A dynamic version of these pages will be available at www.cambridge.org/climate research. The authors intend to regularly update these resources for the coming years.
Statistical Downscaling Software Packages and Portals
Here we present (in alphabetical order) a selection of open-source software packages and online portals to perform statistical downscaling. This list is not comprehensive. We may have missed useful and important resources. Moreover, the methods listed here are affected by the limitations discussed throughout the book and should thus be selected and applied carefully in a given context.
R package by the Santander Meteorology group containing functions for MOS such as scaling, and different quantile mapping versions, and PP methods such as linear regression, generalised linear models, weather-type-based downscaling and the analog method.
ENSEMBLES Downscaling Portal
Online portal of the Santander Meteorology Group to carry out downscaling. The webpage provides different sets of predictor and predictand data (with upload options) and a range of MOS and PP methods.
R package by Rasmus Benestad, Abdelkader Mezghani and Kajsa Parding. The package contains a range of functions to post-process and analyse large data sets (e.g. in NetCDF format) including PP statistical downscaling based on linear regression and temporal disaggregation.
R package for a conditional multisite, multivariate weather generator based on generalised linear models developed by Richard Chandler.
Matlab toolbox of the Santander Meteorology group for statistical analysis and data mining in meteorology, focusing on statistical downscaling methods.
Online statistical downscaling tool by Rob Wilby for perfect prognosis and changefactor weather generators.
R package by Lukas Gudmundsson for quantile mapping.
Programmes and Initiatives
The Coupled Model Intercomparison Project (CMIP) defined a framework to conduct and intercompare simulations with coupled atmosphere–ocean GCMs. The most recent phase is CMIP5 (Taylor et al. 2012).
Initiative of the World Climate Research Programme (WCRP) to advance and coordinate the science and application of climate downscaling through global partnerships, in particular to generate large high-resolution multimodel ensembles for all regions of the Earth.