Evaluating the ability of numerical models to capture important shifts in environmental time series:A fuzzy change point approach

Hollaway, M. J. and Henrys, P. A. and Killick, R. and Leeson, A. and Watkins, J. (2021) Evaluating the ability of numerical models to capture important shifts in environmental time series:A fuzzy change point approach. Environmental Modelling and Software, 139. ISSN 1364-8152

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Abstract

Numerical models are essential tools for understanding the complex and dynamic nature of the natural environment. The ability to evaluate how well these models represent reality is critical in their use and future development. This study presents a combination of changepoint analysis and fuzzy logic to assess the ability of numerical models to capture local scale temporal events seen in observations. The fuzzy union based metric factors in uncertainty of the changepoint location to calculate individual similarity scores between the numerical model and reality for each changepoint in the observed record. The application of the method is demonstrated through a case study on a high resolution model dataset which was able to pick up observed changepoints in temperature records over Greenland to varying degrees of success. The case study is presented using the DataLabs framework, a cloud-based collaborative platform which simplifies access to complex statistical methods for environmental science applications.

Item Type:
Journal Article
Journal or Publication Title:
Environmental Modelling and Software
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2300
Subjects:
ID Code:
153096
Deposited By:
Deposited On:
24 Mar 2021 10:25
Refereed?:
Yes
Published?:
Published
Last Modified:
09 Jun 2021 05:53