Skip to main content

Thank you for visiting 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.

Amplification of mega-heatwaves through heat torrents fuelled by upwind drought


Mega-heatwaves are among the deadliest natural disasters in midlatitudes. During such events, the atmospheric circulation is typically governed by persistent anticyclones, enabling cloud-free conditions and advection of hot air. Dry soils in heatwave regions are also known to further contribute to the escalation of air temperatures. However, while local land–atmosphere feedbacks are well studied, the same does not apply to the influence of upwind areas, from where heat is advected. Here we investigate reanalysis data using a Lagrangian heat-tracking model to unravel the role of upwind land–atmosphere feedbacks during the two European mega-heatwaves of this century: the events in 2003 and 2010. Our analysis indicates that advected sensible heat can come in torrents, suddenly and intensely, leading to abrupt increases in air temperatures that further strengthen local land–atmosphere feedbacks via soil desiccation. During both mega-heatwaves, about 30% of the advected sensible heat was caused by the drought upwind. Since subtropical droughts are projected to aggravate during this century, in light of our results, this may be accompanied by consequent intensification of midlatitude mega-heatwaves. We therefore recommend considering not only local, but also upwind land cover and land-use management in the design of adaptation strategies against compound drought–heatwave events.

This is a preview of subscription content

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Summer temperatures and heat budget for the region affected by the 2010 event.
Fig. 2: Origins of the sensible heat anomaly during the 2010 mega-heatwave.
Fig. 3: Downwind propagation of compound drought–heatwave events.

Data availability

ERA-Interim data were accessed from ESA-CCI data were accessed from GLEAM data are available through MSWEP data are available through The FLEXPART model can be downloaded via FLEXPART data are available upon request from the corresponding author.

Code availability

Python scripts are available upon request from the corresponding author.


  1. 1.

    Sánchez-Benítez, A., García-Herrera, R., Barriopedro, D., Sousa, P. M. & Trigo, R. The earliest European summer mega-heatwave of reanalysis period. Geophys. Res. Lett. 45, 1955–1962 (2018).

    Article  Google Scholar 

  2. 2.

    Larcom, S., She, P.-W. & van Gevelt, T. The UK summer heatwave of 2018 and public concern over energy security. Nat. Clim. Change 9, 370–373 (2019).

    Article  Google Scholar 

  3. 3.

    Atlas of Mortality and Economic Losses from Weather, Climate and Water Extremes (1979–2012) WMO-No. 1123 (WMO, 2014).

  4. 4.

    Russo, S., Sillmann, J. & Sterl, A. Humid heat waves at different warming levels. Sci. Rep. 7, 7477 (2017).

    Article  Google Scholar 

  5. 5.

    Mora, C. et al. Global risk of deadly heat. Nat. Clim. Change 7, 501–506 (2017).

    Article  Google Scholar 

  6. 6.

    Sillmann, J. et al. Understanding, modeling and predicting weather and climate extremes: challenges and opportunities. Weather Clim. Extrem. 18, 65–74 (2017).

    Article  Google Scholar 

  7. 7.

    Fischer, E. M. Autopsy of two mega-heatwaves. Nat. Geosci. 7, 332–333 (2014).

    Article  Google Scholar 

  8. 8.

    Fischer, E. M., Seneviratne, S. I., Lüthi, D. & Schär, C. Contribution of land–atmosphere coupling to recent European summer heat waves. Geophys. Res. Lett. 34, L06707 (2007).

    Article  Google Scholar 

  9. 9.

    Miralles, D. G., Teuling, A. J., van Heerwaarden, C. C. & Vilà-Guerau de Arellano, J. Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation. Nat. Geosci. 7, 345–349 (2014).

    Article  Google Scholar 

  10. 10.

    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 

  11. 11.

    Xoplaki, E., González-Rouco, J. F., Luterbacher, J. & Wanner, H. Mediterranean summer air temperature variability and its connection to the large-scale atmospheric circulation and SSTs. Clim. Dyn. 20, 723–739 (2003).

    Article  Google Scholar 

  12. 12.

    Black, E., Blackburn, M., Harrison, G., Hoskins, B. & Methven, J. Factors contributing to the summer 2003 European heatwave. Weather 59, 217–223 (2004).

    Article  Google Scholar 

  13. 13.

    Barriopedro, D., Fischer, E. M., Luterbacher, J., Trigo, R. M. & García-Herrera, R. The Hot summer of 2010: redrawing the temperature record map of Europe. Science 332, 220–224 (2011).

    Article  Google Scholar 

  14. 14.

