Wei Ren

Abstract The stable oxygen isotope ratio (δ 18 O) in precipitation is an integrated tracer of atmospheric processes worldwide. Since the 1990s, an intensive effort has been dedicated to studying precipitation isotopic composition at more than 20 stations in the Tibetan Plateau (TP) located at the convergence of air masses between the westerlies and Indian monsoon. In this paper, we establish a database of precipitation δ 18 O and use different models to evaluate the climatic controls of precipitation δ 18 O over the TP. The spatial and temporal patterns of precipitation δ 18 O and their relationships with temperature and precipitation reveal three distinct domains, respectively associated with the influence of the westerlies (northern TP), Indian monsoon (southern TP), and transition in between. Precipitation δ 18 O in the monsoon domain experiences an abrupt decrease in May and most depletion in August, attributable to the shifting moisture origin between Bay of Bengal (BOB) and southern Indian Ocean. High‐resolution atmospheric models capture the spatial and temporal patterns of precipitation δ 18 O and their relationships with moisture transport from the westerlies and Indian monsoon. Only in the westerlies domain are atmospheric models able to represent the relationships between climate and precipitation δ 18 O. More significant temperature effect exists when either the westerlies or Indian monsoon is the sole dominant atmospheric process. The observed and simulated altitude‐δ 18 O relationships strongly depend on the season and the domain (Indian monsoon or westerlies). Our results have crucial implications for the interpretation of paleoclimate records and for the application of atmospheric simulations to quantifying paleoclimate and paleo‐elevation changes.

Internet-of-Things (IoT) are increasingly operating in the zero-trust environments where any devices and systems may be compromised and hence untrusted. In addition, data collected by and sent from IoT devices may be shared with and processed by edge computing systems, in order to reduce the reliance on centralized (cloud) servers, leading to further security and privacy issues. To cope with these challenges, this paper proposes an innovative blockchain-enabled information sharing solution in zero-trust context to guarantee anonymity yet entity authentication, data privacy yet data trustworthiness, and participant stimulation yet fairness. This new solution is able to support filtering of fabricated information through smart contracts, effective voting, and consensus mechanisms, which can prevent unauthenticated participants from sharing garbage information. We also prove that the proposed solution is secure in the universal composability framework, and further evaluate its performance over an Ethereum-based blockchain platform to demonstrate its utility.