Exploits dynamical seasonal forecasts in order to provide
information relevant to stakeholders at the seasonal timescale. The package
contains process-based 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. This package was developed in the context of the
ERA4CS project MEDSCOPE and the H2020 S2S4E project.
Doblas-Reyes et al. (2005)
This website graphically displays the MEDSCOPE Git project. It allows you to monitor its progress and to interact with other developers via the Issues section.
While it provides some very basic tools to add and modify files in the Git project, if you plan on contributing, you should rather clone the project on your workstation and modify it using the basic Git commands (clone, branch, add, commit, push, merge, ...).
The source code of the MEDSCOPE prototype will be structured as an R package. The code of each function should live in a separate file with the .R extension under the R folder, and the documentation of each function should live in a separate file with the .Rd extension under the man folder.
For an introductory video on Git, you can have a look at https://vimeo.com/41027679.
You can also find all the necessary documentation on git here: https://git-scm.com/book/en/v2 A lot of it may be a bit complicated for beginners (and not necessary for us), but the "Getting started" and "Git basics" sections are a good resources. And you can find supporting videos here: https://vimeo.com/41027679.