Search Results (34)

We report a landscape-scale natural experiment that followed the abundance and demography of forest-floor small mammals and the activity of small mustelids over a 4-year period of an extreme heat wave and abundant coniferous cone crops. Deer mice (Peromyscus maniculatus) and southern red-backed voles (Myodes gapperi) are major species in the coniferous forest-floor small mammal community near Summerland in southern British Columbia, Canada. Their major mammalian predators include the short-tailed weasel (Mustela richardsonii), long-tailed weasel (Neogale frenata), and American marten (Martes americana). We evaluated three hypotheses (H) that may explain the changes in these mammals from 2021 to 2024: (H₁) that large coniferous cone crops in 2022 would have generated high populations of forest-floor small mammals in 2023 owing to enhanced reproductive output and overwinter survival; (H₂) that increased activity of mustelids would have followed population increases, resulting in the decline of small mammal prey in 2024; and (H₃) that the widespread occurrence of cone crops in 2022 would also have elicited the same mammalian responses in 2023 at a second study area (Golden, BC) 276 km and three mountain ranges from Summerland. During the summer periods of each year, small mammal populations were monitored by intensive live-trapping, and mustelid presence was measured via an index of activity based on live traps, fecal scats, and predation events. The mean abundance and reproductive performance of the P. maniculatus and M. gapperi populations increased in response to the coniferous seedfall, thereby supporting H₁. The activity of small mustelids responded positively to increased numbers of small mammal prey and potentially acted in a regulatory and top–down function in these communities, and hence partially support H₂. Similar responses at Summerland and Golden indicated that this seedfall event and changes in the mammalian community occurred at a landscape-scale, thereby providing partial support for H₃. Potential differential effects of large seed crops on consumers did not affect the mean abundance patterns for P. maniculatus but apparently reduced this metric for M. gapperi. Heat waves, induced by anthropogenic climate change, may alter the frequency of coniferous masting events, and their effects may temporarily change the number and species of mammalian seed consumers and their predators. Full article

The impact of the quasi-biennial oscillation (QBO) and Madden–Julian oscillation (MJO) on the dynamics of major sudden stratospheric warmings (SSWs) observed in the winters of 2018, 2019, and 2021 is investigated. Using data from the MERRA-2 reanalysis, we analyze the daily mean variability of critical atmospheric parameters at the 10 hPa level, including zonal mean polar cap temperature, zonal mean zonal wind, and the amplitudes of planetary waves 1 and 2. The results reveal dramatic increases in polar cap temperature and significant wind reversals during the SSW events, particularly in 2018. The analysis of planetary wave (PW) amplitudes demonstrates intensified wave activity coinciding with the onset of SSWs, underscoring the pivotal role of PWs in these stratospheric disruptions. Further examination of outgoing long-wave radiation (OLR) anomalies highlights the influence of QBO phases on tropical convection patterns. During westerly QBO (w-QBO) phases, enhanced convective activity is observed in the western Pacific, whereas the easterly QBO (e-QBO) phase shifts convection patterns to the maritime continent and central Pacific. This modulation by QBO phases influences the MJO’s role during SSWs, affecting tropical and extra-tropical weather patterns. The day-altitude variability of upward heat flux reveals distinct spatiotemporal patterns, with pronounced warming in the polar regions and mixed heat flux patterns in low latitudes. The differences observed between the SSWs of 2017–2018 and 2018–2019 are likely related to the varying QBO phases, emphasizing the complexity of heat flux dynamics during these events. The northern annular mode (NAM) index analysis shows varied responses to SSWs, with stronger negative anomalies observed during the e-QBO phase compared to the w-QBO phases. This variability highlights the significant role of the QBO in shaping the stratospheric and tropospheric responses to SSWs, impacting surface weather patterns and the persistence of stratospheric anomalies. Overall, the study demonstrates the intricate interactions between stratospheric dynamics, QBO, and MJO during major SSW events, providing insights into the broader implications of these atmospheric phenomena on global weather patterns. Full article

