Synergistic impacts of wintertime regional snow anomalies in the Northern Hemisphere on the summer rainfall pattern in China

Snow cover significantly impacts atmospheric circulation, exhibiting more seasonal variability than sea surface temperature (Arduini et al 2019). Research has emphasized its role in regional climate change, especially in winter-to-summer effects (Coumou et al 2018). Snow cover's impact on global climate and hydrology draws attention in studies, with a focus on some regions like Eurasia, the Tibetan Plateau (TP), and North America (NA) (Henderson et al 2018).

Eurasian snow cover significantly affects summer precipitation in China (Wu et al 2009). This cross-season correlation is independent of the El Niño-Southern Oscillation (ENSO) and has remained stable over the past 40 years (Wu et al 2009). Snowmelt, with delayed hydrological effects, enhances soil moisture and heat absorption, creating a 'land bridge' that affects summer atmospheric circulation (Koster et al 2011). This leads to persistent soil moisture anomalies, triggering Rossby waves in Eurasia (Zhang et al 2020), which influence East Asian atmospheric circulation during summer (Zuo et al 2015, Shen et al 2020).

Snow cover on the TP may influence summer rainfall in China. Research confirms that increased TP snow cover reduces surface heat flux, leading to lower tropospheric temperatures nearby (Liu et al 2020). This reduction in temperature weakens the East Asian summer monsoon intensity (Ding et al 2008). The correlation is dependent on the radiative cooling of snow and 'wet soil' acting as cold sources (You et al 2020).

Recent studies have emphasized the significance of snow cover in northern China and Mongolia (Shen et al 2020). Persistent surface cooling in the region extends into summer owing to the memory effect of snow and its interaction with the monsoon. This results in unusual shifts in summertime temperature gradients and upper-level westerly airflow (Koster et al 2010, Chiang et al 2017). Enhanced westerly winds over the northern TP combined with plateau topography induced convergence over North China and compensatory divergence over the southern basin, causing anticyclonic circulation and reduced rainfall (Xiao et al 2016).

Furthermore, increased NA snow-cover induces atmospheric cooling through heightened albedo and reduced upward sensible heat flux (Henderson et al 2018). This sustained cooling prompts low-level westerly anomalies in the tropical central-eastern Pacific by adjusting the geopotential and temperature gradients. These anomalies promote convergence and upward motion in the tropical eastern Pacific (Cao et al 2018, Wang et al 2020). Then, affecting China's summer circulation via teleconnection patterns, such as Circumglobal Teleconnection (CGT), East Asia-Pacific, and East Asia-Pacific-NA atmospheric teleconnection (Vavrus et al 2017, Zhou et al 2020).

Previous researchers have identified the influence of regional snow cover on summer circulation and China's precipitation. However, the synergistic impacts of Northern Hemisphere (NH) snow anomalies remain unclear. To address this shortcoming, this study focuses on overall NH snow cover and explores the relationship(s) between winter snow and summer precipitation over China. Specifically, the synergistic impacts of multiple snow cover on atmospheric circulation and the process of cross-seasonal transmission of snow signals.

2.1. Data

2.2. Calculation of wave activity flux (WAF)

The energy propagation characteristics of quasi-stationary waves were described by the three-dimensional WAF defined by Takaya and Nakamura (2001). In spherical coordinates, the expression is as follows:

$$\begin{align}WAF = \frac{{p{\text{cos}}\varphi }}{{2\left| U \right|}} \left\{ {\begin{array}{*{20}{c}} {\frac{U}{{{\alpha ^2}{\text{co}}{{\text{s}}^2}\varphi }}\left[ {{{\left( {\frac{{\partial \psi ^{\prime}}}{{\partial \lambda }}} \right)}^2} - \psi ^{\prime}\frac{{{\partial ^2}\psi ^{\prime}}}{{\partial {\lambda ^2}}}} \right] + \frac{V}{{{\alpha ^2}{\text{co}}{{\text{s}}^2}\varphi }}\left[ {\frac{{\partial \psi ^{\prime}}}{{\partial \lambda }}\frac{{\partial \psi ^{\prime}}}{{\partial \varphi }} - \psi ^{\prime}\frac{{{\partial ^2}\psi ^{\prime}}}{{\partial \lambda \partial \varphi }}} \right]} \\ {\frac{U}{{{\alpha ^2}{\text{co}}{{\text{s}}^2}\varphi }}\left[ {\frac{{\partial \psi ^{\prime}}}{{\partial \lambda }}\frac{{\partial \psi ^{\prime}}}{{\partial \varphi }} - \psi ^{\prime}\frac{{{\partial ^2}\psi ^{\prime}}}{{\partial \lambda \partial \varphi }}} \right] + \frac{V}{{{\alpha ^2}}}\left[ {{{\left( {\frac{{\partial \psi ^{\prime}}}{{\partial \varphi }}} \right)}^2} - \psi ^{\prime}\frac{{{\partial ^2}\psi ^{\prime}}}{{\partial {\varphi ^2}}}} \right]} \end{array}} \right\}\end{align} \tag{ 1 }$$

