Climate

In small island regions, the influence of climate change assumes particular relevance. In the Azores archipelago, made up of nine islands, the geographical circumstances, oceanic condition, territorial dispersion, land use model and other physiographic constraints reinforce and enhance the vulnerability of the islands to changes in current weather patterns. Coupled Model Intercomparison Phase 6 (CMIP6) projections are used for the northeast Atlantic region to evaluate daily extreme climate events in large scale for the Azores region. Results shows changes in the annual maximum number of consecutive dry days, the annual number of wet days, and especially in the annual number of tropical nights. Despite limitations due to the lack of spatial detail, the large-scale framework suggests changes that may be enhanced by topography, particularly with respect to precipitation. The conclusions point to the need to establish standard rules in the processes of design, reviewing and/or amending territorial management instruments at the municipal scale in the Autonomous Region of the Azores, with the goal of adapting to a different climate from the recent past. Full article

This study analyzes insurance claim data from an 11-county area in the Florida Panhandle following the landfall of Hurricane Michael. The data includes 1467 non-mobile home structures, with 902 (61.5%) storm-damaged structures in Bay County. The analysis focuses on Wind Mitigation form 1802. Specifically, building design variables were analyzed via linear regression as to their influence on the percent claim loss. The building design variables included total square footage, dwelling construction type, age of the building, roof type, roof cover type, roof deck attachment type, roof to wall attachment, the presence of secondary water resistance (or sealed roof deck), opening protection type, and roof shape. Results show that building design variables for insurance claims have a high predictive value relative to a Category 5 hurricane event. However, the predictive values of building design variables are also dependent on the dwelling’s proximity to the coast, its location relative to the strong or weak side of the storm, the diameter of the storm, and other wind field variables. Full article

An attempt has been made to explore the relative contributions of moisture feedback processes on tropical intraseasonal oscillation or Madden–Julian Oscillation (MJO). We focused on moisture feedback processes, including evaporation wind feedback (EWF) and moisture convergence feedback (MCF), which integrate the mechanisms of convective interactions into the tropical atmosphere. The dynamical framework considered here is a moisture-coupled, single-layer linear shallow-water model on an equatorial beta-plane with zonal momentum damping. With this approach, we aimed to recognize the minimal physical mechanisms responsible for the existence of the essential dispersive characteristics of the MJO, including its eastward propagation ($k>0$), the planetary-scale (small zonal wavenumbers) instability, and the slow phase speed of about ≈5 m/s. Furthermore, we extended our study to determine each feedback mechanism’s influence on the simulated eastward dispersive mode. Our model emphasized that the MJO-like eastward mode is a possible outcome of the combined effect of moisture feedback processes without requiring additional complex mechanisms such as cloud radiative feedback and boundary layer dynamics. The results substantiate the importance of EWF as a primary energy source for developing an eastward moisture mode with a planter-scale instability. The eastward moisture mode exhibits the highest growth rate at the largest wavelengths and is also sensitive to the strength of the EWF, showing a significant increase in the growth rate with the increasing strength of the EWF; however, the eastward moisture mode remains unstable at planetary-scale wavelengths. Moreover, our model endorses that the MCF alone could not produce instability without surface fluxes, although it has a significant role in developing deep convection. It was found that the MCF exhibits a damping mechanism by regulating the frequency and growth rate of the eastward moisture mode at shorter wavelengths. Full article

