Most of the uncertainty in the climate sensitivity of contemporary general circulation models (GCMs) is believed to be connected with differences in the simulated radiative feedback from clouds. Traditional methods of evaluating clouds in GCMs compare time–mean geographical cloud fields or aspects of present-day cloud variability, with observational data. In both cases a hypothetical assumption...

In this paper, multi-objective uniform-diversity genetic algorithm (MUGA) with a diversity preserving mechanism called the ε-elimination algorithm is used for Pareto optimization of 5-degree of freedom vehicle vibration model considering the five conflicting functions simultaneously. The important conflicting objective functions that have been considered in this work are, namely, vertical accel...

In this study, we apply a clustering algorithm to ISCCP Cloud Optical Thickness – Cloud Top Pressure histograms in order to derive Weather States (WS) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global weather states are derived, a combination of CloudSat/CALIPSO vertical cloud structure retrie...

A physically based retrieval algorithm was developed to estimate snowfall over land. The retrieval algorithm relies on the MM5 model that generates the vertical structure of a snow cloud, including snow mass, snow particle effective diameter, and water vapor. The MM5 cloud simulation was used to provide statistics for generating the cloud characteristics. The snow cloud profile and surface emis...

As conceptual model for a cloud a system is considered which is open for condensate mass transport and subject to internal processes such as cloud microphysical transformation and vertical condensate transport. The effects of microphysical processes are represented in parameterized form and the system is divided into two layers to account for the vertical structure. The evolution is mathematica...

An identical twin methodology is applied to a three-dimensional cloud model to study the dynamics of adjustment in deep convective storms. The principal goal is to diagnose how mass and velocity fields mutually adjust in order to better understand the relative information content (value) of observations, the physical interdependency among variables, and to help in the design of dynamically cons...