<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Nowadays there is a strong degree of agreement that the climate change is the defining challenge of our time, which will exert influence on the ecosystems, on all branches of the international economy and on the quality of life. The analysis based on climate indices is widely used non-parametric approach for quantification of the mean state as well as extreme climate events. This study, which is continuation of our previous efforts, is dedicated to the assessment of the trend magnitude and the trend statistical significance of six temperature-based and three precipitation-based indices in projected future climate over Southeast Europe up to the end of the 21st century. The indices are computed from the bias-corrected output of five CMIP5 global models, reinforced with all four RCP emission scenarios. The model output is accessed from the section of the Inter Sectoral Impact Model Intercomparison Project in the Copernicus Data Store. The multi model ensemble medians of the temperature-based indices shows considerable increase which is consistent with the warming of the mean temperatures. These changes are statistically significant in most cases and intensify with the radiative forcing. The revealed tendencies of the precipitation-based indices are more complex when compared with temperature tendencies.</p></abstract>

Nowadays there is a strong degree of agreement that the climate change is the defining challenge of our time, which will exert influence on the ecosystems, on all branches of the international economy and on the quality of life. The analysis based on climate indices is widely used non-parametric approach for quantification of the mean state as well as extreme climate events. This study, which is continuation of our previous efforts, is dedicated to the assessment of the trend magnitude and the trend statistical significance of six temperature-based and three precipitation-based indices in projected future climate over Southeast Europe up to the end of the 21st century. The indices are computed from the bias-corrected output of five CMIP5 global models, reinforced with all four RCP emission scenarios. The model output is accessed from the section of the Inter Sectoral Impact Model Intercomparison Project in the Copernicus Data Store. The multi model ensemble medians of the temperature-based indices shows considerable increase which is consistent with the warming of the mean temperatures. These changes are statistically significant in most cases and intensify with the radiative forcing. The revealed tendencies of the precipitation-based indices are more complex when compared with temperature tendencies.

Trend Analysis of CMIP5 Ensemble of Climate Indices over Southeast Europe with Focus on Agricultural Impacts

National Institute of Meteorology and Hydrology (NIMH)

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Nowadays there is a strong degree of agreement that the climate change is the defining challenge of our time, which will exert influence on the ecosystems, on...

Trend Analysis of CMIP5 Ensemble of Climate Indices over Southeast Europe with Focus on Agricultural Impacts

Publicado en línea: 31 dic 2020

Páginas: 155 - 165

Recibido: 15 sept 2020

Aceptado: 23 oct 2020

DOI: https://doi.org/10.2478/cait-2020-0069

Palabras clave
Climate indices, RCP, CMIP5 Ensemble, future climate, trend analysis

© 2020 Hristo Chervenkov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Trend Analysis of CMIP5 Ensemble of Climate Indices over Southeast Europe with Focus on Agricultural Impacts

Publicado en línea: 31 dic 2020

Páginas: 155 - 165

Recibido: 15 sept 2020

Aceptado: 23 oct 2020

DOI: https://doi.org/10.2478/cait-2020-0069

Palabras claveClimate indices, RCP, CMIP5 Ensemble, future climate, trend analysis

© 2020 Hristo Chervenkov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Palabras clave
Climate indices, RCP, CMIP5 Ensemble, future climate, trend analysis