Abstract

The moisture supplies over Siberia and Northeast Asia are investigated by comparing their similarities and differences, enlightened by the seesaw pattern in their summer precipitation. Based on the rotated empirical orthogonal functions in the 3-month standardized precipitation evapotranspiration index (SPEI_03), Siberia and Northeast Asia are defined as the regions within 55°–70°N, 80°–115°E and 40°–55°N, 90°–115°E, respectively. Our results show that over both regions, evaporation contributes the most to the precipitation amount at the annual time scale, and moisture convergence contributes the most on the interannual time scale. For moisture convergence, both the stationary and transient terms are subject to impacts of the midlatitude westerlies. For the annual cycle, the net moisture supply over both Siberia and Northeast Asia is closely associated with both stationary and transient moisture transport. However, on the interannual time scale, the net moisture convergence is closely related to the stationary term only. The examination of the boundary moisture transport shows that in addition to the zonal component, the meridional stationary moisture transport plays a key role in the net moisture convergence. The transient moisture transport mainly depends on moisture transport through the western and southern boundaries, with a comparable magnitude to that of the stationary one, further confirming the importance of the stationary and transient terms on the moisture supply for the annual cycle. In addition, the circulations responsible for moisture transport anomalies indicate that the stationary moisture circulation is the key factor for the moisture supply anomalies over both Siberia and Northeast Asia, with limited impacts from the transient moisture circulation.

1. Introduction

Northeast Asia, located between the middle and high latitudes, mainly consists of Mongolia, the north of Inner Mongolia, and part of north China. The annual total precipitation in this region ranges from less than 50 mm in the southwest to more than 350 mm in the northeast, covering arid and semiarid climate zones. With a low annual total amount and large interannual variability, the precipitation here has a large impact on agricultural production and economic development throughout the year (Mu et al. 2013; Munkhtsetseg et al. 2007; Peng et al. 2013; Yamanaka et al. 2007). The precipitation variability is closely related to vegetation cover (Chuai et al. 2013; Lee et al. 2002), lake shrinkage (Tao et al. 2015; Zhang et al. 2012), and dust storm frequency over Northeast Asia (Lee and Sohn 2011; Liu et al. 2004). Many studies have been performed to explore the associated factors of precipitation anomalies over Northeast Asia (Wu et al. 2009; Ye 2001; Yoon and Yeh 2010; Li et al. 2014). Lee et al. (2005) found that the summer rainfall over Northeast Asia is associated with ENSO and the Eurasian wave pattern. Liu and Yanai (2002) suggested that the Eurasian snow cover in the spring can exert a great impact on summer rainfall in northern Mongolia through a Rossby wave train–like response. The Northern Hemisphere circumglobal teleconnection can also contribute to the precipitation anomalies over northern China via modulating moisture transportation and ascending motion (Huang et al. 2011). Recently, a significant decadal shift in the late 1990s was identified over Northeast Asia (Liu et al. 2011; Piao et al. 2017; Zhu et al. 2011), with decreased precipitation causing water shortage and drought development. It motivates the further investigation on the moisture supply to the region.

The available moisture mostly comes from local evaporation and large-scale moisture transport. In terms of moisture origins, Sato et al. (2007) investigated the summer situation in 2003 over Northeast Asia and showed that they are mainly from central Asia and western Siberia, instead of tropical Asia, the South China Sea, or the Atlantic Ocean (Ma et al. 2008; Numaguti 1999; Yatagai and Yasunari 1998). Simmonds et al. (1999) investigated the moisture transport over southeast China and northeast China, and suggested that the midlatitude westerlies are critical for moisture transport over northeast China, and moisture convergence plays a significant role in the interannual variation of precipitation over the region. Sato and Kimura (2005) stated the blocking effects of the Tian Shan and Altai mountain ranges for moisture transported into northern China. In addition, Ma and Gao (2006) identified interdecadal variations of moisture transportation paths over north China with the HYSPLIT_4 model and reanalysis data. Their results showed that the dominant direction of moisture transportation at 850 hPa is from the south during 1950–70, but changes to the west during the 1970s. After the late 1970s, moisture is mainly transported from the northwest.

