoffrey K. 2006. Atmospheric and Ocean Fluid Dynamics: Fundamentals and Large-Scale Circulation. Cambridge University Press.Google Scholar
Vallis, Geoffrey K., Zurita-Gotor, P., Cairns, C., and Kidston, J. 2015. Response of the large-scale structure of the atmosphere to global warming. Quarterly Journal of the Royal Meteorological Society, 141, 1479–501.Google Scholar
van de Hulst, H. C. 1980. Light Scattering by Small Particles. Dover Publications.Google Scholar
van der Ent, R. J., Savenije, H. H. G., Schaefli, B., and Steele-Dunne, S. C. 2010. Origin and fate of atmospheric moisture over continents. Water Resources Research, 46(9).Google Scholar
van Heerwaarden, C. C., and Vilà Guerau de Arellano, J. 2008. Relative humidity as an indicator for cloud formation over heterogeneous land surfaces. Journal of Atmospheric Sciences, 65, 3263–77.Google Scholar
vanZanten, M. C., Duynkerke, P. G., and Cuijpers, J. W. M. 1999. Entrainment parameterization in convective boundary layers. Journal of Atmospheric Sciences, 56, 813–28.Google Scholar
Vial, Jessica, Dufresne, Jean-Louis, and Bony, Sandrine. 2013. On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Climate Dynamics, 41(11–12), 3339–62.Google Scholar
Vihma, T., Pirazzini, R., Fer, I., et al. 2014. Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review. Atmospheric Chemistry and Physics, 14(17), 9403–50.Google Scholar
Vilà-Guerau de Arellano, J., van Heerwaarden, C. C., van Stratum, B. J. J., and van den Dries, K. 2015. Atmospheric Boundary Layer: Integrating Air Chemistry and Land Interactions. Cambridge University Press.Google Scholar
Voigt, Aiko, Stevens, Bjorn, Bader, Jürgen, and Mauritsen, Thorsten. 2013. The observed hemispheric symmetry in reflected shortwave irradiance. Journal of Climate, 26(2), 468–77.Google Scholar
Wakimoto, R. M., and Srivastava, R. 2003. Radar and Atmospheric Science: A Collection of Essays in Honor of David Atlas. Meteorological Monographs. Vol. 30. American Meteorological Society.Google Scholar
Walker, Christopher C., and Schneider, Tapio. 2006. Eddy influences on Hadley circulations: simulations with an idealized GCM. Journal of the Atmospheric Sciences, 63(12), 3333–50.Google Scholar
Webb, M., Senior, C., Bony, S., and Morcrette, J.-J. 2001. Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models. Climate Dynamics, 17, 905–22.Google Scholar
Weitkamp, Claus. 2005. Lidar: Range-Resolved Optical Remote Sensing of the Atmosphere. Springer.Google Scholar
Wendisch, M., and Brenguier, J.-l. (eds). 2013. Airborne Measurements for Environmental Research: Methods and Instruments. Wiley-VCH Verlag GmbH & Co, Weinheim.Google Scholar
Westbrook, C. D., Hogan, R. J, and Illingworth, A. J. 2008. The capacitance of pristine ice crystals and aggregate snowflakes. Journal of Atmospheric Sciences, 65, 206–19.Google Scholar
Wexler, H. 1936. Cooling in the lower atmosphere and the structure of polar continental air. Monthly Weather Review, 64(4), 122–36.Google Scholar
Wheeler, Matthew C., and Hendon, Harry H. 2004. An all-season real-time multivariate MJO index: development of an index for monitoring and prediction. Monthly Weather Review, 132(8), 1917–32.Google Scholar
Wild, Martin, Folini, Doris, Hakuba, Maria Z., et al. 2015. The energy balance over land and oceans: an assessment based on direct observations and CMIP5 climate models. Climate Dynamics, 44(11), 3393–429.Google Scholar
Wild, Martin, Gilgen, H., Roesch, A., et al. 2005. From dimming to brightening: decadal changes in solar radiation at Earth’s surface. Science, 308, 847–50.Google Scholar
Wilks, D. S. 2011. Statistical Methods in the Atmospheric Sciences. Elsevier.Google Scholar
Williams, K. D., Bodas-Salcedo, A., Déqué, M., et al. 2013. The Transpose-AMIP II Experiment and its application to the understanding of Southern Ocean cloud biases in climate models. Journal of Climate, 26(10), 3258–74.Google Scholar
Wilson, D. K. 2001. An alternative function for the wind and temperature gradients in unstable surface layers. Boundary-Layer Meteorology, 99, 151–8.Google Scholar
Wing, A. A., Emanuel, K., Holloway, C. E., and Muller, C. 2017. Convective self-aggregation in numerical simulations: a review. Surveys in Geophysics, 38, 1173–97.Google Scholar
WMO. 2017. International Cloud Atlas: Manual on the Observation of Clouds and Other Meteors. https://cloudatlas.wmo.int/home.html. Accessed 13/11/2017.Google Scholar
Wood, R. 2007. Cancellation of aerosol indirect effects in marine stratocumulus through cloud thinning. Journal of the Atmospheric Sciences, 64, 2657–69.Google Scholar
Wood, R. 2012. Stratocumulus clouds. Monthly Weather Review, 140, 2373–423.Google Scholar
Wood, R., and Bretherton, C. S. 2004. Boundary layer depth, entrainment, and decoupling in the cloud-capped subtropical and tropical marine boundary layer. Journal of Climate, 17, 3576–88.Google Scholar
Wood, R., Field, Paul R., and Cotton, W. R. 2002. Autoconversion rate bias in stratiform boundary layer cloud parameterizations. Atmospheric Research, 65(1), 109–28.Google Scholar
Wood, R., and Field, Paul R. 2011. The distribution of cloud horizontal sizes. Journal of Climate, 24(18), 4800–16.Google Scholar
Wyant, Matthew C., Bretherton, Christopher S., Chlond, Andreas, et al. 2007. A single-column model intercomparison of a heavily drizzling stratocumulus-topped boundary layer. Journal of Geophysical Research, 112(D24), D24204 -n/a.Google Scholar
Wyngaard, John C. 2010. Turbulence in the Atmosphere. Cambridge University Press.Google Scholar
Yanai, Michia, Esbensen, Steven, and Chu, Jan-Hwa. 1973. Determination of bulk properties of tropical cloud clusters from large-scale heat and moisture budgets. Journal of the Atmospheric Sciences, 30, 611–27.Google Scholar
Zelinka, Mark D., and Hartmann, Dennis L. 2010. Why is longwave cloud feedback positive? Journal of Geophysical Research, 115(D16).Google Scholar
Zelinka, Mark D., Klein, Stephen A., and Hartmann, Dennis L. 2012. Computing and Partitioning cloud feedbacks using cloud property histograms. Part II: attribution to changes in cloud amount, altitude, and optical depth. Journal of Climate, 25(11), 3736–54.Google Scholar
Zelinka, Mark D., Klein, Stephen A., Taylor, Karl E., et al. 2013. Contributions of different cloud types to feedbacks and rapid adjustments in CMIP5. Journal of Climate, 26(14), 5007–27.Google Scholar
Zhang, Chidong. 2005. Madden-Julian oscillation. Reviews of Geophysics, 43(2).Google Scholar
Zhang, Guang J. 2002. Convective quasi-equilibrium in midlatitude continental environment and its effect on convective parameterization. Journal of Geophysical Research: Atmospheres, 107(D14), ACL 12-1– ACL 12 –16.Google Scholar
Zhang, Guang J. 2003. Convective quasi-equilibrium in the tropical western Pacific: comparison with midlatitude continental environment. Journal of Geophysical Research: Atmospheres, 108(D19).Google Scholar
Zhang, M., Bretherton, C. S., Blossey, P. N., et al. 2013. CGILS: results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in single column models. Journal of Advances in Modeling Earth Systems, 5(4), 826–42.Google Scholar
Zipser, Edward. 1969. The role of organized unsaturated downdrafts in the structure and rapid decay of an equatorial disturbance. Journal of Applied Meteorology, 8, 799814.Google Scholar
Zygmuntowska, M., Mauritsen, T., Quaas, J., and Kaleschke, L. 2012. Arctic Clouds and Surface Radiation – a critical comparison of satellite retrievals and the ERA-Interim reanalysis. Atmospheric Chemistry and Physics, 12(14), 6667–77.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×