Annual Maximum Temperature Research Articles

Spatiotemporal dynamics and influencing factors of native and invasive saltmarshes in a rapidly silting bay during 1985–2023

Globally, native saltmarshes are declining, while invasive saltmarshes are expanding rapidly. However, the underlying processes and driving mechanisms behind these trends remain poorly understood, particularly in rapidly silting coastal bays. Here, we investigated the spatiotemporal dynamics and influencing factors of native saltmarshes (Scirpus mariqueter and Phragmites australis) and invasive Spartina alterniflora in Yueqing Bay, eastern China, by interpreting Landsat series images during 1985-2023. Results showed that native saltmarshes significantly decreased from 632.24 ha to complete disappearance, while S. alterniflora expanded from zero to 2872.90 ha in Yueqing Bay during 1985-2023. Specifically, S. mariqueter experienced a notable decline from 1985 to 1995, subsequent growth between 2000 and 2005, and another reduction from 2005 to 2010. P. australis expanded from 2005 to 2010 but shrank from 2010 to 2015 as S. alterniflora encroached upon its habitats. By contrast, S. alterniflora consistently expanded annually, except when it was eradicated by human interference. Both natural factors and human activities influenced native and invasive saltmarshes; for instance, mudflat reclamation facilitated saltmarsh expansion by creating suitable habitats during a certain period, particularly for S. alterniflora. From 1984 to 2018, the coastline extended seaward, causing sedimentation and landward transformation, which contributed to the expansion of S. alterniflora. However, the 118.05 ha mangrove forests negatively impacted S. alterniflora, as planting mangroves often involves the removal of existing S. alterniflora. Additionally, maximum tidal range and mean annual temperature positively affected saltmarshes. Our study highlighted the influence of natural factors and human activities on the spatiotemporal dynamics of both native and invasive saltmarshes in rapidly silting bays, underscoring the urgent need for conservation, restoration, and management of native saltmarshes.

Climate change projections in temperature and precipitation using cmip6 in Central Mexico

Knowing the spatiotemporal variability of temperature and precipitation, as well as their future projections, is essential to assess environmental risks and plan long-term mitigation and adaptation. In this study, the General Circulation Models (GCMs) HadGEM3-GC31-LL, MRI-ESM2-0 and ACCESS-ESM1-5 of the Coupled Model Intercomparison Project (CMIP6) have been used, under two Shared Socioeconomic Pathways (SPP2-4.5 and SSP5-8.5), to project the minimum and maximum air temperature and the mean annual precipitation in Atlacomulco Rural Development District (ARDD). 30 meteorological stations were used to perform regionalized climate change projections by downscaling using LARS-WG 7. The expected changes were evaluated for three time horizons: near horizon (2021–2040), mid horizon (2041–2060) and far horizon (2061–2080); compared to the historical period (1985–2017). Based on the results, the annual minimum temperature towards the far horizon is projected to increase by 2.0 ºC with SSP2-4.5, and 3.1 ºC with SSP5-8.5; while the annual maximum temperature towards the far horizon is projected to increase between 2.5 ºC with SSP2-4.5 and 3.8 ºC using SSP5-8.5. Precipitation shows an increase for SSP2-4.5 in the near and middle horizons with 15.7 and 42.5 mm.year−1, respectively, while the largest decrease is projected towards the middle horizon of SSP5-8.5 with − 26.3 mm.year−1. The findings of this study provide detailed information on climate change projections in the ARDD and can serve as a useful guide for the management of different ecosystems.

Impact of Climatic Factors on the Temporal Trend of Malaria in India from 1961 to 2021.