Most of the abovementioned studies investigated the moisture transport over Northeast Asia from the vertically integrated total column moisture flux, which can imply where the moisture comes from but not detect the quantitative contribution. Here, we present more quantitative insight into moisture transport over Northeast Asia. Besides, a seesaw pattern exists in the summer rainfall between Northeast Asia and Siberia (Iwao and Takahashi 2006, 2008). For the moisture condition over Siberia, most studies have focused on the moisture origin (Numaguti 1999; Serreze et al. 2002; Stohl and James 2005; van der Ent et al. 2010) instead of the moisture transport. In consideration of this, we further compare the similarities and differences of moisture transport between the two regions in detail. In section 2, we describe the datasets and methods used in this study. The main results are documented in section 3, including the moisture budget and the related moisture circulations for the anomalies of moisture supply over the two regions. We present the conclusions and discussion in section 4.

2. Data and methods

The datasets used in this study include the following: precipitation, evaporation, surface temperature, horizontal wind, specific humidity, and surface pressure from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim), with a horizontal resolution of 2.5° × 2.5° (latitude and longitude). Both monthly and 6-hourly data are used, spanning from 1979 to 2016. Besides, two other datasets are employed to confirm the results derived by the ERA-Interim: 1) the Climate Prediction Center Merged Analysis of Precipitation (CMAP) data (Xie and Arkin 1997) with a horizontal resolution of 2.5° × 2.5° from 1979 to 2016, and 2) the evaporation field from the Global Land Evaporation Amsterdam Model (GLEAM) on a 0.25° × 0.25° grid in longitude and latitude from 1980 to 2016. The GLEAM is a set of algorithms that provides estimations of various components of land evaporation based on the satellite observations (Martens et al. 2017; Miralles et al. 2011).

The calculation of moisture budget is based on the balance equation for atmospheric water vapor (Schmitz and Mullen 1996), which can be expressed as below:

 
formula

where W, E, and P represent the total column moisture, evaporation, and precipitation, respectively. The Q is the vertically integrated water vapor flux, calculated based on the following equation:

 
formula

where is the pressure at the top of the troposphere, while is the surface pressure, g is the acceleration due to gravity, V is the horizontal wind, and q is the specific humidity. In this study, we are interested in the monthly vertical integral of the water vapor flux, which could be partitioned into four terms (Peixoto and Oort 1992) as follows:

 
formula

where the two terms on the right side stand for the mean moisture transported by the mean wind (Q1), and the transient moisture transported by the transient wind (Q2), respectively. The variables Q1 and Q2 represent the moisture transport accompanied by monthly mean flow and cyclone activities, respectively (Oshima et al. 2015). The overbar denotes the monthly average, and the prime is deviation from the mean. The moisture transported through each boundary is then further explored, following the method below mentioned in Schmitz and Mullen (1996):

 
formula

where n represents the inward unit vector normal to the corresponding boundary, and L is the length of the boundary.

Besides, a drought index is employed, the standard precipitation evapotranspiration index (SPEI). SPEI has advantages of both the sensitivity to temperature variation and multiscalar character, as its calculation procedure takes into account the effects of both precipitation and evapotranspiration. The time scales of SPEI are arbitrary but typical, with 3 months representing the impacts of precipitation deficits on soil moisture (SPEI_03). Hence, SPEI_03 is employed to reflect the moisture condition over the two regions. This index is widely used for detecting, monitoring, and exploring the drought conditions (Vicente-Serrano et al. 2010). We calculate the SPEI_03 by using monthly mean precipitation and potential evapotranspiration (PET) from the ERA-Interim dataset.

In this study, the annual cycle and seasonal mean (i.e., MAM, JJA, SON, and DJF mean) are investigated to obtain a basic understanding of the moisture supply. The statistical methods include the correlation analysis, the composite analysis, the empirical orthogonal function (EOF), and rotated EOF (REOF), all of which are performed from 1979 to 2016. The composite analysis is employed to determine the differences in the moisture circulation between wet and dry years, with the wet (dry) years defined as the period when the standardized deviation of regional mean moisture convergence is larger (smaller) than 1 (−1). The Student’s t test is adopted for the significance test.

3. Results

a. Definition of Northeast Asia and Siberia

The seesaw pattern identified in the summer precipitation between Northeast Asia and Siberia is suggested to be associated with a quasi-stationary Rossby wave along the Asian jet and over the Eurasian continent (Iwao and Takahashi 2006, 2008). As the moisture supply is one of the key factors influencing the precipitation change, then what is the moisture situation over these two regions? Fig. 1 shows the REOF analysis on the annual mean SPEI_03, which is performed on the 10 leading EOFs. It is considered to be more statistically stable and physically reasonable than the EOF method (Hannachi et al. 2007; Horel 1981). The percent variances explained by the first two modes are 17.1% and 10.7%, respectively (Figs. 1a,b). The centers of significant values are located over Northeast Asia for the first REOF and the Siberia region for the second REOF (Figs. 1a,b), which manifests the independence of the moisture situation within these two regions. According to the results of the REOF method, we defined the regions within 40°–55°N, 90°–115°E and 55°–70°N, 80°–115°E as Northeast Asia and Siberia, respectively.

