The generation of climate forecast products adjusted to user-needs tends to be costly in time and resources. In order to help address this issue, the ERA4CS project MEDSCOPE recently released a Climate Services Toolbox called CSTools. Designed to allow seamless merging of the many post-processing steps typically applied to seasonal forecasts, CSTools is an easy-to-use toolbox designed and built to assess and improve the quality of climate forecasts, from seasonal to multi–annual scales. The package contains process-based state-of-the-art methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. The package also allows the users to easily create their own post-processing chain.
CSTools has been developed by applying the good practices of software development, and relied on documentation and a development policy designed at the Barcelona Supercomputing Center (Spain) with support from the participating partners. The nested structure of CSTools functions led to concise and easy to understand code, facilitating its maintenance while also making it easy to use by the community and straightforward to parallelize and employ on an HPC platform. CSTools is written in R and is now available on CRAN. A series of videos showcasing the toolbox is available online and a manuscript describing the tool is in preparation (Pérez Zanon et al. 2020).
Pérez-Zanon et al. (2020) The CSTools toolbox: from climate forecasts to climate forecast information. In preparation.
Figure 1: PlotForecastPDF, a function in CSTools, can be used to easily visualize the full distribution of multiple forecasts.