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Purpose: We examined fluid intake, the relation between body mass (BM) loss and performance, and core temperature in young triathletes during a competition in tropical climate. Methods: Fluid intake and pre and post BM were measured in 35 adolescent athletes, and core temperature was measured in one female and one male. Results: Mean urine specific gravity (1.024 [0.007]) indicated that athletes were in suboptimal state of hydration upon waking. Race time was 73.2 (8.0) minutes. BM decreased by 0.6 (0.3) kg (P <.05). Fluid intake (528.5 [221.6] mL) replaced 47% of the fluid loss (1184.9 [256.4] mL) and was higher during run (11.5 [6.6] mL·min−1) compared to bike (7.3 [3.1] mL·min−1), P <.01. Loss in BM was ≥1.0% in 66% and ≥1.5% in 29% of the athletes. Males showed a moderate association between percentage loss in BM and finishing time (r = −.52), higher sweat rates (1.0 [0.3] L·h−1), and faster times (69.4 [7.5] min; P <.05). Core temperature rose to 40.1 °C in the female and 39.6 °C in the male. Conclusion: Young triathletes competing in a hot/humid climate became mildly to moderately dehydrated and hyperthermic even when water and sports drinks were available but did not show symptoms of heat illness. [ABSTRACT FROM AUTHOR]

Purpose: To assess elite racewalkers' preparation strategies, knowledge, and general practices for competition in the heat and their health status during the World Athletics Race Walking Teams Championships (WRW) Muscat 2022. Methods: Sixty-six elite racewalkers (male: n = 42; mean age = 25.8 y) completed an online survey prior to WRW Muscat 2022. Athletes were grouped by sex (males vs females) and climate (self-reported) they live/trained in (hot vs temperate/cold), with differences/relationships between groups assessed. Relationships between ranking (medalist/top 10 vs nonmedalist/nontop 10) and precompetition use of heat acclimation/acclimatization (HA) were assessed. Results: All surveyed medalists (n = 4) implemented, and top 10 finishers were more likely to report using (P =.049; OR = 0.25; 95% CI, 0.06%–1%), HA before the championships. Forty-three percent of athletes did not complete specific HA training. Females (8% [males 31%]) were less likely to have measured core temperature (P =.049; OR = 0.2; 95% CI, 0.041–0.99) and more likely to not know expected conditions in Muscat (42% vs 14%; P =.016; OR = 4.3; 95% CI, 1%–14%) or what wet bulb globe temperature is (83% vs 55%; P =.024; OR = 4.1; 95% CI, 1%–14%). Conclusions: Athletes who implemented HA before the championships tended to place better than those who did not. Forty-three percent of athletes did not prepare for the expected hot conditions at the WRW Muscat 2022, primarily attributed to challenges in accessing and/or cost of equipment/facilities for HA strategies. Further efforts to bridge the gap between research and practice in this elite sport are needed, particularly in female athletes. [ABSTRACT FROM AUTHOR]

It has been shown that a proxy determination of the magnetospheric open-closed magnetic field line boundary (OCB) location can be made by examining the ultra-low-frequency (ULF) wave power in magnetometer data, with particular interest in the Pc5 ULF waves with periods of 3-10 min. In this study, we present a climatology of such Pc5 ULF waves using groundbased magnetometer data from the South Pole Station (SPA), McMurdo (MCM) station, and the Automatic Geophysical Observatories (AGOs) located across the Antarctic continent, to infer OCB behavior and variability during geomagnetically quiet times (i.e., Ap < 30 nT). For each season [i.e., austral fall (20 February 2017-20 April 2017), austral winter (20 May 2017-20 July 2017), austral spring (20 August 2017-20 October 2017), and austral summer (20 November 2017-20 January 2018)], north-south (i.e., H-component) magnetic field line residual power-spectral density (PSD) measurements taken during geomagnetically quiet periods within a 60-day window centered at the austral solstice/equinox are averaged in 10-min temporal bins to form the climatology at each station. These residual PSDs thus enable the analysis of Pc5 activity (and lower period "long-band" oscillations) and, thus, OCB location/variability as a function of season and magnetic latitude. The dawn and dusk transitions across the OCB are analyzed, with a discussion of dawn and dusk variability during nominally quiet geomagnetic periods. In addition, latitudinal dependencies of the OCB and peak Pc5 periods at each station are discussed, along with the empirical Tsyganenko model comparisons to our site measurements. [ABSTRACT FROM AUTHOR]

The models that participated in the Coupled Model Intercomparison Project (CMIP) exhibit large biases in Arctic sea ice climatology that seem related to biases in seasonal atmospheric and oceanic circulations. Using historical runs of 34 CMIP6 models from 1979 to 2014, we investigate the links between the climatological sea ice concentration (SIC) biases in September and atmospheric and oceanic model climatologies. The main intermodel spread of September SIC is well described by two leading EOFs, which together explain ∼65% of its variance. The first EOF represents an underestimation or overestimation of SIC in the whole Arctic, while the second EOF describes opposite SIC biases in the Atlantic and Pacific sectors. Regression analysis indicates that the two SIC modes are closely related to departures from the multimodel mean of Arctic surface heat fluxes during summer, primarily shortwave and longwave radiation, with incoming Atlantic Water playing a role in the Atlantic sector. Local and global links with summer cloud cover, low-level humidity, upper or lower troposphere temperature/circulation, and oceanic variables are also found. As illustrated for three climate models, the local relationships with the SIC biases are mostly similar in the Arctic across the models but show varying degrees of Atlantic inflow influence. On a global scale, a strong influence of the summer atmospheric circulation on September SIC is suggested for one of the three models, while the atmospheric influence is primarily via thermodynamics in the other two. Clear links to the North Atlantic oceanic circulation are seen in one of the models. [ABSTRACT FROM AUTHOR]

By decomposing the total sea surface current into its geostrophic and ageostrophic components, we examined the contribution of each to the long-term variability of the total sea surface current. Our findings demonstrate the importance of geostrophic currents in Baltic Sea gyre formations. Additionally, ageostrophic currents contribute significantly to the flow across the region. Quantifying the difference between total sea surface current fields has revealed two dominant general sea surface circulation patterns in the Baltic Sea, whose characteristics correspond to the monthly mean climatology of sea surface current fields in May and December. Subsequently, a machine learning technique was employed to effectively detect the types of sea surface circulation patterns using wind vectors and sea level anomaly fields. This underscored the combined influence of sea level anomaly-driven and wind-driven components in shaping surface current vectors in the Baltic Sea, consistent with geostrophic and ageostrophic decompositions. [ABSTRACT FROM AUTHOR]

The participation of a diverse --in terms of geography, discipline and gender-- group of Early Career Researchers (ECRs) in the peer review process can help alleviate the workload of senior researchers and counteract the perceptual biases that the latter tend to show. Moreover, ECRs can benefit from developing skills that are often not included in educational programs. From 2018 to 2021, the Association of Polar Early Career Scientists, in collaboration with other associations, organized six group reviews of the Intergovernmental Panel on Climate Change (IPCC) reports by a total of more than 600 ECRs from over 70 different countries. This study aims to evaluate this group review in terms of its contribution to the production of scientific knowledge, and as a career development opportunity for ECRs. The data analyzed consists of application forms, review comments, and feedback surveys that were collected during each review process. The results of this study show that, overall, the group reviews were a success in terms of the experience of ECRs and their contribution to the peer review of the IPCC reports. Most survey respondents considered the general organization of the group reviews satisfactory and expressed interest in participating in future group reviews. However, most participants did not engage in discussions with their peers, which constitutes a missed opportunity to engage in active learning and the shared production of knowledge. ECRs made a significant contribution to the review of the IPCC reports by producing an average of 2,422 ± 532 comments per group review, 36% of which were substantive. PhD students were shown to be as proficient reviewers as postdoctoral researchers and faculty reviewers. More importantly, the diversity of reviewers in terms of geography and discipline, together with the fact that they are ECRs, can help produce more balanced scientific reports since they bring new perspectives, thus counteracting the biases that senior researchers have. These group reviews could be improved by providing more comprehensive training and facilitating communication among reviewers so that they can engage in meaningful exchanges. We conclude that the IPCC should formalize the inclusion of ECRs in future reviews of the IPCC reports. [ABSTRACT FROM AUTHOR]

