This paper presents a series of responses from Western Australian based artists and scholars from a range of disciplines including: meteorology, science, education, social work, psychology, art and performance studies, to a year-long exhibition titled Forecast in Gallery 09 at The Art Gallery of Western Australia (AGWA). Forecast is a collaboration between AGWA’s Head of Learning and Creativity Research, Lilly Blue, Edith Cowan University’s Centre for People, Place and Planet artist-scholar, Jo Pollitt, together with artists Dianne Jones and Eva Fernández. The exhibition invites audiences to contribute to two participatory works: Weather Patterns, a daily changing installation that makes room for slow feeling, attention and care at a time of rising eco-anxiety and climate grief, and Disappearing Forests, which encourages participants to paint evaporating treescapes with water. Forecast was the stimulus for a discussion among and between interdisciplinary artists and scholars in reflecting on extreme weather, resilience building and the arts. This article proposes the embodied and participatory methods of the exhibition as a model for engaging in feeling with and responding to the climate crisis. Each of the responses draw on the exhibition to consider the ways in which Forecast in its negotiation of weather states opens up questions of response and responsibility, of time, pace and scale and, ultimately, how the exhibition invites audiences to engage in a process of slow feeling as they participate in and reflect on their experience of weather in the exhibition.

Fasciola hepatica infections in cattle often lead to significant production losses. Infection rates are expected to increase due to environmental changes at regional and global level which favour the life cycle of F. hepatica. This study aimed to identify environmental and herd factors associated with F. hepatica antibody positivity in bulk tank milk (BTM) of Dutch dairy cattle herds. In total, 10403 BTM samples were collected yearly in October, from 2018 till 2023. For each farm, monthly averages of weather factors and soil moisture level were obtained for the twelve months preceding October, along with soil type and number and grazing of dairy cows. Logistic regression analyses were performed retrospectively using generalized estimating equations, with continuous variables analysed as quartiles. The odds of F. hepatica antibody positivity in BTM are higher for farms on peat (OR 1.69, 95% CI [1.27, 2.24]) and heavy clay soils (OR 1.75, 95% CI [1.30, 2.35]) compared to those on sand soil. In addition, the odds of antibody positivity increased with higher monthly temperatures (December: ORQ1-Q4 2.94, 95% CI [1.94, 4.46]) and rainfall (November: ORQ1-Q4 2.33, 95% CI [1.62, 3.34]) at the end of the previous grazing season. Stratified analyses by soil type yielded results consistent with those across soil types. Weather patterns that favour the number of overwintering snails infected with F. hepatica seem to increase the infection risk for dairy cattle in the next grazing season, which highlights the potential of prediction tools that facilitate early detection of new F. hepatica infections.

Using novel nighttime lights and high-resolution atmospheric reanalysis, this paper exploits exogenous fluctuations in temperature and precipitation to identify the causal effects of weather disturbances on local economic growth in the Philippines – the world’s most disaster-prone country. Our findings reveal that heightened temperature variability significantly dampens growth, but only in poor municipalities. This effect persists for at least 2 years after the initial shock. Furthermore, the relationship between weather shocks and growth is nonlinear. We also demonstrate that adverse weather events impede growth by disrupting agricultural productivity and essential service sectors, including wholesale and retail trade, health and education. Overall, our results highlight the importance of understanding the distributional impact of climate change within countries, its underlying mechanisms, and how economic development policies can help shield poor municipalities from the vagaries of the weather.

Stochastic generators are useful for estimating climate impacts on various sectors. Projecting climate risk in various sectors, e.g. energy systems, requires generators that are accurate (statistical resemblance to ground-truth), reliable (do not produce erroneous examples), and efficient. Leveraging data from the North American Land Data Assimilation System, we introduce TemperatureGAN, a Generative Adversarial Network conditioned on months, regions, and time periods, to generate 2 m above ground atmospheric temperatures at an hourly resolution. We propose evaluation methods and metrics to measure the quality of generated samples. We show that TemperatureGAN produces high-fidelity examples with good spatial representation and temporal dynamics consistent with known diurnal cycles.