Malaria remains a significant public health problem in India. Although temperature influences Anopheline mosquito feeding intervals, population density, and longevity, the reproductive potential of the Plasmodium parasite and rainfall influence the availability of larval habitats, and evidence to correlate the impact of climatic factors on the incidence of malaria is sparse. Understanding the influence of climatic factors on malaria transmission will help us predict the future spread and intensification of the disease. The present study aimed to determine the impact of temporal trend of climatic factors such as annual average maximum, minimum, mean temperature, and rainfall on the annual incidence of malaria cases in India for a period of 61 years from 1961 to 2021 and relative humidity for a period of 41 years from 1981 to 2021. Two different analyses were performed. In the first analysis, the annual incidence of malaria and meteorological parameters such as annual maximum, minimum, and mean temperature, annual rainfall, and relative humidity were plotted separately in the graph to see if the temporal trend of climatic factors had any coherence or influence over the annual incidence of malaria cases. In the second analysis, a scatter plot was used to determine the relationship of the incidence of malaria in response to associated climatic factors. The incidence of malaria per million population was also calculated. In the first analysis, the annual malaria cases showed a negative correlation of varying degrees with relative humidity, minimum, maximum, and mean temperature, except rainfall, which showed a positive correlation. In the second analysis, the scatter plot showed that the rainfall had a positive correlation with malaria cases, and the rest of the climatic factors, such as temperature and humidity, had negative correlations of varying degrees. Out of the total 61 years studied, in 29 years, malaria cases increased more than 1000 square root counts when the minimum temperature was at 18-19 °C; counts also increased over a period of 33 years when the maximum temperature was 30-31 °C, over 37 years when the mean temperature was 24-25 °C, over 20 years when the rainfall was in the range of 100-120, and over a period of 29 years when the relative humidity was at 55-65%. While the rainfall showed a strong positive correlation with the annual incidence of malaria cases, the temperature and relative humidity showed negative correlations of various degrees. The increasing temperature may push the boundaries of malaria towards higher altitude and northern sub-tropical areas from the southern peninsular region. Although scanty rainfall reduces the transmission, increases in the same would increase the malaria incidence in India.

Climate Change Vulnerability of Livelihoods of People Residing in Kaski District of Nepal

This study assesses the climate change vulnerability of livelihoods across altitudinal gradients in the Kaski district of Nepal. A sample of sixty-five households from four different communities in municipalities (Annapurna rural municipality and Machhapuchchhre rural municipality) was selected through random sampling and surveyed at various elevations. The Principal Component Analysis (PCA) approach and the Composite Index Method (CIM) were employed to evaluate and determine IPCC-VI. To derive Adaptive capacity, Sensitivity, and Exposure, the components such as Social Demographic Profile (SDP), Social Networking (SN), Livelihood Strategies (LS), Health (H), Water (W), Food (F), Natural Disaster and Climate Variability (ND CV) were used. The trend of the temperature and rainfall were analyzed and it was found that the mean annual maximum temperature is increasing at a rate of 0.036°C per year and the annual rainfall is decreasing at 14.532 mm per year. Among the communities, Melache (2210m), in Annapurna Rural Municipality exhibited the highest vulnerability (IPCC-VI: 0.118), whereas Hudu (1490m) showed a lower vulnerability index (0.025). In Machhapuchchhre Rural Municipality, Dhampus upper region (1660m) displayed moderate vulnerability (IPCC-VI: 0.043), with the Dhampus lower region (1360m) showing the least vulnerability (-0.011). So, all the communities demonstrated intermediate vulnerability levels indicating a need for tailored adaptation strategies across the elevation levels. Effective adaptation efforts could improve community resilience by addressing local climate challenges, ensuring sustainable livelihoods, and reducing future vulnerability risks.

Effects of Climate Change on the Fish Community, and Rhynchocypris kumgangensis (Cypriniformes: Cyprinidae) Distribution in Deogyusan National Park