Tropical cyclones (TCs) are one of the most destructive natural hazards to impact on Australia’s population, infrastructure, and the environment. To examine potential TC impacts, it is important to understand which assets are exposed to the hazard and of these, which are vulnerable to damage. The aim of this study is to improve TC risk assessments through developing an exposure–vulnerability index, utilising a case study for the six Local Government Areas (LGAs) impacted by the landfall of TC Debbie in 2017: Burdekin Shire, Charters Towers Region, Isaac Region, Mackay Region, City of Townsville, and Whitsunday Region. This study utilised a natural hazard risk assessment methodology, linking exposure and vulnerability indicators related to social factors, infrastructure, and the environment. The two LGAs with the most extreme exposure–vulnerability values were the coastal regions of Mackay Region and the City of Townsville. This is consistent with urbanisation and city development trends, with these LGAs having more people (social) and infrastructure exposed, while the environmental domain was more exposed and vulnerable to TC impacts in rural LGAs. Therefore, further resilience protocols and mitigation strategies are required, particularly for Mackay Region and the City of Townsville, to reduce the damage and ultimate loss of lives and livelihoods from TC impacts. This study serves as a framework for developing a TC risk index based on hazard, exposure, and vulnerability indices, and insight into the improved mitigation strategies for communities to implement in order to build resilience to the impacts of future TCs. Full article

China has long sought to address climate change in line with other development goals. However, research supporting this alignment often employs data-driven models that downplay the policies and institutions needed to achieve the multiple benefits that studies feature in their analyses. This oversight is troubling because it neglects gaps between goals and the actual integration of climate and development or co-control of air pollution and greenhouse gases (GHGs). Additionally, this oversight may overlook growing implementation challenges as China pursues synergies between net-zero emissions, biodiversity, and circularity. This article illustrates these challenges by tracing the goals and policies/institutions in China over three phases: (1) integration (1979–2010), (2) co-control (2011–2019), and (3) synergies (2020–present). This article argues that China needs to strengthen the science–policy interface and ensure that new market-based policy instruments (such as emissions trading programs) as well as the leadership responsibility system incentivize reductions in overall GHG emissions while shrinking ecological footprints in the shifts to synergies. Full article

This study answers four research questions by contextualising the background to Japan’s “carbon neutrality and net-zero” (CNN) policy, which was announced in October 2020, and identifying important changes in Japanese climate policy between 1990 and 2020. What is the link between the problem of fairness under the Kyoto targets and the Japanese government’s initial reluctance towards ambitious carbon emission reductions? Why did the Japanese business sector initially resist the possibility of ambitious carbon emission reductions? How has the term “climate crisis” contributed to the need for CNN policy? Why did the Japanese government change its reluctant stance and announce the CNN policy in October 2020? Four main findings were extracted from a narrative technique-based analysis of Japan’s policy documents related to CNN. The following are the findings: [i] the framing of climate change as a “climate crisis” by influential Japanese climate stakeholders was a key motivation for Japan to formally announce its CNN policy in October 2020; [ii] pressure from the international community and the political leadership of the Yoshihide Suga administration are essential factors that led the Japanese government to change its stance and announced this policy; [iii] it is possible that the policy could have been announced sooner, but concern among Japanese climate stakeholders about the problem of fairness in the Kyoto Protocol’s emission reduction targets likely impeded such an announcement; and [iv] this concern underpinned Keidanren’s (or the business sector’s) consistent opposition to the introduction of regulatory schemes. These results emerge for the first time in a study of Japan’s carbon neutrality, particularly in terms of the broader context of climate politics. Finally, we offer a possible explanation for Suga’s deliberate announcement of the CNN policy. This opens up space for future research to complement our study by providing important indicators on the trajectory of this important policy. Full article

Tropical cyclones (TC) are one of the deadliest natural meteorological hazards with destructive winds and heavy rains, resulting losses often reach billions of dollars, imposing a substantial and long-lasting burden on both local and national economies. The El-Niño Southern Oscillation (ENSO), a tropical ocean–atmosphere interaction, is known to significantly impact cyclonic systems over global ocean basins. This study investigates the variability of TC activity in the presence of ENSO over the North Indian Ocean (NIO), comprising the Arabian Sea (ARB) and the Bay of Bengal (BOB) basins during the pre- and post-monsoon season, using accumulated cyclone energy (ACE) over the last 29 years. Our analysis reveals a significant rise in tropical cyclone energy intensity over the past two decades, with eight of the ten most active years occurring since the 2000s. Total ACE over the NIO is found to be higher in La-Niña. Higher ACE observed over ARB is strongly associated with a combination of elevated sea surface height (SSH) anomaly and low vertical wind shear during the El-Niño episodes, with higher sea surface temperatures (SST) during the post-monsoon season. Whereas in the BOB, El Niño not only reduces ACE, but also decreases basin-wide variability, and more pronounced effects during the post-monsoon season, coinciding with warmer SST and higher SSH along the coast during La-Niña. Full article