Brown algae (Phaeophyceae) dominate intertidal and shallow subtidal areas globally, where larger species form extensive underwater forests. These structurally complex and highly productive habitats enhance local biodiversity and support food webs in coastal areas through secondary production, thereby shaping local oceanography and ecology. Macroalgal aquaculture is an important and growing sector, where approximately 40% of all cultivated algae belong to Phaeophyceae. However, both cultured and natural brown algae have been under increasing pressure due to climate-driven factors, such as ocean warming, eutrophication, and herbivore outbreaks. We conducted a comprehensive literature review on abiotic (temperature, light intensity, and UV radiation, nutrients, water motion, salinity, and substrata and sediment) and biotic (bacteria, viruses, fungi, eukaryotic endophytes and endoparasites, epiphytes, and grazers) stressors and illnesses in marine brown macroalgae, as well as brown algae defense mechanisms, and discuss how these parameters may affect the production of a sustainable crop for the aquaculture industry under future climate change scenarios. [ABSTRACT FROM AUTHOR]

Climate variability in the growing season is well suited for testing adaptation measures. Adaptation to adverse events, such as heatwaves and droughts, increases the capacity of players in agri-food systems, not only producers but also transporters and food manufacturers, to prepare for production disruptions due to seasonal extremes and climate change. Climate impact models (e.g., crop models) can be used to develop adaptation responses. To run these models, historical records and climate forecasts need to be combined as a single daily time series. We introduce the daily 0.5° global hybrid reanalysis-forecast meteorological forcing dataset from 2010 to 2021. The dataset consists of the Japanese 55-yr Reanalysis (JRA55) and the Japan Meteorological Agency/Meteorological Research Institute Coupled Prediction System version 2 (JMA/MRI-CPS2) 5-member ensemble forecast. Both are bias-corrected using the Delta method and integrated with a baseline climatology derived from the Environmental Research and Technology Development Fund's Strategic Research 14 Meteorological Forcing Dataset (S14FD). The dataset is called JCDS (JRA55-CPS2-Delta-S14FD) and offers a framework for monitoring and forecasting applications towards adaptation. [ABSTRACT FROM AUTHOR]

Does repeated exposure to climate-skeptic claims influence their acceptance as true, even among climate science endorsers? Research with general knowledge claims shows that repeated exposure to a claim increases its perceived truth when it is encountered again. However, motivated cognition research suggests that people primarily endorse what they already believe. Across two experiments, climate science endorsers were more likely to believe claims that were consistent with their prior beliefs, but repeated exposure increased perceptions of truth for climate-science and climate-skeptic claims to a similar extent. Even counter-attitudinal claims benefit from previous exposure, highlighting the insidious effect of repetition. [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) are powerful weather systems that can cause extreme disasters. The International Best Track Archive for Climate Stewardship (IBTrACS) dataset has been used extensively to estimate TC climatology. However, it has low data coverage, lacking intensity and outer size data for more than half of all recorded storms, and is therefore insufficient as a reference for researchers and decision makers. To fill this data gap, we reconstructed a long-term TC dataset by integrating IBTrACS and European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) data. This new dataset covers the period 1959–2022, with 3 h temporal resolution. Compared to the IBTrACS dataset, it contains approximately 3–4 times more data points per characteristic. We established machine learning models to estimate the maximum sustained wind speed (Vmax) and radius to maximum wind speed (Rmax) in six basins for which TCs were generated using ERA5-derived 10 m azimuthal median azimuthal wind profiles as input, with Vmax and Rmax data from the IBTrACS dataset used as training data. An empirical wind–pressure relationship and six wind profile models were employed to estimate the minimum central pressure (Pmin) and outer size of the TCs, respectively. Overall, this high-resolution TC reconstruction dataset demonstrated global consistency with observations, exhibiting mean biases of <1 % for Vmax and 3 % for Rmax and Pmin in almost all basins. The new dataset is publicly available from https://doi.org/10.5281/zenodo.12740372 (Xu et al., 2024) and significantly advances our understanding of TC climatology, thereby facilitating risk assessments and defenses against TC-related disasters. [ABSTRACT FROM AUTHOR]

Background: Research on climatic parameters contributing to psychiatric disorder seasonality is limited, particularly in subtropical, arid climates like Rajasthan, necessitating investigation into seasonal variations in psychiatric disorder incidence in the region. This study investigates seasonal variations in psychiatric disorder prevalence over 2 years at a Rajasthan tertiary healthcare center, aiming to uncover links with climatic factors. Aims: To investigate seasonal variations in the utilization of outpatient psychiatry services and elucidate potential determinants contributing to these temporal variations. Settings and Design: This is a hospital-based study. A retrospective chart review of all new patients who utilized psychiatry outpatient services from July 2021 to July 2023 was conducted. Methods and Material: Data were gathered from psychiatric outpatient records of adults (July 2021 to July 2023), diagnosed using ICD-10. Seasons were categorized: winter (November-January), spring (February-April), summer (May-July), and rainy (August-October). Meteorological data, temperature, and day length were obtained. Statistical analyses, including Pearson correlation and Chi-square fitness, assessed seasonal associations with psychiatric disorders. Results: A total of 29,164 patient records were observed. Depression correlated with temperature and photoperiod. Mania peaked in August, linked to day length. Schizophrenia showed seasonal variation without environmental correlation. Anxiety peaked in March with no statistical significance. Obsessive compulsive disorder cases spiked in June, moderately correlated with temperature and photoperiod. Alcohol-related disorders peaked in December, while opioid dependence remained steady. Cannabis-induced psychosis peaked in summer, strongly correlated with temperature and day length. Headaches surged in August, positively correlated with temperature and day length. Conclusions: This study reveals complex relationships between seasonality, environmental factors, and psychiatric disorders, emphasizing their importance in mental health research and practice. [ABSTRACT FROM AUTHOR]

In the 20th century, Australia's Great Barrier Reef emerged as a political battleground when governing bodies planned to turn its coral territories into a vast mining zone. But in the 21st century, as the temporalisation of the Reef exerts increasing influence on the governance, securitisation and anticipation of planetary futures, coral time has emerged as a new site of political and imaginative conflict. Responding to this shift from territory to temporality, how can we pay closer attention to those skilfully making coral time? In this article, I introduce 'dimensional friction' as a tool for considering how the temporal structure of corals intersects with the temporal structure of global climate science in a coring laboratory. Based on my fieldwork at the Australian Institute of Marine Science, I analyse simultaneously discursive, technical, and imaginative problems that emerge when scientists transform the mineral skeletons of corals into time data. Dimensional friction appears whenever this skeletal matter is manipulated, surfacing the lab-based production of vertical time-depth but also suggesting other ways of temporalising (and corporally appropriating) coral time. Viewed in this way, coral cores might be better understood as 'temporal volumes' rather than chronostratigraphic records amenable to linear timelines and trajectories. [ABSTRACT FROM AUTHOR]

