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Against the backdrop of global warming, extreme precipitation events have become more frequent. In complex terrain regions, due to the vulnerability of their ecosystems, extreme precipitation events can lead to significant secondary disasters. Utilizing daily rainfall data from the National Meteorological Information Center of China and statistical analysis, this study explores the spatial and temporal distribution of extreme precipitation in the Central Southwest China (CSC) region. The temporal pattern of extreme precipitation in CSC shows a consistent trend, while the spatial distribution reveals an opposite phase between the northern and southern parts of CSC. Based on this, we propose a new method for constructing extreme precipitation prediction models for complex terrain regions based on physical mechanisms, and take CSC area as a study case. Instead of anonymous feature selection, this method improves the accuracy and stability of the model by studying the impact of sea–air interactions on extreme precipitation and then introducing it into deep learning. It was found that the sea surface temperature (SST) anomaly in the South Indian Ocean affects extreme precipitation in the CSC by influencing uplift, atmospheric instability, and moisture. The SST anomaly also affects the intensity of cross-equatorial airflow, which changes the trajectory of the Pacific–Japan teleconnection wave and impacts extreme precipitation. These findings provide a comprehensive and reliable approach for forecasting extreme precipitation in CSC and are further integrated into the extreme precipitation prediction models. [ABSTRACT FROM AUTHOR]

High efficiency and stability, low-cost and large-area solution processing are critical for the commercialization of organic solar cells (OSCs), and there are still great challenges to develop an appropriate cathode interlayer (CIL) for efficient and stable large-area OSCs. Herein, by ingeniously combining a cross-linkable interfacial polymer (PFOPy) and a n-type self-doped interfacial molecule (PDINN), a robust and thickness-insensitive hybrid CIL (PFOPy-N) is developed to enable high-efficiency and stable inverted OSCs. The PFOPy-N CIL shows strong solvent resistance properties due to the crosslinking characteristic of PFOPy. Moreover, the PFOPy-N CIL achieves significantly increased electrical conductivity due to the n-type self-doping characteristic of PDINN and the charge transfer between PFOPy and PDINN and simultaneously offers a further reduced work function of ITO, which synergistically enhances charge transport and extraction and reduces charge recombination in inverted OSCs. Consequently, inverted OSCs based on the PFOPy-N CIL (10 wt% PDINN) show significantly improved photovoltaic performance compared to pure PFOPy and PDINN based devices as well as ZnO based devices. Utilizing a PM6:L8-BO active layer, an optimal PFOPy-N based device exhibits an outstanding PCE of 17.65%, which is one of the highest values for inverted OSCs with an organic cathode interlayer. The PFOPy-N based devices with the CIL thickness range of 7 to 39 nm all exhibit high PCEs of over 15.06%, showing obviously increased thickness insensitivity. PFOPy-N based large-area and flexible devices also exhibit superior PCEs of 15.95% and 15.84%, respectively, indicating the great potential of the PFOPy-N CIL in large-area and flexible OSCs. Notably, the PFOPy-N based device possesses significantly higher thermal cycling stability compared to the ZnO based device, indicating the robust resistance of the PFOPy-N CIL to thermal cycling stress. The impressive results will inspire the simple and effective strategy of combining crosslinking and self-doping characteristics to develop robust and thickness-insensitive hybrid CILs for high-efficiency and stable OSCs. [ABSTRACT FROM AUTHOR]