Climate Adaptation Strategies Research Articles

Indigenous, ethnic, and racial diversity and climate justice: New Zealand's climate adaptation policies and policy approaches

Abstract This research paper interrogates the extent to which indigenous, ethnic, and racial diversity is substantively integrated into climate justice discussions with a focus on New Zealand’s climate change adaptation policies. A qualitative research design is used, employing a documentary analysis and summative content analysis to scrutinise New Zealand climate change adaptation policies and their responsiveness to indigenous, ethnic and racial diversity within the ambit of climate justice. This study aims to measure the extent to which these policies promote inclusive and equitable climate adaptation outcomes. This study makes a significant contribution to the nuanced understanding of climate justice research, particularly regarding indigenous and ethnic minority communities. The study is expected to contribute to the existing knowledge base and inform the formulation of inclusive policies that integrate the diverse perspectives of these communities into climate adaptation and policy-making processes. The research findings highlight existing gaps and emphasise the importance of incorporating indigenous, ethnic, and racial diversity into policy development and implementation. The aim is to shape climate adaptation strategies that are representative of aware of insights from various communities in contemporary cities.

Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables

This study assesses the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023. Employing high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments, integrated with climate variables from CHIRPS and ERA5 datasets, our approach leverages Google Earth Engine (GEE) for efficient processing. It combines statistical methodologies, including linear regression, Mann–Kendall trend tests, Sen's slope estimator, partial correlation, and cross wavelet transform analyses. The findings highlight significant spatial and temporal variations in NDVI, with an annual increase averaging 0.00197 per year (p < 0.0001). This positive trend is coupled with an increase in precipitation by 0.4801 mm/year (p = 0.0016). In contrast, our analysis recorded a slight decrease in temperature (− 0.01011 °C/year, p < 0.05) and a reduction in solar radiation (− 0.27526 W/m2/year, p < 0.05). Notably, cross-wavelet transform analysis underscored significant coherence between NDVI and climatic factors, revealing periods of synchronized fluctuations and distinct lagged relationships. This analysis particularly highlighted precipitation as a primary driver of vegetation growth, illustrating its crucial impact across various Pakistani regions. Moreover, the analysis revealed distinct seasonal patterns, indicating that vegetation health is most responsive during the monsoon season, correlating strongly with peaks in seasonal precipitation. Our investigation has revealed Pakistan's complex association between vegetation health and climatic factors, which varies across different regions. Through cross-wavelet analysis, we have identified distinct coherence and phase relationships that highlight the critical influence of climatic drivers on vegetation patterns. These insights are crucial for developing regional climate adaptation strategies and informing sustainable agricultural and environmental management practices in the face of ongoing climatic changes.

Predicting the short and long term effects of food price inflation, armed conflicts, and climate variability on global acute malnutrition in Somalia

BackgroundMalnutrition poses a substantial challenge in Somalia, impacting approximately 1.8 million children. This critical issue is exacerbated by a multifaceted interplay of factors. Consequently, this study seeks to examine the long-term and short-term effects of armed conflicts, food price inflation, and climate variability on global acute malnutrition in Somalia.MethodsThe study utilized secondary data spanning from January 2015 to December 2022, sourced from relevant databases. Two distinct analytical approaches were employed to comprehensively investigate the dynamics of global acute malnutrition in Somalia. Firstly, dynamic autoregressive distributed lag (ARDL) simulations were applied, allowing for a nuanced understanding of the short and long-term effects of armed conflicts, food price inflation, and climate variability on malnutrition. Additionally, the study employed kernel-based regularized least squares, a sophisticated statistical technique, to further enhance the robustness of the findings. The analysis was conducted using STATA version 17.ResultsIn the short run, armed conflicts and food price inflation exhibit positive associations with global acute malnutrition, particularly in conflict-prone areas and during inflationary periods. Moreover, climatic variables, specifically temperature and rainfall, demonstrate positive associations. It is important to note that temperature lacks a statistically significant relationship with global acute malnutrition in the short run. In the long run, armed conflicts and food price inflation maintain persistent impacts on global acute malnutrition, as confirmed by the dynamic ARDL simulations model. Furthermore, both temperature and rainfall continue to show positive associations with global acute malnutrition, but it is worth noting that temperature still exhibits a non-significant relationship. The results from kernel-based regularized least squares were consistent, further enhancing the robustness of the findings.ConclusionsIncreased armed conflicts, food price inflation, temperature, and rainfall were associated with increased global acute malnutrition. Strategies such as stabilizing conflict-prone regions, diplomatic interventions, and peace-building initiatives are crucial, along with measures to control food price inflation. Implementing climate adaptation strategies is vital to counter temperature changes and fluctuating rainfall patterns, emphasizing the need for resilience-building. Policymakers and humanitarian organizations can leverage these insights to design targeted interventions, focusing on conflict resolution, food security, and climate resilience to enhance Somalia's overall nutritional well-being.

