1. Introduction
Drought ranks as one of the most influential and damaging disasters in the world (Wilhite 2000; Zhang 2005). The global annual economic losses caused by drought during 1980–2009 were $17.3 billion, and the losses reached $23.1 billion from 2010 to 2017 (Wilhite 2000; Buda et al. 2018). China is heavily affected by drought. With substantial changes in affected areas regarding the frequencies and intensities of drought under the background of global warming, increasingly severe impacts on the economy, society, and people in China have been reported (Fu 1994; Zhai et al. 2010; Dai 2013; Qin et al. 2014; Wang et al. 2016). Since the 1970s, China’s average annual drought-affected area has been 2.09 × 107 hm2, with the annual losses in grain production ranging from several million tons to over 30 million tons and the annual direct economic losses reaching $6.5 billion (Buda et al. 2018). Due to its great social and economic impacts, drought has long been a hot topic in the meteorological community worldwide (Nicholls 1985; 2004; Bradley et al. 1987; Hulme 1996; Cook et al. 1999; Nicholson et al. 2000; Mishra and Singh 2010; Sheffield et al. 2012; Estrela and Vargas 2012; Montaseri and Amirataee 2017; Qian et al. 2017a,b). Particular focus is given to the influential factors and possible mechanisms referring to the climatic variability of drought to provide a deeper understanding and better disaster prevention and mitigation plans.
Drought most frequently hit Northwest China, North China, Northeast China, Southwest China, and South China (Zhang et al. 2012; Zhang and Zhou 2015; Zhang et al. 2020). Because it is located in the inland region of the Eurasian continent, Northwest China is rarely reached by warm and moist oceanic airflows. The local precipitation is mainly affected by the westerly zone (Wu and Qian 1996; Qian and Zhu 2001; Zhang 2009). Moreover, the dynamic and thermal effects of the Tibetan Plateau greatly contribute to the formation of the arid and semiarid climate over Northwest China (Ye and Gao 1979; Xu and Zhang 1983; Zhang 2009). However, eastern China belongs to the East Asian monsoon regime, where wet and dry conditions are dominated by variability in the East Asian monsoon system (Tao and Chen 1987; Chang et al. 2000; Ding and Chan 2005). With the stepwise northward shift of the northwestern Pacific subtropical high during summer, active and break precipitation covers different regions from South China to Northeast China and affects the occurrence of drought and flooding (Zhao 1999; Zhou and Yu 2005). Located on the edge of the East Asian monsoon regime, eastern Northwest China is affected by a combination of the westerly system and East Asian monsoon (Chen et al. 2010; H. Zhang et al. 2016; Xing and Wang 2017; Liu et al. 2018). Due to the diversity of climate types and influential factors across China, drought is widespread in China and occurs in any season. Moreover, the factors and mechanisms related to the occurrence and climate variability of drought in China are complicated and not completely clear. This research tried to shed light on the interdecadal variation in the days with drought of China.
The characteristics and influential factors of drought, as well as the mechanisms related to interdecadal variations in drought across China, are different among varying regions and seasons. Since the mid- to late 1970s, the frequencies and intensities of drought events in North China have increased significantly (Ma and Fu 2003; 2006; Li et al. 2015). The interdecadal weakening of the East Asian summer monsoon is generally believed to be a major contributor to this increase. As the weakening of the monsoon resulted in the interdecadal southward shift of the East Asian summer monsoon rain belt, precipitation has decreased greatly in North China (Huang et al. 1999; Chang et al. 2000; Yang and Lau 2004; Ding et al. 2009). The Pacific decadal oscillation (PDO) has also exerted great impacts on drought in North China, as its warm phase corresponds to high temperatures and less-than-normal precipitation levels in situ (Yang et al. 2005; Ma 2007; Li et al. 2010; Qian and Zhou 2014). Moreover, the PDO was found to dominate the summer drought frequency over eastern China from the 1960s to early 1990s, but the impacts from the Atlantic multidecadal oscillation (AMO) subsequently increased (Qian et al. 2014). Autumn drought in Southwest China strengthened after the mid-1990s, and the sea surface temperature (SST) from the tropical eastern Indian Ocean to the tropical western Pacific played an important role by affecting the location and intensity of the northwestern Pacific subtropical high (G. Zhang et al. 2016). Heavier autumn drought in South China was observed after the late 1980s, which can possibly be attributed to the heat content in the tropical Indian Ocean (Zeng and Gao 2017). However, the warm and dry climate in western Northwest China transferred to the warm and moist state after the late 1980s (Shi et al. 2002). Although the interdecadal variability of the regional and seasonal drought has been discussed, the interdecadal variation in the annual number of days with drought over China is still unknown. Therefore, this research will reveal the spatial and temporal characteristics of the interdecadal variations in the annual number of days with drought over China, investigate its relationships with different influential factors, and discuss the possible mechanisms.
