
==== Front
Commun Earth Environ
Commun Earth Environ
Communications Earth & Environment
2662-4435
Nature Publishing Group UK London

1633
10.1038/s43247-024-01633-y
Article
Breaking Rossby waves drive extreme precipitation in the world’s arid regions
http://orcid.org/0000-0002-1175-6474
de Vries Andries Jan andries-jan.devries@unil.ch

12
http://orcid.org/0000-0003-3388-1003
Armon Moshe 2
http://orcid.org/0000-0002-8425-8150
Klingmüller Klaus 3
http://orcid.org/0000-0002-2456-6258
Portmann Raphael 24
http://orcid.org/0000-0003-0904-9495
Röthlisberger Matthias 2
http://orcid.org/0000-0002-1463-929X
Domeisen Daniela I. V. 12
1 https://ror.org/019whta54 grid.9851.5 0000 0001 2165 4204 Institute of Earth Surface Dynamics, University of Lausanne, Lausanne, Switzerland
2 https://ror.org/05a28rw58 grid.5801.c 0000 0001 2156 2780 Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
3 https://ror.org/02f5b7n18 grid.419509.0 0000 0004 0491 8257 Atmospheric Chemistry, Max Planck Institute for Chemistry, Mainz, Germany
4 grid.417771.3 0000 0004 4681 910X Climate and Agriculture, Agroscope Reckenholz, Zürich, Switzerland
20 9 2024
20 9 2024
2024
5 1 49329 1 2024
19 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
More than a third of the world’s population lives in drylands and is disproportionately at risk from hydrometeorological hazards such as drought and flooding. While weather systems governing precipitation formation in humid regions have been widely explored, our understanding of the atmospheric processes generating precipitation in arid regions remains fragmented at best. Here we show, using a variety of precipitation datasets, that Rossby wave breaking is a key atmospheric driver of precipitation in arid regions worldwide. Rossby wave breaking contributes up to 90% of daily precipitation extremes and up to 80% of total precipitation amounts in arid regions equatorward and downstream of the midlatitude storm tracks. The relevance of Rossby wave breaking for precipitation increases with increasing land aridity. Contributions of wave breaking to precipitation dominate in the poleward and westward portions of arid subtropical regions during the cool season. Our findings imply that Rossby wave breaking plays a crucial role in projections and uncertainties of future precipitation changes in societally vulnerable regions that are exposed to both freshwater shortages and flood hazards.

Daily extremes in precipitation as well as total precipitation amounts in arid regions worldwide are associated with extratropical Rossby wave breaking, according to analyses of different types of precipitation datasets.

Subject terms

Atmospheric dynamics
Natural hazards
Climate and Earth system modelling
https://doi.org/10.13039/501100001711 Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) #TMPFP2_216989 PP00PP2_198896 de Vries Andries Jan https://doi.org/10.13039/501100004189 Max-Planck-Gesellschaft (Max Planck Society) MaxWater Initiative de Vries Andries Jan https://doi.org/10.13039/501100003006 Eidgenössische Technische Hochschule Zürich (Federal Institute of Technology Zurich) 21-1 FEL-67 de Vries Andries Jan https://doi.org/10.13039/100010661 EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) EMME-CARE de Vries Andries Jan https://doi.org/10.13039/100010663 EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) grant agreement no. 787652 de Vries Andries Jan issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Drylands cover more than 40% of the Earth’s land surface and host more than two billion people. These dry regions are projected to expand in a warming climate1 along with an expected doubling of the number of people living in these regions by the end of the 21st century2. The population in these regions is disproportionately exposed to hydrometeorological hazards such as drought3 and flooding4 as developing countries, which are common in these regions, often have limited resources to mitigate freshwater shortages5 and flood hazards. A horrific example is the destructive flooding that unfolded in Libya in September 2023 and left more than 12,000 people dead according to the Emergency Event Database (EM-DAT). On the other hand, precipitation in arid regions can also replenish scarce freshwater resources on which food security and ecosystems rely6,7. Precipitation deficits and severe droughts in already water-scarce regions, amplified by climate change, have been suggested to foster armed conflict8,9 and migration10. Further increased stress on water resources in the future will likely put societies that are already affected by political and economic instability, civil unrest, and armed conflict under even larger pressure.

Under global warming, climate models generally project a decline in precipitation amounts in much of the dry subtropics11,12, while the intensities of the most severe precipitation extremes are anticipated to increase13–16, exacerbating the dual impacts of precipitation in these regions. However, projected changes in precipitation in these regions are subject to large uncertainties that stem from the regionally varying response of the atmospheric circulation to climate change, model bias, and internal climate variability17. Whereas atmospheric thermodynamics leads to a spatially homogenous and robust increase in extreme precipitation intensity globally, atmospheric dynamics can modify the extreme precipitation response to global warming at a regional level, particularly in the dry subtropics18. Understanding the atmospheric dynamics that govern precipitation formation in these dry regions is thus a prerequisite for developing plausible storylines of hydrometeorological hazards in arid regions in a future climate as well as for a process-based climate model evaluation regarding these hazards.

Weather systems at synoptic scales (~1000 km and one to several days) that govern precipitation formation in humid tropical and extratropical regions have been widely studied from a global perspective. In humid extratropical regions, precipitation largely results from extratropical cyclones19,20 and associated warm conveyor belts21, fronts22,23, and atmospheric rivers24,25. In humid (sub)tropical regions, precipitation is often associated with tropical cyclones26, monsoon lows27, and tropical easterly waves28. However, synoptic-scale weather systems leading to precipitation in arid regions have virtually only been studied at the regional scale, pointing to a variety of atmospheric processes at play29–35. These processes often include upper-level troughs36,37 and cutoff lows38–42 of midlatitude origin, suggesting a key role of extratropical wave breaking into low latitudes for the formation of precipitation in arid regions.

Rossby waves in the extratropical atmospheric circulation owe their existence to the rotation and spherical shape of the Earth43 and are of central importance for midlatitude weather and extreme events44,45. Rossby waves can amplify in the meridional direction, leading to the overturning and breaking of these waves and vigorous mixing of air masses between higher and lower latitudes46,47. Rossby wave breaking (RWB) can support the formation of precipitation by providing both atmospheric moisture advection and forcing for ascent. The influence of the upper tropospheric forcing associated with the breaking waves can extend toward the lower troposphere, inducing enhanced moisture transport and dynamically forced ascent ahead of the breaking waves, and reducing the static stability underneath, making the atmosphere conducive to deep moist convection48,49. Existing studies have linked RWB to observed precipitation extremes in several regions, including North America50, the Alpine region51, and the Middle East52 as well as to reanalysis-based precipitation in subtropical and extratropical regions globally53,54.

Here, we quantify the contribution of RWB to both precipitation extremes and total precipitation amounts in arid regions worldwide. We identify RWB by combining diagnostics for potential vorticity (PV) streamers and cutoffs (see Methods) and applying these diagnostics to atmospheric reanalysis data. Given that precipitation is a challenging variable to measure, we quantify the contribution of wave breaking to precipitation using precipitation data from different sources, including reanalysis, satellite-based estimates, station-based observations, and a product that combines these three different data sources (see Methods). We examine the contribution of RWB to precipitation over land with different degrees of aridity and provide a detailed regional and seasonal analysis focused on the world’s largest arid regions.

Results

Contribution of RWB to precipitation globally

We first demonstrate the role of RWB as a driver of extreme precipitation by 8 catastrophic flood events that caused fatalities and damages in different arid regions around the world (Fig. 1 and Table 1). For all events, the extreme precipitation occurred downstream (to the east) of the breaking waves. The upper tropospheric forcing associated with the wave breaking induces a cyclonic circulation, steering anomalous atmospheric water vapor transport toward the region of extreme precipitation. Most events feature dynamically forced ascent at the eastern flank of the breaking waves coinciding with the regions of extreme precipitation, providing a potential mechanism to build up and release conditional instability. Accordingly, in most cases, the breaking waves generate a tropospheric environment that is conducive to the occurrence of deep moist convection, evinced by climatologically anomalous to extremely high values of convective available potential energy. Reduced static stability only appears to a limited extent underneath the wave breaking, and only coincides with extreme precipitation over the ocean to the south of South Africa and Australia (not shown). This suggests that, for the cases analyzed here, the relevance of reduced static stability underneath wave breaking for precipitation is primarily limited to oceans, consistent with previous studies48,54.Fig. 1 Demonstrative example cases of Rossby wave breaking leading to catastrophic flooding in arid regions.

Eight extreme precipitation events, associated with RWB, causing flooding with catastrophic societal impacts in (a) southwest North America, (b) central North America, (c) North Africa, (d) central Asia, (e) the Atacama region, (f) Patagonia, (g) South Africa, and (h) Australia. The vertical depth of potential vorticity streamers and cutoffs is shown in blue shading (each isentropic surface with a PV structure represents a vertical depth of 5 K) for the timestep indicated in the panel titles. Black contours demarcate the daily fields used to attribute the daily precipitation to RWB based on the spatially extended PV structures (see Methods). Orange and gray dots depict the MSWEP daily extreme precipitation attributed and not attributed to RWB, respectively. Red vectors show the standardized anomalies of vertically integrated horizontal water vapor transport, gray contours the quasi-geostrophic omega at 0.1, 0.2, 0.3, and 0.4 Pa s−1 with negative (positive) values in solid (dashed) corresponding to ascent (descent), and the green diagonal and crossed hatching the convective available potential energy values exceeding the 95th and 99th percentile thresholds, respectively, for the timestep indicated in the panel titles (see Methods).

Table 1 Societal impacts of 8 flood-related natural disasters in arid regions linked to RWBa

No.	Date	Country	Location (provinces)	Deaths	Affected people	Damage USD (thousand)	
1	24 Nov 2013	United States	Oklahoma, Texas, California, New Mexico, Arizona	14		2000	
2	4–8 May 2007	United States	Colorado, Iowa, Kansas, Minnesota, Missouri, Nebraska, Oklahoma, South Dakota	12	40	350,000	
3	10–14 Nov 2001	Algeria	Alger, Boumerdes, Chlef, Mascara, Mostaganen, Oran, Relizane, Saida, Tipaza, Tizi Ouzou, Tlemcen, Ain-Defla	921	45,423	300,000	
4	21–29 Jul 2002	China	Xinjiang, Uygur, Zizhiqu	11	12,312	38,600	
5	19 Jun 1991	Chile	Antofagasta	141	82,811	6000	
6	5–21 Apr 2017	Argentina	Chubut	1	9000		
7	25 Jul–3 Aug 2016	South Africa	Western Cape, Kwazulu Natal	7	6900	180,000	
8	10–22 Sep 2016	Australia	Victoria, South Australia	1	280	25,000	
aThe data are taken from the Emergency Event Database (EM-DAT), accessed on 24-10-2023.

