Abstract: new method is presented for cloud detection and the retrieval of three-dimensional cloud fraction from satellite infrared radiances. This method, called multivariate minimum residual (MMR), is inspired by the minimum ...

Abstract: n Part I of this two-part paper, the multivariate minimum residual (MMR) scheme was introduced to retrieve profiles of cloud fraction from satellite infrared radiances and identify clear observations. In this paper it is ...

Abstract: The structure of the analysis increments in a variational data assimilation scheme is strongly driven by the formulation of the background error covariance matrix, especially in data-sparse areas such as the Antarctic ...

Abstract: he control variable transform (CVT) is a keystone of variational data assimilation. In publications using such a technique, the background term of the transformed cost function is defined as a canonical inner product of ...

Abstract: ocalization and hybridization are two methods used in ensemble data assimilation to improve the accuracy of sample covariances. It is shown in this paper that it is beneficial to consider them jointly in the framework of ...

Abstract: onvective-scale models used in NWP nowadays include detailed realistic parameterization for the representation of cloud and precipitation processes. Yet they still lack advanced data assimilation schemes able to efficiently ...

Abstract: he study of evolution characteristics of initial perturbations is an important subject in four-dimensional variational data assimilation (4DVAR) and mesoscale predictability research. This paper evaluates the impact of ...

Abstract: he Feature Calibration and Alignment technique (FCA) has been developed to characterize errors that a human would ascribe to a change in the position or intensity of a coherent feature, such as a hurricane. Here the feature ...

Abstract: ybrid variational?ensemble data assimilation (hybrid DA) is widely used in research and operational systems, and it is considered the current state of the art for the initialization of numerical weather prediction models. ...

Abstract: lignment errors [i.e., cases where coherent structures (?features?) of clouds or precipitation in the background have position errors] can lead to large and non-Gaussian background errors. Assimilation of cloud-affected ...