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Winston C. Chao

1. Introduction The simulation of the precipitation diurnal cycle (PDC) over land using traditional general circulation models 1 (GCMs) has been a long-standing challenge. Over most of the land, in less mountainous regions of the globe, the simulated PDC in traditional GCMs exhibits a peak around noon, 4–6 h ahead of the observed cycle ( Randall et al. 1991 ; Dai et al. 1999 ; Bechtold et al. 2004 ; Lee et al. 2007b ; among many others). Also, the amplitude of the simulated PDC is too weak

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William J. Moroz

land the depth of the layer of onshore flow is approximately 750 m and a maximum velocity of5-7 m sec-~ is observed within 250 m of the surface directly over the lake shore. Above the lake breeze current a well defined return flow is apparent by midafternoon. The layer of returnflow is about twice as deep as the lake breeze and velocities in the return flow are proportionately lower.The local wind system extends through a depth exceeding 2500 m. Using climatological records it is demonstrated

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Aiguo Dai and Junhong Wang

correlated with DTR, suggesting that sensible heat flux is a major forcing for S 1 over land areas. In section 2 , we describe the datasets used in this study. Harmonic and zonal harmonic analysis methods are described in section 3 . The global distributions of S 1 and S 2 , their seasonal variations, and zonal wave components are presented and compared with earlier studies in section 4 . In section 5 we compare the seasonal and spatial patterns of S 1 and S 2 with those of atmospheric

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Charles L. Martin and Roger A. Pielke

a linear analytic model and a nonlinear numerical model, the adequacy of the hydrostatic modelis investigated for use in the simulation of sea and land breezes over fiat terrain. Among the results it isfound that for a given horizontal scale of heating, the hydrostatic assumption becomes less valid as theintensity of surface heating increases, and as the synoptic temperature lapse rate becomes less stable. Thespatial scale at which the hydrostatic assumption fails is substantially' smaller than

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Werner Alpers, Jen-Ping Chen, I-I. Lin, and Chun-Chi Lien

fronts in the marine boundary layer by using SAR images acquired from aircraft and satellites. They include synoptic-scale wind fronts ( Ivanov et al. 2004 ; Young et al. 2005 ), land breeze fronts ( Sikora et al. 1996 ; Winstead and Mourad 2000 ), and katabatic wind fronts ( Alpers et al. 1998 ). In this paper, we investigate alongshore coastal atmospheric fronts off the east coast of Taiwan by using SAR images of the sea surface acquired by the European Remote Sensing Satellites ERS-1 and ERS

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Donald E. Strebel, David R. Landis, K. Fred Huemmrich, Jeffrey A. Newcomer, and Blanche W. Meeson

1. Introduction The First International Satellite Land Surface Climatology Project Field Experiment (FIFE) occurred at a time when concepts and technology for handling field experiment data and information were rapidly changing. During the course of the experiment, it became possible to communicate routinely to an international group of investigators via e-mail, to use the Internet to remotely and interactively query a large online database and download query results, and to produce a permanent

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John E. Walsh

. Anexamination of the model results in Section 3 showsthat the model produces a realistic sea breeze despitethe simplified treatment of diffusion. The results canthen be used in a variety of applications, among whichis a study of the role played by the sea breeze in thegeneral circulation. The scaling of the velocity components is such thatone can determine the land-sea temperature differencerequired to create a net onshore ffow in the presence ofan offshore gradient wind. Such a relationship is

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Yu Du and Richard Rotunno

during the Joint Air–Sea Monsoon Interaction Experiment (JASMINE; Webster et al. 2002 ). Gille et al. (2005) , using four-times-daily sea surface winds, found that the diurnal perturbations of sea surface winds propagate progressively offshore at speeds ranging from 2 to 15 m s −1 , resembling gravity waves. Yang and Slingo (2001) using brightness temperatures from multiple satellites, found that a strong signal over land in the tropics, such as in the diurnal cycles of convection, cloudiness and

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Michael D. Fromm, Lanning M. Penn, John J. Cahir, and Hans A. Panofsky

, independentof previous models, that produces the greatest improvement in the fraction of variance explained. Theprocedure terminates when further substantial improvement is not possible.5-.'a. Predictors The predictors tested on the monthly mean fieldsare listed in Table 1. The variable P is a PlanckTABLE 1. Predictors of IR flux and albedo. Letters in parentheses indicate whether used for land (l), ocean (o), or both (b).Predictorsymbol U nits DescriptionT, (I

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Clark J. Weaver, Paul Ginoux, N. Christina Hsu, Ming-Dah Chou, and Joanna Joiner

TOMS AI over part of the Sahara (29°–33°N, 5°W–15°E) using data from July 1985. The approach was to bin both the TOMS AI and ERBE fluxes onto 1° latitude by 1° longitude grids. Data from the High Resolution Infrared Radiation Sounder (HIRS) instrument (which flew on the same satellite as ERBE) was used to remove points contaminated by clouds and high water vapor. The remaining clear sky data points were sorted by the underlying surface (land vs ocean) and linearly regressed. The slope, ∂ F ERBE

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