Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/Joint International Research Laboratory of Climate and Environmental Change (ILCEC), Nanjing University of Information Science & Technology, Nanjing 210044
2.
School of Atmospheric Sciences, Nanjing University of Information Science & Technology, Nanjing 210044
Recent studies have suggested a close relationship between early summer precipitation over Northeast China and spring land surface thermal anomalies in West Asia. However, is this relationship the same over the multidecadal timescale? This study aims to identify the long-term variation in this relationship and the accompanying atmospheric circulation anomalies by using singular value decomposition, correlation analysis, and linear regression based on the ECMWF Reanalysis v5 (ERA5) atmospheric data, ERA-Land reanalysis, and CN05 gridded observations during 1961–2020 (60 yr). It is found that an interdecadal transition of the relationship between the spring surface temperature/thermal anomalies in West Asia and early summer precipitation over Northeast China occurred around 1990, and the temperature–rainfall relationship intensified after 1990. Based on the Mann–Kendall test, the study period was divided into P1 (1961–1990) and P2 (1991–2020). Further analysis indicated significant differences in the corresponding atmospheric circulation before and after the interdecadal transition. During P2, spring land surface warming in West Asia corresponded to a significantly enhanced early summer Circumglobal Teleconnection (CGT), which in turn suppressed the Northeast China cold vortex (NECV). The changes in circulation patterns further resulted in weakened moisture transport, strengthened subsidence, reduced precipitation triggering, and eventually, weakened precipitation. Additionally, the results suggest that the interdecadal transition of the relationship and the changes in the corresponding atmospheric circulation may be related to activities of the westerly jet stream. The second princi-pal component (PC2) mode of empirical orthogonal function (EOF) of zonal wind in June over Asia demonstrated a pattern similar to that of the atmospheric circulation corresponding to land surface thermal anomalies. In addition, during P2, the PC2 mode of the westerly jet stream in June showed a strong positive correlation with the NECV, thereby suppressing precipitation over Northeast China. Therefore, it is concluded that the westerly jet stream may have affected the interdecadal transition of the temperature–rainfall relationship around 1990.
Northeast China is an important grain-growing region, where crop yield is tightly linked to climate—especially precipitation (P) anomalies. Studies have shown that summer precipitation over Northeast China exhibits interannual variability and intraseasonal variations (Sun et al., 2000; Jia et al., 2003; Liang et al., 2011; Li and Chen, 2021; Zhang and Zhao, 2022), which are affected by different atmospheric circulation patterns (Sun et al., 2016). Meanwhile, summer precipitation over Northeast China is also characterized by significant interdecadal variability (Qian and Qin, 2008; Li et al., 2009) and has undergone multiple wet and dry transitions in the 1960s, 1980s, and 1990s (Huang et al., 2013; Zhao et al., 2018). Accurate prediction of summer rainfall in Northeast China remains a significant challenge.
Summer climate in Northeast China is affected by many atmospheric circulation factors. For example, at the synoptic scale, theoretical and observational analyses have indicated that the Northeast China cold vortex (NECV) is an important weather system affecting summer precipitation over Northeast China (Shen et al., 2011; Liu et al., 2015; Xie and Bueh, 2015; Gao and Gao, 2018; Fang et al., 2021). At an interannual scale, the westerly jet, which is a crucial circulation system in the Northern Hemisphere, has a significant impact on the climate in Northeast China (Xie et al., 2015; Wei et al., 2017). The intensity and position of the westerly jet jointly influence the moisture and the conditions triggering summer precipitation over Northeast China, along with other circulation systems, such as the East Asian summer monsoon (Sun et al., 2017) and the subtropical high-pressure system (Shen et al., 2011). Furthermore, the westerly jet itself is closely linked to the disruption of the NECV, advance and retreat of the East Asian summer monsoon (Wei et al., 2017), and positions and intensities of the western Pacific subtropical high and South Asian high (Xie et al., 2015), which exert complex effects on precipitation.
In addition, external forcings, such as sea surface temperature (SST) anomalies (including the El Niño–Southern Oscillation; ENSO) (Mao et al., 2011; Wen et al., 2015, 2019; Bi et al., 2018; Lu et al., 2020) and sea ice (Wu et al., 2009; Han et al., 2021), could also continuously exchange heat and water vapor with the local atmosphere, thus affecting the climate over Northeast China through the global circulation system, and eventually influencing precipitation over Northeast China.
