Impact Of Climate Variability Research Articles

Hydro-Climatic Trends in Central Italy: A Case Study from the Aterno-Pescara River Watershed

Climate change is reshaping water systems and trends in hydro-climatic variables, such as temperature, precipitation, and river runoff, providing critical insights into the hydrological shifts influenced by climate change. However, the impact of climate variability on these variables varies by geographic location, making it necessary to study hydro-climatic variations in the Mediterranean’s changing climate to determine its impacts. This study analyzed the hydro-climatic trends in the Aterno-Pescara River watershed in central Italy from 1936 to 2013. We employed linear regression, Mann–Kendall, Sen’s slope, and Spearman correlation tests to estimate annual and seasonal trends. The results showed a significant warming trend on annual (0.037 °C/year) and seasonal time scales. Precipitation trends exhibited significant reductions annually, specifically during the autumn season, with a decrease of −0.68 mm/year; while showing a decline, other seasons were statistically insignificant. River runoff revealed drying trends annually and seasonally, decreasing by −0.29 m3 s−1/year over the study period. Furthermore, linear regression and Spearman correlation coefficients suggested a significant relationship between hydro-climatic variables with varying strengths (at 95% and 99% confidence levels) annually and seasonally. This decrease in precipitation and river runoff trends with the continuous rate points towards potential meteorological and hydrological droughts occurring in the future in this watershed. This study’s findings provide scientific grounds that could help develop sustainable strategies in the watershed.

Smallholder Farmers' Perception on Impact of Climatic Change and Variability on Coffee Production and its adaptation Practices in Mattu District, South West Ethiopia

Smallholder Farmers' Perception on Impact of Climatic Change and Variability on Coffee Production and its adaptation Practices in Mattu District, South West Ethiopia

Impact of climate variability on rice yield in South Korea

Impact of climate variability on rice yield in South Korea

Teleconnection Impacts of Climatic Variability on Tuna and Billfish Fisheries of the South Atlantic and Indian Ocean: A Study Towards Sustainable Fisheries Management

Teleconnection Impacts of Climatic Variability on Tuna and Billfish Fisheries of the South Atlantic and Indian Ocean: A Study Towards Sustainable Fisheries Management

Impacts of climate variability on the spatio-temporal dynamics of plant formations in the forest-savannah transition zone: the case of the Lamto Scientific Reserve, Central Côte d’Ivoire

Understanding climatic variability’s effects on land and biodiversity is vital for guiding sustainability, conservation, and climate impact predictions in fragile ecosystems like Côte d’Ivoire’s forest-savanna transition zone. This study aims to analyse the impact of climate variability on the spatio-temporal dynamics of land use in the Lamto Scientific Reserve. To do this, a set of monthly climate data covering the period from 1990 to 2022 was used, including indicators such as rainfall, maximum, minimum and average temperatures, drought and standardised rainfall indices. The study also involved the classification of Landsat images dating from 1990, 2002, 2012 and 2022, enabling changes in land use to be observed. The corresponding areas were correlated with the climatic variables using a Spearman correlation test. The results show a transition from savannah to denser tree cover in the reserve. In addition, an increase in rainfall, varying between 900 and 1687 mm, suggests that Lamto could be classified as a humid region. The analysis highlights the complex interactions between climate change, particularly high temperatures, and land-use dynamics. Gallery and semi-deciduous forests show resilience in the face of rising temperatures, favouring their expansion. On the other hand, pre-forest formations, such as open forests and wooded savannahs, are more affected by these temperatures, which hinders their development. Tree savannahs also show a certain resilience, while shrub savannahs and bare land are often associated with ecological degradation processes in response to high temperatures. Finally, although rainfall plays a role, its influence seems minor, suggesting that other environmental or climatic factors, such as watercourses or microclimate, play a more significant role in land use/land cover dynamics.

