1. Introduction
The Tibetan Plateau (TP), regarded as the “Asian Water Tower,” owns abundant freshwater sources, including a number of glaciers, which are crucial to the downstream socioeconomic lives. The Southeast Tibetan Plateau (SETP) is a major glacier region (Yao et al. 2012; Yang et al. 2016; Farinotti et al. 2019), where precipitation is dominantly controlled by the South Asian summer monsoon (SASM). Recently, the glaciers in this region have been shrinking considerably (Yang et al. 2013; Yao et al. 2010, 2012), ascribing to the increasing temperature and decreasing precipitation in the wet season (June–September) (Jouberton et al. 2022; Yang et al. 2016; Zhu et al. 2018). However, both field measurements and glacier mass balance simulations show that some of these glaciers are mainly accumulated in early spring, in which season precipitation mostly falls as snow due to the low air temperature (Maussion et al. 2014; Shi and Liu 2000; Yang et al. 2013). Thus, the variability of early spring precipitation in the SETP plays a vital role in the local glacier balance.
Previous studies (Lu et al. 2008; Ouyang et al. 2020; Ren et al. 2017; Yang et al. 2013) have shown that precipitation in the SETP is characterized by a bimodal seasonal variation with peaks in spring and summer, where spring precipitation even dominates the annual precipitation in some areas of this region, such as Zayu, Bomi, and Gongshan. Some glaciers in these areas are also characterized as the “spring-accumulation type” glaciers (Yang et al. 2013). This spring peak may be related to the subtropical westerlies, where the upper-layer cold air brought by the subtropical westerlies during spring superimposes on the lower-layer warm air over the SETP to form intense convective precipitation (Fujinami and Yasunari 2001; Toumi and Qie 2004). This bimodal feature is distinct from other monsoon-impacted TP areas, which indicates the complexity of precipitation in the SETP.
However, moisture sources and processes of spring precipitation in the SETP remain unclear. Lu et al. (2008) demonstrated that moisture of spring precipitation in the SETP is transported by the south branch of the subtropical westerlies from a far-field moisture source, i.e., the northern Arabian Sea. However, Ouyang et al. (2020) suggested that a near-field moisture source, i.e., the Bay of Bengal, may be a contributor to spring precipitation in the SETP led by the southwesterly winds near the surface. These may imply that there are multiple moisture sources for spring precipitation in the SETP. It is worth noting that the above analysis of Lu et al. (2008) took the 3 months of spring as a whole and did not consider the possible transition of the spring atmospheric circulation, while the latter study of Ouyang et al. (2020) only presented the statistical analysis of the atmospheric circulation without tracking the moisture sources. Furthermore, the capability of the moisture transport carrier is critical to the variation of precipitation in the TP. For example, the increased summer precipitation over the inner TP is due to more water vapor intrusion from the Arabian Sea when the subtropical westerlies weakened and migrated northward (Sun et al. 2020), and the variation of precipitation in the TP interior is mainly driven by the subtropical westerlies (Cui et al. 2021). These motivate us to clarify the moisture sources of spring precipitation in the SETP and their variability.
Moisture sources of spring precipitation may be tracked by Lagrangian or Eulerian models. Among them, a posteriori Eulerian tracking model, termed Water Accounting Model-2layers (WAM-2layers), has been widely applied to investigate the changes in precipitation in different areas of the TP. For example, by using the WAM-2layers, it is found that the increased precipitation in the central-western TP is mainly due to the enhanced water vapor transport from the Indian Ocean (Y. Li et al. 2019; Zhang et al. 2017a). And the decreased summer precipitation in the southeast of the TP is due to weakened moisture supply from the Indian Ocean (Zhang 2020; Zhang et al. 2017b). By using WAM-2layers, differences in summer precipitation trends between the northern and southern TP were revealed, which were attributed to the moisture change induced by the Asian monsoon (Zhang et al. 2019).
In this study, we investigate the changes in early spring precipitation in the SETP in terms of moisture sources by employing the WAM-2layers and further reveal its corresponding physical mechanisms. The outline of this paper is as follows. The data, study area, and methods used in this study, including the brief introduction of the WAM-2layers, are described in section 2. In section 3, the decadal change in early spring precipitation in the SETP and its physical mechanisms are investigated. Discussion about the belt impact of the weakened subtropical westerlies on precipitation in the midlatitude and the role of the subtropical westerlies in the interannual variability of early precipitation in the SETP is in section 4. Concluding remarks are given in section 5.