The remainder of this paper is organized as follows. The data and methods are introduced in section 2. The temporal and spatial characteristics of the interdecadal variation in the annual number of days with drought over China are explained in section 3. In section 4, the possible reasons for the interdecadal variation in the annual number of days with drought in China are discussed by investigating its relationship with temperature and precipitation, general circulation, and such large-scale factors as the PDO and AMO. Conclusions and discussion are presented in section 5.
2. Data and methods
Daily mean temperature and precipitation from 2419 meteorological stations in China from 1 January 1961 to 31 December 2019 are used to calculate the daily drought index. The distribution of the stations is shown in Fig. 1. The dataset is compiled by the National Meteorological Information Center of the China Meteorological Administration, with spatial consistency, temporal consistency, and internal consistency being checked and the suspicious records being adjusted (Cao et al. 2016). The dataset is accessible from http://data.cma.cn. From 1961 to 2019, the station numbers of this dataset increased stably from 2040 to 2419. To obtain more reliable climatic statistics, two more steps were conducted. First, the years with total missing records equal to or more than 20% were removed for a single station. Second, the stations with consecutive records of less than 30 years were excluded. Then, the data from 2265 stations were adopted in this analysis. The Cressman objective analysis is performed on the station data to get the grid interpolation, with the spatial resolution being 0.5° × 0.5° grids. And then an area average is obtained by the latitude weighed average of the grid.
Distribution of observatory stations used in this study (crosses) and the climatology (shading; days) of the annual number of days with drought based on the 90-day SPEI across China.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
The National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis dataset covering the same period is used to provide the circulation patterns related to drought in China (Kalnay et al. 1996). The spatial resolution consists of 2.5° × 2.5° grids.
The monthly PDO index is downloaded from the website of the National Oceanic and Atmospheric Administration (NOAA) at https://www.ncdc.noaa.gov/teleconnections/pdo/ (Mantua and Hare 2002). Following Trenberth and Shea (2006), the AMO index is defined as the detrended 10-yr low-pass filtered area-averaged SST anomalies over the North Atlantic basin (0°–65°N, 80°W–0°E). Then the monthly AMO index is calculated using monthly NOAA Extended Reconstructed Sea Surface Temperature (ERSST) V5 data (B. Y. Huang et al. 2017).
To monitor and assess drought quantitatively, various drought indices are defined. Some of the most popular indices include the Palmer drought severity index (PDSI) (Palmer 1965), standardized precipitation index (SPI) (McKee et al. 1993), standardized precipitation evapotranspiration index (SPEI) (Vicente-Serrano et al. 2010), and effective drought index (EDI) (Byun and Wilhite 1999). Evaluations of these different indices can be found in Heim (2000), Keyantash and Dracup (2002), Dai (2011), and Zhang and Zhou (2015). The SPEI is based on the difference between precipitation and evapotranspiration. It combines the simple calculation of the SPI with the PDSI’s sensitivity to changes in evaporation caused by temperature (Vicente-Serrano et al. 2011). In this study, the SPEI is used to identify days with drought in China.