Evaluating the impact of climatic factors and variability on rice production over varied seasons in irrigated rice system of peninsular India through Empirical approach

Rice is the principle and staple food crop of peninsular India, and its production is highly sensitive to climatic factors and variability. The climate change may cause considerable negative impact on rice productivity that could jeopardize food security and livelihood of smallholders. The present study investigates how the changes in mean and variability of climatic factors may impact rice yield during various rice seasons throughout the year. Panel data of districts of Cauvery Delta Region (CDR) from 2000-2022 was used for the analysis and fixed-effects regression with Panel-Corrected Standard Errors (PCSE) model was employed for all three seasons viz, Kuruvai, Samba and Navarai. The results of the study showed that temperature and rainfall significantly impacted rice yields directly and demonstrated the existence of nonlinear relationship between climatic factors and yield. It also revealed intricate, season-specific correlations between rice productivity and environmental variables. The time trend used in the study indicated a significant positive increase in yield continuously through adoption of yield improvement technologies such as high yielding, resistant and climate resilient varieties. This study helps researchers and policymakers in devising proper adaptation strategies to ensure food system security in the region when the climate conditions change and helpful for predicting future productivity.

The impact of natural climate variability on the global distribution of Aedes aegypti: a mathematical modelling study.

Aedes aegypti spread pathogens affecting humans, including dengue, Zika, and yellow fever viruses. Anthropogenic climate change is altering the spatial distribution of Ae aegypti and therefore the locations at risk of vector-borne disease. In addition to climate change, natural climate variability, resulting from internal atmospheric processes and interactions between climate system components (eg, atmosphere-land and atmosphere-ocean interactions), determines climate outcomes. However, the role of natural climate variability in modifying the effects of anthropogenic climate change on future environmental suitability for Ae aegypti has not been assessed fully. In this study, we aim to assess uncertainty arising from natural climate variability in projections of Ae aegypti suitability up to the year 2100. In this mathematical modelling study, we developed an ecological model in which Ae aegypti population dynamics depend on climate variables (temperature and rainfall). We used 100 projections of future climate from the Community Earth System Model, a comprehensive climate model that simulates natural climate variability as well as anthropogenic climate change, in combination with our ecological model to generate a range of equally plausible scenarios describing the global distribution of suitable conditions for Ae aegypti up to 2100. Each of these scenarios corresponds to a single climate projection, allowing us to explore the difference in Ae aegypti suitability between the most-suitable and the least-suitable projections. Our key finding was that natural climate variability generates substantial variation in future projections of environmental suitability for Ae aegypti. Even for projections generated under the same Shared Socioeconomic Pathway (SSP) scenario (SSP3-7.0), in 2100 climatic conditions in London might be suitable for Ae aegypti for 0-5 months of the year, depending on natural climate variability. Natural climate variability affects environmental suitability for important disease vectors. Some regions could experience vector-borne disease outbreaks earlier than expected under climate change alone. Engineering and Physical Sciences Research Council and Wellcome Trust.

Assessing Commercial Sugarcane Irrigators’ Intentions to Adapt Water-Use Behaviour in Response to Climate Variability in South Africa

The scarcity of water resources in South Africa remains a considerable challenge for water users. This study evaluated the impact of climate variability on the adaptive water-use behaviour of sugarcane producers by identifying the factors influencing their adaptation decisions. A survey, the Theory of Planned Behaviour (TPB), and structural equation modelling (SEM) were used to achieve this objective. The study involved 54 sugarcane producers from the Impala Irrigation Scheme, selected through random sampling. Socio-economic profiles revealed a largely male, older demographic with varied education levels and farm characteristics. Results indicated that attitude (β = 0.349, p < 0.1) and subjective norms (β = 0.281, p < 0.05) significantly influenced farmers’ intentions to adapt, while perceived behavioural control had no significant effect (β = 0.051, p > 0.1). These findings suggest that improving farmers’ attitudes and strengthening social support systems can enhance their intentions to adopt adaptive strategies. However, the model’s explanatory power (R² = 0.276) suggests that other unexamined factors may also influence farmers’ adaptive intentions, highlighting the need for further research. Overall, our findings suggest that interventions targeting attitudes, social support, and resource access can improve adaptive behaviours.

