Multivariate interpolation of large sets of scattered data
ACM Transactions on Mathematical Software (TOMS)
Smooth interpolation to scattered data by bivariate piecewise polynomials of odd degree
Computer Aided Geometric Design
Scattered data interpolation in three or more variables
Mathematical methods in computer aided geometric design
An interpolation method for estuarine and oceanographic data
Computers & Geosciences
IEEE Computer Graphics and Applications - Special issue on computer-aided geometric design
ACM Transactions on Mathematical Software (TOMS)
A two-dimensional interpolation function for irregularly-spaced data
ACM '68 Proceedings of the 1968 23rd ACM national conference
An architecture for a scientific visualization system
VIS '92 Proceedings of the 3rd conference on Visualization '92
Visual exploration and evaluation of climate-related simulation data
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
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The ordinarily arid climate of coastal Peru is disturbed every few years by a phenomenon called El Niño, characterized by a warming in the Pacific Ocean. Severe rainstorms are one of the consequences of El Niño, which cause great damage. An examination of daily data from 66 rainfall stations in the Chiura-Piura region of north-western Peru from late 1982 through mid-1983 (associated with an El Niño episode) yields information on the mesoscale structure of these storms. These observational data are typical of a class that are scattered at irregular locations in two dimensions. The use of continuous realization techniques for qualitative visualization (e.g., surface deformation or contouring) requires an intermediate step to define a topological relationship between the locations of data to form a mesh structure. Several common methods are considered, and the results of their application to the study of the rainfall events are analyzed.