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LPJ-GUESS global hourly RTOT for 2018

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LPJ-GUESS (revision 6562) forced with hourly ERA5 climate datasets to simulate global terrestrial NEE, GPP and total respiration in 0.5 degree. LPJ-GUESS is a process-based dynamic global vegetation model, it uses time series data (e.g. climate forcing and atmospheric carbon dioxide concentrations) as input to simulate the effects of environmental change on vegetation structure and composition in terms of plant functional types (PFTs), soil hydrology and biogeochemistry (Smith et al., 2001, https://web.nateko.lu.se/lpj-guess/).

2018-01-01 00:00:00
2018-12-31 23:00:00
hourly
Wu, Z., Miller, P., Mischurow, M. (2020). LPJ-GUESS global hourly RTOT for 2018, Miscellaneous, https://hdl.handle.net/11676/wlKTe4dwT6XoAzM1wv7qRKKb
BibTex
@misc{https://hdl.handle.net/11676/wlKTe4dwT6XoAzM1wv7qRKKb,
  author={Wu, Zhendong and Miller, Paul and Mischurow, Michael},
  title={LPJ-GUESS global hourly RTOT for 2018},
  year={2020},
  note={LPJ-GUESS (revision 6562) forced with hourly ERA5 climate datasets to simulate global terrestrial NEE, GPP and total respiration in 0.5 degree. LPJ-GUESS is a process-based dynamic global vegetation model, it uses time series data (e.g. climate forcing and atmospheric carbon dioxide concentrations) as input to simulate the effects of environmental change on vegetation structure and composition in terms of plant functional types (PFTs), soil hydrology and biogeochemistry (Smith et al., 2001, https://web.nateko.lu.se/lpj-guess/).},
  keywords={Carbon Dioxide, Carbon Cycle, Land Biogeochemistry, Terrestrial Ecosystems},
  url={https://hdl.handle.net/11676/wlKTe4dwT6XoAzM1wv7qRKKb},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/wlKTe4dwT6XoAzM1wv7qRKKb}
}
RIS
TY - DATA
T1 - LPJ-GUESS global hourly RTOT for 2018
ID - 11676/wlKTe4dwT6XoAzM1wv7qRKKb
PY - 2020
AB - LPJ-GUESS (revision 6562) forced with hourly ERA5 climate datasets to simulate global terrestrial NEE, GPP and total respiration in 0.5 degree. LPJ-GUESS is a process-based dynamic global vegetation model, it uses time series data (e.g. climate forcing and atmospheric carbon dioxide concentrations) as input to simulate the effects of environmental change on vegetation structure and composition in terms of plant functional types (PFTs), soil hydrology and biogeochemistry (Smith et al., 2001, https://web.nateko.lu.se/lpj-guess/).
UR - https://hdl.handle.net/11676/wlKTe4dwT6XoAzM1wv7qRKKb
PB - Carbon Portal
AU - Wu, Zhendong
AU - Miller, Paul
AU - Mischurow, Michael
KW - Carbon Dioxide
KW - Carbon Cycle
KW - Land Biogeochemistry
KW - Terrestrial Ecosystems
ER - 
conv_lpj_hrtot_global_0.50deg_2018.nc
2 GB (1811136007 bytes)
3

Production

2020-05-01 10:00:00

Previewable variables

Name Value type Unit Quantity kind Preview
rtot ecosystem respiration µmol m-2 s-1 particle flux Preview

Statistics

17
1

Submission

2022-03-04 17:51:18
2022-03-04 17:00:47

Technical information

c252937b87704fa5e8033335c2feea44a29b0c0ac0da7b46f447d9bb893be6ed
wlKTe4dwT6XoAzM1wv7qRKKbDArA2ntG9EfZu4k75u0
S: -90, W: -180, N: 90, E: 180
Carbon Cycle Carbon Dioxide Land Biogeochemistry Terrestrial Ecosystems biosphere modeling carbon flux