Review of Technical Photovoltaic Key Performance Indicators and the Importance of Data Quality Routines

Technical key performance indicators (KPIs) are important metrics used to assess and quantitatively summarize various aspects of photovoltaic (PV) systems, including long‐term performance, economic viability, and carbon footprint. Herein, a group of experts of the International Energy Agency's Photovoltaic Power Systems Programme Task 13 collect and describ the most important technical KPIs used in the industry. Thereby, a set of best practices for reliably handling PV system data is presented and the impact of data quality and climatic variability on KPI calculation is investigated. The effective use of technical KPIs allows triggering data‐driven and informed decisions to optimize PV systems and providing a comprehensive overview of how PV systems operate across different conditions and climates. With the worldwide growth of the PV industry, more companies operate/own PV systems in different regions, where the climatic and seasonal profiles differ. This requires context‐aware evaluation of KPIs, or the judicious application of multiple KPIs, to ensure that each asset is evaluated correctly. Beyond that, there is untapped potential in the utilization of KPIs through geospatial mapping and extrapolation of fleet KPIs. This study demonstrates that the uncertainty in KPI estimation is not well understood and depends on data quality, climatic variability, and system configuration.

Assessing the Impact of Climate Variability and Human Activity on Groundwater Resources in the Meskiana Plain, Northeast Algeria

Assessing the Impact of Climate Variability and Human Activity on Groundwater Resources in the Meskiana Plain, Northeast Algeria

Exploring the Impact of Climate Variables and Scenario Simulation on Ecosystem Service Value Profits and Losses in China

Ecosystem restoration can yield multiple benefits, and the quantitative accounting of ecosystem service value (ESV) profits and losses is of significant importance to the economic benefits of ecosystem restoration. This study reveals the dynamic impacts of climate change on ESVs by analyzing the effects of climate variables on ESV profits and losses across different periods and scenarios. The research findings are as follows: (1) From 1990 to 2020, and extending to simulated projections for 2030, China’s ESV exhibits a high distribution pattern in the southern regions. In 2030, under the natural development scenario (NDS), the southwestern region shows a coexistence of high and low ESVs. Under the ecological protection scenario (EPS), ESV in the southwestern region increases, whereas under the urban development scenario (UDS), ESV in the southwest decreases. (2) In both the NDS and UDS, the trends in ESV profits and losses continue from 2010 to 2020. Under the EPS, there is a significant increase in ESV in the southwestern region. The largest contributors to ESV loss are the conversion of grassland to unused land and forest to farmland. The southwestern region shows the most significant spatial differences in ESV profits and losses, with an increase in ESV profits in the northeastern region. In contrast, other regions show no significant spatial differences in ESV profits and losses. (3) From 1990 to 2000, Bio13 (the precipitation of the wettest month) and Bio12 (annual precipitation) had a significant positive impact on ESV profits and losses, indicating that increased precipitation promotes the functioning of ESVs. This study indicates that fluctuations in precipitation and temperature are significant climate factors influencing the value of ESV. Due to climate change, precipitation patterns and temperature swings are now key determinants of ESV changes. By carefully studying ESV profits and losses and their driving factors, this research can serve as the scientific basis for ecosystem restoration and management strategies.

The Impact of Climate Variability on the Livelihoods of Smallholder Farmers in an Agricultural Village in the Wider Belfast Area, Mpumalanga Province, South Africa

