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Mark J. Rodwell and Brian J. Hoskins

paper is used to investigate the mechanisms that sustain thelow-level East African jet. The East African Highlands and a land/sea contrast in surface friction are shown tobe essential for the existence and concentration of cross-equatorial flow. The question of inertial instability asair crosses the equator is addressed from a potential vorticity (PV) perspective. Surface friction and local diabaticheating provide mechanisms for material modification of PV and both are important for the maintenance

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Y. Hayashi and D. G. Golder

planetary waves in the tropics, the effects of topography,midlatitude disturbances and condensational heat are eliminated one by one from a GFDL general circulation model during the period June and July. The time development and three-dimensional propagationof waves are examined by a space-time spectral analysis using the maximum entropy method. It is found that the characteristic scale and period of Kelvin and mixed Rossby-gravity waves do notdepend on land-sea contrast or the zonal variation of sea

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Surabi Menon, Anthony D. Del Genio, Dorothy Koch, and George Tselioudis

multiple regression relationships to predict N for land, N Land , and ocean, N Ocean , are where sulfate, OM, and sea salt are the mass concentrations in μ g m −3 and N is in cm −3 ; N predicted using the above equations is more sensitive to changes in sulfate than to OM due to the higher slope for sulfates, however, the AIE has not been evaluated separately for either sulfates or OM alone. These regressions differ from the commonly used empirical relationships given in Boucher and Lohmann

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E. A. Smith, J. E. Lamm, R. Adler, J. Alishouse, K. Aonashi, E. Barrett, P. Bauer, W. Berg, A. Chang, R. Ferraro, J. Ferriday, S. Goodman, N. Grody, C. Kidd, D. Kniveton, C. Kummerow, G. Liu, F. Marzano, A. Mugnai, W. Olson, G. Petty, A. Shibata, R. Spencer, F. Wentz, T. Wilheit, and E. Zipser

to use the results from the different algorithms to form a “consensus” algorithm. This product was then evaluated by a GPCP merged rain gauge dataset over land and a west Pacific atoll rain gauge dataset over ocean; see Morrissey et al. (1994) for a description of the PIP-1 validation datasets. Of the 17participating algorithms, 16 were designed for application with SSM/I measurements, while the algorithm of Spencer (1993) was designed for measurements from the National Oceanic Atmospheric

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Pragallva Barpanda and Tiffany Shaw

(1999) ]. The SH exhibits a much weaker seasonal evolution of stationary eddy MSE flux ( Fig. 2d ) consistent with its smaller land area. The seasonal evolution of the MSE flux in the NCEP reanalysis is robust when compared to ERA-Interim ( Dee et al. 2011 ) covering the period 1979–2015 (cf. Figs. 2 and 3 with Figs. B1 and B2 ). The NCEP reanalysis data are used to examine storm-track shifts in response to seasonal insolation and the El Niño–Southern Oscillation (ENSO). The ENSO response is

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G. J. Steeneveld, B. J. H. van de Wiel, and A. A. M. Holtslag

-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) mesoscale model (MM5), version 3.5, with U.S. Geologic Survey (USGS) land use classification] for the CASES-99 campaign for 23–26 October 1999. We use both the first-order closure model with prescribed diffusion profile form, medium-range forecast (MRF) ( Hong and Pan 1996 ), and a 1.5-order TKE- l closure model, ETA ( Janjić 1990 ). Horizontal resolution is set to 1 km for the innermost grid nest (in total three nested

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Russell Qualls and Thomas Hopson

) allows the use of (3) to estimate H from land surfaces by means of remotely sensed surface temperatures and ground-based measurements of wind speed, air temperature, and an estimate of atmospheric stability. A simplified form of this method, in which χ = LAI and β = 1, has been applied with surface temperatures obtained from TIMS over FIFE on 11 July1987 by Qualls and Brutsaert (1996a) . Here, the more complete method where χ is given by (8) is applied to as many as 20 surface flux

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Robert G. Gallimore

predicted atmosphericwater vapor used in the determination of the solar and longwave fluxes; 2) a land albedo and surface energybudget dependency on explicit model calculations of snowfall, snow melt and snow accumulation; 3) a'lapserate dependency for the Iongwave emission, sensible heating and mean energy transport; and 4) separatespecification for mean and eddy energy and water vapor transports. . The sensitivity of the model energy and water vapor budgets is similar to that obtained

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Xiping Zeng, Wei-Kuo Tao, Minghua Zhang, Christa Peters-Lidard, Stephen Lang, Joanne Simpson, Sujay Kumar, Shaocheng Xie, Joseph L. Eastman, Chung-Lin Shie, and James V. Geiger

snowpack density), canopy water content, and the energy flux and water flux terms of the surface energy and surface water balances. The LSM land surface parameters were initialized with University of Maryland 1-km datasets for vegetation and land–sea masks ( Hansen et al. 2000 ). Climatological datasets were ingested in order to initialize other vegetation parameters such as albedo and green vegetation fraction. Soils types were set using the State Soil Geographic Database for State ( Soil Survey Staff

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Jeffrey D. Kepert

left-rear quadrant, not the right front as his theory predicts. Thus while the vertical structure of the asymmetry suggests that frictional processes are governing the form of the asymmetry, it is clearly not being generated by the motion-induced surface-friction asymmetry. This structure will later be shown to be produced by asymmetric friction due to the proximity to land. d. Wind reduction factor The horizontal wind analyses were used to calculate the wind reduction factor (WRF), that is, the

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