The SPEI is a multiple time scale index. The 3-month SPEI data are broadly used to study the drought in China (Li et al. 2012a,b; Wang and Chen 2014; Zhou et al. 2014; G. Zhang et al. 2016; Zeng and Gao 2017; Olusola et al. 2017; Jia et al. 2018). On this time scale, drought has a major impact on agriculture (Potop et al. 2014). The 90-day SPEI (SPEI90) is equivalent to 3-month SPEI, and contains both short-term and medium- and long-term drought information. Therefore, the SPEI90 is adopted in this analysis. A drought day is identified when the SPEI90 is equal to or less than −0.5. As shown in Fig. 1, the annual number of days with drought is generally above 110 in China. More days with drought occur over most of northern China, eastern Southwest China, and western South China, about 130–170 days. It should be pointed out that changing the threshold from −0.5 to 0 will not change the results of this study.
3. Interdecadal variation in the annual number of days with drought
Figure 2a shows the annual number of days with drought averaged over China from 1961 to 2019. An obvious interdecadal shift is observed in the mid-1990s. The days with drought are mostly less than normal from the 1960s to the mid-1990s but turn to be more than normal afterward. The Mann‒Kendall test was performed to detect the breakpoint. As shown in Fig. 2b, the statistics UF and UB represent the changing trend of the annual number of days with drought and its reverse series, respectively. The two statistics intersect in 1996, indicating the breakpoint. Moreover, the moving t test also detected the significant breakpoint at the confidence level of 95% (figure not shown). Of note, the annual number of days with drought shows a significant upward trend from 1961 to 2019, and the interdecadal shift contributes greatly to this trend.
(a) Time series of the annual number of days with drought in China from 1961 to 2019 (the blue line with solid circles; days). The red dashed line indicates the interdecadal component, the black solid line presents the climatic mean, and the green dashed line shows the linear trend (days). (b) Mann–Kendall test for the annual number of days with drought in China from 1961 to 2019.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
Interestingly, the interdecadal transition is also obvious in the seasonal number of days with drought in China. As shown in Fig. 3, the number of days with drought increased significantly after the mid-1990s in spring, summer, and autumn. However, the number of days with drought in winter only shows some interdecadal fluctuations. The abrupt increase of the days with drought is detected in 1996 for spring and 1999 for summer. As for autumn, two significant breakpoints occurred in 1989 and 1999, indicating a continuous increase in days with drought. However, there is no breakpoint found in winter (Table 1). Moreover, the correlation analysis indicates that the summer number of days with drought has the highest correlation coefficient with the annual number of days with drought, at 0.95, and exceeds the confidence level of 99% (Table 1). The annual number of days with drought is 0.83 correlated to the autumn number of days with drought and 0.82 to the spring number of days with drought. But the correlation between the annual number of days with drought and the winter number of days with drought is 0.40, failing the reliability test at the 95% level. The significant increase of spring, summer, and autumn drought occurrence all contributes to the interdecadal shift of the annual number of days with drought in China.
Interdecadal components of the (a) spring (blue line), (b) summer (purple line), (c) autumn (orange line), (d) winter (yellow line), and annual (green dashed lines) number of days with drought (days) across China from 1961 to 2019.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
Correlations between the interdecadal variations in the annual number of days with drought in China and those in each season from 1961 to 2019 and the breakpoint of the seasonal numbers of days with drought as determined by the M-K test. Asterisks (*) denote exceeding the confidence level of 95%.
Figure 4 shows the distribution of the predominant mode (EOF1) of the annual number of days with drought and the evolution of the first principal component (PC1). EOF1 accounts for 21.2% of the total variance and is characterized by the opposite variation between most of China and the area comprising northern Northeast China and the central and eastern Tibetan Plateau. Moreover, a much greater magnitude is in the northern part of China than to the south of the Yangtze River (approximately 30°N). PC1 is highly similar to the China-averaged annual number of days with drought shown in Fig. 2a. Their correlation reaches 0.95 on the interannual time scale and 0.97 on the interdecadal time scale, exceeding the confidence level of 99%. This shows that the interdecadal shift in 1996 dominates the climatic variability in the annual number of days with drought in China.