Land surface is also an important component of Earth’s climate system; it regulates the land–atmosphere energy and momentum exchanges, thereby influencing significantly the local and regional weather and climate (Pitman, 2003) and serving as a crucial external forcing factor of the atmosphere (Santanello et al., 2018). Global warming, land surface processes, and their influences on climate have been receiving increasing attention (Gonzalez et al., 2010; McCarthy et al., 2010; Fu and Feng, 2014; Song and Chen, 2023). Global temperatures have been steadily increasing since the 1950s, and land surface temperatures have been exhibiting strong warming trends since 1979 (Zhou et al., 2015, 2016; Chen et al., 2020). Land surface thermal anomalies caused by increasing land surface temperatures can significantly influence climate change both locally and regionally (Gu et al., 2019; Sato and Nakamura, 2019; Dirmeyer et al., 2021). Land surface warming in Eurasia and the climate in various regions in China are closely linked (Zhang et al., 2019, 2020; Sang et al., 2022). Surface warming can affect the atmosphere and hence precipitation systems through its impacts on the subtropical high-pressure system, East Asian summer monsoon, etc. (Gao et al., 2019). These impacts and associations have been confirmed through numerical experiments (Ruscica et al., 2016; Li et al., 2018; Jung et al., 2019; Yuan et al., 2021). Nevertheless, due to the complexity of land surface conditions, the Eurasian warming is spatially heterogeneous (Hong et al., 2017). Conversely, West Asia is a hotspot of land surface warming (Cohen et al., 2012; Zhou et al., 2015).
Land surface warming has been receiving increasing attention, as it is an important external forcing factor of the atmosphere. Yang et al. (2021) indicated that anomalous land surface heating in West Asia in spring can act as an external forcing, causing atmospheric teleconnections that resemble the early summer Circumglobal Teleconnection (CGT) pattern, influencing the enhancement of the Indian monsoon (Yang and Chen, 2022), and eventually affecting the early summer climate in North China. Chen et al. (2018) suggested that anomalous warming of land surface in West Asia in spring can induce anomalous anticyclonic circulation over the Baikal region in early summer, leading to weakened NECV activity and reduced precipitation over Northeast China. Wang et al. (2018) found a close relationship between the decadal variations of surface heating anomalies in West Asia and the NECV activity. The above analyses reveal a close connection between anomalous spring land surface warming in West Asia and early summer precipitation over Northeast China. As we know, the climate system exhibits interdecadal or decadal signals. Do spring land surface thermal anomalies have a stable relationship with the early summer climate in Northeast China? Although this remains unclear, it is important for the effective prediction of early summer rainfall.
In this study, observational and reanalysis data were utilized to investigate the interdecadal variations of this relationship. By comparing the corresponding atmospheric circulation during different periods, this study provide insights regarding the short-term climate prediction of early summer precipitation over Northeast China. The remainder of this paper is organized as follows. Section 2 describes the datasets and methods used in this study. Section 3 explores the decadal transition of the relationship between early summer precipitation over Northeast China and anomalous spring land surface heating in West Asia. Section 4 compares the atmospheric circulation patterns before and after the decadal transition and discusses their differences. Section 5 discusses the possible causes of this transition.
2.
Data and methods
2.1
Data
Land surface temperature (Ts) data with a horizontal resolution of 0.1° × 0.1° were obtained from the ERA-Land reanalysis dataset of the ECMWF (Muñoz-Sabater et al., 2021). Atmospheric ERA5 data (Hersbach et al., 2020) at a resolution of 0.25° × 0.25° and 37 vertical layers were also used. Both datasets are available at http://cds.climate.copernicus.eu. Daily precipitation and air temperature data for China were obtained from CN05 gridded observations (Wu and Gao, 2013). All data covered the period of 1961–2020.
2.2
Methods
We used Singular Value Decomposition (SVD) analysis, correlation analysis, moving correlation analysis, and linear regression. Additionally, the Welch’s t-test was utilized to test the statistical significance (Bretherton et al., 1992; Wallace et al., 1992). Welch’s t-test constructs a new variable ν for the correction degrees of freedom to provide more accurate mutation test results under the assumption of no equal sequence lengths and variances. The corrected degrees of freedom are calculated as follows:
ν≈(s21n1+s22n2)2s41n21ν1+s42n22ν2,
(1)
where s is the standard deviation of the series, n is the number of samples in the series, and ν is the single-sample degree of freedom.