The UN vision of climate resilience contains three independent outcomes: resilient people and livelihoods, resilient business and economies, and resilient environmental systems. This article analyzes the positive contributions of low-carbon energy technologies to climate resilience by reviewing and critically assessing the existing pool of studies published by researchers and international organizations that offer comparable data (quantitative indicators). Compilation, critical analysis, and literature review methods are used to develop a methodological framework that is in line with the UN vision of climate resilience and makes it possible to compare the input of low-carbon energy technologies climate resilience by unit of output or during their lifecycle. The framework is supported by the three relevant concepts—energy trilemma, sharing economy/material footprint, and Planetary Pressures-Adjusted Human Development Index. The study identifies indicators that fit the suggested framework and for which the data are available: total material requirement (TMR), present and future levelized cost of electricity (LCOE) without subsidies, CO₂ emissions by fuel or industry, lifecycle CO₂-equivalent emissions, and mortality rates from accidents and air pollution. They are discussed in the paper with a focus on multi-country and global studies that allow comparisons across different geographies. The findings may be used by decision-makers when prioritizing the support of low-carbon technologies and planning the designs of energy systems. Full article

In the context of climate change, where the average temperature has risen in recent decades on the Mediterranean coast of the Iberian Peninsula, bioclimatic indicators show an increase in thermal discomfort. This is especially relevant in regions with a clear focus on mass and seasonal sun and beach tourism, with a large number of tourists experiencing discomfort in hot and humid summer environments. The research analyses the temporal evolution (1967–2022) of the coasts of the provinces of Alicante and Murcia (Spain) using the Climate Comfort Index (CCI), divided into four different regions. Used are 14 coastal meteorological observatories divided into four regions. Trend analysis was performed using the Mann–Kendall (MKT) and Theil–Sen (TSE) tests. The results revealed a loss of climate comfort during the summer season (−0.3 to −0.4/decade), as well as an expansion of the warm period toward June and early September, with an increase of 38.7 days in “hot” thermal comfort. The increase in thermal discomfort in the summer is influenced by an increase in average temperature (0.5 to 0.7 °C/decade) and a reduction in the average relative humidity (−1.0 to −2.1%/decade) and wind speed (−0.2 to −0.9 km/h/decade). In the last 22 years (2000–2022), decreases (p  ≤ 0.05) have been recorded in July and September (−0.2 to −0.4/decade), reaching “excessive heat” climatic comfort thresholds for the first time. Finally, there has been an increase in thermal comfort in winter, especially during December in recent years (2000–2022). Full article

This study investigated tropical cyclone (TC)-induced flooding in coastal regions of Australia due to the impact of TC Debbie in 2017 utilising a differential evolution-optimised random forest to model flood susceptibility in the region of Bowen, Airlie Beach, and Mackay in North Queensland. Model performance was evaluated using a receiver operating characteristic curve, which showed an area under the curve of 0.925 and an overall accuracy score of 80%. The important flood-influencing factors (FIFs) were investigated using both feature importance scores and the SHapely Additive exPlanations method (SHAP), creating a flood hazard map of the region and a map of SHAP contributions. It was found that the elevation, slope, and normalised difference vegetation index were the most important FIFs overall. However, in some regions, the distance to the river and the stream power index dominated for a similar flood hazard susceptibility outcome. Validation using SHAP to test the physical reasoning of the model confirmed the reliability of the flood hazard map. This study shows that explainable artificial intelligence allows for improved interpretation of model predictions, assisting decision-makers in better understanding machine learning-based flood hazard assessments and ultimately aiding in mitigating adverse impacts of flooding in coastal regions affected by TCs. Full article

