ICOS

FLUXCOM-X monthly diurnal cycle of transpiration on global 0.25 degree grid for 2002

Download

Deprecated data

Latest version(s): aA_613ewrD29_Rw7KW_GBTDM
11676/ceAzEd_8rXHHRTGkyPR5qJqE (link)
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).
2002-01-01 12:00:00
2002-12-01 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 transpiration on global 0.25 degree grid for 2002, Miscellaneous, https://hdl.handle.net/11676/ceAzEd_8rXHHRTGkyPR5qJqE
BibTex
@misc{https://hdl.handle.net/11676/ceAzEd_8rXHHRTGkyPR5qJqE,
  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 transpiration on global 0.25 degree grid for 2002},
  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/ceAzEd_8rXHHRTGkyPR5qJqE},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/ceAzEd_8rXHHRTGkyPR5qJqE}
}
RIS
TY - DATA
T1 - FLUXCOM-X monthly diurnal cycle of transpiration on global 0.25 degree grid for 2002
ID - 11676/ceAzEd_8rXHHRTGkyPR5qJqE
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/ceAzEd_8rXHHRTGkyPR5qJqE
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_2002_025_monthlycycle.nc
245 MB (256917730 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

Statistics

0
0

Submission

2023-07-25 10:19:21
2023-07-25 10:06:18

Technical information

71e03311dffcad71c74531a4c8f479a89a842829f68eeee0608d5efaaedf77cc
ceAzEd/8rXHHRTGkyPR5qJqEKCn2ju7gYI1e+q7fd8w
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES CARBON ECOSYSTEM FUNCTIONS FLUXCOM LAND SURFACE TERRESTRIAL ECOSYSTEMS VEGETATION biosphere modeling carbon flux