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Ronald L. Holle and Michael W. Maier

had spawned the tornado. The life cycle of the tornado and a period of 90 rain surrounding its occurrence'are studied in detail from observed surface winds, radar refiectivity and surface- rain gage data. The evolution of the parent cloud and tornado in a tropical thermodynamic environmentwith local forcing, weak shear and winds, and a potentially unstable sounding contrasts with the conditionsthat accompany large-scale forcing of the parent clouds in which extratropical tornadoes are found

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Song-You Hong and Hua-Lu Pan

computation of precipitation were taken directly from the larger-scale, global medium-range forecast model (MRF) within which the RSM is nested. The MRF physics algorithms are described in Kanamitsu (1989) , Kanamitsu et al. (1991) , and their subsequent developments are presented by Pan and Wu (1995) , and Hong and Pan (1996) . When a prediction model, such as the RSM, can resolve processes with horizontal scale less than 50 km, neglecting the storage of water as cloud droplets may become an

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Jonathan E. Martin

deformation in forcing the thermal evolution, and cloud and precipitation distribution, of the postmature phase midlatitude cyclone. The analysis begins with a brief review of the various forms of the Q–G omega equation in section 2 . We then offer a derivation of the separate vorticity and deformation contributions to Q s (the rotational component of the Q–G vector frontogenesis function) in section 3 . Examples of the separation of these two rotational components in the three cyclones

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Graeme L. Stephens and Norman B. Wood

themselves. (iii) A surprising result that emerged from the analysis of the study was that the cloud structures associated with the majority of cases of observed precipitation (ranging from 45% to 53% of all precipitation-connected radar reflectivity profiles) indicated multilayered structures regardless of the mode of synoptic forcing. The predominant multilayered cloud mode was of higher-level cirrus of varying thickness overlying cumulus congestus–like convection below. This

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Jean-Jacques Morcrette

1. Introduction All general circulation models (GCMs) used for climate studies or weather forecasts have a representation of radiation transfer and a description of cloudiness, either diagnostic or prognostic. Most, if not all, GCMs also have a simplified description of the cloud–radiation interactions. Due to the computational cost of the various radiation transfer codes, the radiative forcing is usually computed less frequently than the dynamics or the other physical processes. In the past

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Nettie R. Arnott, Yvette P. Richardson, Joshua M. Wurman, and Erik M. Rasmussen

skill in summer quantitative precipitation forecasts (QPF) than in winter QPF ( Parsons et al. 2001 ). One reason for this low skill is the typical occurrence of convective events on scales less than the grid spacing for operational models. Hence, the processes forcing these events must be parameterized. Cloud-resolving models have finer grid spacing but incomplete available measurements of the boundary layer water vapor and wind fields, which are crucial for predicting convection and precipitation

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Jean Philippe Duvel

shape of the mean distribution of CL(not shown) is close to that of HI; the CL coverage is,however, generally twice as large. Local maxima of high cloud cover (up to 25%) arelocated near the coast of West Africa, over Cameroonand over central Africa. Over central Africa, the regionof strongest high cloud cover (5-N, 25-E) is locatedwest of a mountain ridge (750-1000 m) orientedsoutheast-northwest from Lake Victoria (Fig. 1 ). Although this mountain ridge is not very high, it maystill force low

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Fei He, Derek J. Posselt, Naveen N. Narisetty, Colin M. Zarzycki, and Vijayan N. Nair

-relevant output variables to the initial conditions are investigated ( Table 1 ). They are the following: maximum wind speed (MWS; intensity; Vmax), total precipitation rate (PRECT), shortwave cloud radiative forcing (SWCF), longwave cloud radiative forcing (LWCF), cloud ice water path (IWP), and cloud liquid water path (LWP). The five physical variables are spatially averaged over the region surrounding the center of the tropical cyclone using the following procedure: 1) find the minimum surface pressure

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Wojciech W. Grabowski and Piotr K. Smolarkiewicz

schemes, respectively. Here, ψ depicts any thermodynamical variable [i.e., any variable from the system (1) ], F c represents forcing terms associated with condensation [i.e., C d in (1) ], and F p depicts forcing terms due to precipitation processes [formation, growth/evaporation and fallout, i.e., A p , C p , E p , and the vertical flux divergence in (1d) ]. In cloud models, the condensation–evaporation of water substance is assumed to be instantaneous. Consequently, time integrations

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James R. McCaa and Christopher S. Bretherton

from the lateral boundaries, verification of the simulations was performed on a 62 × 81 central interior section of the grid, comprising a region from approximately 112° to 162°W, and 13° to 45°N. Estimates of albedo and cloud radiative forcing from the Earth Radiation Budget Experiment (ERBE) ( Hartmann et al. 1986 ; Harrison et al. 1990 ) provide a measure of the impact of clouds on climate. Figure 2 shows the ERBE observed JJA 1987 mean albedo and shortwave cloud radiative forcing (SWCF) for

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