2. Data and methods
a. Data and study area
Daily precipitation from the Chinese Meteorological Administration (CMA) is adopted to investigate the variabilities of spring precipitation in the SETP and examine the performance of reanalysis precipitation datasets. Specifically, precipitation data collected from 12 weather stations in the SETP are used in this study, with their locations highlighted as black dots in Fig. 1a. The station data are homogenized, covering the period from 1979 to 2017.
(a) The distribution of weather stations in the SETP (27°–30°N, 92°–100°E), with the background color indicating the altitude. (b) The seasonal variation of precipitation averaged over the 12 station observations (OBS) and the grids collocated with the stations and the area of the SETP obtained from ERA5. The climatological monthly precipitation (shaded; mm day−1) and wind (vectors; m s−1) at 700 hPa were obtained from ERA5 during 1979 to 2017 in (c) February, (d) March, and (e) April. The black line is the contour of 3000 m above sea level. The red box represents the area of the SETP.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
The atmospheric reanalysis datasets obtained from the fifth-generation European Center for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate (ERA5; Hersbach et al. 2023) are adopted as input variables in the WAM-2layers, including 3-hourly precipitation and evaporation, and 6-hourly wind velocity, specific humidity in 23 pressure levels (200–1000 hPa), surface pressure, and a set of vertically integrated moisture and flux variables (i.e., vertically integrated meridional/zonal water fluxes). These datasets are on a grid of 1° × 1° from 1979 to 2017.
The study area of SETP is mainly within the area of (27°–30°N, 92°–100°E). A spring peak in the annual variation of precipitation in the SETP is presented by both station observations and ERA5 (Fig. 1b). From February to April, the control area of the subtropical westerlies elongates along the midlatitude region (Figs. 1c–e).
Monthly snow-cover extent (SCE) from 1979 to 2017 is obtained from the National Oceanic and Atmospheric Administration (NOAA) snow chart climate data record (Robinson and Estilow 2012). The data are based on the North Hemisphere (NH) polar stereographic projection. Monthly snow cover from the ERA5 is also applied.
Monthly precipitation data from Global Precipitation Climatology Project (GPCP) are also used to see the change of precipitation on a grid of 1° × 1° from 1979 to 2017.
b. Methods
Despite the fact that the WAM-2layers is based on a well-mixed assumption, its result of achieving primary moisture source is comparable to that of a highly accurate 3D water tracking (Knoche and Kunstmann 2013) but with greater calculation efficiency (van der Ent et al. 2013).
In this study, the key output from the WAM-2layers is the tracked evaporation that is used to define the moisture sources of precipitation over the study area. The basic algorithm for moisture backtracking is briefly described as follows.
In each grid column, the tagged water, indicating that the fallen precipitation over the study area returns to the air, is well mixed with the precipitable water at both the bottom and top layers. Since the water vapor flows backward, the tagged water also flows with it to trace the evaporative source regions. Here, a well-mixed atmosphere in a grid is represented by the mixed ratio, indicating that the evaporation from the source regions against the total evaporation in this grid is equal to the corresponding precipitable water against the total precipitable water. If the amount of evaporation is E0 in the grid at the bottom layer and the mixed ratio is γ, it will be E0 × γ amount of evaporation contributing to the precipitation in the study area (i.e., moisture contribution from the moisture sources), and leaves (P0 − E0) × γ amount of tagged water in the air, where P0 represents the amount of precipitation in this grid. This tracing process ends with the depletion of tagged water in the air (van der Ent et al. 2013).
After comparing the mandatory pressure levels in ERA5 with pd, the nearest mandatory pressure level is the division between the upper and bottom layers.
The Mann–Kendall (MK) test and t test are employed to verify the decadal precipitation change in the SETP during early spring.
3. Results
a. The decadal change of spring precipitation in the SETP
Figure 2 shows the time series of early spring precipitation in the SETP obtained from station observations during the period 1979–2017. In March, precipitation in the SETP had an abrupt decadal shift in 1999, decreasing from 2.8 mm day−1 during 1979–98 to 1.6 mm day−1 during 1999–2017 (Fig. 2b). This decadal shift can also be reflected by the MK test and exceeds the significance test of p < 0.05. The decadal change in precipitation in the SETP in February is hardly detected (Figs. 2a,d). In April, the MK test shows an abrupt point of precipitation in 1992 (Fig. 2f), but it does not exceed the significance test of p < 0.05.