Impacts of Climate Change and Adaptation Strategies for Rainfed Barley Production in the Almería Province, Spain

Mediterranean water-stressed areas face significant challenges from higher temperatures and increasingly severe droughts. We assess the effect of climate change on rainfed barley production in the aridity-prone province of Almería, Spain, using the FAO AquaCrop model. We focus on rainfed barley growth by the mid-century (2041–2070) and end-century (2071–2100) time periods, using three Shared Socio-economic Pathway (SSP)-based scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. Using the paired t-test, Spearman and Pearson correlation coefficient, Root Mean Squared Error, and relative Root Mean Squared Error, we verified AquaCrop’s ability to capture local multi-year trends (9 or more years) using standard barley crop parameters, without local recalibration. Starting with a reference Initial Soil Water Content (ISWC), different soil water contents within barley rooting depth were modelled to account for decreases in soil water availability. We then evaluated the efficiency of different climate adaptation strategies: irrigation, mulching, and changing sowing dates. We show average yield changes of +14% to −44.8% (mid-century) and +12% to −55.1% (end-century), with ISWC being the main factor determining yields. Irrigation increases yields by 21.1%, utilizing just 3% of Almería’s superficial water resources. Mulches improve irrigated yield performances by 6.9% while reducing irrigation needs by 40%. Changing sowing dates does not consistently improve yields. We demonstrate that regardless of the scenario used, climate adaptation of field barley production in Almería should prioritize limiting soil water loss by combining irrigation with mulching. This would enable farmers in Almería’s northern communities to maintain their livelihoods, reducing the province’s reliance on horticulture while continuing to contribute to food security goals.

Conceptualising and enacting pathways to transformative climate justice: examples from the Philippines

Conceptualising and enacting pathways to transformative climate justice: examples from the Philippines

Aging in climate change: Unpacking residential mobility and changes of social determinants of health in southern United States

The southern coastal states of the United States are susceptible to extreme weather and climate events. With growing move-in and -out older populations in the region, health implications of their residential mobility lack sufficient knowledge. Using 126,352 person-level records from 2012 to 2021, we examined geospatial and temporal patterns of older populations’ residential mobility, considering the changing social determinants of health and disparities. We found the moves of older populations with socioeconomic or health disadvantages were related to increased exposure to environmental hazards and reduced access to health resources. The findings inform targeted strategies for climate adaptation that address the needs of vulnerable aging populations.

Rainfall variability and welfare of agricultural households: Evidence from rural Niger

AbstractVariable weather continues to be the major source of vulnerability to chronic hunger and poverty in many developing countries due to the strong dependency of livelihood strategies on rainfed farming. Quantifying the effect of climatic parameters on agricultural households is, therefore, necessary to help policymakers understand the benefits of climate policies, improve the allocation of the scarce resources dedicated to adaptation and prioritize among adaptation strategies. This article investigates the empirical relationship between the welfare of rural households and rainfall variability in the semi‐arid tropics, using household panel data and high‐resolution remotely sensed rainfall data from Niger. We find that a standard deviation increase in rainfall variability is associated with a reduction of real food consumption by 11.13%. Results also indicate that a standard deviation increase in rainfall variability reduces expenditures for cereal‐based products, animal‐based products and processed foods by 11.96%, 21.31%, and 16.23%, respectively. Our results are consistent across a battery of robustness checks. Finally, we find geographical‐based differences in terms of the effect and that access to cereal banks cushions the negative effect of rainfall variability. Policy interventions aiming at improving the well‐being of rural households should therefore emphasize improving climate adaptation strategies.