Rhynchocypris kumgangensis, endemic to Korea, is limited to the upper Hangang River and Gucheondongcheon Stream. As a key and climate-sensitive biological indicator species in the Deogyusan National Park, it has a southern range limit in the Gucheondong Valley. Due to climate change, notable shifts in the activity, distribution, and population of R. kumgangensis on the Gucheondongcheon Stream are expected. This study examined trends between the 2020 field survey and previous surveys (2014–2018) for fish faunal changes at 13 sites in the Deogyusan National Park and for the population changes of R. kumgangensis at four sites in the Gucheondongcheon Stream. At 13 sites, we identified 996 individuals of 17 fish species in seven families, including 2 endangered (Pseudopungtungia nigra, Hemibarbus mylodon) and 11 Korea-endemic species. The Fish Assessment Index (FAI) of the 13 sites in the Deogyusan National Park was analyzed and found to be of A-grade in both the 2020 and past surveys, with high scores in all M1–M8 categories. Both the results of CCA and field surveys between the entire fish community and pH, DO, and water temperature revealed that the population of R. kumgangensis had a narrower distribution range and was more sensitive to water temperature than the same cold-water fish, R. oxycephalus. Climate change has been identified as causing the annual maximum temperature (°C) in the Deogyusan National Park to increase year on year and the R. kumgangensis population to decline, suggesting that the time for conservation efforts is “now”.

It Is Normal: The Probability Distribution of Temperature Extremes

The probability of heat extremes is often estimated using the non-stationary generalized extreme value distribution (GEVD) applied to time series of annual maximum temperature. Here, this practice was assessed using a global sample of temperature time series, from reanalysis (both at the grid point and the region scale) as well as station observations. This assessment used forecast negative log-likelihood as the main performance measure, which is particularly sensitive to the most extreme heat waves. It was found that the computationally simpler normal distribution outperforms the GEVD in providing probabilistic year-ahead forecasts of temperature extremes. Given these findings, it is suggested to consider alternatives to the GEVD for assessing the risk of extreme heat.

The Spatiotemporal Characteristics and Driving Factors of Soil Degradation in the Black Soil Region of Northeast China

The Northeastern Black Soil Region in China is recognized as one of the three major black soil regions globally and is often regarded as a cornerstone of national food security. However, prolonged agricultural practices have led to increasingly severe soil degradation, and the mechanisms and driving factors behind the degradation of soil quality remain unclear. Therefore, this study examines the historical and current characteristics of soil quality, focusing on major influencing factors, such as the 70-year history of reclamation and climate change. By accessing different databases, reviewing the relevant literature, and performing Pearson correlation and redundancy analyses (RDA), this study investigated the variation patterns of significant soil quality indicators and their driving factors in the 0–20 cm soil layer along the latitudinal direction (Nenjiang, Beian, Hailun, and Harbin) in the typical black soil region of Northeast China. The main conclusions are as follows: the soil organic matter (SOM) content experienced a rapid decline in the 30 years preceding cultivation (1950~1980), with the greatest decline rate in the Beian area (about 1.10 g/kg per year). The SOM in the Beian, Hailun, and Harbin areas decreased from north to south, changing at rates of 9.40–21.67 g/kg/degree and 0.15–0.34 g/kg/m with latitude and elevation, respectively. Elevation impacts the annual rate of change in soil quality indicators through its influence on the annual mean maximum temperature (AMXT) and annual atmospheric pressure (AP). AMXT and AP exhibit a linear relationship with elevation, based on which regression models were established. The key factors influencing soil quality indicators in the black soil region include cultivation years (Y), annual mean maximum and minimum temperatures (AMXT and AMNT), annual relative humidity (ARH), and AP. An increase in chemical fertilizer application is among the critical factors affecting soil pH. Additionally, the extensive use of agricultural machinery can reduce soil porosity and cause water and salt accumulation, ultimately leading to a decline in soil pH. This study offers theoretical support for mitigating soil degradation in Northeast China’s black soil region, thereby contributing to national food security and promoting sustainable development.

The Analysis and the Impact of Surface Temperature Anomalies on the Health of Residents in the River Niger Basin Development Authority Area, West Africa.