The purpose of this study was to investigate the impact of climate change on smallholder farmers in South Africa, particularly focusing on the relationship between agriculture and weather patterns. Understanding this connection is crucial for helping farmers adapt to changing climate conditions and improve their resilience and sustainability. This research analyses 33 years of climate data (1990–2023) from the Belfast weather station to identify long-term climate trends, seasonal shifts, and the frequency of extreme weather events. Statistical analysis, including the Mann–Kendall test, revealed significant changes in temperature, rainfall, and the intensity of extreme weather events, indicating that climate change is already affecting the region. Specifically, the research highlighted significant damage to agricultural infrastructure, such as greenhouses, due to climate-related wind events. This study emphasises the importance of using digital technologies to monitor weather patterns in real-time, aiding in decision-making, and enhancing agricultural efficiency. Additionally, it calls for further research into the social impacts of climate variability, including its effects on community cohesion, migration, and access to social services among smallholder farmers. These findings provide a foundation for developing effective interventions to support the resilience of smallholder farming communities in the face of climate change. Future studies need to consider how climate variability affects farmers’ abilities to access markets, both in terms of transport and product quality.

Metal-organic frameworks for atmospheric water extraction: Kinetic analysis and stochastic programming under climate variability

Increasing demands for sustainable and distributed freshwater sources drive the exploration of water extraction from ambient air. This study presents a comprehensive computational approach for optimizing unit harvesting cost of the adsorption-based atmospheric water extraction (AWE) systems. There are three objectives (i) assessing the impact of climate variability: utilizing k-means clustering, utilizing climate data in different regions to explore the effects of ambient conditions in dry-hot (California), humid-hot (Florida), and dry-cold (Wyoming) regions, resulting in a preference for harvesting under humid-hot conditions. (ii) performing kinetic analysis: The derived kinetic model connects climate variability to operational time and regeneration temperature, critical process design variables. (iii) assessing adsorption materials: three materials (MIL-100 (Fe), MOF-303, and ZJNU-30) were assessed revealing the impact of variations in maximum capacity and isotherm shape on performance and cost. The optimization algorithm uses a two stage stochastic programming approach to account for climate variability and enables an optimization that balances the capital and operating costs across a range of temperature and humidity conditions.

Impact of Climate Variability and Interventions on Malaria Incidence and Forecasting in Burkina Faso.

Malaria remains a climate-driven public health issue in Burkina Faso, yet the interactions between climatic factors and malaria interventions across different zones are not well understood. This study estimates time delays in the effects of climatic factors on malaria incidence, develops forecasting models, and assesses their short-term forecasting performance across three distinct climatic zones: the Sahelian zone (hot/arid), the Sudano-Sahelian zone (moderate temperatures/rainfall); and the Sudanian zone (cooler/wet). Monthly confirmed malaria cases of children under five during the period 2015-2021 were analyzed using Bayesian generalized autoregressive moving average negative binomial models. The predictors included land surface temperature (LST), rainfall, the coverage of insecticide-treated net (ITN) use, and the coverage of artemisinin-based combination therapies (ACTs). Bayesian variable selection was used to identify the time delays between climatic suitability and malaria incidence. Wavelet analysis was conducted to understand better how fluctuations in climatic factors across different time scales and climatic zones affect malaria transmission dynamics. Malaria incidence averaged 9.92 cases per 1000 persons per month from 2015 to 2021, with peak incidences in July and October in the cooler/wet zone and October in the other zones. Periodicities at 6-month and 12-month intervals were identified in malaria incidence and LST and at 12 months for rainfall from 2015 to 2021 in all climatic zones. Varying lag times in the effects of climatic factors were identified across the zones. The highest predictive power was observed at lead times of 3 months in the cooler/wet zone, followed by 2 months in the hot/arid and moderate zones. Forecasting accuracy, measured by the mean absolute percentage error (MAPE), varied across the zones: 28% in the cooler/wet zone, 53% in the moderate zone, and 45% in the hot/arid zone. ITNs were not statistically important in the hot/arid zone, while ACTs were not in the cooler/wet and moderate zones. The interaction between climatic factors and interventions varied across zones, with the best forecasting performance in the cooler/wet zone. Zone-specific intervention planning and model development adjustments are essential for more efficient early-warning systems.