On 20 July 2021, an extreme rainstorm battered Zhengzhou in China’s Henan Province, killing 302 people, including 14 individuals who drowned in a subway tunnel and 6 who drowned in a road tunnel. As the global climate warms, extreme weather events similar to the Zhengzhou flood will become more frequent, with increasingly catastrophic consequences for society. Taking a case study-based approach by focusing on the record-breaking Zhengzhou flood, this paper examines the governance capacity of inland cities in North China for managing extreme precipitation and flooding events from the perspective of the flood risk management process. Based on in-depth case analysis, our paper hypothesizes that inland cities in North China still have low risk perceptions of extreme weather events, which was manifested in insufficient pre-disaster preparation and prevention, poor risk communication, and slow emergency response. Accordingly, it is recommended that inland cities update their risk perceptions of extreme rainfall and flooding events, which are no longer low-probability, high-impact “black swans”, but turning into high-probability, high-impact “gray rhinos.” In particular, cities must make sufficient preparation for extreme weather events by revising contingency plans and strengthening their implementation, improving risk communication of meteorological warnings, and synchronizing emergency response with meteorological warnings. Full article

In semi-arid regions, climate change has affected crop growing season length and sowing time, potentially causing low yield of the rainfed staple crop pearl millet (Pennisetum glaucum L.) and food insecurity among smallholder farmers. In this study, we used 1994–2023 rainfall data from Namibia’s semi-arid North-Central Region (NCR), receiving November–April summer rainfall, to analyze rainfall patterns and trends and their implications on the growing season to propose climate adaptation options for the region. The results revealed high annual and monthly rainfall variabilities, with nonsignificant negative trends for November–February rainfalls, implying a shortening growing season. Furthermore, we determined the effects of sowing date on grain yields of the early-maturing Okashana-2 and local landrace Kantana pearl millet varieties and the optimal sowing window for the region, using data from a two-year split-plot field experiment conducted at the University of Namibia—Ogongo Campus, NCR, during the rainy season. Cubic polynomial regression models were applied to grain-yield data sets to predict grain production for any sowing date between January and March. Both varieties produced the highest grain yields under January sowings, with Kantana exhibiting a higher yield potential than Okashana-2. Kantana, sown by 14 January, had a yield advantage of up to 36% over Okashana-2, but its yield gradually reduced with delays in sowing. Okashana-2 exhibited higher yield stability across January sowings, surpassing Kantana’s yields by up to 9.4% following the 14 January sowing. We determined the pearl millet optimal sowing window for the NCR to be from 1–7 and 1–21 January for Kantana and Okashana-2, respectively. These results suggest that co-cultivation of early and late pearl millet varieties and growing early-maturing varieties under delayed seasons could stabilize grain production in northern Namibia and enhance farmers’ climate adaptation. Policymakers for semi-arid agricultural regions could utilize this information to adjust local seed systems and extension strategies. Full article

This paper addresses the riverine flood events that have occurred in Greece over the last 136 years (i.e., during the 1886–2022 period), focusing, amongst others, on the case of urban floods. The flood record of various sites of the country has been collected and analyzed to determine their spatial and temporal distribution. Greece is a country where flood data and records are very scarce. Therefore, as there is not an integrated catalog of Greek floods spanning from the 19th century to recently, this is the first attempt to create an integrated catalog for Greece. The sources used include published papers, local and regional newspapers and public bodies (mainly the Ministry of Environment and Energy and the official websites of Greek municipalities). Additionally, the main factors responsible for their occurrence have been issued, regarding the country’s climatic, geological and geomorphological setting, as well as human interventions. In addition, the atmospheric circulation driving factors of floods are assessed via an unsupervised neural network approach (i.e., Self-Organizing Maps). Based on the results of this research, an online GIS-based database has been created, depicting the areas that have been struck by riverine floods in Greece. By clicking a flood event in the online database, one can view several characteristics, depending on data availability, such as duration and height of the rainfall that caused them and number of fatalities. Long-term trends of mean and extremes seasonal precipitation also linked to the spatial distribution of floods. Our analysis shows that urban floods are a very large portion of the overall flood record, and they mainly occur in the two large urban centers, Athens and Thessaloniki, as well as near large rivers such as Pineios. Autumn months and mainly November are the periods with higher flood hazards, based on past records and cyclonic atmospheric circulation constitutes the principal driving factor. Our results indicate that a flood catalog at national level is of fundamental importance, as it can provide valuable statistical insights regarding seasonality, spatial distribution of floods, etc., while it can also be used by stakeholders and researchers for flood management and flood risk analysis and modelling. Full article

