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By observing well‐known sea surface temperature (SST) indices and outputs from Climate Forecast System version 2 (CFSv2) hindcasts and predictions, in this study, we developed a hybrid statistical downscaling prediction model (HSDPM) based on a timescale decomposition approach, which effectively improved the forecasting ability of summer (June–August) precipitation over Hainan Island (HNSP) in China; this precipitation presented multiple obvious timescale variabilities. We found that the interannual variability of the HNSP is closely related to the observed North Atlantic tripole SST anomalies in the preceding winter and the summer sea level pressure over the South China Sea by CFSv2 predicted in March. On the other hand, the interdecadal variability in the HNSP is linked to the prewinter Pacific Interdecadal Oscillation (PDO) according to the observations, the CFSv2 predictions of the summer surface air temperature over the tropical central‐east Pacific. On this basis, both the interannual and interdecadal components of the HNSP are effectively predicted using the corresponding predictors via multiple regression; thus, the HSDPM is ultimately established by combining the above two components. Compared with the original CFSv2 model, the HSDPM model achieves a considerable improvement in performance in predicting the HNSP. Specifically, the temporal correlation coefficient, ratio of root‐mean‐square error and anomaly sign consistency rate between the observed and HSDPM‐predicted HNSPs are 0.70, 17.4% and 80.5%, respectively, which are significantly greater than the above three forecasting index values of 0.23, 38.3% and 48.8%, respectively, obtained from the original CFSv2 predictions. The application of the HSDPM may be beneficial for drought and flood prevention and mitigation in Hainan Island. [ABSTRACT FROM AUTHOR]

The variation of tropical cyclone (TC) genesis over the North Indian Ocean (NIO) and South China Sea (SCS) during the post‐monsoon season is explored during 1979–2020. A zonal see‐saw variation of TC genesis is detected between the Arabian Sea (AS) and Bay of Bengal (BOB) –SCS (BOBSCS for brevity). More (less) TCs over the AS tend to concur with fewer (more) TCs over the BOBSCS. Analyses of both the observations and the Coupled Model Intercomparison Project Phase 6 outputs show that tripole sea surface temperature (SST) anomalies in the tropical Indian and Pacific Oceans play a crucial role in the zonal see‐saw variation of TC genesis. Positive western Indian (WI) Ocean and tropical central and eastern Pacific (CEP) Ocean SST anomalies and negative western Pacific (WP) SST anomalies induce anomalous ascending and descending motions and high and low humidity transportation to the middle troposphere over the AS and BOBSCS, respectively. Meantime, anticyclonic vorticity anomalies appear in the BOBSCS region and negative anomalies of vertical wind shear are induced over the NIO and SCS. The combined positive contributions of upward motion, mid‐level humidity increase, and low vertical wind shear favor higher TC genesis over the AS, whereas the joint negative effects of downward motion, mid‐level water vapor decrease, and lower‐level anticyclonic vorticity anomalies result in less TC genesis over the BOBSCS. Numerical experiments show a critical role of the WI SST anomalies in the dipole pattern of vertical motion, which is crucial for the zonal dipole variation of TC genesis. Plain Language Summary: Although the tropical cyclones (TCs) frequency number that form over the South China Sea (SCS), Bay of Bengal (BOB) and Arabian Sea (AS) are relatively small, these regions are densely populated, which means that the impacts of TCs can be significant and widespread. The study presents observational and modeling evidence for a see‐saw variation of tropical cyclogenesis between the AS and BOB‐SCS during the post‐monsoon season (September–December). Composite analyses display that the zonal see‐saw connection of tropical cyclogenesis frequency over the AS and BOB‐SCS is closely linked to the zonal tripole distribution of the sea surface temperature anomalies over the tropics of the Indian and Pacific Oceans, which exert a significant influence on the vertical–zonal overturning circulation and the environmental parameters for TC formation over the AS and BOB‐SCS. We conduct an evaluation of 19 CMIP6/AMIP (CMIP6/CMIP) simulations and reveal that 53% (26%) models are able to successfully simulate the zonal dipole pattern of TC‐related variables between AS and BOB‐SCS regions. The present findings may have the potential to enhance the seasonal prediction for tropical cyclogenesis over the SCS, AS and BOB regions. Key Points: A zonal see‐saw variation of TC genesis is detected between the Arabian Sea (AS) and the Bay of Bengal‐South China Sea (BOBSCS)The tripole SST anomalies over the tropical Indian and Pacific Oceans play a crucial role in the zonal see‐saw variation of TC genesisNumerical experiments show a critical role of SST anomalies in the western Indian Ocean in the dipole pattern of vertical motion [ABSTRACT FROM AUTHOR]

