As far as the representation of deep moist convection is concerned, only two kinds of model physics are used at present: highly parameterized as in the conventional general circulation models (GCMs) and explicitly simulated as in the cloud-resolving models (CRMs). Ideally, these two kinds of model physics should be unified so that a continuous transition of model physics from one kind to the ot...

The use of look-up-tables (LUTs) to represent parameterizations within numerical weather prediction and other atmospheric models is presented. We discuss several approaches as to how the use of LUTs can be optimized in order to retain the physical representation of the parameterization, yet be much more computationally efficient than the parent parameterization from which they are derived. tras...

Recent observational analysis reveals the central role of three multicloud types, congestus, stratiform, and deep convective cumulus clouds, in the dynamics of large-scale convectively coupled Kelvin waves, westward-propagating two-day waves, and the Madden–Julian oscillation. A systematic model convective parameterization highlighting the dynamic role of the three cloud types is developed here...

The Cumulus Pricing Scheme (CPS) determines an important management functionality of commercial networks in future and it is the only approach known so far defining a clear relation between different time-scales of accounting periods, measurement periods, and charging periods. Prices in this scheme are based on flat fees and hence predictable and transparent. CPS is backed by the design and imp...

A realistic yet simple 3D cloud synthesis method is examined in this work. Our synthesis framework consists of two main components. First, by introducing a similarity approach for physics-based cumulus cloud simulation to reduce the computational complexity, we introduce a particle system for cloud modeling. Second, we adopt a voxel-based scheme to model the water phase transition effect and th...