FluxHourly: global long-term hourly 9&thinsp;km terrestrial water-energy-carbon fluxes

Han, Qianqian; Zeng, Yijian; Wang, Yunfei; Alidoost, Fakhereh; Nattino, Francesco; Liu, Yang; Su, Bob

doi:10.5194/essd-17-7101-2025

Articles | Volume 17, issue 12

https://doi.org/10.5194/essd-17-7101-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-17-7101-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 12

Data description article

|

11 Dec 2025

Data description article |

| 11 Dec 2025

FluxHourly: global long-term hourly 9 km terrestrial water-energy-carbon fluxes

Qianqian Han, Yijian Zeng, Yunfei Wang, Fakhereh Alidoost, Francesco Nattino, Yang Liu, and Bob Su

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3,037	757	144	3,938	431	125	190

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PDF: 757
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Views and downloads (calculated since 29 Apr 2025)

Month	HTML	PDF	XML	Total
Apr 2025	52	7	1	60
May 2025	234	34	5	273
Jun 2025	80	22	9	111
Jul 2025	92	19	7	118
Aug 2025	210	9	3	222
Sep 2025	826	35	3	864
Oct 2025	72	16	2	90
Nov 2025	51	19	4	74
Dec 2025	404	120	19	543
Jan 2026	249	106	8	363
Feb 2026	120	85	15	220
Mar 2026	140	96	20	256
Apr 2026	243	94	17	354
May 2026	131	24	16	171
Jun 2026	28	9	1	38
Jul 2026	78	47	3	128
Aug 2026	27	15	11	53

Cumulative views and downloads (calculated since 29 Apr 2025)

Month	HTML	PDF	XML	Total
Apr 2025	52	7	1	60
May 2025	234	34	5	273
Jun 2025	80	22	9	111
Jul 2025	92	19	7	118
Aug 2025	210	9	3	222
Sep 2025	826	35	3	864
Oct 2025	72	16	2	90
Nov 2025	51	19	4	74
Dec 2025	404	120	19	543
Jan 2026	249	106	8	363
Feb 2026	120	85	15	220
Mar 2026	140	96	20	256
Apr 2026	243	94	17	354
May 2026	131	24	16	171
Jun 2026	28	9	1	38
Jul 2026	78	47	3	128
Aug 2026	27	15	11	53

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Short summary

Understanding how land interacts with the atmosphere is crucial for studying climate change, yet global high-resolution data on energy, water, and carbon exchanges remain limited. This study introduces a new dataset FluxHourly that estimates these exchanges hourly from 2000 to 2020 by combining physical process model, field measurements, and machine learning with satellite and meteorological data. Fluxhourly enables analysis of ecosystem responses to climate extremes.