This study investigates the impact of surface temperature anomalies on the health of residents within the River Niger Basin Development Authority (RIBDA) enclave, which covers Nigeria, Niger, and Mali in West Africa, with a focus on the regional implications for public health. Historical climate data from 1985 to 2014, sourced from the Climatic Research Unit Time-Series, Version 3.22 (CRU TS 3.22), was analyzed to comprehend past climate patterns and establish a baseline for future comparisons. Predictions for future climate conditions (2015-2044) were derived by adjusting the CRU data using temperature projections from the Community Climate System Model 4 under the Representative Concentration Pathway 8.5 scenario. To assess the potential impacts of these climate changes, particularly during the boreal summer season of July-August-September (JAS), the study utilized the Hydrology, Entomology, and Malaria Transmission Simulator (HYDREMATS). Findings indicate that surface temperature can intricately influence disease transmission, with varied effects on parameters such as Ro, EIR, prevalence, and immunity index. Observations revealed fluctuations in temperature anomalies over the years, with negative anomalies in 1991-1995 and positive anomalies in subsequent years. Although precise predictions for 2016-2044 are challenging based solely on data trends from 1985 to 2015, continued temperature rises could potentially lead to increased disease prevalence and decreased immunity index. Moreover, the analysis identified a notable temporal increase in mean annual temperature and mean annual maximum temperature from 1999 to 2020, suggesting a faster warming trend in maximum temperatures compared to minimum temperatures. This increase in temperature variability may alter the onset and cessation dates of the rainy season, affecting water availability, accessibility, and consumption, consequently fostering conditions conducive to health-related diseases. By incorporating predicted long-term temperature changes due to greenhouse gas emissions while maintaining current inter-annual climate patterns, this approach allows researchers to anticipate potential future health implications in the studied regions.

Climatic Trends and Local Perception in Nechasalyan Rural Municipality: A Climate Change Scenario

Climatic policy responses are influenced by how communities and individuals perceive and understand climate variabilities and changes. Integrating community perceptions with observed climate data can provide valuable information to support policies to reduce climate-related risks and enhance climate change adaptation. This study examines climate change in the Nechasalyan Rural Municipality of Solukhumbu district, Nepal, through an integrated analysis of meteorological data and local people's perceptions. Temperature and rainfall data for 31 years i.e. 1991-2021 were collected and analyzed from nearest Meteorological station (Okhaldhunga Station). Local peoples’ perceptions were gathered from the household survey (n=70) along with key informant interview (n= 10) and focus group discussion (n= 5). The analysis revealed that the average maximum, winter and summer temperature trends seemed to be increasing where average minimum trend was decreasing of which only average winter temperature was significant (p<0.05). Despite insignificance in the increases in average annual maximum and summer temperatures, they pose potential challenges in the long run. Similarly, the average annual rainfall as well as seasonal rainfall trends seemed to be decreasing, and only average July rainfall trend was statistically significant (p<0.05). The results indicate that while local perceptions about the changes in the temperature were consistent, there was disconnection between these perceptions and observed rainfall trends. The consistency between local perceptions and rising temperature trends suggests that people remember temperature changes more vividly than rainfall patterns, warranting future research to investigate the causes of disparities between local perceptions and observed climate trends. Additionally, exploring effective communication strategies to bridge the gap between scientific findings and local understanding could enhance community climate resilience.

Variability of Temperature Extreme Observes in Kalimantan

This study aims to analyze the trend of extreme temperatures in Kalimantan over the past few decades. The data used are daily temperatures from meteorological stations in West Kalimantan, Central Kalimantan, and South Kalimantan, with an observation period of January 1985 to December 2022. The research methodology involves four main stages: data collection, extreme temperature index calculation, trend detection, and correlation analysis with ENSO and IOD. The results showed an increasing trend in extreme temperatures (warming). The increase in mean annual maximum temperature (TXmean) ranged from 0.03°C to 2°C per century, while the mean annual minimum temperature increased from 0.2°C to 0.5°C per century. Monthly maximum value of daily max temperature (TXx) the increasing trend ranged from 0.19°C to 1.7°C, monthly maximum value of daily min temperature (TNx) increased from 0.1°C to 0.5°C. The monthly mean difference between daily max and min temperature (DTR) also shows an increase of 0.5°C to 1.7°C. This trend indicates that daytime (TXmean, TXx) and nighttime (TNmean, TNx) conditions in Kalimantan, especially in West, Central, and South Kalimantan, are getting hotter, with the daytime experiencing a more significant increase in temperature. The correlation between the extreme temperature index and ENSO and IOD is negative and positive, indicating that ENSO and IOD do not fully influence the increase in extreme temperatures. These findings have important implications for disaster mitigation planning and adaptation to climate change in the Kalimantan region.