    Quesada, B., Vautard, R., Yiou, P., Hirschi, M. & Seneviratne, S. I. Asymmetric European summer heat predictability from wet and dry southern winters and springs. Nat. Clim. Change 2, 736–741 (2012).

    Article  Google Scholar 

  15. 15.

    Miralles, D. G., Gentine, P., Seneviratne, S. I. & Teuling, A. J. Land–atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges. Ann. N. Y. Acad. Sci. 1436, 1–17 (2019).

    Article  Google Scholar 

  16. 16.

    Seneviratne, S. I., Lüthi, D., Litschi, M. & Schär, C. Land–atmosphere coupling and climate change in Europe. Nature 443, 205–209 (2006).

    Article  Google Scholar 

  17. 17.

    Santanello, J. A., Peters-Lidard, C. D., Kumar, S. V., Alonge, C. & Tao, W.-K. A modeling and observational framework for diagnosing local land–atmosphere coupling on diurnal time scales. J. Hydrometeorol. 10, 577–599 (2009).

    Article  Google Scholar 

  18. 18.

    Miralles, D. G., van den Berg, M. J., Teuling, A. J. & de Jeu, R. A. M. Soil moisture–temperature coupling: a multiscale observational analysis. Geophys. Res. Lett. 39, L21707 (2012).

    Article  Google Scholar 

  19. 19.

    Coumou, D., Di Capua, G., Vavrus, S., Wang, L. & Wang, S. The influence of Arctic amplification on mid-latitude summer circulation. Nat. Commun. 9, 2959 (2018).

    Article  Google Scholar 

  20. 20.

    Zampieri, M. et al. Hot European summers and the role of soil moisture in the propagation of Mediterranean drought. J. Clim. 22, 4747–4758 (2009).

    Article  Google Scholar 

  21. 21.

    Wegren, S. K. Food security and Russia’s 2010 drought. Eurasia. Geogr. Econ. 52, 140–156 (2011).

    Article  Google Scholar 

  22. 22.

    Sun, Y. et al. Rapid increase in the risk of extreme summer heat in Eastern China. Nat. Clim. Change 4, 1082–1085 (2014).

    Article  Google Scholar 

  23. 23.

    Hauser, M., Orth, R. & Seneviratne, S. I. Role of soil moisture versus recent climate change for heat waves in western Russia. Geophys. Res. Lett. 43, 2819–2826 (2016).

    Article  Google Scholar 

  24. 24.

    Russo, S. et al. Half a degree and rapid socioeconomic development matter for heatwave risk. Nat. Commun. 10, 136 (2019).

    Article  Google Scholar 

  25. 25.

    Rasmijn, L. M. et al. Future equivalent of 2010 Russian heatwave intensified by weakening soil moisture constraints. Nat. Clim. Change 8, 381–385 (2018).

    Article  Google Scholar 

  26. 26.

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

    Article  Google Scholar 

  27. 27.

    Christidis, N., Jones, G. S. & Stott, P. A. Dramatically increasing chance of extremely hot summers since the 2003 European heatwave. Nat. Clim. Change 5, 46–50 (2015).

    Article  Google Scholar 

  28. 28.

    Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597 (2011).

    Article  Google Scholar 

  29. 29.

    Stohl, A., Forster, C., Frank, A., Seibert, P. & Wotawa, G. Technical note: the Lagrangian particle dispersion model FLEXPART version 6.2. Atmos. Chem. Phys. 5, 2461–2474 (2005).

    Article  Google Scholar 

  30. 30.

    Sodemann, H., Schwierz, C. & Wernli, H. Interannual variability of Greenland winter precipitation sources: Lagrangian moisture diagnostic and North Atlantic Oscillation influence. J. Geophys. Res. 113, D03107 (2008).

    Google Scholar 

  31. 31.

    Miralles, D. G. et al. Global land-surface evaporation estimated from satellite-based observations. Hydrol. Earth Syst. Sci. 7, 8479–8519 (2011).

    Article  Google Scholar 

  32. 32.

    Martens, B. et al. GLEAM v3: satellite-based land evaporation and root-zone soil moisture. Geosci. Model Dev. 10, 1903–1925 (2017).

    Article  Google Scholar 

  33. 33.

    Liu, Y. Y. et al. Trend-preserving blending of passive and active microwave soil moisture retrievals. Remote Sens. Environ. 123, 280–297 (2012).

    Article  Google Scholar 

  34. 34.

    Dorigo, W. A. et al. ESA CCI Soil Moisture for improved Earth system understanding: state-of-the art and future directions. Remote Sens. Environ. 203, 185–215 (2017).

    Article  Google Scholar 

  35. 35.

    Beck, H. E. et al. MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data. Hydrol. Earth Syst. Sci. 21, 589–615 (2017).

