Articles | Volume 13, issue 4
Model experiment description paper
28 Apr 2020
Model experiment description paper |  | 28 Apr 2020

Configuration and intercomparison of deep learning neural models for statistical downscaling

Jorge Baño-Medina, Rodrigo Manzanas, and José Manuel Gutiérrez

Model code and software

Deep Downscaling Santander Met Group

downscaleR.keras Santander Met Group

climate4R.value Santander Met Group

Short summary
In this study we intercompare different deep learning topologies for statistical downscaling purposes. As compared to the top-ranked methods in the largest-to-date downscaling intercomparison study, our results better predict the local climate variability. Moreover, deep learning approaches can be suitably applied to large regions (e.g., continents), which can therefore foster the use of statistical downscaling in flagship initiatives such as CORDEX.