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Clustering extreme weather events are concurrent or consecutive occurrences of disastrous weather in multiple regions, resulting in cumulative impacts. Here we discovered a significant increasing trend in clustering extreme precipitation events over the Indo-Pacific rim over the past four decades. This trend can be largely attributable to the increasing frequency of the Rossby wave response, including the circum-Pacific and cross-Pacific patterns due to Rossby wave activity propagation, and the Pacific anticyclone pattern due to Rossby wave breaking. The three patterns show remarkable disparity in seasonality, persistence, and hydrological impacts. They can increase the occurrences of most severe precipitation by up to 5, 8, and 25 times, respectively. The Indian Summer Monsoon heat sources and La Niña are identified as key drivers, and the mid-latitude jet streams are modulators contributing to the events. Our findings suggest that specific Rossby wave patterns may influence the potential evolution of future clustering extremes.

Coastal ocean acidification is a worldwide problem associated with anthropogenic activity and climate change. In this study, a close relationship between submarine groundwater discharge (SGD) and coastal ocean acidification in Hong Kong's coastal waters is discovered. We for the first time evaluated the direct influence of SGD on seawater pH decline. Results show that SGD can contribute to up to 48% of seawater pH variation among terrestrial water input, air-sea CO2 exchange, photosynthesis/respiration, and bay-open water exchange in semi-closed bays through direct input of carbonate species. Local air-sea CO2 exchange has negligible influences on the seawater pH. In the semi-closed bay areas, SGD and aerobic respiration are major contributors to seawater pH variation but in areas with open space, the exchange process with open waters is more important. In addition to the direct input of carbonate species (total alkalinity and dissolved inorganic carbon), SGD also influences the seawater pH via considerable nutrient loadings. The findings highlight the importance of the investigation and management of groundwater to alleviate the fast coastal ocean acidification. © 2023 The Authors.

Face recognition technology is widely used in the financial field, and various types of liveness attack behaviors need to be addressed. Existing liveness detection algorithms are trained on specific training datasets and tested on testing datasets, but their performance and robustness in transferring to unseen datasets are relatively poor. To tackle this issue, we propose a face liveness detection method based on image-text pairs and contrastive learning, dividing liveness attack problems in the financial field into eight categories and using text information to describe the images of these eight types of attacks. The text encoder and image encoder are used to extract feature vector representations for the classification description text and face images, respectively. By maximizing the similarity of positive samples and minimizing the similarity of negative samples, the model learns shared representations between images and texts. The proposed method is capable of effectively detecting specific liveness attack behaviors in certain scenarios, such as those occurring in dark environments or involving the tampering of ID card photos. Additionally, it is also effective in detecting traditional liveness attack methods, such as printing photo attacks and screen remake attacks. The zero-shot capabilities of face liveness detection on five public datasets, including NUAA, CASIA-FASD, Replay-Attack, OULU-NPU and MSU-MFSD also reaches the level of commercial algorithms. The detection capability of proposed algorithm was verified on 5 types of testing datasets, and the results show that the method outperformed commercial algorithms, and the detection rates reached 100% on multiple datasets. Demonstrating the effectiveness and robustness of introducing image-text pairs and contrastive learning into liveness detection tasks as proposed in this paper.