Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Northern ecosystem productivity reduced by Rossby-wave-driven hot–dry conditions

Nature Geoscience volume 18, pages 615–623 (2025)Cite this article

Subjects

Abstract

Large-scale quasi-stationary Rossby waves in the tropospheric jet stream favour spatially compounding hot–dry and cold–wet weather across the northern hemisphere. However, how this circumglobal circulation pattern affects northern hemisphere ecosystem productivity remains unexplored. Here, using satellite proxies of vegetation photosynthesis, we assess the impact of Rossby wave-7 events during which the jet stream exhibits seven peaks and troughs and tends to produce prolonged weather anomalies. Our results show organized declines in vegetation productivity in warm cores and enhancement in cold cores at northern mid-latitudes during summer Rossby wave-7 events. Mid-latitude biomes within warm cores become much more susceptible to water limitations, resulting from an increased exposure to compound hot–dry (or cold–wet) extremes and a nonlinear physiological response to compound stressors. Of the warm cores analysed, wave events elevate the climatic risk of productivity declines by a factor of 8.3, 6.2 and 4.0 over western Europe, western Asia and the western United States, respectively, due to hot–dry extremes. In particular, 32–44% of the warm anomalies and 52–88% of the dry anomalies fall within the range of warmer–drier conditions projected for 2081–2100 by state-of-the-art climate models under a medium emissions scenario. Therefore, the observed Rossby-wave-driven impacts provide an indication of how a warmer–drier future climate could reduce the carbon uptake capacity of northern hemisphere ecosystems.

Access through your institution
Buy or subscribe

This is a preview of subscription content, access via your institution

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Regionally averaged productivity anomalies during RW7 events.
Fig. 2: The dependence of vegetation productivity on SM.
Fig. 3: Productivity anomalies during compound RW7 events.
Fig. 4: Productivity response to joint occurrences of Ta and SM extremes.
Fig. 5: AIF for hot–dry and cold–wet extremes during RW7 events.
Fig. 6: RW7-observed Ta and SM anomalies versus projected future Ta and SM changes.

Similar content being viewed by others

Data availability

All observational data that support the findings of this study are available as follows. The MODIS fPAR data are available at https://e4ftl01.cr.usgs.gov/MOLT/MOD15A2H.061/. MODIS surface reflectance data for deriving NIRV are available at https://e4ftl01.cr.usgs.gov/MOTA/MCD43C4.061/. The ERA5 reanalysis product is available at https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels?tab=overview. The ERA5-land reanalysis product is available at https://cds.climate.copernicus.eu/datasets/reanalysis-era5-land?tab=overview. The CSIF data are available at https://osf.io/8xqy6/. The Breathing Earth System Simulator PAR data are available at https://www.environment.snu.ac.kr/data/. The CMIP6 ESM outputs are available at https://esgf-node.ipsl.upmc.fr/search/cmip6-ipsl/.

Code availability

All data analyses and visualizations were performed using MATLAB 2024b. The processing codes are available from the corresponding author upon request.

References

  1. Ciais, P. et al. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437, 529–533 (2005).

    Article  CAS  Google Scholar 

  2. Reichstein, M. et al. Climate extremes and the carbon cycle. Nature 500, 287–295 (2013).

    Article  CAS  Google Scholar 

  3. Seneviratne, S. I. et al. Weather and Climate Extreme Events in a Changing Climate. in Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Masson-Delmotte, V. et al.) 1513–1766 (Cambridge Univ. Press, 2021).

  4. Singh, J., Ashfaq, M., Skinner, C. B., Anderson, W. B. & Singh, D. Amplified risk of spatially compounding droughts during co-occurrences of modes of natural ocean variability. npj Clim. Atmos. Sci. 4, 7 (2021).

    Article  Google Scholar 

  5. Lau, W. K. M. & Kim, K.-M. The 2010 Pakistan flood and Russian heat wave: teleconnection of hydrometeorological extremes. J. Hydrometeorol. 13, 392–403 (2012).

    Article  Google Scholar 

  6. Lu, R. et al. Heat waves in summer 2022 and increasing concern regarding heat waves in general. Atmos. Ocean. Sci. Lett. 16, 100290 (2023).

    Article  Google Scholar 

  7. Zachariah, M. et al. Extreme Heat in North America, Europe and China in July 2023 Made Much More Likely by Climate Change (Imperial College London, 2023); https://doi.org/10.25561/105549

  8. Rousi, E., Kornhuber, K., Beobide-Arsuaga, G., Luo, F. & Coumou, D. Accelerated western European heatwave trends linked to more-persistent double jets over Eurasia. Nat. Commun. 13, 3851 (2022).