Evaluating the temperature–mortality relationship over 16 years in Cyprus

ABSTRACT In many regions of the world, the relationship between ambient temperature and mortality is well-documented, but little is known about Cyprus, a Mediterranean island country where climate change is progressing faster than the global average. We Examined the association between daily ambient temperature and all-cause mortality risk in Cyprus. We conducted a time-series analysis with quasipoisson distribution and distributed lag non-linear models to investigate the association between temperature and all-cause mortality from 1 January 2004 to 31 December 2019 in five districts in Cyprus. We then performed a meta-analysis to estimate the overall temperature-mortality dose-response relationship in Cyprus. Excess mortality was computed to determine the public health burden caused by extreme temperatures. We did not find evidence of heterogeneity between the five districts (p = 0.47). The pooled results show that for cold effects, comparing the 1st, 2.5th, and 5th percentiles to the optimal temperature (temperature associated with least mortality, 25 ℃), the overall relative risks of mortality were 1.55 (95% CI: 1.32, 1.82), 1.41 (95% CI: 1.21, 1.64), and 1.32 (95% CI: 1.15, 1.52), respectively. For heat effects, the overall relative risks of mortality at the 95th, 97.5th and 99th percentiles were 1.10 (95% CI: 1.04, 1.16), 1.17 (95% CI: 1.07, 1.29), and 1.29 (95% CI: 1.11, 1.5), respectively. The excess mortality attributable to cold days accounted for 8.0 deaths (95% empirical CI: 4.5–10.8) for every 100 deaths, while the excess mortality attributable to heat days accounted for 1.3 deaths (95% empirical CI: 0.7–1.7) for every 100 deaths. The results prompt additional research into environmental risk prevention in this under-studied hot and dry region that could experience disproportionate climate change related exposures. Implications: The quantification of excess mortality attributable to temperature extremes shows an urgent need for targeted public health interventions and climate adaptation strategies in Cyprus and similar regions facing rapid climate change. Future steps should look into subpopulation sensitivity, coping strategies, and adaptive interventions to reduce potential future risks.

Influence of Climate Change Adaptation Policies on Sheep Farming Viability in Australia

Purpose: The aim of the study was to analyze the influence of climate change adaptation policies on sheep farming viability in Australia. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Climate change adaptation policies in Australia have significantly influenced the viability of sheep farming in recent years. Research indicates that the implementation of targeted adaptation measures, such as improved pasture management and water conservation strategies, has helped mitigate the adverse impacts of climate change on sheep farming viability. Studies have shown that farms adopting these policies have experienced higher survival rates of livestock and increased profitability compared to those without such measures. Additionally, government support programs aimed at assisting sheep farmers in implementing climate adaptation strategies have been instrumental in enhancing the resilience of the sector. Unique Contribution to Theory, Practice and Policy: Adaptation theory in environmental economics, resilience theory &amp; theory of planned behavior (TPB) may be used to anchor future studies on analyze the impact of climate change on wheat yields in Australia. The enhancement of breeding programs focuses on practical genetic advancements to create drought and heat-resistant sheep varieties, addressing direct climate impacts on livestock. By advocating for government and industry funding for genetic research, the recommendations influence policy towards investing in long-term solutions for climate resilience.

Climate mitigation and adaptation strategies in the transport sector: An empirical investigation in Germany

Due to climate change, extreme weather events will increase in intensity, frequency, and duration in the future, negatively impacting logistics and transport systems. The threat of missing climate targets and a lack of climate adaptivity strategies in the transport sector leads to growing climate-related risks for transportation companies. The present paper provides a qualitative study exploring mitigation and adaptation strategies within the logistics sector. It analyzes the challenges transportation companies face in developing climate-neutral business models and adapting to the consequences of climate change. Our results show that logistics companies need to be more prepared for the consequences of climate change and, at the same time, insufficiently address climate change mitigation, making the sector more vulnerable to climate extremes in the future. A transformation framework is developed to assess the logistics firms’ climate protection measures and climate adaptation strategies while highlighting existing development lags in climate mitigation and climate adaptation. Moreover, possible future strategies to combat climate risks in the sector are pathed.