Fig. 1.

The spatial distribution of correlation coefficients between the (a) first and (b) second REOF time series and SPEI_03 index. The shadings denote correlation coefficients significant at the 90% confidence level based on the Student’s t test. The upper and lower black boxes represent the defined study areas in Siberia and Northeast Asia, respectively.

Fig. 1.

The spatial distribution of correlation coefficients between the (a) first and (b) second REOF time series and SPEI_03 index. The shadings denote correlation coefficients significant at the 90% confidence level based on the Student’s t test. The upper and lower black boxes represent the defined study areas in Siberia and Northeast Asia, respectively.

b. Data reliability over Northeast Asia and Siberia

It should be noted that the precipitation and evaporation data of the ERA-Interim are obtained from the forecast field, which is strongly dependent on the forecast model. Though the ERA-Interim can better depict the hydrological cycle than previous ERA reanalyses (Tavolato and Isaksen 2011; Trenberth et al. 2011), it still makes some deviations in reproducing meteorological fields, especially over high-altitude regions (Li et al. 2013; Tong et al. 2014). Hence, it is necessary to examine the applicability of the two variables over Siberia and Northeast Asia. Two other datasets are employed for comparison: 1) the CMAP precipitation field and 2) the GLEAM evaporation product. For the climatological mean of annual total precipitation, the ERA-Interim and CMAP exhibit similar spatial patterns, with the precipitation amount increasing from Mongolia to the western part of Siberia (Figs. 2a,b). However, the precipitation amount derived from the ERA-Interim shows larger values than that from the CMAP, especially over the western part of Siberia and the northern part of Northeast Asia. Despite the overestimation of the precipitation amount by the ERA-Interim compared to the CMAP, the regional mean of annual total precipitation obtained from these two datasets are significantly related during 1979–2016, for both Siberia and Northeast Asia. Based on the similar results derived by the two datasets, it is suggested that the ERA-Interim has the ability to capture the basic features of precipitation change, including the climatological mean state and interannual variation. In terms of the evaporation, similarities can also be found in the spatial distribution of the climatological mean (Figs. 2c,d) based on the ERA-Interim and GLEAM, both of which show strong evaporation to the north of Mongolia (between 50° and 60°N) and weak evaporation over Northeast Asia (Figs. 2c,d). The correlation coefficient of regional mean annual total evaporation between the ERA-Interim and GLEAM is also significant at the 99% confidence level according to the Student’s t test, for both Siberia and Northeast Asia. Because of the consistency of both climatological mean and interannual variation between the ERA-Interim and Gleam, the evaporation dataset from the ERA-Interim is considered reliable for our investigation.

Fig. 2.

The climatological mean of annual total precipitation (mm yr−1) derived from (a) ERA-Interim and (b) CMAP. (c) As in (a), but for evaporation (mm yr−1). (d) As in (c), but for the evaporation from GLEAM.

Fig. 2.

The climatological mean of annual total precipitation (mm yr−1) derived from (a) ERA-Interim and (b) CMAP. (c) As in (a), but for evaporation (mm yr−1). (d) As in (c), but for the evaporation from GLEAM.