    Article  CAS  Google Scholar 

  9. Dorado-Liñán, I. et al. Jet stream position explains regional anomalies in European beech forest productivity and tree growth. Nat. Commun. 13, 2015 (2022).

    Article  Google Scholar 

  10. Kornhuber, K. et al. Extreme weather events in early summer 2018 connected by a recurrent hemispheric wave-7 pattern. Environ. Res. Lett. 14, 054002 (2019).

    Article  Google Scholar 

  11. Teng, H., Branstator, G., Wang, H., Meehl, G. A. & Washington, W. M. Probability of US heat waves affected by a subseasonal planetary wave pattern. Nat. Geosci. 6, 1056–1061 (2013).

    Article  CAS  Google Scholar 

  12. White, R. H., Kornhuber, K., Martius, O. & Wirth, V. From atmospheric waves to heatwaves: a waveguide perspective for understanding and predicting concurrent, persistent, and extreme extratropical weather. Bull. Am. Meteorol. Soc. 103, E923–E935 (2022).

    Article  Google Scholar 

  13. Kornhuber, K. et al. Amplified Rossby waves enhance risk of concurrent heatwaves in major breadbasket regions. Nat. Clim. Change 10, 48–53 (2019).

    Article  Google Scholar 

  14. Röthlisberger, M., Frossard, L., Bosart, L. F., Keyser, D. & Martius, O. Recurrent synoptic-scale Rossby wave patterns and their effect on the persistence of cold and hot spells. J. Clim. 32, 3207–3226 (2019).

    Article  Google Scholar 

  15. Lewis, S. C., King, A. D. & Perkins-Kirkpatrick, S. E. Defining a new normal for extremes in a warming world. Bull. Am. Meteorol. Soc. 98, 1139–1151 (2017).

    Article  Google Scholar 

  16. van der Woude, A. M. et al. Temperature extremes of 2022 reduced carbon uptake by forests in Europe. Nat. Commun. 14, 6218 (2023).

    Article  Google Scholar 

  17. Wolf, S. et al. Warm spring reduced carbon cycle impact of the 2012 US summer drought. Proc. Natl Acad. Sci. USA 113, 5880–5885 (2016).

    Article  CAS  Google Scholar 

  18. Kornhuber, K. et al. Risks of synchronized low yields are underestimated in climate and crop model projections. Nat. Commun. 14, 3528 (2023).

    Article  CAS  Google Scholar 

  19. Lesk, C. et al. Compound heat and moisture extreme impacts on global crop yields under climate change. Nat. Rev. Earth Environ. 3, 872–889 (2022).

    Article  Google Scholar 

  20. Choat, B. et al. Triggers of tree mortality under drought. Nature 558, 531–539 (2018).

    Article  CAS  Google Scholar 

  21. Williams, P. A. et al. Temperature as a potent driver of regional forest drought stress and tree mortality. Nat. Clim. Change 3, 292–297 (2012).

    Article  Google Scholar 

  22. Morfopoulos, C. et al. Vegetation responses to climate extremes recorded by remotely sensed atmospheric formaldehyde. Glob. Change Biol. 28, 1809–1822 (2022).

    Article  CAS  Google Scholar 

  23. Peters, W., Bastos, A., Ciais, P. & Vermeulen, A. A historical, geographical and ecological perspective on the 2018 European summer drought. Philos. Trans. R. Soc. London B 375, 20190505 (2020).

    Article  Google Scholar 

  24. Kroll, J. et al. Spatially varying relevance of hydrometeorological hazards for vegetation productivity extremes. Biogeosciences 19, 477–489 (2022).

    Article  CAS  Google Scholar 

  25. Wu, X. & Jiang, D. Probabilistic impacts of compound dry and hot events on global gross primary production. Environ. Res. Lett. 17, 034049 (2022).

    Article  Google Scholar 

  26. Yang, H. et al. The detection and attribution of extreme reductions in vegetation growth across the global land surface. Glob. Change Biol. 29, 2351–2362 (2023).

    Article  CAS  Google Scholar 

  27. Zhang, Y. et al. Future reversal of warming-enhanced vegetation productivity in the Northern Hemisphere. Nat. Clim. Change 12, 581–586 (2022).