where $U = \left( {U,V} \right)$ is the basic flow field, $\left| U \right|$ is the climatological magnitude of the winds, $\alpha$ is the mean radius of Earth, and $\lambda$, $\varphi$, $p$ represent the longitude, latitude, height, and pressure scaled by 1000 hPa, respectively. $\psi ^{\prime}$ denotes the perturbed geostrophic stream function.

3.1. Association between NH wintertime snow cover and Chinese summer precipitation

Empirical orthogonal function (EOF) analysis is applied to examine the NH winter snow cover and summer precipitation patterns over China. The first leading modes, EOF1, accounts for 14.8% and 20.3%, respectively (figures 1(a) and (b)). Figure 1(a) shows that Europe and Mongolia at middle to high latitudes have negative values of snow cover, while the TP and NA at mid-latitudes exhibit positive values. Zhao et al (2016) pointed out a significant relationship between the AO and winter NH snow-cover, and this relationship strengthened after the 1970s. Figure 1(c) shows the principal component of EOF1, PC1. The correlation coefficient between winter AO and PC1 of NH winter snow cover is 0.69 (p < 0.01), suggesting that this synergistic NH snow change likely reflects the impact of AO. The AO index for the winter of 2020 was the second-highest on record, reaching 2.08 (data sourced from CMAP).

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The EOF1 of summer rainfall dominated by precipitation changes in the middle and lower reaches of the YRB (figure 1(b)). The PC1 for summer precipitation exhibited clear inter-decadal and inter-annual variability (figure 2(a), blue line) and changes that were consistent with the preceding winter snow PC1. The correlation coefficient between the two PC1s was 0.40 (p < 0.01; figure 1(c)). The two largest PC1 values occurred in 1998 and 2020, coinciding with major flooding in the YRB and corresponding to the two large PC1 values for winter snow cover. After removing the influence of ENSO, the correlation coefficient between the two is 0.32 (p < 0.05). The map of the correlation coefficient between China's summer precipitation and winter NH snow cover PC1 (figure 1(e)) also shows a pattern similar to that of the summer precipitation EOF1 (figure 1(b)), with a spatial correlation coefficient of 0.70.

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To further evaluate the impact of statistical synergies, we selected four regions (red boxes in figure 1(d)) with the highest correlations between the winter snow anomaly and precipitation PC1: Europe (0°–40° E, 40°–60° N), Mongolia (90°–120° E, 45°–50° N), TP (80°–100° E, 30°–35° N), and NA (70°–120° W, 25°–42° N). This comparison of hemispheric and regional results can help elaborate on the common and different influences of snow cover in different regions on the summer circulation in China. Moreover, such comparisons can help us identify which effect is more important for summer precipitation patterns: the synergistic effect (i.e. the main mode) of NH snow cover or the regional snow effect. The supplementary material contains a comprehensive discussion and analysis of the results (figure S1, tables S2 and S3), including correlations, removal of influences, and the correlation fields. Overall, we confirm that synergies exert a greater influence than single regions and thus are more likely to cause summertime flooding in the YRB. This underscores the importance of evaluating hemispheric snow cover in relation to regional precipitation.

3.2. Dynamic analysis

3.2.1. Extratropical path of snow synergistic impacts

After removing European (Mongolian) snow cover, the correlation coefficient between NH winter snow cover and Chinese summer precipitation PC1 decreased to 0.13 (0.22) (table S3). Therefore, statistically speaking, European snow cover appears to be more significant. In Europe, following winters with relatively less snow cover, springtime soil moisture was generally low (figures 2(a)–(c)). Due to the persistence of soil moisture anomalies from winter to summer (highlighted by red boxes in figures 2(d)–(f)), the latent heat flux during European summer decreases. Simultaneously, both the sensible heat flux and the net surface-upward energy flux increase (figure S2). This leads to elevated surface air temperatures and the formation of low-pressure anomalies (figures 2(g)–(i)). Moreover, a low-pressure circulation, induced by thermal forces over Europe and featuring easterly anomalies to the north, disrupts the typical trajectory of westerly airflows (e.g. Haarsma et al 2009). Consequently, this disturbance leads to a decrease in local precipitation and contributes to further soil column drying (Coumou et al 2018). As depicted in figures 2(d)–(f), low soil moisture at around 45°N tends to persist in summer, reflecting the positive feedback between winter snow cover, springtime soil moisture, and summer atmospheric circulation. This phenomenon is referred to as the snow-soil moisture-atmospheric circulation feedback. It involves a process in which diminished spring snow cover postpones the drying effect on soils until mid-summer. This delay results in higher temperatures due to suppressed evaporative cooling, impacting both regional and hemispheric atmospheric circulation (Coumou et al 2018).

