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Pathogens of the enterovirus genus, including poliovirus and coxsackieviruses, typically circulate in the summer months suggesting a possible positive association between warmer weather and transmission. Here we evaluate the environmental and demographic drivers of enterovirus transmission, as well as the implications of climate change for future enterovirus circulation. We leverage pre-vaccination era data on polio in the US as well as data on two enterovirus A serotypes in China and Japan that are known to cause hand, foot, and mouth disease. Using mechanistic modeling and statistical approaches, we find that enterovirus transmission appears positively correlated with temperature although demographic factors, particularly the timing of school semesters, remain important. We use temperature projections from Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate future outbreaks under late 21st-century climate change for Chinese provinces. We find that outbreak size increases with climate change on average, though results differ across climate models depending on the degree of wintertime warming. In the worst-case scenario, we project peak outbreaks in some locations could increase by up to 40%., (© 2024. The Author(s).)

Understanding tropical cyclone (TC) climatology is a problem of profound societal significance and deep scientific interest. The annual cycle is the biggest radiatively forced signal in TC variability, presenting a key test of our understanding and modeling of TC activity. TCs over the North Atlantic (NA) basin, which are usually called hurricanes, have a sharp peak in the annual cycle, with more than half concentrated in only 3 mo (August to October), yet existing theories of TC genesis often predict a much smoother cycle. Here we apply a framework originally developed to study TC response to climate change in which TC genesis is determined by both the number of pre-TC synoptic disturbances (TC "seeds") and the probability of TC genesis from the seeds. The combination of seeds and probability predicts a more consistent hurricane annual cycle, reproducing the compact season, as well as the abrupt increase from July to August in the NA across observations and climate models. The seeds-probability TC genesis framework also successfully captures TC annual cycles in different basins. The concise representation of the climate sensitivity of TCs from the annual cycle to climate change indicates that the framework captures the essential elements of the TC climate connection., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Towards the end of June 2021, temperature records were broken by several degrees Celsius in several cities in the Pacific Northwest areas of the US and Canada, leading to spikes in sudden deaths and sharp increases in emergency calls and hospital visits for heat-related illnesses. Here we present a multi-model, multi-method attribution analysis to investigate the extent to which human-induced climate change has influenced the probability and intensity of extreme heat waves in this region. Based on observations, modelling and a classical statistical approach, the occurrence of a heat wave defined as the maximum daily temperature (TXx) observed in the area 45-52N, 119-123W, was found to be virtually impossible without human-caused climate change. The observed temperatures were so extreme that they lay far outside the range of historical temperature observations. This makes it hard to state with confidence how rare the event was. Using a statistical analysis that assumes that the heat wave is part of the same distribution as previous heat waves in this region led to a first-order estimation of the event frequency of the order of once in 1000 years under current climate conditions. Using this assumption and combining the results from the analysis of climate models and weather observations, we found that such a heat wave event would be at least 150 times less common without human-induced climate change. Also, this heat wave was about 2 C hotter than a 1-in-1000-year heat wave would have been in 1850-1900, when global mean temperatures were 1.2 C cooler than today. Looking into the future, in a world with 2 C of global warming (0.8 C warmer than today), a 1000-year event would be another degree hotter. Our results provide a strong warning: our rapidly warming climate is bringing us into uncharted territory with significant consequences for health, well-being and livelihoods. Adaptation and mitigation are urgently needed to prepare societies for a very different future.

The temporal structure of heat waves having substantial human impact varies widely, with many featuring a compound structure of hot days interspersed with cooler breaks. In contrast, many heat wave definitions employed by meteorologists include a continuous threshold-exceedance duration criterion. This study examines the hazard of these diverse sequences of extreme heat in the present, and their change with global warming. We define compound heat waves to include those periods with additional hot days following short breaks in heat wave duration. We apply these definitions to analyze daily temperature data from observations, NOAA Geophysical Fluid Dynamics Laboratory global climate model simulations of the past and projected climate, and synthetically generated time series. We demonstrate that compound heat waves will constitute a greater proportion of heat wave hazard as the climate warms and suggest an explanation for this phenomenon. This result implies that in order to limit heat-related mortality and morbidity with global warming, there is a need to consider added vulnerability caused by the compounding of heat waves.

Category 4 landfalling hurricane Harvey poured more than a metre of rainfall across the heavily populated Houston area, leading to unprecedented flooding and damage. Although studies have focused on the contribution of anthropogenic climate change to this extreme rainfall event.sup.1-3, limited attention has been paid to the potential effects of urbanization on the hydrometeorology associated with hurricane Harvey. Here we find that urbanization exacerbated not only the flood response but also the storm total rainfall. Using the Weather Research and Forecast model--a numerical model for simulating weather and climate at regional scales--and statistical models, we quantify the contribution of urbanization to rainfall and flooding. Overall, we find that the probability of such extreme flood events across the studied basins increased on average by about 21 times in the period 25-30 August 2017 because of urbanization. The effect of urbanization on storm-induced extreme precipitation and flooding should be more explicitly included in global climate models, and this study highlights its importance when assessing the future risk of such extreme events in highly urbanized coastal areas.Modelling the contribution of urbanization to the impacts associated with hurricane Harvey in August 2017 shows that urbanization worsens rainfall and flooding., Author(s): Wei Zhang [sup.1] , Gabriele Villarini [sup.1] , Gabriel A. Vecchi [sup.2] [sup.3] , James A. Smith [sup.4] Author Affiliations:(1) IIHR-Hydroscience & Engineering, The University of Iowa, Iowa City, [...]

The response of tropical cyclone (TC) frequency to sea surface warming is uncertain in climate models. We hypothesize that one source of uncertainty is the anomalies of large-scale atmospheric radiation in response to climate change, and whose influence on TC frequency is investigated. Given two atmospheric models with opposite TC frequency responses to uniform sea surface warming, we interchange their atmospheric radiation anomalies in experiments with prescribed radiative heating rates. The largest model discrepancy occurs in the western North Pacific, where the TC frequency tends to increase with anomalous large-scale ascent caused by prescribed positive radiation anomalies, while the TC frequency tends to decrease with anomalous large-scale descent caused by prescribed negative radiation anomalies. The model spread in TC frequency response is approximated by the model spread in the frequency response of pre-TC vortices (seeds), which is explained by changes in the large-scale circulation using a downscaling formula known as the seed propensity index. We further generalize the index to predict the influence of large-scale radiation anomalies on TC seed frequency. The results show that model spread in TC and seed frequency response can be reduced when constraining the large-scale radiation anomalies. Significance Statement: It is difficult to predict whether tropical cyclones will occur more or less frequently in the future and by how much. We show that tropical cyclone frequency is strongly influenced by the global pattern of heating and cooling due to radiation, a process that has been neglected in existing theories. Our theory improves understanding of how tropical cyclones respond to climate change, explaining why one model may predict a frequency increase while a different but equally realistic model may predict a frequency decrease. One reason for the difficulty in predicting tropical cyclone frequency is found to be the difficulty in predicting how global cloud distribution will change in the future. [ABSTRACT FROM AUTHOR]