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J. R. Garratt

horizontalmomentum is transferred from atmosphere to surfaceto be calculated. Taylor actually used wind observations made overSalisbury Plain and, utilizing his theory of eddy motionin the atmosphere (Taylor, 1915), derived a coefficientof '~2-3X 10-s. Sutcliffe also used pilot balloon windobservations made over similar countryside and calculated the ageostrophic wind components, yielding acoefficient ~ 4-7 X 10-a. A similar method gave 0.4 X 10-afrom observations over the sea. In the succeeding years

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Robert A. Houze Jr.

the western North Pacific Ocean, and cyclones in the South Pacific and Indian Oceans. They are all the same phenomenon. Gray (1968) identified most of the environmental factors favoring tropical cyclones. They originate over oceans, as their primary energy source is the latent heat of water vapor in the atmospheric boundary layer. They nearly always form over regions where the sea surface temperature (SST) exceeds 26.5°C ( Fig. 1a ). Once tropical cyclones form, they tend to be advected by the

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Dayton G. Vincent

,.:~ .~ ~~:~'~ ... ~ ~.. ~ .'~ ..~ :~~:.~?? _~::~?? .?.~~ /: o ;~0 ~$?OE IZtO I-~ 180 IS'O I,,~ V ' ~1 FIG. 1. Schematic view of the main convergence zones, the ITCZand SPCZ, along with the annual mean sea level pressure contoursand surface wind streamlines. (Extracted from Trenberth 1991a.) 'of low-level moisture convergence, between the predominantly northeasterly flow west of the eastern Pacific subtropical

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Roland A. Madden and Paul R. Julian

momentum. The oscillation is an important factor in the timing of active and break phasesof the Indian and Australian monsoons. It affects ocean waves, currents, and air-sea interaction. The oscillationwas particularly active during the First GARP (Global Atmospheric Research Program) Global Experiment year,and some features that were evident during the Monsoon Experiment are described.1o Introduction Reviewing the literature on the phenomenon that we(Madden and Julian 1971) called the 40-50-day

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Robert Wood

lower-tropospheric stability, which is markedly higher during winter ( Klein and Hartmann 1993 ). The summertime maximum has been attributed to warmer temperatures and therefore greater moisture availability over the melting sea ice ( Hermann and Goody 1976 ), but dissipation of clouds during wintertime through ice formation at colder temperatures has also been hypothesized to contribute to their seasonal cycle ( Beesley and Moritz 1999 ). 2) Synoptic variability The thickness and coverage of

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Peter Jan van Leeuwen

sea ice strength parameters during a 2-yr assimilation experiment in a finite-element model of the Arctic Ocean, both in space and time. Real sea ice concentration observations were used from the Special Sensor Microwave Imager (SSM/I) satellite instrument together with sea ice drift observations from the Quick Scatterometer (QuikSCAT). Only 32 particles were used to obtain results that converged when the localization area was made small enough and observation errors were large enough. A strong

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John Molinari and Michael Dudek

areavailable to be advected horizontally and verticallyduring subsequent time steps. It is possible empiricallyto simulate the evolution of vertical motion and stability with a traditional approach, so that the cumulusparameterization produces an appropriate updraftdowndraft couplet on the grid scale in the correct timeperiod (Molinari and Corsetti 1985). Once this occursin a model with traditional cumulus parameterization,however, the explicit formulation must then spin upcloud water and ice, as well as

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Bogdan Antonescu, David M. Schultz, Fiona Lomas, and Thilo Kühne

waterspouts would be restrictive for some European countries. Several countries have a large part of their landscape covered by lakes (e.g., 187 000); others countries contain peninsulas (e.g., southern Italy). Other countries consist entirely of a single island (e.g., Malta in the Mediterranean Sea) or comprise archipelagos (e.g., Greece has more than a thousand islands). To accommodate these countries, in this article, the following tornado definition adapted from Rauhala et al. (2012) is used: a

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Markus Gross, Hui Wan, Philip J. Rasch, Peter M. Caldwell, David L. Williamson, Daniel Klocke, Christiane Jablonowski, Diana R. Thatcher, Nigel Wood, Mike Cullen, Bob Beare, Martin Willett, Florian Lemarié, Eric Blayo, Sylvie Malardel, Piet Termonia, Almut Gassmann, Peter H. Lauritzen, Hans Johansen, Colin M. Zarzycki, Koichi Sakaguchi, and Ruby Leung

). Figure 1a schematically shows the variety of model components and the different aspects of discretizing them in both space and time, as well as the coupling between them. For simplicity, Fig. 1a includes only two component models: the atmosphere and the ocean. However, modeling systems often include a large number of other components, such as land, glacier, sea ice, atmospheric chemistry, and ocean biogeochemistry models. These components are inherently coupled to each other through the momentum

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Daniel Keyser and M. A. Shapiro

force. The significant role of rotation infronts distinguishes them from a number of relatedphenomena in which divergence is dominant, such asinternal gravity waves, gravity or density currents andsquall lines. Furthermore, lineal phenomena generatedprimarily through localized surface-based differentialheating rather than synoptic-scale deformation (e.g.,sea-breeze fronts) usually are excluded from dynamicalconsiderations of fronts. The time scale in which frontsform from "smooth" synoptic

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