Legionellosis is a respiratory infection caused by Legionella sp. that is found in water and soil. Infection may cause pneumonia (Legionnaires’ Disease) and a milder form (Pontiac Fever). Legionella colonizes water systems and results in exposure by inhalation of aerosolized bacteria. The incubation period ranges from 2 to 14 days. Precipitation and humidity may be associated with increased risk. We used Medicare records from 1999 to 2020 to identify hospitalizations for legionellosis. Precipitation, temperature, and relative humidity were obtained from the PRISM Climate Group for the zip code of residence. We used a time-stratified bi-directional case-crossover design with lags of 20 days. Data were analyzed using conditional logistic regression and distributed lag non-linear models. A total of 37 883 hospitalizations were identified. Precipitation and relative humidity at lags 8 through 13 days were associated with an increased risk of legionellosis. The strongest association was precipitation at day 10 lag (OR = 1.08, 95% CI = 1.05–1.11 per 1 cm). Over 20 days, 3 cm of precipitation increased the odds of legionellosis over four times. The association was strongest in the Northeast and Midwest and during summer and fall. Precipitation and humidity were associated with hospitalization among Medicare recipients for legionellosis at lags consistent with the incubation period for infection.

Recent advances in clinical prediction for diarrhoeal aetiology in low- and middle-income countries have revealed that the addition of weather data to clinical data improves predictive performance. However, the optimal source of weather data remains unclear. We aim to compare the use of model estimated satellite- and ground-based observational data with weather station directly observed data for the prediction of aetiology of diarrhoea. We used clinical and etiological data from a large multi-centre study of children with moderate to severe diarrhoea cases to compare their predictive performances. We show that the two sources of weather conditions perform similarly in most locations. We conclude that while model estimated data is a viable, scalable tool for public health interventions and disease prediction, given its ease of access, directly observed weather station data is likely adequate for the prediction of diarrhoeal aetiology in children in low- and middle-income countries.

In this article, we examine how weather variables affect markets for U.S. high-end wines, both luxury wines and wines from the same region that are still high-end but not in the very limited highest category. Specifically, we compare so-called “cult wines” with “non-cult wines” from the same subregions that are known for their high-quality wines. We investigate associations between weather conditions and prices, price gaps (the difference between the secondary market price and release price), the number of cases produced, and wine scores assigned for both cult and non-cult wines. We further examine whether associations with weather differ across wine regions. Implementing a fixed-effects methodology, cult and non-cult wines from three U.S. regions were studied: both Napa and Sonoma in California, and Walla Walla on the border of Washington State and Oregon. Overall, the analysis suggests that weather is associated with various characteristics of wine markets, including prices, price gaps for cult wines, wine scores, and cases produced. The nature of the associations depends on the type of wine (cult or non-cult, red or white) and timing of weather conditions throughout the year and growing region.

Welfare is being promoted as a reason why ostriches should not be kept on farms in Europe. It is reasoned that the climate, particularly during winter, is unsuitable for these birds despite there being little scientific evidence to support this claim. This study recorded the frequency of behaviours of male and female adult ostriches kept on a farm in Britain during the spring of 1996. ‘Rainy’, ‘dull and dry’, ‘bright and dry’, and ‘sunny’ weather categories were used to assess the influence of climate on behaviour. Six main behaviours (sitting, standing, pacing, walking, foraging and feeding) were observed together with a variety of low frequency ‘other’ behaviours which were combined for analysis. Gender had no significant effect on any of the behaviour frequencies. During ‘rainy’ periods both males and females showed sitting behaviour five times more than during ‘dull’ and ‘bright’ weather and two and a half times more than during ‘sunny’ weather. Increased sitting behaviour during rainy periods was due to a significant reduction in pacing and ‘other’ behaviours with no significant effect on feeding and foraging behaviours. Sitting during sunny weather also occurred more often than during dull and bright weather but not at the expense of any other particular behaviour. Adult ostriches in Britain alter their behaviour in response to prevailing weather conditions, particularly rain.