FLUXCOM-X monthly diurnal cycle of gross primary productivity on global 0.25 degree grid for 2017
Deprecated data
Latest version(s):
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11676/s1vA7cL3EYKQ0awQxEdBDZRB (link)
X-BASE GPP (Gross Primary Productivity) is based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce this global product. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorlogical data, plant functional type classification as well as MODIS based vegitation indicies and land surface temperature. XGBoost was used as the machine learning algorithm. The GPP estimates from the eddy covariance data was based on the Nighttime Partitioning method.
2017-01-01 12:00:00
2017-12-01 12:00:00
hourly
Gans, F., Duveiller, G., Hamdi, Z., Jung, M., Kraft, B., Nelson, J., Walther, S., Weber, U., Zhang, W. (2023). FLUXCOM-X monthly diurnal cycle of gross primary productivity on global 0.25 degree grid for 2017, Miscellaneous, https://hdl.handle.net/11676/s1vA7cL3EYKQ0awQxEdBDZRB
BibTex
@misc{https://hdl.handle.net/11676/s1vA7cL3EYKQ0awQxEdBDZRB, author={Gans, Fabian and Duveiller, Gregory and Hamdi, Zayd and Jung, Martin and Kraft, Basil and Nelson, Jacob A. and Walther, Sophia and Weber, Ulrich and Zhang, Weijie}, title={FLUXCOM-X monthly diurnal cycle of gross primary productivity on global 0.25 degree grid for 2017}, year={2023}, note={X-BASE GPP (Gross Primary Productivity) is based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce this global product. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorlogical data, plant functional type classification as well as MODIS based vegitation indicies and land surface temperature. XGBoost was used as the machine learning algorithm. The GPP estimates from the eddy covariance data was based on the Nighttime Partitioning method.}, keywords={BIOGEOCHEMICAL CYCLES, ECOSYSTEM FUNCTIONS, TERRESTRIAL ECOSYSTEMS, VEGETATION, CARBON, LAND SURFACE, FLUXCOM}, url={https://hdl.handle.net/11676/s1vA7cL3EYKQ0awQxEdBDZRB}, publisher={Carbon Portal}, copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence}, pid={11676/s1vA7cL3EYKQ0awQxEdBDZRB} }
RIS
TY - DATA T1 - FLUXCOM-X monthly diurnal cycle of gross primary productivity on global 0.25 degree grid for 2017 ID - 11676/s1vA7cL3EYKQ0awQxEdBDZRB PY - 2023 AB - X-BASE GPP (Gross Primary Productivity) is based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce this global product. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorlogical data, plant functional type classification as well as MODIS based vegitation indicies and land surface temperature. XGBoost was used as the machine learning algorithm. The GPP estimates from the eddy covariance data was based on the Nighttime Partitioning method. UR - https://hdl.handle.net/11676/s1vA7cL3EYKQ0awQxEdBDZRB PB - Carbon Portal AU - Gans, Fabian AU - Duveiller, Gregory AU - Hamdi, Zayd AU - Jung, Martin AU - Kraft, Basil AU - Nelson, Jacob A. AU - Walther, Sophia AU - Weber, Ulrich AU - Zhang, Weijie KW - BIOGEOCHEMICAL CYCLES KW - ECOSYSTEM FUNCTIONS KW - TERRESTRIAL ECOSYSTEMS KW - VEGETATION KW - CARBON KW - LAND SURFACE KW - FLUXCOM ER -
GPP_2017_025_monthlycycle.nc
261 MB (273467889 bytes)
3
Production
2023-06-21 00:00:00
Gregory Duveiller,
Zayd Hamdi,
Martin Jung,
Basil Kraft,
Jacob A. Nelson,
Sophia Walther,
Ulrich Weber,
Weijie Zhang
Previewable variables
Name | Value type | Unit | Quantity kind | Preview |
---|---|---|---|---|
GPP | gross primary productivity of carbon | gC m-2 d-1 | particle flux | Preview |
Statistics
0
0
Technical information
b35bc0edc2f7118290d1ac10c447410d9441113c92e31c1a44c50592c0034729
s1vA7cL3EYKQ0awQxEdBDZRBETyS4xwaRMUFksADRyk
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES
CARBON
ECOSYSTEM FUNCTIONS
FLUXCOM
LAND SURFACE
TERRESTRIAL ECOSYSTEMS
VEGETATION
biosphere modeling
carbon flux