Maize is affected by drought and heat, abiotic stress factors that have been encountered more often in recent years in various parts of Europe. In the area of Turda, Romania, extreme temperatures and heat waves combined with an uneven distribution of precipitation have been recorded that had an unfavorable influence on the maize crop. In this study, the ASI (anthesis-to-silking interval), yield, and stability of 35 old and new maize hybrids created at the Agricultural Research and Development Station Turda were studied under drought and heat conditions. An increase in temperature was observed during vegetative growth and grain filling, and rainfall was deficient during and after flowering. These conditions had a negative influence on ASI, grain filling, and, indirectly, yield, which varied significantly during the seven experimental years. The five newest hybrids (Turda335, Turda2020, Turda380, Sur18/399, and HST148) stood out, with average yields of over 8400 kg ha⁻¹ in unfavorable years and over 15–16,000 kg ha⁻¹ under favorable conditions. They generally outperformed the mean by 29–33%. In contrast, the old hybrids achieved yields up to 22% lower than the experimental mean. Yield was 43.1% lower in 2022 and 31.8% lower in 2023 compared to the best year (2021). Full article

This study investigates the impact of green roof (GR) implementations as a mitigation strategy for urban heating during an extreme heat wave event in Athens, Greece, from 28 July to 5 August 2021. Three GR scenarios were simulated, namely 100% grass coverage, 100% sedum coverage, and 50% grass coverage, using the Weather Research and Forecasting model (WRF) in conjunction with the multi-layer urban-canopy-model BEP&BEM (Building Effect Parameterization/Building Energy Model) and extra urban land-use categories from Local Climate Zones (LCZ). Based on the results, GRs alter the local heat balance in the Greater Area of Athens (GAA), leading to a total temperature reduction. The 100% grass coverage proved to be the most effective, particularly during daytime, reducing the 2 m temperature field by approximately 0.7 ${}^{\circ }$C (mean value) in the GAA. In some locations, temperature reductions exceeded 2 ${}^{\circ }$C, depending on the local characteristics and the direction of the prevailing winds. Grass offered superior cooling effects compared to sedum, although sedum is more resilient to dry and moderate climates. The extent of vegetation coverage played an important role in the effectiveness of GRs. Reducing the coverage by 50% significantly reduced the cooling benefits, highlighting the importance of maximizing vegetation coverage to achieve notable temperature reductions. Full article

The urban heat island effect (UHI) is among the major challenges of urban climate, which is continuously intensifying its impact on urban life and functioning. Against the backdrop of increasingly prolonged heatwaves observed in recent years, practical questions about adaptation measures in cities are growing—questions that traditional meteorological monitoring can hardly answer adequately. On the other hand, UHI has long been the focus of research interest, but due to the technological complexity of providing accurate spatially referenced data at high spatial resolution and the requirement to survey at strictly defined parts of the day, information provision is becoming a major challenge. This is one of the main reasons why UHI research results are less often used directly in urban spatial planning. However, advances in geospatial technologies, including unmanned aerial systems (UASs), are providing more and more reliable tools that can be applied to achieve better and higher-quality information resources that adequately characterize the UHI phenomenon. This paper presents a developed and tested methodology for the rapid and efficient assessment and mapping of the effects of surface urban heat island (SUHI). It is entirely based on the integrated use of data from unmanned aerial systems (UAS)-based remote sensing methods, including thermal photogrammetry and GIS-based analysis methods. The study follows the understanding that correct SUHI research depends on a proper understanding of the urban geosystem, its spatial and structural heterogeneity, and its functional systems, which in turn can only be achieved by supporting the research process with accurate and reliable information resources. In this regard, the possibilities offered by the proposed methodological scheme for efficient geospatial registration of SUHI variations at the microscale, including the calculation of intra-urban SUHI intensity, are discussed in detail. The methodology builds on classical approaches for using local climate zoning (LCZ), adding capabilities for precise delineation of individual zone types and for geostatistical characterization of the urban surface heat island (SUHI). Finally, the proposed scheme is based on state-of-the-art technological tools that provide flexible and automated capabilities to investigate the phenomenon at microscales, including by enabling flexible observation of its dynamics in terms of heat wave manifestation and evolution. Results are presented from a series of sequential tests conducted on the largest residential area in Bulgaria’s capital city, Sofia, in terms of area and population, over a relatively long period from 2021 to 2024. Full article

