Computer Science > Machine Learning
arXiv:2603.09868 (cs)
[Submitted on 10 Mar 2026]
Title:CarbonBench: A Global Benchmark for Upscaling of Carbon Fluxes Using Zero-Shot Learning
View a PDF of the paper titled CarbonBench: A Global Benchmark for Upscaling of Carbon Fluxes Using Zero-Shot Learning, by Aleksei Rozanov and 3 other authors
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Abstract:Accurately quantifying terrestrial carbon exchange is essential for climate policy and carbon accounting, yet models must generalize to ecosystems underrepresented in sparse eddy covariance observations. Despite this challenge being a natural instance of zero-shot spatial transfer learning for time series regression, no standardized benchmark exists to rigorously evaluate model performance across geographically distinct locations with different climate regimes and vegetation types.
We introduce CarbonBench, the first benchmark for zero-shot spatial transfer in carbon flux upscaling. CarbonBench comprises over 1.3 million daily observations from 567 flux tower sites globally (2000-2024). It provides: (1) stratified evaluation protocols that explicitly test generalization across unseen vegetation types and climate regimes, separating spatial transfer from temporal autocorrelation; (2) a harmonized set of remote sensing and meteorological features to enable flexible architecture design; and (3) baselines ranging from tree-based methods to domain-generalization architectures. By bridging machine learning methodologies and Earth system science, CarbonBench aims to enable systematic comparison of transfer learning methods, serves as a testbed for regression under distribution shift, and contributes to the next-generation climate modeling efforts.
| Subjects: | Machine Learning (cs.LG); Atmospheric and Oceanic Physics (physics.ao-ph) |
| Cite as: | arXiv:2603.09868 [cs.LG] |
| (or arXiv:2603.09868v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2603.09868
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arXiv-issued DOI via DataCite
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Submission history
From: Arvind Renganathan [view email][v1] Tue, 10 Mar 2026 16:33:28 UTC (2,551 KB)
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View a PDF of the paper titled CarbonBench: A Global Benchmark for Upscaling of Carbon Fluxes Using Zero-Shot Learning, by Aleksei Rozanov and 3 other authors
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