In 2021, the Yangtze–Huaihe River Basin (YHRB) of China underwent normal precipitation during the classical Meiyu period in June–July but suffered extreme precipitation and severe floods in August. The present study revealed that the extreme heavy precipitation anomalies over the YHRB region were closely related to the combined effect of the strong western North Pacific anomalous anticyclone (WNPAC) and East Asian middle–high latitude circulation anomalies in August 2021. Moreover, the background of sea surface temperature (SST) anomalies was a strong eastern-Pacific La Niña event that rapidly decayed in spring and a second La Niña emerged in late summer, accompanied by a weak tropical Indian Ocean warming and a strong tropical Atlantic warming in summer. The rapidly decaying La Niña event and the weak tropical Indian Ocean warming alone seem to be insufficient to induce the strong WNPAC in August 2021. Observational evidence and numerical experiments suggest that the rapid tropical Atlantic warming from late spring to summer observably contributed to the enhancement and westward shift of the WNPAC, and the cold SST anomalies in the eastern tropical Pacific associated with the second La Niña event also provided favorable conditions for a strong WNPAC in August 2021. Overall, rapid tropical Atlantic warming and the development of the second La Niña contributed to the strong WNPAC in August 2021, while the maintenance mechanism of the East Asian middle–high latitude circulation anomalies that controlled cold air activity remains unclear. [ABSTRACT FROM AUTHOR]

Northeast China (NEC) is located between the subtropical monsoon and temperate-frigid monsoon regions and exhibits two successive rainy seasons with different natures: the northeast cold vortex rainy season in early summer (May–June) and the monsoon rainy season in late summer (July–August). Summer rainfall over NEC (NECR) has a fundamental influence on society, yet its successful seasonal prediction remains a long-term scientific challenge to current dynamical models. The poor NECR prediction skill is partly attributed to the large NECR variability at both the interannual and interdecadal time scales. Here, we focus on the oceanic drivers of the late summer NECR variability and associated physical processes at interannual time scale. Then, we establish an empirical prediction model to predict the interannual variability of summer NECR at 1-month lead time (in June). The analysis of observations spanning 40 years (1963–2002) reveals three physically and synergistically influencing predictors of the late summer NECR interannual variability. Above-normal NECR is preceded in the previous spring by (a) warm sea surface temperature (SST) anomalies in the tropical northern Indian Ocean, (b) a positive thermal contrast tendency in the tropical West–East Pacific SST, and (c) a positive tendency of the North Atlantic tripolar SST. These precursors enhance the anomalous low-level anticyclone over the western North Pacific and southerly anomalies over NEC in late summer, which are beneficial to enhancing NECR. An empirical prediction model built on these three predictors achieves a forecast temporal correlation coefficient (TCC) skill of 0.72 for 1961–2019, and a 17-year (2003–2019) independent forecast shows a significant TCC skill of 0.70. The skill is substantially higher than that of five state-of-the-art dynamical models and their ensemble mean for 1979–2019 (TCC = 0.24). These results suggest that the proposed empirical model is a meaningful approach for the prediction of NECR, although the dynamical prediction of NECR has considerable room for improvement. [ABSTRACT FROM AUTHOR]

In this study, we investigate the interdecadal variation characteristics of the dominant mode of summer precipitation over East Asia‐Northwest Pacific (EA‐NWP) before and after late 1990s, reveal the physical mechanism, and address its possible connection with the regional ocean warming background. Study results show that the empirical orthogonal function mode 1 (EOF1) of summer precipitation anomalies over EA‐NWP during the global ocean warming acceleration period (1979–1998) present a more significant dipole pattern between Yangtze River Basin (YRB) and tropical NWP compared with that during the global ocean warming slowdown period (1999–2012). And then we find that the anomalous dipoles of low‐level winds, geopotential height, convection, and associated wave activity fluxes over NWP significantly shift westward (eastward) and enhance (weaken) in 1979–1998 (1999–2012), which are regarded as the direct cause of the adjustment of dipole pattern between YRB and tropical NWP. Further analysis reveals that the negative sea surface temperature (SST) anomalies in the tropical NWP are prominent (not prominent), resulting in the stronger (weaker) Pacific–Japan Teleconnection over Japan and Tropics in NWP during the period 1979–1998 (1999–2012), and ultimately lead to the change of summer precipitation EOF1 in EA‐NWP. By regressing vertical velocity, outgoing longwave radiation, relative vorticity, wave activity fluxes, and precipitation onto the NWP SST in the two periods, the impacts of the SST in the NWP on the interdecadal variation of summer precipitation EOF1 in EA‐NWP are verified. Finally, the mechanism diagram of interdecadal variation of summer precipitation is given, which can be useful for short‐term precipitation prediction of East Asia. [ABSTRACT FROM AUTHOR]

Accurate short-term climate predictions, specifically the prediction of dominant rain belts during flood seasons, represent a significant challenge, particularly in the absence of notable external forcing signal anomalies in the previous winter. To address this challenge, we propose a novel climate index based on an Auto-Encoder (AE) Neural Network that exhibits superior performance in indicating several significant precipitation events in the Yangtze and Huaihe River Basins under varying El Niño conditions. Notably, the novel climate index rectifies the discrepancy between the 2019/2020 Niño index and the 2020 summer precipitation. In order to understand the information source of AE, the causality between AE and other indices was further analyzed by Granger Causality. The results show that AE index mainly contains the information of subtropical high index and ocean index, which is consistent with previous studies. • AE obtained by Auto-encoder can make up for the "failure" of Nino index in abnormally heavy precipitation events. • In terms of magnitude and state, AE has better description of precipitation than Nino3.4. • The main indices of AE information are subtropical high-pressure index and sea surface temperature index. [ABSTRACT FROM AUTHOR]