Estimation of Future Climate Change in Low Folded Zone, Iraq with the LARS-WG and Five GMS Models under CMIP5 Scenarios

This study investigates the trends of climate change in the Low Folded Zone region of Iraq and provides future projections for daily maximum and minimum temperatures, as well as precipitation. Using the LARS-WG model and five General Circulation Models (GCMs) under three Representative Concentration Pathways (RCP) scenarios, the research aims to provide valuable insights into the anticipated changes in climate variables. The calibration and validation of the model demonstrate its capability to simulate future climatic data, with statistical indices indicating a strong correlation between observed and generated data. The projected future temperatures showed a consistent increase across all selected stations, with average annual maximum temperatures expected to rise by 1.06 to 5.48°C by the end of the twenty-first century. The highest increase in temperatures was predicted under the high-emission scenario RCP8.5. The results also indicated spatial and temporal variations in precipitation patterns, with the annual percentage increase in precipitation ranging from 7.07% to 10.75% for RCP 2.6, 0% to 2.2% for RCP4.5, and 3.7% to 6.8% for RCP8.5. The findings reveal a projected increase in annual temperatures and variable precipitation patterns, highlighting the urgency of proactive measures to address the challenges posed by climate change in the region. The results of this study are crucial for informing decision-makers and planners in developing strategies for climate change adaptation and resource management, particularly in water resource management and agricultural planning.

Classification Importance of Seed Morphology and Insights on Large-Scale Climate-Driven Strophiole Size Changes in the Iberian Endemic Chasmophytic Genus Petrocoptis (Caryophyllaceae).

Recruitment poses significant challenges for narrow endemic plant species inhabiting extreme environments like vertical cliffs. Investigating seed traits in these plants is crucial for understanding the adaptive properties of chasmophytes. Focusing on the Iberian endemic genus Petrocoptis A. Braun ex Endl., a strophiole-bearing Caryophyllaceae, this study explored the relationships between seed traits and climatic variables, aiming to shed light on the strophiole's biological role and assess its classificatory power. We analysed 2773 seeds (557 individuals) from 84 populations spanning the genus' entire distribution range. Employing cluster and machine learning algorithms, we delineated well-defined morphogroups based on seed traits and evaluated their recognizability. Linear mixed-effects models were utilized to investigate the relationship between climate predictors and strophiole area, seed area and the ratio between both. The combination of seed morphometric traits allows the division of the genus into three well-defined morphogroups. The subsequent validation of the algorithm allowed 87% of the seeds to be correctly classified. Part of the intra- and interpopulation variability found in strophiole raw and relative size could be explained by average annual rainfall and average annual maximum temperature. Strophiole size in Petrocoptis could have been potentially driven by adaptation to local climates through the investment of more resources in the production of bigger strophioles to increase the hydration ability of the seed in dry and warm climates. This reinforces the idea of the strophiole being involved in seed water uptake and germination regulation in Petrocoptis. Similar relationships have not been previously reported for strophioles or other analogous structures in Angiosperms.

The Loss and Recovery Potential of Net Ecosystem Productivity in Mining Areas: A Global Assessment Based on Data for 2000–2020

