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Drought self-propagation in drylands due to land–atmosphere feedbacks

Abstract

Reduced evaporation due to dry soils can affect the land surface energy balance, with implications for local and downwind precipitation. When evaporation is constrained by soil moisture, the atmospheric supply of water is depleted, and this deficit may propagate in time and space. This mechanism could theoretically result in the self-propagation of droughts, but the extent to which this process occurs is unknown. Here we isolate the influence of soil moisture drought on downwind precipitation using Lagrangian moisture tracking constrained by observations from the 40 largest recent droughts worldwide. We show that dryland droughts are particularly prone to self-propagating because evaporation tends to respond strongly to enhanced soil water stress. In drylands, precipitation can decline by more than 15% due to upwind drought during a single event and up to 30% during individual months. In light of projected widespread reductions in water availability, this feedback may further exacerbate future droughts.

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Fig. 1: Impact of upwind soil drought on downwind column water vapour.
Fig. 2: Upwind soil drought propagation to downwind precipitation deficits.
Fig. 3: Drought self-propagation in drylands.
Fig. 4: Upwind drought in drylands.

Data availability

The FLEXPART model can be downloaded via https://www.flexpart.eu/. ERA-Interim data were obtained from http://apps.ecmwf.int/datasets. GLEAM data are available through https://www.gleam.eu/. MSWEP data are accessible through http://www.gloh2o.org/. The FLEXPART simulation employed here was performed by R. Nieto, A. Drumond and L. Gimeno and is not publicly accessible. Due to the large data volumes, post-processed FLEXPART data are available upon request from the corresponding author, and sample data are publicly accessible through Zenodo at https://doi.org/10.5281/zenodo.5839819, together with the complete drought event data used for analysis and event-aggregated results. Source data are provided with this paper.

Code availability

The code used for analysis is publicly available through Zenodo at https://doi.org/10.5281/zenodo.5840791.

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Acknowledgements

The authors acknowledge support from the European Research Council (ERC) under grant agreement no. 715254 (DRY–2–DRY). We also thank R. Nieto, L. Gimeno and A. Drumond for providing FLEXPART simulations and related support. The computational resources and services used for this study 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

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Contributions

D.G.M. conceived the study. D.L.S. and J.K. designed the experiments. D.L.S. conducted the analysis. D.L.S., D.G.M., J.K. and P.D. 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.

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Nature Geoscience thanks Niko Wanders, Jeffrey Basara 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.

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Extended data

Extended Data Fig. 1 All drought events used for analysis.

Analogous to Fig. 1a, yet using colors for all 40 events; for aesthetic reasons, a shows the 20 largest droughts, gauged by both their spatial extent and duration. b visualizes the remaining events, ranked 21–40.

Extended Data Fig. 2 Main climatological source regions of water vapor for the six highlighted droughts.

Source regions of tropospheric water vapor (light blue) over the respective drought areas (pink contours), covering 70% of the total water vapor; for the period 1980–2016. The extent of the respective main source region can be compared across events to gauge the dependence on proximate or more remote evaporation.

Extended Data Fig. 3 Soil stress S during the six highlighted droughts.

S, given by the ratio of E over Ep, is expressed as anomalies with respect to the climatological mean. This is calculated per pixel and using only months for which drought conditions were present according to the morphed droughts — in other words, the climatology is obtained analogously to the drought values, for the same months (or seasons), but based on 1980–2016. Brighter colors imply more soil stress (lower S) and thus more severely water-limited evaporation.

Extended Data Fig. 4 Peak drought self-propagation as a function of the climatological precipitation recycling ratio.

Similar to Fig. 3, but displaying the peak self-propagation on the y-axis, while the fraction of the respective drought pixels being classified as dryland (P/Ep < 0.65) is visualized by the color of each marker.

Supplementary information

Supplementary Information

Supplementary Table 1 and Figs. 1–3.

Source data

Source Data Fig. 1

Water-vapour data for each highlighted event.

Source Data Fig. 2

Precipitation data for each highlighted event.

Source Data Fig. 3

Drought self-propagation estimates for all events.

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Schumacher, D.L., Keune, J., Dirmeyer, P. et al. Drought self-propagation in drylands due to land–atmosphere feedbacks. Nat. Geosci. 15, 262–268 (2022). https://doi.org/10.1038/s41561-022-00912-7

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