Impact of summer Tibetan Plateau snow cover on the variability of concurrent compound heatwaves in the Northern Hemisphere

Concurrent compound heatwaves (CCHWs) occurring simultaneously in multiple regions in the Northern Hemisphere (NH) pose high-end risks to human health and global supply chains. Over the past decade, CCHWs related to human health have substantially increased in occurrence. However, the mechanisms of the CCHWs remain uncertain. This work has revealed a significant relationship between the variability of summer CCHWs in the NH and changes in quasi-stationary waves during 1979–2021, which can be attributed to the variation of summer snow cover over the western Tibetan Plateau (SC_WTP). Excessive SC_WTP causes diabatic cooling by modulating the surface energy budget and stimulating a tripolar Rossby wave source. The atmospheric response to the SC_WTP-driven disturbance manifests as a circumglobal circulation pattern, weakening the meridional temperature gradients and causing a ‘double jet stream’ in the NH. These changes modulate the phase, amplitude and proportion of quasi-stationary waves with wavenumbers 4–6, leading to an increase in CCHWs in the NH. In addition, population exposure to CCHWs reaches 4.91 billion person-day when the SC_WTP increases by one standard deviation. Our study highlights the significance of early warning and forecasting implications related to SC_WTP for CCHWs that impact human health within the context of climate change.


Introduction
The Northern Hemisphere (NH) has experienced an unprecedented rise in extreme climate events in recent decades due to global warming (Alizadeh et al 2020).In particular, the frequency and severity of concurrent compound heatwaves (CCHWs), i.e., the simultaneous occurrence of heatwaves across multiple regions, have been increasing at an accelerated rate with a tendency of occurrence in wider regions over recent decades (Li et al 2018a, Messori et al 2021, Vargas Zeppetello et al 2022) (supplementary figures 1 and 2).Such concurrent extreme climate events may lead to increased heat-related mortality (Stone et al 2021), and they may lead to power outages and have a more serious and far-reaching impact on ecologically sustainable development, global food supply, social balance, and human health than regional heatwave events (Mazdiyasni et al 2017, Zscheischler et al 2017, Kornhuber et al 2019, Kuhla et al 2021, Stone et al 2021, Vargas Zeppetello et al 2022).Furthermore, they can initiate a series of global chain reactions that can exacerbate the damage caused by such events (Zscheischler et al 2018, Raymond et al 2020).However, the mechanism that drives the variability of concurrent heatwaves related to human health on a global scale has not yet been thoroughly investigated.
Various composite indicators are defined to calculate the multivariate compound heatwaves (CHWs) (Sherwood andHuber 2010, Ullah et al 2022).In this work, a Universal Thermal Climate Index (UTCI) is used to define the CHWs in the NH (Di Napoli et al 2018, Zare et al 2018).The UTCI takes into account the coupling relationship between temperature, humidity, wind and radiation, which offers advantages for investigating multivariable synergistic CHWs (Bröde et al 2012).Notably, UTCI serves as a heat stress indicator and can gauge human comfort levels (Di Napoli et al 2018).In contrast to the WBGT index, which is typically used to assess heat stress in athletes and laborers (Ullah et al 2022), UTCI represents an enhanced heat stress metric designed to offer a standardized approach for evaluating heat stress across various aspects of human biometeorology.Furthermore, UTCI exhibits distinct advantages when investigating CHWs about human health, particularly due to its heightened sensitivity to humidity under high-temperature conditions (Bröde et al 2012).
There is an increasing body of evidence to suggest that, in addition to the thermodynamic mechanisms associated with the increased baseline temperature due to global warming (Vogel et al 2019, Wang et al 2020, Ha et al 2022, Rogers et al 2022, Zhao et al 2023), concurrent climate extremes are closely linked to changes in quasi-stationary atmospheric Rossby waves (Teng et al 2013, Chan et al 2022, Lin et al 2022, Cardil et al 2023, Tang et al 2023).For example, an amplified hemisphere-wide wavenumber 7 circulation pattern caused simultaneous extreme heat events in North America, Europe, the Caspian Sea, and Japan during the summer of 2018 (Kornhuber et al 2019, Vogel et al 2019, Kueh and Lin 2020).Stationary Rossby waves with zonal wavenumbers 5 and 7 can induce simultaneous extreme heat events in Central North America, Eastern Europe, and Eastern Asia (Kornhuber et al 2020).High amplitude quasistationary wavenumbers 6 and 7 are increasing by quasi-resonant amplification (QRA), which led to more NH mid-latitude weather extremes (Kornhuber et al 2017).The frequency of heatwaves increases within the areas characterized by atmospheric ridges, predominantly observed for wavenumbers 5 and 6 (Jiménez-Esteve et al 2022).A persistent anomalous Rossby wave with wavenumber 4 accompanied by pronounced high-temperature anomalies in Europe and Russia (Bartusek et al 2022).