Wildfires present a major global environmental issue, exacerbated by climate change. The Iranian Northern Zagros Forests, characterized by a Mediterranean climate, are particularly vulnerable to fires during hot, dry summers. This study investigates the impact of climate change on forest fires in these forests from 2006 to 2023. The analysis revealed significant year-to-year fluctuations, with notable fire occurrence in years 2007, 2010, 2021, and 2023. The largest burned area occurred in 2021, covering 2655.66 ha, while 2006 had the smallest burned area of 175.27 ha. Climate variables such as temperature, humidity, precipitation, wind speed, heat waves, and solar radiation were assessed for their effects on fire behavior. Strong correlations were found between higher average temperatures and larger burned areas, as well as between heat waves and increased fire frequency. Additionally, higher wind speeds were linked to larger burned areas, suggesting that increased wind speeds may enhance fire spread. Multiple linear regression models demonstrated high predictive accuracy, explaining 84% of the variance in burned areas and 69.6% in the variance in fire frequency. These findings document the growing wildfire risk in the Northern Zagros region due to climate change, highlighting the urgent need to integrate scientific research with policies to develop effective wildfire management strategies for sustainable forest management. Full article

Wave-induced mixing can enhance vertical mixing in the upper ocean, facilitating the exchange of heat and momentum between the surface and deeper layers, thereby influencing ocean circulation and climate patterns. Building on previous research, this study proposes a wave-induced mixing parameterization scheme (referred to as EXP3) specifically designed for typhoon periods. This scheme was integrated into the fully coupled ocean–wave–atmosphere model COAWST and applied to analyze Typhoon In-Fa (2021) as a case study. The simulation results were validated against publicly available data, demonstrating a good overall match with observed phenomena. Subsequently, a comparative analysis was conducted between the EXP3 scheme, the previous scheme (EXP2) and the original model scheme (EXP1). Validation against Argo and Drifter buoy data revealed that both EXP2 and EXP3, which include wave-induced mixing effects, resulted in a decrease in the simulated mixed layer depth (MLD) and mixed layer temperature (MLT), with EXP3 showing closer alignment with the observed data. Compared to the other two experiments, EXP3 enhanced vertical motion in the ocean due to intensified wave-induced mixing, leading to increased upper-layer water divergence and upwelling, a decrease in sea surface temperature and accelerated rightward deflection of surface currents. This phenomenon not only altered the temperature structure of the ocean surface layer but also significantly impacted the regional ocean dynamics. Full article

Algeria, the main fire hotspot on the southern rim of the Mediterranean Basin, lacks a complete fire dataset with official fire perimeters, and the existing one contains inconsistencies. Preprocessed global and regional burned area (BA) products provide valuable insights into fire patterns, characteristics, and dynamics over time and space, and into their impact on climate change. Nevertheless, they exhibit certain limitations linked with their inherent spatio-temporal resolutions as well as temporal and geographical coverage. To address the need for reliable BA information in Algeria, we systematically reconstructed, validated, and analyzed a 40-year (1984–2023) BA product (NEALGEBA; North Eastern ALGeria Burned Area) at 30 m spatial resolution in the typical Mediterranean ecosystems of this region, following international standards. We used Landsat data and the BA Mapping Tools (BAMTs) in the Google Earth Engine (GEE) to map BAs. The spatial validation of NEALGEBA, performed for 2017 and 2021 using independent 10 m spatial resolution Sentinel-2 reference data, showed overall accuracies > 98.10%; commission and omission errors < 8.20%; Dice coefficients > 91.90%; and relative biases < 3.44%. The temporal validation, however, using MODIS and VIIRS active fire hotspots, emphasized the limitation of Landsat-based BA products in temporal fire reporting accuracy terms. The intercomparison with five readily available BA products for 2017, by using the same validation process, demonstrated the overall outperformance of NEALGEBA. Furthermore, our BA product exhibited the highest correspondence with the ground-based BA estimates. NEALGEBA currently represents the most continuous and reliable time series of BA history at fine spatial resolution for NE Algeria, offering a significant contribution to further national and international fire hazard and impact assessments and acts as a reference dataset for contextualizing future weather extremes, such as the 2023 exceptional heat wave, which we show not to have led to the most extreme fire year over the last four decades. Full article

