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H. L. Kuo and Y. F. Qian

Abstract

The influences of the Tibetian Plateau on the cumulative and diurnal changes of the meteorological fields in July are investigated by the use of a five-layer primitive equation model which includes the effects of solar and longwave radiation, cumulus convection, topography, internal and surface friction and a mean flow field. It is found that prominent diurnal variations in the meteorological fields are created by the special influence of the plateau on the distribution of solar energy. The vertical circulation so created is such that at 1800 LST at 90°E the motion is upward over the entire Plateau and its surroundings from the surface to the 100 mb level except in a very narrow region close to the eastern edge of the Plateau. At 0600 downward motion prevails over the Plateau and along the surrounding slopes up to the 300 mb level, but above 300 mb ascending motion still persists. The daily mean vertical circulation is characterized by ascending motion over the entire region of the Plateau and its surroundings, which is in general agreement with the mean July flow pattern obtained from observations by Yeh and Gao (1979).

In addition, the distribution of rainfall rate obtained from the simulation also is in fair agreement with the observed distribution in July, with cumulus rainfall contributing to more than three-fourths of the total rainfall in the tropics.

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M. W. Qian, A. Longhetto, C. Cassardo, C. Giraud, Z. X. Hong, W. D. Luo, and Y. J. Zhao

Abstract

A simple and physically consistent expression for the turbulent heat flux equation in the convective atmospheric boundary layer (CABL) has been suggested by . In their equation, valid under quasi-steady states and horizontal homogeneity, the countergradient term resulted from the third-moment transport effect rather than from the buoyancy production term. In this paper, experimental observation data from the World Laboratory Applied Research Project on Drought and Desertification (WL-ARPDD94 Experiment), carried out in a flat region of the greater Beijing area, China, have been utilized with the purpose of checking the validity of the Holtslag and Moeng equation. The result of this experimental check proved to be more than satisfactory through most of the CABL.

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J. F. Scinocca, V. V. Kharin, Y. Jiao, M. W. Qian, M. Lazare, L. Solheim, G. M. Flato, S. Biner, M. Desgagne, and B. Dugas

Abstract

A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs’ value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2.

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W. J. Gutowski Jr., P. A. Ullrich, A. Hall, L. R. Leung, T. A. O’Brien, C. M. Patricola, R. W. Arritt, M. S. Bukovsky, K. V. Calvin, Z. Feng, A. D. Jones, G. J. Kooperman, E. Monier, M. S. Pritchard, S. C. Pryor, Y. Qian, A. M. Rhoades, A. F. Roberts, K. Sakaguchi, N. Urban, and C. Zarzycki
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W. J. Gutowski Jr, P. A. Ullrich, A. Hall, L. R. Leung, T. A. O’Brien, C. M. Patricola, R. W. Arritt, M. S. Bukovsky, K. V. Calvin, Z. Feng, A. D. Jones, G. J. Kooperman, E. Monier, M. S. Pritchard, S. C. Pryor, Y. Qian, A. M. Rhoades, A. F. Roberts, K. Sakaguchi, N. Urban, and C. Zarzycki

ABSTRACT

Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.

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