c. Contribution of evaporation and moisture convergence to precipitation

Regarding a specific region as a bucket, the water in this bucket is balanced by the evaporation and precipitation in the vertical and moisture convergence in the horizontal. Therefore, the precipitation is determined by the underlying evaporation and dynamical moisture convergence. Figure 3 shows the climatological (1979–2016) annual cycle of evaporation, moisture convergence, and precipitation over Siberia and Northeast Asia. The time variation of total column water vapor is not shown because of its rather small values. The two regions have the most precipitation in summer months, from June to August. Northeast Asia has very dry conditions in winter months from December to February with little precipitation (Fig. 3b). However, Siberia still receives considerable precipitation throughout the year (Fig. 3a). Over Siberia, the local evaporation is remarkably strong during summer and dominates the precipitation. In July the evaporation is even compensated by the moisture divergence to keep the regional water balance (Fig. 3a). Being located in a high latitude, Siberia becomes colder after summer and less efficient in surface evaporation (Fig. 3a). Therefore, the precipitation in other seasons mostly comes from moisture convergence. The ERA reanalysis shows that the annual total precipitation is about 553 mm yr−1 over Siberia, and the moisture convergence and evaporation are 320 and 218 mm yr−1, respectively. Hence, it is indicated that in the perspective of the annual cycle, the evaporation contributes most to the precipitation during the wet season, with the moisture convergence being the dominant source for precipitation in the dry season over Siberia. As for Northeast Asia, the monthly evolution of precipitation resembles that of evaporation for the whole year, with some contributions from moisture convergence from April to July (Fig. 3b). The total annual precipitation over Northeast Asia is approximately 320 mm yr−1. The amount of evaporation is up to 273 mm yr−1, in contrast to 58 mm yr−1 for moisture convergence. Based on atmospheric water budget, it is suggested that the evaporation can exert important influence on precipitation in both the wet season and dry seasons, with limited impacts of moisture convergence on precipitation over Northeast Asia for the annual cycle. The result is consistent with previous studies, which also demonstrated the dominant role of evaporation on precipitation over eastern Siberia in regard to the climatological mean (Fujinami et al. 2016; Fukutomi et al. 2003; Serreze and Etringer 2003; Serreze et al. 2002). It should be noted that the moisture budget is not closed over the two regions because of data quality, with deviations () of 15.2 and 11.2 over Siberia and Northeast Asia, respectively. For the relatively small values of deviations compared with precipitation, evaporation, and moisture convergence, the ERA-Interim is considered reliable for the investigation of the moisture budget over Siberia and Northeast Asia.

Fig. 3.

The climatological annual cycle of precipitation (gray bars), evaporation (red line with red circles), and moisture convergence (blue line with blue circles) over (a) Siberia and (b) Northeast Asia based on the ERA-Interim dataset (mm month−1).

Fig. 3.

The climatological annual cycle of precipitation (gray bars), evaporation (red line with red circles), and moisture convergence (blue line with blue circles) over (a) Siberia and (b) Northeast Asia based on the ERA-Interim dataset (mm month−1).

Figure 4 shows that the moisture convergence is significantly correlated with precipitation in all months over the two regions. For the relationship between evaporation and precipitation, generally there exists a complicated feedback: evaporation can add more moisture in favor of a precipitation increase on the one hand, and on the other, reduce the surface air temperature, causing a precipitation decrease (Meehl 1994); the precipitation in turn can have a positive impact on local evaporation by providing enough water to evaporate and cause a negative impact through moderating the temperature (Li et al. 2013). Regarding the correlation between evaporation and precipitation, the significant positive correlation is identified from September to March but with a weak, even negative, relationship in the wet season over Siberia (Fig. 4a). Considering the significant role of moisture convergence on precipitation, the evaporation change in the wet season seems to be caused by, rather than results in, the precipitation variation. Hence, the negative relationship might be associated with the negative impact of precipitation on evaporation. In addition, the correlation coefficients between evaporation and precipitation are weak during most months over Northeast Asia, except for the significant positive ones in the wet season from July to September (Fig. 4b). The weak correlation might be due to the positive impact of precipitation on evaporation counteracting the negative one. Hence, it is considered that in the interannual scale, the moisture convergence dominates precipitation variation in both regions. The results are in accordance with the study of Simmonds et al. (1999), whih demonstrated that the moisture convergence plays a dominant role on the rainfall anomalies over northeast China.

Fig. 4.

The correlation coefficients between precipitation and evaporation (red line with red circles) and moisture convergence (blue line with blue circles) for each month over (a) Siberia and (b) Northeast Asia. The dashed lines represent the value that is significant at the 90% confidence level based on the Student’s t test.

Fig. 4.

The correlation coefficients between precipitation and evaporation (red line with red circles) and moisture convergence (blue line with blue circles) for each month over (a) Siberia and (b) Northeast Asia. The dashed lines represent the value that is significant at the 90% confidence level based on the Student’s t test.