This study identified the practices of adaptation strategies to climate change in Jimma, Bedelle, Bonga, and Sokorru urban centers using a survey of 384 households, 55 key informant interviews, 4 focus group discussions, and field observations. A cross-sectional study design was employed from 2019 to 2021. The adaptive capacity of municipalities to reduce climate extreme events was rated as poor by the majority (51%), mostly reactive measures (76%). The climate hazards identified in four urban centers were riverine and flash floods, urban heat waves, landslides, and windstorms. The urban households practiced lifestyle modification, reduce paved surfaces, the use of air conditioner, planting trees, and multiple windows. The adaptation strategies practiced by municipalities include the relocation of prone areas, the support of basic amenities, the construction of protection walls, diversion ditches, the clearance of waterways and rivers, greenery, and park development. The adaptation actions were constrained by a lack of awareness, commitment, cooperation and coordination, adaptive capacity, and participation. Gray/physical infrastructures (costly but important) as adaptation actions were hampered by the low municipal capacity. We recommend that urban authorities should incorporate climate change adaptation strategies into urban planning and development proactively to ensure future resilient climate smart urban centers of southwest Ethiopia. Full article

Using shallow-water buoy observations, reanalysis data, and numerical models, this study analyzes the variations in sea temperature and significant wave height (SWH) caused by two sequential tropical cyclones (TCs) ‘Lionrock’ and ‘Kompasu’ in October 2021 in the northeast Beibu Gulf, South China Sea. The results show that the sea surface temperature (SST) cooling of the nearshore waters was larger than the offshore water in the basin of the gulf, with the cooling amplitude and rate decreasing and the cooling time lagging behind wind increasing from coast to offshore. The near-surface temperature at the buoy station had a maximum decrease of 2.8 °C after ‘Lionrock’, and the decrease increased slightly to 3 °C after the stronger wind of ‘Kompasu’. The total decrease of 4.6 °C indicates that the sequential TCs had a superimposed effect on the cooling of the Beibu Gulf. The heat budget analysis revealed that the sea surface heat loss and the Ekman pumping rate in the nearshore waters during ‘Kompasu’ (−535 W/m² and 5.8 × 10⁻⁴ m/s, respectively) were significantly higher than that (−418 W/m² and 4 × 10⁻⁴ m/s) during ‘Lionrock’. On the other hand, the SST cooling (−1.2 °C) during the second TC is smaller than (−1.6 °C) the first weaker TC in the gulf basin, probably due to the deepening of the mixed layer. During the observation period, the waves in the Beibu Gulf were predominantly wind-driven. The maximum SWHs reached 1.58 m and 2.3 m at the bouy station near shore during the two TCs, and the SWH variation was highly correlated to the wind variation with a correlation of 0.95. The SWH increases from the nearshore to offshore waters during the TCs. The SAWN and ARCIRC coupled model results suggest that wave variations in the Beibu Gulf are primarily influenced by water depth, bottom friction, and whitecapping. Two days after the TCs, sea surface cooling and high waves appeared again due to a cold air event. Full article