Next, we proceed from demonstrative case studies to a climatological analysis. To quantify the portion of precipitation that forms under the influence of RWB, we compute the fractions of daily extreme precipitation occurrences and precipitation amounts that coincide with RWB in a year-round analysis and examine where this relation has a significant or non-significant positive or negative association (see Methods). A positive (negative) association indicates that precipitation is more (less) likely to co-occur with wave breaking than under locally climatological conditions. RWB is significantly associated with precipitation in subtropical and extratropical regions equatorward and downstream of the midlatitude storm tracks (Fig. 2a and Supplementary Figs. 1a, c, e and 2a, c, e, g), where wave breaking occurs relatively frequently compared to other regions (Supplementary Fig. 3). Fractions of daily precipitation extremes significantly associated with RWB exceed 80–90% in southwest and central North America, the entire Mediterranean Basin and adjacent parts of North Africa, the Middle East and eastern Europe, the Atacama region, Patagonia, and the southern flanks of southern Africa and Australia (Fig. 2a). In the same regions, up to 70–80% of the total annual precipitation amounts occur under the influence of RWB (Supplementary Fig. 2a). Evaluation of all four precipitation datasets provides generally consistent estimates of precipitation patterns and fractions associated with RWB (Fig. 2a and Supplementary Figs. 1a, c, e and 2a, c, e, g).Fig. 2 Contribution of RWB to year-round extreme precipitation.

Fractions of year-round MSWEP daily extreme precipitation occurrences associated with RWB (a) and daily extreme precipitation occurrence surplus due to RWB (b). Crossed hatching and stippling in black (gray) in (a) indicate regions where the relationship between extreme precipitation and RWB has a significant (nonsignificant) positive and negative association, respectively (see Methods). Orange contours in (a) and purple contours in (b) denote the midlatitude storm tracks based on annual mean eddy kinetic energy (EKE; see Methods) at 0.7, 0.85, and 1.1 MJ m−2 intervals.

In contrast to the aforementioned regions, RWB has a significant negative association with precipitation (i.e., significantly less precipitation occurs during RWB than under locally climatological conditions) in humid low- and high-latitude regions where other weather systems are primarily responsible for precipitation formation (Fig. 2a and Supplementary Figs. 1a, c, e and 2a, c, e, g). Prominent regions are found over the eastern parts of the North American and Asian continents and adjacent western parts of the North Pacific and North Atlantic Ocean basins, where tropical cyclones26, extratropical cyclones19,20, and fronts22,23 govern much of the precipitation formation. Other regions where precipitation has a significant negative association with RWB can be found over the extratropical west coasts of North America, Europe, southern South America, and New Zealand, where landfalling atmospheric rivers dominate precipitation generation24,25.

The relevance of RWB for precipitation is further examined using an estimate of how much precipitation is enhanced or reduced due to RWB, referred to as precipitation surplus (see Methods). Positive and negative values (precipitation surplus and deficit) indicate how much precipitation would differ in a hypothetical world without RWB. Over the aforementioned subtropical and extratropical regions equatorward and downstream of the midlatitude storm tracks, daily extreme precipitation occurrences due to RWB attain a 60–80% surplus (Fig. 2b), and annual precipitation amounts reach a 40–60% surplus (Supplementary Fig. 2b). Over the humid low- and high-latitude regions, precipitation surplus reaches below −80% for daily extreme occurrences and below −20 to −60% for total annual precipitation amounts. Examination of all four precipitation datasets shows consistent estimates of the precipitation surplus due to RWB (Fig. 2b and Supplementary Figs. 1b, d, f and 2b, d, f, h), albeit somewhat lower fractions are found based on GPM IMERG precipitation data compared to the other three precipitation datasets (see Methods).

The relevance of RWB for precipitation follows the seasonality of the large-scale circulation (Fig. 3 and Supplementary Figs. 4 and 5). In winter, RWB contributions to precipitation reach the largest values over lower latitudes when the midlatitude storm tracks attain their strongest intensity and most equatorward influence55. For example, hotspots of winter extreme precipitation attributed to wave breaking emerge over southwestern North America and the Mediterranean in the Northern Hemisphere (Fig. 3a, c) and the Atacama region, southern Africa, and southern Australia in the Southern Hemisphere (Fig. 3b, d). In summer, large RWB contributions to extreme precipitation are evident at higher latitudes over central North America and Europe (Fig. 3b, d) and across Patagonia and the Antarctic coast (Fig. 3a, c). In several regions, the sign of the association reverses between the winter and summer seasons. For example, in the Southern Hemisphere, a negative association over the larger parts of the Atacama region, southern Africa, and Australia in austral summer (Fig. 3a, c) changes to a positive association in austral winter (Fig. 3b, d), showing that wave breaking contributes to precipitation formation in these regions primarily during winter. Seasonal precipitation amounts attributed to RWB follow a very similar pattern compared to those of extreme precipitation, albeit fractions remain somewhat lower (Fig. 3 and Supplementary Figs. 4 and 5). Across all four precipitation datasets, RWB contributions to seasonal precipitation extremes and total amounts show overall similar patterns and fractions (Fig. 3 and Supplementary Figs. 4–11), strengthening the confidence in this study’s results.Fig. 3 Contribution of RWB to seasonal extreme precipitation.

Fractions of MSWEP daily extreme precipitation occurrences associated with RWB (a, b) and daily extreme precipitation occurrence surplus due to RWB (c, d) in DJF (a, c) and JJA (b, d). Regions where extreme precipitation occurrences fall below 5% of the year-round extreme precipitation occurrences are masked in gray. Crossed hatching and stippling in black and gray in (a, b) denote associations as in Fig. 2, but for the respective seasons. Orange contours in (a, b) and purple contours in (c, d) denote the midlatitude storm tracks based on the seasonal mean EKE at 0.5, 0.7, 0.9, and 1.1 MJ m−2 intervals.

Relevance of RWB for precipitation increases with land aridity

The analysis above shows that RWB substantially contributes to precipitation equatorward and downstream of the midlatitude storm tracks, where most of the world’s arid regions are located. In a next step, we link the relevance of RWB for precipitation to land with different degrees of aridity (see Methods). Much of the arid land, here defined by a dry sub-humid to a hyper-arid climate (i.e., drylands), features a significant positive association between precipitation and wave breaking, specifically across their poleward and westward flanks (Fig. 4a, b and Supplementary Fig. 12). In contrast, the equatorward and eastward flanks of these arid regions show to a varying extent a significant negative association, most prevalent over central Asia, the Atacama region, southern Africa, and Australia. This diagonally oriented dipole pattern over several prominent arid regions shows that the extratropical forcing through RWB into low latitudes is a key driver of precipitation in the poleward and westward portions of arid regions and suggests that weather systems of tropical origin control much of the precipitation in the equatorward and eastward parts of arid regions.Fig. 4 Relevance of RWB for precipitation in arid regions.

Global aridity index categories, Antarctica excluded, and the associations between MSWEP year-round daily extreme precipitation occurrences (a) and total annual precipitation amounts (b) and RWB. As in Fig. 2a, black (gray) hatching and stippling indicate regions where precipitation has a significant (nonsignificant) positive and negative association with RWB, respectively, and green contours denote the midlatitude storm tracks. Bar segments represent fractions of land surface where precipitation has a positive (crossed hatching) or negative (stippling) association with RWB, considered significant in black and nonsignificant in gray, for the five aridity index categories for extreme precipitation occurrences (c) and total precipitation amounts (d). In (c, d) the colors and numbers indicate the distribution and spatially aggregated precipitation surplus due to RWB (see Methods) as a fraction of precipitation totals over land from the different aridity index categories based on precipitation from, left to right, MSWEP, ERA5, CPC, and GPM IMERG. Gray shaded parts of the bar denote the fraction of land surface where precipitation datasets have missing values for >50% of all days.

Portions of land surface where precipitation has a positive association with RWB increase with land aridity. Across the four evaluated precipitation datasets, fractions of land surface where extreme precipitation occurrences have a positive association with RWB reach from 17 to 41% in the world’s humid regions up to 64–79% in regions with a hyper-arid climate (Fig. 4c). Similarly, land surface fractions where total annual precipitation amounts have a positive association with RWB increase from 24 to 54% in humid regions up to 71–83% in hyper-arid regions (Fig. 4d). Turning our attention to spatially aggregated contributions of RWB to precipitation, we note that the extreme precipitation occurrence surplus ranges from a 2% surplus to a 7% deficit in humid regions to a 7–14% surplus in hyper-arid regions for extreme precipitation occurrences (Fig. 4c). Likewise, the total precipitation amount surplus reaches from a 1% surplus to a 4% deficit in humid regions to a 5–13% surplus in hyper-arid regions (Fig. 4d). Thus, from a spatially aggregated and year-round perspective, RWB tends to suppress precipitation in humid regions and supports precipitation in arid regions. While the relatively low spatially aggregated precipitation surplus values can be expected given the strong regionally and seasonally varying relationship between precipitation and RWB, this analysis shows that wave breaking contributions to precipitation increase with increasing land aridity.

Conceptually, we can interpret the increasing relevance of wave breaking for precipitation with increasing land aridity as follows (Fig. 5). Precipitation in humid subtropical and extratropical regions occurs primarily under the influence of weather systems other than RWB, leading to primarily negative precipitation-RWB associations and a precipitation deficit due to RWB in these regions. Humid tropical regions reside largely beyond the reach of the extratropical forcing, resulting in near-neutral precipitation-RWB associations in these regions. In dry sub-humid to arid regions poleward and westward of hyper-arid core regions, RWB strongly contributes to precipitation, partially offset by negative precipitation-RWB associations in the dry sub-humid to arid regions equatorward and eastward of these hyper-arid regions where RWB tends to suppress precipitation. The positive association patterns poleward and westward of the hyper-arid core regions reach to a large extent across these hyper-arid regions, leading to the largest contributions of RWB to precipitation in these very dry regions.Fig. 5 Schematic representation of the relevance of RWB for precipitation in arid regions.

