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This paper examines the impact of extreme rainfall shocks on the performance in test scores of students living near at-risk urban areas in Brazil.

To identify the causal effect, we consider the exogenous variation of rainfall at the municipal level conditioned on the distance from the school to risk areas and the rainfall intensity in the school months.

The results suggest that extreme precipitation shocks, defined as a shock of at least three months of high-intensity rainfall, have an adverse impact on both math and language performance. Through a heterogeneous effects analysis, we find that the impact varies by student gender, with girls being more affected. In addition, among students who study near at-risk areas, those with better previous school performance and higher socioeconomic status are more negatively affected.

Our results suggest that extreme weather events can increase the differences in human capital accumulation between the population living near risk areas and those living more distant from these areas.

Three Coupled Model Intercomparison Project Phase 5 models involved in the G4 experiment of the Geoengineering Model Inter-comparison Project (GeoMIP) project were used to investigate the impact of stratospheric aerosol injection (SAI) on the mean surface air temperature and precipitation extremes in Africa.

This impact was examined under G4 and Representative Concentration Pathway (RCP) 4.5 scenarios on the total precipitation, the number of rainy days (RR1) and of days with heavy rainfall (R20 mm), the rainfall intensity (SDII), the maximum length of consecutive wet (CWD) and dry (CDD) days and on the maximum rainfall in five consecutive days (Rx5day) across four regions: Western Africa (WAF), Eastern Africa (EAF), Northern Africa and Southern Africa (SAF).

During the 50 years (2020–2069) of SAI, mean continental warming is −0.40°C lower in G4 than under RCP4.5. During the post-injection period (2070–2090), the temperature continues to increase, but at a lower rate (−0.19°C) than in RCP4.5. During SAI, annual rainfall in G4 is significantly greater than in RCP4.5 over the high latitudes (especially over SAF) and lower over the tropics. The termination of SAI leads to a significant increase of rainfall over Sahel and EAF and a decrease over SAF and Guinea Coast (WAF).

Compared to RCP4.5, SAI will contribute to reducing significantly regional warming but with a significant decrease of rainfall in the tropics where rainfed agriculture account for a large part of the economies. After the SAI period, the risk of drought over the extratropical regions (especially in SAF) will be mitigated, while the risk of floods will be exacerbated in the Central Sahel.

To meet the Paris Agreement, African countries will implement mitigation measures to contribute to keep the surface air temperature below 2°C. Geoengineering with SAI is suggested as an option to meet this challenge, but its implication on the African climate system needs a deep investigation in the aim to understand the impacts on temperature and precipitation extremes. To the best of the authors’ knowledge, this study is the first to investigate the potential impact of SAI using the G4 experiment of GeoMIP on temperature and precipitation extremes of the African continent.

The main aim of this study is to investigate the impact of climate change and water salinity on farmer’s income risk with future outlook mitigation. Salinity and climate change are a threat to agricultural productivity worldwide. However, the combined effects of climate change and salinity impacts on farmers' income are not well understood, particularly in developing countries.

The response-yield function and general maximum entropy methods were used to predict the impact of temperature, precipitation and salinity on crop yield. The target minimization of total absolute deviations (MOTAD)-positive mathematical programming model was used to simulate the impact of climate change and salinity on socioeconomic and environmental indicators. In the end, a multicriteria decision-making model was used, aiming at the selection of suitable climate scenarios.

The results revealed that precipitation shows a significantly decreasing trend, while temperature and groundwater salinity (EC) illustrate a significantly increasing trend. Climate change and EC negatively impact the farmer's income and water shadow prices. Maximum reduction in income and water shadow prices was observed for A2 scenario (−12.4% and 19.4%) during 2050. The environmental index was the most important, with priority of 43.4% compared to socioeconomic indicators. Subindex amount of water used was also significant in study area, with 28.1% priority. The technique for order preference by similarity to ideal solution ranking system found that B1 was the best climatic scenario for adopting climate change adaptation in the research region.

In this study, farmers' income threats were assessed with the aspects of different climate scenario (A1, A1B and B1) over the horizons of 2030, 2040 and 2050 and three different indicators (economic, social and environmental) in Northwestern region of Pakistan. Only in arid and semiarid regions has climate change raised temperature and reduced rainfall, which are preliminary symptoms of growing salinity.

The purpose of this paper is to explore the impact of supply capacity constraint, water delivery loss and fairness concern on the operational decisions/efficiency of the IBWT supply chain under the random precipitation.

Two game-theoretic decision models for the IBWT supply chain coordination considering water delivery loss without/with fairness concern under the supply capacity constraint and random precipitation are developed, analyzed and compared. On this basis, the corresponding numerical analyses are conducted and compared to derive the corresponding management insights and policy implications.

The research results indicate that the two-part tariff contract could effectively coordinate the IBWT supply chain and achieve operational performance improvement; the binding supply capacity constraint makes the water capacity to be allocated among IBWT distributors in accordance with fair shortage allocation rule and reduces the profit (or utility) of the IBWT supply chain and its members; the existence of fairness concern reduces the utility of the IBWT supply chain and its members; a lower precipitation utilization factor in the case with non-binding capacity constraint is beneficial for improving the profit/utility of the IBWT supply chain while a higher precipitation utilization factor in the case with binding capacity constraint is beneficial for improving the profit/utility of the IBWT supply chain; and reducing the water delivery loss rate, the mainline transfer cost, the branch-line transfer cost, the holding cost and the shortage cost and setting a higher retail price are beneficial for improving the profit/utility of the IBWT supply chain.

Two innovative coordination decision models under random precipitation are developed, analyzed and compared through game-theoretic approaches to investigate the impact of supply capacity constraint, water delivery loss and fairness concern on the operational decisions/efficiency of the IBWT supply chain, which have enhanced the optimization decision theory for the operations management of IBWT projects and provided a better decision support for the IBWT stakeholders to make better operations strategies.

The purpose of this study is to examine the relative importance of climate normals (average long-term temperature and precipitation) in explaining net farm revenue per hectare (NRh) for supplementary irrigated and rainfed cocoa farms in Nigeria.

NRh was estimated for 280 cocoa farmers sampled across seven Nigerian states. It was regressed on climate, household socio-economic characteristics and other control variables by using a Ricardian analytical framework. Marginal calculations were used to isolate the effects of climate change (CC) on cocoa farm revenues under supplementary irrigated and rainfed conditions. Future impacts of CC were simulated using Six CORDEX regional climate model (RCM) ensemble between 2036-2065 and 2071-2100.

Results indicate high sensitivity of NRh to Nigerian climate normals depending on whether farms use supplementary irrigation. Average annual temperature increases and precipitation decreases are associated with NRh losses for rainfed farms and gains for supplementary irrigated cocoa farms. Projections of future CC impacts suggest a wide range of NRh outcomes on supplementary irrigated and rainfed farm revenues, demonstrating the importance of irrigation as an effective adaptation strategy in Nigeria.

This paper uses novel data sets for simulating future CC impacts on land values in Nigeria. CORDEX data constitute the most comprehensive RCMs projections available for Africa.

Heavy rainfall is one of the main causes of the degradation of historic rammed Earth architecture. For this reason, ensuring the conservation thereof entails understanding the factors involved in these risk situations. The purpose of this study is to research three past events in which rainfall caused damage and collapse to historic rammed Earth fortifications in Andalusia in order to analyse whether it is possible to prevent similar situations from occurring in the future.

The three case studies analysed are located in the south of Spain and occurred between 2017 and 2021. The hazard presented by rainfall within this context has been obtained from Art-Risk 3.0 (Registration No. 201999906530090). The vulnerability of the structures has been assessed with the Art-Risk 1 model. To characterise the strength, duration, and intensity of precipitation events, a workflow for the statistical use of GPM and GSMaP satellite resources has been designed, validated, and tested. The strength of the winds has been evaluated from data from ground-based weather stations.

GSMaP precipitation data is very similar to data from ground-based weather stations. Regarding the three risk events analysed, although they occurred in areas with a torrential rainfall hazard, the damage was caused by non-intense rainfall that did not exceed 5 mm/hour. The continuation of the rainfall for several days and the poor state of conservation of the walls seem to be the factors that triggered the collapses that fundamentally affected the restoration mortars.

A workflow applied to vulnerability and hazard analysis is presented, which validates the large-scale use of satellite images for past and present monitoring of heritage structure risk situations due to rain.

The Sertão, located in the Northeastern region of Brazil, is the most populous semi-arid region in the world. The region also faces the highest rates of poverty, food insecurity and climate risks in this country. Basic economic activities, such as extensive livestock and dairy farming, tend to be mainly affected by the increasing temperatures and recurrent droughts taking place in the past decades. This paper aims to analyze farmers’ responses to climatic variability in the Sertão.