The Impact of Climate Variability on Cattle Heat Stress in Vanuatu

Heat stress is a climate extreme that impacts cattle health, fertility, feed intake, production, and well-being. In Vanuatu, the beef industry is crucial to local livelihoods and the nation’s economy, thus the objective of this study was to examine the impact of heat stress on cattle health and production. This study uses the Heat Load Index (HLI) and Accumulated Heat Load (AHL) as proxies to assess the impact of heat stress on cattle in Vanuatu over a 30-year period (1994–2023), using the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate (ERA5) data. The analysis examines historical patterns of heat stress in cattle across Vanuatu, identifying more instances of heat stress occurring during the wet season due to characteristically elevated temperatures, humidity, and low wind speeds. Findings also suggest that El Niño events may increase the intensity and duration of heat stress events. These insights inform the development of an Early Warning System for heat stress in cattle, establishing a crucial foundation for targeted adaptation strategies aimed at enhancing the resilience and sustainability of Vanuatu’s beef industry to climate variability and change.

The Effects of Air Quality and the Impact of Climate Conditions on the First COVID-19 Wave in Wuhan and Four European Metropolitan Regions

This paper investigates the impact of air quality and climate variability during the first wave of COVID-19 associated with accelerated transmission and lethality in Wuhan in China and four European metropolises (Milan, Madrid, London, and Bucharest). For the period 1 January–15 June 2020, including the COVID-19 pre-lockdown, lockdown, and beyond periods, this study used a synergy of in situ and derived satellite time-series data analyses, investigating the daily average inhalable gaseous pollutants ozone (O3), nitrogen dioxide (NO2), and particulate matter in two size fractions (PM2.5 and PM10) together with the Air Quality Index (AQI), total Aerosol Optical Depth (AOD) at 550 nm, and climate variables (air temperature at 2 m height, relative humidity, wind speed, and Planetary Boundary Layer height). Applied statistical methods and cross-correlation tests involving multiple datasets of the main air pollutants (inhalable PM2.5 and PM10 and NO2), AQI, and aerosol loading AOD revealed a direct positive correlation with the spread and severity of COVID-19. Like in other cities worldwide, during the first-wave COVID-19 lockdown, due to the implemented restrictions on human-related emissions, there was a significant decrease in most air pollutant concentrations (PM2.5, PM10, and NO2), AQI, and AOD but a high increase in ground-level O3 in all selected metropolises. Also, this study found negative correlations of daily new COVID-19 cases (DNCs) with surface ozone level, air temperature at 2 m height, Planetary Boundary PBL heights, and wind speed intensity and positive correlations with relative humidity. The findings highlight the differential impacts of pandemic lockdowns on air quality in the investigated metropolises.

Holocene paleoenvironmental and paleoclimatic variability in a high mountain lake in Sierra Nevada (Spain): Insights from diatom analysis

This study examines the Holocene history of Río Seco Lake (3040 m a.s.l; Sierra Nevada, Southern Spain) by analysing diatom remains and other paleoenvironmental data. The aim is to understand the impact of long-term environmental and climatic variability on the aquatic ecosystem over the past 21,000 years. Our results suggest that shifts in diatom assemblages were mainly climate-driven in terms of temperature and water availability. The absence of diatom remains during the Late Pleistocene indicated low temperatures and prolonged lake snow cover. Five distinct periods were identified during the Holocene. The high abundance of epiphytic and bog-inhabiting taxa and tychoplanktonic Tabellaria flocculosa in the period 11,000–6700 cal yr BP were indicative of a humid climate. The onset of the tychoplanktonic Aulacoseira alpigena between 6700 and 5100 cal yr BP indicated a drop in temperature. These changes intensified during the period 5100–3300 cal yr BP, when the most significant changes in diatom assemblages took place with the dominance of A. alpigena and an abrupt increase in the abundance of the epiphytic Fragilaria radians. During the subsequent period (3300–1500 cal yr BP), the significant declines in A. alpigena and in epiphytic taxa were indicative of increased aridity and higher alkalinity values due to increased aridity and Saharan dust input during this period. The last period (1500–256 cal yr BP) was characterized by a rise in the abundance of Staurosirella pinnata, indicative of warmer temperatures and higher alkalinity values coincident with a marked increase in proxies of temperature and aridity. The increase in aridity and temperature during the last period, which has led to changes in diatom assemblages, is a matter of great concern in an ecosystem that is particularly susceptible to global warming.