2.3
NECV index definition
The NECV is a key weather system that significantly influences early summer precipitation over Northeast China. To quantitatively describe the basic characteristics of NECV variations, an NECV index (INECV) was defined based on surface air temperature, following Miao et al. (2006). First, the Ulanhot station with the maxi-mum air temperature variance was selected as the reference station (Figs. 1a, b). The correlation between air temperature at Ulanhot station and that at each surrounding station was calculated, as shown in Fig. 1c. Based on the significant correlation area, the region defined by 40°–52°N, 116°–132°E marked by the green rectangle in Fig. 1c was selected as the target area. For convenience, the NECV index was defined based on the normalized averaged air temperature in the target area multiplied by −1.0. A positive index indicates stronger or more frequent cold vortex activity, whereas a negative index indicates weaker or less frequent cold vortex activity.
Fig
1.
(a) Distribution of the variance (shaded) of surface air temperature in June at each station (dots) in the Chinese mainland, (b) the largest variances at 20 stations, (c) distribution of the correlation (shaded dots) between June surface air temperature at Ulanhot station and the surrounding stations [the green rectangle denotes the target area used for calculating the Northeast China cold vortex (NECV) index, INECV], and (d) temporal evolution of INECV in June 1961–2020.
3.
Relationship between early summer precipitation over Northeast China and spring land surface thermal anomalies in West Asia
SVD analysis was performed to determine the possible coupling relationship between spring (March–April–May; MAM) land surface temperature in West Asia and early summer (June) precipitation over Northeast China. Figure 2 shows the first coupled singular vectors of June precipitation and MAM land surface temperature (accounting for 49.7% of the total variance) and their corresponding principal components (time series). The left field represents the typical spatial pattern of June precipitation anomalies in Northeast China (Fig. 2a), and the right field represents the MAM land surface temperature anomalies in West Asia (Fig. 2b). Both are characterized by consistent spatial variations. The maximum rainfall anomalies are located over the Greater Khingan Mountains and Northeast Plain, whereas the maximum temperature anomalies appear in the Iranian Plateau and its northeast region. This suggests that spring land surface warming over West Asia is closely associated with a decrease in early summer rainfall over Northeast China, as revealed by previous studies (Yang et al., 2021).
Fig
2.
(a) Spatial patterns for the first Singular Value Decomposition (SVD) mode of June precipitation (P) over Northeast China, (b) spring (March–April–May; MAM) land surface temperature in West Asia during 1961–2020, (c) corresponding normalized time series for the first SVD mode, and (d) 11-yr running correlation of the two time series in the SVD analysis. Dashed lines indicate the significance level of p < 0.05.
According to the time series of the two SVD modes, June rainfall in Northeast China is negatively correlated (−0.37; p < 0.01) with spring land surface temperature in West Asia. However, the 11-yr running correlation analysis suggests that this relationship was unstable throug-hout the study period (Fig. 2d). There was a transition of the temperature–rainfall relationship around 1990. More specifically, the temperature–rainfall correlation was gen-erally weakly negative and even positive before 1990, whereas it became significantly negative after 1990, implying a possible interdecadal shift in the rainfall–temperature relationship on a long-term timescale.
Further quantitative analysis of this interdecadal change of the temperature–rainfall relationship was performed. Based on the SVD analysis results, Northeast China (38–55°N, 118–135°E) and West Asia (30–40°N, 55–75°E) were selected as the target areas for early summer precipitation and MAM land surface temperature variations, respectively. Then, the Northeast China summer precipitation index (INECP) and West Asia land thermal index (IWALT) were defined by using the normalized regionally averaged rainfall and temperature over these two key regions (Fig. 3). The correlation between INECP and IWALT was −0.29 (p < 0.05) over the entire period.
Fig
3.
(a) Northeast China summer precipitation index (INECP) and West Asian spring land thermal index (IWALT), and (b) 11-yr running correlation coefficients between INECP and IWALT and results from the Mann–Kendall (MK) test. Dashed lines indicate the significance levels of p < 0.10 and p < 0.05 for the moving windows. Sequential Mann–Kendall test statistics, i.e., UF value and its inverse order UB value, are shown by the red and blue lines, respectively.