    Article  Google Scholar 

  36. 36.

    Stohl, A., Hittenberger, M. & Wotawa, G. Validation of the Lagrangian particle dispersion model FLEXPART against large-scale tracer experiment data. Atmos. Environ. 32, 4245–4264 (1998).

    Article  Google Scholar 

  37. 37.

    Stohl, A. & James, P. A Lagrangian analysis of the atmospheric branch of the global water cycle. Part I: method description, validation, and demonstration for the August 2002 flooding in central Europe. J. Hydrometeorol. 5, 656–678 (2004).

    Article  Google Scholar 

  38. 38.

    Gimeno, L. et al. Oceanic and terrestrial sources of continental precipitation. Rev. Geophys. 50, RG4003 (2012).

    Article  Google Scholar 

  39. 39.

    Ramos, A. M. et al. Atmospheric rivers moisture sources from a Lagrangian perspective. Earth Syst. Dynam. 7, 371–384 (2016).

    Article  Google Scholar 

  40. 40.

    Salah, Z., Nieto, R., Drumond, A., Gimeno, L. & Vicente-Sorrano, S. M. A Lagrangian analysis of the moisture budget over the Fertile Crescent during two intense drought episodes. J. Hydrol. 560, 382–395 (2018).

    Article  Google Scholar 

  41. 41.

    Stohl, A., Wotawa, G., Seibert, P. & Kromp-Kolb, H. Interpolation errors in wind fields as a function of spatial and temporal resolution and their impact on different types of kinematic trajectories. J. Appl. Meteorol. Climatol. 34, 2149–2165 (1995).

    Article  Google Scholar 

  42. 42.

    Pisso, I., Marécal, V., Legras, B. & Berthet, G. Sensitivity of ensemble Lagrangian reconstructions to assimilated wind time step resolution. Atmos. Chem. Phys. 10, 3155–3162 (2010).

    Article  Google Scholar 

  43. 43.

    Emanuel, K. A. A scheme for representing cumulus convection in large-scale models. J. Atmos. Sci. 48, 2313–2329 (1991).

    Article  Google Scholar 

  44. 44.

    Seibert, P. & Frank, A. Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode. Atmos. Chem. Phys. 4, 51–63 (2004).

    Article  Google Scholar 

  45. 45.

    Van der Ent, R. J. & Tuinenburg, O. A. The residence time of water in the atmosphere revisited. Hydrol. Earth Syst. Sci. 21, 779–790 (2017).

    Article  Google Scholar 

  46. 46.

    Läderach, A. & Sodemann, H. A revised picture of the atmospheric moisture residence time. Geophys. Res. Lett. 43, 924–933 (2016).

    Article  Google Scholar 

  47. 47.

    Stohl, A. & Seibert, P. Accuracy of trajectories as determined from the conservation of meteorological tracers. Q. J. R. Meteorol. Soc. 124, 1465–1484 (1998).

    Article  Google Scholar 

  48. 48.

    DeCaria, A. J. Relating static energy to potential temperature: a caution. J. Atmos. Sci. 64, 1410–1412 (2006).

    Article  Google Scholar 

  49. 49.

    Miralles, D. G. et al. Contribution of water-limited ecoregions to their own supply of rainfall. Environ. Res. Lett. 11, 124007 (2016).

    Article  Google Scholar 

  50. 50.

    Miralles, D. G. et al. The WACMOS-ET project – Part 2: evaluation of global terrestrial evaporation data sets. Hydrol. Earth Syst. Sci. 20, 823–842 (2016).

    Article  Google Scholar 

Download references


The authors acknowledge support from the European Research Council (ERC) under grant agreement no. 715254 (DRY–2–DRY). We also thank L. Gimeno and R. Nieto for their support related to FLEXPART. The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation - Flanders (FWO) and the Flemish Government, Department of Economy, Science and Innovation (EWI).

Author information




D.G.M. and D.L.S. conceived the study. D.L.S, D.G.M., J.K. and C.C.v.H. designed the experiments. D.L.S. conducted the analysis. J.K. provided the FLEXPART simulations. D.L.S., D.G.M. and J.K. wrote the paper. All authors contributed to the interpretation and discussion of the results and the editing of the manuscript.

Corresponding author

Correspondence to Dominik L. Schumacher.

Ethics declarations

Competing interests

The authors declare no competing interests.

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 figures.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Schumacher, D.L., Keune, J., van Heerwaarden, C.C. et al. Amplification of mega-heatwaves through heat torrents fuelled by upwind drought. Nat. Geosci. 12, 712–717 (2019).

Download citation

Further reading


Quick links