MJO:Its Propertiy Reconstruction And Casual Influences On The Precipitation Over China

Using the recently developed filter, multiscale window transform (MWT), which is capable of handling the highly nonlinear and intermittent processes in the atmospheric circulations, and a rigorous analysis method to unravel quantitatively the causality between time series, we reconstructed the Madden-Julian Oscillation (MJO) and examined its influences on the precipitation over China. We first formed two highly idealized series, and tested the filtering effect of MWT against the traditional and mostly used band-pass Butterworth filter. It is found that the MWT always makes fairly accurate reconstructions, while the Butterworth filter tends to yield series with smaller amplitude. Besides, the boundary effect is successfully suppressed in the MWT reconstructions, in contrast to the Butterworth results. With these observations in mind, we reconstruct the MJO using the MWT method. The results show that MJO propagate eastward in zonal. On the yearly mean meridional distribution, it is found that, from January through June, the MJO wave packet propagates from south to north; but from June through December, the propagation reverses its direction, becoming from north to south which is very different with the traditional description. On the seasonal distribution, MJO is stronger in spring and winter than that in summer and autumn.How to unravel the causality between time series is a fundamental problem which has wide applications in different disciplines. It is also a very challenging problem; in fact, it has been identified as one of the biggest challenges in data science. Here we took advantage of the most recent advance in this field and studied the causal influences of MJO on the precipitation over China. The causality is measured in terms of the rate of Liang-Kleeman information flow lying in between. The major findings can be summarized as:The causal hotpots are Tibetan Plateau, the Northeast China region and the Yangtze-Huaihe region; hereafter we refer to them as TP, NC, and YH, respectively. In the light of information flow, MJO makes the precipitation variability over Tibet and the Northeast more uncertain, while making that over the Yangtze-Huaihe region more certain. By comparison, MJO exerts the strongest influence to the precipitation over Tibet. The causal relations between MJO and TP and NC are found to be mutual, in contrast to that between MJO and YH, which is a one-way causality from the former to the latter. We have also performed a composite analysis to substantiate these findings. Specifically, MJO is divided into two phases, i.e., phases of strong and weak events, and the precipitation anomalies are investigated correspondingly. Essentially this reproduces the causal pattern as illustrated above. In the strong MJO phase, the anomalies over these regions are negative; the wind and water vapor transport are southward from the continent to South China Sea and its ambient seas; the Northeast China is affected by an anticyclonic water vapor transport; the convections over India and South China Sea are suppressed; the water vapor diverges over the Tibetan Plateau. These are all reversed during the weak MJO phase. Generally speaking, MJO’s effect is enhanced at its onset and decay. The precipitation over TP is mainly affected by the first phase, that over NC by the sixth phase, and that over YH by both the second and sixth phase. During the MJO evolution, the OLR and vapor flux divergence also travel from the west to east, generating the strongest convection system in phase 5, and finally disappearing at the dateline. In a lifecycle of MJO, the transport directions of the 850hPa zonal wind and water vapor flux are almost the same, both corresponding to the precipitation patterns in the 8 MJO phases.