East Asian summer monsoon precipitation (EASMP) features marked interdecadal variations (> 10 years) and complicated interdecadal variability with multiple time periods and spatial patterns (Fig. 1a). Understanding and predicting its evolution is of great guiding significance to the national medium and long-term strategic planning. The cause of EASMP’s interdecadal variability has always been a hotspot in the climate change research, attracting continuous attention from academics at home and abroad since the end of the 20th century. Professor Xiu-Qun Yang’s research group, from School of Atmospheric Sciences (SAS) in Nanjing University (NJU), has been studying interdecadal climatic variability for many years. At present, important progress has been made in the influence of interdecadal sea surface temperature (SST) signals on the EASMP’s interdecadal variability. On the interdecadal time scale, the Pacific Decadal Oscillation (PDO, Fig. 1b), Atlantic Multidecadal Oscillation (AMO, Fig. 1c) and Indian Ocean Basin Mode (IOBM, Fig. 1d) are strong signals of SST anomalies in the Pacific, Atlantic and Indian Oceans, respectively, and their oscillating periods and temporal evolutions are basically independent from each other. Most previous studies only considered the effect of SST signal, such as PDO or AMO, in a certain basin on interdecadal variability of EASMP, which is so complicated that it cannot be well explained (Fig. 1a). Professor Xiu-Qun Yang’s team took overall consideration of the 'joint influence' of three oceanic interdecadal signals (i.e., PDO, AMO, and IOBM) on the EASMP. By means of different phase combinations, they could commendably explain the formation mechanism of the observed EASMP’s interdecadal variability over the past 100 years, which could be further applied to the interdecadal climatic prediction of future precipitation in East Asia including China. This study, entitled 'Understanding the Interdecadal Variability of East Asian Summer Monsoon Precipitation: Joint Influence of Three Oceanic Signals', was published in Journal of Climate (No.14, Vol. 31, 2018), the journal of American Meteorological Society (AMS).
FIG. 1. (a), (left) Time-latitude cross section of 11-yr running averaged JJA precipitation anomalies (mm day-1) over eastern China (110°-121°E), accompanied by (right) their linear correlation coefficients with the 11-yr running averaged JJA oceanic indices at each latitude (PDO is green, AMO is magenta, and IOBM is gold; thickened curves indicate the 95% confidence level). Detrended and standardized indices of (b) JJA PDO, (c) AMO, and (d) IOBM (filled bars) with their 11-yr running average (colored thick lines). (e) Combined PDO and AMO phases marked with gray shading, wherein plus and minus signs indicate positive and negative phases, respectively.
The positive and negative phases of the PDO and the AMO are actually overlapped with each other resulting from their different periods of quasi-oscillations (Fig. 1e). Therefore, in terms of the positive and negative phases of PDO and AMO, there are four pairs of combined PDO and AMO phases in total, namely, the out-of-phase combination (PDO+/AMO− vs PDO−/AMO+) and the in-phase combination (PDO−/AMO− vs PDO+/AMO+). When PDO and AMO are out of phase, the EASMP anomalies show a meridional tripole mode, and the anomalies are in opposite sign to each other (symmetrical) between the two pairs: when PDO is in positive (negative) phase and AMO is in negative (positive) phase, there is more (less) precipitation in the Huang He-Huai River valley (HHRV) and southern China, and less (more) precipitation in the Yangtze River valley (YRV), as shown in Figs. 2a and 2b; when PDO and AMO are in phase, the EASMP anomalies show a meridional Dipole mode, and the anomalies are not symmetric between the two pairs: when PDO and AMO are both in positive phases, the precipitation decreases in northern China and HHRV, while increases in southern China; when PDO and AMO are both in negative phases, the precipitation decreases in YRV, while increases in HHRV (Fig. 2c and 2d). On the other hand, IOBM also has an indispensable influence on the interdecadal EASMP anomalies, leading to abnormal distribution of precipitation in the form of 'southern flood and northern drought (SFND)'. That is, with the warming (cooling) of the IOBM, the precipitation in northern China is remarkably less (more), while significantly more (less) in the YRV (Fig. 3).
Fig. 2. EASMP anomalies under different phase combinations of PDO and AMO (mm/day). Four pairs of combined PDO and AMO phases are as follows: (a) PDO+/AMO−, (b) PDO−/AMO+, (c) PDO−/AMO−, and (d) PDO+/AMO+. The 90% and 95% confidence levels are denoted by thick black contour lines and cross hatching, respectively.
Fig. 3. Differences of EASMP anomalies between 1999-2010 (IOBM warming/PDO-/AMO+) and 1946-1961 (IOBM cooling/PDO-/AMO+). The 90% and 95% confidence levels are denoted by thick black contour lines and cross hatching, respectively.
By analyzing associated atmospheric circulation anomalies and the Rossby wave activity flux, it is pointed out that when PDO and AMO are in in-phase or out-of-phase combination, the interdecadal EASMP anomalies is related to the propagation of anomalous Rossby wave train in Asian westerly jet over Eurasian continent from the North Atlantic: when PDO and AMO are out-of-phase, there is a zonally orientated stationary teleconnection wave train propagating from North Atlantic to northern East Asia across the Eurasian mid-to-high latitudes along the Asian westerly jet waveguide , which directly produces the atmospheric circulation anomalies in the northern East Asia, influencing the EASMP; when PDO and AMO are in-phase, the anomalous Rossby wave train from North Atlantic mainly propagates along a great circle route into the western central Asia, causing Indian summer monsoon precipitation (ISMP) anomalies, which in turn stimulates a new Rossby wave train propagating northeastward to the northern East Asia and North Pacific along the great circle route by its released diabatic heating, affecting East Asian climate anomalies. At the same time, based on Rossby wave propagation theory, the anomalous stationary wavenumber in the eastern Mediterranean region is the key factor affecting the Rossby wave propagation route.
IOBM’s influence on the interdecadal variability of EASMP is mainly due to the its impact on the interdecadal ISMP anomalies, and such influence can be linearly superimposed on the different combined PDO and AMO phases, thus playing a role of linear modulation. IOBM warming (cooling) will directly cause less (more) precipitation in ISMP, and the associated diabatic cooling (heating) release will stimulate a Rossby wave train propagating to downstream East Asia in the upper troposphere, and anomalous cyclone (anticyclone) circulation over the northwestern Pacific in the lower troposphere through Kelvin wave response and the process of 'Thermal Adaptation'. Under the combined impacts of the anomalous cyclone (anticyclone) in the northwestern Pacific and the anomalous anticyclone (cyclone) circulation in the northern East Asia, the East Asian summer monsoon (EASM) weakens (strengthens), thus the precipitation in the YRV increases (decreases), and that in northern China decreases (increases), with the EASMP displaying the Dipole mode like the 'SFND' (Fig. 4).
Fig. 4. Schematic diagram of the joint influence of the PDO, AMO, and IOBM on the interdecadal variability of the EASMP.
In recent years, AMO is in a warm phase, the Indian Ocean is in progressive warming, and PDO is in the transition from negative to positive phase. According to the findings and conclusions of this study, it is predicted that in the coming decade, the 'SFND' will remain the main pattern of summer precipitation anomalies in China, representing the continuous drought over northern China, a shift from flood to drought in the HHRV, while the risk of flood disasters over southern China will increase.
This work was funded by the innovation research group program and the general program of National Natural Science Foundation of China. Zhiqi Zhang, a doctoral student from SAS, is the first author of the paper. Associate Professor Xuguang Sun and Professor Xiu-Qun Yang are the co-corresponding authors. This research was completed with the support of CMA-NJU Joint Laboratory for Climate Prediction Studies.