Climate change control requires more land to increase ecosystem carbon sequestration. With the high-intensity development of mineral resources in past decades, massive mining areas have been generated worldwide. However, few studies have evaluated the carbon sequestration of these mining areas. In this study, we analyzed the net ecosystem productivity (NEP) changes and calculated the NEP losses in global terrestrial mining areas. We adopted the random forest model to evaluate the NEP recovery potential and its driving factors. The key findings are that (1) the NEP of global mining areas exhibited a relatively obvious decreasing trend from 2000 to 2020, with an overall reduction of 29.1% and a maximum decline of 35.7%. By 2020, the NEP loss in mining areas was 11.9 g C m−2 year−1, and the total loss reached 576.9 Gg C year−1. (2) Global mining areas demonstrate significant NEP recovery potential, with an average of 12.0 g C m−2 year−1. Notably, Oceania and South America have significantly higher recovery potentials, with average mine site NEP recovery potentials of 15.9 g C m−2 year−1 and 16.1 g C m−2 year−1. In contrast, European mines have considerably lower recovery potentials of less than 10 g C m−2 year−1. In Asia, North America and Africa, the NEP recovery potential varies widely from mine to mine, but generally meets the global average. (3) The annual precipitation, population density, organic soil carbon, and average slope are important drivers of NEP recovery in mining areas and exhibit positive correlations with the NEP recovery potential. In contrast, mine area and minimum temperature exhibit a negative correlation. The dependency curves of the three drivers, standardized precipitation evapotranspiration index, average elevation, and annual maximum temperature, are U-shaped, indicating that the recovery potential was poorer in the tropical and frigid zones with less precipitation. The results of this study provide a scientific basis for ecological restoration and sustainable development of mining areas worldwide.

Climate and Altitude Drive Spatial and Temporal Changes in Forests on the Eastern Tibetan Plateau—Evidence from the Shaluli Mountain

Forests are widely distributed in terrestrial ecosystems, covering about one-third of the global land area. They play a key role in sequestering carbon, releasing oxygen, mitigating climate change, and maintaining ecosystem balance. The ecology of the Tibetan Plateau is very fragile, but the impact of environmental change on regional forest ecosystems is not yet clear. Located in the Eastern Tibetan Plateau, the Shaluli Mountain has the richest biodiversity and the widest distribution of forests on the Tibetan Plateau. Assessing the dynamics of forest change is the basis for correctly formulating forest management measures, and is important for regional biodiversity conservation. However, traditional field surveys have the shortcomings of high cost, being time-consuming, and having poor regional coverage in forest dynamics monitoring. Remote sensing methods can make up for these shortcomings. Therefore, in this study, satellite remote sensing images were used to extract forest information from 2000 to 2020 in Shaluli Mountain, and the main drivers of forest change were analyzed with full consideration of the Spatially Stratified Heterogeneity (SSH) of environmental factors. The results found that the forest area increased from 23,144.20 km2 in 2000 to 28,429.53 km2 in 2020, and the average Percentage of Forest Cover (PFC) increased from 19.76% to 21.67%, with significant improvement in forest growth. The annual minimum temperature (TMN), altitude, annual maximum temperature (TMX), and annual precipitation (PRE) were the main driving factors of forest change, with an average driving power (q-value) of 0.4877, 0.2706, 0.2342, and 0.2244, and TMN was the primary limiting factor for forest growth. In addition, the driving power of all environmental factors on forest change increased from 2000 to 2020. The results of this study can provide a basis for the development of forest management strategies, and provide reference materials for regional biodiversity conservation.

Hyperspectral Leaf Reflectance Detects Interactive Genetic and Environmental Effects on Tree Phenotypes, Enabling Large-Scale Monitoring and Restoration Planning Under Climate Change.