The Tibetan Plateau (TP) is the most significant summer heat source in the NH (Liu et al 2020).Previous research has indicated that snow anomalies over the TP can modulate the thermal condition of the TP through the snow albedo effect and snow hydrological effect (Qian et al 2019), and affect the climate locally and globally (Li et al 2018b, Liu et al 2020, 2022).Meanwhile, TP snow can regulate atmospheric circulation variability by coupling with other external forcing factors, such as SST and Arctic sea ice, thus influencing the broader climate system (Jia et al 2021, Chen et al 2023).Furthermore, the snow cover (SC) in the cold season has good persistence and impacts on subsequent climate (Smith et al 2010, Matsumura and Yamazaki 2012, Coumou et al 2018, Lu et al 2020).A cross-seasonal relationship exists between the winter SC in the NH and the summer compound hot and dry extreme in China (Yao et al 2022).Consequently, snow over the TP is a critical indicator for climate prediction and is considered an amplifier of global climate change (Molnar et al 2010, Liu et al 2020, Sun et al 2022a, Tang et al 2023).However, the relationship between SC over the TP and concurrent heatwaves in the NH remains unclear.Therefore, in this study, we aim to reveal the link between the changes in SC over the TP and the occurrence of CCHWs in the NH.

Data
The weekly climate data record for SC is obtained from the Rutgers University Global Snow Lab, which has a horizontal resolution of 25 km for the period of 1979-2021.Then, we convert the SC data to monthly mean data with a horizontal resolution of 1 • × 1 • .The SC over the Western TP (SC_WTP) index is the regional average for the Western TP (31 The SC data is validated by comparing it with ERA5 reanalysis SC data.The strong agreement between the two datasets confirms the accuracy and reliability of the SC over the western TP, bolstering the robustness of our analysis (supplementary figure 3).Monthly mean surface and atmospheric variables are obtained from ERA5 reanalysis data (Hersbach et al 2020) and NCEP-NCAR Reanalysis 1 data (Kalnay et al 1996), including upward shortwave/longwave radiation, mean surface sensible/latent heat flux (LHF), surface temperature, 10 cm soil temperature, geopotential height, temperature, vertical velocity, SC, meridional and zonal wind, with a horizontal resolution of 1 • × 1 • .The daily UTCI, which combines air temperature, wind, radiation, and humidity for June-August from the ECMWF-ERA5 dataset, has a horizontal resolution of 1 • × 1 • .The gridded demographic datasets are from the Gridded Population of the World, Version 4 (CIESIN 2020).To mitigate the influence of global warming on our analysis of CCHWs and causality, we initially removed linear trends from all data.

Definition of CHWs
In the current work, the identification of CHWs is based on ERA5 UTCI (Bröde et al 2012), which integrates temperature, humidity, wind and radiation, thus manifesting a substantial health risk (Russo et al 2017, Di Napoli et al 2018).Therefore, this work emphasizes the consideration of climate change and its impact on human health by focusing primarily on multivariate CHWs.Following Bröde et al (2012), the mathematical term of UTCI is expressed as: UTCI (Ta, Tr, va, pa) = Ta + Offset (Ta, Tr, va, pa) (1 where Ta is the air temperature of the reference condition causing the same model response as the actual condition.The Offset represents the deviation of UTCI depends on the actual values of air and mean radiant temperature (Tr), wind speed (va) and water vapor pressure (pa).CHWs days are firstly defined when detrended daily UTCI exceeds the 90th percentile of the UTCI index within a centered 15 day window; then, the occurrence of three consecutive days meeting this criterion is needed to define a CHW event (Rousi et al 2022).In addition, we also employed the 95th percentile to identify CHWs for validation purposes, and the results were not sensitive to the thresholds (supplementary figures 1 and 2).This work examines the total number of CHWs days in summer.The time series associated with the first empirical orthogonal function (EOF) of the total days of CHWs in the NH (PC1_CHWs) is used to represent the CCHWs variation in the NH.

