p_model_drivers_vcmax25 | R Documentation |
Small tests dataset to validate if compiled code and optimization routines can run for leaf traits data
p_model_drivers_vcmax25
A tibble of model driver data:
A character string containing the site names.
A tibble of forcing climate data for an "average" year, including the following variables:
Date in YYYY-MM-DD format (here representative of the day of the year instead of the date of observation).
Air temperature in ^\circ
C.
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}
. If all values are NA,
it indicates that net radiation should be calculated by the SPLASH
model.
Atmospheric pressure in Pa.
Cloud coverage in %. This is only used when either PPFD or net radiation are not prescribed.
Snow in mm d^{-1}
.
Rain in mm d^{-1}
.
Fraction of photosynthetic active radiation (fAPAR), taking values between 0 and 1.
Annually varying observed atmospheric CO_2
, identical
across sites.
Daily minimum air temperature in ^\circ
C (set equal to temp).
Daily maximum air temperature in ^\circ
C.(set equal to temp).
A tibble containing simulation parameters.
A logical value indicating whether this simulation does spin-up.
Number of spin-up years.
Length of standard recycling period, in days.
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.
Longitud of the site location.
Latitude of the site location.
Elevation of the site location, in meters.
A numeric value for the root zone water holding capacity (in mm), used for simulating the soil water balance.
Atkin, O. K., Bloomfield, K. J., Reich, P. B., Tjoelker, M. G., Asner, G. P., Bonal, D., et al. (2015). Global variability in leaf respiration in relation to climate, plant functional types and leaf traits. New Phytol. 206 (2), 614–636. doi:10.1111/nph.13253
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.
C.D. Keeling, R.B. Bacastow, A.E. Bainbridge, C.A. Ekdahl, P.R. Guenther, and L.S. Waterman, (1976), Atmospheric carbon dioxide variations at Mauna Loa Observatory, Hawaii, Tellus, vol. 28, 538-551
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