Figure 3(a) shows that European winter snow cover influences summertime Rossby-wave activity. This activity leads to downstream energy flow from Europe, splitting into two branches over Central Asia. One branch continues eastward towards eastern China, as depicted in figures 3(a) and 4(a), which can strengthen the southern YRB high-pressure system. However, it is worth noting that the low-pressure anomalies in the northern part of YRB are not very pronounced. On the other hand, the other branch propagates northeastward and strengthens the high-pressure ridge over northern East Asia. Moreover, Mongolian winter snow cover anomalies not only reinforce the high-pressure anomaly over northern East Asia but also enhance the low-pressure anomaly over the northern YRB. Therefore, it is the synergy between dominant European snow cover and the enhancing effect of Mongolian snow cover. The synergy leads to the formation of a meridional '+ _ +' wave train structure. This structure strengthens the East Asia and Pacific wave train, a dominant feature of the East Asian Summer monsoon period (Nitta 1987, Lau et al 2000). Additionally, it enhances the north-south propagation of wave energy, making the East Asian precipitation pattern more sensitive to meridional changes. Similar circulation and planetary wave characteristics are observed in the correlation fields of NH snow-cover PC1 and summer precipitation PC1 (figures 3(c) and (d)). These characteristics align with conditions conducive to summertime flooding events in the YRB (Ding et al 2008, Wu et al 2009).

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3.2.2. Subtropical path of snow synergistic impacts

Based on the characteristics of Rossby-wave activity, we constructed vertical profiles for the four areas depicted in figure 4 (points A [30° E, 55° N], B [80° E, 30° N], C [120° E, 30° N], and D [120° E, 60° N]) to investigate the synergistic impacts of snow cover in Europe, Mongolia, and TP. An anomalous upward and eastward propagation of WAF occurs from Europe and TP to the YRB, strengthening the cut-off low-pressure system over the YRB (figures 4(a), (b) and 5(a)). This phenomenon can also be induced by the accumulation of snow in Mongolia (figure 3(b)). However, solely relying on winter snowfall from the TP is insufficient to significantly trigger the East Asia and Pacific pattern (figure 5(a)). Figure 4(c) shows the anomalous eastward propagation of WAF that starts in Mongolia. The propagation of these WAFs collaboratively reinforces the high-pressure ridge in Northeast Asia (figure 5(b)). The correlation figures of NH winter snow-cover PC1 (figures 3(c) and 4(d)) reveal a synergistic interaction with Chinese summer precipitation PC1 (figures 3(d) and 4(e)).

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When the TP experiences relatively more winter snow cover, it hinders warming in the subsequent spring and summer seasons (Liu et al 2020, Sun et al 2021). This leads to the development of an anomalous meridional temperature gradient over the region. Consequently, a strong westerly airflow occurs over the TP, accompanied by anticyclonic circulation to the south and cyclonic circulation to the north. Additionally, a reduction in winter snow cover in Europe leads to a thermal gradient between the northern TP and Mongolia. This reinforces the subtropical westerly jet and causing it to shift southward (figures 5(a) and (b)). This configuration promotes upward motion, leading to rainfall over the middle and lower reaches of the YRB (Yang et al 2002, Zhao et al 2007).

The positive winter snow-cover anomaly in the TP strengthens the meridional temperature gradient and zonal wind anomaly (figure S3). Southerly winds transport a significant amount of water vapor from the Bay of Bengal and South China Sea, leading to increased summer precipitation in the middle and lower reaches of the YRB.

3.2.3. The teleconnection effect of snow in North America

Owing to snow-hydrological effects, a significant wetness signal develops at 40° N latitude in NA during spring and summer (figure 6, upper panels). Additionally, a cold temperature signal at 2 m persists into the summer (figure 6, lower panels). Crucially, we note that (1) the significant soil moisture signal emerges before the cold temperature signal, suggesting that soil moisture at about 40° N may be a potential driver, and (2) the late-winter soil moisture signal shows seasonal transmissions. This relationship drives changes in the meridional thermal gradient and fosters easterly (westerly) anomalies north (south) of 40° N, resulting in an anomalous summertime cyclonic circulation in the lower troposphere over NA (figure 7(a)). According to figure 7(c), anomalous cyclonic eddies near 45° N strengthen the westerly jet. They propel the eastward propagation of the North Atlantic jet and enhance its connection to the Asian-African jet. A cyclonic eddy forms downstream and excites Rossby waves that reach the Caspian Sea, Mongolia, and China. Similar to the CGT, this wave-wave interaction not only strengthens the cyclonic anomaly over northern China but also leads to the intensification of the high-altitude westerly jet over the YRB. This shift southward of the jet's position could lead to increased precipitation in the YRB (Wu et al 2016).

