• Aerosols in Polar Atmospheres

    Broadening our knowledge of the relevant physical, chemical, and biological components of polar atmospheric and climate science, with a particular focus on regional atmospheric aerosol composition.

    Open for submissions
  • New Collection: The Role of Ocean Dynamics

    Scrutinizing the role of ocean dynamics in the climate system, such as the impact of ocean dynamics on regional and global climate variability and change patterns, the role of ocean circulation in transporting heat, nutrients, and pollutants. Particular attention is also given to studies on coupled Ocean-Atmosphere modes of variability on various time scales.

    Open for submissions


  • Uncertainties in projected 21st century warming were very large a decade ago, increasing the costs of climate change adaptation, especially those associated with long-lived infrastructure. Here we show that through progress in climate policy and climate science, these uncertainties have decreased dramatically over the past decade.

    • Nathan P. Gillett
    CommentOpen Access
  • The Madden–Julian oscillation (MJO) is a major tropical weather system and one of the largest sources of predictability for subseasonal-to-seasonal weather forecasts. Skillful prediction of the MJO has been a highly active area of research due to its large socio-economic impacts. Silini et al., herein S21, developed a machine learning model to predict the MJO, which they claimed to have an MJO prediction skill of 26–27 days over all seasons and 45 days for December–February (DJF) winter. If true, this would make the skill of their model competitive with that of the state-of-the-art dynamical MJO prediction systems at 20–35 days. However, here we show that the MJO prediction was calculated incorrectly in S21, which spuriously increased the performance of their model. Correctly computed skill of their model was substantially lower than that reported in S21; the skill for all seasons drops to 11–12 days and the skill for forecasts initialized during DJF drops to 15 days. Our findings clarify that the S21 machine learning model is not competitive with state-of-the-art numerical weather prediction models in predicting the MJO.

    • Tamaki Suematsu
    • Zane K. Martin
    • Eric D. Maloney
    CommentOpen Access
  • Population ageing is expected to lead to significant rises in climate risks because vulnerability rises sharply throughout people’s later years. When assessing the vulnerability of older people, however, what’s important isn’t the number of years someone has lived (i.e. “chronological age”) but rather their functional abilities and characteristics; the latter is better captured by remaining life expectancy or “prospective age”. Here, we show that assessing growth in the size of older populations using a prospective rather than chronological age perspective can help avoid overestimates of future risks to climate change. Compared to an analysis based on chronological age, the projected increase in the vulnerable population share seen in the prospective age analysis is considerably lower. The differences between the two perspectives increase with age, decrease with country income level, and are larger in futures that give priority to sustainable development. Thus, while ageing certainly poses major challenges to societies facing climate change, these may be smaller than thought. Prospective age offers a relatively easily implemented alternative for projecting future vulnerability that better accounts for rising longevity.

    • Simon J. Lloyd
    • Erich Striessnig
    • Joan Ballester
    CommentOpen Access
  • Rainfall enhancement has historically been overlooked as a key component of sustainability and climate change adaptation strategies. In this comment, we argue that rainfall enhancement is emerging as a viable contributor to addressing growing water security concerns in a warming climate. We specifically consider current progress and future directions for rainfall enhancement applications based on the experience of the United Arab Emirates (UAE) with its national decade-long operational cloud seeding program and its grant-based international research and development program.

    • Youssef Wehbe
    • Steve Griffiths
    • Abdulla Al Mandous
    CommentOpen Access
  • Due to the greater negative impacts on humans and ecosystems, compound events (CEs) have received increasing attention in China over recent decades. Previous studies mainly considered combinations of frequent hazards (e.g., extreme hot and dry events or heatwaves and extreme precipitation), potentially leading to an inadequate understanding of CEs hotspots, as the occurrence of CEs varies considerably with the diverse hazard types and their temporal sequence (multivariate compound events (MCEs) and temporally compounding events (TCEs)). Here, using daily meteorological observations from 1961 to 2020, we identify 44 CEs types considering the temporal sequences of various hazards from that period and explore their occurrence patterns in China. The results show that 12 CEs types related to extreme hot or dry events widely and frequently (return period < 1 year) occur in China, particularly compound extreme hot-dry-high fire risk events (return period of 0.2–0.4 yrs). Regarding the temporal sequences, MCEs and TCEs have similar spatial distributions, but the magnitudes of MCEs are approximately 1.1 to 2.6 times those of TCEs. This difference is obvious in CEs formed by multiple hazards (>2). By considering occurrence patterns (return period and magnitude), temporal trends, and correlations between different hazards, we determine that the southern humid regions of China are prone to CEs. These results provide a general reference on the national scale for identifying CEs hotspots where more climate action is needed in the future.

    • Xuezheng Zong
    • Yunhe Yin
    • Tong Cui
    EditorialOpen Access
  • Population ageing is one of the most challenging social and economic issues facing governments in the twenty-first century1. Yet the compounding challenges of people living longer while also coping with the impacts of climate change has been subject to less examination. Here, we show that often-used binary definitions of”vulnerable” older communities – such as people over the age of 65 – can lead to the underestimation of future risks from extreme weather in a warming climate. Within this broad grouping, successively older age groups not only exhibit higher vulnerability to the impacts of climate extremes, but they also show more rapid growth in the future. Lower income countries are more likely to underestimate future climate risks if simplistic classifications of vulnerable older communities persist.

    • Luke J. Harrington
    • Friederike E. L. Otto
    CommentOpen Access

Climate and Weather Extremes

Humans and ecosystems struggle to cope with extreme weather and climate conditions. Research into phenomena that are extreme in their rarity, intensity, or both aims to help societies better anticipate and manage the challenges of the most impactful future weather and climate events, be they weeks or decades from now. Extreme weather and events have catastrophic impact on humans and the environment, and their prediction is essential for planning and mitigation preparation. In this Collection, we highlight research looking at extreme events across the globe and their prediction. Extreme events in the Arctic have a disproportionate effect on global climate and weather and there is a Collection addressing this topic specifically.


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