Small tests dataset to validate if compiled code and optimization routines can run
p_model_drivers
A tibble of driver data:
A character string containing the site name.
A tibble of a time series of forcing climate data, including the following variables:
Date of the observation in YYYY-MM-DD format.
Daytime average air temperature in \(^\circ\)C.
Daytime average vapour pressure deficit in Pa.
Photosynthetic photon flux density (PPFD) in mol m\(^{-2}\) s\(^{-1}\). If all values are NA, it indicates that PPFD should be calculated by the SPLASH model.
Net radiation in W m\(^{-2}\). This is currently ignored as a model forcing.
Atmospheric pressure in Pa.
Snow in water equivalents mm s\(^{-1}\).
Rain as precipitation in liquid form in mm s\(^{-1}\).
Daily minimum air temperature in \(^\circ\)C.
Daily maximum air temperature in \(^\circ\)C.
Fraction of photosynthetic active radiation (fAPAR), taking values between 0 and 1.
Atmospheric CO\(_2\) concentration.
Cloud coverage in %. This is only used when either PPFD or net radiation are not prescribed.
A tibble of simulation parameters.
A logical value indicating whether this simulation does spin-up.
Number of spin-up years.
Length of standard recycling period, in years.
An integer indicating the output periodicity.
A logical value, TRUE
if evergreen tree.
A logical value, TRUE
if evergreen tree and N-fixing.
A logical value, TRUE
if deciduous tree.
A logical value, TRUE
if deciduous tree and N-fixing.
A logical value, TRUE
if grass with C3 photosynthetic pathway.
A logical value, TRUE
if grass with C3 photosynthetic
pathway and N-fixing.
A logical value, TRUE
if grass with C4 photosynthetic pathway.
A tibble containing site meta information.
Longitude of the site location in degrees east.
Latitude of the site location in degrees north.
Elevation of the site location, in meters above sea level.
A numeric value for the rooting zone water holding capacity (in mm)
Pastorello, G., Trotta, C., Canfora, E. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci Data 7, 225 (2020). https://doi.org/10.1038/s41597-020-0534-3
University of East Anglia Climatic Research Unit; Harris, I.C.; Jones, P.D.; Osborn, T. (2021): CRU TS4.05: Climatic Research Unit (CRU) Time-Series (TS) version 4.05 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2020). NERC EDS Centre for Environmental Data Analysis, date of citation. https://catalogue.ceda.ac.uk/uuid/c26a65020a5e4b80b20018f148556681
Weedon, G. P., G. Balsamo, N. Bellouin,S. Gomes, M. J. Best, and P. Viterbo(2014), The WFDEI meteorologicalforcing data set: WATCH Forcing Datamethodology applied to ERA-Interimreanalysis data, Water Resour. Res.,50,7505–7514, doi:10.1002/2014WR015638.
Fick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37 (12): 4302-4315.