Climate volatility and poverty vulnerability in Tanzania

Climate volatility could change in the future, with important implications for agricultural productivity. For Tanzania, where food production and prices are sensitive to climate, changes in climate volatility could have severe implications for poverty. This study uses climate model projections, statistical crop models, and general equilibrium economic simulations to determine how the vulnerability of Tanzania's population to impoverishment by climate variability could change between the late 20th Century and the early 21st Century. Under current climate volatility, there is potential for a range of possible poverty outcomes, although in the most extreme of circumstances, poverty could increase by as many as 650,000 people due to an extreme interannual decline in grain yield. However, scenarios of future climate from multiple climate models indicate no consensus on future changes in temperature or rainfall volatility, so that either an increase or decrease is plausible. Scenarios with the largest increases in climate volatility are projected to render Tanzanians increasingly vulnerable to poverty through impacts on staple grains production in agriculture, with as many as 90,000 additional people entering poverty on average. Under the scenario where precipitation volatility decreases, poverty vulnerability decreases, highlighting the possibility of climate changes that oppose the ensemble mean, leading to poverty impacts of opposite sign. The results suggest that evaluating potential changes in volatility and not just the mean climate state may be important for analyzing the poverty implications of climate change.     

近百年武汉市主汛期降水特征分析

本文对武汉市1906-2000年主汛期（6-8月）的降水量资料进行了分析。结果表明，近百年来武汉市有两个旱涝事件多发时段，出现在30年代中期以前和60年代以后，主汛期降水量气候基本态在20世纪经历了高、低、高、低、高5个阶段，目前处于高基本态高变率时段，还利用小波变换揭示出了武汉市近百年来主汛期降水的多时间尺度特点，分析了其主要周期振荡和突变特征，指出武汉市主汛期降水存在40年、25年、10年、4-7年左右的周期振荡，并由降水的周期性推知本世纪初武汉市汛期将进入下一个少雨时段。     

长江中下游气候的长期变化及基本态特征

研究了1885年以来，我国长江中下游四季及年降水量，四季及年平均气温的长期变化，指出长江中下游四个季及年的总降水量（平均气温）都是正的趋势，但有季节的差异，春季是升温同时增雨最显著的季节，还研究了我国长江中下游降水与气温的气候基本态及气候变率的特征及时间演变规律，指出，60年代以后夏季气温变化的异常程度几乎比以前大了一倍，在冬季，近期在暖背景下的冬季气温变率变小的特征表明长江中下游可能出现持续发暖冬特征，还指出，80年代后我国的长江中下游存季降水处于高基本态与高气候变率时段，应注意频繁发生的夏季洪涝灾害，研究还指出，长江中下游夏季降水与印度季风的气候基本态反相关密切，印度季风及东亚夏季风与长江中下游夏季气温变化在各种尺度上有明显的正相关。     

Adaptation to climate change in Africa: Challenges and opportunities identified from Ethiopia

Africa is widely held to be highly vulnerable to future climate change and Ethiopia is often cited as one of the most extreme examples. With this in mind we seek to identify entry points to integrate short- to medium-term climate risk reduction within development activities in Africa, drawing from experiences in Ethiopia. To achieve this we employ a range of data and methods. We examine the changing nature of climate risks using analysis of recent climate variability, future climate scenarios and their secondary impacts. We assess the effects of climate variability on agricultural production and national GDP. Entry points and knowledge gaps in relation to mainstreaming climate risks in Ethiopia are identified using the Government's plan for poverty reduction. We end with a case study incorporating climate risks through drought insurance within the current social protection programme in Ethiopia, which provides support to 8.3 million people.Rainfall behaviour in Ethiopia shows no marked emergent changes and future climate projections show continued warming but very mixed patterns of rainfall change. Economic analysis highlights sensitivities within the economy to large-scale drought, however, while the effects are clear in major drought years in other years the relationship is weak. For social protection fairly small positive and negative effects on the number of recipients and frequency of cash payments during drought occur under the extreme range of climate model rainfall projections (2020s).Our analysis highlights several important challenges and opportunities for addressing climate risks. Challenges primarily relate to the large uncertainties in climate projections for parts of Africa, a weak evidence base of complex, often non-deterministic, climate-society interactions and institutional issues. Opportunities relate to the potential for low-regrets measures to reduce vulnerability to current climate variability which can be integrated with relatively modest effort within a shift in Africa from a disaster-focused view of climate to a long-term perspective that emphasises livelihood security and vulnerability reduction.     