Penguatan Kapasitas Adaptasi Generasi Z Pedesaan Dalam Menghadapi Variabilitas Iklim

Introduction: The climate variability that occurs in Indonesia results in various losses for society, especially in rural areas. Rural communities whose livelihoods depend on agricultural and fishing activities are very threatened by climate variability which hampers the community's economy. Objective: This service aims to analyze participation in strengthening the adaptation of rural Generation Z in facing climate variability Method: The focus of community service in this activity is the Z generation who live in rural areas. To make it easier to provide information to generation Z. A participatory approach is used in this activity. Result: There are 3 main activities in strengthening adaptation capacity for generation Z, namely: 1. Introduction stage, including a basic understanding of several forms of climate variability that occur in rural areas. 2. Advanced stage, namely providing education regarding the impact of climate variability in rural areas, especially agriculture and fisheries, 3. Adjustment stage, namely developing adaptation strategies that must be carried out when exposure to extreme climate variability occurs. Conclusion: The results of this service show an increase in generation Z's knowledge in anticipating climate variability.

Impacts of forced and internal climate variability on changes in convective environments over the eastern United States

Hazards from convective weather pose a serious threat to the contiguous United States (CONUS) every year. Previous studies have examined how future projected changes in climate might impact the frequency and intensity of convective weather using simulations with both convection-permitting regional models and coarser-grid climate and Earth system models. We build on this existing literature by utilizing a large-ensemble of historical and future Earth system model simulations to investigate the time evolution of the forced responses in large-scale convective environments and how those responses might be modulated by the rich spectrum of internal climate variability. Specifically, daily data from an ensemble of 50 simulations with the most recent version of the Community Earth System Model was used to examine changes in the convective environment over the eastern CONUS during March-June from 1870 to 2100. Results indicate that anthropogenically forced changes include increases in convective available potential energy and atmospheric stability (convective inhibition) throughout this century, while tropospheric vertical wind shear is projected to decrease across much of the CONUS. Internal climate variability on decadal and longer time scales can either significantly enhance or suppress these forced changes. The time evolution of two-dimensional histograms of convective indices suggests that future springtime convective environments over the eastern CONUS may, on average, be supportive of relatively less frequent and shorter-lived, but deeper and more intense convection.

Effect of Climate Variability on Productivity of Crop in Gicumbi District of Rwanda, (2007-2022)

Climate change has been raising concerns about potential changes to crop yields and production systems. The focus of the present study is to assess the impact of climate variability on food crop yield in the Gicumbi district of Rwanda. Independent Climate variables like rainfall and temperature, and dependent beans and Irish potatoes production data over the past fifteen years i.e. a period from 2007 to 2022 have been used to investigate the evidence of climate variability in Gicumbi, changes in mentioned food crop production, and the likelihood of relationship between crop production of food crops and these climatic variables. Therefore, this research analyzed the effect of climate variability on the productivity of food crops (beans and Irish potatoes) in the Gicumbi district. The specific objectives are to analyze the climate variability in the Gicumbi district from 2007 up to 2022, to assess the productivity of beans and Irish potatoes in the same period, and to determine the extent to which climate variability influences the production of beans and Irish potatoes. The researcher used a descriptive research design. The total population of this study is from 3 selected sectors of Gicumbi totaling 91,054 residents and the sample size is 204 respondents selected using a convenient sampling technique. The primary data was collected using a questionnaire and key informant interviews. The regression analysis was used to analyze the relationship between climate variability and the changes in food crop production in study areas. Specifically, regression analysis was used to determine the relationship between temperature and rainfall variability and food crops (beans & Irish potatoes) production in the focus District.