Diagnostic methods
(1) Quasi-stationary wave decomposition: the amplitudes, phase and proportion of quasistationary waves of zonal wavenumbers 4-6 are calculated by applying a fast Fourier transform to monthly 200 hPa meridional wind in the NH (10  and Nakamura (2006).The baroclinic energy conversion (CP) is calculated following Kosaka and Nakamura (2010).
(3) Atmospheric heat analysis: In order to improve the understanding of the forcing of surface snow on the above column atmosphere, the atmospheric heat source (Q 1 ) is calculated following Yanai et al (1973) andLi et al (2021).
More details of the RWS, CK, CP and Q 1 can be found in the supplementary information.

Relationship between summer SC_WTP and CCHWs
The long-term trends of summer CHWs in the NH for 1979-2019 have large loading over Southern North America (SNA), North Africa-Europe (NAE) and South Asia-Southeast Asia (SASA) (figure 1(a)).The leading EOF (EOF1) of the summer CHWs variation (with linear trends removed) in the NH, which has a variance contribution of 12.8%, shows a global scale pattern (figure 1(b)), with a similar pattern to figure 1(a).This indicates that the CHWs occurring in SNA, NAE and SASA exist at different time scales and have a close relationship.To further verify the synchronization of CHWs in the above three regions, we calculate the correlation between the area-averaged CHWs in SNA and grid-point CHWs in the NH (figure 1(c)).The correlation coefficients exceed the 95% significance test in all the above three regions.In addition, the correlation coefficients between the time series associated with the EOF1 of the CHWs (PC1_CHWs) (figure 1(f), red line) and the area-averaged CHWs in SNA, NAE and SAS are 0.63, 0.88 and 0.72, respectively, all are significant at the 99% confidence level, indicating that the CHWs are changing synchronously in the three regions.In the following, the PC1_CHWs represents the variation in summer CCHWs in the NH.A high index value of PC1_CHWs indicates that all three regions experienced a higher number of CHWs days during the summer, exceeding the climatology.Notably, the spatial patterns of multivariate CHWs are distinct from the univariate heatwaves studied by previous researchers (Zhang et al 2022, Wang et al 2023), while multivariate CHWs more accurately reflect the risks of human health exposure to climate change, which reinforces the necessity of studying multivariate CHWs and their mechanisms in this work.
The western TP demonstrates the largest values for both the climatological mean and variation in summer SC (supplementary figure 4).The distribution of the regressed summer SC (with linear trends removed) over the TP onto the PC1_CHWs illustrates a strong relationship between the variation of the SC over the western TP (SC_WTP) and CCHWs in the NH (figure 1(d)).An SC_WTP index is then constructed by averaging the anomalies of summer SC (with linear trends removed) over the region of 26-45 • N and 69-90 • E (indicated by the gray box in figure 1(d)), which can represent effectively the variation of summer SC over the western TP (figure 1(e)).The contemporaneous correlation coefficient between the SC_WTP and PC1_CHWs indices is 0.44 (p < 0.01).Furthermore, the preceding SC_WTP can have a cross-seasonal impact on the occurrence of CCHWs in the following summer.Firstly, excessive SC_WTP can persist from spring to summer, maintaining the snow-atmosphere coupling effect (supplementary figure 5).Secondly, we evaluate the correlation between the summer PC1_CHWs and the SC_WTP index spanning from spring to summer (table S1).The results consistently demonstrate a significant relationship between SC_WTP and summer CCHWs throughout the spring to summer period.These findings highlight the enduring influence of SC_WTP on the occurrence of summer CCHWs.In addition, the regression map of summer CCHWs in the NH onto the SC_WTP index (figure 1(g)) is similar to figure 1(b), confirming the correlation of SC_WTP with the CHWs while with the most significant correlations over SNA, NAE and SASA.The above results imply that the excessive SC over the western TP from spring to summer is likely to be followed by the occurrence of summer CCHWs in the NH.