Social risk perceptions of climate change: A case study of farmers and agricultural advisors in northern California

Crop and livestock farmers must respond to climate change, including a range of physical and cultural impacts and risks. In rural northern California, farmers face extreme drought and catastrophic wildfires with increasing frequency. I draw on an extended case study of farmers and agricultural advisors in Siskiyou County to understand how rural agriculturalists perceive risks when navigating climate change discourses. While farmers are changing their management practices in response to the physical effects of climate change, many perceive substantial social risks within their communities if they align themselves publicly with climate change beliefs or actions. Perceived social consequences included loss of access to the benefits of membership in formal and informal farming groups. Efforts focused on educating or convincing farmers of climate science may, in some contexts, increase rather than decrease the perceived social risks of climate action. The framing of climate policies, programs, and practices – especially by public agricultural advisors like Cooperative Extension Advisors and local USDA staff (e.g., Farm Service Agency) – is important not only for increasing farmer participation, but also for reducing perceived social risks associated with climate change. Interventions that focus on livelihood impacts and validate existing land stewardship-oriented values have more potential to increase the pace and scale of climate change mitigation and adaptation in agriculture.     

Socioeconomic geography of climate change views in Europe

Climate change views have their socioeconomic foundations but also specific geographies. In merging these perspectives, this analysis uses ESS Round 8 data from 23 European countries to examine whether climate change scepticism and concern, pro-environmental personal norm and a willingness to engage in energy-saving behaviour exhibit, first, urban–rural and/or regional differences, and second, if these attitudes can be explained at individual level by socioeconomic position and wellbeing resources. We find that climate change scepticism and concern do exhibit urban–rural differences, where living in a country village is associated with greater climate scepticism and lower concern compared to living in a big city. Also, higher climate change concern and pro-environmental norms are associated with living in a region with constant population growth. These geographical differences are independent of individual-level socioeconomic attributes as well as one’s political orientation. Additionally, the results show that both climate change attitudes and reporting energy-saving behaviour are strongly stratified by level of education and reveal that those in lower income deciles feel less pro-environmental norm but nonetheless report greater engagement with energy-saving behaviour. In sum, the results highlight that climate change mitigation is not a uniform project either spatially or within certain socioeconomic strata. Hence, our results suggest that socioeconomic disadvantage (belonging to the lowest education and income levels) and spatial marginalisation (living in more rural surroundings and declining regions) should be better acknowledged when reworking climate change and environmental policies in the EU.     

Natural variability of summer rainfall over China in HadCM3

Summer rainfall over China has shown decadal variability in the past half century, which has resulted in major north–south shifts in rainfall with important implications for flooding and water resource management. This study has demonstrated how multi-century climate model simulations can be used to explore interdecadal natural variability in the climate system in order to address important questions around recent changes in Chinese summer rainfall, and whether or not anthropogenic climate change is playing a role. Using a 1,000-year simulation of HadCM3 with constant pre-industrial external forcing, the dominant modes of total and interdecadal natural variability in Chinese summer rainfall have been analysed. It has been shown that these modes are comparable in magnitude and in temporal and spatial characteristics to those observed in the latter part of the twentieth century. However, despite 1,000 years of model simulation it has not been possible to demonstrate that these modes are related to similar variations in the global circulation and surface temperature forcing occurring during the latter half of the twentieth century. This may be in part due to model biases. Consequently, recent changes in the spatial distribution of Chinese summer rainfall cannot be attributed solely to natural variability, nor has it been possible to eliminate the likelihood that anthropogenic climate change has been the driving factor. It is more likely that both play a role.     

Seasonal variability of rainfall extremes

Monthly rainfall extremes have been analyzed for three stations in Southern Ontario. The double exponential probability distribution was fitted to the extreme values for each month considered, each duration selected, and sets of annual extremes. A station‐year approach yielded monthly and annual extreme value distributions for the lumped region of Southern Ontario. The analysis has revealed a pronounced seasonal pattern in the rainfall extremes – the amount of rain expected with a selected probability of occurrence during the summer being considerably greater than the rainfall that might be expected to be exceeded at the same probability level during the spring or fall. The extent of the seasonal variability was found also to vary with duration. The implications of the variability are seen to be significant for the estimation of the magnitude and frequency of floods.     

The impacts of the Indian summer rainfall on North China summer rainfall

Previous studies have indicated a connection between interannual variations of the Indian and North China summer rainfall. An atmospheric circulation wave pattern over the mid-latitude Asia plays an important role in the connection. The present study compares the influence of the above-normal and below-normal Indian summer rainfall on the North China summer rainfall variations. Composite analysis shows that the mid-latitude Asian atmospheric circulation and the North China rainfall anomalies during summer tend to be anti-symmetric in above-normal and below-normal Indian rainfall years. Analysis indicates that the Indian-North China summer rainfall relation tends to be stronger when larger Indian rainfall anomaly occurs during a higher mean rainfall period. The observed long-term change in the Indian-North China summer rainfall relationship cannot be explained by the impact of the El Niño-Southern Oscillation (ENSO). The present study evaluates the Indian-North China summer rainfall relationship in climate models. Analysis shows that the Indian-North China summer rainfall relationship differs largely among different climate models and among different simulations of a specific model. The relationship also displays obvious temporal variations in both individual and ensemble mean model simulations. This suggests an important role of the atmospheric internal variability in the change of the Indian-North China summer rainfall relationship.     