(a) The first mode (EOF1) of the annual number of days with drought based on the 90-day SPEI in China. (b) The first principal component (PC1) of the EOF1 mode from 1961 to 2019 (the red solid line), with the green dashed line representing the interdecadal component.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
According to the breakpoint in 1996, the difference in the annual number of days with drought between two periods of 20 years each (1996–2015 minus 1976–95) is calculated. It should be noted that the selection of the time period does not change the result. For example, the difference between 1996–2019 and 1961–95 is highly similar to that between 1996–2015 and 1976–95. As shown in Fig. 5, the statistically significant increases in days with drought cover two regions. The one is a zonal belt from southern Xinjiang to southern Northeast China and North China, and the other is a meridional belt from eastern Northwest China to eastern Southwest China. The annual number of days with drought in the zonal belt (75°–125°E, 36.5°–45°N) is highly similar to the China-averaged number shown in Fig. 2a and the PC1 shown in Fig. 4b on the interdecadal time scale (Fig. 6a); the correlations reach 0.95 and 0.99, respectively. It shows that the interdecadal variation in the zonal belt dominates the climatic variation of the number of days with drought in China. In the meridional belt (102.5°–110°E, 22.5°–36.5°N), two significant breakpoints are detected in 1981 and 2001 and depict a continuous increase of days with drought (Fig. 6b). Interdecadal variations in the zonal and meridional belt are consistent, with the correlation being 0.64 and exceeding the confidence level of 95%. Severe drought hit North China in 1999, 2000, and 2010 (Wei et al. 2004, Shen et al. 2012). Severe drought in eastern Southwest China caused great economic losses and social impacts in 2006 (Peng et al. 2007). Heavy drought frequently occurred in Southwest China in 2005 and from 2009 to 2011 (Liu et al. 2006; Huang et al. 2012; Yang et al. 2012). These events also reflect the increase of drought after the mid-1990s from the perspective of extreme climate events. However, only slight and insignificant increases and decreases are observed over the “four corners” region comprising northern Xinjiang, Northeast China, central Southwest China, and southeastern China. Comparing with Fig. 1, it can be seen that drought-prone regions were hit by drought more frequently after the mid-1990s. Additionally, this pattern is also consistent with the distribution of the linear trend of the annual number of days with drought in China (figure not shown), suggesting the important role of the interdecadal shift on linear trends.
Differences in the annual number of days with drought in China based on the 90-day SPEI between the two periods of 1996–2015 and 1976–95 (shading; days). The crosses denote stations exceeding the confidence level of 95%. The blue frames indicate the zonal belt of 75°–125°E, 36.5°–45°N and the meridional belt of 102.5°–110°E, 22.5°–36.5°N, where the annual number of days with drought increased significantly.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
Interdecadal components of annual number of days with drought, surface temperature, and precipitation averaged over the (a) zonal belt and (b) meridional belt indicated in Fig. 5. The blue dashed line indicates the annual number of days with drought, the red line with solid circles shows temperature, and the green solid line presents precipitation.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
4. Possible reasons
SPEI is derived from temperature and precipitation. Circulation anomalies directly affect the weather and climate. And the PDO and AMO are two major interdecadal signals. Then, possible reasons for the interdecadal variation of the annual number of days with drought are discussed from these three aspects in this section.
a. Relationship with temperature and precipitation
High temperature exaggerates evaporation. Deficient precipitation reduces the water supply. Therefore, temperature and precipitation are taken as the direct influential factors of drought. Figure 6 shows the evolution of the annual number of days with drought, temperature, and precipitation in the zonal and meridional belt, respectively. In the zonal belt, the increase of days with drought accompanies the obvious warming, with the correlation coefficient being 0.83 and exceeding the confidence level of 99%. Warming temperature accelerates evapotranspiration and then contributes to the increase in the occurrence of drought. However, the precipitation is weakly related to the number of days with drought in the zonal belt, with the correlation being only −0.16.
In the meridional belt, warming is also evident after the mid-1990s. The evolutions of temperature and the number of days with drought are similar, with the correlation being 0.53 and exceeding the confidence level of 95%. Meanwhile, the interdecadal variation of precipitation is almost opposite to that of the number of days with drought. Their correlation reaches −0.79, exceeding the confidence level of 95%. Moreover, an abrupt decrease in precipitation is detected in 1992, corresponding to the interdecadal increase of days with drought. Overall, warming of temperature mainly contributes to the increase of days with drought in the zonal belt, while both the increase of temperature and the reduction of precipitation play important role in the meridional belt.
b. Related circulation anomalies
To clarify the circulation anomalies related to the interdecadal variation in the annual number of days with drought in China, regression analysis is conducted against the average number of days with drought in the zonal and meridional belt, respectively.
