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 - Journal Article
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
R&D Projects: GA ČR GA16-05665S; GA ČR(CZ) GA16-16549S
Institutional support: RVO:67985874
Keywords : climate model * correlation * outlier * bias correction
OECD category: Hydrology
Impact factor: 5.153, year: 2019
Method of publishing: 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.
Permanent Link: http://hdl.handle.net/11104/0295529