Our phenor package for modelling leaf phenology has had moderate success over the past years. However, much of its power resides in being able to scale parameterized models across time and space. Across the US hindcasting and spatially validating data could be easily accomplished by leveraging the DAYMET data. Forecasting using CMIP scenarios was also easily accomplished using the NASA-NEX downscaled CMIP scenarios (e.g. image below). Sadly, NASA-Earth Exchange (NEX) data became hard to access and therefore support was dropped from the package. This left the package with no predictive capabilities, a core tasks within the phenology research domain.
As of release v1.3.2
phenor once more supports forecasting capabilities by
using the ECMWF Climate Data Store provided CMIP6 scenarios. Although not downscaled, and provided at various resolutions, CMIP6 scenarios provide the latest model intercomparison data at your fingertips. Downloading of this data relies on our in house
ecmwfr package. As a consequence, downloading of ERA5 (-land) data is also supported, allowing hindcasting across the globe using the new ERA5 datasets. Once more, trade-offs are made with respect to resolution (~25 and 9 km, for ERA5 and ERA5-land, respectivelly) but increasing coverage.
Both features are available in the 1.3.2 release but will be consolidated in an upcoming major version (v2.0) including up-to-date documentation. Users should consider this release experimental, but might want to explore the capabilities. Watch our blog/news for future updates of the package and the stable v2.0 release.
If you need help, or encounter issues with the package please file an issue at https://github.com/bluegreen-labs/phenor/issues.