Analysis of the Impact of Urban Green Spaces on Mitigating the Urban Heat Island Effect

The Urban Heat Island (UHI) effect, characterized by higher temperatures in urban areas compared to their rural surroundings, poses significant challenges for energy consumption, air quality, and public health. This study examines the impact of urban green spaces on mitigating the UHI effect in four major Spanish cities: Madrid, Barcelona, Seville, and Valencia. Using high-resolution satellite imagery, ground-based temperature measurements, and advanced GIS and statistical modeling techniques, we quantified the temperature differences between green and non-green urban areas. Our findings indicate that green spaces, including parks, street trees, and green roofs, significantly reduce urban temperatures, with parks exhibiting the highest cooling effects. The spatial analysis revealed that UHI hotspots are concentrated in densely built-up areas, while green spaces effectively mitigate these effects. Seasonal variations show that the cooling benefits of green spaces are more pronounced during the summer months. This study highlights the importance of incorporating diverse and well-distributed green spaces in urban planning to enhance thermal comfort, reduce energy consumption, and improve urban livability. Policy recommendations are provided to guide the integration of green infrastructure in climate adaptation strategies for Spanish cities.

Financing climate adaptation in Flemish cities: Unpacking financial strategies and policy dynamics for nature-based solutions

As climate change continues to impact cities, nature-based solutions (NBS) are being advanced as important adaptation strategies for mitigating these negative effects. As is the case throughout Europe, Flemish cities have enacted adaptation policies and plans outlining the importance of NBS. Nevertheless, the implementation of NBS has been slow. Local governments identify financing as an important barrier. Although private financing is often proposed as a solution, few studies have applied a public-financing perspective to generate insight into and remedies for such issues. In this article, we examine how four Flemish cities are financing NBS implemented in public spaces as climate adaptation strategies. Based on a multiple case study approach, our results uncover that different financing strategies are employed during the design, implementation and maintenance phase of developing NBS projects. Additionally, we learn that the interplay between policy and financing becomes an important catalyst for investments in public NBS. We identified three approaches administrations use to secure (public) resources. During the design phase, support is developed within the administration and politically through (1) fostering internal collaboration by developing integrated spatial NBS designs. In the implementation phase resources are attracted by (2) putting the developed spatial designs to work and seizing available funding opportunities. During the maintenance phase (3) strategic partnerships are established with NBS beneficiaries to alleviate costs for municipalities. We conclude that, in the absence of more long-term forms of public financing, these approaches offer smaller cities tools to overcome the financial barrier.

Structural outcomes of climate adaptation treatments in two contrasting northern temperate forests

Forest managers require climate adaptation strategies that are regionally relevant and translatable into planning processes. Adaptation frameworks, such as the resistance, resilience, transition framework, can guide the development of these strategies. However, there are limited examples of how these concepts can be operationalized with concomitant estimates of changes in forest structural complexity and diversity, which may support adaptive capacity. To address this knowledge gap, two operational-scale, replicated experiments were studied to understand how application of the resistance, resilience, transition framework influences stand structure in two contrasting northern forests: mixed pine and mesic hardwoods. We found that treatments corresponding to each adaptation approach (resistance, resilience, transition) manifested differently in each forest type. In mixed-pine, there were greater differences in structural diversity metrics among treatments; there were fewer differences among treatments in the mesic hardwood forest, which had comparatively greater pre-treatment structural variation. In both forests, our analyses demonstrate that management strategies associated with greater emphasis on change and adaptation (i.e., resilience and transition) created a quantifiably more heterogeneous arrangement of structural elements across treatment units, supporting shifts in stand-scale understory resource patterning. These results underscore the importance of accounting for the influence of pre-treatment stand conditions on outcomes of adaptation treatments and that stand-wide averaging of plot measurements may serve to obscure stand-scale diversity metrics. The variation in structural conditions across stands that we found is expected to contribute to forest response to novel disturbances by providing multiple recovery pathways. Based on these findings, application of adaptive silvicultural treatments can generate varying levels of structural heterogeneity at the stand-scale which in turn can confer adaptation potential; however, ecological memory strongly influences post-management stand conditions.