The monthly mean moisture convergence can be decomposed into two terms based on Eq. (3): Q1 (the stationary term) and Q2 (the transient term). The spatial distributions of their seasonal mean are shown in Figs. 5 and 6. It is clearly seen that the stationary moisture transports over the two regions are both subject to the strong influences of the midlatitude westerlies during the whole year. The stationary moisture transport is mainly from the west for Siberia and from the northwest for Northeast Asia. Siberia is covered by stationary moisture convergence in spring, autumn, and winter and moisture divergence in summer, whereas Northeast Asia is dominated by moisture divergence for the whole year, though the divergence has a noisy structure (Fig. 5). In the spring, moisture divergence covers Japan, Northeast Asia, and north and northeast China, with moisture convergence situated over Siberia and the western part of the Eurasian continent (Fig. 5a). The spatial distribution is similar in autumn and winter (Figs. 5c,d), except for the stronger magnitude of divergence and convergence. In the summer, significant moisture divergence is noticed over Siberia and western Asia, with moisture convergence over north and northeast China and Japan, which is nearly opposite to that of other seasons (Fig. 5b). The moisture convergence might result from the strong East Asia summer monsoon, which could bring abundant moisture into north and northeast China and Japan. For the moisture divergence, it is considered to be related to the stronger northwesterly flow over Northeast Asia, which transports moisture out of Siberia into its southern regions, as shown in the study of Yatagai and Yasunari (1998). The magnitude of the transient term is much smaller, less than half of the stationary term (Fig. 6). For spring, autumn, and winter over Siberia, the transient moisture transport shows a similar mode as follows: the moisture is transported from the southwest into Siberia, causing moisture convergence here (Figs. 6a,c,d). However, in the summer, the southerly flow dominates this area, transporting moisture from Siberia into the Arctic region, and results in moisture divergence (Fig. 6b). It seems that the role of the transient term on moisture transport over Siberia strengthens the stationary term. Northeast Asia is subject to the southerly transient moisture transport during the whole year, which brings in moisture from its southern regions, weakening the moisture divergence caused by the stationary term (Fig. 6). Figure 7 further shows the correlation coefficients between the two terms and the net moisture convergence for each month from 1979 to 2016. It is clear that the net moisture supply has a close relationship with the stationary moisture transport during the whole year over the two regions, but a weak connection with the transient transport.

Fig. 5.

The climatological mean of vertically integrated stationary water vapor flux (vectors; kg m−1 s−1) and its divergence (shading; 10−5 kg m−2 s−1) in the (a) spring, (b) summer, (c) autumn, and (d) winter.

Fig. 5.

The climatological mean of vertically integrated stationary water vapor flux (vectors; kg m−1 s−1) and its divergence (shading; 10−5 kg m−2 s−1) in the (a) spring, (b) summer, (c) autumn, and (d) winter.

Fig. 6.

As in Fig. 5, but for transient water vapor flux.

Fig. 6.

As in Fig. 5, but for transient water vapor flux.

Fig. 7.

The correlation coefficients between the net moisture convergence and the stationary moisture convergence (blue line with blue dots) and the transient moisture convergence (red line with red dots) for each month over (a) Siberia and (b) Northeast Asia.

Fig. 7.

The correlation coefficients between the net moisture convergence and the stationary moisture convergence (blue line with blue dots) and the transient moisture convergence (red line with red dots) for each month over (a) Siberia and (b) Northeast Asia.

d. The boundary moisture transport over Siberia and Northeast Asia

In this section, we provide a quantitative view of the moisture amount transported into the study area via each boundary and evaluate their contributions to the net moisture convergence, respectively. For the stationary boundary moisture transport over both regions, it is noticed that the moisture transport through the western (QW) and eastern boundary (QE) is much larger than that through other boundaries, with QW and QE showing inverse variation with each other (Figs. 8a,b). QW is regarded as the most important moisture input and QE is the most important moisture output. Although there are large amplitudes of QW and QE, the net zonal moisture transport shows rather small values because of the counteraction between them. In terms of the moisture transport through the southern boundary (QS) and northern boundary (QN), they both exhibit relatively small values and vary smoothly, compared with QW and QE (Figs. 8a,b). By calculation, the net meridional moisture transport shows negative values during the whole year over the two regions, with the magnitude similar to that of the net zonal moisture transport. For Siberia, the annual cycle of net moisture convergence is in accordance with that of both the zonal and meridional moisture transport (Fig. 8a). In terms of the situation over Northeast Asia, the meridional moisture transport is the key factor for the net moisture convergence during the first half year, but the zonal transport is the key in the second half (Fig. 8b). Hence, it is suggested that the zonal and meridional moisture transport together dominate the net stationary moisture supply over both Siberia and Northeast Asia, despite the prominent role of the westerlies shown in Fig. 5. It should be noted that the monthly evolution of the net stationary moisture convergence in Siberia is nearly opposite to that in Northeast Asia.

Fig. 8.

(a) The monthly evolution of stationary moisture transported into Siberia (108 kg month−1) via the southern boundary (green line), the northern boundary (blue line), the western boundary (red line), the eastern boundary (purple line), the net meridional (blue line with blue circles) and zonal (red line with red quadrates) boundary moisture transport, and the regional mean stationary moisture convergence (black line with black circles). (b) As in (a), but for Northeast Asia.

Fig. 8.