In this study, a total of 34 Spanish minority varieties were studied during four seasons from 2020 to 2023, and their behavior was characterized according to their main phenological stages (bud break, bloom, veraison, and maturity) and complete cycle. We focused on the varieties prospected in the central Spanish plateau and conserved in the “El Encín” grapevine collection, aiming to identify the potential for adaptation of these varieties and for them to be considered by winegrowers as an alternative to current climate change conditions. The growing degree days required for the expression of the phenological stage, and the duration of each stage, were compiled. Characteristics of oenological interest were also monitored, such as °Brix, pH, and titratable acidity in must at the time of harvest. This study was carried out in years with atypical snowfall and cold spells (winter 2021), as well as with heat waves (summer 2022), with average temperatures 3–5 °C higher than normal and absolute maximum temperatures over 40 °C. Both cases also exceeded records of historical series (1957–2019). Veraison has been identified as the stage most susceptible to damage from high temperatures, in addition to the maturation and duration of the complete cycle. The varieties were classified into five groups according to the duration of each phenological stage (very early, early, medium, late, and very late). Some varieties with late or very late maturation and with must characteristics of 20–23 °Brix, 3–5 g/L of titratable acidity, and pH 3.5–4.5, as well as others, retained stability in their phenological periodicity and must quality. The results suggest that special attention should be given to thoroughly evaluating these varieties, and that the strategies contemplated should be considered as a feasible cultivation alternative in viticulture to mitigate the effects of climate change. Full article

Among the most vulnerable to the health-harming effects of heat are people experiencing homelessness. However, during the 2021 Heat Dome, the deadliest extreme heat event (EHE) recorded in Canada to date, people experiencing homelessness represented the smallest proportion of decedents (n = 3, 0.5%)—despite the impacted region (British Columbia) having some of the highest rates of homelessness in the country. Thus, we sought to explore the 2021 Heat Dome as a media-based case study to identify potential actions or targeted strategies that were initiated by community support agencies, individuals and groups, and communicated in the news during this EHE that may have aided in the protection of this group or helped minimize the mortality impacts. Using media articles collated for a more extensive investigation into the effects of the 2021 Heat Dome (n = 2909), we identified a subset which included content on people experiencing homelessness in Canada (n = 274, 9%). These articles were thematically analysed using NVivo. Three main themes were identified: (i) public warnings issued during the 2021 Heat Dome directly addressed people experiencing homelessness, (ii) community support services explicitly targeting this population were activated during the heat event, and (iii) challenges and barriers faced by people experiencing homelessness during extreme heat were communicated. These findings suggest that mass-media messaging and dedicated on-the-ground initiatives led by various organizations explicitly initiated to support individuals experiencing homelessness during the 2021 Heat Dome may have assisted in limiting the harmful impacts of the heat on this community. Full article

Accurate sea surface temperature (SST) prediction is vital for disaster prevention, ocean circulation, and climate change. Traditional SST prediction methods, predominantly reliant on time-intensive numerical models, face challenges in terms of speed and efficiency. In this study, we developed a novel deep learning approach using a 3D U-Net structure with multi-source data to forecast SST in the South China Sea (SCS). SST, sea surface height anomaly (SSHA), and sea surface wind (SSW) were used as input variables. Compared with the convolutional long short-term memory (ConvLSTM) model, the 3D U-Net model achieved more accurate predictions at all lead times (from 1 to 30 days) and performed better in different seasons. Spatially, the 3D U-Net model’s SST predictions exhibited low errors (RMSE < 0.5 °C) and high correlation (R > 0.9) across most of the SCS. The spatially averaged time series of SST, both predicted by the 3D U-Net and observed in 2021, showed remarkable consistency. A noteworthy application of the 3D U-Net model in this research was the successful detection of marine heat wave (MHW) events in the SCS in 2021. The model accurately captured the occurrence frequency, total duration, average duration, and average cumulative intensity of MHW events, aligning closely with the observed data. Sensitive experiments showed that SSHA and SSW have significant impacts on the prediction of the 3D U-Net model, which can improve the accuracy and play different roles in different forecast periods. The combination of the 3D U-Net model with multi-source sea surface variables, not only rapidly predicted SST in the SCS but also presented a novel method for forecasting MHW events, highlighting its significant potential and advantages. Full article