Aerosol–cloud interactions play a crucial role in shaping Earth's climate and hydrological cycle. Observing these interactions with high precision and accuracy is of the utmost importance for improving climate models and predicting Earth's climate. Over the past few decades, lidar techniques have emerged as powerful tools for investigating aerosol–cloud interactions due to their ability to provide detailed vertical profiles of aerosol particles and clouds with high spatial and temporal resolutions. This review paper provides an overview of recent advancements in the study of ACI using lidar techniques. The paper begins with a description of the different cloud microphysical processes that are affected by the presence of aerosol, and with an outline of lidar remote sensing application in characterizing aerosol particles and clouds. The subsequent sections delve into the key findings and insights gained from lidar-based studies of aerosol–cloud interactions. This includes investigations into the role of aerosol particles in cloud formation, evolution, and microphysical properties. Finally, the review concludes with an outlook on future research. By reporting the latest findings and methodologies, this review aims to provide valuable insights for researchers engaged in climate science and atmospheric research. [ABSTRACT FROM AUTHOR]

Species are often expected to shift their distributions either poleward or upslope to evade warming climates and colonise new suitable climatic niches. However, from 18‐years of fixed transect monitoring data on 88 species of butterfly in the midwestern United States, we show that butterflies are shifting their centroids in all directions, except towards regions that are warming the fastest (southeast).Butterflies shifted their centroids at a mean rate of 4.87 km year−1. The rate of centroid shift was significantly associated with local climate change velocity (temperature by precipitation interaction), but not with mean climate change velocity throughout the species' ranges.Species tended to shift their centroids at a faster rate towards regions that are warming at slower velocities but increasing in precipitation velocity.Surprisingly, species' thermal niche breadth (range of climates butterflies experience throughout their distribution) and wingspan (often used as metric for dispersal capability) were not correlated with the rate at which species shifted their ranges.We observed high phylogenetic signal in the direction species shifted their centroids. However, we found no phylogenetic signal in the rate species shifted their centroids, suggesting less conserved processes determine the rate of range shift than the direction species shift their ranges.This research shows important signatures of multidirectional range shifts (latitudinal and longitudinal) and uniquely shows that local climate change velocities are more important in driving range shifts than the mean climate change velocity throughout a species' entire range. [ABSTRACT FROM AUTHOR]

This study introduces new insights into the climatology of South Atlantic (SAt) cyclones by employing a novel cyclone life cycle detection method, the CycloPhaser. Utilizing the minimum relative vorticity series and its derivative at the cyclone centre, the program effectively identifies distinct phases in the cyclone life cycle. Cyclone tracks are obtained through the analysis of relative vorticity at 850 hPa, using the ERA5 dataset. The study identified six main cyclone life cycle patterns from the analysis of 28,458 systems. The predominant cyclone type, accounting for approximately 60% of the analysed systems, exhibited a four‐phase configuration: incipient, intensification, mature and decay. Detailed statistics for each developmental phase and the overall life cycle are presented, offering valuable comparisons and new insights while corroborating previous research findings. Key genesis regions in the SAt are identified, along with track density maps that reveal distinct preferences in cyclone developmental cycle. The main outcome of this study is the demonstration that the automated classification procedure enables the analysis of cyclones' life cycles to be conducted promptly and with low computing costs, facilitating the comprehensive study of cyclone behaviour with high efficiency. [ABSTRACT FROM AUTHOR]

Northeast India (NEI) receives most of its rainfall in the southwest monsoon (SWM) season. The region is known to have frequent and persistent rainfall events of high intensities and the region is vulnerable to potential high‐impact meteorological events. This study analyses observed daily rainfall data for the SWM months (JJAS) during 1991–2020 to better understand the climatology of high‐intensity rainfall (HIR) occurrences and their persistence. The agglomerative hierarchical cluster analysis has delineated four distinct clusters and Cramer's t test indicates no significant fluctuations at 5% significant level in the HIR events in these clusters. ERA‐5 reanalysis data have been used to find the moisture transport for synoptic‐scale (3–7 days), quasi‐bi‐weekly oscillations (10–20 days) and intraseasonal oscillations (30–60 days) for each cluster. Under positive synoptic‐scale phases, HIR in the clusters on southern latitudes of NEI occurs due to moisture incursion from the Bay of Bengal from southwesterlies at 850 hPa, and in the clusters on the northern latitudes, it is primarily due to westerlies. For, quasi‐bi‐weekly oscillations, westerlies at 850 hPa are favourable for moisture transport in most of the clusters during its positive phase. On the other hand, for positive phase of intraseasonal oscillations, westerlies at 850 hPa dominate the moisture transport in all the clusters. Also, most of the HIR events occur whenever Madden–Julian Oscillation (MJO) is in phase 1 and 2 with higher amplitude (RMM ≥1). [ABSTRACT FROM AUTHOR]

The Kingdom of Saudi Arabia (KSA) is characterized by a desert climate, with rainfall mainly occurring during the cooler months (November–April) and sometimes in conjunction with intense extratropical systems that can cause serious damage and casualties. Given the vast size of KSA, there are gaps in understanding the association between large‐scale atmospheric circulations and local organized rainfall events, and in characterizing the diversity of this association. To address these gaps, we analyse an in‐house 5‐km horizontal grid spacing regional atmospheric reanalysis that has been specifically generated for the Arabian Peninsula to explore the mechanisms behind the organized rainfall events over KSA. Nine major regions with distinct climate regimes were objectively selected to represent KSA rainfall climatology. The results demonstrate that organized thunderstorms over KSA only occur under sufficient moisture and environmental instabilities. Mesoscale convective systems responsible for organized rainfall generally develop and propagate with low‐level moisture flow from the nearby seas (the Red Sea to the west and Arabian Gulf to the east) toward the desert. In the central part of KSA, the most frequent physical mechanism responsible for rainfall is winter extratropical influence, followed by spring extratropical–tropical interactions, and spring tropical influence. The east coast is characterized by two rainfall modes: a continuous southwest–northeast rain corridor and concentrated southwestern rain. Large‐scale organized convection following three physically distinct mechanisms (extratropical, transition and tropical) is revealed along the west coast. [ABSTRACT FROM AUTHOR]

Introduction: Pressure injuries are a preventable yet highly prevalent health concern. Wheelchair cushion prescription can have significant implications for wheelchair users' risk of pressure injury development, which can impact functional abilities and quality of life. The efficacy of a wheelchair cushion to redistribute pressure has been well‐researched, but the efficacy to manage the microclimate is less clear, particularly in warm‐hot environments. The aim of this study was to systematically review studies examining the effect of wheelchair cushions on temperature, moisture and thermal perception to determine which cushions are superior to improve these responses. Method: A systematic review with meta‐analyses of randomised cross‐over and randomised control trials of wheelchair cushion interventions on measures of temperature, moisture, and thermal perception was conducted. Results: Eight studies were identified that met the eligibility criteria and six meta‐analyses were conducted. Pooled analyses identified a significantly lower temperature on foam‐gel cushions compared to air cushions (MD = 0.80, 95% CI: 0.31, 1.29; p = 0.002) and a significantly lower temperature on foam‐gel cushions compared to foam cushions (SMD = 0.76, 95%CI; 0.45, 1.06; p < 0.00001). Pooled analyses also demonstrated significantly lower relative humidity (i.e., moisture) on foam cushions compared to foam‐gel cushions (p = 0.02). Differences in thermal perception were inconclusive due to limited data found. Conclusion: It is clear that not one cushion is ideal in managing all aspects of microclimate, as foam‐gel cushions were the superior cushion to manage temperature and foam cushions were the superior cushion to manage moisture. This article provides occupational therapists and other health professionals with evidence‐based information to assist with wheelchair cushion prescription that minimises the temperature and moisture accumulation, and associated risk of pressure injury for wheelchair users. [ABSTRACT FROM AUTHOR]

