FLUXCOM-X monthly diurnal cycle of net ecosystem exchange on global 0.25 degree grid for 2016
11676/2muN43SsAFgqwJv8_5iD_Gt8 (link)
The X-BASE products are global fluxes based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce these global products. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorological data, plant functional type classification as well as MODIS based vegetation indices and land surface temperature. XGBoost was used as the machine learning algorithm.
Published paper: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-165/
2016-01-01 00:00:00
2016-12-01 00:00:00
hourly
Nelson, J.A., Walther, S., Jung, M., Gans, F., Kraft, B., Weber, U., Hamdi, Z., Duveiller, G., Zhang, W., 2023. FLUXCOM-X-BASE. https://doi.org/10.18160/5NZG-JMJE
BibTex
@misc{https://doi.org/10.18160/5nzg-jmje, doi = {10.18160/5NZG-JMJE}, url = {https://meta.icos-cp.eu/collections/zfwf1Ak2I7OlziGDTX8Xl6_T}, author = {Nelson, Jacob A. and Walther, Sophia and Jung, Martin and Gans, Fabian and Kraft, Basil and Weber, Ulrich and Hamdi, Zayd and Duveiller, Gregory and Zhang, Weijie}, keywords = {BIOGEOCHEMICAL CYCLES, CARBON, ECOSYSTEM FUNCTIONS, FLUXCOM, LAND SURFACE, TERRESTRIAL ECOSYSTEMS, VEGETATION, biosphere modeling, carbon flux, FLUXCOM-X}, title = {FLUXCOM-X-BASE}, publisher = {ICOS ERIC -- Carbon Portal}, year = {2023}, copyright = {ICOS CCBY4 Data Licence} }
RIS
TY - DATA T1 - FLUXCOM-X-BASE AU - Nelson, Jacob A. AU - Walther, Sophia AU - Jung, Martin AU - Gans, Fabian AU - Kraft, Basil AU - Weber, Ulrich AU - Hamdi, Zayd AU - Duveiller, Gregory AU - Zhang, Weijie DO - 10.18160/5NZG-JMJE UR - https://meta.icos-cp.eu/collections/zfwf1Ak2I7OlziGDTX8Xl6_T AB - The X-BASE products are global fluxes based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce these global products. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorological data, plant functional type classification as well as MODIS based vegetation indices and land surface temperature. XGBoost was used as the machine learning algorithm. Published paper: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-165/ KW - BIOGEOCHEMICAL CYCLES KW - CARBON KW - ECOSYSTEM FUNCTIONS KW - FLUXCOM KW - LAND SURFACE KW - TERRESTRIAL ECOSYSTEMS KW - VEGETATION KW - biosphere modeling KW - carbon flux KW - FLUXCOM-X PY - 2023 PB - ICOS ERIC -- Carbon Portal ER -
NEE_2016_025_monthlycycle.nc
258 MB (270709911 bytes)
3
Production
2023-11-09 11:00:00
Gregory Duveiller,
Fabian Gans,
Zayd Hamdi,
Martin Jung,
Basil Kraft,
Jacob A. Nelson,
Sophia Walther,
Ulrich Weber,
Weijie Zhang
Previewable variables
Name | Value type | Unit | Quantity kind | Preview |
---|---|---|---|---|
NEE | net ecosystem exchange of carbon | gC m-2 d-1 | particle flux | Preview |
Statistics
32
0
Technical information
da6b8de374ac00582ac09bfcff9883fc6b7c776fd88e1efae92cb7a7df9ce33b
2muN43SsAFgqwJv8/5iD/Gt8d2/Yjh766Sy3p9+c4zs
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES
CARBON
ECOSYSTEM FUNCTIONS
FLUXCOM
FLUXCOM-X
LAND SURFACE
TERRESTRIAL ECOSYSTEMS
VEGETATION
biosphere modeling
carbon flux