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We studied the potential synergy between air pollution and meteorology and their impact on mortality in nine European cities with data from 2004 to 2010. We used daily series of Apparent Temperature (AT), measurements of particulate matter (PM10), ozone (O3), and nitrogen dioxide (NO2) and total non-accidental, cardiovascular, and respiratory deaths. We applied Poisson regression for city-specific analysis and random effects meta-analysis to combine city-specific results, separately for the warm and cold seasons. In the warm season, the percentage increase in all deaths from natural causes per °C increase in AT tended to be greater during high ozone days, although this was only significant for all ages when all causes were considered. On low ozone days, the increase in the total daily number of deaths was 1.84% (95% CI 0.87, 2.82), whilst it was 2.20% (95% CI 1.28, 3.13) in the high ozone days per 1 °C increase in AT. Interaction with PM10 was significant for cardiovascular (CVD) causes of death for all ages (2.24% on low PM10 days (95% CI 1.01, 3.47) whilst it is 2.63% (95% CI 1.57, 3.71) on high PM10 days) and for ages 75+. In days with heat waves, no consistent pattern of interaction was observed. For the cold period, no evidence for synergy was found. In conclusion, some evidence of interactive effects between hot temperature and the levels of ozone and PM10 was found, but no consistent synergy could be identified during the cold season.

The perinatal period is a time of increased vulnerability for perinatal mood and anxiety disorders (PMADs). Emotional trauma is a risk factor for PMAD development and is common among survivors of extreme weather events (EWEs), which are becoming more frequent and intense as the climate crisis progresses. EWE-related stress and anxiety have not been extensively studied in the perinatal population. However, the limited available data suggest a negative impact of EWE exposure on perinatal mental health, warranting further investigation and investment. To address this knowledge gap, we interviewed new Australian mothers to understand how EWEs affect the mental health of the perinatal population. Australian mothers (18 years of age or older) with a baby under 12 months of age were recruited to participate in a single virtual focus group session (seven group sessions were run in total) and complete an anonymous survey. Participants were asked questions regarding their concerns about extreme weather and its impact, as well as their general maternal functioning. Maternal functioning, depression, and climate distress were measured via the survey. The study sample comprised 31 Australian mothers ( = 31.74,  = 4.86), predominantly located in Queensland. Findings from the focus groups suggested six key themes; however, of focus to this study are three themes related to maternal mental health: health and well-being, helplessness and avoidant coping, and resilience and adaptation. Predominant subthemes focused on trauma resulting from EWE exposure, economic and heat concerns, social isolation, hopelessness about the future, and feelings of resilience. The evidence linking adverse perinatal mental health outcomes with climate change and EWEs highlights the urgent need for interventions in this context to protect perinatal mental health and well-being. By acknowledging the traumatic impact of these experiences on mothers, this study supports advocacy for policies that specifically address this issue.

Introduction The effects of climate change and extreme weather events on the health system are becoming unbearable globally. We conducted a health policy analysis to understand the health system’s response strategies to the effects of climate change extreme weather events in Malawi and identified implementation response challenges for improvement. Methods The policy triangle model was used to analyze health system policies. A list of policies was obtained from the Department of Policy, Planning, and Development at the Ministry of Health. We retrieved the policies from the Ministry of Health Website, and hard copies were obtained for those not published online. A data extraction form was created to capture all climate change-related issues, which were grouped according to the policy triangle model, including context, content, process, and actors. We further identified implementation challenges to climate change. Results In total, we obtained 32 health policy documents from the Department of Planning at the Ministry of Health that were screened for climate change-related issues. Out of these, only three had climate change-related themes and strategies. Guided by the policy triangle framework, we present our findings under five themes: policy context, policy contents, policy process, actors, and the implementation gaps. Contextually, the policies were aligned with both local and international goals. The contents of the analyzed policies have climate change thematic areas and strategies not specific to health system improvement. The process involved situation analysis and consultations with both national and international stakeholders. The actors involved included government ministries, local councils, development partners, community leaders, and global organizations. Some of the implementation challenges include a lack of health system-specific climate change strategies and guidelines, a lack of clear funding mechanisms, limited consideration of local knowledge, and a lack of capacity building strategies among health workers. Conclusion The health system in Malawi is moving in the right direction to minimize the effects of climate change extreme weather events on health. The availability of climate change thematic areas, objectives, and strategies in the analyzed health policies shows that some efforts are being made to address the effects climate change extreme weather events in the country. We recommend developing climate change-specific health policies with clear strategies and financing mechanisms.

The last few years have seen an explosion of interest in extreme event attribution, the science of estimating the influence of human activities or other factors on the probability and other characteristics of an observed extreme weather or climate event. This is driven by public interest, but also has practical applications in decision-making after the event and for raising awareness of current and future climate change impacts. The World Weather Attribution (WWA) collaboration has over the last 5 years developed a methodology to answer these questions in a scientifically rigorous way in the immediate wake of the event when the information is most in demand. This methodology has been developed in the practice of investigating the role of climate change in two dozen extreme events world-wide. In this paper, we highlight the lessons learned through this experience. The methodology itself is documented in a more extensive companion paper. It covers all steps in the attribution process: the event choice and definition, collecting and assessing observations and estimating probability and trends from these, climate model evaluation, estimating modelled hazard trends and their significance, synthesis of the attribution of the hazard, assessment of trends in vulnerability and exposure, and communication. Here, we discuss how each of these steps entails choices that may affect the results, the common problems that can occur and how robust conclusions can (or cannot) be derived from the analysis. Some of these developments also apply to other attribution methodologies and indeed to other problems in climate science.

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’.

