2013
DOI: 10.1109/tgrs.2013.2258161
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Transitioning From CRD to CDRD in Bayesian Retrieval of Rainfall From Satellite Passive Microwave Measurements: Part 2. Overcoming Database Profile Selection Ambiguity by Consideration of Meteorological Control on Microphysics

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Cited by 43 publications
(41 citation statements)
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“…Besides corroborating the success of meteorological guidance in conditioning Bayesian retrieval solutions, Casella et al (2013) have demonstrated the high reliability of the coupled CRM-RMS modeling system's simulated TB manifold, quantified by the close agreement to its observed counterpart. See Panegrossi et al (1998), Casella (2010 and Casella et al (2013) for explanations of simulationobservation database TB manifolds.…”
Section: Rms Calibration Through Simulation-observation Database Manisupporting
confidence: 56%
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“…Besides corroborating the success of meteorological guidance in conditioning Bayesian retrieval solutions, Casella et al (2013) have demonstrated the high reliability of the coupled CRM-RMS modeling system's simulated TB manifold, quantified by the close agreement to its observed counterpart. See Panegrossi et al (1998), Casella (2010 and Casella et al (2013) for explanations of simulationobservation database TB manifolds.…”
Section: Rms Calibration Through Simulation-observation Database Manisupporting
confidence: 56%
“…The PR-OBS-1 algorithm represents a modified and improved methodology applied to the now conventional Cloud Radiation Database (CRD) methodology originally developed by Smith et al (1992Smith et al ( , 1994a and Mugnai et al (1993), and applied repeatedly since that time, e.g., see Pierdicca et al (1996), Bauer et al (2000Bauer et al ( , 2001Bauer et al ( , 2005, , Chen and Staelin (2003, Tassa et al (2003Tassa et al ( , 2006, Grecu et al (2004), Mugnai et al (2008) and Surussavadee and Staelin (2008a, b) as cases in point. In physical terms, the new methodology is referred to as a Cloud Dynamics and Radiation Database (CDRD) algorithm; see the series of papers by Sanò et al (2013), Casella et al (2013) and which explain Neural Network Operational the attributes of the new methodology and its performance when used in an applied retrieval setting. Figure 2 shows the algorithm flow diagram.…”
Section: Isac-rome's H-saf Pmw Precipitation Algorithms In Trmm Eramentioning
confidence: 99%
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