The 11-yr running correlation between INECP and IWALT indicates that although a weak and positive correlation existed with an average correlation coefficient of −0.09 (insignificant) before 1990, it became significant and negatively correlated with a correlation coefficient of −0.40 (p < 0.05) after 1990. Both the SVD results and analysis based on the indices demonstrated that the relationship between early summer precipitation over Northeast China and the preceding spring surface temperature in West Asia experienced a decadal change around 1990. This was indicated by the Mann–Kendall (MK) test. Therefore, we divided the entire study period into a pre-decadal transition period (1961–1990; P1) and a post-transition period (1991–2020; P2).
To further examine this change of the relationship, Fig. 4 presents the distribution of the correlation between INECP and IWALT as well as the correlation between IWALT and early summer precipitation for P1 and P2. During 1961–2020, IWALT was negatively correlated with early summer precipitation in most areas in Northeast China (Fig. 4a1), and INECP was also negatively correlated with land surface temperature in the target area over West Asia. The spatial patterns are similar to those of the SVD analysis in Fig. 2. These significant correlations disappeared during P1 (Figs. 4b1, 4b2). However, both correlations intensified during P2 (Figs. 4c1, 4c2). In summary, an interdecadal change of the relationship between spring surface thermal anomalies in West Asia and early summer precipitation over Northeast China occurred around 1990.
Fig
4.
Spatial distributions of the correlation between spring IWALT and June precipitation in Northeast China (top panels), INECP and mean spring surface temperature in West Asia (bottom panels) for time periods (a) 1961–2020, (b) P1, and (c) P2, respectively. The dotted areas denote values significant at p < 0.1 (gray) and p < 0.05 (white).
4.
Atmospheric responses to land surface thermal forcing before and after the interdecadal transition
To better understand the possible reasons for the interdecadal change of the temperature–rainfall relationship, we further analyzed the basic features of the atmospheric circulation anomalies in P1 and P2 corresponding to spring land surface heating anomalies in West Asia. Figure 5 presents the spring and early summer 200-hPa geopotential height fields regressed onto IWALT for P1 and P2. As suggested by Yang et al. (2021), land surface heating anomalies can trigger a CGT-like atmospheric teleconnection pattern in spring, which is maintained in early summer. During 1961–2020, the upper-level (200 hPa) atmosphere in spring corresponding to spring land surface thermal anomalies in West Asia was characterized by positive geopotential height anomalies in West Asia and the polar regions, but negative geopotential height anomalies in Northeast Asia (Fig. 5a1). In June, two significant positive potential height anomalies occurred in West and Northeast Asia (Fig. 5a2). Positive anomalies over Northeast Asia can directly affect the early summer climate in Northeast China, which is the main pathway by which spring land surface thermal anomalies in West Asia affect the climate in Northeast China. Similar atmospheric responses occurred in both P1 and P2 (Figs. 5b, c); however, there were significant differences in the abnormal circulation patterns, especially in Northeast Asia. The atmospheric response during P2 was much stronger than that during P1, indicating a more pronounced CGT-like spatial pattern during P2.
Fig
5.
Regressed geopotential height anomalies (shaded; gpm) in spring (left panels) and June (right panels) in (a) 1961–2020, (b) P1, and (c) P2 at 200 hPa onto spring IWALT. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
We further examined the differences in the corresponding atmospheric circulation in the middle (500 hPa) and lower (850 hPa) troposphere by looking into the main features of atmospheric circulation anomalies in early summer obtained from the regression onto the spring IWALT (Fig. 6). At 500 hPa, the corresponding atmospheric circulation is generally characterized by negative geopotential height anomalies in the middle–high latitudes of the Eurasian continent, with two anomalous cyclonic circulations centered in Europe and the northern part of the Asian continent. Meanwhile, positive geopotential height anomalies (or abnormal anticyclonic circulation) appeared over West Asia and near Lake Baikal (Fig. 6a). The 850-hPa circulation anomalies are almost the same as those at 500 hPa except for the negative geopotential height anomalies and anomalous cyclonic circulation over West Asia (Fig. 6b). This response was well explained by Yang et al. (2021). Comparison of the corresponding atmospheric circulations among these three periods shows that the anomalies intensified during P2 (Figs. 6a3, 6b3).