(a) The monthly evolution of stationary moisture transported into Siberia (108 kg month−1) via the southern boundary (green line), the northern boundary (blue line), the western boundary (red line), the eastern boundary (purple line), the net meridional (blue line with blue circles) and zonal (red line with red quadrates) boundary moisture transport, and the regional mean stationary moisture convergence (black line with black circles). (b) As in (a), but for Northeast Asia.

The magnitude of the transient moisture transport through each boundary is much smaller than that of the stationary moisture transport (Fig. 9). As expected, the transient moisture transport through the western and southern boundaries contributes the most to the moisture input, and that through the northern boundary contributes the most to the moisture output over Siberia and Northeast Asia (Fig. 9), which is consistent with the results shown in Fig. 6. On the other hand, despite the small amount of transient moisture transport through each boundary, the net transient moisture convergence is similar or even larger than that of the stationary one. The variation of the net transient moisture transport over Siberia and Northeast Asia is very similar, which is in accordance with that of the transient moisture transport through the western boundary (Fig. 9). For Siberia, the annual cycle of the net transient moisture convergence is consistent with the stationary one (Fig. 9a), which results in relatively large net moisture convergence in Fig. 3a. On the contrary, the net transient moisture convergence over Northeast Asia stays positive for the whole year (Fig. 9b), which offsets the negative values of the net stationary one (Fig. 8b). The counteraction of the two terms over Northeast Asia may explain the relatively small net moisture convergence in Fig. 3b. Hence, both the stationary and transient boundary moisture transport play crucial roles in the net moisture supply over Siberia and Northeast Asia for the annual cycle. Though Oshima et al. (2015) discussed the relationship of the total moisture convergence to the stationary and transient components over the three major river basins of Siberia (the Lena, Yenisei, and Ob), we provide more comprehensive results based on analysis of boundary moisture transport in contrast to the area-weighted mean in their work. Besides, we further revealed the relative importance of the net zonal and meridional moisture transport to the net moisture convergence for both the stationary and transient components.

Fig. 9.

As in Fig. 8, but for the transient moisture transport.

Fig. 9.

As in Fig. 8, but for the transient moisture transport.

e. The pathways for moisture transport anomalies

Studies have been performed on the climate change over the Eurasian continent with respect to terrestrial water cycles, and the trend and interannual variation of precipitation (Fujinami et al. 2016; Hiyama et al. 2016; Oshima et al. 2015). Oshima et al. (2015) focused on the water cycles of the Siberian rivers and investigated the climatological moisture transport within each river basin. Some studies emphasized the trend and interannual variability of summer precipitation over eastern Siberia and revealed the related atmospheric circulation anomalies (e.g., Fujinami et al. 2016; Hiyama et al. 2016). However, little attention has been paid to the role of the responsible moisture circulations for moisture supply anomalies. In this section, we discuss the contribution of the stationary and transient moisture circulations to the anomalies of the moisture supply over Siberia and Northeast Asia on the interannual time scale.

Figure 10 shows the interannual variation of the standardized regional mean moisture convergence during the four seasons over Siberia and Northeast Asia. It is noticed that the time series of different seasons over either of the two regions vary very differently (Figs. 10a,b), which means that the moisture condition for each season is mainly independent from that for others. In addition, the temporal variation in summer over Siberia (red line in Fig. 10a) seems to be opposite to that over Northeast Asia (red line in Fig. 10b). By calculation, they are significantly related with the correlation coefficient reaching −0.45, indicating that moisture conditions might contribute to the dipole pattern found in summer precipitation between Siberia and Northeast Asia. Reasons for these interannual variations are complicated and will be investigated in a future study.

Fig. 10.

The time series of standardized regional mean moisture convergence during four seasons over (a) Siberia and (b) Northeast Asia.

Fig. 10.

The time series of standardized regional mean moisture convergence during four seasons over (a) Siberia and (b) Northeast Asia.