Schematic depiction of land with different degrees of aridity (aridity index categories), the climate zones and associated general circulation patterns (black text), and prevailing synoptic weather systems (green text and arrows). The relevance of RWB for precipitation is shown by positive and negative associations, and by precipitation surplus and deficit due to RWB, as indicated in the legend.

A regional and seasonal perspective

To further understand the regionally and seasonally varying relevance of RWB for precipitation formation in arid regions, we further explore their relationship in eight prominent arid regions during traditionally defined seasons. These regions are (1) southwest North America, (2) central North America, (3) the southern Mediterranean, North Africa, and the Middle East, (4) central Asia, (5) the Atacama, (6) Patagonia, (7) southern Africa, and (8) Australia (Fig. 4a, b). Figure 6 and Supplementary Fig. 13 show the spatially aggregated precipitation characteristics attributed to RWB in the same fashion as in Fig. 4c, d, but based on seasonally partitioned precipitation (heights of the bars) over the dry sub-humid to hyper-arid portions of these eight regions only.Fig. 6 Contribution of RWB to extreme precipitation in arid regions and seasons.

Seasonal distribution of daily extreme precipitation occurrences in eight selected arid regions, indicated by the gray boxes in Fig. 4a, b, considering their portions with a dry sub-humid to hyper-arid climate only: southwest North America; 123–95°W, 20–40°N (a), central North America; 123–95°W, 40–60°N (b), the southern Mediterranean, North Africa, and the Middle East; 20°W–75°E, 15–40°N (c), central Asia; 40–85°E, 40–55°N and 75–120°E, 35–50°N (d), the Atacama region; 75–65°W, 15–35°S (e), Patagonia; 72.5–62.5°W, 35–55°S (f), southern Africa; 10–40°E, 15–35°S (g), and Australia; 110–155°W, 15–40°S (h). The bar height denotes the fraction of the seasonal extreme precipitation occurrences from the total annual occurrences, and the bar segments with crossed hatching and stippling reflect the fraction of arid land surface where the relationship between extreme precipitation and RWB has a positive or negative association, respectively, significant in black and nonsignificant in gray. The color in the bars indicate the distribution of extreme precipitation occurrence surplus due to RWB based on precipitation from, left to right, MSWEP, ERA5, CPC, and GPM IMERG, while the numbers above the bars show the minima and maxima of spatially aggregated extreme precipitation occurrence surplus across the four evaluated precipitation datasets. Gray shaded parts of the bar denote the fraction of land surface without any extreme precipitation occurrences during that season or where the precipitation dataset has >50% missing values for all days during that season.

In subtropical arid regions (southwest North America, the Mediterranean - North Africa - Middle East, the Atacama, southern Africa, and Australia), RWB contributes to much of the precipitation during the transition seasons and winter (Fig. 6 and Supplementary Fig. 13). Apart from Australia in MAM, RWB substantially enhances precipitation in these regions and seasons, with the spatially aggregated extreme precipitation surplus reaching from 4 to 11% in southwest North America in boreal autumn to 54–68% in southern Africa during austral winter (Fig. 6a, g; numbers above the bars). Fractions of land surface where extreme precipitation has a positive association with RWB reach from nearly half to the entire land surface (Fig. 6a, c, e, g, h; hatched parts of the bars), showing that RWB widely governs precipitation formation in the arid subtropics during the transition seasons and winter, whether being the wetter (Mediterranean - North Africa - Middle East) or the drier (the Atacama, southern Africa, and Australia) seasons of the year. In contrast, during summer, extreme precipitation has a systematic negative association with wave breaking in much of the arid land surface, except for the Mediterranean - North Africa - Middle East region, and spatially aggregated precipitation surplus due to RWB show a 7 to 19% deficit over southwest North America, southern Africa and Australia (Fig. 6). Among these regions, southern Africa and Australia receive most of their precipitation during summer (Fig. 6g, h), consistent with the significant negative association across a large part of these regions in the year-round analysis (Fig. 4a, b and Supplementary Fig. 12). These findings demonstrate that arid subtropical regions receive much of their precipitation during the transition seasons and winter under the influence of extratropical forcing through wave breaking into low latitudes and suggest that weather systems of tropical origin control much of the precipitation in these regions during the warm season when the tropical circulation exerts its most poleward influence.

Arid regions at extratropical latitudes receive precipitation under the influence of RWB during varying seasons throughout the year (Fig. 6b, d, f and Supplementary Fig. 13b, d, f). Central North America and Patagonia receive enhanced precipitation due to RWB during the transition seasons and summer, while precipitation is suppressed by RWB over central North America during winter. Over Central Asia, spatially aggregated precipitation surplus ranges from a weak deficit to moderate surplus across all seasons. Thus, extratropical arid regions differ from their subtropical counterparts, as breaking Rossby waves contribute to precipitation formation in extratropical arid regions during varying seasons throughout the year, while this is confined to the transition seasons and winter for subtropical arid regions, consistent with the seasonality of the large-scale circulation.

Discussion

This study shows that RWB significantly contributes to a large fraction of precipitation extremes and total amounts in subtropical and extratropical regions equatorward and downstream of the midlatitude storm tracks. Our results corroborate findings from previous studies that linked RWB to deep convection and precipitation in specific regions in the tropics48,56,57, subtropics36,52,58–61, and midlatitudes49–51,62,63, and to reanalysis-based precipitation53 and larger-scale extreme precipitation events54 globally. The present study substantially extends previous work by adopting a more complete diagnostic for the identification of RWB through combining PV streamers and cutoffs, by using precipitation from various datasets, by introducing a measure of how much precipitation is enhanced or reduced due to RWB, by explicitly quantifying the contributions of RWB to precipitation in arid regions globally, and by providing a detailed regional and seasonal analysis focused on the world’s major arid regions. Our results also seem to contradict previous studies that suggested an important role of RWB for extreme precipitation over the eastern United States50 and convection over the Intra-Americas during the warm season64. Our findings show mostly a suppression of precipitation by RWB in these regions and seasons, which may stem from the dynamically forced descent upstream (at the western flank) of the breaking waves, and RWB hindering the formation of other types of weather systems being relevant for precipitation in these regions, such as tropical cyclones65.

Previous studies showed several mechanism through which RWB can lead to precipitation, including (i) a strengthening of the low-tropospheric moisture transport at the eastern flank of the breaking wave toward the region of precipitation, (ii) the influence of topography on the circulation through slowing down the motion of the upper tropospheric PV anomaly and orienting the low-tropospheric moist air flow against the mountain barrier leading to orographic lifting of the moist air flow, (iii) dynamically forced ascent on the eastern flank of the breaking wave, and (iv) reduced static stability underneath the upper-tropospheric PV anomaly, based on case studies48,49,60 and climatological analyses50–52,54. Our demonstrative case studies confirm that RWB can support the formation of extreme precipitation through inducing anomalous moisture transport and dynamically forced ascent at the eastern flank of the breaking waves, generating a tropospheric environment that is conducive to deep moist convection.

We show that RWB is responsible for much of the precipitation in arid regions around the world. The importance of RWB for precipitation is particularly strong in the poleward and westward portions of subtropical arid regions, including those with a Mediterranean-type climate12, where the extratropical forcing governs precipitation formation during the cool season through wave breaking into low latitudes (Fig. 5). In contrast, the equatorward and eastward flanks of several prominent arid regions display a negative association between precipitation and RWB, suggesting that tropical weather systems regulate much of the precipitation generation during the warm season in these regions. Subtropical arid regions are typically situated at the transition between extratropical and tropical circulation regimes. As a result, these regions experience a strong seasonally alternating and geographically varying influence of both types of circulation regimes, making these regions likely very sensitive to climatic changes. In some regions, changes have been observed, or are projected to occur in the future, toward increased precipitation during the warm season and reductions in cool season precipitation66 along with a ceasing of extratropical weather systems67–69.

The findings of this study have important societal and scientific implications for understanding and predicting extremes and climatic changes in the water cycle in arid regions around the world. Applying RWB diagnostics to operational model forecasts has the potential to assist medium-range to (sub)seasonal prediction of hydrometeorological hazards in arid regions based on the demonstrated predictability of RWB variability arising from sea surface temperature forcing70. In the context of climate change, we note that wave breaking contributions to precipitation are particularly large in arid subtropical regions where climate models project a future decline in precipitation amounts17 and where projected changes in precipitation extremes suffer from large uncertainties18. This implies that the response of RWB to a warming climate is of direct relevance to the projected precipitation decline in these regions and that robust projections of future changes in precipitation extremes critically depend on climate models’ ability to accurately simulate this atmospheric process and associated precipitation generation. Earlier studies demonstrated that climate models tend to simulate wave breaking reasonably well, but they also reported substantial biases in RWB frequencies in subtropical regions71 and in the latitudinal distribution of RWB characteristics across models72. Extending our analysis to climate model simulations in future studies will thus help clarify the role of atmospheric dynamics in projections and uncertainties of future precipitation changes in societally vulnerable regions exposed to both flood hazards and freshwater shortages.