Plants respond to rapid environmental change in ways that depend on both their genetic identity and their phenotypic plasticity, impacting their survival as well as associated ecosystems. However, genetic and environmental effects on phenotype are difficult to quantify across large spatial scales and through time. Leaf hyperspectral reflectance offers a potentially robust approach to map these effects from local to landscape levels. Using a handheld field spectrometer, we analyzed leaf-level hyperspectral reflectance of the foundation tree species Populus fremontii in wild populations and in three 6-year-old experimental common gardens spanning a steep climatic gradient. First, we show that genetic variation among populations and among clonal genotypes is detectable with leaf spectra, using both multivariate and univariate approaches. Spectra predicted population identity with 100% accuracy among trees in the wild, 87%-98% accuracy within a common garden, and 86% accuracy across different environments. Multiple spectral indices of plant health had significant heritability, with genotype accounting for 10%-23% of spectral variation within populations and 14%-48% of the variation across all populations. Second, we found gene by environment interactions leading to population-specific shifts in the spectral phenotype across common garden environments. Spectral indices indicate that genetically divergent populations made unique adjustments to their chlorophyll and water content in response to the same environmental stresses, so that detecting genetic identity is critical to predicting tree response to change. Third, spectral indicators of greenness and photosynthetic efficiency decreased when populations were transferred to growing environments with higher mean annual maximum temperatures relative to home conditions. This result suggests altered physiological strategies further from the conditions to which plants are locally adapted. Transfers to cooler environments had fewer negative effects, demonstrating that plant spectra show directionality in plant performance adjustments. Thus, leaf reflectance data can detect both local adaptation and plastic shifts in plant physiology, informing strategic restoration and conservation decisions by enabling high resolution tracking of genetic and phenotypic changes in response to climate change.

CLIMATE CHANGE TRENDS IN THE RED RIVER DELTA

The Red River Delta (RRD) is one of the regions most significantly impacted by climate change (CC) in Vietnam. This study utilizes correlation assessment methods and regression equations to evaluate the trends of certain meteorological factors and extreme weather events during the period 1961 - 2020 in the RRD. Overall, climate factors across the region exhibit quite clear trends of change. The highest trends in annual average temperature and maximum annual average temperature are observed in the northwestern part of the RRD, especially in major cities such as Ha Noi (the increase in mean annual temperature ranges from 0.0317 - 0.0336 ºC/year). The lowest trends in these temperatures are found in coastal, island, and mountainous areas (the increase in mean annual temperature ranges from 0.0133 - 0.0224 ºC/year). The annual rainfall reports a decreasing trend at 17 out of 23 meteorological stations in the RRD, varying from -11 to 9 mm/year. Extreme weather phenomena report little significant change, with maximum daily rainfall records a decreasing trend, varying from -3.119 to 1.395 mm/year; the number of days with rainfall exceeding 50 mm also reports a decrease, varying from -0.058 to 0.017 days/year. The results of this study will serve as a basis for developing action plans to respond to CC in the RRD.

Performance Evaluation of CMIP6 Climate Model Projections for Precipitation and Temperature in the Upper Blue Nile Basin, Ethiopia

The projection and identification of historical and future changes in climatic systems is crucial. This study aims to assess the performance of CMIP6 climate models and projections of precipitation and temperature variables over the Upper Blue Nile Basin (UBNB), Northwestern Ethiopia. The bias in the CMIP6 model data was adjusted using data from meteorological stations. Additionally, this study uses daily CMIP6 precipitation and temperature data under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios for the near (2015–2044), mid (2045–2074), and far (2075–2100) periods. Power transformation and distribution mapping bias correction techniques were used to adjust biases in precipitation and temperature data from seven CMIP6 models. To validate the model data against observed data, statistical evaluation techniques were employed. Mann–Kendall (MK) and Sen’s slope estimator were also performed to identify trends and magnitudes of variations in rainfall and temperature, respectively. The performance evaluation revealed that the INM-CM5-0 and INM-CM4-8 models performed best for precipitation and temperature, respectively. The precipitation projections in all agro-climatic zones under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios show a significant (p < 0.01) positive trend. The mean annual maximum temperature over UBNB is estimated to increase by 1.8 °C, 2.1 °C, and 2.8 °C under SSP1-2.6, SSP2-4.5, and SSP5-8.5 between 2015 and 2100, respectively. Similarly, the mean annually minimum temperature is estimated to increase by 1.5 °C, 2.1 °C, and 3.1 °C under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. These significant changes in climate variables are anticipated to alter the incidence and severity of extremes. Hence, communities should adopt various adaptation practices to mitigate the effects of rising temperatures.

