Process‐based evaluation of the VALUE perfect predictor experiment of statistical downscaling methods

Abstract

Statistical downscaling methods (SDMs) are techniques used to downscale and/or bias‐correct climate model results to regional or local scales. The European network VALUE developed a framework to evaluate and inter‐compare SDMs. One of VALUE's experiments is the perfect predictor experiment that uses reanalysis predictors to isolate downscaling skill. Most evaluation papers for SDMs employ simple statistical diagnostics and do not follow a process‐based rationale. Thus, in this paper, a process‐based evaluation has been conducted for the more than 40 participating model output statistics (MOS, mostly bias correction) and perfect prognosis (PP) methods, for temperature and precipitation at 86 weather stations across Europe. The SDMs are analysed following the so‐called “regime‐oriented” technique, focussing on relevant features of the atmospheric circulation at large to local scales. These features comprise the North Atlantic Oscillation, blocking and selected Lamb weather types and at local scales the bora wind and the western Iberian coastal‐low level jet. The representation of the local weather response to the selected features depends strongly on the method class. As expected, MOS is unable to generate process sensitivity when it is not simulated by the predictors (ERA‐Interim). Moreover, MOS often suffers from an inflation effect when a predictor is used for more than one station. The PP performance is very diverse and depends strongly on the implementation. Although conditioned on predictors that typically describe the large‐scale circulation, PP often fails in capturing the process sensitivity correctly. Stochastic generalized linear models supported by well‐chosen predictors show improved skill to represent the sensitivities.

Regional climate downscaling over Europe: perspectives from the EURO-CORDEX community

“…In a first experiment, VALUE investigated the downscaling skill of some 50 statistical methods for present climate, when driven with reanalysis-based predictors. These results have recently been published in a special issue (Maraun et al 2017(Maraun et al , 2018Gutiérrez et al 2018;Hertig et al 2018;Soares et al 2018). These types of activities have been integrated into the ESD pillar into EURO-CORDEX (Fig.…”

“…Modelling groups focusing on empirical statistical downscaling (ESD) employ a wide range of approaches (Benestad et al 2017a;Maraun et al 2015Maraun et al , 2018Gutiérrez et al 2018;Hertig et al 2018;Soares et al 2018;Widmann et al 2019). The two approaches to downscaling are seen as complementary within the EURO-CORDEX community, each with its relative strengths.…”

“…The added value of higher resolution simulations was also addressed, both directly and indirectly, in a number of studies including dynamical downscaling (Warrach-Sagi et al 2013;Torma et al 2015;Casanueva et al 2016b;Coppola et al 2018a;Prein and Gobiet 2016;Ivanov et al 2017;Soares and Cardoso 2017;Fantini et al 2018;Sørland et al 2018) and statistical methods (Casanueva et al 2016a;Soares et al 2018). Joint evaluation studies also focused on extreme climate events, such as heat waves (Vautard et al 2013;Lhotka et al 2017) and extreme precipitation (Fantini et al 2018), medicanes (Gaertner et al 2018) or physical process analysis, such as land-atmosphere interactions (e.g., Davin et al 2016;Knist et al 2017) and coastal circulations (Cardoso et al 2016).…”

Uncovering the shortcomings of a weather typing based statistical downscaling method

“…The latter experiment has been extended by a hydrological impact analysis. In doing so, we respond to the recent focus of the statistical downscaling community on the validation of SDMs (Gutiérrez et al, 2018;Haberlandt et al, 2015;Hertig et al, 2018;Maraun et al, , 2017Maraun et al, , 2015Pryor and Schoof, 2019;Soares et al, 2018;Werner and Cannon, 2016) and bring the validation into practice.…”

Evaluation of downscaling methods over Europe: Results of the EU‐COST action VALUE

“…The performance of different methods was also unpacked with respect to atmospheric processes or circulation regimes: Soares et al . () find strong differences in how different classes of methods represent the local‐scale responses under different circulation regimes providing further understanding of the applicability of different classes of methods and individual methods. A valuable synthesis of results is presented in Maraun et al .…”