Methods

Precipitation

Precipitation is challenging to measure due to its very high spatiotemporal variability, specifically in arid regions73. To obtain well-informed estimates of precipitation attributed to RWB, we use 4 precipitation products based on 3 different types of data sources: (1) the ERA5 reanalysis74 of the European Centre for Medium-Range Weather Forecasts for 1979–2021, (2) the Integrated Multi-satellitE Retrievals of the Global Precipitation Measurement (GPM) Mission (IMERG)75, final version 6, for 2001–2020, (3) the Climate Prediction Center (CPC) global unified gauge-based analysis of daily precipitation76 of the National Oceanic and Atmospheric Administration (NOAA) for 1979–2021, and (4) the Multi-Source Weighted-Ensemble Precipitation (MSWEP)77 version V280 for 1979–2020. Each of these data sources has its own strengths and limitations78. Precipitation from reanalysis has a full coverage across space and time, and is generated by a physically consistent model, but stems from a short-range model forecast at a relatively coarse resolution and relies on parameterization for convective precipitation. The GPM IMERG product has a very high spatiotemporal resolution and provides measurements for regions with limited station coverage, but has deteriorated accuracy over mountains79 and arid regions79,80, reduced coverage toward higher latitudes80, relies in part on bias adjustment to spatially heterogeneously distributed station observations, and covers only the period since 2000. CPC precipitation is directly derived from ground-based observations, but rain gauge measurement are subject to errors, interrupted time series, and limited station density, particularly in arid regions81. The MSWEP product is based on the combination of these three different data sources to leverage their respective strengths77. Daily precipitation fields from each dataset are interpolated using first-order conservative remapping on a 0.5-degree regular grid to facilitate the attribution to RWB at the grid scale. Extreme precipitation days are defined by days on which precipitation amounts exceed the 99th percentile of all days throughout the period under consideration (Supplement Fig. 14). For the seasonal analysis, we use the same selection of year-round defined extreme precipitation days and partition these across the corresponding seasons.

Identification of RWB

Data are retrieved from the ERA5 reanalysis on a global 0.5-degree regular grid at 6-h time intervals. Potential vorticity (PV) is computed from data on model levels and then interpolated onto isentropic surfaces between 275 and 360 K with 5 K intervals. PV fields are smoothed using a 9-point local smoothing to reduce excessive small-scale PV structures. For the detection of RWB we combine the object-based identification methods of PV streamers and cutoffs, first introduced by ref. 82, and using some of the newer adaptations from refs. 52,54,83 for PV streamers, and from refs. 84,85 for PV cutoffs. Other studies have used other indicators of RWB, such as PV contour advection86, meridional reversal of PV87, and meridionally overturning contours of PV88,89, potential temperature90,91, or absolute vorticity72. Here we briefly summarize the applied identification method in this study and refer for more details, motivations for specific choices, and sensitivity analyses to refs. 52,54,82–85.

The detection of PV streamers and cutoffs is based on PV fields on single isentropic surfaces and follows three steps. First, we define in each hemisphere the stratospheric reservoir by the +2 potential vorticity unit (PVU; 1 PVU = 10−6 kg K−1 m2 s−1) contour (−2 PVU contour in the Southern Hemisphere) - representing the dynamical tropopause - at the lowest latitude that encircles the Pole. If no circumglobal PV contour is present, the longest ±2 PVU contour is designated as the stratospheric reservoir, provided it spans more than 180° in the zonal direction and reaches at least partly poleward of ±80° N. Assigned stratospheric reservoirs are evaluated on their vertical connection up to the 360 K isentropic surface to avoid erroneous classification of large-scale high PV air masses near the Earth’s surface over the Poles as stratospheric reservoir. Additionally, stratospheric reservoirs that intersect with the Earth’s surface as a result of the interpolation of PV fields from model levels to isentropic surfaces are removed.

Second, PV streamers are defined by elongated structures in the ±2 PVU contours that encircle the stratospheric reservoir. Each combination of contour points (A and B), obtained by the get_isolines function of NCL version 6.6.292, on the ±2 PVU contour is evaluated on the four following geometric criteria (see also ref. 52, their Fig. 1): (1) the width (the great-circle distance between points A and B) <1500 km, (2) the length (the largest great circle distance of any contour point between points A and B, and the great circle of points A and B) >1000 km, (3) the ratio length over width >1, after refs. 52,54, and (4) the length along the contour between points A and B <15,000 km, after ref. 83. If more than 50% of the stratospheric reservoirs’ surface is classified as streamer, all streamers are removed on that isentropic surface.

Third, all remaining >2 PVU (<- 2 PVU in the Southern Hemisphere) air masses that are not part of the stratospheric reservoir are considered as potential PV cutoffs. PV cutoffs are scrutinized on their vertical connection to the stratospheric reservoir aloft and low moisture content (specific humidity <0.1 g kg-1 and relative humidity <70% for at least 50% of the PV cutoff surface area) to remove PV structures with an orographic frictional and diabatic origin, respectively, after refs. 84,85. Only PV cutoffs with a surface area <5 × 106 km2, after ref. 85, and >2.5 × 104 km2 are retained to focus on synoptic-scale structures.

Atmospheric moisture transport and forcing for ascent

To provide insight into the mechanisms through which RWB can bring about (extreme) precipitation, we depict anomalous atmospheric moisture transport, quasi-geostrophic omega, and an index of environmental conditions favorable for deep moist convection in Fig. 1, all based on ERA5 data. More specifically, we compute standardized anomalies of the zonal and meridional components of vertically integrated horizontal water vapor transport, after refs. 52,54. The standardized anomalies are based on a 21-day running window of the mean and standard deviation with reference to period of 1979–2022. Quasi-geostrophic vertical motion is computed through the inversion of the quasi-geostrophic omega equation in Q-vector form93 using ERA5 coarse grained data at a 1.5-degree grid. We use quasi-geostrophic omega at 500 hPa based on the forcing from levels above 550 hPa to focus on the upper tropospheric forcing (i.e., wave breaking) for ascent94. Finally, we retrieved convective available potential energy as a measure of the tropospheric environmental conditions conducive to the occurrence of deep moist convection and we signify values exceeding the 95th and 99th percentile thresholds based on a 21-day running window for the period of 1979–2022.

Attribution of precipitation to RWB

Precipitation occurring under the influence of wave breaking typically forms at the downstream flank of the breaking waves (Fig. 1). The upper-level forcing and associated cyclonic circulation of the breaking waves induces enhanced moisture transport and dynamical lifting at this location48–51,54. Therefore, to attribute precipitation to wave breaking, we provide the PV structures with an extended area around their circumference using a fixed distance of 500 km, adjusted from refs. 53,54. Precipitation is attributed to wave breaking based on the following spatiotemporal criteria. Daily precipitation extremes as well as daily precipitation amounts are attributed to RWB if PV structures, including their extended area, overlap with precipitation at the grid scale on at least 3 of the 5 time intervals during daily precipitation (00, 06, 12, and 18 UTC of the same day and 00 UTC of the next day) on at least 2 isentropic surfaces as a proxy of wave breaking with a vertical depth of approximately 10 K or more. Figure 1 demonstrates the attribution of extreme precipitation to PV structures based on eight extreme precipitation events in different arid parts of the world.

Positive and negative associations and statistical significance testing

To examine the relationship between precipitation and RWB, we determine where this relationship has a positive or negative association and where this association can be considered significant. To this end, we follow the following procedure, which includes the testing of the null hypothesis that precipitation and RWB occur independently, and this hypothesis is rejected in regions where precipitation co-occurs with RWB significantly more or less than expected under independence (i.e., a two-sided test).

First, we perform a Monte Carlo test whereby the dates of PV streamers and cutoffs are shuffled by taking a random day in the same month of a different year, while the dates of precipitation are kept as in reality. In this way, the seasonal influence on the relationship between precipitation and wave breaking is accounted for. This procedure is repeated 100 times for the entire period under consideration. At each grid cell, the Monte Carlo test results in 100 computed fractions of precipitation attributed to wave breaking assuming an independent relationship. The p-value is then determined based on the ranking of the observed fraction of precipitation attributed to RWB as in reality within the distribution of 100 fractions based on random matching.

Second, we control the number of false rejections of the null hypothesis by using the false discovery rate (FDR) test95 with alpha = 0.1. Grid points with >50% missing values are not included in the FDR test. This procedure yields global fields with information at each grid point indicating whether the relationship between precipitation and RWB has a significant positive, nonsignificant, or significant negative association. A significant positive association indicates that precipitation is significantly more likely to occur in the presence of RWB than under climatology (i.e., normal conditions). A significant negative association indicates that precipitation is significantly less likely to occur in the presence of wave breaking than under climatology, suggesting the dominance of other weather systems for precipitation generation that tend to not co-occur with wave breaking. This procedure is repeated for both precipitation extremes and total amounts, for the year-round and seasonal analyses, and for each precipitation dataset.

The results from the significance testing inherently depend on the sample size, i.e., the length of the datasets that differ among the used precipitation products. To obtain consistent indications of spatially aggregated land surface where RWB favors precipitation formation, we define in addition to the significant associations, also nonsignificant positive and negative associations between precipitation and RWB at grid points where the observed fraction is larger and smaller, respectively, than the median of the fractions from the Monte Carlo samples. While positive and negative associations do not indicate statistical significance, the sign of the association is much less dependent on the length of the respective data records and is thus more easily compared across datasets with different lengths.

Precipitation surplus

Fractions of precipitation associated with RWB can be large even in regions where there is a significant negative association between precipitation and RWB, for example, in much of the humid extratropics, where wave breaking occurs relatively frequently. To obtain estimates of how much precipitation is enhanced or reduced due to RWB (note the difference to “precipitation associated with RWB”), we introduce a measure termed the precipitation surplus, denoted S. First, we compute the daily precipitation rate conditional to days without RWB, RnoRWB, and derive the total precipitation that would have formed throughout the period under consideration assuming the absence of RWB, by multiplying RnoRWB by the number of days in the considered time period (i.e., the length of the respective precipitation datasets, days with missing values excluded), yielding PnoRWB. The difference between the observed total precipitation, denoted P, and the hypothetical total precipitation in absence of RWB yields the so-called precipitation surplus, i.e., S=P−PnoRWB(1). We compute the precipitation surplus S for all months separately to account for the seasonality in the relationship between precipitation and RWB and then sum it across the year or seasons, corresponding to the respective analyses in this study. Fractions of precipitation surplus are expressed relative to total precipitation at the grid scale (Figs. 2 and 3, and Supplementary Figs. 1, 2, 4–11) or based on spatially aggregated quantities (Figs. 4c, d, 6 and Supplementary Fig. 13). Spatial aggregations of precipitation surplus are area-weighted based on the surface area that each grid point represents. Identical computations are performed for both the extreme precipitation occurrences and precipitation amounts. This approach provides an ad hoc estimate of the precipitation that forms due to (surplus) or is suppressed by (deficit) RWB and supports an adequate comparison of RWB contributions to precipitation across regions with a spatially varying RWB climatology and precipitation from various datasets.

