Conceptual monthly trend polygon methodology and climate change assessments

Abstract

Climate change impact search methodologies, for a single hydro-meteorological record, are based mostly on probabilistic, statistical and stochastic processes. The application of these methodologies requires some restrictive assumptions for their validation, which may not be embedded in the structure of the record. Either transformations or approximations are taken into consideration, with idealization and simplification assumptions. In this paper, a series of conceptual trend polygon methodologies are presented without mathematical expression or restrictive assumptions. These are serial, cross- and double polygonal trend methods, in addition to trend star graphs. They help in identifying, interpreting and calculating monthly shifts, producing useful scientific information that cannot be obtained by the classical monotonic trend identification approaches. The methodology is applied to hydro-meteorological series from different regions of the world including precipitation and discharge records.