The impact of anomalous SC_WTP on local and remote atmospheric circulations
Previous work revealed that surface SC can affect local climate by modulating the thermal conditions through the snow albedo effect.Here we show that the surface albedo increased with excessive SC_WTP, which resulted in positive anomalous upward shortwave radiation over the western TP as more shortwave radiation was reflected into space (figure 2(a)).Less solar radiation was absorbed by the surface and the 10 cm soil temperature decreased (figure 2(f)), thereby causing a significant decrease in the upward sensible heat flux (figure 2(b)) and longwave radiation (figure 2(c)).In addition, the excessive SC_WTP led to weak upward LHF from the land to the atmosphere (figure 2(d)).As a result, excessive SC_WTP caused a decrease in skin temperature (figure 2(e)) over the western TP.Furthermore, a significant negative atmospheric heat source (Q 1 ) anomaly is seen over the western TP with an eastward tilt (figure 2(g)).This indicates a cooling effect of the excessive SC_WTP on the column of the atmosphere from the surface to the upper troposphere.The result suggests that the cooling effect of the excessive SC_WTP was not limited to the lower atmosphere, but extended to the middle and high troposphere.Notably, the relationship between the SC_WTP and CCHW persists from spring to summer (table S1).The spring atmospheric response to anomalous SC_WTP is mainly confined to the local area (supplementary figure 7(a)).In contrast, the summer atmospheric response to anomalous SC_WTP exhibits a significant mid-latitude quasi-stationary wave train (supplementary figure 7 1985).In addition, the surface anomalous SC and the tropospheric quasi-stationary waves also interact with each other.Excessive TP SC can enhance and sustain the quasi-stationary waves, while the lowpressure anomalies associated with these waves over the TP help maintain the surface anomalous TP SC by mechanisms of snow-atmosphere positive feedback (Henderson et al 2018).
During the boreal summer, quasi-stationary waves in the NH are primarily dominated by zonal wavenumbers 4-6 (supplementary figure 8).Notably, their anomalies frequently act as triggers for simultaneous extreme events across multiple regions.The correlation coefficients between PC1_CHWs and the phase, amplitude, and proportion of quasistationary waves, computed for the compositing of wavenumbers 4-6 and averaged over the NH, are 0.43 (p < 0.01), 0.51 (p < 0.01) and 0.30 (p < 0.05), respectively.It suggests a significant correlation between the quasi-stationary waves with wavenumbers 4-6 and CCHWs.Based on the aforementioned analysis, it is possible that the SC_WTP anomaly may influence CCHWs in the NH by changing the thermal conditions of the TP, stimulating hemispheric atmospheric circulation, and modulating quasi-stationary planetary waves.
Figures 4(a)-(c) present the regression of meridional winds for waves 4-6 on the SC_WTP index.These quasi-stationary waves, when combined, give rise to a global-scale quasi-stationary planetary wave, as depicted in figure 3, featuring significant anticyclonic high-pressure anomalies over NAE, SNA and SASA.The meridional wind regressed against PC1_CHWs displays a pattern similar to the regression against the SC_WTP (figures 4(d)-(f)).The SC_WTP-related waves with wavenumbers 4-6 at 500 hPa exhibit a pattern resembling that of figures 4(a)-(c) (supplementary figure 9), indicating a quasi-barotropic structure.The phases of the quasi-stationary waves, associated with the SC_WTP, strongly favor the occurrence of CCHWs.The correlation coefficient between the SC_WTP and the phase of quasi-stationary waves, computed The weakened zonal westerlies lead to higher amplitude trough and ridge systems that propagate more slowly, resulting in more persistent extreme events (Francis and Vavrus 2012, 2015, Coumou al 2014, 2018).An increasing number of studies have suggested that the increase in quasi-stationary planetary waves of wavenumbers 6-8, is caused by the QRA effect (Mann et al 2018, Teng et al 2019).The QRA can be triggered under the favorable conditions of decelerating zonal westerlies and a 'double jet stream' (enhanced polar and subtropical jet streams) (Rousi et al 2022).Rossby waves with wavenumbers 6-8 can be effectively trapped within the mid-latitude waveguide, and a 'double jet stream' prevents wave energy from escaping to the Arctic and the equator.If the waveguide is circumglobal, the Rossby wave energy is constrained within the extratropics.Furthermore, if some trapped planetary waves are close to the quasistationary waves excited by thermal or orographic forcing, the QRA will occur (Mann et al 2018).
