This R package contains routines for the analysis of ensembles of time series of climate projections from multiple climate models, accounting for complex shared discrepancies between properties of the models and the real climate system. Routines are provided for situations where the climate models can be considered as exchangeable, and also for structured ensembles using coupled pairs of models (such as global and regional model pairs in regional modelling experiments). The methodology is suitable for use with time series containing a single value per year. It is based around Gaussian dynamic linear models, although options are provided for ensuring that postprocessed projections remain non-negative if required.
The methodology is described in detail in
Chandler, R.E., C.R. Barnes and C.M. Brierley (2023): Decision-relevant characterisation of uncertainty in UK climate projections. Technical report, UK Climate Resilience Programme project CR20-3 Enabling the use and producing improved understanding of EuroCORDEX data over the UK.
The package has been tested under R (version 4.1.2 and later), under both Windows and Ubuntu operating systems.
It makes use of the dlm, Hmisc, magick and numDeriv add-on packages in R.
Note, however: there are memory leaks in the official version of the dlm package as
distributed via CRAN. The package author has been notified but has not fixed them:
a patched version is needed, therefore. See the 'Installation' section below.
Installation requires the devtools package in R. The instructions below assume that this has been installed (e.g. via the Tools menu in RStudio or via install.packages("devtools", lib=<whatever>) from an R console).
If you have the devtools package installed in R then, from the R command line, the package can be installed using:
library(devtools)
install_github("Richard-Chandler/TimSPEC")
To install the corrected version of the dlm library (version 1.1-6 on CRAN at time of writing, renumbered here to start at version 1.1-600), Windows users may need to install Rtools as described here. Mac users also may need to ensure that the relevant compilation tools are available, depending on their setup.
Then:
library(devtools)
install_github("Richard-Chandler/dlmPatched")
If this succeeds, you are now ready to start. help(SLLTSmooth) may be a useful entry point.