The time series of precipitation in the SETP during the period of 1979–2017 in (a) February, (b) March, and (c) April and (d)–(f) their corresponding MK test obtained from the station observations. The gray line represents the means of 1979–98 and 1999–2017. The black dashed lines in the MK test indicate the significance test of p < 0.05. UF (red line) and UB (blue line) in the MK test indicate the progressive and retrograde series.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
The decadal change in precipitation in the SETP in early spring can also be reproduced by ERA5, with a significant and abrupt decrease in March (Fig. 3). Actually, it has been proven that although the amount of precipitation in ERA5 is larger than that in station observations, the variability of precipitation in the TP can be successfully captured by ERA5 (Yuan et al. 2021). Thus, adopting ERA5 to further investigate the decadal change in March precipitation in the SETP is convincing.
As in Fig. 2, but precipitation obtained from ERA5 averaged over the SETP (27°–30°N, 92°E–100°E).
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
b. Change in moisture sources of March precipitation associated with westerlies
As the decadal change in precipitation in February and April is relatively weak, we focus on the track of moisture sources of precipitation in March. Here, we use the WAM-2layers to trace the primary moisture sources. The traced results are shown in Fig. 4a, in which the gray line delineates the areas with the moisture contribution greater than 1 mm month−1 for precipitation in March. These areas within the gray line are defined as the primary moisture sources, contributing 80% of the total moisture to March precipitation in the SETP. Based on the geographical position, we define the primary moisture sources in the west of 70°E as the far-field sources, which are dominated by the subtropical westerlies, and the east of 70°E as the near-field, which are driven by local evaporation and relevant atmospheric circulations. The moisture contribution differences in the SETP between 1999–2017 and 1979–98 in March is shown in Fig. 4b, which exhibits a contrast mode with a decrease in the west of 70°E, i.e., the far-field sources, and an increase in the east of 70°E, i.e., the near-field sources. Accordingly, the decreased March precipitation in the SETP is due to the reduction of moisture contribution from the far-field sources. It is worth mentioning that these results of the moisture tracking can also be observed by using ERA-Interim datasets on a grid of 1.5° × 1.5° as the input data (figures are in the online supplemental material).
The distribution of climatological moisture contribution (unit: mm month−1) to (a) the March precipitation in the SETP and (b) the difference between 1999–2017 and 1979–98. The gray solid line delineates the areas with a moisture contribution greater than 1 mm month−1. The black dashed line in (b) denotes 70°E. The red box represents the SETP, and the dots in (b) denotes that the difference pass the significance test of p < 0.1.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
Since the change of moisture contribution is affected by the capability of moisture carrier and the amount of evaporative sources (Keys et al. 2012; Zhang et al. 2019), the variation of atmospheric circulation and surface condition is further explored. Figure 5 exhibits distributions of the mean difference between 1999–2017 and 1979–98 in moisture transport, wind at 700 hPa and surface evaporation. In March, the distribution of evaporation difference only presents a remarkable decrease over the central Asia (Fig. 5b). In contrast, impressive easterly wind anomalies prevailed along the midlatitude region (Fig. 5a), indicating that the westerlies got weaker and its capability of moisture transport was strongly weakened after 1999. Thus, the decreased March precipitation in the SETP is mainly attributed to the weakened subtropical westerlies.
(a) The differences in the mean moisture transport [vectors; unit: g (cm s hPa)−1] and zonal wind (shaded; unit: m s−1) at 700 hPa and (b) the differences in surface evaporation (unit: mm month−1) between 1999–2017 and 1979–98 in March. The brown box represents the SETP, and the black dashed line in (b) delineates 70°E. TP is masked at 700 hPa, and only the differences passing the significance test of p < 0.1 are presented. The data source is ERA5.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
To see the decrease of the westerlies clearly, we defined a westerlies index (WI) as the standardized zonal wind at 700 hPa (the subtropical westerlies) and 200 hPa (the subtropical jet) averaged in the core area of (25°–30°N, 55°–65°E) to verify the decadal change in the westerlies. Here, the subtropical jet and the subtropical westerlies share the same area due to their same location along (20°–30°N) in March (Schiemann et al. 2009). Since 1999, both the subtropical jet and the subtropical westerlies have experienced a decrease, which can be detected in their MK test (Figs. 6b,c). These weakened westerlies brought less moisture from the far-field sources to the SETP. In the following analysis, we only use the subtropical WI (700 hPa) due to much more moisture transport in the lower layers.