GIS-BASED REGRESSION ANALYSIS OF AIR QUALITY AND LAND SURFACE TEMPERATURE IN METRO MANILA AIRSHEDS

Abstract. This study examines the spatial relationship of land surface temperature (LST) derived from MODIS, elevation, and air quality parameters (CO, NO2, and SO2) derived from Sentinel 5P in the Metro Manila airsheds from January 2019 to March 2023. Using Ordinary Least Squares (OLS) and Generalized Linear Regression (GLR), mean LST and heat index from the Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA) ground stations exhibit a strong positive correlation, allowing the use of LST for further analysis. Across different combinations between LST, elevation, and air quality parameters, a weak to low negative correlation was seen between DEM to LST, CO, and NO2. In addition, weak to low positive correlation was seen between LST to CO and NO2. Almost no correlation was found between DEM and SO2, and LST and SO2. These results may be unreliable due to overfitting, non-stationarity, bias, or misspecification as implied by their statistical parameters. To enhance the reliability, it is recommended to investigate additional air quality parameters such as Normalized Difference Built-Up Index (NDBI) as high LST, CO, and NO2 have shown clustering in urban areas of Metro Manila. Moreover, it suggests exploring other regression modeling and methodologies, such as training and test sets, to identify the best-fit model. In conclusion, this study provides an exploratory foundation for future research and comparative assessment on using different methods for modeling these variables. This comprehensive approach enhances understanding of the complex interplay between temperature, elevation, and air quality, aiding the development of informed urban climate adaptation strategies.

Assessing the Impact of Climate Change on Snowfall Conditions in Poland Based on the Snow Fraction Sensitivity Index

This study focuses on temperature and snowfall conditions in Poland, both of which were analyzed from 1981 to 2020. A 40-year record of daily snow fraction time series values was reconstructed using a unique and global multi-source weighted-ensemble precipitation (MSWEP) product, which provided a spatially and temporally consistent reference for the assessment of meteorological conditions. The average states and trends in snow fraction and temperature were analyzed across several years, focusing on the 6-month cold season (November–April). The impact of temperature on the snow fraction pattern was assessed by introducing a snow fraction sensitivity index. To predict short-term changes in snow conditions, a proxy model was established; it incorporated historical trends in the snow fraction as well as its mean state. This study provides clear evidence that the snow fraction is principally controlled by increases in temperature. A warming climate will thus cause a decline in the snow fraction, as we observed in vast lowland areas. Given the ongoing global warming, by the 2050s, snow-dominated areas may go from covering 86% to only 30% of the country’s surface; they will be converted into transient rain–snow areas. Our results demonstrate that a decline in snow water resources has already occurred, and these resources are expected to diminish further in the near future. New insights into the sensitivity of the snow fraction to climate warming will expand our collective knowledge of the magnitude and spatial extent of snow degradation. Such widespread changes have implications for the timing and availability of soil and groundwater resources as well as the timing and likelihood of floods and droughts. Thus, these findings will provide valuable information that can inform environmental managers of the importance of changing snowfall conditions, guiding them to include this aspect in future climate adaptation strategies.

Consequence of habitat specificity: a rising risk of habitat loss for endemic and sub-endemic woody species under climate change in the Hyrcanian ecoregion

Endemic species are more impacted by climate change than other taxa. However, assessing the vulnerability of endemics to these changes in some regions, such as the Hyrcanian forest, is limited, despite its importance for biodiversity and ecosystem function. To address the question of expected habitat shifts under climate change across the Hyrcanian ecoregion, we built an ensemble of species distribution models (SDM) under two emission scenarios (RCP 4.5 and RCP 8.5) for 15 endemic woody taxa. To identify the potential priority conservation areas, we also applied a spatial prioritization approach. Overall, our results suggest that the impacts of climate change are more severe on the eastern parts of the region (Golestan) and the Talysh Mountains (north-western Hyrcanian ecoregion) with over 85% and 34% loss of suitable habitats over the next 80 years. The central part of the Alborz Mountains (Mazandaran) and some areas in the Talysh Mountains could be potential climatic refugia under the future conditions for endemic taxa. The most prominent changes are expected for Ruscus hyrcanus, Gleditsia capsica, Acer velutinum, Frangula grandifolia, and Buxus hyrcana. The worrying predicted loss of suitable habitats for most studied taxa would dramatically affect the stability and resilience of forests, threatening thus biodiversity of the Hyrcanian ecoregion. We present the first estimation of the potential risks involved and provide useful support for regional climate-adaptation strategy, indicating potential conservation priority areas for maintaining and preserving its resources. Notably, only 13.4% of areas designated for conservation and management under climate change will be located within the current Hyrcanian protected areas, yet the majority of these areas are classified as low priority.

