ICOS

FLUXCOM-X monthly diurnal cycle of gross primary productivity on global 0.25 degree grid for 2007

Download

Deprecated data

Latest version(s): YpGR386AiEYK2t2gdsJTrXs7
11676/I2G9kIv19TOFE6emlDsKJCuF (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.
2007-01-01 12:00:00
2007-12-01 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 2007, Miscellaneous, https://hdl.handle.net/11676/I2G9kIv19TOFE6emlDsKJCuF
BibTex
@misc{https://hdl.handle.net/11676/I2G9kIv19TOFE6emlDsKJCuF,
  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 2007},
  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/I2G9kIv19TOFE6emlDsKJCuF},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/I2G9kIv19TOFE6emlDsKJCuF}
}
RIS
TY - DATA
T1 - FLUXCOM-X monthly diurnal cycle of gross primary productivity on global 0.25 degree grid for 2007
ID - 11676/I2G9kIv19TOFE6emlDsKJCuF
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/I2G9kIv19TOFE6emlDsKJCuF
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_2007_025_monthlycycle.nc
262 MB (274459400 bytes)
3

Production

2023-06-21 00:00:00

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

Submission

2023-07-25 11:23:33
2023-07-25 11:18:56

Technical information

2361bd908bf5f5338513a7a6943b0a242b85eebb57282fa73186bf3ffaf55647
I2G9kIv19TOFE6emlDsKJCuF7rtXKC+nMYa/P/r1Vkc
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES CARBON ECOSYSTEM FUNCTIONS FLUXCOM LAND SURFACE TERRESTRIAL ECOSYSTEMS VEGETATION biosphere modeling carbon flux