Next Article in Journal
Application of Data Fusion Techniques to Improve Air Quality Forecast: A Case Study in the Northern Italy
Previous Article in Journal
Fire Behavior, Fuel Consumption, and Turbulence and Energy Exchange during Prescribed Fires in Pitch Pine Forests
Open AccessArticle

Evaluation of a New Statistical Method—TIN-Copula–for the Bias Correction of Climate Models’ Extreme Parameters

1
Department of Meteorology Climatology, School of Geology Aristotle, University of Thessaloniki, GR54124 Thessaloniki, Greece
2
Climate and Atmoshere Research Center (CARE-C), The Cyprus Institute, 20 Konstantinou Kavafi Street, 2121 Aglantzia, Nicosia, Cyprus
3
52°North Initiative for Geospatial Open Source Software GmbH, Martin-Luther-King-Weg 24, 48155 Muenster, Germany
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(3), 243; https://doi.org/10.3390/atmos11030243
Received: 21 January 2020 / Revised: 20 February 2020 / Accepted: 27 February 2020 / Published: 29 February 2020
(This article belongs to the Section Climatology)
During the last decades, global and regional climate models have been widely used for the estimation of future climate conditions. Unfortunately, the models’ estimated values present important biases relative to the observed values, especially when the estimations refer to extremes. Consequently, several researchers have studied several statistical methods that are able to minimize the biases between climate models and observed values. The present study evaluates a new statistical method for bias correction: The triangular irregular network (TIN)-copula method. This method is a combination of the triangular irregular networks and the copula theory. In the present research, the new method is applied to ten Mediterranean stations and its results are compared with the bias-corrected values of three other widely used methods: The delta, the scaling, and the empirical quantile mapping methods. The analysis was made for maximum mean temperature (TMX) and minimum mean temperature (TMN) as well as for extreme precipitation (R99). According to the results, the TIN-copula method is able to correct extreme temperature and precipitation values, estimated by regional climate models, with high accuracy. Additionally, it is proven that the TIN-copula method is a useful tool for bias correction as it presents several advantages compared with the other methods, and it is recommended for future works. View Full-Text
Keywords: TIN-copula; triangular irregular networks; copula; bias correction; Mediterranean; extremes TIN-copula; triangular irregular networks; copula; bias correction; Mediterranean; extremes
Show Figures

Figure 1

MDPI and ACS Style

Lazoglou, G.; Angnostopoulou, C.; Tolika, K.; Benedikt, G. Evaluation of a New Statistical Method—TIN-Copula–for the Bias Correction of Climate Models’ Extreme Parameters. Atmosphere 2020, 11, 243.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop