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We present new climate field reconstructions (CFR) of tropical Pacific ENSO sea surface temperatures (HadISST) for the boreal winter season using a circum‐Pacific tree‐ring network from known El Niño rainfall impact regions. We use two different CFR methods: Point‐by‐Point Regression (PPR) and reduced‐space Orthogonal Spatial Regression (OSR). Both methods produce reconstructions with high validation skill, but OSR is preferred because it has less spatial noise and is more efficient. Only the leading EOF of the SST field (EOF1) can be skillfully reconstructed by either method; EOF2 does not validate. The success of EOF1 reflects its importance for ENSO rainfall impacts over land; the failure with EOF2 is from the lack of these impacts. EOF1 allows for the reconstruction of many ENSO indices, including the ENSO Longitudinal Index (ELI). We also find evidence in our reconstructions for a recent increase in ENSO activity. Plain Language Summary: Earth's climate is strongly affected by how warm the tropical Pacific Ocean "El Niño" region is. This is especially true for the delivery of rainfall over many parts of the globe. Tree growth can thus be strongly affected by El Niño impacts on rainfall. We use this relationship to reconstruct tropical Pacific sea surface temperatures associated with El Niño over most of the past millennium from a network of annual tree‐ring chronologies located in regions known to be impacted by El Niño rainfall. Only the leading mode of variability in Pacific sea surface temperatures associated with El Niño can be reconstructed well, but it reflects most of the long‐term variability of El Niño exceptionally well. The reconstruction extends back to 1500 with exceptional skill and back to 1100 with acceptable skill. We can thus compare recent El Niño variability, perhaps affected by global warming, with what happened over the previous centuries unaffected by human activity. We find evidence for an increase in El Niño activity, and for an overall warming in recent decades. Key Points: Tree‐ring series from ENSO rainfall impact regions reconstruct tropical Pacific SSTs with high degrees of skill back to 1500 CE and 1100 CETwo very different reconstruction methods produce similar results and each can only reconstruct the leading EOF mode of SST variabilityReconstructions extending back 1100 CE indicate a recent increase in El Niño variability, and overall SST warming in the equatorial Pacific [ABSTRACT FROM AUTHOR]

Due to low adaptive capacities and high reliance on weather-sensitive natural ecosystems for their livelihoods and food production, smallholder farmers are highly vulnerable to risks associated with climate change and variability. Such risks are location-specific; thus, to cope with them, smallholder farmers require tailored adaptation strategies. To support these farmers, this study aimed to identify climatic risks threatening sustainable smallholder farming in the Limpopo Province regions of Gavaza, Ga-Makanye and Giyani. Weather station records spanning up to 1980–2021 were used to identify climatic risks, for the October–April dryland maize growing season. Risks were identified based on temporal trends and/or interannual variability patterns for reference evapotranspiration and a suite of agriculturally relevant rainfall and temperature indices. Based on the identified risks, tailor-made adaptation strategies were devised for application by farmers within the study region. The results revealed the specific risks of growing seasons becoming shorter and increasingly hotter with highly irregular rainfall patterns. To adapt and improve agricultural productivity despite these prevailing climatic risks, farmers within the study region will benefit if they plant drought tolerant, early maturing and higher yielding crop varieties, apply soil water conservation techniques and make use of seasonal and daily weather forecasts to guide their decision-making. [ABSTRACT FROM AUTHOR]

Although the social and spatial dimensions of climate impacts are increasingly recognized, livelihood vulnerability studies combining gender and agro-ecology have received less attention. Moreover, to the best of our knowledge, these studies have not employed stepwise Principal Component Analysis (PCA).This study examines livelihood vulnerability to climate change and variability from gender and agro-ecological perspectives in Bako-Tibe District, Ethiopia. Rural livelihood analysis was used to measure the adaptive capacity of households. Two-stage PCA was employed to index vulnerability dimensions: sensitivity and exposure in the first stage, and adaptive capacity in the second stage. The results show that disparity in adaptive capacity largely mediates vulnerability levels. Further, for agro-ecological factors, households residing within more climate exposure have better adaptive capacity; hence, they are less vulnerable than those in lower exposure agro-ecology. In all comparisons, female-headed households are significantly more vulnerable than male-headed households, but do not necessarily possess lower adaptive capacities. While agro-ecological and gender-specific factors differentiate vulnerability of male-and female-headed household across agro-ecologies, only gender-specific factors set such variations at district level and within agro-ecology. The results imply that scrutinizing the potential sensitivity of vulnerability level to study context is crucial. Results also suggest that, managing agro-ecological and/or gender-specific factors that hamper livelihood assets is vital for reducing climate-induced vulnerability. [ABSTRACT FROM AUTHOR]

Abstract We present new climate field reconstructions (CFR) of tropical Pacific ENSO sea surface temperatures (HadISST) for the boreal winter season using a circum‐Pacific tree‐ring network from known El Niño rainfall impact regions. We use two different CFR methods: Point‐by‐Point Regression (PPR) and reduced‐space Orthogonal Spatial Regression (OSR). Both methods produce reconstructions with high validation skill, but OSR is preferred because it has less spatial noise and is more efficient. Only the leading EOF of the SST field (EOF1) can be skillfully reconstructed by either method; EOF2 does not validate. The success of EOF1 reflects its importance for ENSO rainfall impacts over land; the failure with EOF2 is from the lack of these impacts. EOF1 allows for the reconstruction of many ENSO indices, including the ENSO Longitudinal Index (ELI). We also find evidence in our reconstructions for a recent increase in ENSO activity.

The concentration of chlorophyll‐a (CHL) is an important proxy for autotrophic biomass and primary production in the ocean. Quantifying trends and variability in CHL are essential to understanding how marine ecosystems are affected by climate change. Previous analyses have focused on assessing trends in CHL mean, but little is known about observed changes in CHL extremes and variance. Here we apply a quantile regression model to detect trends in CHL distribution over the period of 1997–2022 for several quantiles. We find that the magnitude of trends in upper quantiles of global CHL (>90th) are larger than those in lower quantiles (≤50th) and in the mean, suggesting a growing asymmetry in CHL distribution. On a regional scale, trends in different quantiles are statistically significant at high latitude, equatorial, and oligotrophic regions. Assessing changes in CHL distribution has potential to yield a more comprehensive understanding of climate change impacts on CHL. Plain Language Summary: The marine environment is essential to nature and society, as it provides food and other important services such as Earth's climate regulation and habitat for species. Marine primary productivity is increasingly stressed due to global climate change. Detecting the impact of climate change on primary producers should be a priority given their critical role in the climate system. Most studies focus on the impact of climate change by evaluating the mean state of primary productivity, but little is known about whether and how climate change is impacting variance and extremes. Here we assess changes in chlorophyll‐a (CHL), which is an important proxy for primary production of marine ecosystems. We quantify long‐term changes in different aspects of the CHL distribution (mean, variance, and extremes) using a quantile regression model. We find that CHL high extremes and variability are slightly intensified globally during the 26 years of observational record. Trends in regional scales, especially in high‐latitude and North Atlantic Subtropical Gyre, show that CHL high extremes have been increasing since 1997. Our results suggest that more emphasis should be put into understanding the impact of climate change on the variance and extremes of primary productivity for climate change adaptation and mitigation. Key Points: Long‐term changes are detected in different aspects of the distribution of chlorophyll‐a (not just the mean state)Oceanic chlorophyll‐a high extremes are changing faster than chlorophyll‐a mean globally during 1997–2022On a regional scale, chlorophyll‐a extremes trends are predominant at high latitude (+), equatorial (−), and oligotrophic regions (−) [ABSTRACT FROM AUTHOR]

The Umlindi newsletter was developed to provide information towards climate advisories, considering, for instance, drought conditions, presented in a relevant manner for the agricultural and disaster sectors in South Africa. This newsletter, which is disseminated on a monthly basis, provides information derived from climate-related monitoring products obtained from an integration of remote sensing and in situ data from weather stations. It contains useful indicators, such as rainfall, vegetation, and fire conditions, that provide an overview of conditions across the country. The present study demonstrates how these natural resource indices are integrated and consolidated for utilization by farmers, policy-makers, private organizations, and the general public to make day-to-day decisions on the management and mitigation of natural disasters. However, there is a need to expand these baseline observation initiatives, including the following: (1) forecasting future conditions to strengthen coping mechanisms of government, farmers, and communities at large; and (2) incorporating information on other natural disasters such as floods and extreme heat. In the context of South Africa, this information is important to improve disaster preparedness and management for agricultural productivity. In a global context, the Umlindi newsletter can be insightful for developing and disseminating natural resources information on adaptation to and mitigation of climate change and variability impacts to other regions facing similar risks. Furthermore, while international organizations also provide natural resource information, the Umlindi newsletter may be distinguished by its regional focus and linkages to individual communities. It bridges the gap between global environmental data and local decision-making by illustrating how global scientific knowledge may be applied locally. [ABSTRACT FROM AUTHOR]

Social and biophysical vulnerability of agriculture to climate change has increased exponentially in Sub-Sahara Africa (SSA). Although contract farming (CF) schemes have burgeoned in developing countries as a resilience-building strategy for smallholder farmers, there is a lack of empirical evidence to show how and why CF enhances smallholder farmers’ resilience to climate change in SSA. This paper combines theoretical insights from climate change adaptation literature with qualitative data to explore three CF schemes implemented in northern Ghana to find out whether or not they enhance smallholder farmers’ resilience to climate change. The results show that smallholder farmers perceived a change in climate parameters, namely declining rainfall, uneven rainfall distribution and rising temperatures, leading to reduced agricultural yields. In response, smallholder farmers have implemented three CF schemes, which vary, not only in terms of crops cultivated but in terms of the contractual arrangement, as a resilience-building strategy to the changing climate. The CF schemes provided material and non-material resources to participating farmers and enhanced their resilience to climate change better than non-contract farmers. Contrarily, depending on how production risks are distributed in the schemes studied, CF can undermine the resilience of smallholder farmers. Ultimately, the paper provides critical insights on how to design and implement CF schemes to enhance the resilience of agrarian societies in the face of increasing climate change in SSA and beyond. [ABSTRACT FROM AUTHOR]

Abstract The concentration of chlorophyll‐a (CHL) is an important proxy for autotrophic biomass and primary production in the ocean. Quantifying trends and variability in CHL are essential to understanding how marine ecosystems are affected by climate change. Previous analyses have focused on assessing trends in CHL mean, but little is known about observed changes in CHL extremes and variance. Here we apply a quantile regression model to detect trends in CHL distribution over the period of 1997–2022 for several quantiles. We find that the magnitude of trends in upper quantiles of global CHL (>90th) are larger than those in lower quantiles (≤50th) and in the mean, suggesting a growing asymmetry in CHL distribution. On a regional scale, trends in different quantiles are statistically significant at high latitude, equatorial, and oligotrophic regions. Assessing changes in CHL distribution has potential to yield a more comprehensive understanding of climate change impacts on CHL.

Agriculture is the world's main economic activity. According to the Intergovernmental Panel on Climate Change, this activity is expected to be impacted by drought. In the Northeast region of Brazil (NEB), most agricultural activity is carried out by small rural communities. Local socio-economic data were analyzed using multivariate statistical techniques in this study to determine agricultural sensitivity to drought events (SeA) and agricultural vulnerability to drought extremes (VaED). The climate data used to develop the risk factor (Rdrought) were the drought indicator with the Standard Precipitation Index (SPI) and the average number of drought disasters from 1991 to 2012. Conditional probability theory was applied to determine agricultural vulnerability to drought extremes (VaED). Characterization of the risk of agricultural drought using the proposed methodology showed that the rainy season presents high risk values in the central region, covering areas of the states of Ceará, Piauí, Pernambuco and Rio Grande do Norte, as well as all areas of the semi-arid region. The risk ranged from high to medium. The results also indicated that part of the south of Bahia and the west of Pernambuco have areas of extreme agro-climatic sensitivity. Consequently, these states have an extreme degree of climate vulnerability during the region's rainy season. [ABSTRACT FROM AUTHOR]

Pegged on Protection Motivation Theory, a modified socio-cognitive model of private adaptation to climate change and variability was deployed in order to provide a better understanding of the determinants of small-scale farmers' adaptation intent and adoption of adaptation strategies in semi-arid lowlands of Mwanga District. In this regard, adaptation was conceptualized as a two-step process encompassing farmers' perceptions that climate was changing and farmers' response to changes. Basing on a pragmatic philosophy, a cross-sectional sequential explanatory mixed methods research design was deployed. During the first step-process, categorical data were collected through administration of a closed-ended survey questionnaire to 328 household heads. Binary and proportional odds logistic regressions were run through IBM SPSS (Version 20) in order to analyze categorical data for testing nine (9) null hypotheses. Statistically significant results were established when p values were < 0.05 at 95% confidence intervals. During the second step-process, qualitative data were generated through focus group discussions with 30 participants, in-depth interviews with 16 key informants, and participant observations and subjected to iterative thematic content analysis. The findings revealed that income, village's geographical location, farming system, membership to farmer-based group, competitive price for produce, credit, age, education, and extension service positively influenced farmers' adoption of adaptation strategies while workforce and perceived risk of rain on crop yields negatively influenced farmers' adoption of adaptation strategies. Thus, it was concluded that farmers' adaptation intent and adoption of adaptation strategies in the study area were largely explained by objective adaptive capacity rather than cognitive factors. [ABSTRACT FROM AUTHOR]

The 6th Assessment of the Intergovernmental Panel on Climate Change projects increasing thermal‐associated morbidity and mortality under anthropogenically induced warming. Over 100 indices exist to quantify thermal stress, and among these, the Universal Thermal Climate Index (UTCI) was developed for regional investigations of thermal stress influences on human health. Although by definition a universal index, current applications are mainly limited to Europe. For regions such as Africa, use of the UTCI has been hampered by a lack of available requisite input variables from ground‐based meteorological stations. To overcome this, a gridded dataset, derived from ERA5 reanalysis, of UTCI equivalent temperatures was developed by the European Centre for Medium‐Range Weather Forecasts. Using this dataset for daily average, minimum and maximum UTCI values, we explore spatiotemporal patterns and changes thereof over annual, seasonal, and monthly scales across southern Africa from 1979 to 2021. Across these scales, 9 of 10 UTCI thermal stress categories were observed, ranging from very strong cold stress to extreme heat stress. Spatially, no thermal stress was most widespread for daily mean values, whereas for daily maximum (minimum) values there was a wider heat (cold) stress incidence, with frequent occurrences of moderate and strong heat stress (slight and moderate cold stress). Interannually, a clear El Niño–Southern Oscillation influence on thermal stress was evident during summer, with El Niño (La Niña) phases extending (reducing) heat stress incidences by up to 13.8% (2.9%). Over the study period, heat stress increased at statistically significant rates in many instances, with the strongest, most widespread increases, for the daily average and maximum (minimum), during spring (summer), averaging 0.28 and 0.29°C·decade−1 (0.23°C·decade−1); few regions experienced statistically significant decreasing trends. Overall, the trend results highlight regions vulnerable to significant thermal climate changes, and thus should be considered in decision‐making regarding outdoor activities. [ABSTRACT FROM AUTHOR]

The viability of food production by smallholder farmers in Tanzania's semi-arid regions is threatened by climate variability and change. This study's main goal was to comprehend the available options for farmers in Tanzania's Great Ruaha River Sub-Basin and the factors that influenced their decisions. We used both quantitative and qualitative data collection methods. Primary data were gathered through focus groups and household questionnaire surveys, while secondary data came from records collected by government organizations. A logistic regression analysis was undertaken so as to determine factors that influence smallholder farmers' perceptions and choice of response measures during dry years. Smallholder farmers mostly relied on their prior knowledge and locally accessible resources when developing their response strategies. Findings indicate that climate awareness, gender, age, education level, village location, wealth rank, and farmer experience are factors that have a substantial impact on farmers' decisions regarding choice of adaptation strategies to climate change. Therefore, decision-makers at all levels of government, from local authorities to the national level, should play a crucial role in improving adaptation strategies appropriate for a given climatic shock on the research area. The study suggests that GRRB farmers increase their knowledge and understanding of climate change. In order to successfully adapt to climate change, farmers should also work to create associations that will operate as a forum for knowledge exchange about indigenous farming techniques. [ABSTRACT FROM AUTHOR]

This study breaks away from traditional macroeconomic-data-based research that often overlooks the subjective experiences of communities and social groups in assessing their resilience to external stressors. Instead, we conducted a nuanced analysis of self-assessments provided by 364 household heads in the Nam Dong District, Thua Thien Hue Province, Vietnam, to gain a comprehensive understanding of household resilience. Our investigation focused on two upland communities—the Kinh majority and Co Tu ethnic minority households—evaluating their resilience levels in terms of the five livelihood capitals and identifying significant disparities among different ethnic and gender groups. Our findings reveal notable differences in livelihood resilience to climate change and variability among these groups, particularly for women, the poor, and ethnic minorities who exhibit lower resilience levels. This underscores the need for policies and programs designed to improve resilience capacity while taking into account these groups' cultural and social norms. We suggest focusing on improving financial, human, and social capitals to increase households' resilience to external shocks. Specifically, building resilience for disadvantaged groups must go hand in hand with promoting their overall well-being and alleviating poverty. Additionally, we recommend tailored training programs to raise awareness among households and strengthening institutional systems to enhance overall resilience. [ABSTRACT FROM AUTHOR]

Over the last few years, the occurrence and severity of climate change-induced floods in urban Kumasi, Ghana, have increased considerably, leading to devastating effects on both lives and properties. Yet, policy developments have often ignored the perspectives of residents who have experienced these floods. This study used a mixed-method approach including household surveys with 150 households and 5 key informant interviews to determine the drivers and coping mechanisms for floods in three selected communities in urban Kumasi, Ghana. Rainfall data (2001–2021) were analyzed using the Mann–Kendall trend test. A binary logistic regression was used to determine the enablers and barriers to coping mechanisms for floods. Results showed that the study respondents perceived changes in rainfall and floods through increasing amounts of rainfall, increasing duration of the rainy season, and increased incidences of floods. The perceptions of the respondents regarding rainfall changes were consistent with the analyzed rainfall data (2001–2021) which showed an increasing annual rainfall. A multiplicity of causes including poor design of drains, choked drains, and inadequate drainage infrastructure were reported by the study respondents. Destruction of properties, decreased economic productivity and soil erosion were reported as the major effects of floods. The respondents implemented various coping mechanisms including temporary migration and relying on family and friends to manage the adverse effects of floods. Findings indicated that access to climate information, access to household communication gadgets, age of respondents, and period of staying in the community significantly affected the coping mechanisms employed by the respondents (p < 0.05). Barriers impeding the implementation of these coping mechanisms reported by the study respondents included financial constraints, inadequate support from government and non-governmental institutions, and a lack of understanding of early warning systems. Accessibility to timely climate information should be prioritized to help people improve their information-sharing and decision-making processes in managing floods in urban Kumasi. [ABSTRACT FROM AUTHOR]

Consistent with global patterns, heatwaves have increased in frequency, duration and intensity across southern Africa; under enhanced global warming this is projected to worsen. Heatwaves have many adverse impacts, but in biologically unique mountainous regions, like the Maloti-Drakensberg region, impacts on ecological processes and hydrological cycles are particularly dire given their highly sensitive nature. Despite this, extreme temperature changes and interannual variability patterns remain understudied in mountainous regions, owing largely to remoteness and inaccessibility. This is especially true for the Maloti-Drakensberg region. Hence, using heatwave indices developed by the World Meteorological Organization (WMO) Expert Team on Sector-Specific Climate Indices (ET-SCI), we explored spatiotemporal patterns for the seasonal average number, length and magnitude of summer (November-March) heatwaves for 1979/80–2020/21 using the AgERA5 reanalysis. Although higher elevation regions typically experienced more frequent, longer-lasting heatwave events with higher interannual variability levels, on average the Maloti-Drakensberg region experienced 1.4 heatwave events, lasting for 6.5 days with a magnitude of 3.5°C2. Interannually, the El Niño-Southern Oscillation influenced variability of heatwave characteristics, with positive (negative) heatwave number and length anomalies predominantly detected during El Niño (La Niña) phases, while for heatwave magnitudes no clear pattern was evident. These heatwave aspects were predominantly characterised by increasing trends, however, few regions exhibited statistically significant trends. Overall, trends averaged 0.003 events/year, 0.03 days/year and 0.02°C2/year for the mean number, length and magnitude of heatwaves, respectively. These results highlight that the Drakensberg-Maloti region is vulnerable to an increasing frequency, duration and magnitude of heatwaves, however, implications thereof require further study. [ABSTRACT FROM AUTHOR]