Based on the time series shown in Fig. 10, we defined the wet (dry) years as the period when the value is larger (smaller) than 1 (−1). With the wet and dry years selected (Table 1), it is further shown the stationary and transient moisture circulations are responsible for the anomalous moisture convergence over Siberia (Fig. 11). In the spring, anomalous moisture convergence is closely connected with the stationary moisture transport through the western boundary, which is related to the northwesterly steering over the western part of the local anomalous cyclone over Siberia (Fig. 11a). The moisture seems to be carried from the adjacent regions west of Siberia, where weak moisture divergence is identified. In the following summer, the local anomalous cyclone becomes much stronger, which is considered to be part of a teleconnection pattern propagating from southwest Europe to Northeast Asia (Fig. 11c). This teleconnection pattern has anticyclonic centers over western Europe and Northeast Asia and cyclonic ones over Spain and Siberia. In this case, two moisture transport routines are identified: one is westerly moisture transport, which brings in abundant moisture from the northern part of Russia along the Kara Sea coast, and the other is the southwesterly moisture transport connected with the anticyclonic moisture circulation over Northeast Asia, which carries the moisture over this region northward to Siberia. The anomalous circulation in autumn is similar to that in summer, except for weaker strength and the northward shift of the related teleconnection pattern (Fig. 11e). In autumn, most of the moisture transported into Siberia is from the Barents–Kara Sea, based on the significant moisture divergence within this region. In winter, the corresponding moisture circulation also presents a wavelike pattern, with the anticyclonic center over Spain and the cyclonic one over the Barents–Kara Sea (Fig. 11g). The area with the most significant moisture divergence shifts eastward, compared to that in autumn (Fig. 11e).

Table 1.

Wet and dry years for each season over Siberia and Northeast Asia. Wet (dry) years are defined as the period when the standardized regional mean moisture convergence is larger (smaller) than 1 (−1).

Wet and dry years for each season over Siberia and Northeast Asia. Wet (dry) years are defined as the period when the standardized regional mean moisture convergence is larger (smaller) than 1 (−1).
Wet and dry years for each season over Siberia and Northeast Asia. Wet (dry) years are defined as the period when the standardized regional mean moisture convergence is larger (smaller) than 1 (−1).
Fig. 11.

The composite differences in stationary water vapor flux (vectors; kg m−1 s−1) and its divergence (shading; 10−5 kg m−2 s−1) between wet and dry years over Siberia in (a) spring, (c) summer, (e) autumn, and (g) winter. (b),(d),(f),(h) As in (a),(c),(e),(g), but for the transient water vapor flux and its divergence. The dotted areas represent the differences of the water vapor divergences significant at the 95% confidence level based on the Student’s t test.

Fig. 11.

The composite differences in stationary water vapor flux (vectors; kg m−1 s−1) and its divergence (shading; 10−5 kg m−2 s−1) between wet and dry years over Siberia in (a) spring, (c) summer, (e) autumn, and (g) winter. (b),(d),(f),(h) As in (a),(c),(e),(g), but for the transient water vapor flux and its divergence. The dotted areas represent the differences of the water vapor divergences significant at the 95% confidence level based on the Student’s t test.

In terms of the situation over Northeast Asia, the stationary moisture transport responsible for the anomalous moisture convergence in the spring is associated with a teleconnection pattern, where the anticyclonic centers are located over the region north of the Caspian Sea and the cyclonic ones are over western Europe and Northeast Asia (Fig. 12a). The cyclonic moisture circulation over Northeast Asia carries the moisture within Siberia and the region northwest of Northeast Asia into Northeast Asia. During the summer, the anomalous moisture circulation resembles that which was identified over Siberia in the summer, with cyclonic centers over western Europe and Northeast Asia and anticyclonic ones over the eastern Atlantic and Siberia (Fig. 12c). The anticyclonic circulation over Siberia transports moisture within Siberia into Northeast Asia through the northern boundary, with the cyclonic circulation over Northeast Asia being favorable for moisture input from southwest Mongolia. In the following autumn and winter, the cyclonic center still exists over Northeast Asia with much weaker strength (Figs. 12e,g), transporting the moisture from Siberia into Northeast Asia. It is important to note that the teleconnection pattern identified in summer over Siberia and Northeast Asia plays a crucial role on anomalous moisture convergence over both regions by transporting moisture over one region to the other. Iwao and Takahashi (2006) have also stated the dominant role of this teleconnection pattern on the seesaw pattern of summer precipitation between Siberia and Northeast Asia.

Fig. 12.

As in Fig. 11, but for Northeast Asia.

Fig. 12.

As in Fig. 11, but for Northeast Asia.

As for the transient moisture circulation responsible for anomalous moisture convergence over Siberia, the spring and summer anomalous east wind implies the decreased moisture carried by westerlies, causing anomalous moisture convergence over Siberia (Figs. 11b,d). In the autumn and winter, no significant signals are noticed (Figs. 11f,h). For Northeast Asia, the transient moisture circulation also contributes little to the moisture supply, based on the insignificant signals over the northeast during all the seasons (Figs. 12b,d,f,h). These results indicate the dominant role of the stationary moisture transport on the anomalous moisture supply over both Siberia and Northeast Asia.