Differences in results from the varying precipitation datasets

All analyses in this study, from global to regional scales and from year-round to seasonal timescales, show generally robust results across the four evaluated precipitation datasets, providing confidence in the results. However, we note a systematic lower contribution of RWB to precipitation based on GPM IMERG compared to the other three datasets (ERA5, CPC, and MSWEP) in terms of local associations and surplus (Figs. 2 and 3, Supplementary Figs. 1,2,4–11) and land surface with a positive association and spatially aggregated precipitation surplus (Figs. 4c, d and 6, Supplementary Fig. 13). Although well beyond the scope of this paper to investigate this further, we speculate that these differences stem from the abovementioned strengths and limitations of the different precipitation products. Local convective precipitation, for which synoptic-scale processes such as RWB can be of reduced relevance compared to larger-scale precipitation events, may be better represented in GPM IMERG than in the relatively coarse resolution precipitation forecasts from reanalysis, while these storms may be missed by stations due to the low-density network in arid regions. On the other hand, precipitation from GPM IMERG has reduced accuracy over mountains and arid regions79,80, and for winter precipitation and snowfall79,80, which may contribute to the differences between the datasets, particularly the large differences for winter precipitation in the midlatitudes (Fig. 6 and Supplementary Fig. 13).

Eddy kinetic energy

To illustrate the location and intensity of the midlatitude storm tracks, we compute the eddy kinetic energy (EKE) using the 10-day high-pass filtered (fast Fourier transform) horizontal wind of ERA5 at a regular 2-degree grid at 6-h time steps and vertically integrate the mass-weighted EKE across 37 pressure levels between 1 and 1000 hPa, adjusted from ref. 55.

Aridity index

We retrieved monthly precipitation and potential evapotranspiration from the Climate Research Unit (CRU) dataset96 for the period 1979–2021. The data have a global coverage over land except for Antarctica. The aridity index (AI) is computed as the ratio of precipitation over potential evapotranspiration: AI=precipitationpotential evapotranspiration(2), and the AI categories are defined as follows, following refs. 73,97: humid (AI ≥ 0.65); dry sub-humid (0.5 ≤ AI < 0.65); semi-arid (0.2 ≤ AI < 0.5); arid (0.05 ≤ AI < 0.2); and hyper-arid (AI < 0.05).

Supplementary information

Peer Review file

Supplementary Material

Supplementary information

The online version contains supplementary material available at 10.1038/s43247-024-01633-y.

Acknowledgements

The authors thank Michael Sprenger (ETH Zurich) for generously providing quasi-geostrophic omega and Heini Wernli (ETH Zurich) for commenting on an earlier version of the manuscript. The authors appreciate the constructive comments from three reviewers that helped to improve the presentation of the results and the quality of the manuscript. M.A. was supported by an ETH Zurich Postdoctoral Fellowship (Project No. 21-1 FEL-67), by the Stiftung für Naturwissenschaftliche und Technische Forschung, the ETH Zurich Foundation, and by the Swiss National Science Foundation (grant #TMPFP2_216989). K.K. received funding from the Max Planck Graduate Center in Mainz, the MaxWater Initiative of the Max Planck Society, and the European Union’s Horizon Europe programme under grant agreement 856612 (EMME-CARE). M.R. acknowledges funding of the INTEXseas project form the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 787652). Support from the Swiss National Science Foundation through project PP00PP2_198896 to D.D. is gratefully acknowledged.

Author contributions

A.V. initiated and conceptualized the study, performed the analysis, and wrote the manuscript. M.A., K.K., R.P., M.R., and D.D. contributed to the conceptualization of the study, the discussion and interpretation of the results, and editing of the manuscript. M.R. conceived the concept of precipitation surplus.

Peer review

Peer review information

Communications Earth & Environment thanks Chuan-Chieh Chang, Ravi Kumar Kunchala and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Heike Langenberg. A peer review file is available.

Data availability

All datasets used in this study are freely available from the respective data providers. ERA5 reanalysis data from the ECWMF were obtained via the MARS archive and are also available from the Climate Data Store (https://cds.climate.copernicus.eu). Other datasets used for precipitation were accessed from NASA for GPM-IMERG, from NOAA for CPC, and from GloH2O (https://www.gloh2o.org) for MSWEP, while monthly data from CRU were obtained via https://data.ceda.ac.uk/badc/cru/. Societal impacts from 8 demonstrative extreme precipitation events driven by RWB were obtained from the Emergency event database (EM-DAT) via https://www.emdat.be, accessed on 24-10-2023. All figures have been produced using the NCAR Command Language (NCL) version 6.6.2 software. The source data for producing the figures are available under 10.5281/zenodo.12775438.

Code availability

All computer codes used for the analyses are available from the authors upon request.

Competing interests

The authors declare no competing interests.