In the upper troposphere (Figs. 7a,e), a wave train stretches from the northwest to southeast, with negative centers over the North Atlantic, the Ural Mountains, and the subtropical northwestern Pacific and positive centers over western Europe and the Lake Baikal/Lake Balkhash area. This wave train suggests that the observed interdecadal variation in the annual number of days with drought in China is connected to the signal from the North Atlantic.
Regressions of (a),(e) 200-hPa meridional wind (m s−1), (b),(f) 500-hPa geopotential height (gpm), (c),(g) 850-hPa wind (m s−1), and (d),(h) 850-hPa vertical wind speed (10−3 m s−1; a negative value indicates ascending motion, and vice versa) against the annual number of days with drought in the (left) zonal and (right) meridional belt indicated in Fig. 5 on the interdecadal time scale from 1961 to 2019. The dots denote values exceeding the confidence level of 95%. The region higher than 1500 m is masked out.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
Along the westerly waveguide in the upper troposphere, a zonal wave train at the 500-hPa level is also visible, although generally positive geopotential height anomalies cover the whole region (Figs. 7b,f). The “low-west and high-east” pattern over mid-to-high-latitude Eurasia favors the zonal airflow and causes warm conditions in China. In particular, the positive geopotential height anomalies have greater magnitudes over northern China than to the south of the Yangtze River, providing more favorable conditions for drought occurrence in northern China.
Corresponding to the strong ridge in the mid- to high troposphere, a significant anomalous anticyclone controls the northern part of China, with the center located over Lake Baikal (Figs. 7c,g). Thus, in most parts of northern and central China, northerly anomalies prevail. The intensified northerly airflows, which are from the polar and high-latitude areas, lead the cold and dry air to move southward and then favor the occurrence of drought. By the impact of circulation anomalies at different levels, convection intensifies over the four corners area but weakens over the zonal and meridional belt (Figs. 7d,h). Active convection is favorable for the occurrence of precipitation, while the suppressed convection tends to cause a dry and warm condition. This pattern well corresponds to the interdecadal increase of the number of days with drought in the zonal and meridional belt and a slight decrease in the four corners area after the mid-1990s.
It can be easily noticed that the circulation regressions are highly similar against the number of days with drought averaged in the zonal and meridional belt. The spatial correlations of 200-hPa meridional wind, 500-hPa geopotential height, 850-hPa horizontal wind, and 850-hPa vertical wind in the zonal and meridional belt reach 0.71, 0.65, 0.84, 0.89, and 0.87, respectively. Therefore, the interdecadal increase of days with drought in the zonal and meridional belt is affected by similar circulation anomalies.
c. Relationship with the AMO and PDO
The interdecadal signals from different oceanic basins tend to cause circulation anomalies and subsequently affect regional climate variations (J. P. Huang et al. 2017). In recent years, the AMO has received much attention due to its near‐global scale and great impacts (Knight et al. 2006; Ting et al. 2011). The interdecadal component of the annual number of days with drought averaged over China, the zonal and meridional belt are all highly correlated to the AMO. The correlation coefficient reaches 0.86, 0.92, and 0.70, respectively, exceeding the confidence level of 99% (Fig. 8). Interestingly, the AMO is observed to lead the number of days with drought before the late 1990s but lags it afterward. And the lead–lag correlation analysis confirms the observation. This phenomenon indicates a longer period of AMO than the number of days with drought.