Extreme heat such as that seen in the United States and Europe in summer 2022 can have significant impacts on human health and infrastructure. The Occupational Safety and Health Administration (OSHA) and the U.S. Army use wet-bulb globe temperature (WBGT) to quantify the impact of heat on workers and inform decisions on workload. WBGT is a weighted average of air temperature, natural wet-bulb temperature, and black globe temperature. A local hourly, daily, and monthly WBGT climatology will allow those planning outdoor work to minimize the likelihood of heat-related disruptions. In this study, WBGT is calculated from the ERA5 reanalysis and is validated by the Oklahoma Mesonet and found to be adequate. Two common methods of calculating WBGT from meteorological observations are compared. The Liljegren method has a larger diurnal cycle than the Dimiceli method, with a peak WBGT about 1°F higher. The high- and extreme-risk categories in the southern U.S. Great Plains (USGP) have increased from 5 days per year to 15 days from 1960 to 2020. Additionally, the largest increases in WBGT are occurring during DJF, potentially lengthening the warm season in the future. Heat wave definitions based on maximum, minimum, and mean WBGT are used to calculate heat wave characteristics and trends with the largest number of heat waves occurring in the southern USGP. Further, the number of heat waves is generally increasing across the domain. This study shows that heat wave days based on minimum WBGT have increased significantly which could have important impacts on human heat stress recovery. [ABSTRACT FROM AUTHOR]

Using monthly observations and ensemble hindcasts of the Nanjing University of Information Science and Technology Climate Forecast System (NUIST-CFS1.0) for the period 1983–2020, this study investigates the forecast skill of marine heatwaves (MHWs) over the globe and the predictability sources of the MHWs over the tropical oceans. The MHW forecasts are demonstrated to be skillful on seasonal-annual time scales, particularly in tropical oceans. The forecast skill of the MHWs over the tropical Pacific Ocean (TPO) remains high at lead times of 1–24 months, indicating a forecast better than random chance for up to two years. The forecast skill is subject to the spring predictability barrier of El Niño-Southern Oscillation (ENSO). The forecast skills for the MHWs over the tropical Indian Ocean (TIO), tropical Atlantic Ocean (TAO), and tropical Northwest Pacific (NWP) are lower than that in the TPO. A reliable forecast at lead times of up to two years is shown over the TIO, while a shorter reliable forecast window (less than 17 months) occurs for the TAO and NWP. Additionally, the forecast skills for the TIO, TAO, and NWP are seasonally dependent. Higher skills for the TIO and TAO appear in boreal spring, while a greater skill for the NWP emerges in late summer-early autumn. Further analyses suggest that ENSO serves as a critical source of predictability for MHWs over the TIO and TAO in spring and MHWs over the NWP in summer. [ABSTRACT FROM AUTHOR]

Climate change is one of the most important drivers of ecosystem change, the global‐scale impacts of which will intensify over the next 2 decades. Estimating the timing of unprecedented changes is not only challenging but is of great importance for the development of ecosystem conservation guidelines. Time of emergence (ToE) (point at which climate change can be differentiated from a previous climate), a widely applied concept in climatology studies, provides a robust but unexplored approach for assessing the risk of ecosystem collapse, as described by the C criterion of the International Union for Conservation of Nature's Red List of Ecosystems (RLE). We identified 3 main theoretical considerations of ToE for RLE assessment (degree of stability, multifactorial instead of one‐dimensional analyses, and hallmarks of ecosystem collapse) and 4 sources of uncertainty when applying ToE methodology (intermodel spread, historical reference period, consensus among variables, and consideration of different scenarios), which aims to avoid misuse and errors while promoting a proper application of the framework by scientists and practitioners. The incorporation of ToE for the RLE assessments adds important information for conservation priority setting that allows prediction of changes within and beyond the time frames proposed by the RLE. [ABSTRACT FROM AUTHOR]

A number of studies have examined historical climatological trends back to the Middle Ages. However, few have investigated these trends near important historical sites such as medieval battlefields. Most studies on medieval battles and battlefields focus almost exclusively on interpreting the written records from a literary standpoint and on knowledge of the site on which the battle took place, with rarely much consideration for other perspectives. While the written records are important, only focusing on them limits understanding and ignores the environment itself. A historical climatological perspective would contribute to the study of medieval warfare by exploring relevant long-term climatic proxies as well as mapping weather conditions around the time of the campaign and battle. As an example, this study will investigate the weather during Duke William's voyage to England in 1066. The study concludes with a discussion of the implications of these techniques for applying weather analyses to other historical events. [ABSTRACT FROM AUTHOR]

Tackling environmental challenges that face humanity requires us to acknowledge new ways of working and to cross disciplinary boundaries. However, the methodological toolkit used by environmental researchers to explore the human attitudes, knowledge and behaviours that drive global challenges such as biodiversity loss and climate breakdown remains constrained.Here, we describe participatory video, a methodology for capturing and communicating knowledge, which goes beyond interviews, focus groups and participant observation. We draw from the literature and our own experience of conducting participatory video projects in Nepal, Guyana and Peru. We demonstrate the diverse ways in which the methodology can be applied to environmental research and highlight its strengths and limitations.Participatory video provides a more holistic understanding of environmental issues by using multiple types of data, its longer‐term engagement with issues, opening channels of communication between stakeholders, engaging a diversity of knowledge systems and advocating for transformative change.By taking a participatory video approach, environmental researchers may begin to counter commonplace criticisms about lack of diversity and entrenched colonialism. This simultaneously responds to wider calls for environmental research to engage with social justice issues, represent diverse voices, understand different contexts and acknowledge the role of power. Crucially, this helps build trust amongst all those involved.By demonstrating how we have successfully used participatory video in projects in conservation, ecology and climate science, we provide guidance for researchers looking to expand their methodological toolkit. Ultimately, we seek to improve the use of participatory methods to help support communities to tackle the environmental challenges that they face. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

In this article, we claim that recent developments in climate science and renewable energy should prompt a reframing of debates surrounding climate change mitigation. Taken together, we argue that these developments suggest (1) global climate collapse in this century is a non-negligible risk, (2) mitigation offers substantial benefits to current generations, and (3) mitigation by some can generate social tipping dynamics that could ultimately make renewables cheaper than fossil fuels. We explain how these claims undermine familiar framings of climate change, wherein mitigation is understood as self-sacrifice that individuals and governments must be morally persuaded or incentivized to undertake. [ABSTRACT FROM AUTHOR]

AbstractThe recent IPCC report (IPCC, 2023) highlighted the need to increase the perception of risk and prompt climate action through education. The question is what contribution science and environmental education can make—if any—to this challenge. Psychological research has suggested that knowledge (topical and epistemological) and beliefs about self-efficacy are relevant starting points, but the evidence is scarce and inconsistent. We conducted a transversal correlational study to test the direct and indirect effects of system knowledge of climate change, personal engagement with science, and trust in climate science on the willingness to mitigate the effects of climate change. The participants were 386 students attending high schools in Chile. The results reveal that there is no direct effect of climate change system knowledge on the willingness to act. We did find indirect effects of system knowledge on the willingness to act, mediated by personal engagement with science and trust in climate science knowledge. The results also demonstrate a direct effect of personal engagement with science, and an indirect effect mediated by trust in science. The implications for science education are discussed. [ABSTRACT FROM AUTHOR]