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

1. Feng S Fu Q Expansion of global drylands under a warming climate Atmos. Chem. Phys. 2013 13 10081 10094 10.5194/acp-13-10081-2013
Feng, S. & Fu, Q. Expansion of global drylands under a warming climate. Atmos. Chem. Phys. 13, 10081–10094 (2013).
2. Lickley M Solomon S Drivers, timing and some impacts of global aridity change Env. Res. Lett. 2018 13 104010 10.1088/1748-9326/aae013
Lickley, M. & Solomon, S. Drivers, timing and some impacts of global aridity change. Env. Res. Lett. 13, 104010 (2018).
3. Tanahrte M Chfadi T De Vries AJ Zittis G Severe drought in North Africa: a review of drivers, impacts and management Earth-Syst. Rev. 2024 250 104701 10.1016/j.earscirev.2024.104701
Tanahrte, M., Chfadi, T., De Vries, A. J. & Zittis, G. Severe drought in North Africa: a review of drivers, impacts and management. Earth-Syst. Rev. 250, 104701 (2024).
4. Yin J Flash floods – why are more of them devastating the world’s driest regions? Nature 2023 615 212 215 10.1038/d41586-023-00626-9 36882611
Yin, J. et al. Flash floods – why are more of them devastating the world’s driest regions? Nature 615, 212–215 (2023).36882611
5. Mirzabaev, A. et al. Desertification, in Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems, (eds Shukla, P. R., et al.) (University Cambridge Press, 2019). https://www.cambridge.org/core/books/climate-change-and-land/desertification/6EFB9CF89B0E8A6089583718BEBDA4E1.
6. Wang L Dryland productivity under a changing climate Nat. Clim. Change 2022 12 981 994 10.1038/s41558-022-01499-y
Wang, L. et al. Dryland productivity under a changing climate. Nat. Clim. Change 12, 981–994 (2022).
7. Berdugo M Global ecosystem thresholds driven by aridity Science 2020 367 787 790 10.1126/science.aay5958 32054762
Berdugo, M. et al. Global ecosystem thresholds driven by aridity. Science 367, 787–790 (2020).32054762
8. Gleick PH Water, drought, climate change, and conflict in Syria Weather Clim. Soc. 2014 6 331 340 10.1175/WCAS-D-13-00059.1
Gleick, P. H. Water, drought, climate change, and conflict in Syria. Weather Clim. Soc. 6, 331–340 (2014).
9. Kelley CP Mohtadi S Cane MA Seager R Kushnir Y Climate change in the Fertile Crescent and implications of the recent Syrian drought Proc. Natl Acad. Sci. 2015 112 3241 3246 10.1073/pnas.1421533112 25733898
Kelley, C. P., Mohtadi, S., Cane, M. A., Seager, R. & Kushnir, Y. Climate change in the Fertile Crescent and implications of the recent Syrian drought. Proc. Natl Acad. Sci. 112, 3241–3246 (2015).25733898
10. Cattaneo C Human migration in the era of climate change Rev. Env. Econom. Policy 2019 13 189 206 10.1093/reep/rez008
Cattaneo, C. et al. Human migration in the era of climate change. Rev. Env. Econom. Policy 13, 189–206 (2019).
11. He J Soden BJ A re-examination of the projected subtropical precipitation decline Nat. Clim. Change 2017 7 53 57 10.1038/nclimate3157
He, J. & Soden, B. J. A re-examination of the projected subtropical precipitation decline. Nat. Clim. Change 7, 53–57 (2017).
12. Seager R Climate variability and change of Mediterranean-Type climates J. Clim. 2019 32 2887 2915 10.1175/JCLI-D-18-0472.1
Seager, R. et al. Climate variability and change of Mediterranean-Type climates. J. Clim. 32, 2887–2915 (2019).
13. Donat MG Lowry AL Alexander LV O’Gorman PA Maher N More extreme precipitation in the world’s dry and wet regions Nat. Clim. Change 2016 6 508 513 10.1038/nclimate2941
Donat, M. G., Lowry, A. L., Alexander, L. V., O’Gorman, P. A. & Maher, N. More extreme precipitation in the world’s dry and wet regions. Nat. Clim. Change 6, 508–513 (2016).
14. Donat MG Angelil O Ukkola AM Intensification of precipitation extremes in the world’s humid and water-limited regions Env. Res. Lett. 2019 14 065003 10.1088/1748-9326/ab1c8e
Donat, M. G., Angelil, O. & Ukkola, A. M. Intensification of precipitation extremes in the world’s humid and water-limited regions. Env. Res. Lett. 14, 065003 (2019).
15. Zittis G Bruggeman A Lelieveld J Revisiting future extreme precipitation trends in the Mediterranean Weather Clim. Extremes 2021 34 100380 10.1016/j.wace.2021.100380
Zittis, G., Bruggeman, A. & Lelieveld, J. Revisiting future extreme precipitation trends in the Mediterranean. Weather Clim. Extremes 34, 100380 (2021).
16. Armon M Reduced rainfall in future heavy precipitation events related to contracted rain area despite increased rain rate Earth’s Future 2022 10 e2021EF002397 10.1029/2021EF002397
Armon, M. et al. Reduced rainfall in future heavy precipitation events related to contracted rain area despite increased rain rate. Earth’s Future 10, e2021EF002397 (2022).
17. Shepherd TG Atmospheric circulation as a source of uncertainty in climate change projections Nat. Geosci. 2014 7 703 708 10.1038/ngeo2253
Shepherd, T. G. Atmospheric circulation as a source of uncertainty in climate change projections. Nat. Geosci. 7, 703–708 (2014).
18. Pfahl S O’Gorman PA Fischer EM Understanding the regional pattern of projected future changes in extreme precipitation Nat. Clim. Change 2017 7 423 427 10.1038/nclimate3287
Pfahl, S., O’Gorman, P. A. & Fischer, E. M. Understanding the regional pattern of projected future changes in extreme precipitation. Nat. Clim. Change 7, 423–427 (2017).
19. Pfahl S Wernli H Quantifying the relevance of cyclones for precipitation extremes J. Clim. 2012 25 6770 6780 10.1175/JCLI-D-11-00705.1
Pfahl, S. & Wernli, H. Quantifying the relevance of cyclones for precipitation extremes. J. Clim. 25, 6770–6780 (2012).
20. Hawcroft M Shaffrey L Hodges K Dacre H How much Northern Hemisphere precipitation is associated with extratropical cyclones? Geophys. Res. Lett. 2012 39 L24809 10.1029/2012GL053866
Hawcroft, M., Shaffrey, L., Hodges, K. & Dacre, H. How much Northern Hemisphere precipitation is associated with extratropical cyclones? Geophys. Res. Lett. 39, L24809 (2012).
21. Pfahl S Madonna E Boettcher M Joos H Wernli H Warm conveyor belts in the ERA-Interim dataset (1979-2010). Part II: moisture origin and relevance for precipitation J. Clim. 2014 27 27 40 10.1175/JCLI-D-13-00223.1
Pfahl, S., Madonna, E., Boettcher, M., Joos, H. & Wernli, H. Warm conveyor belts in the ERA-Interim dataset (1979-2010). Part II: moisture origin and relevance for precipitation. J. Clim. 27, 27–40 (2014).
22. Catto JL Jakob C Nicholls N Relating global precipitation to atmospheric fronts Geophys. Res. Lett. 2012 39 L10805 10.1029/2012GL051736
Catto, J. L., Jakob, C. & Nicholls, N. Relating global precipitation to atmospheric fronts. Geophys. Res. Lett. 39, L10805 (2012).
23. Catto JL Madonna E Joos H Rudeva I Simmonds I Global relationship between fronts and warm conveyor belts and the impact on extreme precipitation J. Clim. 2015 28 8411 8429 10.1175/JCLI-D-15-0171.1
Catto, J. L., Madonna, E., Joos, H., Rudeva, I. & Simmonds, I. Global relationship between fronts and warm conveyor belts and the impact on extreme precipitation. J. Clim. 28, 8411–8429 (2015).
24. Waliser D Guan B Extreme winds and precipitation during landfall of atmospheric rivers Nat. Geosci. 2017 10 179 183 10.1038/ngeo2894
Waliser, D. & Guan, B. Extreme winds and precipitation during landfall of atmospheric rivers. Nat. Geosci. 10, 179–183 (2017).
25. Guan B Waliser DE Detection of atmospheric rivers: evaluation and application of an algorithm for global studies J. Geophys. Res. Atmos. 2015 120 12514 12535 10.1002/2015JD024257
Guan, B. & Waliser, D. E. Detection of atmospheric rivers: evaluation and application of an algorithm for global studies. J. Geophys. Res. Atmos. 120, 12514–12535 (2015).
26. Khouakhi A Villarini G Vecchi GA Contribution of tropical cyclones to rainfall at the global scale J. Clim. 2017 30 359 372 10.1175/JCLI-D-16-0298.1
Khouakhi, A., Villarini, G. & Vecchi, G. A. Contribution of tropical cyclones to rainfall at the global scale. J. Clim. 30, 359–372 (2017).
27. Hurley JV Boos WR A global climatology of monsoon low-pressure systems Q. J. Roy. Meteor. Soc. 2015 141 1049 1064 10.1002/qj.2447
Hurley, J. V. & Boos, W. R. A global climatology of monsoon low-pressure systems. Q. J. Roy. Meteor. Soc. 141, 1049–1064 (2015).
28. Crétat J Vizy EK Cook KH The relationship between African easterly waves and daily rainfall over West Africa: observations and regional climate simulations Clim. Dyn. 2015 44 385 404 10.1007/s00382-014-2120-x
Crétat, J., Vizy, E. K. & Cook, K. H. The relationship between African easterly waves and daily rainfall over West Africa: observations and regional climate simulations. Clim. Dyn. 44, 385–404 (2015).
29. Yang L Smith J Baeck ML Morin E Flash flooding in arid/semiarid regions: climatological analyses of flood-producing storms in central Arizona during the North American monsoon J. Hydrometeorol. 2019 20 1449 11471 10.1175/JHM-D-19-0016.1
Yang, L., Smith, J., Baeck, M. L. & Morin, E. Flash flooding in arid/semiarid regions: climatological analyses of flood-producing storms in central Arizona during the North American monsoon. J. Hydrometeorol. 20, 1449–11471 (2019).
30. Sierks MD Kalansky J Cannon F Ralph FM Characteristics, origins and impacts of summertime extreme precipitation in the Lake Mead Watershed J. Clim. 2020 33 2663 2680 10.1175/JCLI-D-19-0387.1
Sierks, M. D., Kalansky, J., Cannon, F. & Ralph, F. M. Characteristics, origins and impacts of summertime extreme precipitation in the Lake Mead Watershed. J. Clim. 33, 2663–2680 (2020).
31. Armon M De Vries AJ Marra F Peleg N Wernli H Saharan rainfall climatology and its relationship with surface cyclones Weather Clim. Extremes 2024 43 100638 10.1016/j.wace.2023.100638
Armon, M., De Vries, A. J., Marra, F., Peleg, N. & Wernli, H. Saharan rainfall climatology and its relationship with surface cyclones. Weather Clim. Extremes 43, 100638 (2024).
32. Ning G Understanding the mechanisms of summer extreme precipitation events in Zinjiang or arid northwest China J. Geophys. Res. Atm. 2021 126 e2020JD034111 10.1029/2020JD034111
Ning, G. et al. Understanding the mechanisms of summer extreme precipitation events in Zinjiang or arid northwest China. J. Geophys. Res. Atm. 126, e2020JD034111 (2021).
33. Reyers M Boehm C Knarr L Shao Y Crewell S Synoptic-to-regional-scale analysis of rainfall in the Atacama Desert (18°-26°S) using a long-term simulation with WRF Mon. Weather Rev. 2021 149 91 112 10.1175/MWR-D-20-0038.1