The Pacific Walker circulation (PWC) significantly affects the global weather patterns, the distribution of mean precipitation, and modulates the rate of global warming. In this study, we review and compare 10 different indices measuring the strength of the PWC using data from the ERA5 reanalyses for the period 1951–2020. We propose a revised velocity potential index, while we also discuss two streamfunction indices. We show that the normalized PWC indices largely agree on the annual-mean strength of the PWC, with the highest correlations observed between indices that measure closely linked physical processes. The indices tend to disagree the most during the periods of strong El Niño. Therefore, the trends in PWC strength vary depending on the chosen time frame. While trends for 1981–2010 show PWC strengthening, trends for 1951–2020 are mostly neutral, and the recent trends (2000–2020) show (insignificant) weakening of the PWC. The results hint at the multidecadal variability in the PWC strength with a period of approximately 35 years, which would result in continued weakening of the PWC in the coming decade. [ABSTRACT FROM AUTHOR]

Non-climatic reasons, such as station replacement and changing the measurement device and calculation method, may make climate data unrepresentative of the actual variation of the regional climate. Data quality control and homogenization tests for climate data are critical. Thus, this study aims to evaluate the quality and homogeneity level of precipitation time series in arid and semi-arid climatic zones and specify the breakpoint in the datasets. The proposed methodology has been used to conduct arid and semi-arid representative case studies comprising 40 annual precipitation series for Iraq between 1979 and 2014. A Box-Cox transformation has been used to adjust the non-normally distributed datasets. Outliers have been censored by truncating extreme values. The results of the outliers indicate that they may be caused more by climate variability than by human-induced reasons. Homogeneity adjustments have been developed by applying these four homogeneity tests: Pettitt's test, the Standard Normal Homogeneity method, Buishand's test, and von Neumann's check. Approximately 40% of the series (i.e., 16 stations out of 40) were homogeneous. Each homogeneity test was evaluated separately, and non-homogeneous stations were identified. Then, the series was classified into three groups that were assigned the labels "useful", "doubtful", and "suspect". The results indicated that twenty-one stations were associated with the class 'suspect', three of the stations belonged to the class 'doubtful', and sixteen locations were within the class 'useful'. Furthermore, the data analysis indicated no influence of the outliers on the results of the homogeneity tests. Accordingly, the study recommends further research on homogeneity tests that can be applied without considering outlier tests for similar case studies. [ABSTRACT FROM AUTHOR]

The farmers' perceptions of climate change (CC) and variability in Okpuje were assessed and compared with historical climate data. They perceive an occurrence of change that affects their farm activities, but lack the scientific understanding of this change. While some do not know what causes the change, others attribute it to God's vengeance. The perceptions of rising temperature and delay in the onset of the rainy season are corroborated by the analysis of the climate data. The temperature is significantly rising and it increased at the rate of 0.14° C per decade between 1960 and 2019. The rainfall decreased at the rate of 8.5 mm per decade. The rainy season tends toward late-onset and early cessation dates. However, the perception of increasing rainfall in the area was not upheld by the trend analysis of the rainfall data. The difference might be due to high variability in rainfall in space and time. The high rainfall recorded lately might have posed difficulty for the human memory as closer events are remembered easier than distant events and hence can be unravelled via a scientific approach. Nevertheless, since perception shapes adaptation, the people's indigenous perceptions and experiences should form part of intervention measures and policies for CC adaptation to command greater participation and wider acceptance. Thus, farmers' perceptions provide vital information but would be more reliable if integrated with scientific data analysis for policy and decision-makers in CC science, implying that none of them should be relegated but integrated.

Climate change has the greatest negative impact on low-income countries, which burdens agricultural systems. Climate change and extreme weather events have caused Ethiopia’s agricultural production to decline and exacerbated food insecurity over the last few decades. This study investigates whether farmers’ awareness and perceptions of climate change play a role in climate change adaptation using climate-smart agricultural practices. To collect data, 385 households in Southern Ethiopia were sampled using a multistage sampling. A Heckman probit two-stage selection model was applied to investigate the factors influencing farmers’ perceptions to climate change and adaptation measures through adoption of climate-smart agriculture practices, complemented with key informant interviews and focused group discussions. The results indicated that most farmers (81.80%) perceived that the local climate is changing, with 71.9% reporting increased temperature and 53.15% reporting decreasing rainfall distribution. Therefore, farmers attempted to apply some adaptation practices, including soil and water conservation with biological measures, improved crop varieties, agroforestry, improved breeds, cut and carry system, controlled grazing, and residue incorporation. The empirical results revealed that farmers adaptation to climate change through adoptions of CSA practices was significantly influenced by education, family size, gender, landholding size, farming experience, access to climate information, training received, social membership, livestock ownership, farm income and extension services. The study found that farmers’ perceptions of climate change and variability were significantly influenced by their age, level of education, farming experience, and access to climate information, hence, the need to focus on enhancing the accuracy of weather information, strengthening extension services, and considering a gender-sensitive adaptation approach toward improving farmers’ knowledge and aspirations. Agricultural policies should support the efforts of farmers to increase the reliance on climate risk and alleviate farmers’ difficulties in adopting climate-smart agriculture practices.

Identifying hydro-meteorological trends is critical for assessing climate change and variability both at a basin and regional level. This study examined the long- and short-term trends from stream discharge, temperature, and rainfall data around the Rietspruit sub-basin in South Africa. The data were subjected to homogeneity testing before performing the trend tests. Inhomogeneity was widely detected in discharge data, hence no further analyses were performed on such data. Temperature and rainfall trends and their magnitudes at yearly, seasonal, and monthly time steps were identified after applying the non-parametric Mann-Kendall and Sen's slope estimator. The possible starting point of a trend was determined by performing the sequential Mann-Kendall test. This study revealed a combination of upward and downward trends in both temperature and rainfall data for the time steps under observation. For rainfall on an annual basis, there were no statistically significant monotonic trends detected, although non-significant downward trends were dominant. However, significant decreasing rainfall trends were observed in dry and low rainfall months, which were April, August, September, and November. In contrast, significant upward temperature trends were detected at the Vereeniging climate station at an annual scale and in October, November, spring, and winter. The findings are critical for climate risk management and reduction decisions for both near- and long-term timescales. HIGHLIGHTS The need to perform homogeneity tests to avoid erroneous conclusions is emphasised.; The study cautions the direct use of stream discharge data for climate analyses in urban areas.; Long-term data show no significant changes in rainfall while temperature is rising.; Findings will improve the understanding of hydro-meteorological trends specific to the Rietspruit sub-basin mainly due to temperature spatial variability.;

The Bale mountains ecoregion in Ethiopia provides a number of benefits for the local communities mainly in terms of water supply, power generation, tourism activity, and irrigation development. Notwithstanding, the ecoregion has been characterized primarily by recurring floods and droughts, as well as crop failure due to a variety of natural and human-activity-driven change factors. As a matter of fact, the purpose of this study would be to examine long-term changes and fluctuation in precipitation (PCP), maximum temperature (Tmax), and minimum temperature (Tmin) in the Bale mountains ecoregion using ensembles of three climate models with three representative concentration pathways (RCPs) scenarios from the coupled model inter-comparison project phase five (CMIP5) dataset. Statistical downscaling model (SDSM) was applied to project PCP, Tmax, and Tmin in the forthcoming period considering three RCPs: low emission (RCP2.6), intermediate (RCP4.5), and high emission (RCP8.5). SDSM's performance in capturing historical daily PCP, Tmax, and Tmin has been validated using standard statistical metrics such as coefficient of determination (R2), Nash Sutcliff efficiency (NSE), and root mean square error (RMSE). SDSM has the potential to generate a statistical transfer function between large-scale variables and local climate, allowing PCP, Tmax, and Tmin to be downscaled to a point scale for the ecoregion. The magnitude of mean yearly changes in PCP, Tmax, and Tmin were investigated throughout three thirty-year time slices, corresponding to the 2020s, 2050s, and 2080s. The Mann-Kendall non-parametric test was used to analyse trends in PCP, Tmax, and Tmin from 2011 to 2100. Inter-annual variability in PCP, Tmax, and Tmin were investigated for the aforementioned period, taking standard deviation into account under each RCP scenarios. The results reveal that mean annual PCP, Tmax, and Tmin are rising in all three time slices and in all three CMIP5 RCP scenarios as compared to the baseline scenario. Mean annual PCP is projected to increase within the uncertainty range of 6.68% to 17.93% (RCP2.6), 7.45% to 21.94% (RCP4.5), and 19.70% to 33.69% (RCP4.5) (RCP8.5). Tmax increases from 0.04°C to 0.24°C (RCP2.6), 0.05°C to 0.31°C (RCP4.5), and 0.04°C to 0.42°C (RCP8.5), whereas Tmin increases from 0.22°C to 0.52°C (RCP2.6), 0.23°C to 0.67°C (RCP4.5), and 0.26°C to 1.14°C (RCP8.5) (RCP8.5). For future projections at the end of the 21st century, the mean annual PCP, Tmax, and Tmin for all three analysed climate models and RCPs have shown a positive trend. The inter-annual variability of PCP, Tmax, and Tmin is higher in the RCP8.5 than RCP4.5 and RCP2.6 in all climate models. The findings clearly implied that prior understanding of long-term climate change and variability need to be addressed to plan effective and efficient mitigation strategies, as well as to maintain adequate quantity and quality of water supplies to the communities residing in the ecoregion. [ABSTRACT FROM AUTHOR]

Given rising concerns about climate change and development in Africa, this paper draws on Community Risk Assessment for mapping the risks of Fulani Herders to climate change in North-Western Ghana. Herder communities are seldom explored in climate change related studies although their livelihoods largely depend on the natural environment. Thus, a case study of the Fulani Herder Community of Kpongu in the Wa Municipality was conducted. The design employed Participatory Rural Appraisal instruments for data collection and analysis. The results reveal multiple indicators of climate change, including longer dry seasons and dry spells, shrinking sizes of water bodies, formation of iron pans on top soils, stunted growth of grass species, smaller grass stalks and less concentration of grasses. These have culminated into scarcity of fodder and water and increased distances of cattle herding under excruciating sunshine and temperatures in search of feed and water as an adaptive mechanism. The paper underscores that herder knowledge of climate change reveals a drying trend in climate and de-concentration in vegetation, especially grass species. The paper advocates climate change adaptation planning and policy attention to providing supplementary sources of water and feed in support of cattle herding and herder communities for climate change adaptation.

An increasingly volatile hydroclimate increases California's reliance on precipitation from atmospheric rivers (ARs) for water resources. Here, we simulate the AR that contributed to the Oroville Dam crisis in early February 2017 under global climate conditions representing preindustrial, present‐day, mid‐, and late‐21st century environments. This event consisted of two distinct AR pulses: the first snowy, westerly, and cool followed by a southwesterly and warm pulse resulting in copious rain‐on‐snow. We estimate that climate change to date results in ∼11% and ∼15% increase in precipitation over the Feather River Basin in Northern California for the first and second pulses, respectively, with late‐21st century enhancements upwards of ∼21% and ∼59%, respectively. Although both pulses were enhanced by the imposed climate changes, the thermodynamic response and subsequent precipitation increases were most substantial during the second pulse. The disparate changes demonstrated here highlight that not all ARs will respond similarly in a warmer world. Plain Language Summary: California's reliance on precipitation from atmospheric rivers is expected to increase as our climate warms. Understanding how climate change is impacting this increasingly dominant mode of precipitation is vitally important for water‐resource management throughout the state, across the North American West Coast, and for other similarly impacted regions. Our case study of an impactful atmospheric river from early February 2017 that contributed to the Oroville Dam crisis in Northern California, modeled under preindustrial, present‐day, mid‐, and late‐21st century unabatedly warming environments, demonstrates an overwhelming increase in precipitation throughout the event. This particular storm was comprised of two distinct pulses, and while both pulses of the storm are enhanced in the warmer future epochs, the estimated precipitation increases are disproportionately higher for the second pulse due to larger increases in temperature and moisture. Our results therefore suggest that not all atmospheric rivers are similarly affected by climate change and point to specific directions for relevant future research. Key Points: Climate change enhanced the precipitation associated with the February 2017 atmospheric river over Northern CaliforniaThe two distinct pulses comprising this event were differentially impactedA stronger thermodynamic response during the second pulse enabled a precipitation increase more than double that of the first pulse [ABSTRACT FROM AUTHOR]

Agro-pastoralists in the tropical semi-arid dryland areas of Sub-Saharan Africa (SSA) are significantly affected by climate change and variability. Agro-pastoral families are coping with production-related climatic risks through livelihood diversification to ensure food security. Data were collected from a sample of 411 agro-pastoralists across five districts in the semi-arid northern and central regions of Tanzania through a survey conducted between November 2017 and July 2018. Secondary data regarding crop yields and livestock populations for eight years from 2009 to 2017 were collected from the National Bureau of Statistics and the respective District offices. Results show that about three-quarters of the agro-pastoralists managed diversified crop and livestock portfolios with two or more crops and animal species. However, simulated crop yields reveal positive correlations. Construction of integrated portfolios that generate good returns at a modest risk can be achieved through strategic choices between high-return, high-risk and low-return, low-risk crop and livestock activities. Thus, the paper recommends costly long-term breeding and genotype improvement programs, strategically changing the make-up of the current crop and livestock portfolios, which appear to be an affordable and tailored solution for building risk resilience among agro-pastoral communities in the drylands.

Abstract An increasingly volatile hydroclimate increases California's reliance on precipitation from atmospheric rivers (ARs) for water resources. Here, we simulate the AR that contributed to the Oroville Dam crisis in early February 2017 under global climate conditions representing preindustrial, present‐day, mid‐, and late‐21st century environments. This event consisted of two distinct AR pulses: the first snowy, westerly, and cool followed by a southwesterly and warm pulse resulting in copious rain‐on‐snow. We estimate that climate change to date results in ∼11% and ∼15% increase in precipitation over the Feather River Basin in Northern California for the first and second pulses, respectively, with late‐21st century enhancements upwards of ∼21% and ∼59%, respectively. Although both pulses were enhanced by the imposed climate changes, the thermodynamic response and subsequent precipitation increases were most substantial during the second pulse. The disparate changes demonstrated here highlight that not all ARs will respond similarly in a warmer world.

Rainforests are continuously threatened by various anthropogenic activities. In addition, the ever-changing climate severely impacts the world’s rainforest cover. The consequences of these are paid back to human at a higher cost. Nevertheless, little or no significant attention was broadly given to this critical environmental issue. The World Heritage Sinharaja Rainforest in Sri Lanka is originating news on its forest cover due to human activities and changing climates. The scientific analysis is yet to be presented on the related issues. Therefore, this paper presents a comprehensive study on the possible impact on the Sinharaja Rainforest due to changing climate. Landsat images with measured rainfall data for 30 years were assessed and the relationships are presented. Results showcased that the built-up areas have drastically been increased over the last decade in the vicinity and the declared forest area. The authorities found the issues are serious and a sensitive task to negotiate in conserving the forest. The rainfall around the forest area has not shown significant trends over the years. Therefore, the health of forest cover was not severely impacted. Nevertheless, six cleared-up areas were found inside the Singaraja Rainforest under no human interactions. This can be due to a possible influence from the changing climate. This was justified by the temporal variation of Land Surface Temperature (LST) assessments over these six cleared-up areas. Therefore, the World Heritage rainforest is threatened due to human activities and under the changing climate change. Hence, the conservation of the Sinharaja Rainforest would be challenging in the future.

This study assesses the sustainability of adaptation strategies in rainfed agriculture to the effects of climate change and variability (CC & V) in Nyang'oro ward in Iringa District, Tanzania. The study involved a total of 138 respondents, of which 120 were household heads; whereby 82 respondents were from Nyang'oro village, and 38 were from Chamndindi village. The study employed a cross-sectional survey research design using both quantitative and qualitative research approaches. Primary data were collected through questionnaires, in-depth interviews and focus group discussions; and secondary data were collected through documentary review. Descriptive statistics were used to analyse quantitative data with the SPSS software, version 27; while qualitative data were analysed through content analysis. The study found that strategies used to adapt to the effects of CC & V in rainfed agriculture varied in terms of sustainability, such that some were sustainable while others were not. Sustainable adaptation strategies were used by a few households. As a result, crop production remains vulnerable to the effects of CC & V. The study concludes that the vulnerability of rainfed agriculture to the effects of CC & V in the study area is caused by the household heads' selection of strategies as few individuals used sustainable adaptation strategies. The study recommends the government and other stakeholders to put more efforts on capacity building on the use of sustainable strategies in the adaptation to the effects of CC & V on rainfed agriculture by smallholder farmers to ensure optimum and sustainable crop production in a changing climate. [ABSTRACT FROM AUTHOR]

This study seeks to provide an understanding of the effectiveness of adaptation strategies to climate change and variability in enhancing food security of rural smallholder farmers in Mvomero District. Food availability, measured by surplus food production, was the indicator of food security. Simple random sampling was used to get 373 respondents, while purposive sampling was used to get 38 key informants and 56 focus group participants. Household questionnaire interviews, in-depth interviews, focus group discussions, and a review of document were used to collect data. Descriptive and inferential statistics were used to analyse the quantitative data, while the qualitative data were analysed through content analysis. The results revealed that a majority of the respondents (27%) frequently practised intercropping as an adaptation strategy to climate change and variability. Others grew drought-resistant crops and early-maturing crop varieties, mixed farming, irrigation farming, and being involved in off-farm activities. Also, the majority (53%) had no surplus food production, indicating that they were food insecure. The results further revealed that the cultivation of drought-resistant crops and intercropping strategies had statistically significant (p<0.05) negative relationship with surplus food production, suggesting that respondents who were rarely, or not practising these strategies, were less likely to have surplus food production compared to respondents who were frequently practising them. Thus, growing of drought-resistant crops and intercropping are effective strategies in improving food security; suggesting that these strategies should be promoted to improve food security of rural smallholder farmers in Mvomero district. [ABSTRACT FROM AUTHOR]

The Pacific Walker circulation (PWC) significantly affects the global weather patterns, the distribution of mean precipitation, and modulates the rate of global warming. In this study, we review and compare 10 different indices measuring the strength of the PWC using data from the ERA5 reanalyses for the period 1951–2020. We propose a revised velocity potential index, while we also discuss two streamfunction indices. We show that the normalized PWC indices largely agree on the annual-mean strength of the PWC, with the highest correlations observed between indices that measure closely linked physical processes. The indices tend to disagree the most during the periods of strong El Niño. Therefore, the trends in PWC strength vary depending on the chosen time frame. While trends for 1981–2010 show PWC strengthening, trends for 1951–2020 are mostly neutral, and the recent trends (2000–2020) show (insignificant) weakening of the PWC. The results hint at the multidecadal variability in the PWC strength with a period of approximately 35 years, which would result in continued weakening of the PWC in the coming decade.

Non-climatic reasons, such as station replacement and changing the measurement device and calculation method, may make climate data unrepresentative of the actual variation of the regional climate. Data quality control and homogenization tests for climate data are critical. Thus, this study aims to evaluate the quality and homogeneity level of precipitation time series in arid and semi-arid climatic zones and specify the breakpoint in the datasets. The proposed methodology has been used to conduct arid and semi-arid representative case studies comprising 40 annual precipitation series for Iraq between 1979 and 2014. A Box-Cox transformation has been used to adjust the non-normally distributed datasets. Outliers have been censored by truncating extreme values. The results of the outliers indicate that they may be caused more by climate variability than by human-induced reasons. Homogeneity adjustments have been developed by applying these four homogeneity tests: Pettitt’s test, the Standard Normal Homogeneity method, Buishand’s test, and von Neumann’s check. Approximately 40% of the series (i.e., 16 stations out of 40) were homogeneous. Each homogeneity test was evaluated separately, and non-homogeneous stations were identified. Then, the series was classified into three groups that were assigned the labels “useful”, “doubtful”, and “suspect”. The results indicated that twenty-one stations were associated with the class ‘suspect’, three of the stations belonged to the class ‘doubtful’, and sixteen locations were within the class ‘useful’. Furthermore, the data analysis indicated no influence of the outliers on the results of the homogeneity tests. Accordingly, the study recommends further research on homogeneity tests that can be applied without considering outlier tests for similar case studies.

Climate change and variability remain a pressing global challenge directly and indirectly affecting human health. This has increased the demand for usable climate information for adaptation to climate related health challenges and for building effective response strategies. Climate services for health can help to enhance human well-being and in extreme cases can save human lives by reducing morbidity and mortality. Very little has been done and understood about how we can enhance climate services for health. The main aim of this perspective article is to bring empirical evidence, conceptual clarity and interdisciplinary approaches to policy makers and practitioners dealing with this crucial issue. The article explores the application of a holistic, broadly termed ‘systems’ approach to climate services for health in the context of adaptation and resilience. It uses illustrative examples from Ethiopia, Bhutan and Germany to demonstrate and elaborate the application and merits of the systems approach to emerging climate services for health. The systems approach improves conceptual thinking about climate services for health. In addition, it is a valuable analytical framework that unifies the diverse stakeholders involved in health adaptation and resilience planning, interventions and policy making. This perspective article fills in the existing gaps in scientific literature on the subject and enhances conceptualisation of climate services for health. It makes suggestions to improve understanding of climate services for health.

The direct and indirect effects of global emissions of black carbon (BC) on the evolution of Arctic climate has been well documented. The significance of within-Arctic emissions of BC is less certain. In light of this, an ensemble of scenarios are developed that simulate the hypothetical diversion of 75% of current and projected shipping traffic from the Suez Canal to the Northern Sea Route (NSR). This experiment shows that BC from ships results in a small change in climate forcing that does not influence the Arctic-wide trajectory of change. However, the shift in forcing from the Suez route to the NSR not only influences regional evolution of sea ice cover, but also results in regional feedbacks that in some locations amplify (e.g. Greenland Sea) and in other locations damp (e.g. Labrador Sea) the sea ice retreat under anthropogenic climate change. The primary mechanism underlying these regional effects is a shift in circulation rather than direct thermodynamic forcing. The most significant impacts are distal from the emissions sources, which is likely to have policy implications as the expansion of industrial and transportation activities into the Arctic is considered. [ABSTRACT FROM AUTHOR]

Climate change is affecting agricultural production and other aspects of life but only limited number of studies took interest in characterizing and projecting climate and its impact on crop production at local level. The threat to agricultural sector is more serious in Ethiopia, where climate is influenced by diverse topography and varying landscape features. This study was conducted in Welmera area to model the impacts of climate change on production of two faba bean (Vicia faba L.) varieties (Tums and Gora). Historical climate and crop yield data were obtained from the National Meteorological Agency of Ethiopia and Holeta Agricultural Research Center, respectively. Future climate data were downscaled by an average ensemble of four GCMs (BSS-CSM1-1, HadGEM2-ES, MIROC-ESM, NorESM1-M) in near- and mid-century (2030s and 2050s) under both RCP 4.5 and RCP 8.5. Rainfall by near-century will increase by up to 50% depending on the concentration pathway considered compared to the baseline period (1988–2017). The projected average rainfall total of belg season (FMAM) will increase by 88.17% under RCP 4.5 scenario and 95.38% under RCP 8.5 scenario in near-century. The future projection revealed that the highest mean monthly rainfall and temperature changes will occur in July (147.3 mm/month) and August (0.24 °C/month) under RCP8.5. However, in August and September mean monthly rainfall will decrease dramatically by 50.85 % and 31.05% from 2020 to 2079 under RCP 8.5 and RCP 4.5, respectively. The yield of Tumsa variety will decrease by up to 24.19% under RCP8.5 in mid-century. Gora variety will see an increase of yield by 18.24% under RCP 4.5 in mid-century and 28.03% under RCP 8.5 in near-century. Overall, the area will experience an increase and a decrease in faba bean yield for both varieties in the upcoming decades in the study area. Performance evaluation of the models showed that they were able to predict future yield faba bean varieties in the area with acceptable accuracy. Inconsistency of future climate variables and impact on fababean production underscores the need to develop location-specific adaptation strategies. Further studies that consider wider area could be necessary to better understand the impact of future climate on faba bean production in the study area and similar agroecologies in the country.

This study used multinomial logit regression to determine the factors that influence farmers’ choice of adaptation strategies to climate change and variability of farmers in Savelugu-Nanton district, Northern region of Ghana. A simple random sampling was used to select 180 farmers. The data was analysed using a Multinomial logit regression model. From the results, the level of climate change and variability awareness was high and the adaptation strategies identified were mixed cropping, change crop varieties, changing planting time/date, soil conservation techniques, increased irrigation, increased female livestock herd, and seasonal migration. Farmers confirmed empirically observations that climate change would lead to a reduction in crop production. Also, gender, age, education, household size, farming experience, access to extension, access to credit, access to mobile phone and perceived decreased rainfall influenced farmers’ choices of a particular adaptation strategy. The findings support and justified calls for education of farmers on climate change and variability.

Whilst the capability of climate services to reduce climate impacts is alluring, empirical evidence on how best to mainstream climate information services in Africa is lacking. This paper determines how climate information services have been incorporated into national policies by Anglophone West African states for building agricultural resilience and provides a detailed analysis of issues facing Ghanaian agricultural systems. The paper addresses the questions: (i) to what extent is climate change recognised as a threat to agricultural development in national climate facing policies of Anglophone West African states? (ii) to what extent have climate information services been incorporated into national and regional policy frameworks of Anglophone West African states for resilient agricultural systems? (iii) what are the key challenges in mainstreaming climate information services into national policies for resilient agricultural building in Ghana? The study employed thematic content analysis, multi-stakeholder workshops and expert interviews to understand climate discourses around climate services. Findings show that climate change is highlighted in national and regional level policies as a serious threat to socioeconomic development and agricultural productivity in West Africa. Anglophone West Africa countries are at various stages in establishing a National Framework for Climate Services to help guide future adaptation planning. This study shows that Anglophone West African states have not yet incorporated climate information services into strategic national and regional climate facing policies that are critical in shaping efforts aimed at managing climate risks. For the case of Ghana, the study reveals low awareness of climate change among policy-makers, human and institutional capacity constraints as some of the key factors militating against the mainstreaming of climate information services. Capacity building of policy makers and institutional strengthening are both vital for more effective mainstreaming of climate services across West Africa.

The study contributes to the development and use of effective climate services for sustainability in agriculture. Specifically, we assessed farming practices of a coastal smallholder farming community in Kilifi County (hereinafter Kilifi), Kenya, to identify barriers to climate services’ effective use. The smallholder farmers in Kilifi represent many smallholder farming communities in East Africa whose primary livelihood is rainfed agriculture. First, we carried out an analysis of historical and future rainfall patterns over Kilifi to determine the area’s climate patterns. We used a set of five descriptors of rainfall in Kilifi representing seasonal mean daily precipitation and annual precipitation intensity (SDII) and rainy days (R1MM) for the analysis. We assessed March-May (MAM), June-August (JJA), and October-December (OND) seasons, corresponding to the three planting seasons in Kilifi. Here, values for the five descriptors in the historical period (1977–2005) were compared with those in the future period (2071–2099) to determine the potential changes in the rainfall patterns. Results showed high year-to-year rainfall variability, relatively low mean daily rainfall per season, high variability within seasons, and uneven distribution of rainfall within seasons. MAM, OND, and SDII showed an increase in the future period while JJA recorded a considerable reduction in rainfall. No discernible changes were recorded for R1MM. Results from a social survey showed that the smallholder farmers in Kilifi were indeed experiencing climate variability and change. While some effort had been made towards building the farmers’ adaptive capacity, the interventions were reported to be too sporadic and inadequately coordinated to achieve meaningful results. Through Focus Group Discussions (FGDs), Key-Informant Interviews (KIIs), and literature review, an innovative climate change adaptation model was developed. Thus, this study provides a preliminary framework for strengthening an enabling environment for climate services for agricultural productivity and sustainable development in a changing climate.

The ability of smallholder farmers to utilise seasonal climate forecast (SCF) information in farm planning to reflect anticipated climate is a precursor to improved farm management. However, the integration of SCF by smallholder farmers into farm planning has been poor, partly because of the lack of forecast skill, lack of communication and inability to see the relevance of the SCFs for specific farming decisions. The relevance of seasonal climate forecasting in farming decisions can be enhanced through improved understanding of SCF from the smallholder farmers’ perspective. Studies that have been done of how smallholder farmers understand SCF and how the available SCFs influence smallholder farmers’ decisions are limited. Therefore, the objective of this paper was to review how smallholder farmers make decisions on farming practices based on SCFs and the challenges and opportunities thereof. The review shows that the majority of smallholder farmers in Africa make use of either scientific or indigenous knowledge climate forecasts and, in some cases, a combination of both. There are mixed results in the area of evaluating benefits of SCFs in decision-making and farm production. In some cases, the outcomes are positive, whereas in others they are difficult to quantify. Thus, the integration of SCFs into smallholder farmers’ decision-making is still a challenge. We recommend that significant work must be done to improve climate forecasts in terms of format, and spatial and temporal context in order for them to be more useful in influencing decision-making by smallholder farmers. Significance: • At the farm level, making the right decisions at the right time is rendered even more difficult in light of the increasing frequency of extreme weather patterns. • The threat of climate change makes accurate seasonal climate forecasting essential for African smallholder farmers. • Technological, social and interdisciplinary issues, communication and scale are some key challenges which impact the utility and uptake of SCFs in rural smallholder farms. • The integration of both scientific and indigenous knowledge forecasts is an opportunity for further exploration.

This study synthesizes the observed trends and projected changes in the Intertropical Convergence Zones (ITCZs). Under future warming, the seasonal ITCZs are projected to shift equatorward, widen, and weaken. The equatorward‐shifted seasonal ITCZs cause a squeeze of the annual‐mean zonal‐mean tropical ascent. Over 1979–2014, however, the seasonal ITCZs have shifted poleward in South Pacific and generally narrowed and strengthened. The observed annual‐mean zonal‐mean changes are largely opposite to the future squeeze. Such contrasting ITCZ changes are attributed to the distinct tropical warming patterns. Specifically, the equatorial Pacific has cooled following a phase change in the Pacific Decadal Oscillation (PDO) but will warm more than the tropics in future. The ITCZ response to tropical warming pattern is consistent with thermodynamic/energetic theories and demonstrated through SST‐forced experiments. In the coming decades, a positive PDO can act jointly with anthropogenically forced equatorial warming, leading to substantial ITCZ changes that are distinct from recent trends. Key Points: Under anthropogenically forced enhanced equatorial warming, the seasonal ITCZs are projected to shift equatorward, widen, and weakenOver 1979–2014 with a positive‐to‐negative PDO phase change, the seasonal ITCZs have shifted poleward in SH and sharpened generallyIn the coming decades, a positive PDO can enhance the equatorial warming and amplify the anthropogenically forced ITCZ changes [ABSTRACT FROM AUTHOR]

In this paper, a systematic literature review was conducted to synthesize understanding on farmers' perception on climate change. Farmers' perception of climate change is conceptualized as comprising of three dimensions—first, as farmers' "awareness"; second, "conceptual understanding"; and third, the "experience" of climate change. The review included 162 papers published during the period January 2000 to July 2019. The highest number of studies was conducted in Africa, followed by Asia. A large majority of farmers report being aware of climate change. However, only a few studies elicit the difference between climate variability and climate change from farmers. A negligible number of studies attempt to identify the role of agricultural activities in greenhouse gas emissions and climate change. Furthermore, authors compare farmers' perception with meteorological evidence, which is more aligned in terms of change in "temperature" rather than "precipitation." The insights from the review provide guidance on conceptualization and operationalization of the variable "farmers' perception of climate change" for future studies. [ABSTRACT FROM AUTHOR]

Over the years, climate change and variability have led to a substantial decline in agricultural productivity in both developing and developed countries. Small-scale farmers are particularly at risk. The responses of farmers to climate change and variability are often dependent on their perceptions of climate change. Therefore, it is important to understand the nature of adaptation strategies that are feasible and practised at farm level. Despite this need, in some developing countries such as Botswana, there is a dearth of studies that use mixed research methods to critically analyse farmers' perceptions of climate change and their adaptation strategies. This study uses empirical data collected from farming households in the Ngamiland East region of Botswana to (i) analyse the perceptions of small-scale farmers regarding climate change, (ii) analyse small-scale farmers' adaptation strategies to climate change, and (iii) determine constraints faced by farmers in adapting to climate change and variability. The results show that there is a direct relationship between the farmers' adaptation strategies and education. Unlike findings from other studies, the results of the study show that there is no significant relationship between gender and farmers' adaptation strategies. The results verify that there is high heterogeneity characterising the case studies, making adaptation studies case-specific. Farmers in the Ngamiland region are faced with several challenges in their attempt to adapt to climate change. Chief among the constraints is the lack of financial resources and lack of appropriate skills. The government should empower the farmers through provision of subsidies and skills training. [ABSTRACT FROM AUTHOR]

The ability of smallholder farmers to utilise seasonal climate forecast (SCF) information in farm planning to reflect anticipated climate is a precursor to improved farm management. However, the integration of SCF by smallholder farmers into farm planning has been poor, partly because of the lack of forecast skill, lack of communication and inability to see the relevance of the SCFs for specific farming decisions. The relevance of seasonal climate forecasting in farming decisions can be enhanced through improved understanding of SCF from the smallholder farmers’ perspective. Studies that have been done of how smallholder farmers understand SCF and how the available SCFs influence smallholder farmers’ decisions are limited. Therefore, the objective of this paper was to review how smallholder farmers make decisions on farming practices based on SCFs and the challenges and opportunities thereof. The review shows that the majority of smallholder farmers in Africa make use of either scientific or indigenous knowledge climate forecasts and, in some cases, a combination of both. There are mixed results in the area of evaluating benefits of SCFs in decision-making and farm production. In some cases, the outcomes are positive, whereas in others they are difficult to quantify. Thus, the integration of SCFs into smallholder farmers’ decision-making is still a challenge. We recommend that significant work must be done to improve climate forecasts in terms of format, and spatial and temporal context in order for them to be more useful in influencing decision-making by smallholder farmers. [ABSTRACT FROM AUTHOR]