Abstract:
Although land precipitation across China is dominated by inter-annual variability, we identify the areas of significant variability of decadal (10—20 a), multidecadal (20—50 a) and secular trend (>50 a) by applying singular spectrum analysis (SSA). In addition, relative contributions of different sea surface temperature (SST) modes to the trend and (inter) decadal variability of precipitation over China during June—August (summer)/December—February (winter) of 1934—2018 are investigated by singular value decomposition (SVD) and multiple linear regression methods. Based on SVD analysis of precipitation in China and SST in the middle and low latitudes, it is found that global warming (GW) is the primary SST mode affecting precipitation in China in both winter and summer. The Interdecadal Pacific Oscillation (IPO) plays a second role. A multivariate linear regression model is then applied to quantitatively evaluate the variance contributions and relative contributions of GW, IPO and Atlantic Multidecadal Oscillation (AMO) to precipitation in different regions of China. The results show that GW, IPO and AMO can explain about 30% of the trend and (inter) decadal precipitation in Northwest China and North China in summer, and the relative contribution of GW is the largest, followed by that of IPO. In winter, the above three factors can explain 42% of the trend and (inter) decadal precipitation in Northeast China and about 30% in Northwest China and North China. In Northeast China and Northwest China, the relative contribution of GW is dominant, and the contribution of AMO is second to that of GW. In North China, GW contribution is also dominant, followed by that of IPO.