This study explores spatial and temporal changes in the rainfall climatology of Puerto Rico in order to identify areas where annual, seasonal or daily precipitation is increasing, decreasing, or remaining normal. Total annual, seasonal, and daily rainfall were retrieved from 23 historical rain gauges with consistent data for the 1956–2021 period. Mann–Kendall trend tests were done on the annual and seasonal rainfall series, and percentage change differences between two different climatologies (1956–1987 and 1988–2021) were calculated. Most of the stations did not exhibit statistically significant annual or seasonal trends in average rainfall. However, of the sites that did experience changes, most of them had statistically significant decreasing trends in mean precipitation. The annual, dry, and early wet season had more sites with negative trends when compared with positive trends, especially in the northwestern and southeastern region of the island. The late wet season was the only period with more sites showing statistically significant trends when compared with negative trends, specifically in the northern region of the island. Results for daily events show that extreme rainfall occurrences have generally decreased, especially in the western region of the island. When the 1955–1987 and 1988–2022 climatologies are compared, the results for annual average rainfall show two main regions with mean precipitation reductions, and those are the northwestern and southeastern areas of the island. The dry season was the only period with more areas exhibiting percentage increases in mean rainfall when the two climatologies were analyzed. The early and late wet season months exhibited similar patterns, with more areas on the island showing negative percentage decreases in average seasonal precipitation. The best predictor for the decreasing annual and seasonal trend in the northwest was a higher sea level pressure, and the variable that best explained the increasing trend in the northeast was total precipitable water. Full article

Homogenization of climatic time series aims to remove non-climatic biases which come from the technical changes in climate observations. The method comparison tests of the Spanish MULTITEST project (2015–2017) showed that ACMANT was likely the most accurate homogenization method available at that time, although the tested ACMANTv4 version gave suboptimal results when the test data included synchronous breaks for several time series. The technique of combined time series comparison was introduced to ACMANTv5 to better treat this specific problem. Recently performed tests confirm that ACMANTv5 adequately treats synchronous inhomogeneities, but the accuracy has slightly worsened in some other cases. The results for a known daily temperature test dataset for four U.S. regions show that the residual errors after homogenization may be larger with ACMANTv5 than with ACMANTv4. Further tests were performed to learn more about the efficiencies of ACMANTv4 and ACMANTv5 and to find solutions for the problems occurring with the new version. Planned changes in ACMANTv5 are presented in the paper along with related test results. The overall results indicate that the combined time series comparison can be kept in ACMANT, but smaller networks should be generated in the automatic networking process of the method. To improve further the homogenization methods and to obtain more reliable and more solid knowledge about their accuracies, more synthetic test datasets mimicking the true spatio-temporal structures of real climatic data are needed. Full article

Tornadoes present an undisputable danger to communities throughout the United States. Despite this known risk, there is a limited understanding of how tornado frequency varies spatially at the mesoscale across county or city area domains. Furthermore, while previous studies have examined the relationships between various climate indices and continental or regional tornado frequency, little research has examined their influence at a smaller scale. This study examines the relationships between various climate indices and regional tornado frequency alongside the same relationships at the mesoscale in seven cities with anomalous tornado patterns. The results of a correlation analysis and generalized linear modeling show common trends between the regions and cities. The strength of the relationships varied by region, but, overall, the ENSO had the greatest influence on tornado frequency, followed in order by the PNA, AO, NAO, MJO, and PDO. However, future research is critical for understanding how the effects of climate indices on tornado frequency vary at different spatial scales, or whether other factors are responsible for the atypical tornado rates in certain cities. Full article