(a) Time series of the WI at 700 (red line) and 200 hPa (blue line) in March and (b),(c) their MK test. The black line indicates the year 1999. The black dashed lines in the MK test indicate the significance test of p < 0.05. UF (red line) and UB (blue line) in the MK test indicate the progressive and retrograde series.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
c. Physical processes of subtropical westerlies weakening
Snow cover, as a potential indicator for subseasonal to seasonal prediction (Jeong et al. 2013; F. Li et al. 2019; Orsolini et al. 2013), can alter the air thermal conditions through an instantaneous albedo effect (Cohen and Entekhabi 1999; Dickson 1984). This albedo effect depends on the intensity of the solar radiation and thus will be amplified from winter to spring. As Kim et al. (2013) indicated that SCE in eastern Europe has an abrupt shift in the late 1990s during early spring due to air warming, and Li et al. (2021, 2020, 2018) proved that SCE over the TP can affect the upper-level westerlies, SCE in midlatitude Eurasia thereby is analyzed to see its role in March. The distribution of SCE difference between 1999–2017 and 1979–98 averaged over the (30°–80°E) is presented in Fig. 7. From February to April, the decadal reduction in SCE in midlatitude Eurasia is observed in both ERA5 and NOAA. In February, SCE experienced a decrease in the south of 45°N. In March, SCE rapidly reduced in midlatitude Eurasia (north of 45°N). In April, the reduced SCE moved northward to the circumpolar area. Thus, the reduced SCE in midlatitude Eurasia may have caused a warming belt that moved from south to north.
The distributions of monthly early spring SCE difference between 1999–2017 and 1979–98 obtained from (a)–(c) NOAA and (d)–(f) ERA5. Dots denote the difference passing the significance test of p < 0.1.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
To see the thermal effect of SCE reduction, Fig. 8 shows the differences of surface net solar radiation (SSR) and sensible heat flux (SHF) between 1999–2017 and 1979–98 in the areas that SCE reduced. In response to the reduction of the SCE, increased SSR can be detected from February to April (Figs. 8a–c). Consequently, the corresponding SHF increased (Figs. 8d–f). Specifically, anomalous surface heating was weaker in February. With the increasing solar angle in March, more significant surface heating anomalies occupied midlatitude Eurasia. In April, the center of anomalous surface heating was in northern Eurasia.
The distributions of monthly early spring (a)–(c) surface net solar radiation (SSR) and (d)–(f) sensible heat flux (SHF) difference between 1999–2017 and 1979–98 obtained from ERA5. Dots denote the difference passing the significance test of p < 0.1.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
The anomalous surface heating caused by the SCE reduction in midlatitude Eurasia may lead to a change in the subtropical westerlies. To prove this hypothesis, Fig. 9 depicts the vertical slices of air temperature, geopotential height, and zonal wind difference averaged over the (30°–80°E) between 1999–2017 and 1979–98. In February, anomalous air warming is observed in the midlatitude region (Fig. 9a), and the thermal adaption caused the upper-level geopotential height anomalies over the region of 30°N (Fig. 9b). As a result of geostrophic adjustment, there was an easterly anomaly in the south of 30°N, and thus the subtropical westerlies were weakened (Fig. 9c). However, these weakened subtropical westerlies prevailed along the latitudinal 20°N belt, which is too far to the SETP, explaining why there is no significant decadal change in precipitation in the SETP in February. As the solar angle increased in March, the anomalous air warming shifted northward and was intensified (Fig. 9d), contributing to a strongly anomalous high pressure over the region of 40°N (Fig. 9e). In the south of this anomalous high, the subtropical westerlies were weakened due to the geostrophic adjustment (Fig. 9f), which brought less moisture from the far-field sources to the SETP. In April, an anomalous air warming centered in northern Eurasia (Fig. 9g), with little effect on the subtropical westerlies (Fig. 9i).
Latitude–height profiles of air temperature (units: K), geopotential height (units: m), and zonal wind (units: m s−1) difference averaged over the (30°–80°E) between 1999–2017 and 1979–98 in (a)–(c) February, (d)–(f) March and (g)–(i) April. Shaded areas are the difference passing significance test of p < 0.1. The data source is ERA5.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
Figure 10 summarizes the physical processes described above. SCE in the midlatitude Eurasia has prominently decreased since 1999. With the increasing solar angle in March, the air warming was amplified through snow albedo–radiation feedback and extended upward. According to the theory of thermal adaption, an anomalous high was formed over the midlatitude, which caused an easterly anomaly in its south through geostrophic adjustment, thus retarding the subtropical westerlies along the midlatitude. As a result, less moisture from the far-field sources was brought to the SETP, leading to decreasing precipitation.