Interdecadal components of the annual number of days with drought averaged over (a) China, (b) the zonal belt, and (c) the meridional belt indicated in Fig. 5 based on the 90-day SPEI (red solid line), the AMO index (blue dashed line), and the PDO index (green dashed line) from 1961 to 2019. The orange dashed line indicates the annual number of days with drought, the blue solid line shows the AMO index, and the purple line with solid circles indicates the PDO index.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
To further understand the physical process by which the AMO affects the interdecadal variability in days with drought, the interdecadal components of circulation at different layers are regressed against the AMO index. At the 200-hPa level, an obvious wave train stretches from North Atlantic to East Asia (Fig. 9a). Moreover, the wave train is more significant in summer and autumn, with the regression over each activity center exceeding the confidence level of 95% (Fig. 10). The wave train connects the forcing from the Atlantic to the climatic anomaly in China. At the 500-hPa level (Fig. 9b), generally positive height anomalies cover most of the Eastern Hemisphere, but the wave train is still visible due to its relatively high and low centers. China is wholly controlled by positive geopotential height, with a high center over central and northern China. At the 850-hPa level (Fig. 9c), the positive AMO phase corresponds to a wide anticyclone over northern China. Obvious northerly anomalies prevail over most of central and northern China. And convection weakens greatly over most of the zonal and meridional belt but intensifies significantly over the four corners region (Fig. 9d). It is obvious that the circulation anomalies caused by the AMO well match with those affecting the interdecadal variation of days with drought shown in Fig. 8. The calculation presents that their spatial correlations range from 0.70 to 0.97 (Table 2). In particular, the spatial correlations of circulation regressions against the AMO and the number of days with drought in the zonal belt vary from 0.91 to 0.97, generally higher than those in the meridional belt. Therefore, the AMO affects the interdecadal variation of days with drought in China through the favorable circulation patterns.
Regressions of (a) 200-hPa meridional wind (m s−1), (b) 500-hPa geopotential height (gpm), (c) 850-hPa wind (m s−1; shadings indicate the topographic height), and (d) 850-hPa vertical wind speed (10−3 m s−1; a negative value indicates ascending motion, and vice versa) against the AMO index on the interdecadal time scale from 1961 to 2019. The dots denote values exceeding the confidence level of 95%.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
Regressions of 200-hPa meridional wind against the AMO index (m s−1) in (a) summer and (b) autumn on the interdecadal time scale from 1961 to 2019. The dots denote values exceeding the confidence level of 95%.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
Spatial correlation of 200-hPa meridional wind (V200), 500-hPa geopotential height (H500), 850-hPa zonal wind (U850), 850-meridional wind (V850), and 850-hPa vertical wind (W850) between those regressed against the number of days with drought in the zonal belt (Reg. DdN) and the meridional belt (Reg. DdS) shown in Fig. 5, on the AMO index (Reg. AMO) from 1961 to 2019, and on the PDO index (Reg. PDO) from 1980 to 2019 on the interdecadal time scale.
Additionally, the AMO is closely related to the temperature in the zonal and meridional belt, with the correlation being 0.92 and 0.95, respectively, and exceeding the confidence level of 99% (Fig. 12a). As the correlation between precipitation and the number of days with drought is high in the meridional belt but low in the zonal belt on the interdecadal time scale, we only calculated the correlation between the AMO and the precipitation in the meridional belt and a much weaker relationship is found. It can be seen that temperature rather than precipitation plays an important role in bridging the AMO and the interdecadal variation in the days with drought in China.
The PDO has long been regarded as one of the most important interdecadal forcings and is often described as a long-lived El Niño–like pattern of Pacific climate variability (Mantua et al. 1997; Mantua and Hare 2002; Dong and Dai 2015). The PDO is weakly correlated to the number of days with drought in all of China and in the zonal and meridional belts from 1961 to 2019, with the correlations being−0.42, −0.26, and −0.42, respectively (Fig. 8). However, the correlations have increased to be −0.83, −0.62, and −0.91 from 1980 to 2019, exceeding the confidence level of 95%. In the mid-1990s, the PDO transferred from a positive phase to a negative phase, corresponding to the interdecadal increase of the number of days with drought in China.
Figure 11 shows the circulation anomalies regressed against the negative PDO index on the interdecadal time scale from 1980 to 2019. It can be observed that they are also highly similar to what affects the interdecadal variation of the number of days with drought shown in Fig. 7. At the negative phase of PDO, the wave train across Eurasia at the high level, the broad high geopotential height anomalies over China, and the northerly anomalies and intensified sinking motion over the most zonal and meridional belt dominate. The spatial correlations of the circulation regressions against the PDO and the interdecadal component of the number of days with drought vary from −0.80 to −0.95 (Table 2).