Mock‐Walker simulations have the potential to play a key role in a tropical model hierarchy, bridging small‐scale Radiative‐Convective Equilibrium simulations and global models of tropical circulations. We demonstrate that mock‐Walker simulations transition from single‐ to double‐celled overturning circulations as mean Sea Surface Temperature (SST) is increased, with the transition occurring near 300 K. The transition is robust to domain geometry and microphysical scheme, and is favored by larger SST gradients. The transition is associated with the development of a mid‐tropospheric minimum in the radiative‐subsidence velocity over the cold pool of the simulations, and is likely reinforced by zonal moisture and temperature fluxes between the warm and cold pools. Several methods of suppressing the transition are investigated, but all set‐ups produce a double‐cell at sufficiently warm mean SSTs. The striking dynamical transition of mock‐Walker simulations dominates their response to warming, though its relevance for observed tropical climate change is unclear. Plain Language Summary: Untangling the coupled interactions between clouds and large‐scale atmospheric flows is one of the "Grand Challenges" of climate science. Large‐scale flows are the main control on the spatial distribution of cloud‐types in the tropics, but clouds in turn play a key role in setting the strengths and spatial structures of these flows. Here, we investigate "mock‐Walker" simulations as a potential idealized modeling set‐up for investigating the two‐way interactions between clouds and tropical circulations. Mock‐Walker simulations include the zonal sea‐surface temperature (SST) gradient needed to generate realistic tropical circulations, while using grid resolutions sufficient to partially resolve clouds. However, in this study we document a robust transition in the large‐scale flow in mock‐Walker simulations from a single overturning cell to two vertically‐stacked overturning cells (a double‐celled flow) as the mean SST is increased. This transition occurs for a mean SST close to the observed SSTs in the equatorial Pacific, and dominates the response of mock‐Walker simulations to warming. The transition is robust to domain geometry, microphysical scheme and to fixing the radiation. While we are unable to provide a complete explanation of the transition, it does seem to be associated with extreme dryness over the cold pools of the simulations. Key Points: Mock‐Walker simulations transition from single‐to a double‐celled circulation as the mean SST is increasedThis is associated with a mid‐tropospheric minimum in the cold pool radiative‐subsidence velocityElevated stability maxima cause transitions in mock‐Walker simulations with fixed radiative cooling and artificial moisture sources [ABSTRACT FROM AUTHOR]

Improving tropical cyclone (TC) rainfall prediction is vital as climate change has led to an increase in TC rainfall rates. Enhanced reliability in predicting TC tracks has paved the way for statistical methodologies to make use of them in estimating current TC rainfall, achieved by identifying similar past TC tracks and obtaining their corresponding rainfall data. While the Fuzzy C Means (FCM) clustering algorithm is widely used, it has limitations stemming from its clustering‐centric design, hindering its ability to pinpoint the most appropriate similar TCs. Our study introduces the Sinkhorn distance, a novel similarity metric that measures the cost of transforming one set of data to another, for assessing TC similarity in rainfall prediction. Our findings indicate that utilizing Sinkhorn distance enhances the accuracy of TC rainfall predictions across the Western North Pacific region. When compared to the conventional approach using FCM, our Sinkhorn distance‐based methodology yields slightly better yet statistically significant results. The improvement is due to better identification of similar TCs, characterized by closer proximity of similar TC tracks to the target TC track, facilitated by Sinkhorn distance. This underscores how minor differences in TC track can alter rainfall distribution, emphasizing the critical importance of accurate track prediction in rainfall prediction and the need to reconsider how we categorize TCs together, which can have implications for climate and atmospheric sciences. Collectively, the inclusion of Sinkhorn distance stands as a valuable addition to our toolkit for discerning similar TC tracks, thus elevating the accuracy of TC rainfall predictions. Plain Language Summary: We need to get better at predicting how much rain tropical cyclones will bring because climate change is making them bring more rain. We have gotten better at predicting their paths, which lets us use a method that looks at similar past storms to guess how much rain the current one will bring. The usual method, called Fuzzy C Means (FCM), has some problems because it focuses too much on grouping storms. Our study introduces Sinkhorn distance, a measure of moving a cyclone to the path of another cyclone, as a new way of measuring how similar storms are. We found that using the Sinkhorn distance makes our predictions of tropical cyclone rainfall in the Western North Pacific slightly more accurate, primarily because it better identifies similar cyclone paths, thus highlighting the sensitivity of rainfall to minor changes in cyclone tracks. Compared to the usual FCM method, the Sinkhorn distance generally gives better results. So, including the Sinkhorn distance in our toolkit helps us find storms that are more similar, which makes our predictions of rainfall more accurate. This study is an important step forward in making more accurate prediction for tropical cyclone rainfall in the Western North Pacific region. Key Points: Proposed in this study is the use of Sinkhorn distance as a novel measure of tropical cyclone (TC) similarity in rainfall predictionSinkhorn distance statistically significantly improves TC rainfall prediction accuracy, serving as an alternative similarity measureResults highlight minor differences in TC tracks can alter rainfall, due to the interaction between TC and land topography [ABSTRACT FROM AUTHOR]

The Deep Space Climate Observatory (DSCOVR) spacecraft drifts about the Lagrangian point ≈ 1.4 − 1.6 × 106 km from Earth, where its Earth Polychromatic Imaging Camera (EPIC) observes the entire sunlit face of Earth every 1–2 h. In an attempt to detect “signals,” i.e., longer-term changes and semi-permanent features such as the ever-present ocean glitter, while suppressing geographic “noise,” in this study, we introduce temporally and conditionally averaged reflectance images, performed on a fixed grid of pixels and uniquely suited to the DSCOVR/EPIC observational circumstances. The resulting images (maps), averaged in time over months and conditioned on surface/cover type such as land, ocean, or clouds, show seasonal dependence literally at a glance, e.g., by an apparent extent of polar caps. Clear ocean-only aggregate maps feature central patches of ocean glitter, linking directly to surface roughness and, thereby, global winds. When combined with clouds, these blue planet “moving average” maps also serve as diagnostic tools for cloud retrieval algorithms. Land-only images convey the prominence of Earth’s deserts and the variable opacity of the atmosphere at different wavelengths. Insights into climate science and diagnostic and educational tools are likely to emerge from such average reflectance maps. [ABSTRACT FROM AUTHOR]

Three ~12‐km reanalysis‐driven regional climate models (RCMs) are evaluated in terms of capturing climatologies and extremes of precipitation, temperature and surface wind over Aotearoa/New Zealand (NZ). NZ provides an excellent case study for evaluating high‐resolution RCMs due to its coastal and complex terrain and isolated geographical position in the midlatitudes, exposed to both tropical and polar influences. Overall, we find that the RCMs faithfully reproduce the observed climate, with precipitation and temperature climatologies particularly well‐captured. However, the RCMs display significant differences from observations in capturing the surface wind climatology, highlighting a remaining key challenge. The excess “drizzle problem” is apparent to varying degrees, leading to a weaker representation in the length of meteorological drought in some regions. The RCMs also diverge in reproducing diurnal temperature range which appears partly related to cloud cover. Finally, we discuss the important role of observational uncertainty in the context of model evaluation. [ABSTRACT FROM AUTHOR]