Reyers, M., Boehm, C., Knarr, L., Shao, Y. & Crewell, S. Synoptic-to-regional-scale analysis of rainfall in the Atacama Desert (18°-26°S) using a long-term simulation with WRF. Mon. Weather Rev. 149, 91–112 (2021).
34. Rapolaki RS Blamey RC Hermes JC Reason CJC A classification of synoptic weather patterns linked to extreme rainfall over the Limpopo River basin in southern Africa Clim. Dyn. 2019 53 2265 2279 10.1007/s00382-019-04829-7
Rapolaki, R. S., Blamey, R. C., Hermes, J. C. & Reason, C. J. C. A classification of synoptic weather patterns linked to extreme rainfall over the Limpopo River basin in southern Africa. Clim. Dyn. 53, 2265–2279 (2019).
35. Black AS Australian northwest cloudbands and their relationship to atmospheric rivers and precipitation Mon. Weather Rev. 2021 149 1125 1139 10.1175/MWR-D-20-0308.1
Black, A. S. et al. Australian northwest cloudbands and their relationship to atmospheric rivers and precipitation. Mon. Weather Rev. 149, 1125–1139 (2021).
36. Knippertz P Tropical–extratropical interactions related to upper-level troughs at low latitudes Dyn. Atmos. Oceans 2007 43 36 62 10.1016/j.dynatmoce.2006.06.003
Knippertz, P. Tropical–extratropical interactions related to upper-level troughs at low latitudes. Dyn. Atmos. Oceans 43, 36–62 (2007).
37. Ward N Fink AH Keane RJ Parker DJ Upper-level midlatitude troughs in boreal winter have an amplified low-latitude linkage over Africa Atmos. Sci. Lett. 2022 24 e1129 10.1002/asl.1129
Ward, N., Fink, A. H., Keane, R. J. & Parker, D. J. Upper-level midlatitude troughs in boreal winter have an amplified low-latitude linkage over Africa. Atmos. Sci. Lett. 24, e1129 (2022).
38. Abatzoglou JT Contribution of cutoff lows to precipitation across the United States J. Appl. Meteorol. Clim. 2016 55 893 899 10.1175/JAMC-D-15-0255.1
Abatzoglou, J. T. Contribution of cutoff lows to precipitation across the United States. J. Appl. Meteorol. Clim. 55, 893–899 (2016).
39. Barbero R Abatzoglou JT Fowler HJ Contribution of large-scale midlatitude disturbances to hourly precipitation extremes in the United States Clim. Dyn. 2019 52 197 208 10.1007/s00382-018-4123-5
Barbero, R., Abatzoglou, J. T. & Fowler, H. J. Contribution of large-scale midlatitude disturbances to hourly precipitation extremes in the United States. Clim. Dyn. 52, 197–208 (2019).
40. Favre A Hewitson B Lennard C Cerezo-Mota R Tadross M Cutoff lows in the South Africa region and their contribution to precipitation Clim. Dyn. 2013 41 2331 2351 10.1007/s00382-012-1579-6
Favre, A., Hewitson, B., Lennard, C., Cerezo-Mota, R. & Tadross, M. Cutoff lows in the South Africa region and their contribution to precipitation. Clim. Dyn. 41, 2331–2351 (2013).
41. Grosfeld NH McGregor S Tschetto AS An automated climatology of cool-season cutoff lows over southeastern Australia and relationships with the remote climate drivers Mon. Weather Rev. 2021 149 4167 4181 10.1175/MWR-D-21-0142.1
Grosfeld, N. H., McGregor, S. & Tschetto, A. S. An automated climatology of cool-season cutoff lows over southeastern Australia and relationships with the remote climate drivers. Mon. Weather Rev. 149, 4167–4181 (2021).
42. Barnes MA King M Reeder M Jakob C The dynamics of slow-moving coherent cyclonic potential vorticity anomalies over the eastern seaboard of Australia Quart. J. Roy. Meteorol. Soc. 2023 149 2233 2251 10.1002/qj.4503
Barnes, M. A., King, M., Reeder, M. & Jakob, C. The dynamics of slow-moving coherent cyclonic potential vorticity anomalies over the eastern seaboard of Australia. Quart. J. Roy. Meteorol. Soc. 149, 2233–2251 (2023).
43. Wirth V Riemer M Chang EKM Martius O Rossby wave packets on the midlatitude waveguide – a review Mon. Weather Rev. 2018 146 1965 2001 10.1175/MWR-D-16-0483.1
Wirth, V., Riemer, M., Chang, E. K. M. & Martius, O. Rossby wave packets on the midlatitude waveguide – a review. Mon. Weather Rev. 146, 1965–2001 (2018).
44. White RH Kornhuber K Martius O Wirth V From atmospheric waves to heatwaves: a waveguide perspective for understanding and predicting concurrent, persistent, and extreme extratropical weather B. Am. Meteorol. Soc. 2022 103 923 935 10.1175/BAMS-D-21-0170.1
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. B. Am. Meteorol. Soc. 103, 923–935 (2022).
45. Screen JA Simmonds I Amplified mid-latitude planetary waves favour particular regional weather extremes Nat. Clim. Change 2014 4 704 709 10.1038/nclimate2271
Screen, J. A. & Simmonds, I. Amplified mid-latitude planetary waves favour particular regional weather extremes. Nat. Clim. Change 4, 704–709 (2014).
46. McIntyre ME Palmer TN Breaking planetary waves in the stratosphere Nature 1983 305 593 600 10.1038/305593a0
McIntyre, M. E. & Palmer, T. N. Breaking planetary waves in the stratosphere. Nature 305, 593–600 (1983).
47. Appenzeller C Davies HC Structure of stratospheric intrusions into the troposphere Nature 1992 358 570 572 10.1038/358570a0
Appenzeller, C. & Davies, H. C. Structure of stratospheric intrusions into the troposphere. Nature 358, 570–572 (1992).
48. Funatsu BM Waugh DW Connections between potential vorticity intrusions and convection in the Eastern Tropical Pacific J. Atmos. Sci. 2008 65 987 1002 10.1175/2007JAS2248.1
Funatsu, B. M. & Waugh, D. W. Connections between potential vorticity intrusions and convection in the Eastern Tropical Pacific. J. Atmos. Sci. 65, 987–1002 (2008).
49. Schlemmer L Martius O Sprenger M Schwierz C Twitchett A Disentangling the forcing mechanisms of a heavy precipitation event along the alpine south side using potential vorticity inversion Mon. Weather Rev. 2010 138 2336 2353 10.1175/2009MWR3202.1
Schlemmer, L., Martius, O., Sprenger, M., Schwierz, C. & Twitchett, A. Disentangling the forcing mechanisms of a heavy precipitation event along the alpine south side using potential vorticity inversion. Mon. Weather Rev. 138, 2336–2353 (2010).
50. Moore BJ Keyser D Bosart LF Linkages between extreme precipitation events in the central and eastern United States and Rossby wave breaking Mon. Weather Rev. 2019 147 3327 3349 10.1175/MWR-D-19-0047.1
Moore, B. J., Keyser, D. & Bosart, L. F. Linkages between extreme precipitation events in the central and eastern United States and Rossby wave breaking. Mon. Weather Rev. 147, 3327–3349 (2019).
51. Martius O Zenklusen E Schwierz C Davies HC Episodes of alpine heavy precipitation with an overlying elongated stratospheric intrusion: a climatology Int. J. Climatol. 2006 26 1149 1164 10.1002/joc.1295
Martius, O., Zenklusen, E., Schwierz, C. & Davies, H. C. Episodes of alpine heavy precipitation with an overlying elongated stratospheric intrusion: a climatology. Int. J. Climatol. 26, 1149–1164 (2006).
52. De Vries AJ Identification of tropical-extratropical interactions and extreme precipitation events in the Middle East based on potential vorticity and moisture transport J. Geophys. Res. Atmos. 2018 123 861 881 10.1002/2017JD027587
De Vries, A. J. et al. Identification of tropical-extratropical interactions and extreme precipitation events in the Middle East based on potential vorticity and moisture transport. J. Geophys. Res. Atmos. 123, 861–881 (2018).
53. Portmann, R. The life cycles of potential vorticity cutoffs: climatology, predictability, and high impact weather, PhD thesis, (ETH Zurich, 2020). https://www.research-collection.ethz.ch/handle/20.500.11850/466735.
54. De Vries AJ A global climatological perspective on the importance of Rossby wave breaking and intense moisture transport for extreme precipitation events Weather Clim. Dyn. 2021 2 129 161 10.5194/wcd-2-129-2021
De Vries, A. J. A global climatological perspective on the importance of Rossby wave breaking and intense moisture transport for extreme precipitation events. Weather Clim. Dyn. 2, 129–161 (2021).
55. Shaw TA Storm track processes and the opposing influences of climate change Nat. Geosci. 2016 9 656 664 10.1038/ngeo2783
Shaw, T. A. et al. Storm track processes and the opposing influences of climate change. Nat. Geosci. 9, 656–664 (2016).
56. Kiladis GN Observations of Rossby waves linked to convection over the eastern Tropical Pacific J. Atmos. Sci. 1998 55 321 339 10.1175/1520-0469(1998)055<0321:OORWLT>2.0.CO;2
Kiladis, G. N. Observations of Rossby waves linked to convection over the eastern Tropical Pacific. J. Atmos. Sci. 55, 321–339 (1998).
57. Waugh, D. W., Impact of potential vorticity intrusions on subtropics upper tropospheric humidity, J. Geophys. Res. Atmos. 110, 10.1029/2004JD005664 (2005).
58. Argence S High resolution numerical study of the Algiers 2001 flash flood: sensitivity to the upper-level potential vorticity anomaly Adv. Geosci. 2006 7 251 257 10.5194/adgeo-7-251-2006
Argence, S. et al. High resolution numerical study of the Algiers 2001 flash flood: sensitivity to the upper-level potential vorticity anomaly. Adv. Geosci. 7, 251–257 (2006).
59. Knippertz P Martin JE Tropical plumes and extreme precipitation in subtropical and tropical West Africa, Q. J. Roy. Meteorol. Soc. 2005 131 2337 2365 10.1256/qj.04.148
Knippertz, P. & Martin, J. E. Tropical plumes and extreme precipitation in subtropical and tropical West. Africa, Q. J. Roy. Meteorol. Soc. 131, 2337–2365 (2005).
60. Martius O The role of upper-level dynamics and surface processes for the Pakistan flood of July 2010 Q. J. R. Meteorol. Soc. 2013 139 1780 1797 10.1002/qj.2082
Martius, O. et al. The role of upper-level dynamics and surface processes for the Pakistan flood of July 2010. Q. J. R. Meteorol. Soc. 139, 1780–1797 (2013).
61. Vellore R Monsoon–extratropical circulation interactions in Himalayan extreme rainfall Clim. Dyn. 2016 46 3517 3546 10.1007/s00382-015-2784-x
Vellore, R. et al. Monsoon–extratropical circulation interactions in Himalayan extreme rainfall. Clim. Dyn. 46, 3517–3546 (2016).
62. Ryoo JM Impact of Rossby wave breaking on U.S. West Coast winter precipitation during ENSO events J. Clim. 2013 26 6360 6382 10.1175/JCLI-D-12-00297.1
Ryoo, J. M. et al. Impact of Rossby wave breaking on U.S. West Coast winter precipitation during ENSO events. J. Clim. 26, 6360–6382 (2013).
63. Hu H Dominguez F Wang Z Linking atmospheric river hydrological impacts on the U.S. West Coast to Rossby wave breaking J. Clim. 2017 30 3381 3399 10.1175/JCLI-D-16-0386.1
Hu, H., Dominguez, F. & Wang, Z. Linking atmospheric river hydrological impacts on the U.S. West Coast to Rossby wave breaking. J. Clim. 30, 3381–3399 (2017).
