The Theory Behind KrigR
Climate reanalyses are the go-to data products for climate scientists and represent the best-in-class approximations of climate characteristics across the Earth.
The accuracy of climate reanalyses is largely owed to the number of observations assimilated, the underlying dynamical model, and the data assimilation methodology. Furthermore, climate reanalyses offer access to a vast array of Essential Climate Variables (ECVs) at unparalleled temporal resolutions. Lastly, as reanalyses are created from multiple models (i.e. ensembles), we can obtain data uncertainty for each data record.
To our mind, this makes climate reanalyses the gold standard in climate data products for use in macroecological analyses.
Please have a look at these Slides for an introduction to climate science.
KrigR package has been designed to overcome the major stop-gaps in integrating climate reanalyses data into our research frameworks:
- Accessing, downloading, and processing of climate reanalysis data
- Matching spatial resolutions which downstream applications have become used to
For an introduction to
KrigR in presentation form, please have a look at these Slides.