Technical note: Changes in cross- and auto-dependence structures in climate projections of daily precipitation and their sensitivity to outliers

0502344 - ÚH 2020 RIV DE eng J - Článek v odborném periodiku
Hnilica, Jan - Hanel, M. - Puš, V.
Technical note: Changes in cross- and auto-dependence structures in climate projections of daily precipitation and their sensitivity to outliers.
Hydrology and Earth System Sciences. Roč. 23, č. 3 (2019), s. 1741-1749. ISSN 1027-5606. E-ISSN 1607-7938
Grant CEP: GA ČR GA16-05665S; GA ČR(CZ) GA16-16549S
Institucionální podpora: RVO:67985874
Klíčová slova: climate model * correlation * outlier * bias correction
Obor OECD: Hydrology
Impakt faktor: 5.153, rok: 2019
Způsob publikování: Open access

Simulations of regional or global climate models are often used for climate change impact assessment. To eliminate systematic errors, which are inherent to all climate model simulations, a number of post processing (statistical downscaling) methods have been proposed recently. In addition to basic statistical properties of simulated variables, some of these methods consider also a dependence structure between or within variables. In the present paper we assess the changes in cross- and auto-correlation structures of daily precipitation in six regional climate model simulations. In addition the effect of outliers is explored making distinction between ordinary outliers (i.e. values exceptionally small or large) and dependence outliers (values deviating from dependence structures). It is demonstrated that correlation estimates can be strongly influenced by few outliers even in large data sets. In turn, any statistical downscaling method relying on sample correlation can therefore provide misleading results. An exploratory procedure is proposed to detect the dependence outliers in multi-variate data and to quantify their impact on correlation structures.
Trvalý link: http://hdl.handle.net/11104/0295529