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Uni- and multivariate bias adjustment methods in Nordic catchments: Complexity and performance in a changing climate

Authors :
Faranak Tootoonchi
Jan O. Haerter
Andrijana Todorović
Olle Räty
Thomas Grabs
Claudia Teutschbein
Source :
Science of the Total Environment, Tootoonchi, F, Haerter, J O, Todorovic, A, Raty, O, Grabs, T & Teutschbein, C 2022, ' Uni-and multivariate bias adjustment methods in Nordic catchments : Complexity and performance in a changing climate br ', Science of the Total Environment, vol. 853, 158615 . https://doi.org/10.1016/j.scitotenv.2022.158615
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

For climate-change impact studies at the catchment scale, meteorological variables are typically extracted from ensem-ble simulations provided by global and regional climate models, which are then downscaled and bias-adjusted for eachstudy site. For bias adjustment, different statistical methods that re-scaleclimate model outputs have been suggested inthe scientific literature. They range from simple univariate methods that adjust each meteorological variable individ-ually, to more complex and more demanding multivariate methods that take existing relationships between meteoro-logical variables into consideration. Over the past decade, several attempts have been made to evaluate such methodsin various regions. There is, however, still no guidance for choosing appropriate bias adjustment methods for a study athand. In particular, the question whether the benefits of potentially improved adjustments outweigh the cost of in-creased complexity, remains unanswered.This paper presents a comprehensive evaluation of the performance of two commonly used univariate and two multi-variate bias adjustment methods in reproducing numerous univariate, multivariate and temporal features of precipita-tion and temperature series in different catchments in Sweden. The paper culminates in a discussion on trade-offs between the potential benefits (i.e., skills and added value) and disadvantages (complexity and computational de-mand) of each method to offer plausible, defensible and actionable insights from the standpoint of climate-change im-pact studies in high latitudes.We concluded that all selected bias adjustment methods generally improved the raw climate model simulations, but that not a single method consistently outperformed the other methods. There were, however, differences in the methods' performance for particular statistical features, indicating that other practical aspects such as computationaltime and heavy theoretical requirements should also be taken into consideration when choosing an appropriate biasadjustment method

Details

ISSN :
00489697
Volume :
853
Database :
OpenAIRE
Journal :
Science of The Total Environment
Accession number :
edsair.doi.dedup.....b53c76cd628560cec72994d40add954a