In the North West Shelf region of Australia is a surface current (Holloway Current), which flows southwestward along the shelf break. This paper describes a seasonal undercurrent below the Holloway Current. A 5-day climatology is constructed from the output of an eddy-resolving oceanic general circulation model (OGCM). A seasonal northeastward-flowing undercurrent is found on the upper continental slope during the climatological April-May. This undercurrent reverses during February-March. During its annual cycle, the phase of the undercurrent tends to propagate southwestward and upward. The annual frequency dominates, but the positive and negative phases of the undercurrent are not symmetric in the yearly cycle because of the contributions from the semi-annual and 1/3-annual components. We propose a hypothesis that this undercurrent is a beam of coastal trapped wave (CTW). As an initial attempt to assess the plausibility of this hypothesis, we construct an idealized linear coastal-trapped wave (CTW) solution driven by an idealized harmonic meridional winds at the annual frequency. The solution takes the form of a beam originating from the forcing region on the continental shelf and propagating offshore and southward. When it emerges on to the continental slope, it takes the form of an undercurrent. This idealized solution shares several properties with the undercurrent in the OGCM despite several discrepancies. [ABSTRACT FROM AUTHOR]

Ice clouds are a crucial component of the Earth's weather system, and their representation remains a principal challenge for current weather and climate models. Several past and future satellite missions were explicitly designed to provide observations offering new insights into cloud processes, but these specialized cloud sensors are limited in their spatial and temporal coverage. Geostationary satellites have been observing clouds for several decades and can ideally complement the sparse measurements from specialized cloud sensors. However, the geostationary observations that are continuously and globally available over the full observation record are restricted to a small number of wavelengths, which limits the information they can provide on clouds. The Chalmers Cloud Ice Climatology (CCIC) is a novel cloud-property dataset that aims to provide an improved climate record of ice hydrometeor concentrations by applying state-of-the-art machine-learning techniques to retrieve ice cloud properties from globally gridded, single-channel geostationary observations that are readily available from 1980 onwards. CCIC offers a novel perspective on the record of geostationary IR observations by providing spatially and temporally continuous retrievals of the vertically integrated and vertically resolved concentrations of frozen hydrometeors, typically referred to as ice water path (IWP) and ice water content (IWC). In addition to that, CCIC provides 2D and 3D cloud masks and a 3D cloud classification. A fully convolutional quantile regression neural network constitutes the core of the CCIC retrieval, providing probabilistic estimates of IWP and IWC. The network is trained against CloudSat retrievals using 3.5 years of global collocations. Assessed on a held-out test dataset, the CCIC-provided IWP and IWC estimates achieve correlations exceeding 0.7 and 0.6, respectively, and biases better than - 5 % and - 2 % demonstrating considerable skill in estimating both IWP and IWC. In addition, CCIC is extensively validated against both in situ and remote sensing measurements from two flight campaign series and a ground-based radar. The results of this independent validation confirm the ability of CCIC to retrieve IWP and IWC. CCIC thus ideally complements temporally and spatially more limited measurements from dedicated cloud sensors by providing spatially and temporally continuous estimates of ice cloud properties. The CCIC network and its associated software are made accessible to the scientific community. [ABSTRACT FROM AUTHOR]

The optimal control problems of degenerate parabolic equations have many applications in economics, physics, climatology, and so on. Motivated by the applications, we consider the optimal control problems of a class of nonlinear degenerate parabolic equations in this paper. The main result is that we deduce the first order necessary condition for the optimal control problem of nonlinear degenerate parabolic equations by variation method. Moreover, we investigate the uniqueness of the solutions to the optimal control problems. For the linear equations, we obtain the global uniqueness, while for the nonlinear equations, we obtain only the local uniqueness. Finally, we give a numerical example to validate the theoretical results. [ABSTRACT FROM AUTHOR]

Numerous recent tropical cyclones have caused extreme rainfall and flooding events in the CONUS. Climate change is contributing to heavier extreme rainfall around the world. Modeling studies have suggested that tropical cyclones may be particularly efficient engines for transferring the additional water vapor in the atmosphere into extreme rainfall. This paper develops a new indicator for climate change using the enhanced rainfall metric to evaluate how the frequency and/or intensity of extreme rainfall around tropical cyclones has changed. The enhanced rainfall metric relates the amount of rain from a storm over a given location to the 5-yr return period rainfall in that location to determine the severity of the event. The annual area exposed to tropical-cyclone-related 5-yr rainfall events is increasing, which makes it a compelling climate change indicator. Quantile regression illustrates that the distribution of tropical cyclone rainfall is also changing. For tropical storms, all quantiles are increasing. However, major hurricanes show large increases in their most extreme rainfall. This study does not attempt to make any detection claims (vs natural variability) or attribution of the observed trends to anthropogenic forcing. However, the sensitivity of the results to natural variability in tropical cyclone frequency was somewhat constrained by comparing 2 decades from the previous active era (1951–70) with two from the current era (2001–20). This comparison also shows that both the mean rainfall and the maximum rainfall associated with tropical cyclones are increasing over most areas of the eastern CONUS with the most significant increases from northern Alabama to the southern Appalachians. Significance Statement: The purpose of this study is to analyze the changes in frequency and magnitude of extreme precipitation events associated with tropical cyclones with the goal of developing a new indicator for climate change. This is important because heavy rainfall and associated flooding is one of the primary causes of tropical cyclone destruction and fatalities, especially in inland locations away from where storms initially make landfall. Our results show that both the frequency and magnitude of extreme rainfall events from tropical cyclones have increased over the CONUS. The strongest storms (major hurricanes) also show more of an increase in extreme rainfall than storms of weaker intensities. [ABSTRACT FROM AUTHOR]

A three‐dimensional winter (DJF) climatology of Lagrangian diffusivity characterizing eddy mixing and transport in the northern middle atmosphere is presented. To emphasize aspects other than zonal averages, we use the theory of Lagrangian diffusivity (κyy) hitherto not applied in stratospheric contexts to our knowledge. Our formulation of Lagrangian diffusivity requires the calculation of parcel trajectories, which is made on isentropic surfaces. A Lagrangian descriptor is used to estimate the boundary of the stratospheric polar vortex (SPV). To characterize quasi‐geostrophic motions and their influence on the SPV we apply the wave activity flux (W) and Local Wave Activity (A) $(\mathcal{A})$. Our data set is the ERA5 reanalysis for the period 1979–2013. Results for κyy show important zonal asymmetries. In the lower and middle stratosphere, κyy is highest at midlatitudes, particularly around the prime meridian. This location is surrounded by manifolds associated with hyperbolic trajectories emanating from the outer SPV boundary. κyy is also high within the SPV, and near the locations where the SPV boundary is open. Zonal asymmetries are also clear in W at midlatitudes. The larger values of A $\mathcal{A}$ are at high latitudes and upstream of the opening of the vortex boundary. The role of quasi‐geostrophic waves on the south‐north shift of the midlatitude westerlies is highlighted. In particular, the waves contribute to open the SPV boundary at around 90W. The interannual variability of κyy is explored by contrasting winters with positive‐negative Northern Annular Mode index, and Sudden Stratospheric Warmings of displacement‐split type. Plain Language Summary: This paper applies a novel approach to studying eddy mixing and transport in the northern middle atmosphere during winter (December–January–February). The approach is based on the concept of Lagrangian diffusivity, a measure of how quickly air parcels mix together. Unlike traditional diagnostics that rely on longitudinal or contour‐based averages, Lagrangian diffusivity provides a detailed three‐dimensional view of the mixing. This approach, hitherto restricted to oceanographic applications, is a significant contribution of the present work. We employ a Lagrangian descriptor, a tool based on parcel trajectory length, to locate the stratospheric polar vortex SPV boundary. Also, we investigate the influence of quasi‐geostrophic motions on the SPV using wave activity flux and local wave activity (LWA). The data set is the ERA5 reanalysis from 1979 to 2013. The results reveal pronounced zonal asymmetries in Lagrangian diffusivity and wave activity flux. Mixing is highest at midlatitudes around the prime meridian and at locations within the SPV. LWA is elevated at high latitudes and upstream of the climatological vortex boundary opening, highlighting the role of quasi‐geostrophic waves in the southward displacement of midlatitude westerlies. Comparisons are made of diffusivity during weak and strong vortex winters, as well as of during winters with and without Sudden Stratospheric Warmings. Key Points: Locally, the largest values of Lagrangian diffusivity around the vortex are along the prime meridian at all levels in the stratosphereThe location of maximum diffusivity is bounded by the edge of the climatological displaced vortex and a manifold emanating from the vortex edgeWhen the Northern Annular Mode is positive, the vortex boundary closes and diffusivity is much lower inside [ABSTRACT FROM AUTHOR]

