A Norwegian Approach to Downscaling

TL;DR

This paper presents a comprehensive, open-source geoscientific downscaling framework developed over 20 years, including novel metrics and data storage conventions, to improve climate change adaptation support.

Contribution

It introduces a new, comprehensive downscaling strategy with an evaluation scheme and open-source R tool, enhancing reproducibility and regional climate assessment.

Findings

Development of the 'esd' R-based open-source tool.

Introduction of new metrics for model performance assessment.

A novel data storage convention for large ensemble datasets.

Abstract

A comprehensive geoscientific downscaling model strategy is presented outlining an approach that has evolved over the last 20 years, together with an explanation for its development, its technical aspects, and evaluation scheme. This effort has resulted in an open-source and free R-based tool, 'esd', for the benefit of sharing and improving the reproducibility of the downscaling results. Furthermore, a set of new metrics was developed as an integral part of the downscaling approach which assesses model performance with an emphasis on regional information for society (RifS). These metrics involve novel ways of comparing model results with observational data and have been developed for downscaling large multi-model global climate model ensembles. This paper presents for the first time an overview of the comprehensive framework adopted by the Norwegian Meteorological Institute for downscaling aimed at supporting climate change adaptation. A literature search suggests that this comprehensive downscaling strategy and evaluation scheme are not widely used within the downscaling community. In addition, this strategy involves a new convention for storing large datasets of ensemble results that provides fast access to information and drastically saves data volume.