The Koppen Climate Classification system is one of the examples dissecting global climate process into uniform zones. Due to the fractal structure of geographic phenomenon, the classification of climate zones may be applied at different scales to promote further understanding of climate system at the human-environment interface. This research presents a workflow of classifying climate zones by ...

Cross-domain ground-based cloud classification is a challenging issue as the appearance of cloud images from different cloud databases possesses extreme variations. Two fundamental problems which are essential for cross-domain ground-based cloud classification are feature representation and similarity measurement. In this paper, we propose an effective feature representation called transfer of ...

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are conside...

Although fog is an important component of the hydrological cycle drylands, its formation mechanisms are not fully understood leading to discrepancy type classifications using different methodologies. Such discrepancies may result in under or over estimation potential impacts global climate change on ecohydrology dependent ecosystems. To fill this knowledge gap, study applies hydrogen and oxygen...

The meteorological visibility estimation is an important task, for example, in road traffic control and aviation safety, but its reliable automation is difficult. The conventional light scattering measurements are limited into a small space and the extrapolated values are often erroneous. The current meteorological visibility estimates relying on a single camera work only with data captured in ...