Analyses are based on farm-level data of the Agricultural Census 2006 and on historical climate data gathered by meteorological stations. The climate impacts and the effectiveness of adaptive strategies are compared between three groups of farms, which discriminate different levels of social and environmental vulnerability. Four production functions are modeled (milk, cattle, goat and sheep) accounting for sample selectivity bias.

In response to increasing temperatures, farmers tend to shift their activities mainly to cattle and dairy farming. But the overall productivity tends to reduce with the recurrence of droughts. Decreasing precipitation affects mainly the production of milk of smallholder family farmers and the cattle herd of non-family farmers.

Analyses do not account for short- and medium-run productive impacts of extreme droughts, which usually have devastating socioeconomic effects in the region.

Smallholder family farmers are the most vulnerable group who deserve more social and technical intervention, as they lack basic social and technological resources that can greatly improve their productivities and overcome the impacts of decreasing precipitation.

In this study, the authors examine the push and pull effects of extreme weather events on migration among governorates in Egypt.

To estimate the effect of extreme weather events on internal migration, the authors use migration gravity models and data from the 1996 and 2006 Population and Housing Censuses. The authors measure weather extremes by the number of months in the past 36 months with temperatures or precipitation of a governorate below the 5th percentile and above the 95th percentile of the distribution of monthly temperatures or precipitation of the corresponding governorate during the period 1900–2006.

This study’s results suggest that high temperatures in the origin area act as a push factor. High-temperature extremes have a positive effect on out-migration. A 1% increase in the number of months with high-temperature extremes in the original governorate results in a 0.1% increase in the number of out-migrants.

The study suggests that people may respond to weather extremes through migration. However, climate migrants in Egypt may encounter several significant risks that authorities must address.

This study is one of the first attempts to measure the push and pull effect of weather extremes on migration in Egypt.

The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess Plateau has undergone great changes. This paper aims to clarify the response mechanisms of vegetation to climate change, to provide support for the restoration and environmental treatment of vegetation on the Loess Plateau.

The Savitsky–Golay (S-G) filtering algorithm was used to reconstruct time series of moderate resolution imaging spectroradiometer (MODIS) 13A2 data. Combined with trend analysis and partial correlation analysis, the influence of climate change on the phenology and enhanced vegetation index (EVI) during the growing season was described.

The S-G filtering algorithm is suitable for EVI reconstruction of the Loess Plateau. The date of start of growing season was found to gradually later along the Southeast–Northwest direction, whereas the date of the end of the growing season showed the opposite pattern and the length of the growing season gradually shortened. Vegetation EVI values decreased gradually from Southeast to Northwest. Vegetation changed significantly and showed clear differentiation according to different topographic factors. Vegetation correlated positively with precipitation from April to July and with temperature from August to November.

This study provides technical support for ecological environmental assessment, restoration of regional vegetation coverage and environmental governance of the Loess Plateau over the past two decades. It also provides theoretical support for the prediction model of vegetation phenology changes based on remote sensing data.

This paper aims to study the temporal and spatial variation of vegetation and the influence of climate change on vegetation coverage in the Yellow River basin, China. The current study aimed to evaluate the role of a series of government-led environmental control projects in restoring the ecological environment of the Yellow River basin.

This paper uses unary linear regression, Mann–Kendall and wavelet analyses to study the spatial–temporal variations of vegetation and the response to climate changes in the Yellow River, China.

The results showed that for the past 17 years, not only the mean annual increase rate of the Normalized Difference Vegetation Index (NDVI) was 0.0059/a, but the spatial heterogeneity also yields significant results. The vegetation growth in the southeastern region was significantly better than that in the northwestern region. The variation period of the NDVI in the study area significantly shortened, and the most obvious oscillation period was half a year, with two peaks in one year. In addition, there are positive and negative effects of human activities on the change of vegetation cover of the Loess Plateau. The project of transforming cultivated land to forest and grassland promotes the increase of vegetation cover of the Loess plateau. Unfortunately, the regional urbanization and industrialization proliferated, and the overloading of grazing, deforestation, over-reclamation, and the exploitation and development of the energy area in the grassland region led to the reduction of the NDVI. Fortunately, the positive effects outweigh the negative ones.

This paper provides a comprehensive insight to analysis of the vegetation change and the responses of vegetation to climate change, with special reference to make the planning policy of ecological restoration. This paper argues that ecological restoration should be strengthened in areas with annual precipitation less than 450 mm.