This paper details the creation of a tropical cyclone (TC) size dataset using the NCEP/NCAR Reanalysis I dataset for landfalling TCs along the United States coastline from 1948 to 2022. The radius of the outermost closed isobar (ROCI) is used as the size parameter. The dataset comprises landfall ROCI for 220 TCs. Storms are split into three zones (Texas–Alabama, Florida and Georgia–Maine) to determine if TC size varies geographically. Results showed a significant difference in landfall size, with Florida storms larger on average than the Texas–Alabama storms. Additionally, TC size increased with increasing intensity from tropical storm to Category 3, and storms tended to be larger later in the hurricane season, but there was no significant trend in landfall size over the 75‐year period. ROCI exhibited statistically significant positive correlations with longitude and wind speed and a negative correlation with the outermost closed isobar's pressure. The dataset's creation is an example of how reanalysis datasets can be used to develop a TC size climatology. [ABSTRACT FROM AUTHOR]

The research on the thermal bioclimate is increasingly valuable in the context of climate change. Human well-being is threatened not only from direct exposure to extreme thermal conditions and complications from underlying health issues but also from disruptions of health and social services. This study aims at examining the thermal bioclimate in Greece. Data of ERA5-Land reanalysis dataset were used to estimate the Universal Thermal Climate Index (UTCI, in °C). The analysis covered a 30-year period (1991–2020) examining UTCI climatology and trends. Additionally, the intensity of two recent heatwaves which occurred in summers 2021 and 2023 was assessed. During the period 1991–2020, the UTCI equivalent temperature ranges between -49.8 °C and 51.9 °C [mean ± standard deviation (sd) = 13.3 ± 12.2 °C] classifying thermal stress from 'extreme cold stress' to 'extreme heat stress'. Across the country, the mean UTCI ranges from 7.5 °C to 17.8 °C (mean ± sd = 13.3 ± 2.1 °C), with a decrease of 0.5 °C per latitude degree. Mountainous regions exhibit the lowest UTCI equivalent temperatures, while inland plains display higher UTCI equivalent temperatures, especially in the eastern regions of the country. An increasing trend in mean annual UTCI (mean = 0.05 °C/year) is identified, more pronounced in higher latitude regions. Both the 2021 and 2023 heatwaves were exceptionally severe, with about 99% of the population to experience mean UTCI equivalent temperatures falling within stress categories of 'moderate heat stress' and above. The 2023 heatwave set a new record with the highest absolute maximum UTCI (52.1 °C) and number of heat stress hours compared to the period 1991–2020. The bioclimatic maps developed in this study analyze the spatial variability in the thermal conditions across Greece identifying high-risk areas. These findings can contribute to impact studies for tourism, energy efficiency, urban design and public health purposes. [ABSTRACT FROM AUTHOR]

We propose a forecasting tool for precipitation based on analogues of circulation defined from 5‐day hindcasts and a stochastic weather generator that we call "HC–SWG." In this study, we aim to improve the forecast of European precipitation for subseasonal lead times (from 2 to 4 weeks) using the HC–SWG. We designed the HC–SWG to generate an ensemble precipitation forecast from the European Centre of Medium‐range Weather Forecasts (ECMWF) and Centre National de la Recherche Météorologique (CNRM) subseasonal‐to‐seasonal ensemble reforecasts. We define analogues from 5‐day ensemble reforecast of Z500 from the ECMWF (11 members) and CNRM (10 members) models. Then, we generate a 100‐member ensemble for precipitation over Europe. We evaluate the skill of the ensemble forecast using probabilistic skill scores such as the continuous ranked probability skill score (CRPSS) and receiver operating characteristic curve. We obtain reasonable forecast skill scores within 35 days for different locations in Europe. The CRPSS shows positive improvement with respect to climatology and persistence at the station level. The HC–SWG shows a capacity to distinguish between events and non‐events of precipitation within 15 days at the different stations. We compare the HC–SWG forecast with other precipitation forecasts to further confirm the benefits of our method. We found that the HC–SWG shows improvement against the ECMWF precipitation forecast until 25 days. [ABSTRACT FROM AUTHOR]

Philosophers have yet to provide a systematic analysis of the relationship between historical science and model-based science. In this paper I argue that prototypical model-based sciences exhibit features understood to be central to historical science. Philosophers of science have argued that historical scientists are distinctly concerned with inference to the best explanation, that explanations in historical science tend to increase in complexity over time, and that the explanations take the form of narratives. Using general circulation models in climate science as a reference, I illustrate how simulation models in model-based science share these features exhibited by historical science. That model based sciences share these features raises important philosophical questions about how we should understand prototypical types of scientific enquiry, including the relationship between experimental science, historical science, and model-based science. I conclude by exploring several options for how to accommodate the noted similarities within a more general taxonomy of the sciences. [ABSTRACT FROM AUTHOR]

Philosophers of science have paid close attention to climate simulations as means of projecting the severity and effects of climate change, but have neglected the full diversity of methods in climate science. This paper shows the philosophical richness of another method in climate science: the practice of using paleoclimate analogues to inform our climate projections. First, I argue that the use of paleoclimate analogues can offer important insights to philosophers of the historical sciences. Rather than using the present as a guide to the past, as is common in the historical sciences, paleoclimate analogues involve using the past as a guide to the future. I thereby distinguish different methods in the historical sciences and argue that these distinctions bear on debates over whether the historical sciences can produce generalizations or predictions. Second, I suggest that paleoclimate analogues might actually be considered a type of climate model, and, as such, their use expands on common characterizations of models to include those that are full-scale, naturally occurring, and non-manipulable. [ABSTRACT FROM AUTHOR]

The ICESat‐2 (Ice, Cloud and Land Elevation Satellite‐2) photon‐counting laser altimeter technology required the design and development of very sophisticated onboard algorithms to collect, store and downlink the observations. These algorithms utilize both software and hardware solutions for meeting data volume requirements and optimizing the science achievable via ICESat‐2 measurements. Careful planning and dedicated development were accomplished during the pre‐launch phase of the mission in preparation for the 2018 launch. Once on‐orbit all of the systems and subsystems were evaluated for performance, including the receiver algorithms, to ensure compliance with mission standards and satisfy the mission science objectives. As the mission has progressed and the instrument performance and data volumes were better understood, there have been several opportunities to enhance ICESat‐2's contributions to Earth observation science initiated by NASA and the ICESat‐2 science community. We highlight multiple updates to the flight receiver algorithms, the onboard software for signal processing, that have extended ICESat‐2's data capabilities and allowed for advanced science applications beyond the original mission objectives. Plain Language Summary: NASA launched its second Earth observing laser altimeter in 2018 with mission objectives of collecting observations in support of Earth science as a window into climate change impacts on our planet. Pre‐launch studies focused on specific instrument settings and on‐board data processing to support the mission objectives without violating data volume constraints. Once the instrument was on‐orbit and operational, evaluation of the algorithms for success in signal detection, signal finding, and signal telemetry was undertaken. In response to the evaluation, updates have been made to optimize the data provided by the mission. Key Points: Since the 2018 ICESat‐2 (Ice, Cloud and Land Elevation Satellite‐2) launch multiple updates have been made to the onboard flight receiver algorithm parameters to improve access and utility of the data for a multi‐disciplinary science communityThe adjustments have been primarily in the in the vertical telemetry band settings and have facilitated enhanced observations of blowing snow and increased detection opportunities of bathymetry in nearshore environmentsThe parameter changes have been made to mitigate data losses in certain situations and to advance science applications outside of the primary science objectives of the ICESat‐2 mission [ABSTRACT FROM AUTHOR]

