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a priori error ESTIMATES OF A COMBINED MIXED FINITE ELEMENT AND DISCONTINUOUS GALERKIN METHOD FOR COMPRESSIBLE MISCIBLE DISPLACEMENT WITH MOLECULAR DIFFUSION AND DISPERSION

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Journal of Computational Mathematics 2011年第1期29卷 91-107页

作者： Jiming Yang Yanping Chen College of Science Hunan Institute of Engineering Xiangtan 411104 China School of Mathematical Sciences South China Normal University Guangzhou 510631 China

A combined approximation for a kind of compressible miscible displacement problems including molecular diffusion and dispersion in porous media is studied. Mixed finite el- ement method is applied to the ftow equation, and the transport one is solved by the symmetric interior penalty discontinuous Galerkin method （SIPG）. To avoid the inconve- nience of the cut-off operator in [3, 21], some induction hypotheses different from the ones in [6] are used. Based on interpolation projection properties, a priori hp error estimates are obtained. Comparing with the existing error analysis that only deals with the diffusion case, the current work is more complicated and more significant.

关键词： a priori error Mixed finite element Discontinuous Galerkin Compressiblemiscible clisplacement.

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Use of Total Precipitable Water Classification of a priori error and Quality Control in Atmospheric Temperature and Water Vapor Sounding Retrieval

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Advances in Atmospheric Sciences 2012年第2期29卷 263-273页

作者： Eun-Han KWON Elisabeth WEISZ School of Earth and Environmental Sciences Seoul National University Seoul 151-747 Korea Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-Madison1225 West Dayton Street Madison WI 53706 USA

This study investigates the use of dynamic a priori error information according to atmospheric moistness and the use of quality controls in temperature and water vapor profile retrievals from hyperspectral infrared （IR） sounders. Temperature and water vapor profiles are retrieved from Atmospheric InfraRed Sounder （AIRS） radiance measurements by applying a physical iterative method using regression retrieval as the first guess. Based on the dependency of first-guess errors on the degree of atmospheric moistness, the a priori first-guess errors classified by total precipitable water （TPW） are applied in the AIRS physical retrieval procedure. Compared to the retrieval results from a fixed a priori error, boundary layer moisture retrievals appear to be improved via TPW classification of a priori first-guess errors. Six quality control （QC） tests, which check non-converged or bad retrievals, large residuals, high terrain and desert areas, and large temperature and moisture deviations from the first guess regression retrieval, are also applied in the AIRS physical retrievals. Significantly large errors are found for the retrievals rejected by these six QCs, and the retrieval errors are substantially reduced via QC over land, which suggest the usefulness and high impact of the QCs, especially over land. In conclusion, the use of dynamic a priori error information according to atmospheric moistness, and the use of appropriate QCs dealing with the geographical information and the deviation from the first-guess as well as the conventional inverse performance are suggested to improve temperature and moisture retrievals and their applications.

关键词： atmospheric sounding AIRS total precipitable water a priori error quality control

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