In recent decades, large-scale urbanisation has developed rapidly, resulting in significant changes in the local and regional environment and climate. Large metropolitan areas worldwide induce significant changes in local atmospheric circulation and boundary layer meteorology by modifying the underlying surface characteristics and through the emission of anthropogenic heat and pollutants into the atmosphere. We investigate the urban heat island (UHI) characteristics in the city of Athens, Greece, which is one of Europe’s largest metropolitan complexes with a population of approximately 3.7 million inhabitants. The UHI effect is intense due to the city’s size, dense construction, high incident solar radiation, and almost complete lack of natural vegetation, with previous studies suggesting a temperature rise of 4 °C on average in the city centre compared to summer background conditions. We used high-resolution WRF simulations (1-km horizontal grid) driven with ERA5 reanalysis data to produce surface temperature maps in the city of Athens and the surrounding areas (Region of Attiki) during the summer period of 1 July–20 August 2021. Different model parameterizations were tested, both with respect to urban characteristics and physical parameters. The daily minimum and maximum temperatures (T_min and T_max) derived from the model were validated against observational data from a dense network of weather stations covering metropolitan Athens and surrounding locations. We further investigate the influence of different meteorological conditions on the UHI gradients as produced by the model and the observational dataset, including the extreme heat wave of 28 July–5 August 2021, during which persistent maximum temperatures of >40 °C were recorded for nine consecutive days. The results indicate a strong correlation between WRF output and recorded minimum and maximum temperatures throughout the test period (R ranges from 0.80 to 0.93), with an average mean absolute bias (MAB) of 1.5 °C, and reveal the intensity and spatiotemporal variability of the UHI phenomenon in the city of Athens, with UHI magnitude reaching 8–9 °C at times. Our work aims to maximise the potential of using high-resolution WRF modelling for simulating extreme heat events and mapping the UHI effect in large metropolitan complexes. Full article

With the acceleration of urbanization, urban heat waves have become a major problem affecting the lives of citizens. In this context, the accurate identification of the key patches and nodes of urban heat islands is important for improving the urban environment. This study examined the Landsat image data from Xiamen city in 2001, 2011, and 2021 to analyze the construction of the urban heat island (UHI) network. A morphological spatial pattern analysis (MSPA) and landscape connectivity model were utilized to identify the central thermal landscape patches and key nodes of UHI and their spatial and temporal evolution characteristics in the urban development process. The ultimate goal of this research is to provide valuable insights that can contribute to the enhancement of the urban environment. The results showed that (1) there was a significant increase in the heat island area (HIA) of Xiamen from 2001 to 2021, and the heat island patches show a concentrated trend. The temperature contrast between the urban area and the surrounding countryside was more distinct, indicating the urban construction land has a tendency to gather and spread. (2) The core area of the heat island accounted for the largest proportion of the thermal landscape area during the study period, and its proportion increased significantly. And the rate of increase was first rapid and then slow. The areas of the edge, branch, islet, bridge, loop, and perforation classes all showed different degrees of a decreasing trend. This indicates an increasing degree of aggregation between heat island patches. (3) The top 20 thermal landscape patches with high landscape connectivity importance values were identified. Among them, the importance value and area of the first four patches are relatively large, and belong to the three importance classes of extremely important, important, and generally important heat island core patches, which deserve focused attention and optimization. (4) Cooling measures can be prioritized for core areas of heat islands with high importance values. Connections between hot and cold islands can be interrupted or connected to mitigate the heat island effect throughout the region. The results of this study have important practical guidance for urban planning and sustainable development. Full article