64. Vigaud N Robertson A Convection regimes and tropical-midlatitude interactions over the Intra-American Seas from May to November Int. J. Climatol. 2017 37 987 1000 10.1002/joc.5051
Vigaud, N. & Robertson, A. Convection regimes and tropical-midlatitude interactions over the Intra-American Seas from May to November. Int. J. Climatol. 37, 987–1000 (2017).
65. Zhang G Wang Z Peng MS Magnusdottir G Characteristics and impacts of extratropical Rossby wave breaking during the Atlantic hurricane seasons J. Clim. 2017 30 2363 2379 10.1175/JCLI-D-16-0425.1
Zhang, G., Wang, Z., Peng, M. S. & Magnusdottir, G. Characteristics and impacts of extratropical Rossby wave breaking during the Atlantic hurricane seasons. J. Clim. 30, 2363–2379 (2017).
66. McKay R Can southern Australian rainfall decline be explained? A review of possible drivers WIREs Clim. Change 2023 14 e820 10.1002/wcc.820
McKay, R. et al. Can southern Australian rainfall decline be explained? A review of possible drivers. WIREs Clim. Change 14, e820 (2023).
67. Pepler AS Rudeva I Anomalous subtropical zonal winds drive decreases in southern Australian frontal rain Weather Clim. Dyn 2023 4 175 188 10.5194/wcd-4-175-2023
Pepler, A. S. & Rudeva, I. Anomalous subtropical zonal winds drive decreases in southern Australian frontal rain. Weather Clim. Dyn. 4, 175–188 (2023).
68. Zappa G Hawcroft MK Shaffrey L Black E Brayshaw DJ Extratropical cyclones and the projected decline of winter Mediterranean precipitation in the CMIP5 models Clim. Dyn. 2015 45 1727 1738 10.1007/s00382-014-2426-8
Zappa, G., Hawcroft, M. K., Shaffrey, L., Black, E. & Brayshaw, D. J. Extratropical cyclones and the projected decline of winter Mediterranean precipitation in the CMIP5 models. Clim. Dyn. 45, 1727–1738 (2015).
69. Seager R Vecchi GA Greenhouse warming and the 21st century hydroclimate of southwestern North America Proc. Natl Acad. Sci. 2010 107 21277 21282 10.1073/pnas.0910856107 21149692
Seager, R. & Vecchi, G. A. Greenhouse warming and the 21st century hydroclimate of southwestern North America. Proc. Natl Acad. Sci. 107, 21277–21282 (2010).21149692
70. Zhang, G. et al. Seasonal predictability of baroclinic wave activity, npj Clim. Atm. Sci. 5, 10.1038/s41612-021-00209-3 (2021).
71. Béguin A Tropopause level Rossby wave breaking in the Northern Hemisphere: a feature-based validation of the ECHAM5-HAM climate model Int. J. Climatol. 2013 33 3072 3082 10.1002/joc.3631
Béguin, A. et al. Tropopause level Rossby wave breaking in the Northern Hemisphere: a feature-based validation of the ECHAM5-HAM climate model. Int. J. Climatol. 33, 3072–3082 (2013).
72. Barnes EA Hartmann DL Detection of Rossby wave breaking and its response to shifts of the midlatitude jet with climate change J. Geophys. Res. Atmos. 2012 117 D09117 10.1029/2012JD017469
Barnes, E. A. & Hartmann, D. L. Detection of Rossby wave breaking and its response to shifts of the midlatitude jet with climate change. J. Geophys. Res. Atmos. 117, D09117 (2012).
73. Morin, E., Marra, F. & Armon, M. Dryland precipitation climatology from satellite observations in Satellite precipitation measurements. Adv. Glob. Change Res. 69, 843–859 (2020).
74. Hersbach H The ERA5 global reanalysis Quart. J. Roy. Meteorol. Soc. 2020 146 1999 2049 10.1002/qj.3803
Hersbach, H. et al. The ERA5 global reanalysis. Quart. J. Roy. Meteorol. Soc. 146, 1999–2049 (2020).
75. Huffman GJ Integrated multi-satellite retrievals for the Global Precipitation Measurement (GPM) Mission (IMERG) Adv. Glob. Change Res. 2020 67 343 353 10.1007/978-3-030-24568-9_19
Huffman, G. J. et al. Integrated multi-satellite retrievals for the Global Precipitation Measurement (GPM) Mission (IMERG). Adv. Glob. Change Res. 67, 343–353 (2020).
76. Chen M Assessing objective techniques for gauge-based analyses of global daily precipitation J. Geophys. Res. Atmos. 2008 113 D04110
Chen, M. et al. Assessing objective techniques for gauge-based analyses of global daily precipitation. J. Geophys. Res. Atmos. 113, D04110 (2008).
77. Beck HE MSWEP V2 Global 3-hourly 0.1° precipitation Bull. Am. Meteorol. Soc. 2019 100 473 500 10.1175/BAMS-D-17-0138.1
Beck, H. E. et al. MSWEP V2 Global 3-hourly 0.1° precipitation. Bull. Am. Meteorol. Soc. 100, 473–500 (2019).
78. Sun Q A review of global precipitation data sets: Data sources, estimation, and intercomparison Rev. Geophys. 2018 56 79 107 10.1002/2017RG000574
Sun, Q. et al. A review of global precipitation data sets: Data sources, estimation, and intercomparison. Rev. Geophys. 56, 79–107 (2018).
79. Pradhan RK Review of GPM IMERG performance: a global perspective Remote Sens. Env. 2022 268 112754 10.1016/j.rse.2021.112754
Pradhan, R. K. et al. Review of GPM IMERG performance: a global perspective. Remote Sens. Env. 268, 112754 (2022).
80. Li Z Two-decades of GPM IMERG early and final run products intercomparison: similarity and difference in climatology, rates, and extremes J. Hydrol. 2021 594 125975 10.1016/j.jhydrol.2021.125975
Li, Z. et al. Two-decades of GPM IMERG early and final run products intercomparison: similarity and difference in climatology, rates, and extremes. J. Hydrol. 594, 125975 (2021).
81. Kidd C So, how much of the Earth’s surface is covered by rain gauges? Bull. Am. Meteorol. Soc. 2017 98 69 78 10.1175/BAMS-D-14-00283.1 30008481
Kidd, C. et al. So, how much of the Earth’s surface is covered by rain gauges? Bull. Am. Meteorol. Soc. 98, 69–78 (2017).30008481
82. Wernli H Sprenger M Identification and ERA-15 climatology of potential vorticity streamers and cutoffs near the extratropical tropopause J. Atmos. Sci. 2007 64 1569 1586 10.1175/JAS3912.1
Wernli, H. & Sprenger, M. Identification and ERA-15 climatology of potential vorticity streamers and cutoffs near the extratropical tropopause. J. Atmos. Sci. 64, 1569–1586 (2007).
83. Sprenger M Martius O Arnold J Cold surge episodes over southeastern Brazil - a potential vorticity perspective Int. J. Climatol. 2013 33 2758 2767 10.1002/joc.3618
Sprenger, M., Martius, O. & Arnold, J. Cold surge episodes over southeastern Brazil - a potential vorticity perspective. Int. J. Climatol. 33, 2758–2767 (2013).
84. Skerlak B Sprenger M Pfahl S Tyrlis E Wernli H Tropopause folds in ERA-Interim: Global climatology and relation to extreme weather events J. Geophys. Res. Atmos. 2015 120 4860 4877 10.1002/2014JD022787
Skerlak, B., Sprenger, M., Pfahl, S., Tyrlis, E. & Wernli, H. Tropopause folds in ERA-Interim: Global climatology and relation to extreme weather events. J. Geophys. Res. Atmos. 120, 4860–4877 (2015).
85. Portmann R Sprenger M Wernli H The three-dimensional life cycles of potential vorticity cutoffs: a global and selected regional climatologies in ERA-Interim (1979-2018) Weather Clim. Dyn. 2021 2 507 534 10.5194/wcd-2-507-2021
Portmann, R., Sprenger, M. & Wernli, H. The three-dimensional life cycles of potential vorticity cutoffs: a global and selected regional climatologies in ERA-Interim (1979-2018). Weather Clim. Dyn. 2, 507–534 (2021).
86. Scott RK Cammas J-P Wave breaking and mixing at the subtropical tropopause J. Atmos. Sci. 2002 59 2347 2361 10.1175/1520-0469(2002)059<2347:WBAMAT>2.0.CO;2
Scott, R. K. & Cammas, J.-P. Wave breaking and mixing at the subtropical tropopause. J. Atmos. Sci. 59, 2347–2361 (2002).
87. Postel GA Hitchman MH A climatology of Rossby wave breaking along the subtropical tropopause J. Atmos. Sci. 1999 56 359 373 10.1175/1520-0469(1999)056<0359:ACORWB>2.0.CO;2
Postel, G. A. & Hitchman, M. H. A climatology of Rossby wave breaking along the subtropical tropopause. J. Atmos. Sci. 56, 359–373 (1999).
88. Ndarana T Waugh DW A climatology of Rossby wave breaking on the Southern Hemisphere tropopause J. Atmos. Sci. 2011 68 798 811 10.1175/2010JAS3460.1
Ndarana, T. & Waugh, D. W. A climatology of Rossby wave breaking on the Southern Hemisphere tropopause. J. Atmos. Sci. 68, 798–811 (2011).
89. Strong C Magnusdottir G Tropospheric Rossby wave breaking and the NAO/NAM J. Atmos. Sci. 2011 65 2861 2876 10.1175/2008JAS2632.1
Strong, C. & Magnusdottir, G. Tropospheric Rossby wave breaking and the NAO/NAM. J. Atmos. Sci. 65, 2861–2876 (2011).
90. Bowley KA Gyakum JR Atallah EH A new perspective toward cataloging Northern Hemisphere Rossby wave breaking on the dynamic tropopause Mon. Weather Rev. 2019 147 409 431 10.1175/MWR-D-18-0131.1
Bowley, K. A., Gyakum, J. R. & Atallah, E. H. A new perspective toward cataloging Northern Hemisphere Rossby wave breaking on the dynamic tropopause. Mon. Weather Rev. 147, 409–431 (2019).
91. LaChat G Bowley JR Gervais M Diagnosing flavors of tropospheric Rossby wave breaking and their associated dynamical and sensible weather features Mon. Weather Rev. 2024 152 513 530 10.1175/MWR-D-23-0153.1
LaChat, G., Bowley, J. R. & Gervais, M. Diagnosing flavors of tropospheric Rossby wave breaking and their associated dynamical and sensible weather features. Mon. Weather Rev. 152, 513–530 (2024).
92. The NCAR Command Language (Version 6.6.2) [Software]. Boulder, Colorado: UCAR/NCAR/CISL/TDD. 10.5065/D6WD3XH5 (1992).
93. Reinert, P. Bericht zum Programm zur Berechnung der diagnostischen, quasigeostrophischen Vertikalgeschwindigkeit. Technical report ETH, 16 pp, 10.3929/ethz-b-000500755 (2009).
94. Besson P Fischer LJ Schemm S Sprenger M A global analysis of the dry-dynamic forcing during cyclone growth and propagation Weather Clim. Dyn. 2021 2 991 10.5194/wcd-2-991-2021
Besson, P., Fischer, L. J., Schemm, S. & Sprenger, M. A global analysis of the dry-dynamic forcing during cyclone growth and propagation. Weather Clim. Dyn. 2, 991 (2021).
95. Wilks DS “The stippling shows statistically significant grid points”: how research results are routinely overstated and overinterpreted, and what to do about it Bull. Am. Meteorol. Soc. 2016 97 2263 2273 10.1175/BAMS-D-15-00267.1
Wilks, D. S. “The stippling shows statistically significant grid points”: how research results are routinely overstated and overinterpreted, and what to do about it. Bull. Am. Meteorol. Soc. 97, 2263–2273 (2016).
96. Haris I Osborn TJ Jones P Lister D Version 4 of the CRU TS monthly high-resolution gridded multivariate climate datasets Sci. Data 2020 7 109 10.1038/s41597-020-0453-3 32246091
Haris, I., Osborn, T. J., Jones, P. & Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate datasets. Sci. Data 7, 109 (2020).32246091
97. Middleton, N. & Thomas, D. World Atlas of desertification, United Nations Environment Programme, (Arnold publishers, John Wiley & Sons, Inc., 1997).