The regressions of the 200 hPa zonal wind and meridional temperature gradient in the NH on the SC_WTP index (supplementary figure 10) show that significant negative westerly anomalies dominate the mid-latitude NH, resulting from weakened meridional temperature gradients.This condition would promote the meridional development and deceleration of mid-latitude trough-ridge systems (Francis andVavrus 2012, 2015), contributing to the formation and amplification of quasi-stationary waves.Furthermore, a strengthened polar jet is also observed, forming a distinctive 'double jet stream' pattern in the NH.The decreasing SC_WTPassociated changes in the upper-level circulations lead to conditions that are favorable for the slow movement of quasi-stationary planetary waves and the QRA of quasi-stationary planetary waves with wavenumber 6.
The quasi-stationary wave with wavenumber 6 associated with SC_WTP and CCHWs, as depicted in figures 4(c) and (f), bears a striking resemblance to the circumglobal Rossby wave with wavenumber 6 identified in a prior investigation on the QRA effect.These results suggest that the excessive SC_WTP can promote the generation and amplification of wavenumber 6-dominated quasi-stationary waves by weakening mid-latitude westerly winds and creating a 'double jet stream' pattern, thereby creating favorable conditions for the simultaneous occurrence of surface heatwaves in various regions.

Conclusion and discussion
We revealed that the occurrence of CCHWs related to human health over North America (SNA), NAE, and SASA has exhibited a close relationship in recent decades.This phenomenon is intricately connected to changes in quasi-stationary waves at wavenumbers 4-6.The alteration of the phase, amplitude, and proportion of these planetary waves due to specific mechanisms can lead to a weakening of westerly winds and the occurrence of QRA, consequently, creating favorable conditions for CCHWs.We found that excessive SC_WTP stimulates an upper-level tripole pattern of RWSs by modulating local thermal conditions on the surface and in the atmosphere.The atmospheric response to the anomalous SC_WTP-related disturbance is a circumglobal circulation pattern that dominates the mid-latitudes, with the related quasistationary waves of wavenumbers 4-6 forming a pattern favorable for CCHWs in the NH, especially in the three key CCHWs regions of SNA, NAE and SASA.The effects of excessive SC_WTP are apparent in the weakening of the zonal westerlies and the formation of a 'double jet stream' pattern in the NH, which also provide favorable conditions for the slow propagation and amplification of quasi-stationary waves.Notably, these quasi-stationary waves primarily influence the seasonal temperature field in the NH during the summer, which then regulates the frequency of CHWs in summer.
Previous studies have shown that heatwaves have significantly affected global public health, particularly among vulnerable groups like the elderly and children (Campbell et al 2018, Romanello et al 2021, Chen et al 2022).We also identified a notable overlap between the high-value areas of CCHWs examined in the current work and regions with significant population concentrations (figure 5(a)), implying that a large portion of the population in the NH is at risk of experiencing CCHWs.In addition, the quantitative analysis results reveal that a one-standard-deviation increase in SC_WTP corresponds to CCHW exposures of 0.273, 1.42 and 3.11 billion (person-day) in SNA, NAE and SASA (figure 5(b)), respectively.The cumulative exposure across these three regions totals 4.91 billion (person-day).
Our research provides a novel perspective, offering the first insights that the SC over the western TP may serve as an important predictable reservoir contributing to the fluctuations of CCHWs related to human health across the NH.This suggests that the global health effects of the TP under the context of climate change, as the third pole, are also an aspect that deserves our further attention.
While this work highlights the significance of the SC_WTP impact on the CHWs variability, it is crucial to recognize that other factors, such as sea surface temperature, and internal atmospheric variability, among others, can also contribute to the variation of CHWs.However, it is important to acknowledge certain limitations and uncertainties in this work.While this work provides evidence based on the observations that SC over the TP significantly impacts quasistationary waves, there is a lack of quantitative analysis and numerical modeling of the effects of SC on the amplitudes and speeds of these quasi-stationary waves.Therefore, further investigations are essential to address these aspects in the future.
