The JapanFlux2024 dataset for eddy covariance observations covering Japan and East Asia from 1990 to 2023
<p>Eddy covariance observations play a pivotal role in understanding the land–atmosphere exchange of energy, water, carbon dioxide (CO<span class="inline-formula"><sub>2</sub></span>), and other trace gases, as well as the global carbon cycle and earth system....
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-08-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/17/3807/2025/essd-17-3807-2025.pdf |
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| Summary: | <p>Eddy covariance observations play a pivotal role in understanding the land–atmosphere exchange of energy, water, carbon dioxide (CO<span class="inline-formula"><sub>2</sub></span>), and other trace gases, as well as the global carbon cycle and earth system. To promote the networking of individual measurements and the sharing of data, FLUXNET links regional networks of researchers studying land–atmosphere processes. JapanFlux was established in 2006 as a national branch of AsiaFlux. Despite the growing amount of shared data globally, the availability in Asia is currently limited. In this study, we developed an open dataset of the eddy covariance observations for Japan and East Asia, called JapanFlux2024, that was conducted by researchers affiliated with Japanese research institutions. The data were processed using selected standard methods from the FLUXNET community, with adaptations specific to the JapanFlux2024 dataset. Here, we present the data description and data processing and show the value of processed fluxes of sensible heat, latent heat, and CO<span class="inline-formula"><sub>2</sub></span>. The dataset will facilitate important studies for Japan and East Asia, such as land–atmosphere interactions, improvement of process models, and upscaling fluxes using machine learning and remote sensing technology, as well as bridge collaborations between Asia and FLUXNET.</p> |
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| ISSN: | 1866-3508 1866-3516 |