Fig
6.
1Regressed geopotential height (shaded; gpm) and wind (vector; m s−1) in June for (a1, b1) 1961–2020, (a2, b2) P1, and (a3, b3) P2 at (a) 500 and (b) 850 hPa onto the spring IWALT. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
Since NECV is the main circulation system affecting early summer precipitation in Northeast China, the evident anomalies over Northeast Asia might be the direct pathway through which spring land surface thermal anomalies in West Asia affect the climate in Northeast China. Figure 7 presents the regressed relative vorticity anomalies and geopotential height anomalies in June on IWALT for all three periods. Spatially, compared to P1, P2 exhibited warmer West Asian land temperatures, corresponding to lower vorticity and higher geopotential height over Lake Baikal to the northeast of China in June (Figs. 7a2, 7a3,7b2, 7b3), implying a decrease in the frequency or intensity of early summer NECV activity. To quantitatively evaluate this change, a moving correlation analysis between spring IWALT and early summer INECV during 1961–2020 was performed, as shown in Fig. 7. The results reveal a negative correlation between them, which was enhanced after the end of the 1980s.
Fig
7.
Regressed relative vorticity anomalies (shaded; s−1) and geopotential height anomalies (contour; gpm) in June at (a) 200 and (b) 500 hPa for ((a1, b1) 1961–2020, ((a2, b2) P1, and ((a3, b3) P2 onto the spring IWALT. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively. (c) 11-yr running correlation coefficients between INECV and spring IWALT. Dashed lines indicate the significance levels of p < 0.10 and p < 0.05 for the moving windows.
Notably, such anomalous circulation patterns not only inhibit the activity of NECV, but also impact local verti-cal motion and moisture transport. As shown in Fig. 8, during P2, under this circulation pattern, upward motion was suppressed, leading to weakened convection unfavorable for precipitation. Meanwhile, as shown in Fig. 9, during P2, when anomalous warming occurred in West Asia, moisture from the western Pacific tended to bypass Northeast China and move northward, resulting in local moisture flux convergence in Northeast China. As a result of the combined effects of these factors, precipitation over Northeast China was decreased during the years of anomalous warming in West Asia.
Fig
8.
Vertical profile of 11-yr running correlation coefficients between spring IWALT and vertical velocity over the Northeast China critical zone in June. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
Fig
9.
Composite of moisture flux (vector; m s−1) and divergence of moisture flux [shaded; kg m (kg s)−1] of spring IWALT for ((a1, b1) positive and ((a2, b2) negative anomaly years and ((a3, b3) differences during (a) P1 and (b) P2. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
5.
Possible links between interdecadal transition of the temperature–rainfall relationship and the westerly jet stream
Previous results have suggested that there is an interdecadal change of the atmospheric circulation corresponding to spring land surface thermal anomalies in West Asia. In spring, during P2, the center of the CGT-like response of the upper atmosphere over West Asia exhibited little change, accompanied by a significant negative center over Northeast China. In early summer, there was a significant enhancement of the global CGT centers, particularly of the negative vorticity center formed over Northeast China, which was much stronger than that during P1. According to Yang et al. (2021), an anomalous anticyclone triggered by land surface warming in West Asia can induce a Rossby wave train that persists from spring to early summer. As the westerly jet stream weakens and shifts northward from spring to early summer, the anomalous wave train transitions into a CGT-like mode. This mode generates an intensified wave activity center over Northeast China, thereby influencing the climate in Northeast China.
The interdecadal transition is possibly linked to the westerly jet stream. Figure 10 shows the empirical orthogonal function (EOF) analysis of the zonal wind at 200 hPa in June and regressed zonal wind on IWALT. The second principal component (PC2) mode of the EOF zonal wind in early summer exhibits a zonal asymmetry feature. Conversely, there are differences between P1 and P2 regarding the corresponding patterns of the zonal wind regressed to IWALT. Compared with the dipole distribution in P1, the pattern shows a zonal asymmetry feature similar to the PC2 mode of the EOF zonal wind in early summer. Figure 11 illustrates the relationship between PC2 and INECV, along with their regressions onto the geopotential height and vorticity in early summer. The results demonstrate a significantly enhanced relationship between the jet stream and the NECV during P2, showing strong correlations between West Asia and Northeast China. This asymmetric variation connects the two regions and may facilitate the propagation of negative vorticity downstream from West Asia to Northeast China, suppressing the NECV activity and influencing precipitation over Northeast China.
