ICOS

Global hourly NEP for 2016 based on LPJ-GUESS (generated in 2024)

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10.18160/WRN4-1DV6 (target, metadata)
11676/ahHl1UBJqSoxIoeOkMuLsXg7 (link)

The product is generated in 2024. LPJ-GUESS (version 4.0, revision 6562) is forced with hourly ERA5 climate datasets to simulate global terrestrial CO2 flux at a resolution of 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 with WMO CO2 X2019 scale) as input to simulate the effects of environmental change on vegetation structure and composition in terms of global plant functional types (PFTs), soil hydrology and biogeochemistry (Smith et al., 2001, https://web.nateko.lu.se/lpj-guess/). This simulation models natural fluxes, such as those from vegetation and soil under climate change, via natural processes such as biomass allocation, growth, reproduction, establishment, mortality, and disturbance. This means it does not include anthropogenic activities, such as forest management or agricultural management. The positive value means CO2 uptake from the atmosphere, and the negative value means CO2 release to the atmosphere.

2016-01-01 00:00:00
2016-12-31 23:00:00
hourly
Wu, Z., Michurow, M., Miller, P., 2024. Global hourly NEP, NPP, GPP and heterotrophic respiration for 2010-2023 based on LPJ-GUESS (generated in 2024). https://doi.org/10.18160/WRN4-1DV6
BibTex
@misc{https://doi.org/10.18160/wrn4-1dv6,
  doi = {10.18160/WRN4-1DV6},
  url = {https://meta.icos-cp.eu/collections/E8EEk4983j5zltui3qw7HQQX},
  author = {Wu, Zhendong and Michurow, Michael and Miller, Paul},
  keywords = {Terrestrial Ecosystems, Land Biogeochemistry, Land Surface, Carbon cycle},
  title = {Global hourly NEP, NPP, GPP and heterotrophic respiration for 2010-2023 based on LPJ-GUESS (generated in 2024)},
  publisher = {ICOS ERIC - Carbon Portal},
  year = {2024},
  copyright = {CC BY 4.0}
}
RIS
TY  - DATA
T1  - Global hourly NEP, NPP, GPP and heterotrophic respiration for 2010-2023 based on LPJ-GUESS (generated in 2024)
AU  - Wu, Zhendong
AU  - Michurow, Michael
AU  - Miller, Paul
DO  - 10.18160/WRN4-1DV6
UR  - https://meta.icos-cp.eu/collections/E8EEk4983j5zltui3qw7HQQX
AB  - The product is generated in 2024. LPJ-GUESS (version 4.0, revision 6562) is forced with hourly ERA5 climate datasets to simulate global terrestrial CO2 flux at a resolution of 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 with WMO CO2 X2019 scale) as input to simulate the effects of environmental change on vegetation structure and composition in terms of global plant functional types (PFTs), soil hydrology and biogeochemistry (Smith et al., 2001, https://web.nateko.lu.se/lpj-guess/). This simulation models natural fluxes, such as those from vegetation and soil under climate change, via natural processes such as biomass allocation, growth, reproduction, establishment, mortality, and disturbance. This means it does not include anthropogenic activities, such as forest management or agricultural management. The positive value means CO2 uptake from the atmosphere, and the negative value means CO2 release to the atmosphere.
KW  - Terrestrial Ecosystems
KW  - Land Biogeochemistry
KW  - Land Surface
KW  - Carbon cycle
PY  - 2024
PB  - ICOS ERIC - Carbon Portal
ER  -
conv_lpj_hnep_global_0.5deg_2016.nc
1 GB (1609694170 bytes)
3

Production

2024-06-03 11:00:00
NEP refers to the balance between NPP and HR. Positive values are fluxes into the biosphere

Previewable variables

Name Value type Unit Quantity kind Preview
nep net ecosystem production μmol m-2 s-1 particle flux Preview

Statistics

3
0

Submission

2024-07-03 16:08:59
2024-07-03 15:34:29

Technical information

6a11e5d54049a92a3122878e90cb8bb1783b07538b281e4bb6522c8d6f7322b4
ahHl1UBJqSoxIoeOkMuLsXg7B1OLKB5LtlIsjW9zIrQ
S: -90, W: -180, N: 90, E: 180
Carbon cycle Ecosystem model LPJ-GUESS Land Biogeochemistry Land Surface Terrestrial Ecosystem biosphere modeling carbon flux