) and (c) show a circumglobal quasi-stationary planetary wave with ridges dominating the key CCHW regions of SNA, NAE and SASA, which is a favorable condition for widespread and long-lasting CHWs in the NH (figures 3(b) and (c)).
(b)).Results of energy conversion analysis indicate that the SC_WTP related summer circumglobal circulation pattern can be maintained and enhanced by extracting barotropic (CK) and baroclinic (CP) energy from the basic flow (supplementary figures 6(b) and (c), with CK energy conversion dominating (Wallace and Lau
Liu X, Jia X, Wang M and Qian Q 2022 The impact of Tibetan Plateau snow cover on the summer temperature in Central Asia Adv.Atmos.Sci.39 1103-14 Liu Y, Lu M, Yang H, Duan A, He B,Yang S and Wu G 2020Land-atmosphere-ocean coupling associated with the Tibetan Plateau and its climate impacts Natl Sci.Rev. Vlug A, Piao S, Li F, Wang T, Krinner G and Yao T 2023 Regional and tele-connected impacts of the Tibetan Plateau surface darkening Nat.Commun.14 32 Teng H and Branstator G 2019 Amplification of waveguide teleconnections in the boreal summer Curr.Clim.Change Rep. 5 421-32 Teng H, Branstator G, Wang H, Meehl G A and Washington W M 2013 Probability of US heat waves affected by a subseasonal planetary wave pattern Nat.Geosci.6 1056-61 Ullah I, Saleem F, Iyakaremye V, Yin J, Ma X, Syed S and Omer A 2022 Projected changes in socioeconomic exposure to heatwaves in South Asia under changing climate Earth's Future 10 e2021EF002240 Vargas Zeppetello L R, Raftery A E and Battisti D S 2022 Probabilistic projections of increased heat stress driven by climate change Commun.Earth Environ. 3 183 Vogel M M, Zscheischler J, Wartenburger R, Dee D and Seneviratne S I 2019 Concurrent 2018 hot extremes across Northern Hemisphere due to human-induced climate change Earth's Future 7 692-703 Wallace J M and Lau N C 1985 On the role of barotropic energy conversions in the general circulation Adv.Geophys.28 33-74 Wang Q, Li Y, Li Q and Wang Y 2020 Sea surface temperature extremes of different intensity in the China Seas during the global warming acceleration and hiatus periods J. Trop.Meteorol.26 473-82 Wang Z, Luo H and Yang S 2023 Different mechanisms for the extremely hot central-eastern China in July-August 2022 from a Eurasian large-scale circulation perspective Environ.Res.Lett.18 024023 Yanai M, Esbensen S and Chu J H 1973 Determination of bulk properties of tropical cloud clusters from large-scale heat and moisture budgets J. Atmos.Sci. 30 611-27 Yao H, Zhao L, Shen X, Xiao Z and Li Q 2022 Relationship between summer compound hot and dry extremes in China and the snow cover pattern in the preceding winter Front.Earth Sci. 10 834284 Zare S, Hasheminejad N, Shirvan H E, Hemmatjo R, Sarebanzadeh K and Ahmadi S 2018 Comparing Universal Thermal Climate Index (UTCI) with selected thermal indices/environmental parameters during 12 months of the year Weather Clim.Extremes 19 49-57 Zhang T, Tam C Y, Lau N C, Wang J, Yang S, Chen J and Gao P 2022 Influences of the boreal winter Arctic Oscillation on the peak-summer compound heat waves over the Yangtze-Huaihe River basin: the North Atlantic capacitor effect Clim.Dyn.59 2331-43 Zhao L, Dong W, Shen X, Ding Y, Li Q, Hu Y and Xiao Z 2023 Human activity and simultaneous high-pressure anomalies influence the long-duration cold events of winter in China Clim.Dyn.61 2765-81 Zscheischler J and Seneviratne S I 2017 Dependence of drivers affects risks associated with compound events Sci.Adv. 3 e1700263 Zscheischler J, Westra S, Van Den Hurk B J, Seneviratne S I, Ward P J, Pitman A and Zhang X 2018 Future climate risk from compound events Nat.Clim.Change 8 469-77