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3.3. CMIP6 simulations

We used 20 CMIP6 models to verify the reanalysis described above. First, we compared reanalysis data with the simulated model data and found that (1) most models can reasonably capture the EOF1 of NH winter snow cover and Chinese summer precipitation (see figures S4 and S5), and (2) the simulation performance of multi-model ensembles (MME; figure 8) is considerably better than that of individual climate models (figures S4 and S5). The spatial correlation coefficients of EOF1 patterns between the MME and reanalysis data were >0.70 (figures 8(a) and (b)). Second, we evaluated the MME's ability to simulate the cross-seasonal relationship between NH winter snow cover and Chinese summer precipitation. Results show that the correlation coefficient between the winter snow PC1 and summer precipitation PC1 reached 0.42 (p < 0.01; figure 8(c)).

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Compare the CMIP6 MME snow EOF1 (figure 8(a)) with the reanalysis data, it shows that the former overestimates the NA-Europe correlation and underestimates the role of snow on the TP and Mongolia (tables S2–S6). Excluding the effects of distant snow, NA snow was vital for the NH and YRB summer precipitation (figure S1(d), table S6, r = 0.42).

The figures S6 and S7 illustrate the simulation of cross-seasonal relationships between snow cover and soil moisture, as well as the reproduction of circulation patterns in different regions. While the influence of snow cover on atmospheric circulation needs further refinement, CMIP6 models generally capture the combined impacts of various regional snow anomalies.

Extreme precipitation is increasing in China owing to climate change (IPCC 2021). In this study, snow cover in various NH regions has three synergistic impact paths. These paths serve as a more informative indicator of summer precipitation compared to the influence of snow cover within a single locality.

Firstly, the extratropical path involves westerlies affected by reduced European snow, driven by the snow-soil moisture-atmospheric circulation feedback mechanism (Coumou et al 2018, Henderson et al 2018, Yao et al 2022), further intensified by decreased Mongolian snow and enhanced temperature anomalies. Secondly, the subtropical path sees a meridional thermal difference anomaly. This anomaly is a result of increased snow on the TP and strengthened by reduced snow in Mongolia. The anomaly, in turn, influences the upper-tropospheric westerly jet. Thirdly, increased NA snow reinforced previous paths via CGT patterns. These paths are reflected in the EOF1 of winter NH snow cover and related circulations. This leads to meridional East Asia-Pacific pattern circulation anomalies in summer and results in heightened YRB precipitation. Additionally, snow depth in topographic depressions and treelines has a lasting presence until late spring and occasionally into summer (Mackiewicz 2012). This extended presence plays a more crucial role in influencing soil moisture and the snow-soil moisture-atmospheric circulation feedback mechanisms, especially in late summer, compared to shallow snow cover during winter. The significance of the extended snow depth is attributed to its close association with the seasonal dynamics of the regional climatic system (Lievens et al 2019, Yang et al 2023). Furthermore, while the MME of CMIP6 models capture the cross-seasonal relationship and role of European snow, they tend to overestimate NA's influence on NA and underestimate that of Mongolia and the TP.

While explaining ⩽20% variance, EOF1 of winter snow cover shows mid-to-high latitude patterns, which is important for understanding synergistic impacts and identifying extreme events. The temperature difference between the sea and land caused by the snow is also a significant factor contributing to the excess summer precipitation in the YRB (Ding et al 2008). Moreover, future research should focus on snow depth or snow-atmosphere coupling for better seasonal predictions. Understanding the sensitivity of extratropical variability to climate change, especially the snow-(N)AO/NAM linkage, is crucial for improving predictions on weekly to monthly timescales, and is sensitive to anthropogenic effects.

We thank the reviewers and editor for insightful remarks. We would like to thank the European Centre for Medium-Range Weather Forecasts for providing the ERA5 reanalysis data. The authors acknowledged the Climate Prediction Center of the National Oceanic and Atmospheric Administration of the United States for providing AO index data. This research is supported by the National Natural Science Foundation of China (42075040), Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004) and the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA23090102).

Publicly available datasets were analyzed in this study. These data can be found here: https://apps.ecmwf.int/datasets, https://www.cpc.ncep.noaa.gov/, https://esgf-node.llnl.gov/search/cmip6/.

All data that support the findings of this study are included within the article (and any supplementary files).