New paper: Process-based evaluation of the VALUE perfect predictor experiment of statistical downscaling methods

Tuesday, December 4, 2018

Predictia has participated in the elaboration of the study "An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment" published in the journal International Journal of Climatology.

VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, process‐based, etc.).
Most evaluation papers for statistical donwscaling methods 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 PP methods, for temperature and precipitation at 86 weather stations across Europe.

The statistical donwscaling methods 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.