The Climate Risk and Vulnerability Assessment (CRVA) is a systematic process used to identify gaps in regional climate adaptation strategies. The CRVA method assesses regional vulnerability, adaptation capacity, exposure, and sensitivity to climate change to support improved adaptation policies. This CRVA study assesses Georgia’s climate exposure, geographic sensitivity, and socio-economic sensitivity by focusing on the impacts of climate change on regional hydrology. The projected change in climate extreme indices, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), is assessed against the 1961–1990 baseline under future Representative Concentration Pathway (RCP) scenarios. These indices encompass various climate factors such as the maximum daily temperature, warmth duration, total precipitation, heavy and extreme precipitation, maximum 5-day precipitation, and consecutive drought duration. This evaluation helps us understand the potential climate exposure impacts on Georgia. The climate-induced geographic sensitivity is examined based on water stress, drought risk, and changes in soil productivity using the Normalized Difference Vegetation Index (NDVI). The climate-induced socio-economic sensitivity is determined using the Gross Domestic Product per capita (GDP), Human Development Index, Education Index, and population density. The highest vulnerability to climate change was found in the Kakheti and Kvemo Kartli regions, with the vulnerability index values ranging from 6 to 15, followed by Mtskheta-Mtianeti, Samtskhe–Javakheti, and Shida Kartli with vulnerability index values ranging from 2 to 8. The location of these regions upstream of the Alazani-Iori, Khrami-Debeda, and Mktvari river basins indicates that the country’s water resources are vulnerable to climate change impacts in the future under the RCP 4.5 and 8.5 scenarios. Full article

Resistance to clean energy policy in the United States stems partly from public hesitancy and skepticism toward anthropogenic climate change. This article examines self-declared climate change skeptics’ views of clean energy policy along a continuum of skeptical thought, spanning from epistemic denial to attribution doubt. To perform this, we use data from an online survey administered in the US Pacific Northwest and a series of pilot interviews conducted with skeptics in the same region. Results reveal that skeptics’ support for clean energy policy is consistently linked with their environmental concern across the skepticism continuum. Conspiracy ideation and distrust in science lead to a reduction in support. However, the positive effect of environmental concern trumps the effects of these beliefs. Important and hopeful implications of these findings for climate change communication and policy are discussed. Full article

Understanding the factors that influence the diversity and distribution of butterfly species is crucial for prioritizing conservation. The Eastern Ghats of India is an ideal site for such a study, where butterfly diversity studies have yet to receive much attention. This study emphasized the butterfly assemblages of three prominent habitats in the region: open forests, riparian forests, and dense forests. We hypothesized that riparian forests would be the most preferred habitat for the butterflies, as they provide suitable microclimatic conditions for butterflies. The study collected samples for 35 grids of 2 × 2 km² for each habitat during the dry months (December–June). We considered the relative humidity, temperature, light intensity, elevation, and canopy cover to assess their influences on butterfly richness and abundance. We also considered the impact of disturbances on their distribution. We used structural equation modeling and canonical correspondence analysis to quantify the correlation and causation between the butterflies and their environment. The study recorded 1614 individual butterflies of 79 species from 57 genera and 6 families. During the study, we found that temperature was the most significant factor influencing butterfly richness. Relative humidity was also important and had a positive impact on butterfly richness. Riparian forests, where daytime temperatures are relatively low, were the most preferred microhabitat for butterflies. Open forests had greater species diversity, indicating the critical significance of an open canopy for butterflies. Though riparian forests need greater attention concerning butterfly distribution, maintaining open and dense forests are crucial for preserving butterfly diversity. Full article