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FLUXCOM-X daily transpiration on global 0.25 degree grid for 2016

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X-BASE ET_T (Transpiration) 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 transpiration estimates from the eddy covariance data was based on the Transpiration Estimation Algorithm (TEA).
2016-01-01 12:00:00
2016-12-31 12:00:00
daily
Gans, F., Duveiller, G., Hamdi, Z., Jung, M., Kraft, B., Nelson, J., Walther, S., Weber, U., Zhang, W. (2023). FLUXCOM-X daily transpiration on global 0.25 degree grid for 2016, Miscellaneous, https://hdl.handle.net/11676/nHR3USEaGGrjPgZEw71Fz6xm
BibTex
@misc{https://hdl.handle.net/11676/nHR3USEaGGrjPgZEw71Fz6xm,
  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 daily transpiration on global 0.25 degree grid for 2016},
  year={2023},
  note={X-BASE ET_T (Transpiration) 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 transpiration estimates from the eddy covariance data was based on the Transpiration Estimation Algorithm (TEA).},
  keywords={BIOGEOCHEMICAL CYCLES, ECOSYSTEM FUNCTIONS, TERRESTRIAL ECOSYSTEMS, VEGETATION, CARBON, LAND SURFACE, FLUXCOM},
  url={https://hdl.handle.net/11676/nHR3USEaGGrjPgZEw71Fz6xm},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/nHR3USEaGGrjPgZEw71Fz6xm}
}
RIS
TY - DATA
T1 - FLUXCOM-X daily transpiration on global 0.25 degree grid for 2016
ID - 11676/nHR3USEaGGrjPgZEw71Fz6xm
PY - 2023
AB - X-BASE ET_T (Transpiration) 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 transpiration estimates from the eddy covariance data was based on the Transpiration Estimation Algorithm (TEA).
UR - https://hdl.handle.net/11676/nHR3USEaGGrjPgZEw71Fz6xm
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 - 
ET_T_2016_025_daily.nc
342 MB (359044221 bytes)
3

Production

2023-06-21 00:00:00

Previewable variables

Name Value type Unit Quantity kind Preview
ET_T transpiration mm h-1 particle flux Preview

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Submission

2023-07-25 10:28:18
2023-07-25 10:06:25

Technical information

9c747751211a186ae33e0644c3bd45cfac66f84aa3076c59be50f2d7036e46b0
nHR3USEaGGrjPgZEw71Fz6xm+EqjB2xZvlDy1wNuRrA
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES CARBON ECOSYSTEM FUNCTIONS FLUXCOM LAND SURFACE TERRESTRIAL ECOSYSTEMS VEGETATION biosphere modeling carbon flux