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Global green wave centroid shifts north and east

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Research area:agriculture-foodagronomy-crops

What the study found

The study found that the global "green wave" centroid, meaning the seasonal movement of vegetation across Earth, shifts northward during both boreal and austral summer. It also found that the eastward shift is accelerating, while the overall trajectory amplitude is decreasing.

Why the authors say this matters

The authors conclude that tracking the green wave's centroid reveals how changing land dynamics across regions affect the global functioning of Earth's terrestrial biosphere. They present this as a way to better quantify global phenology, meaning seasonal timing in vegetation.

What the researchers tested

The researchers proposed a concept to quantify global phenology by tracking the green wave's centroid using satellite data and Earth system model data. They used this trajectory to summarize global phenological dynamics and directional trends.

What worked and what didn't

The centroid approach identified northward movement during both summer periods, with the austral summer shift consistently larger than the boreal summer shift across datasets. It also detected an accelerating eastward shift and a decreasing trajectory amplitude, which the abstract says is projected to intensify throughout this century.

What to keep in mind

The abstract does not describe detailed limitations beyond noting that a unified metric had been lacking. It also does not provide numerical values in the summary provided here.

Key points

  • The global green wave centroid shifts northward in both boreal and austral summer.
  • The austral summer northward shift is consistently larger than the boreal summer shift across datasets.
  • The green wave trajectory amplitude is decreasing and is projected to intensify this century.
  • An accelerating eastward shift was detected and described as previously unreported.
  • The approach uses satellite and Earth system model data to track global phenology.

Disclosure

Research title:
Global green wave centroid shifts north and east
Authors:
Miguel D. Mahecha, Guido Kraemer, Martin Reinhardt, David Montero, Fabian Gans, Ana Bastos, Hannes Feilhauer, Ida Flik, Chaonan Ji, Teja Kattenborn, Mirco Migliavacca, Milena Mönks, Johannes Quaas, Sebastian Sippel, Sophia Walther, Sebastian Wieneke, Christian Wirth, Gustau Camps-Valls
Institutions:
Center For Remote Sensing (United States), Center For Remote Sensing (United States), Center For Remote Sensing (United States), Center For Remote Sensing (United States), Center For Remote Sensing (United States), Center For Remote Sensing (United States), Center For Remote Sensing (United States), Center For Remote Sensing (United States), Center For Remote Sensing (United States), Center For Remote Sensing (United States), Center for Scalable Data Analytics and Artificial Intelligence, Center for Scalable Data Analytics and Artificial Intelligence, Center for Scalable Data Analytics and Artificial Intelligence, European Commission, GeoInformation (United Kingdom), German Centre for Integrative Biodiversity Research, German Centre for Integrative Biodiversity Research, German Centre for Integrative Biodiversity Research, German Centre for Integrative Biodiversity Research, German Centre for Integrative Biodiversity Research, German Centre for Integrative Biodiversity Research, Helmholtz Association of German Research Centres, Helmholtz Association of German Research Centres, Helmholtz Centre for Environmental Research, Helmholtz Centre for Environmental Research, Helmholtz Centre for Infection Research, Helmholtz Centre for Infection Research, Leipzig University, Leipzig University, Leipzig University, Leipzig University, Leipzig University, Leipzig University, Leipzig University, Leipzig University, Leipzig University, Leipzig University, Leipzig University, Leipzig University, Leipzig University, Max Planck Institute for Biogeochemistry, Max Planck Institute for Biogeochemistry, Max Planck Institute for Biogeochemistry, Max Planck Institute for Meteorology, Max Planck Institute for Meteorology, Universitat de València, University of Freiburg
Publication date:
2026-02-23
DOI:
10.1073/pnas.2515835123
OpenAlex record:
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AI provenance: This post was generated by gpt-5.4-mini (OpenAI). The original authors did not write or review this post.

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