    Article  Google Scholar 

  28. Huang, M. et al. Air temperature optima of vegetation productivity across global biomes. Nat. Ecol. Evol. 3, 772–779 (2019).

    Article  Google Scholar 

  29. Zscheischler, J. et al. Impact of large-scale climate extremes on biospheric carbon fluxes: an intercomparison based on MsTMIP data. Glob. Biogeochem. Cycles 28, 585–600 (2014).

    Article  CAS  Google Scholar 

  30. Zscheischler, J. et al. A few extreme events dominate global interannual variability in gross primary production. Environ. Res. Lett. 9, 035001 (2014).

    Article  Google Scholar 

  31. Zscheischler, J. & Seneviratne, S. I. Dependence of drivers affects risks associated with compound events. Sci. Adv. 3, e1700263 (2017).

    Article  Google Scholar 

  32. Zscheischler, J. et al. Future climate risk from compound events. Nat. Clim. Change 8, 469–477 (2018).

    Article  Google Scholar 

  33. Dannenberg, M. P., Wise, E. K. & Smith, W. K. Reduced tree growth in the semiarid United States due to asymmetric responses to intensifying precipitation extremes. Sci. Adv. 5, aaw0667 (2019).

    Article  Google Scholar 

  34. Marquis, B., Bergeron, Y., Houle, D., Leduc, M. & Rossi, S. Variability in frost occurrence under climate change and consequent risk of damage to trees of western Quebec, Canada. Sci. Rep. 12, 7220 (2022).

    Article  CAS  Google Scholar 

  35. Diamond, J. M. Ecology: laboratory, field and natural experiments. Nature 304, 586–587 (1983).

    Article  Google Scholar 

  36. Grossiord, C. et al. Manipulative experiments demonstrate how long-term soil moisture changes alter controls of plant water use. Environ. Exp. Bot. 152, 19–27 (2018).

    Article  Google Scholar 

  37. Kullberg, A. T., Coombs, L., Soria Ahuanari, R. D., Fortier, R. P. & Feeley, K. J. Leaf thermal safety margins decline at hotter temperatures in a natural warming ‘experiment’ in the Amazon. N. Phytol. 241, 1447–1463 (2024).

    Article  Google Scholar 

  38. O’sullivan, O. S. et al. Thermal limits of leaf metabolism across biomes. Glob. Change Biol. 23, 209–223 (2017).

    Article  Google Scholar 

  39. Tarvainen, L. et al. Handling the heat – photosynthetic thermal stress in tropical trees. N. Phytol. 233, 236–250 (2022).

    Article  CAS  Google Scholar 

  40. Zhu, L. et al. Plasticity of photosynthetic heat tolerance in plants adapted to thermally contrasting biomes. Plant Cell Environ. 41, 1251–1262 (2018).

    Article  CAS  Google Scholar 

  41. Ummenhofer, C. C. & Meehl, G. A. Extreme weather and climate events with ecological relevance: a review. Philos. Trans. R. Soc. B 372, 20160135 (2017).

    Article  Google Scholar 

  42. Cornic, G. & Briantais, J. M. Partitioning of photosynthetic electron flow between CO2 and O2 reduction in a C3 leaf (Phaseolus vulgaris L.) at different CO2 concentrations and during drought stress. Planta 183, 178–184 (1991).

    Article  CAS  Google Scholar 

  43. Gu, L., Han, J., Wood, J. D., Chang, C. Y.-Y. & Sun, Y. Sun-induced Chl fluorescence and its importance for biophysical modeling of photosynthesis based on light reactions. N. Phytol. 223, 1179–1191 (2019).

    Article  CAS  Google Scholar 

  44. Zhang, Y. et al. On the relationship between sub-daily instantaneous and daily total gross primary production: implications for interpreting satellite-based SIF retrievals. Remote Sens. Environ. 205, 276–289 (2018).

    Article  Google Scholar 

  45. Martini, D. et al. Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production. N. Phytol. 233, 2415–2428 (2021).

    Article  Google Scholar 

  46. Dakos, V. et al. Ecosystem tipping points in an evolving world. Nat. Ecol. Evol. 3, 355–362 (2019).

    Article  Google Scholar 

  47. Fu, Z. et al. Critical soil moisture thresholds of plant water stress in terrestrial ecosystems. Sci. Adv. 8, eabq7827 (2022).

