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Multi-objective environmental model evaluation by means of multidimensional kernel density estimators: Efficient and multi-core implementations

Lopez-Novoa, Unai, Saenz, Jon, Mendiburu, Alexander, Miguel-Alonso, Jose, Errasti, Inigo, Esnaola, Ganix, Ezcurra, Agustin and Ibarra-Berastegi, Gabriel 2015. Multi-objective environmental model evaluation by means of multidimensional kernel density estimators: Efficient and multi-core implementations. Environmental Modelling & Software 63 , pp. 123-136. 10.1016/j.envsoft.2014.09.019

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Abstract

We propose an extension to multiple dimensions of the univariate index of agreement between Probability Density Functions (PDFs) used in climate studies. We also provide a set of high-performance programs targeted both to single and multi-core processors. They compute multivariate PDFs by means of kernels, the optimal bandwidth using smoothed bootstrap and the index of agreement between multidimensional PDFs. Their use is illustrated with two case-studies. The first one assesses the ability of seven global climate models to reproduce the seasonal cycle of zonally averaged temperature. The second case study analyzes the ability of an oceanic reanalysis to reproduce global Sea Surface Temperature and Sea Surface Height. Results show that the proposed methodology is robust to variations in the optimal bandwidth used. The technique is able to process multivariate datasets corresponding to different physical dimensions. The methodology is very sensitive to the existence of a bias in the model with respect to observations.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: Multivariate kernel density estimation; Multidimensional kernel density estimation; Multi-core implementation; Environmental model evaluation
Publisher: Elsevier
ISSN: 1364-8152
Date of Acceptance: 25 September 2014
Last Modified: 25 Jun 2020 13:42
URI: http://orca.cf.ac.uk/id/eprint/105966

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