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Graeme L. Stephens and Christian D. Kummerow

that govern such distributions point to the elementary importance of the synoptic-scale controls of the atmospheric circulations that shape our weather systems ( Rossow and Cairns 1995 ). The vast range of scales that influence cloud and precipitation properties and the effects of these properties on weather and climate dictate a sampling strategy that inevitably requires the use of data collected from sensors flown on earth-orbiting satellites. A number of methods for determining various cloud and

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Arthur Y. Hou and Sara Q. Zhang

this latent heating assimilation procedure in the GEOS system, together with a comprehensive quality control and data selection procedure, to perform data impact studies. Results will be presented in a follow-on paper. 6. Concluding remarks The current generation of global analysis systems can have significant errors in basic hydrological fields such as clouds and precipitation. This paper examines the prospect of improving the quality of global analyses by assimilating precipitation

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

, retrievals are still used in quality control for the identification of cloudy and rainy pixels ( Bauer et al. 2006a ). Some observations are of time-integrated or averaged values. Examples include hourly precipitation accumulated in rain gauges or temporally continuous datasets constructed from periodic satellite observations. The use of such values tends to reduce both data volumes and random errors (the latter by implication of the central limit theorem in statistics). Of course, potentially useful

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Peter M. Norris and Arlindo M. da Silva

preliminary experiments to investigate the assimilation of surface and top-of-atmosphere radiation observations using a one-dimensional variational data assimilation (1DVAR) approach in which linearized cloud diagnostic parameterizations and radiative forward models are used to find increments to the control variables (temperature and humidity profiles and surface pressure) that minimize radiative flux differences between the forward model and cloudy radiance observations. Using both simulated

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

box. Given the definition of the SSM/I 3-dB footprint size and the spectral nature of the model, both model and observations can be assumed comparable in terms of their spatial representation of precipitation variability. The calculations have been performed from two days of assimilation for a total of four assimilation cycles with 12-h assimilation windows. Only data over ocean have been taken and data screening, quality control, and thinning follow the operational procedure ( Bauer et al. 2006a

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