Regressions of (a) 200-hPa meridional wind (m s−1), (b) 500-hPa geopotential height (gpm), (c) 850-hPa wind (m s−1; shadings indicate the topographic height), and (d) 850-hPa vertical wind speed (10−3 m s−1; a negative value indicates ascending motion, and vice versa) against the negative PDO index on the interdecadal time scale from 1980 to 2019. The dots denote values exceeding the confidence level of 95%.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
The PDO is −0.60 and −0.61 correlated to the temperature in the zonal and meridional belt from 1980 to 2019, respectively (Fig. 12b). And the correlations are significant at the confidence level of 95%. Meanwhile, it also has a close relationship to precipitation in the meridional belt, with the correlation being 0.66 and exceeding the confidence level of 95%. Then the transition from the positive phase to the negative phase of PDO in the mid-1990s contributes to both the warming and the dry condition in the meridional belt and also affects the warming in the zonal belt.
(a) Interdecadal components of the AMO index and the temperature in the zonal and meridional belt shown in Fig. 5 from 1961 to 2019, (b) interdecadal components of the PDO index and the temperature in the zonal and meridional belt from 1980 to 2019, and (c) the AMO index, PDO index, and precipitation in the meridional belt from 1980 to 2019. The red dashed line indicates the temperature in the zonal belt, the red dotted line and the green dashed line show the temperature and precipitation in the meridional belt, respectively, the blue solid line presents the AMO index, and the purple line with solid circles indicates the PDO index.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
Considering that the AMO and the PDO after the 1980s are two major influential factors, a combination index is defined by the difference between the normalized AMO index from 1961 to 2019 and the normalized PDO index from 1980 to 2019 on the corresponding year. Figure 13 shows the regressions of the number of days with drought in China against the combination index. It is obvious that high values exist over the zonal and meridional belt, exceeding the confidence level of 95%. It is similar to the difference of the number of days with drought between 1996–2019 and 1961–95 shown in Fig. 5, with the spatial correlation being 0.51. The high similarity further indicates the great impacts of the AMO and PDO on the interdecadal variation of the number of days with drought in China.
Regression of the number of days with drought in China against the AP index (the normalized AMO index from 1961 to 2019 minus the normalized PDO index from 1980 to 2019). The crosses denote values exceeding the confidence level of 95%.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
5. Discussion and conclusions
a. Discussion
Figure 14 shows the spatial distribution and temporal evolution of the annual number of days with drought in China based on the SPI90 and MCI, respectively. A pattern of high values to the east but low values to the west is observed in the climatology of the annual number of days with drought based on the SPI90 (Fig. 14a). And the highest values are located in Northeast China and in the region from eastern Northwest China to eastern Southwest China. However, the MCI calculates fewer days with drought in Northeast China, the mid- to lower reaches of the Yangtze River valley, and western China than do the SPI90 and SPEI90 (Fig. 14b). Moreover, obvious discrepancies in climatic variability are noticed. Different from the increasing trend of days with drought based on SPEI90, the downward trends in days with drought are observed based on the SPI90 and MCI (Figs. 14c,d). Apart from other factors, the relative contributions of temperature and precipitation to constructing the drought indices play important roles in the aforementioned differences. Precipitation is included in all three indices, while temperature plays a large role in the calculation of the SPEI90 and is considered slightly in the MCI but is excluded in the SPI90. Therefore, the climatology of and climatic variability in drought should be understood by combining the definitions of different indices.
(a) Climatology of the annual number of days with drought in China based on the 90-day SPI (shading; days). (b) Time series of the annual number of days with drought based on the 90-day SPI across China from 1961 to 2019 (blue line; days). (c) Climatology of the annual number of days with drought in China based on the MCI (shading; days). (d) Time series of the annual number of days with drought based on the MCI across China from 1961 to 2019 (blue line; days). The red dashed lines indicate the interdecadal components, the black solid lines present the climatic means, and the green dashed lines show the linear trends.
