Abstract: ecent studies have shown the importance of accounting for model physics uncertainty within probabilistic forecasts. Attempts have been made at quantifying this uncertainty in terms of microphysical parameters such as fall ...

Abstract: ncertainty in cloud microphysical parameterization?a leading order contribution to numerical weather prediction error?is estimated using a Markov chain Monte Carlo (MCMC) algorithm. An inversion is performed on 10 microphysical ...

Abstract: AbstractPartitioning of convective ice into precipitating and detrained condensate presents a challenge for GCMs since partitioning depends on the strength and microphysics of the convective updraft. It is an important ...

Abstract: A general drop size distribution (DSD) normalization method is formulated in terms of generalized power series relating any DSD moment to any number and combination of reference moments. This provides a consistent framework ...

Abstract: There is growing interest in combining microphysical models and polarimetric radar observations to improve our understanding of storms and precipitation. Mapping model-predicted variables into the radar observational space ...