    Article  CAS  Google Scholar 

  48. Keen, R. M. et al. Changes in tree drought sensitivity provided early warning signals to the California drought and forest mortality event. Glob. Change Biol. 28, 1119–1132 (2021).

    Article  Google Scholar 

  49. Zhang, Y., Joiner, J., Alemohammad, S. H., Zhou, S. & Gentine, P. A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks. Biogeosciences 15, 5779–5800 (2018).

    Article  CAS  Google Scholar 

  50. Badgley, G., Field, C. B. & Berry, J. A. Canopy near-infrared reflectance and terrestrial photosynthesis. Sci. Adv. 3, e1602244 (2017).

    Article  Google Scholar 

  51. Reichstein, M. et al. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Glob. Change Biol. 11, 1424–1439 (2005).

    Article  Google Scholar 

  52. Pastorello, G. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci. Data 7, 225 (2020).

    Article  Google Scholar 

  53. Baldocchi, D., Novick, K., Keenan, T. & Torn, M. AmeriFlux: its impact on our understanding of the ‘breathing of the biosphere’, after 25 years. Agric. Meteorol. 348, 109929 (2024).

    Article  Google Scholar 

  54. Rebmann, C. et al. ICOS eddy covariance flux-station site setup: a review. Int. Agrophys. 32, 471–494 (2018).

    Article  Google Scholar 

  55. Ryu, Y., Jiang, C., Kobayashi, H. & Detto, M. MODIS-derived global land products of shortwave radiation and diffuse and total photosynthetically active radiation at 5 km resolution from 2000. Remote Sens. Environ. 204, 812–825 (2018).

    Article  Google Scholar 

  56. Dechant, B. et al. Canopy structure explains the relationship between photosynthesis and sun-induced chlorophyll fluorescence in crops. Remote Sens. Environ. 241, 111733 (2020).

    Article  Google Scholar 

  57. Zeng, Y. et al. A practical approach for estimating the escape ratio of near-infrared solar-induced chlorophyll fluorescence. Remote Sens. Environ. 232, 111209 (2019).

    Article  Google Scholar 

  58. Dechant, B. et al. NIRVP: a robust structural proxy for sun-induced chlorophyll fluorescence and photosynthesis across scales. Remote Sens. Environ. 268, 112763 (2022).

    Article  Google Scholar 

Download references

Acknowledgements

X.L. and P.G. acknowledge support from the LEMONTREE (Land Ecosystem Models based on New Theory, obseRvations and ExperimEnts) project, funded through the generosity of E. and W. Schmidt by recommendation of the Schmidt Futures programme. This work is supported by the high-performance computing platform of Peking University.

Author information

Author notes

  1. These authors contributed equally: Xu Lian, Yangmingkai Li.

Authors and Affiliations

  1. Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China

    Xu Lian & Yangmingkai Li

  2. Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA

    Xu Lian, Jiangong Liu & Pierre Gentine

  3. Lamont-Doherty Earth Observatory, Columbia University, New York, NY, USA

    Kai Kornhuber

  4. Climate Analytics, Berlin, Germany

    Kai Kornhuber

  5. Potsdam Institute for Climate Impact Research, Potsdam, Germany

    Kai Kornhuber

  6. Center for Learning the Earth with Artificial intelligence and Physics (LEAP), Columbia University, New York, NY, USA

    Pierre Gentine

  7. Climate School, Columbia University, New York, NY, USA

    Pierre Gentine

Authors
  1. Xu Lian
    View author publications

    Search author on:PubMed Google Scholar

  2. Yangmingkai Li
    View author publications

    Search author on:PubMed Google Scholar

  3. Jiangong Liu
    View author publications

    Search author on:PubMed Google Scholar

  4. Kai Kornhuber
    View author publications

    Search author on:PubMed Google Scholar

  5. Pierre Gentine
    View author publications

    Search author on:PubMed Google Scholar

Contributions

X.L. and P.G. designed the research. X.L. and Y.L. performed analysis and drafted the paper. X.L., Y.L., J.L., K.K. and P.G. contributed to the interpretation of the results and to the text.

Corresponding author

Correspondence to Xu Lian.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Geoscience thanks Yangjian Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Tom Richardson, in collaboration with the Nature Geoscience team

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–10.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lian, X., Li, Y., Liu, J. et al. Northern ecosystem productivity reduced by Rossby-wave-driven hot–dry conditions. Nat. Geosci. 18, 615–623 (2025). https://doi.org/10.1038/s41561-025-01722-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41561-025-01722-3

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing