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FLUXCOM-X daily gross primary productivity on global 0.25 degree grid for 2021

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10.18160/5NZG-JMJE (target, metadata)
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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: Nelson, J. A., Walther, S., Gans, F., Kraft, B., Weber, U., Novick, K., Buchmann, N., Migliavacca, M., Wohlfahrt, G., Šigut, L., Ibrom, A., Papale, D., Göckede, M., Duveiller, G., Knohl, A., Hörtnagl, L., Scott, R. L., Zhang, W., Hamdi, Z. M., Reichstein, M., Aranda-Barranco, S., Ardö, J., Op de Beeck, M., Billesbach, D., Bowling, D., Bracho, R., Brümmer, C., Camps-Valls, G., Chen, S., Cleverly, J. R., Desai, A., Dong, G., El-Madany, T. S., Euskirchen, E. S., Feigenwinter, I., Galvagno, M., Gerosa, G. A., Gielen, B., Goded, I., Goslee, S., Gough, C. M., Heinesch, B., Ichii, K., Jackowicz-Korczynski, M. A., Klosterhalfen, A., Knox, S., Kobayashi, H., Kohonen, K.-M., Korkiakoski, M., Mammarella, I., Gharun, M., Marzuoli, R., Matamala, R., Metzger, S., Montagnani, L., Nicolini, G., O'Halloran, T., Ourcival, J.-M., Peichl, M., Pendall, E., Ruiz Reverter, B., Roland, M., Sabbatini, S., Sachs, T., Schmidt, M., Schwalm, C. R., Shekhar, A., Silberstein, R., Silveira, M. L., Spano, D., Tagesson, T., Tramontana, G., Trotta, C., Turco, F., Vesala, T., Vincke, C., Vitale, D., Vivoni, E. R., Wang, Y., Woodgate, W., Yepez, E. A., Zhang, J., Zona, D., and Jung, M.: X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X, Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, 2024.

2021-01-01 00:00:00
2021-12-31 00:00:00
daily
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: 
Nelson, J. A., Walther, S., Gans, F., Kraft, B., Weber, U., Novick, K., Buchmann, N., Migliavacca, M., Wohlfahrt, G., Šigut, L., Ibrom, A., Papale, D., Göckede, M., Duveiller, G., Knohl, A., Hörtnagl, L., Scott, R. L., Zhang, W., Hamdi, Z. M., Reichstein, M., Aranda-Barranco, S., Ardö, J., Op de Beeck, M., Billesbach, D., Bowling, D., Bracho, R., Brümmer, C., Camps-Valls, G., Chen, S., Cleverly, J. R., Desai, A., Dong, G., El-Madany, T. S., Euskirchen, E. S., Feigenwinter, I., Galvagno, M., Gerosa, G. A., Gielen, B., Goded, I., Goslee, S., Gough, C. M., Heinesch, B., Ichii, K., Jackowicz-Korczynski, M. A., Klosterhalfen, A., Knox, S., Kobayashi, H., Kohonen, K.-M., Korkiakoski, M., Mammarella, I., Gharun, M., Marzuoli, R., Matamala, R., Metzger, S., Montagnani, L., Nicolini, G., O'Halloran, T., Ourcival, J.-M., Peichl, M., Pendall, E., Ruiz Reverter, B., Roland, M., Sabbatini, S., Sachs, T., Schmidt, M., Schwalm, C. R., Shekhar, A., Silberstein, R., Silveira, M. L., Spano, D., Tagesson, T., Tramontana, G., Trotta, C., Turco, F., Vesala, T., Vincke, C., Vitale, D., Vivoni, E. R., Wang, Y., Woodgate, W., Yepez, E. A., Zhang, J., Zona, D., and Jung, M.: X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X, Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, 2024. 
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  -
GPP_2021_025_daily.nc
360 MB (377481110 bytes)
3

Production

2023-11-10 11:00:00

Previewable variables

Name Value type Unit Quantity kind Preview
GPP gross primary productivity of carbon gC m-2 d-1 particle flux Preview

Statistics

78
5

Submission

2024-01-30 15:38:19
2024-01-30 15:22:49

Technical information

ebcba7c650f667a8f1c047baaa5d17c4aff50c7de2bbe43044b50e77973252b0
68unxlD2Z6jxwEe6ql0XxK/1DH3iu+QwRLUOd5cyUrA
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