This article provides, firstly, an overview of Arctic traditional horse herding as one of the Indigenous subsistence practices of the Republic of Sakha (Yakutia). It discusses the origins, characteristics, and spiritual and material importance of Sakha horses and horse herding practices to inform the overall understanding of this traditional subsistence activity, which remains largely unexplored. Secondly, by conducting in-depth semi-structured interviews with Indigenous Sakha horse herders, this study explores the ways in which Indigenous subsistence practices are evolving and reacting to the climate and environmental changes. Results show that climate change is altering the local ecosystem and introducing new challenges to communities in Central Yakutia. Local herders describe climate change as a complex interplay of diverse transformations rather than a singular phenomenon. While historical adaptation strategies relied on the flexibility of traditional practices, today, this flexibility is often hindered by non-climatic factors. This article further discusses adaptability of Indigenous practices to climate change and offers recommendations for their development, particularly traditional horse herding. Future research related to climate change and Arctic Indigenous communities should encompass deeper and broader aspects, covering historical, cultural, social, and economic contexts and the worldviews of Indigenous peoples, distinct from Western perspectives.

As warmer and drier conditions associated with global warming are projected to increase in southern Europe, the Mediterranean countries are currently the most prone to wildfire danger. In the present study, we investigated the statistical relationship between drought and fire weather risks in the context of climate change using drought index and fire weather-related indicators. We focused on the vulnerable and long-suffering area of the Attica region using high-resolution gridded climate datasets. Concerning fire weather components and fire hazard days, the majority of Attica consistently produced values that were moderately to highly anti-correlated (−0.5 to −0.9). This suggests that drier circumstances raise the risk of fires. Additionally, it was shown that the spatial dependence of each variable on the 6-months scale Standardized Precipitation Evapotranspiration Index (SPEI6), varied based on the period and climate scenario. Under both scenarios, an increasing rate of change between the drought index and fire indicators was calculated over future periods versus the historical period. In the case of mean and 95th percentiles of FWI with SPEI6, abrupt changes in linear regression slope values were observed, shifting from lower in the past to higher values in the future periods. Finally, the fire indicators’ future projections demonstrated a tendency towards an increasing fire weather risk for the region’s non-urban (forested and agricultural) areas. This increase was evident from the probability distributions shifting to higher mean and even more extreme values in future periods and scenarios. The study demonstrated the region’s growing vulnerability to future fire incidents in the context of climate change.

The escalating impact of climate change on global weather patterns threatens the functionality and resilience of infrastructure systems. This paper presents a rigorous risk assessment protocol tailored to existing bridge infrastructure, integrating climate change projections, structural integrity, and socioeconomic factors. The protocol’s application involves five sequential steps: selecting a bridge, disassembling the structure into components, calculating utilization factors for design and projected temperatures, evaluating severity factors encompassing structural and socioeconomic aspects, and ultimately determining an overall risk rating. To demonstrate the protocol’s effectiveness, a case study was conducted on the Westminster Drive Underpass in London, Ontario. This study shows how the protocol systematically evaluates the vulnerability of each bridge component to projected temperatures under the Representative Concentration Pathway 6.0 model. The protocol provides a holistic risk assessment by incorporating both the structural response and socioeconomic implications of failure. The results rank the bridge’s risk level and highlight the urgency of intervention. The protocol emerges as a robust tool for decision-makers, practitioners, and engineers, offering a comprehensive approach to strengthen bridge infrastructure against the challenges of climate change.

Despite the wide range of applications of the Spatial Synoptic Classification (SSC), its expansion and utility in the tropics remains limited. This research utilized the fifth generation of European ReAnalysis (ERA5) data to develop an SSC scheme tailored for East Africa with a focus on Kenya. The SSC method classifies weather into seven types: Dry Polar (DP), Dry Moderate (DM), Dry Tropical (DT), Moist Polar (MP), Moist Moderate (MM), Moist Tropical (MT), and Transitional (TR). Frequency and trend analysis between 1959 and 2022 show that the MT and DM weather types are the dominant types in Kenya. The DM type is dominant in the December–February (DJF) dry season while the MT type is common from April to September. We find statistically significant decreasing trends in the DM, MP, and MM weather types and increasing trends in the DT and MT weather types. The results suggest that, generally, the number of days with cool and moderate conditions in Kenya is decreasing, while the number of days with warmer conditions is increasing. This research indicates the potential for the SSC to be utilized in different applications in East Africa including investigating heat vulnerability, as increasing temperatures could be a significant risk factor to human health.

Forest site productivity estimates are crucial for making informed forest resource management decisions. These estimates are valuable both for the tree species currently growing in the stands and for those being considered for future stands. Current models are generally designed for pure stands and do not account for the influence of climate on tree growth. Consequently, site index (SI) conversion equations were developed specifically for jack pine (Pinus banksiana Lamb.) and trembling aspen (Populus tremuloides Michx.) trees grown in naturally originated mixed stands. This work involved sampling 186 trees (93 of each species) from 31 even-aged mixed stands (3 trees per species per site) across Ontario, Canada. Stem analysis data from these trees were utilized to develop stand height growth models by incorporating climate variables for each species. The models were developed using a mixed effects modelling approach. The SI of one species was correlated with that of the other species and climate variables to establish SI conversion equations. The effect of climate on site productivity was evaluated by projecting stand heights at four geographic locations (east, center, west, and far west) in Ontario from 2022 to 2100 using the derived stand height growth models. Height projections were made under three emissions scenarios reflecting varying levels of radiative forcing by the end of the century (2.6, 4.5, and 8.5 watts m−2). Climate effects were observed to vary across different regions, with the least and most pronounced effects noted in the central and far western areas, respectively, for jack pine, while effects were relatively similar across all locations for trembling aspen. Stand heights and SIs of jack pine and trembling aspen trees grown in naturally originated mixed stands can be estimated using the height growth models developed here. Similarly, SI conversion equations enable the estimation of the SI for one species based on the SI of another species and environmental variables.