Climate change is a major source of concern in the Middle East and North Africa (MENA) region, and migration is often understood as one of several strategies used by households to respond to changes in climate and environmental conditions, including extreme weather events. This study focuses on the link between climate change and migration. Most micro-level studies measure climate change either by the incidences of extreme weather events or by variation in temperature or rainfall. A few studies have found that formal and informal institutions as well as policies also affect migration. Institutions that make government more responsive to households (for example through public spending) discourage both international and domestic migration in the aftermath of extreme weather events. Migration is often an option of last resort after vulnerable rural populations attempting to cope with new and challenging circumstances have exhausted other options such as eating less, selling assets, or removing children from school. This study is based in large part on new data collected in 2011 in Algeria, Egypt, Morocco, Syria, and the Republic of Yemen. The surveys were administered by in-country partners to a randomly selected set of 800 households per country. It is also important to emphasize that neither the household survey results nor the findings from the qualitative focus groups are meant to be representative of the five countries in which the work was carried, since only a few areas were surveyed in each country. This report is organized as follows: section one gives synthesis. Section two discusses household perceptions about climate change and extreme weather events. Section three focuses on migration as a coping mechanisms and income diversification strategy. Section four examines other coping and adaptation strategies. Section five discusses perceptions about government and community programs.

In July 2021 extreme rainfall across Western Europe caused severe flooding and substantial impacts, including over 200 fatalities and extensive infrastructure damage within Germany and the Benelux countries. After the event, a hydrological assessment and a probabilistic event attribution analysis of rainfall data were initiated and complemented by discussing the vulnerability and exposure context. The global mean surface temperature (GMST) served as a covariate in a generalised extreme value distribution fitted to observational and model data, exploiting the dependence on GMST to estimate how anthropogenic climate change affects the likelihood and severity of extreme events. Rainfall accumulations in Ahr/Erft and the Belgian Meuse catchment vastly exceeded previous observed records. In regions of that limited size the robust estimation of return values and the detection and attribution of rainfall trends are challenging. However, for the larger Western European region it was found that, under current climate conditions, on average one rainfall event of this magnitude can be expected every 400 years at any given location. Consequently, within the entire region, events of similar magnitude are expected to occur more frequently than once in 400 years. Anthropogenic climate change has already increased the intensity of the maximum 1-day rainfall event in the summer season by 3–19 %. The likelihood of such an event to occur today compared to a 1.2 ∘C cooler climate has increased by a factor of 1.2–9. Models indicate that intensity and frequency of such events will further increase with future global warming. While attribution of small-scale events remains challenging, this study shows that there is a robust increase in the likelihood and severity of rainfall events such as the ones causing extreme impacts in July 2021 when considering a larger region.

This book takes both a global as well as a local perspective in assessing the impacts of climate change on the economy, agricultural sector, and households in three of the MENA countries; Syria, Tunisia and Yemen. The major channels of impact for global climate change are through changing world food (and energy) prices, especially since all the countries under analysis are or have become net importers of oil and petroleum products and many food commodities in recent years. The impacts of local climate change decrease crop yields in the longer run and through them, productivity in the agricultural sector and all the implications this may have on both, the livelihoods of those dependent on the sector as well as the rest of the economy. The analysis also covered what happens when both global and local climate changes work simultaneously for each country. Findings show that in all three countries the effects of climate change are negative for people and the economy-GDP falls and livelihoods suffer. Furthermore, the prevalence of extreme variations in climate-such as the droughts affecting Syria and the floods impacting Yemen-draws attention to the potentially significant drawbacks that are likely to not only affect any strides towards economic growth and development, but may also reverse such strides if appropriate policies are not in place to weather this storm. The analyses in this book apply CGE models.

An important and under-quantified facet of the risks associated with human-induced climate change emerges through extreme weather. In this paper, we present an initial attempt to quantify recent costs related to extreme weather due to human interference in the climate system, focusing on economic costs arising from droughts and floods in New Zealand during the decade 2007–2017. We calculate these using previously collected information about the damages and losses associated with past floods and droughts, and estimates of the “fraction of attributable risk” that characterizes each event. The estimates we obtain are not comprehensive, and almost certainly represent an underestimate of the full economic costs of climate change, notably chronic costs associated with long-term trends. However, the paper shows the potential for developing a new stream of information that is relevant to a range of stakeholders and research communities, especially those with an interest in the aggregation of the costs of climate change or the identification of specific costs associated with potential liability.

Quantile mapping bias correction algorithms are commonly used to correct systematic distributional biases in precipitation outputs from climate models. Although they are effective at removing historical biases relative to observations, it has been found that quantile mapping can artificially corrupt future model-projected trends. Previous studies on the modification of precipitation trends by quantile mapping have focused on mean quantities, with less attention paid to extremes. This article investigates the extent to which quantile mapping algorithms modify global climate model (GCM) trends in mean precipitation and precipitation extremes indices. First, a bias correction algorithm, quantile delta mapping (QDM), that explicitly preserves relative changes in precipitation quantiles is presented. QDM is compared on synthetic data with detrended quantile mapping (DQM), which is designed to preserve trends in the mean, and with standard quantile mapping (QM). Next, methods are applied to phase 5 of the Coupled Model Intercomparison Project (CMIP5) daily precipitation projections over Canada. Performance is assessed based on precipitation extremes indices and results from a generalized extreme value analysis applied to annual precipitation maxima. QM can inflate the magnitude of relative trends in precipitation extremes with respect to the raw GCM, often substantially, as compared to DQM and especially QDM. The degree of corruption in the GCM trends by QM is particularly large for changes in long period return values. By the 2080s, relative changes in excess of +500% with respect to historical conditions are noted at some locations for 20-yr return values, with maximum changes by DQM and QDM nearing +240% and +140%, respectively, whereas raw GCM changes are never projected to exceed +120%.