Work Description

Title: Data for "Influence of vertical heterogeneities in the canopy microenvironment on inter-annual variability of carbon uptake in temperate deciduous forests" Open Access Deposited

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Attribute Value
Methodology
  • Data was obtained via simulation using a suite of Community Land Model (CLM) versions. Analysis was performed in Matlab, the scripts for which are included in this repository. Detailed methods are described in the associated manuscript.
Description
  • Data and Code are divided into separate folders. Data is given for all simulations of all 3 models included in manuscript, as well as the FLUXNET data processed into monthly NetCDF files.
Creator
Depositor
  • mcwoz@umich.edu
Contact information
Discipline
Citations to related material
  • Wozniak, M. C., Bonan, G. B., Keppel-Aleks, G., & Steiner, A. L. (2020). Influence of Vertical Heterogeneities in the Canopy Microenvironment on Interannual Variability of Carbon Uptake in Temperate Deciduous Forests. Journal of Geophysical Research: Biogeosciences, 125(8), e2020JG005658. https://doi.org/10.1029/2020JG005658
Resource type
Last modified
  • 11/18/2022
Published
  • 06/12/2020
DOI
  • https://doi.org/10.7302/scmk-rf50
License
To Cite this Work:
Wozniak, M. C., Dos Santos, T. (2020). Data for "Influence of vertical heterogeneities in the canopy microenvironment on inter-annual variability of carbon uptake in temperate deciduous forests" [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/scmk-rf50

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Files (Count: 2; Size: 2.7 GB)

Data associated with the manuscript “Influence of vertical heterogeneities in the canopy
microenvironment on inter-annual variability of carbon uptake in temperate deciduous
forests”, published in Journal of Geophysical Research – Biogeosciences
(Wozniak et al., in press 2020).

The data from this manuscript are organized into the data generated from simulations by 3
different flavors of the Community Land Model (CLM), as well as the restructured FLUXNET
site data used for model evaluation. In all file folders, the data is further split into
site and model experiment name. The following provides a general description of what to
expect from the data files contained.

In folder CLM4.5, the data are in NetCDF format
(https://www.unidata.ucar.edu/software/netcdf/). Each file is labeled by the actual year
to which it corresponds. Variables that are time-variant are hourly, even though their
units are given as “days since” a specified reference time. You will find a useful script
for reading this data (a MATLAB *.m script) in the code folder Code/Read/read_clm45_data.
The full metadata for the variables and the datasets, themselves, are self-contained as
is standard for NetCDF format.

In folder CLM5, the data are in NetCDF format
(https://www.unidata.ucar.edu/software/netcdf/). The subfolders here are labeled by site
name AND model experiment, where *_bberry corresponds to the “CLM5-noPHS” experiment, and
*_medlyn corresponds to the “CLM5-PHS” experiment. Each data file (*h0*) is labeled by
the relative year to which it corresponds (year since beginning of simulation). Variables
that are time-variant are hourly, even though their units are given as “days since” a
specified reference time. Users will have to use the time variable in coordination with
its units to determine the timestamp for each data point. You will find a useful script
for reading this data (a MATLAB *.m script) in the code folder Code/Read/read_clm5_data,
which accounts for the timestamping already. The full metadata for the variables and the
datasets, themselves, are self-contained as is standard for NetCDF format. Files other
than the *h0* label (*r* and *rs*) files are model restart-related files and are left for
advanced users familiar with the Community Land Model version 5, but are not needed to
explore data directly related to the manuscript.

In folder CLM-ml, the data are comma separated value (CSV) format. Each file is labeled
by the year to which it corresponds. The data are column-order (each column corresponds
to a particular variable). The *flux* files contain scalar variables like GPP and canopy
temperature, in which each row corresponds to a timestamp (hourly). The *profile* files
contain variables of one spatial dimension (the vertical), and every row corresponds
first to a level within the vertical, and secondly to a timestamp. For example, if there
are 45 vertical levels, the first 45 rows would pertain to each of the 45 levels at the
1st simulation timestamp, rows 46-90 would pertain to each of the 45 vertical levels at
the 2nd timestamp, and so on. You will find a useful script for reading this data (a
MATLAB *.m script) in the code folder Code/Read/read_CLMml_output_sunShade. In this
script, all variables are defined and indexed by their proper positions within the *.csv
files.
For details about the simulations used to create this data, please see the methods described in the full manuscript.

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