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The El Niño-Southern Oscillation (ENSO) exhibits highly asymmetric temporal evolutions between its warm and cold phases. While El Niño events usually terminate rapidly after their mature phase and show an already established transition into the cold phase by the following summer, many La Niña events tend to persist throughout the second year and even re-intensify in the ensuing winter. While many mechanisms were proposed, no consensus has been reached yet and the essential physical processes responsible for the multi-year behavior of La Niña remain to be illustrated. Observations show that a unique ocean physical process operates during multi-year La Niña events. It is characterized by rapid double reversals of zonal ocean current anomalies in the equatorial Pacific which exhibits a fairly regular near-annual periodicity. Analyses of mixed-layer heat budget reveal comparable contributions of the thermocline and zonal advective feedbacks to the SST anomaly growth for the first year of multi-year La Niña events; however, the zonal advective feedback plays a dominant role in the re-intensification of La Niña events. Furthermore, the unique ocean process is identified to be closely associated with the preconditioning heat content state in the central to eastern equatorial Pacific before the first year of La Niña, which sets the stage for the future re-intensification of La Niña. The above-mentioned oceanic process can be largely reproduced by state-of-the-art climate models despite systematic underestimation, providing a potential predictability source for the multi-year La Niña events.

Virtual power plants (VPPs) offer an effective means to address the imbalance issue between electricity supply and demand to advance the world’s low-carbon development. To fully utilize the limited resources in the virtual power plant planning stage, a two-sided match between VPPs and distributed energy companies is needed to better implement resource aggregation management. Because of the vagueness in this matching environment, the probabilistic linguistic term set (PLTS) is necessary to apply to express the decision makers’ preference. Considering the complex social relationships and intense competition among companies, a dynamic social network two-sided matching model is proposed for solving the multi-attribute two-sided matching decision-making problem. Firstly, we present a matching satisfaction degree described by PLTS. A dynamic social trust degree based on the sliding time concept is proposed. Secondly, the social trust network relationships are built based on the direct and indirect dynamic trust degree among companies. This relationship is then combined with an improved trust rank algorithm to identify the most authoritative and the most trusted company to provide the target company with a recommendation for the next moment. Besides, given that companies compete for limited resources, we further define the competitive satisfaction degree and apply the two-sided matching model. Additionally, then a two-sided matching model is developed. Finally, our model is tested numerically to ensure its accuracy and reliability.

The present work investigates leading modes of winter fog days over eastern China and possible association with sea surface temperature (SST) variability. Based on the Empirical Orthogonal Function (EOF) analysis, two dominant interannual modes of winter fog days are identified: a monopole mode and a meridional dipole mode. The monopole mode displays a significantly positive relationship with El Nino-Southern Oscillation (ENSO). The meridional dipole mode is closely linked to North Atlantic tripole (NAT) SST anomalies. A quasi-barotropic Rossby wave train can be excited by the NAT SST anomalies and propagates eastwards to East Asia. During winters with the positive phase of the NAT SST anomalies, there appear cyclonic and anticyclonic circulation anomalies over northern and southern China, favoring less and more winter fog frequency, respectively. These observed impacts from the ENSO and NAT SST anomalies can be further reproduced by atmospheric general circulation model (AGCM) experiments. Consideration of the NAT SST anomalies can apparently improve the explained variance of winter fog days over eastern China on the basis of the common-used ENSO signal. When ENSO and NAT occur as in-phase combinations and out-of-phase combinations, winter fog days anomalies appear over southern and northern China, respectively. These results have important implications on the seasonal-to-interannual predictability of the winter fog frequency over eastern China.

Many previous studies have shown that an Indian Ocean basin warming (IOBW) occurs usually during El Niño–Southern Oscillation (ENSO) decaying spring to summer seasons through modifying the equatorial zonal circulation. Decadal modulation associated with the interdecadal Pacific oscillation (IPO) is further investigated here to understand the nonstationary ENSO–IOBW relationship during ENSO decaying summer (July–September). During the positive IPO phase, significant warm sea surface temperature (SST) anomalies are observed over the tropical Indian Ocean in El Niño decaying summers and vice versa for La Niña events, while these patterns are not well detected in the negative IPO phase. Different decaying speeds of ENSO associated with the IPO phase, largely controlled by both zonal advective and thermocline feedbacks, are suggested to be mainly responsible for these different ENSO–IOBW relationships. In contrast to ENSO events in the negative IPO phase, the ones in the positive IPO phase display a slower decaying speed and delay their transitions both from a warm to a cold state and a cold to a warm state. The slower decay of El Niño and La Niña thereby helps to sustain the teleconnection forcing over the equatorial Indian Ocean and corresponding SST anomalies there can persist into summer. This IPO modulation of the ENSO–IOBW relationship carries important implications for the seasonal prediction of the Indian Ocean SST anomalies and associated summer climate anomalies.

The winter fog frequency over eastern China displays remarkable interannual variability, which has a linear relationship with El Nino-Southern Oscillation (ENSO). Eastern China usually experiences more (less) frequent fog during El Nino (La Nina) winters. During El Nino winters, an anomalous anticyclone tends to appear over the western North Pacific (WNP), which can weaken the climatological winter northerly winds and enhance water vapor supply from oceans, conducive to the formation of foggy weather. Roughly opposite anomalies of fog frequency are displayed during La Nina winters. However, this linear relationship is mainly contributed by the La Nina and partial El Nino events, since the El Nino events exhibit diversity in impacts on the winter fog frequency due to their different types. Increased winter fog frequency can be significantly detected during eastern-Pacific (EP) El Nino, while this signal is not observed during central-Pacific (CP) El Nino. It is found that the winter fog frequency during the CP El Nino seems to be dependent on its zonal locations, associated with different WNP atmospheric circulation and local difference between air temperature and dew point temperature (T − Td) anomalies. The further eastward CP El Nino largely coincides with more frequent fog weather similar to the EP El Nino, while the further westward CP El Nino is usually accompanied with less frequent fog weather. This relationship has important implications for seasonal prediction of winter fog frequency and places a high requirement on consideration of zonal location of the CP El Nino.