Fig
10.
Patterns of the (a, b) eigenvectors and (c) eigenvalues of the first two leading EOF modes of zonal wind (U; m s−1) at 200 hPa in June. Regressed zonal wind (U; m s−1) in June in (d) P1 and (e) P2 at 200 hPa onto IWALT. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
Fig
11.
(a) Scatter plot and regression analysis depicting the relationship between INECV and PC2 of the EOF zonal wind. Regression patterns of the 200-hPa relative vorticity (shaded; s−1) and geopotential height (contour; gpm) onto PC2 of the EOF zonal wind in (b) P1 and (c) P2. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
The above analysis indicates that there is a link between the westerly jet stream and the interdecadal relationship transition. A similar pattern implies a possible connection, and during P2, the enhanced relationship between the westerly jet stream and the NECV may contribute to the altered NECV activity, which in turn affects the interdecadal relationship transition.
6.
Conclusions and discussion
This study investigated the interdecadal change in the relationship between spring surface thermal anomalies in West Asia and early summer precipitation over Northeast China, along with variations in atmospheric circulation and associated mechanisms. The main conclusions are as follows:
(1) There has been an interdecadal transition of the relationship between spring surface thermal anomalies in West Asia and early summer precipitation over Northeast China. This shift began in the 1980s, with an initially insignificant positive correlation, which became stronger and negative in the late 1990s. The Mann–Kendall test was used to divide the study period into P1 (1961–1990) and P2 (1991–2020).
(2) There are differences in the corresponding atmospheric circulation and land surface thermal anomalies between the periods before and after the decadal transition. During P2, the warming of spring surface thermal anomalies in West Asia corresponded to an enhanced CGT in early summer, which in turn suppressed the NECV activity. Furthermore, the changes in circulation patterns resulted in weakened moisture transport, strengthened subsidence, reduced precipitation triggering, and consequently, weakening of early summer precipitation over Northeast China.
(3) Further analysis indicated that the decadal transition of the relationship between spring surface thermal anomalies in West Asia and early summer precipitation over Northeast China, as well as the changes in the atmospheric circulation response, may be related to the westerly jet stream. Moreover, a strong positive correlation between the NECV and PC2 of the westerly jet stream during P2 may, in turn, have suppressed precipitation over Northeast China.
This study provides a preliminary exploration of the decadal variations of the relationship between spring surface thermal anomalies in West Asia and early summer precipitation over Northeast China by using observational data and statistical methods. These results have implications for understanding and predicting early summer precipitation over Northeast China. However, there are multiple factors influencing precipitation over Northeast China, such as changes in sea surface temperature. The interactions and mechanisms of these different factors influencing early summer precipitation over Northeast China require further in-depth investigations.
Fig.
10.
Patterns of the (a, b) eigenvectors and (c) eigenvalues of the first two leading EOF modes of zonal wind (U; m s−1) at 200 hPa in June. Regressed zonal wind (U; m s−1) in June in (d) P1 and (e) P2 at 200 hPa onto IWALT. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
Fig.
1.
(a) Distribution of the variance (shaded) of surface air temperature in June at each station (dots) in the Chinese mainland, (b) the largest variances at 20 stations, (c) distribution of the correlation (shaded dots) between June surface air temperature at Ulanhot station and the surrounding stations [the green rectangle denotes the target area used for calculating the Northeast China cold vortex (NECV) index, INECV], and (d) temporal evolution of INECV in June 1961–2020.
Fig.
2.
(a) Spatial patterns for the first Singular Value Decomposition (SVD) mode of June precipitation (P) over Northeast China, (b) spring (March–April–May; MAM) land surface temperature in West Asia during 1961–2020, (c) corresponding normalized time series for the first SVD mode, and (d) 11-yr running correlation of the two time series in the SVD analysis. Dashed lines indicate the significance level of p < 0.05.
Fig.
3.
