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Coefficient C (coefficient + c)

Distribution by Scientific Domains
Earth and Environmental Science75%

Selected Abstracts

A new method of vegetation,climate classification in China

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 9 2008
Sun Yanling
Abstract Coefficient C is a synthetic index from the third correlative equation, which represents the state of moisture in a region and may be used for assigning vegetation zonality. The third correlative equation is a new equation concerning heat and water balance from knowledge of evaporation on land. In this article, coefficient C and accumulated temperature over 5 °C (AT5) are combined to predict the distribution of vegetation zones in China. Predictions of vegetation distribution are made using observational climate data interpolated into a 25 × 25 km grid. The overall impression from examining the resulting vegetation map is that the location and distribution of vegetation zones in China are predicted fairly well. Comparison between the predicted vegetation map and the vegetation regionalization map are based on Kappa statistics and indicate very good agreement for the cold,temperate coniferous forest zone, the subtropical evergreen broadleaved forest zone, and the temperate mixed coniferous,broadleaved forest zone. Agreement is good for the warm,temperate deciduous broadleaved forest zone, the temperate steppe zone, the temperate desert zone, and the Tibetan high-cold plateau zone. Agreement between the regionalization map and the produced map is fair for the tropical rainforest and monsoon forest zone. Compared with those produced by the Holdridge, Thornthwaite, Penman, and the Kira models, as well as the Budyko method, the Kappa statistics in this article are all better except for the cold,temperate (boreal) coniferous forest zone and the temperate desert zone. The results are particularly superior for the Tibetan high-cold plateau zone. Coefficient C provides important information for predicting the distribution of vegetation zones in China, and this article attempts to study vegetation,climate classification on a large scale using coefficient C and AT5. Copyright © 2007 Royal Meteorological Society [source]

An evolutionary optimization of diffuser shapes based on CFD simulations

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 10 2010
S. Ghosh
Abstract An efficient and robust algorithm is presented for the optimum design of plane symmetric diffusers handling incompressible turbulent flow. The indigenously developed algorithm uses the CFD software: Fluent for the hydrodynamic analysis and employs a genetic algorithm (GA) for optimization. For a prescribed inlet velocity and outlet pressure, pressure recovery coefficient C (the objective function) is estimated computationally for various design options. The CFD software and the GA have been combined in a monolithic platform for a fully automated operation using some special control commands. Based on the developed algorithm, an extensive exercise has been made to optimize the diffuser shape. Different methodologies have been adopted to create a large number of design options. Interestingly, not much difference has been noted in the optimum C values obtained through different approaches. However, in all the approaches, a better design has been obtained through a proper selection of the number of design variables. Finally, the effect of diffuser length on the optimum shape has also been studied. Copyright © 2009 John Wiley & Sons, Ltd. [source]

A new method of vegetation,climate classification in China

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 9 2008
Sun Yanling
Abstract Coefficient C is a synthetic index from the third correlative equation, which represents the state of moisture in a region and may be used for assigning vegetation zonality. The third correlative equation is a new equation concerning heat and water balance from knowledge of evaporation on land. In this article, coefficient C and accumulated temperature over 5 °C (AT5) are combined to predict the distribution of vegetation zones in China. Predictions of vegetation distribution are made using observational climate data interpolated into a 25 × 25 km grid. The overall impression from examining the resulting vegetation map is that the location and distribution of vegetation zones in China are predicted fairly well. Comparison between the predicted vegetation map and the vegetation regionalization map are based on Kappa statistics and indicate very good agreement for the cold,temperate coniferous forest zone, the subtropical evergreen broadleaved forest zone, and the temperate mixed coniferous,broadleaved forest zone. Agreement is good for the warm,temperate deciduous broadleaved forest zone, the temperate steppe zone, the temperate desert zone, and the Tibetan high-cold plateau zone. Agreement between the regionalization map and the produced map is fair for the tropical rainforest and monsoon forest zone. Compared with those produced by the Holdridge, Thornthwaite, Penman, and the Kira models, as well as the Budyko method, the Kappa statistics in this article are all better except for the cold,temperate (boreal) coniferous forest zone and the temperate desert zone. The results are particularly superior for the Tibetan high-cold plateau zone. Coefficient C provides important information for predicting the distribution of vegetation zones in China, and this article attempts to study vegetation,climate classification on a large scale using coefficient C and AT5. Copyright © 2007 Royal Meteorological Society [source]

Empirical evaluation of an extended similarity theory for the stably stratified atmospheric surface layer

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 602 2004
Harald Sodemann
Abstract The theory of the atmospheric stable boundary layer (SBL) has recently been extended by a distinction between nocturnal and long-lived SBLs. The latter SBL type, which includes influences from the free atmosphere on fluxes in the surface layer, requires a modification of the traditional Monin,Obukhov similarity theory. In the present study, the applicability of this extended theory for long-lived SBLs is evaluated and the required coefficients are estimated using data from Antarctica. Changes in wind and temperature gradients due to different weather conditions are shown to exert a strong influence on the estimation of the new coefficients CuN and C,N. Using the wind gradient as classification criterion, the momentum flux coefficient CuN is estimated to range between 0.51±0.03 and 2.26±0.08. Using the temperature gradient as classification criterion, the heat flux coefficient C,N is estimated to range between 0.022±0.002 and 0.040±0.001. At present, the proposed new scaling theory is still in a preliminary stage. Possible future improvements should take into account factors influencing the wind and temperature gradients, such as weather conditions. An artificial background correlation strongly imprints upon the parameter estimation, suggesting that both the methodology for estimating the new coefficients CuN and C,N and the choice of the nondimensional variables for this extended scaling theory may require some revision. Copyright © 2004 Royal Meteorological Society [source]