4. Summary and discussion

Enlightened by the seesaw pattern in the summer precipitation between Siberia and Northeast Asia, this study investigated the features of moisture supply over these two regions to examine their similarities and differences. Based on the REOF analysis on the SPEI_03, definitions of Siberia and Northeast Asia are proposed, which are in accordance with the division in the study of Iwao and Takahashi (2008). At the beginning, we explored the monthly evolution of regional-averaged evaporation, moisture convergence, and precipitation, demonstrating the dominant role of evaporation on the precipitation over Siberia and Northeast Asia, with a limited influence of moisture convergence. However, for the interannual time-scale variability, moisture convergence is suggested to contribute the most to precipitation, instead of evaporation.

The stationary and transient moisture transports are mainly investigated over the two regions. The seasonal mean of stationary moisture transport shows net moisture convergence in the spring, autumn, and winter and moisture divergence in the summer over Siberia. For Northeast Asia, net stationary moisture divergence exists for the whole year. On the other hand, the transient term enhances the impacts of the stationary term on the net moisture supply over Siberia, while offsetting the role of the stationary term on the moisture supply over Northeast Asia. Hence, it is inferred that for an annual cycle, the net moisture supply over both Siberia and Northeast Asia are subject to the combined effects of the stationary and transient moisture transports. However, at the interannual time scale, only the stationary term is closely connected with the net moisture supply over both Siberia and Northeast Asia.

The stationary and transient moisture transported through each boundary is further analyzed. In terms of the annual cycle, for both regions, the stationary moisture transport through the western and eastern boundary is considered to be the most important moisture input and output, respectively. In spite of their large magnitude, their counteraction effect leads to a relatively small amount of the net zonal moisture transport, with the magnitude similar to that of the net meridional one. The monthly evolution of the net stationary moisture transport accords with that of both the zonal and meridional terms over Siberia, indicating the equally important roles of the two terms. In case of situations over Northeast Asia, the net stationary moisture transport is dominated by the meridional term during the first half year, but the zonal term in the second half. Therefore, though the significant role of the westerlies on moisture supply is shown in the seasonal mean, not only the zonal but also the meridional moisture transport play key roles in the net stationary moisture transport for the annual cycle in Siberia and Northeast Asia. On the other hand, the net transient moisture input mainly depends on the western and southern boundary moisture transport, while the output is under control of the northern boundary moisture transport. In spite of the weaker transient moisture transport through each boundary than the corresponding stationary ones, the magnitude of the net transient moisture convergence is close to that of the stationary one, indicating that the net moisture supply over Siberia and Northeast Asia is governed by both the stationary and transient moisture transport for the annual cycle.

The stationary and transient moisture circulations responsible for anomalous moisture convergence are then investigated. The results showed that for the stationary part, the anomalous moisture convergence over Siberia is always connected with a local cyclonic moisture circulation, which carries moisture from the adjacent regions to Siberia. In particular, the significant cyclonic moisture circulation in the summer is part of a wavelike teleconnection pattern propagating from southwest Europe to Northeast Asia. On the other hand, for situations over Northeast Asia, the anomalous moisture circulation mainly transports the moisture from Siberia and the region northwest of Mongolia into Northeast Asia. It should be noted that the corresponding summer moisture circulation presents a wavelike teleconnection pattern similar to that found for Siberia, indicating its crucial role in anomalous moisture transportation over both Siberia and Northeast Asia. For the related transient moisture circulation, it plays only a limited role in the net moisture convergence over these two regions, confirming the dominant role of the stationary moisture transport on the moisture supply anomalies over both Siberia and Northeast Asia.

In this paper, we mainly investigated the moisture budget in terms of its annual cycle and interannual time scale over Siberia and Northeast Asia. Recently, several studies have mentioned the interdecadal change of precipitation over Northeast Asia (Liu et al. 2011; Piao et al. 2017; Zhu et al. 2011). As the moisture supply is closely related to the precipitation variation of this region, does the moisture transport contribute to the interdecadal change, and what role does it play in the interdecadal change? In consideration of this, more work needs to be completed in the future to better understand the relationship between moisture supply and precipitation change.

Acknowledgments

We thank the three anonymous reviewers for their constructive suggestions and comments, which helped to improve the paper. This study is supported jointly by the National Natural Science Foundation of China (Grants 41721004, 41711530029, and 41461144001), the Chinese Academy of Sciences “The Belt and Road Initiatives” Program on International Cooperation: Climate Change Research and Observation Project (134111KYSB20160010), and the Swedish Foundation for International Cooperation in Research and Higher Education (STINT; CH2016-6711). The authors declare that they have no conflict of interest.

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Footnotes

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