Schematic diagram of the influence of the midlatitude SCE on the decadal decrease of March precipitation in the SETP. The dark blue shaded base is the distribution of SCE difference between 1999–2017 and 1979–98. The gray and cyan shaded bases indicate continent and ocean, respectively.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
4. Discussion
a. Decreased precipitation along midlatitudes in March
The subtropical westerlies prevail along the area of (20°–30°E), where residences some areas with high terrain. In principle, the weakened subtropical westerlies should have caused a decadal decrease in precipitation over the upwind side of mountains along the midlatitudes. Figure 11 shows the distribution of precipitation difference in March between 1999–2017 and 1979–98 obtained from ERA5 and GPCP. As expected, a significant decadal decrease in precipitation can be observed over the windward slopes of the Zagros and the Himalaya mountains. Thus, the impact of the weakened subtropical westerlies induced by the reduced SCE in midlatitude Eurasia have caused the decadal decrease in precipitation in the major mountains along the latitudinal 30°N belt, including the SETP.
Distribution of the precipitation difference in March between 1999–2017 and 1979–98 obtained from ERA5 and GPCP. Dots indicate the difference passing the significance test of p < 0.1.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0770.1
b. Decadal change in the relationship between the subtropical westerlies and precipitation
Table 1 presents the interannual correlation coefficients (R) of precipitation in the SETP with WI (700 hPa) in March during 1979–98 and 1999–2017. Before 1999, the subtropical westerlies dominated the interannual variability of precipitation by transporting moisture from the far-field moisture to the SETP in March, with R values above 0.6 at the significance level of p < 0.05 for precipitation data obtained from either station observations or ERA5. In other words, the stronger the westerly winds are, the more March precipitation is in the SETP during 1979–98. However, the dominant role of the subtropical westerlies in the interannual variability of precipitation in the SETP has become much weaker and even negative since 1999.
Correlation coefficients (R) of precipitation with the WI in March during the periods of 1999–2017 and 1979–98. The precipitation data are obtained from station observation (OBS) and ERA5.
Thus, the reduced SCE in midlatitude Eurasia not only results in a decadal decrease in precipitation over the windward slopes of high mountains but also breaks the interannual relationship between the subtropical westerlies and precipitation in the SETP. Clearly, there is a need to explore why this relationship got broken, but it is beyond the scope of this study.
5. Concluding remarks
This study shows that the decadal change in early spring precipitation in the SETP features a striking decrease in March after 1999, which may severely threaten the local glacier accumulation.
To investigate this decadal decrease, we adopt an Eulerian moisture backtrack model (WAM-2layers) to trace the moisture sources of March precipitation in the SETP. Climatologically, the primary moisture sources for precipitation in the SETP can be separated by the longitude of 70°E into the far-field and the near-field moisture sources. It is found that the moisture contribution from the near-field sources has increased at a decadal scale since 1999, whereas the moisture contribution from the far-field sources has decreased. So, it is the far-field moisture transport that caused the decrease in March precipitation in the SETP.
The declined far-field moisture contribution in March is probably attributed to the weakened subtropical westerlies induced by the reduced SCE in midlatitude Eurasia. SCE has suffered a remarkable reduction in midlatitude Eurasia in early spring, causing anomalous air warming through snow albedo–radiation feedback. According to the theory of thermal adaption, an anomalous high in the mid- to upper troposphere was formed. This anomalous high led to an anomalous easterly wind in its south through geostrophic adjustment. As a result, the subtropical westerlies were weakened, causing less moisture transport upstream. With the advance of spring (and thus increased solar radiation), the weakening belt of the subtropical westerlies shifted from south to north. In March, the weakening belt moved to the latitude of about 30°N, leading to a decadal decrease in precipitation on mountains’ windward slopes along the latitudinal belt. The decrease in the SETP is part of this change. Moreover, the positive relationship between the subtropical westerlies and March precipitation in the SETP has been disrupted by the SCE reduction in midlatitude Eurasia since 1999.
The decadal decrease in March precipitation in the SETP may have reduced springtime snow accumulation in this region, contributing to the glacial shrinkage. If the reduction trend of the SCE in midlatitude Eurasia cannot be reversed, March precipitation may remain low. In addition, previous studies (Bollasina et al. 2013; Kajikawa et al. 2012; Liu et al. 2019; Xiang and Wang 2013; W. Zhang et al. 2017) have shown that May precipitation in the SETP experienced an increase due to the advanced onset of the South Asian summer monsoon. Therefore, there has been a distinct intraseasonal variation in spring precipitation in the SETP, which may lead to the disappearance of spring precipitation peak in this region in the future.
Acknowledgments.
The authors thank three anonymous reviewers for their constructive comments, which helped to substantially improve the manuscript. This work was supported by Strategic Priority Research Program of Chinese Academy of Sciences (Grant XDA2006010201) and National Science Foundation of China (Grant 41905087).
Data availability statement.
The reanalysis dataset used in this study us available in the European Centre for Medium-Range Weather Forecasts (ECMWF, https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5) (Hersbach et al. 2023) and the station observations are provided by the National Meteorological Information Center.
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