The impact of extreme weather events of projected Canadian regional climate model data on flexible pavement

This paper presents findings about the influence of projected data from the Canadian regional climate model on the performance of flexible pavement, building upon the results from previous work where the data were generated and published, in which a general trend of decreasing the design life was observed. Projected temperature is the most important extreme climate impact on flexible roads. Adopting a conservative approach demonstrated that two extreme events of maximum mean annual air temperature and maximum summer average air temperature resulted in significant reduction of 25 years road design life. The observed trend indicates a severity range of 7%–15% in terms of design service life loss when considering events every year compared to every 5 years. The findings revealed a reduction in pavement design life by 34%, 50%, 73%, and 90% for historical, short, intermediate, and long-term life cycles in the city of Windsor, respectively.

Establishment of characteristic fingerprint of volatile components in Batocera horsfieldi (Coleoptera: Cerambycidae) host plants and correlation analysis with climatic factors.

Batocera horsfieldi is the primary stemboring pest of timber forests and economic forests in China, belonging to the Coleoptera Cerambycidae. In this study, gas chromatography-mass spectrometry was used to analyze the volatile components in the supplementary feeding hosts and oviposition hosts of B. horsfieldi, and characteristic fingerprints were constructed. A total of 168 compounds were detected, primarily consisting of terpenes, hydrocarbons, and aldehydes, with 75, 23, and 14 compounds, respectively. Hierarchical cluster analysis and principal component analysis yielded consistent results. The similarity evaluation results showed that the similarity range between healthy poplar tree bark and healthy poplar leaves was the highest, reaching 0.953-0.98, and 10 common peaks were identified. The analysis of the correlation with climatic factors shows that most compounds are positively correlated with mean annual humidity, mean annual temperature, mean annual minimum temperature, and mean annual maximum temperature. Only caryophyllene and alpha-guaiene are negatively correlated with temperature-related climatic factors. Pathway analysis also reveals differences in the direct effects of different compounds. These analytical results provide a theoretical basis for further studying the selection mechanism of B. horsfieldi on hosts and offer theoretical guidance for identifying plant-derived attractants with biological activity.

Analyzing the Spatiotemporal Changes in Climatic Extremes in Cold and Mountainous Environment: Insights from the Himalayan Mountains of Pakistan

This study assessed the past changes in extreme precipitation and temperature events across the Himalayan Mountains of Pakistan. This cold and mountainous environmental region has witnessed a significant increase in climate-related disasters over the past few decades. Spatiotemporal changes in extreme temperature and precipitation events were analyzed using 24 indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this study, in situ data of 16 national meteorological stations were obtained from the Pakistan Meteorological Department (PMD) for the past three decades (1991–2020). The significance of the trends was assessed using the modified Mann–Kendall (MMK) test, and the Theil–Sen (TS) slope estimator was used to estimate the slope of the trend. The results showed that there has been a consistent decline in the total precipitation amount across the Himalayan Mountains of Pakistan. The trend exhibited a decrease in the annual average precipitation at a rate of −6.56 mm/year. Simultaneously, there was an increasing trend in the annual average minimum and maximum temperatures at rates of 0.02 °C/year and 0.07 °C/year, respectively. The frequencies of consecutive wet days (CWDs) and maximum 5-day precipitation (RX5day) have decreased significantly, with decreasing rates of −0.40 days/year and −1.18 mm/year, respectively. The amount of precipitation during very wet days (R95p) and extremely wet days was decreased by −19.20 and −13.60 mm/decade, respectively. The warm spell duration (WSDI) and the frequency of warm days (TX90p) across the Himalayan Range both increased by 1.5 and 1.4 days/decade. The number of cold days (TX10p) and cold nights (TN10p) decreased by 2.9 and 3.4 days/decade. The average temperature of the hottest nights (TXn) and the diurnal temperature range (DTR) were increased by 0.10 and 0.30 °C/decade. The results indicated an increasing tendency of dry and warm weather in the Himalayan region of Pakistan, which could have adverse consequences for water resources, agriculture, and disaster management in the country. Therefore, it is essential to prioritize the implementation of localized adaptation techniques in order to enhance sustainable climate resilience and effectively address the emerging climate challenges faced by these mountainous regions.