Nature-Inspired Designs in Wind Energy: A Review.

The field of wind energy stands at the forefront of sustainable and renewable energy solutions, playing a pivotal role in mitigating environmental concerns and addressing global energy demands. For many years, the convergence of nature-inspired solutions and wind energy has emerged as a promising avenue for advancing the efficiency and sustainability of wind energy systems. While several research endeavors have explored biomimetic principles in the context of wind turbine design and optimization, a comprehensive review encompassing this interdisciplinary field is notably absent. This review paper seeks to rectify this gap by cataloging and analyzing the multifaceted body of research that has harnessed biomimetic approaches within the realm of wind energy technology. By conducting an extensive survey of the existing literature, we consolidate and scrutinize the insights garnered from diverse biomimetic strategies into design and optimization in the wind energy domain.

Research priorities for global food security under extreme events.

Extreme events, such as those caused by climate change, economic or geopolitical shocks, and pest or disease epidemics, threaten global food security. The complexity of causation, as well as the myriad ways that an event, or a sequence of events, creates cascading and systemic impacts, poses significant challenges to food systems research and policy alike. To identify priority food security risks and research opportunities, we asked experts from a range of fields and geographies to describe key threats to global food security over the next two decades and to suggest key research questions and gaps on this topic. Here, we present a prioritization of threats to global food security from extreme events, as well as emerging research questions that highlight the conceptual and practical challenges that exist in designing, adopting, and governing resilient food systems. We hope that these findings help in directing research funding and resources toward food system transformations needed to help society tackle major food system risks and food insecurity under extreme events.

Multidimensional risk in a nonstationary climate: Joint probability of increasingly severe warm and dry conditions.

We present a framework for quantifying the spatial and temporal co-occurrence of climate stresses in a nonstationary climate. We find that, globally, anthropogenic climate forcing has doubled the joint probability of years that are both warm and dry in the same location (relative to the 1961-1990 baseline). In addition, the joint probability that key crop and pasture regions simultaneously experience severely warm conditions in conjunction with dry years has also increased, including high statistical confidence that human influence has increased the probability of previously unprecedented co-occurring combinations. Further, we find that ambitious emissions mitigation, such as that in the United Nations Paris Agreement, substantially curbs increases in the probability that extremely hot years co-occur with low precipitation simultaneously in multiple regions. Our methodology can be applied to other climate variables, providing critical insight for a number of sectors that are accustomed to deploying resources based on historical probabilities.

A New Time-varying Concept of Risk in a Changing Climate.

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.