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M. Antonelli and R. Rotunno

, complex coastal orography, the Coriolis force, turbulence, cloud cover, and others (for a recent review of observational work see Miller et al. 2003 ). In the present work, we take a small step toward greater realism by using a model capable of simulating three-dimensional turbulence to study the sea-breeze circulation. More specifically, we have used a model that can simulate the mesoscale sea-breeze circulation together with the small-scale turbulent convective boundary layer flow over the land

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George Gutman

zonally-averaged steady-state hemispheric mean-annual climate model is used for conducting a series ofexperiments on land surface alterations: desertification, deforestation and irrigation. In each experiment afixed perturbation of surface albedo and water availability is imposed in a single latitude belt (but a differentperturbation is specified in each experiment). The desertification and deforestation experiments simulatemodifications to the geobotanic state due to destruction of vegetation by

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T. J. Schmugge and G. M. Schmidt

Kalluri and Dubayah (1995) in their papers. This study examines how well satellite observations of thermal infrared radiation from the land surface can be corrected for atmospheric effects. The satellite data are from the Advanced Very High Resolution Radiometer (AVHRR) sensor on the NOAA-9 satellite duringFIFE in 1987. The MODTRAN3 path radiance model ( Kniezys et al. 1988 ) was used with radiosoundings launched during FIFE to calculate the atmospheric path radiance and transmission. The corrected

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Katrina S. Virts, John M. Wallace, Michael L. Hutchins, and Robert H. Holzworth

of land surfaces during the less-cloudy MJO break period could lead to more intense convection and more lightning, a mechanism previously suggested by Sui and Lau (1992) and Kodama et al. (2006) . To test the validity of this mechanism and extend it to wind, we attempt to predict MJO-related anomalous lightning frequency using the relationships between lightning and low-level winds and cloudiness documented in section 3 . At each grid point, for each MJO phase, the following linear prediction

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Jordan L. Sutton, Conway B. Leovy, and James E. Tillman

, ambient and surface temperatures from both Viking Landers have been used to computebulk Richardson numbers and Monin-Obukhov lengths during the earliest phase of the Mars missions.These parameters are used to estimate drag and heat transfer coefficients, friction velocities and surfaceheat fluxes, at the two sites. The principal uncertainW is in the specification of the roughness length.Maximum heat fiuxe~ occur near local noon at both sites, and are estimated to be in the range 15-20 W m-~at the

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Richard W. Zurek and Robert M. Haberle

)ABSTRACT We have computed a steady state, zonally symmetric response of an atmospheric circulation to the combinedeffects of the very large zonal-mean diabatic heating and thermotidal forcing thought to exist in the dustyMartian atmosphere during one of its episodic global dust storms. The zonal-mean components of the tidalfiux-convergences of momentum and heat are computed using an existing classical atmospheric tidal modelconstrained by the surface pressure observations at the two Viking Lander

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Hannu Savijärvi and Tero Siili

winds, and the nocturnal low-level jets werestudied using Prandtl's theory, a mesoscale numerical model, and Viking lander observations. During moderateprevailing large-scale flow, nocturnal jets were simulated that were rather similar to those on Earth. They weremainly caused by inertial oscillation after sunset with some contribution from the slope wind effects over slopingregions (which are very common in Mars). During weak large-scale flow, shallow nocturnal drainage flows withstrong vertical

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Edward N. Lorenz and Kerry A. Emanuel

and land surfaces to allow some chance that the relative merits of various strategies will be properly indicated. In particular, it should behave chaotically; otherwise the forecasting problem will virtually disappear, and the experiments will have little meaning. We shall presently see that the use of simple models can at the very least cast doubt upon certain general approaches whose study with a large model would be rather time-consuming. At the same time, we cannot be certain of the extent

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C. D. Peters-Lidard, E. Blackburn, X. Liang, and E. F. Wood

. Soil thermal conductivity can be a difficult parameter to estimate, since it depends not only on the volumetric water content, but also on mineral composition (particularly quartz content), porosity, dry density, and temperature ( Farouki 1986 ). Table 1 illustrates the range in thermal conductivity and other thermal properties for various soil constituents. In the land surface parameterization literature, the most commonly used formulation for predicting soil thermal conductivity is that of

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Edward G. Patton, Peter P. Sullivan, and Chin-Hoh Moeng

specifying the surface fluxes (which completely decouples the forcing from the overlying atmosphere), Albertson and Parlange (1999) , Albertson et al. (2001) , and Kustas and Albertson (2003) investigated land surface heterogeneity using specified surface temperature and moisture. None of these studies used a dynamically coupled system where the soil responds to the atmosphere and vice versa. Point measurements are potentially impacted by landscape-induced organized motions ( Finnigan et al. 2003

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