The urban heat island (UHI) effect is one of the largest climate-related issues concerning our cities due to the localized temperature increase in highly urbanized areas. This paper aims to investigate the impact of UHI mitigation techniques in promoting climate resilience, by reducing urban air temperatures and cooling energy consumption in buildings. To this end, four mitigation solutions regarding the building envelope—green roofs, green walls, cool roofs, and cool walls—were investigated for the city of Bari in Southern Italy and compared with the current baseline scenario. Hence, five scenarios were simulated—using the ENVI-met microclimate software—during three representative summer days, and the resulting microclimate changes were assessed. Based on these analyses, new climate files—one for each scenario—were generated and used as input to run energy simulations in EnergyPlus to estimate the building cooling consumption. Coupling the microclimate and the consumption outcomes, the mitigation strategies were evaluated from both an urban and building point of view. The study shows that urban characteristics, mainly geometry and materials, are crucial for the UHI phenomenon. All the applied technologies seem to be effective. However, green walls proved to be more efficient in reducing outdoor temperatures (1 °C reduction in daily temperatures), while cool walls performed better in reducing cooling energy consumption, with an overall saving of 6% compared to the current scenario.

This study analyzes temperature trends and thermal comfort during the key hours (i.e., from noon to 3:00 p.m.) of human tower (castells) performances in four significant festivities involving this outdoor exhibition (diada castellera) in Catalonia. Human towers were recognized by UNESCO in 2010 as an Intangible Cultural Heritage. The selected exhibitions were Sant Joan in Valls on 24 June; Festa Major de La Bisbal del Penedès on 15 August; Sant Magí in Tarragona on 19 August; and Sant Fèlix in Vilafranca del Penedès on 30 August. Temperature and relative humidity data were downloaded from the Copernicus Climate Change Service’s ERA5-Land and ERA5 pressure level datasets, respectively, with reanalysis from 1951 to 2023. The results revealed a clear upward trend in temperatures over the last several decades in these four places and for the respective dates, from +0.3 °C per decade in La Bisbal del Penedès to +0.42 °C per decade in Valls. Most of the positive temperature anomalies were concentrated in the last 25 years. The calculation of the Heat Index revealed a higher occurrence of years with possible fatigue due to prolonged exposure and/or physical activity in the three inland locations (i.e., Valls, La Bisbal del Penedès, and Vilafranca del Penedès) and a greater frequency of years with possible heat stroke, heat cramps, and/or heat exhaustion in Tarragona, which is near the Mediterranean Sea. This warming trend and increased discomfort pose potential health risks for participants and suggests a need for adaptive measures. These findings emphasize the importance of incorporating climate considerations into human tower planning.

In rainfed areas, precipitation variations directly impact wheat growth stages such as emergence, tillering, jointing and booting, and maturity. Evaluating the impact of climate change on precipitation patterns during these critical growth stages is crucial for adapting climate change and ensuring global food security. In this study, projections of five General Circulation models (GCMs) under two shared socioeconomic pathways (SSPs) were used to predict the changing characteristics of precipitation during four main growth stages of wheat in the rainfed region of the Pothwar Plateau, Pakistan. Historical datasets of daily precipitation at six weather stations were analyzed to check the past changes in the precipitation patterns. During the baseline period (1985–2014), the annual average precipitation decreased at a rate of −9.75 mm/decade, while the amount of precipitation during the rabi season (wheat-growing season) decreased at a rate of −20.47 mm/decade. An increase in the precipitation was found during the fourth (flowering) stage of crop growth, while the first three stages experienced a decrease in the precipitation amount. The multimodal ensembled data, under the SSP2-4.5 scenario, revealed a significant decline (at the rate of −16.63 mm/decade) in the future annual precipitation. However, it is projected that, under SSP2-4.5, there may be a slight increase (4.03 mm/decade) in the total precipitation amount during the future rabi season. Under the SSP5-8.5 scenario, average annual precipitation exhibited a slightly increasing trend, increasing by 1.0 mm/decade. However, during the rabi season, there was a possibility of a decrease in precipitation amount, with a rate of 11.64 mm/decade. It is also expected that the precipitation amount may vary significantly during the crown root initiation, jointing and booting, and flowering stages in the near future. These results provide a framework for the planning of wheat production in the Pothwar region of Pakistan, taking into account the potential impact of shifting weather patterns, particularly in terms of uneven precipitation.

The Madeira River, a major tributary of the Amazon River, often undergoes severe flood and drought conditions. This study seeks to investigate the climate processes associated with the opposing extreme precipitation events in the Madeira River basin and to relate them to river discharge variability based on a flood awareness dataset. Despite the uncertainty in the observational datasets, the annual precipitation cycle exhibits a rainy season from November to March. A significant result is the high correlation between the rainy season variability in the Madeira River basin and the sea surface temperature (SST) anomalies in the tropical North Atlantic Ocean and the southwestern South Atlantic Ocean. This result indicates that improving the Atlantic SST representation in climate modeling allows for capturing extreme precipitation events in the region. In addition to this impact, certain Madeira River tributaries present significant climate trends. The river discharge variability reveals an increase in hydrological extremes in recent years in the upper sector, but more significantly, in the lower basin, where it has reduced by more than 400 m3/s per decade. These findings highlight the need to improve in situ data and climate and hydrological modeling, with a focus on describing the intense climate variability and trends in river discharges.