(a) Northeast China summer precipitation index (INECP) and West Asian spring land thermal index (IWALT), and (b) 11-yr running correlation coefficients between INECP and IWALT and results from the Mann–Kendall (MK) test. Dashed lines indicate the significance levels of p < 0.10 and p < 0.05 for the moving windows. Sequential Mann–Kendall test statistics, i.e., UF value and its inverse order UB value, are shown by the red and blue lines, respectively.
Fig.
4.
Spatial distributions of the correlation between spring IWALT and June precipitation in Northeast China (top panels), INECP and mean spring surface temperature in West Asia (bottom panels) for time periods (a) 1961–2020, (b) P1, and (c) P2, respectively. The dotted areas denote values significant at p < 0.1 (gray) and p < 0.05 (white).
Fig.
5.
Regressed geopotential height anomalies (shaded; gpm) in spring (left panels) and June (right panels) in (a) 1961–2020, (b) P1, and (c) P2 at 200 hPa onto spring IWALT. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
Fig.
6.
1Regressed geopotential height (shaded; gpm) and wind (vector; m s−1) in June for (a1, b1) 1961–2020, (a2, b2) P1, and (a3, b3) P2 at (a) 500 and (b) 850 hPa onto the spring IWALT. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
Fig.
7.
Regressed relative vorticity anomalies (shaded; s−1) and geopotential height anomalies (contour; gpm) in June at (a) 200 and (b) 500 hPa for ((a1, b1) 1961–2020, ((a2, b2) P1, and ((a3, b3) P2 onto the spring IWALT. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively. (c) 11-yr running correlation coefficients between INECV and spring IWALT. Dashed lines indicate the significance levels of p < 0.10 and p < 0.05 for the moving windows.
Fig.
8.
Vertical profile of 11-yr running correlation coefficients between spring IWALT and vertical velocity over the Northeast China critical zone in June. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
Fig.
9.
Composite of moisture flux (vector; m s−1) and divergence of moisture flux [shaded; kg m (kg s)−1] of spring IWALT for ((a1, b1) positive and ((a2, b2) negative anomaly years and ((a3, b3) differences during (a) P1 and (b) P2. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
Fig.
11.
(a) Scatter plot and regression analysis depicting the relationship between INECV and PC2 of the EOF zonal wind. Regression patterns of the 200-hPa relative vorticity (shaded; s−1) and geopotential height (contour; gpm) onto PC2 of the EOF zonal wind in (b) P1 and (c) P2. Gray and white dots indicate areas with significance levels of p < 0.10 and p < 0.05, respectively.
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Sun, H. J., H. S. Chen, X. G. Du, et al., 2024: Interdecadal change of the relationship between early summer precipitation over Northeast China and spring land surface thermal anomalies in West Asia. J. Meteor. Res., 38(4), 720–732, doi: 10.1007/s13351-024-3227-6
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Sun, H. J., H. S. Chen, X. G. Du, et al., 2024: Interdecadal change of the relationship between early summer precipitation over Northeast China and spring land surface thermal anomalies in West Asia. J. Meteor. Res., 38(4), 720–732, doi: 10.1007/s13351-024-3227-6
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Sun, H. J., H. S. Chen, X. G. Du, et al., 2024: Interdecadal change of the relationship between early summer precipitation over Northeast China and spring land surface thermal anomalies in West Asia. J. Meteor. Res., 38(4), 720–732, doi: 10.1007/s13351-024-3227-6
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Citation:
Sun, H. J., H. S. Chen, X. G. Du, et al., 2024: Interdecadal change of the relationship between early summer precipitation over Northeast China and spring land surface thermal anomalies in West Asia. J. Meteor. Res., 38(4), 720–732, doi: 10.1007/s13351-024-3227-6
.
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Manuscript History
Received: 25 December 2023
Revised: 18 February 2024
Accepted: 27 February 2024
Available online: 28 February 2024
Final form: 20 March 2024
Typeset Proofs: 24 April 2024
Issue in Progress: 24 June 2024
Published online: 25 August 2024
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Abstract
摘要
1.
Introduction
2.
Data and methods
2.1
Data
2.2
Methods
2.3
NECV index definition
3.
Relationship between early summer precipitation over Northeast China and spring land surface thermal anomalies in West Asia
4.
Atmospheric responses to land surface thermal forcing before and after the interdecadal transition
5.
Possible links between interdecadal transition of the temperature–rainfall relationship and the westerly jet stream
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