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Ronald M. Errico, Peter Bauer, and Jean-François Mahfouf

: Improving quantitative precipitation forecasts in the warm season: A USWRP research and development strategy. Bull. Amer. Meteor. Soc. , 85 , 955 – 965 . Gérard , E. , and R. W. Saunders , 1999 : Four-dimensional assimilation of Special Sensor Microwave/Imager in the ECMWF model. Quart. J. Roy. Meteor. Soc. , 125 , 3077 – 3101 . Greenwald , T. J. , R. Hertenstein , and T. Vukićević , 2002 : An all-weather observational operator for radiance data assimilation with mesoscale

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Philippe Lopez

the same respect, observations have shown that the horizontal spreading of convective downdrafts close to the surface (gust fronts) can favor the development of new cells and thereby promote the horizontal propagation of mesoscale cloud systems. This level of detail is currently not available in operational forecast models, although some propagation of mesoscale cloud systems can be already simulated through the large-scale lifting that results from the strong horizontal temperature gradients

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Fuzhong Weng, Tong Zhu, and Banghua Yan

D temperature data from a 1DVAR scheme. Applications of the MM5 adjoint model to a variety of mesoscale weather systems have been demonstrated in papers by Kuo et al. (1996) and Zou and Xiao (2000) . The limited-memory quasi-Newton method of Liu and Nocedal (1989) is used to minimize the objective function in this study. The cost function to be minimized can be written as where J b is the cost function for background term, and the background fields are obtained from NCEP Global Forecast

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Peter M. Norris and Arlindo M. da Silva

, A. E. , and G. D. Modica , 1999 : Assimilation of visible-band satellite data for mesoscale forecasting in cloudy conditions. Mon. Wea. Rev. , 127 , 265 – 278 . Macpherson , B. , B. J. Wright , W. H. Hand , and A. J. Maycock , 1996 : The impact of MOPS moisture data in the U.K. Meteorological Office mesoscale data assimilation scheme. Mon. Wea. Rev. , 124 , 1746 – 1766 . Pincus , R. , C. Hannay , S. A. Klein , K-M. Xu , and R. Hemler , 2005 : Overlap

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K. Franklin Evans

. Software , 24 , 437 – 474 . Greenwald , T. J. , R. Hertenstein , and T. Vukicevic , 2002 : An all-weather observational operator for radiance data assimilation with mesoscale forecast models. Mon. Wea. Rev. , 130 , 1882 – 1897 . Greenwald , T. J. , T. Vukicevic , L. D. Grasso , and T. H. Vonder Haar , 2004 : Adjoint sensitivity analysis of an observational operator for visible and infrared cloudy-sky radiance assimilation. Quart. J. Roy. Meteor. Soc. , 130 , 685 – 705

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Christopher W. O’Dell, Peter Bauer, and Ralf Bennartz

, F. W. Saunders , and J. Eyre , 2000 : A comparison of the impact of TOVS and ATOVS satellite sounding data on the accuracy of numerical weather forecasts. Quart. J. Roy. Meteor. Soc. , 126 , 2911 – 2931 . Greenwald , T. J. , R. Hertenstein , and T. Vukicevic , 2002 : An all-weather observational operator for radiance data assimilation with mesoscale forecast models. Mon. Wea. Rev. , 130 , 1882 – 1897 . Heidinger , A. K. , C. O’Dell , R. Bennartz , and T

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Chinnawat Surussavadee and David H. Staelin

the NWP and RTM models. This was done, for example, by Tassa et al. (2006) for the TRMM frequencies and in a limited way by Surussavadee and Staelin (2006) for AMSU frequencies between 23 and 191 GHz. In the latter work, observed AMSU radiance histograms agreed within approximately ±10 K at all frequencies with those predicted by the NWP fifth-generation Pennsylvania State University–National Center for Atmospheric Research (NCAR) Mesoscale Model (MM5) followed by the RTM model TBSCAT/ F ( λ

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