More than one billion people worldwide are living in urban informal settlements where flood risks are high. Positive collective efficacy beliefs can facilitate community‐level adaptive action. This sub‐study of the Revitalizing Informal Settlements and their Environments (RISE) trial, aimed to identify social and contextual factors influencing residents' collective efficacy appraisals about their settlement's ability to implement community‐level flood prevention, protection and response measures. Forty‐two in‐depth interviews were conducted in 10 settlements in Suva, Fiji using a photovoice methodology. Thematic analysis was used to elicit key themes, which were then interpreted and contextualized collaboratively with the local field team. The most salient influencing factors were formal leadership, shared needs or benefits, collective identity (whether via shared religion, ethnicity or regional/kinship group), past performance experiences and expectations around collective action. While the data revealed some between‐settlement variation on these factors, there was also a large degree of within‐settlement variation concerning perceptions of these factors. Community‐based flood programming should not be undertaken without first assessing the degree to which participants believe that programme objectives reflect shared needs or will yield shared benefits and whether those objectives warrant collective action according to the community's social expectations for participation and contribution. [ABSTRACT FROM AUTHOR]

In climatology, there are several situations for which the response variable has linear and non-linear relations simultaneously in terms of explanatory variables. Another common situation in this area is when the distribution of the response variable presents a bimodal form. So, it is not possible analyzing this type of data using classical distributions belonging to the symmetric class (normal, t-Student, exponential power, etc.), or distributions in an asymmetric class (Weibull, log-logistic, skew normal, etc.). For these problems, we propose a semiparametric regression using a flexible distribution, named the odd log-logistic exponential Gaussian, whose systematic component contains parametric and nonparametric parts to measure the linear and non-linear effects simultaneously from a penalized smoothing based on the P-spline. We add new structural properties of the proposed distribution. Adopting penalized maximum likelihood to estimate the parameters and some simulations show the accuracy of the estimators. Diagnostic measures and residual analysis are discussed. We prove the versatility of our proposal in the climatology area. [ABSTRACT FROM AUTHOR]

The annual, seasonal, and diurnal spatiotemporal heavy convective precipitation patterns over a pan-European domain are analyzed in this study using a combination of datasets, including the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG) precipitation rate product, E-OBS ground-based precipitation gauge data, European climatological gauge-adjusted radar precipitation dataset (EURADCLIM), Operational Programme for the Exchange of Weather Radar Information (OPERA) ground-based radar-derived precipitation rates, and fifth major global reanalysis produced by ECMWF (ERA5) total and convective precipitation products. Arrival Time Difference Network (ATDnet) lightning data are used in conjunction with IMERG and EURADCLIM precipitation rates, with an imposed threshold of 10 mm h−1 to classify precipitation as convective. Annually, the largest convective precipitation accumulations are over the European seas and coastlines. In summer, convective precipitation is more common over the European continent, though relatively large accumulations exist over the northern coastal waters and the southern seas, with a seasonal localized maximum over the northern Adriatic Sea. Activity shifts southward to the Mediterranean and its coastlines in autumn and winter, with maxima over the Ionian Sea, the eastern Adriatic Sea, and the adjacent coastline. Over the continent, 1%–10% of the total precipitation accumulated is classified as convective, increasing to 10%–40% over the surrounding seas. In contrast, 30%–50% of ERA5 precipitation accumulations over land is produced by the convective parameterization scheme and 40%–60% over the seas; however, only 1% of ERA5 convective precipitation accumulations are from rain rates exceeding 10 mm h−1. Regional analyses indicate that convective precipitation rates over the inland mountains follow diurnal heating, though little to no diurnal pattern exists in convective precipitation rates over the seas and coastal mountains. [ABSTRACT FROM AUTHOR]

The conflict between investment treaties and climate action is escalating due to recent investment arbitration cases challenging States' fossil fuel phase‐out measures as violations of investment treaty obligations. As countries continue to implement climate mitigation and adaptation measures across various industries, this tension is expected to result in a rise in climate‐related investment arbitration claims. The current literature has primarily presented the tension between investment and climate treaties as a vertical conflict, with investment treaties having a chilling effect on States' climate regulation. The common defence for States' regulation has been based on their 'right to regulate'. It remains unclear whether there exists a horizontal conflict between investment and climate treaties, primarily due to the flexible nature of climate treaty obligations. However, a sovereignty‐based justification fails to recognise the international obligation of climate action and is insufficient for reconciling the conflict. This article delves into the intricate nature of the conflict between States' climate measures and their investment treaty obligations and argues that the conflict exhibits a 'quasi‐normative' nature, given the combination of binding climate obligations, permissive implementation methods and normative expectations of ambition. The article suggests that investment treaties should include clearly defined conflict clauses that outline the scope of the conflict between investment and climate treaties and establish specific mechanisms for resolving such conflicts. [ABSTRACT FROM AUTHOR]

In an action for annulment against the European Union (EU) Emissions Trading Directive, both the EU General Court and the Court of Justice of the EU (CJEU) found the claim to be inadmissible because the applicants did not satisfy the infamous Plaumann criteria. Conversely, at the national level, the German Federal Constitutional Court (GFCC) accepted to decide on a claim by individuals arguing that the German Climate Protection Act violated their fundamental rights. In its decision, the GFCC makes far‐reaching statements on the protection of fundamental rights in times of global climate change. Some might even argue the GFCC established a fundamental right to climate protection. By contrast, the CJEU did not yet decide on the effective protection of intertemporal rights or a right to climate protection respectively. Almost 50 years after the Solange I decision, one must ask whether there is a substantial deficit of fundamental rights protection at the EU level. [ABSTRACT FROM AUTHOR]

Although the value of climate science in the courtroom is widely acknowledged, few studies have evaluated how judges achieve a scientifically sound grounding for their rulings. Drawing insights from legal culture and science and technology studies, we compare the determination of scientific credibility in leading climate cases in Europe and the United States. Judges on both sides of the Atlantic answer similar questions about scientific facts and commonly use authoritative reports and testimonies from qualified experts. However, while judges in the Netherlands, France and Germany find value in the political mandates of international or national bodies that generate scientific reports, American judges seek to keep scientific expertise from the influence of policy considerations. We make sense of this difference by identifying two competing ideals of expertise, namely the 'view of everyone' ideal in Europe and the 'view from nowhere' ideal in the United States. Although climate science is often articulated in universalist terms, the cultural embeddedness of adjudication means that the evaluation of credibility varies by jurisdiction. [ABSTRACT FROM AUTHOR]

The Kowloon Peninsula, an urban area of Hong Kong, might be one of the most studied cities in terms of urban climate in the world. Both annual mean urban air temperature and humidity have been on the rise following the continual increase in the building volume and continual reduction in the average wind speed in the urban canopy layer. The observed urban warming and humidifying phenomena are a direct result of the city form (i.e., the city shape and size), including the building height and density. We call for a system-of-systems approach to be adopted in urban climate studies. [ABSTRACT FROM AUTHOR]