Evaluating seawater intrusion forecast uncertainty under climate change in the Pajaro Valley, California

Climate change and climate variability impacts such as rising sea levels have the potential to exacerbate seawater intrusion and the strain on coastal freshwater resources in already stressed groundwater basins such as those in the Pajaro Valley groundwater basin, California. Regional hydrologic models are often coupled with climate projections to forecast future hydrologic conditions and inform adaptive resources management strategies. However, there is high uncertainty in the future projections of water resources due to uncertainties from downscaling global general circulation models (GCMs) to local scale climate change projections, future land use changes, and the inherent uncertainty of developed hydrologic models. Future climate projections and the magnitude of their influence on modeled hydrologic drivers are highly variable. Therefore, to develop a forecast model, an ensemble of different projections can be used to capture a wider range of basin responses and the associated uncertainties in the modeled forecasts. Understanding the reliability and uncertainty of forecasts is important for developing climate adaptation strategies such as developing protective thresholds, particularly at the basin scale where the impacts are felt, and adaptation is implemented. To demonstrate this, an uncertainty analysis of groundwater level and seawater intrusion forecasts for the Pajaro Valley groundwater basin was performed using an ensemble of three future climate projections with the Pajaro Valley Integrated Hydrologic Model (PVIHM) and the first-order second moment (FOSM) method. FOSM uncertainty analysis of hydrologic forecasts across a multi-GCM climate ensemble provides an upper and lower bound of potential impacts of climate change on sustainability targets related to mitigating seawater intrusion. The groundwater level forecasts’ narrow range of variability can help policymakers in adaptation planning by constraining possible outcomes to a focused range for risk-management decisions. However, less than one-third of groundwater level forecasts met the current protection thresholds to prevent chronic lowering of groundwater. Therefore, sustainability targets may need to be reassessed. Relative to groundwater level changes, the seawater intrusion forecasts had larger uncertainty due to the GCM climate projections and the simulated hydrologic response that were compounded by the propagation of scaling and bias from the GCMs and model simplifications in simulating the coastal boundary.

Evaluating the Cost-Benefit Analysis of Climate Adaptation Strategies on Coastal Communities

Climate change poses significant challenges to coastal communities worldwide, necessitating the development and implementation of effective adaptation strategies. This research undertakes a rigorous evaluation of the cost-benefit analysis (CBA) associated with various climate adaptation measures tailored to coastal settings. Employing a multidisciplinary approach, encompassing economic, environmental, and social dimensions, the study aims to elucidate the intricate interplay between costs and benefits inherent in these strategies. Through meticulous data collection and methodological rigor, key factors influencing the cost-effectiveness of adaptation interventions are identified and analyzed. The findings reveal nuanced insights into the effectiveness and efficiency of different adaptation approaches, shedding light on their relative merits and limitations. Moreover, this research contributes to advancing the theoretical underpinnings of CBA in the context of climate adaptation, offering practical recommendations for policymakers, planners, and stakeholders tasked with enhancing the resilience of coastal communities. By bridging the gap between theory and practice, this study underscores the imperative of informed decision-making and proactive action in safeguarding coastal regions against the impacts of climate change.

Back-to-back high category atmospheric river landfalls occur more often on the west coast of the United States

The catastrophic December 2022-January 2023 nine atmospheric rivers in California underscore the urgent need to better understand such high-risk weather extremes. Here we applied a machine learning clustering tool to understand the activity of atmospheric river clusters. Reanalysis results show that clusters with high density, that is the time fraction under atmospheric river conditions within a cluster, exhibit more frequent high-category atmospheric rivers, alongside an increased likelihood for extreme precipitation and severe land surface responses. The key circulation patterns of atmospheric river clusters are primarily attributed to subseasonal variability. Furthermore, the occurrence and density of atmospheric river clusters are modulated by the daily variability of the geopotential height field. Climate model projections suggest that atmospheric river clusters with higher density and higher categories will be more frequent as warming level increases. Our findings emphasize the important role of atmospheric river clusters in the development of climate adaptation and resilience strategies.

Horticultural Farmer's Perceptions and Adaptations to Climate Change in East Java, Indonesia

The agricultural sector highly vulnerable to the risks and impacts of global climate change. Horticultural farmers in East Java have experienced climate change, which is marked by a decrease in the level of productivity produced in recent years. This study aims to determine how farmers' perceptions of climate change and adaptation strategies are carried out. Data were collected through direct survey to horticultural farmers in Malang and Kediri Regencies, East Java. Data analysis was carried out descriptively, by describing the data that had been collected regarding the perception and adaptation of farmers. The results of the study shows that farmers have a high perception of climate change. Farmers' strategies in dealing with climate change include the adaptation by changing cropping patterns, changing plant varieties, changing plant types, changing fertilizer inputs, doing irrigation, and increasing knowledge and skills about agriculture.