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.
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ERA-Interim data were accessed from http://apps.ecmwf.int/datasets. ESA-CCI data were accessed from https://www.esa-soilmoisture-cci.org. GLEAM data are available through https://www.gleam.eu/. MSWEP data are available through http://www.gloh2o.org/. The FLEXPART model can be downloaded via https://www.flexpart.eu/. FLEXPART data are available upon request from the corresponding author.
Python scripts are available upon request from the corresponding author.
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).
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).
Atlas of Mortality and Economic Losses from Weather, Climate and Water Extremes (1979–2012) WMO-No. 1123 (WMO, 2014).
Russo, S., Sillmann, J. & Sterl, A. Humid heat waves at different warming levels. Sci. Rep. 7, 7477 (2017).
Mora, C. et al. Global risk of deadly heat. Nat. Clim. Change 7, 501–506 (2017).
Sillmann, J. et al. Understanding, modeling and predicting weather and climate extremes: challenges and opportunities. Weather Clim. Extrem. 18, 65–74 (2017).
Fischer, E. M. Autopsy of two mega-heatwaves. Nat. Geosci. 7, 332–333 (2014).
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).
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).
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).
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).
Black, E., Blackburn, M., Harrison, G., Hoskins, B. & Methven, J. Factors contributing to the summer 2003 European heatwave. Weather 59, 217–223 (2004).
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).
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).
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).
Seneviratne, S. I., Lüthi, D., Litschi, M. & Schär, C. Land–atmosphere coupling and climate change in Europe. Nature 443, 205–209 (2006).
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).
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).
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).
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).
Wegren, S. K. Food security and Russia’s 2010 drought. Eurasia. Geogr. Econ. 52, 140–156 (2011).
Sun, Y. et al. Rapid increase in the risk of extreme summer heat in Eastern China. Nat. Clim. Change 4, 1082–1085 (2014).
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).
Russo, S. et al. Half a degree and rapid socioeconomic development matter for heatwave risk. Nat. Commun. 10, 136 (2019).
Rasmijn, L. M. et al. Future equivalent of 2010 Russian heatwave intensified by weakening soil moisture constraints. Nat. Clim. Change 8, 381–385 (2018).
Zscheischler, J. et al. Future climate risk from compound events. Nat. Clim. Change 8, 469–477 (2018).
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).
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).
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).
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).
Miralles, D. G. et al. Global land-surface evaporation estimated from satellite-based observations. Hydrol. Earth Syst. Sci. 7, 8479–8519 (2011).
Martens, B. et al. GLEAM v3: satellite-based land evaporation and root-zone soil moisture. Geosci. Model Dev. 10, 1903–1925 (2017).
Liu, Y. Y. et al. Trend-preserving blending of passive and active microwave soil moisture retrievals. Remote Sens. Environ. 123, 280–297 (2012).
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).
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).
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).
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).
Gimeno, L. et al. Oceanic and terrestrial sources of continental precipitation. Rev. Geophys. 50, RG4003 (2012).
Ramos, A. M. et al. Atmospheric rivers moisture sources from a Lagrangian perspective. Earth Syst. Dynam. 7, 371–384 (2016).
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).
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).
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).
Emanuel, K. A. A scheme for representing cumulus convection in large-scale models. J. Atmos. Sci. 48, 2313–2329 (1991).
Seibert, P. & Frank, A. Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode. Atmos. Chem. Phys. 4, 51–63 (2004).
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).
Läderach, A. & Sodemann, H. A revised picture of the atmospheric moisture residence time. Geophys. Res. Lett. 43, 924–933 (2016).
Stohl, A. & Seibert, P. Accuracy of trajectories as determined from the conservation of meteorological tracers. Q. J. R. Meteorol. Soc. 124, 1465–1484 (1998).
DeCaria, A. J. Relating static energy to potential temperature: a caution. J. Atmos. Sci. 64, 1410–1412 (2006).
Miralles, D. G. et al. Contribution of water-limited ecoregions to their own supply of rainfall. Environ. Res. Lett. 11, 124007 (2016).
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).
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).
The authors declare no competing interests.
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