Citation: Journal of Climate 35, 6; 10.1175/JCLI-D-20-0985.1
Liu et al. (2015) have reported the significant drying trend in Southwest China, North China, Northwest China, and Central China and the high occurrence of severe drought in 1990s and 2000s. G. Zhang et al. (2016) and Wang et al. (2018) have revealed that the drought in Southwest China has gotten worse since 1994. Ma (2007) has pointed out the warming and drying tendencies in the northern part of China after the late 1970s. These researches well support our findings of the interdecadal variation of days with drought in China. Many previous studies have revealed that the PDO exerts great impacts on the East Asian monsoon, as well as on the temperature and precipitation of China (Zhu and Yang 2003; Lau et al. 2004; Liu and Chiang 2012; Si and Ding 2016; Yang et al. 2017). Meanwhile, the impacts of the AMO on the Afro-Asian summer monsoon (Li et al. 2017), surface temperature over the Northern Hemisphere (Wu et al. 2019), and heavy snowfall events in northern China (Zhou et al. 2021) have been investigated. And the wave train from the North Atlantic to East Asia is believed to play a key role in bridging the AMO and different climatic phenomena (Li et al. 2017; Gao et al. 2019; Wu et al. 2019; Zhou et al. 2021). In addition to these observations, numerical simulations also capture the general pattern of the wave train motivated by the AMO (Wu et al. 2019; Zhang et al. 2019; Zhou et al. 2021). These findings enhance the credibility of the conclusions obtained in this study.
In addition, the seasonal days with drought also show obvious interdecadal variability (Fig. 3). Of note, the discrepancy is observed between different seasons. Due to the limitation of article length, we did not analyze the climatic variability of seasonal days with drought. But they are worth investigating further to clarify the seasonal differences and better understand the climatic variability of the annual drought.
b. Conclusions
In this study, by analysis of the 90-day standardized precipitation evapotranspiration index (SPEI90) in 2419 stations from 1961 to 2019, the characteristics of interdecadal variations in the annual number of days with drought over China are revealed. The possible causes for the variations are also discussed.
A significant interdecadal increase in 1996 is observed, which characterizes the predominant mode of the annual number of days with drought in China. Moreover, this interdecadal transition is significant in all seasons except winter. The abrupt change mainly occurred in the zonal belt from southern Xinjiang to southern Northeast China and North China. Meanwhile, two significant breakpoints in 1981 and 2001 are detected in the meridional belt from eastern Northwest China to eastern Southwest China, showing a continuous increase of days with drought. However, slight increases or decreases in drought occurrence are observed over the “four corners” region comprising northern Xinjiang, Northeast China, central Southwest China, and southeastern China. The significant warming mainly contributes to the increase of days with drought in the zonal belt, while both warming temperature and reduced precipitation jointly play an important role in the meridional belt.
The wave train from the North Atlantic to East Asia at higher levels, general higher-than-normal geopotential height over China, and the anomalous northerly airflows and the intensified sinking motion in northern and central China are features of the circulation patterns affecting the interdecadal variation of the number of days with drought in China. Further analyses show that the AMO and, after the 1980s, the PDO are two significant influential factors. On the one hand, they motivate the circulation anomalies favorable for the interdecadal increase of days with drought. On the other hand, both the AMO and the PDO affect temperature, while the PDO also has high correlations to the precipitation in the meridional belt.
Acknowledgments.
This research was supported by the National Key Research and Development Program of China (2017YFC1502402).
Data availability statement.
The data from 2419 meteorological stations in China are available from the National Meteorological Information Center of the China Meteorological Administration at http://data.cma.cn/. The reanalysis data are available from the National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP–NCAR) at https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html as cited in Kalnay et al. (1996). The monthly PDO index is available from the National Oceanic and Atmospheric Administration (NOAA) at https://www.ncdc.noaa.gov/teleconnections/pdo/ as cited in Mantua and Hare (2002). The AMO index is defined as detrended 10-yr low-pass-filtered area-averaged SST anomalies over the North Atlantic basin (0°–65°N, 80°W–0°E) using NOAA Extended Reconstructed Sea Surface Temperature (ERSST) V5 data from https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html as cited in Trenberth and Shea (2006) and B. Y. Huang et al. (2017).
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