Climatic variability and changing reproductive goals in Sub-Saharan Africa

Using 40 rounds of Demographic and Health Survey data from 18 sub-Saharan African countries, linked to high-resolution historical climate records, we analyze the relationship between climatic variability and fertility goals among reproductive-aged women. We find that, overall, women exposed to above-average temperatures report lower ideal family size and reduced probability of desiring a first or additional child. Results indicate that exposure to precipitation anomalies during the 12 months prior to the DHS survey is associated with a significant reduction in ideal family size, but longer 60-month spells of above-average precipitation are associated with increases in ideal family size. Effects of unusual precipitation are null for women’s fertility preferences at both shorter- and longer-term periods. Additional analyses show that this association varies across sub-populations defined by parity, education, residence in rural or urban areas, and region. In general, our results suggest that women exposed to adverse environmental conditions—namely abnormally hot or dry spells—will reduce their ideal family size and their preferences for having another child. In some cases, however, fertility goals may also decline during spells of favorable environmental conditions, possibly due to increased labor demands among women and their spouses. One implication of the observed links between climate variability and reproductive goals is that policymakers concerned with climate adaptation should work to ensure women have access to the necessary family planning resources needed to realize dynamic reproductive goals in a changing climate.     

Climate variability and inter-provincial migration in South America, 1970–2011

We examine the effect of climate variability on human migration in South America. Our analyses draw on over 21 million observations of adults aged 15–40 from 25 censuses conducted in eight South American countries. Addressing limitations associated with methodological diversity among prior studies, we apply a common analytic approach and uniform definitions of migration and climate across all countries. We estimate the effects of climate variability on migration overall and also investigate heterogeneity across sex, age, and socioeconomic groups, across countries, and across historical climate conditions. We also disaggregate migration by the rural/urban status of destination. We find that exposure to monthly temperature shocks has the most consistent effects on migration relative to monthly rainfall shocks and gradual changes in climate over multi-year periods. We also find evidence of heterogeneity across demographic groups and countries. Analyses that disaggregate migration by the rural/urban status of destination suggest that much of the climate-related migration is directed toward urban areas. Overall, our results underscore the complexity of environment-migration linkages and challenge simplistic narratives that envision a linear and monolithic migratory response to changing climates.     

Measuring household vulnerability to climate change—Why markets matter

Climate change and climate variability affect households in developing countries both directly through their impact on crop yields and indirectly through their impact on wages, food prices and the livelihoods of the poor. Therefore, vulnerable household groups cannot be identified without considering their position in and access to markets. I illustrate the effects – transmitted through markets – that are significant in household exposure, sensitivity and adaptive capacity to climate change by simulating productivity shocks to maize up to 2030 due to climate change in a computable general equilibrium model of Malawi. The results show that rural households with large land holdings may benefit from the adverse impact of climate change on maize yields as a result of increased maize prices. Urban poor and small-scale farmers are vulnerable to climate change due to the large portion of their incomes spent on food. Existing vulnerability measures that do not consider equilibrium effects and characterise all farmers as vulnerable may therefore be misleading.     

The devil is in the details: An investigation of the relationships between conflict,food price and climate across Africa

This study investigates the relationship between violent conflict, food price, and climate variability at the subnational level. Using disaggregated data on 113 African markets from January 1997 to April 2010, interrelationships between the three variables are analyzed in simultaneous equation models. We find that: (i) a positive feedback exists between food price and violence – higher food prices increase conflict rates within markets and conflict increases food prices; (ii) anomalously dry conditions are associated with increased frequencies of conflict; and (iii) decreased rainfall exerts an indirect effect on conflict through its impact on food prices. These findings suggest that the negative effects of climate variability on conflict can be mitigated by interventions and effective price management in local markets. Creating environments in which food prices are stable and reliable, and markets are accessible and safe, can lower the impacts of both climate change and conflict feedbacks.     

高原夏季风指数的定义及其特征分析

基于1958~2002年ECMWF再分析资料,我国160个台站降水和气温资料,从夏季高原季风环流系统特点出发,定义了能较好表征高原夏季风环流变化的特征指数,分析了高原夏季风年际、年代际变化特征,并揭示了高原夏季风强弱异常时的环流特征及其与中国夏季降水和气温的关系,主要结论为:(1)用6~8月600hPa(27.5~30°N,80~100°E)范围内平均的西风分量距平与(35~37.5°N,80~100°E)范围内平均的东风分量距平差定义了高原夏季风指数(PM I)。该指数计算简单,意义清楚,代表性好。(2)1958~2002年高原夏季风整体呈增强趋势,在20世纪60年代中期之前是高原夏季风的强盛期,之后是高原夏季风弱期,在80年代以后又转为季风强期。(3)高原夏季风与中国夏季降水和气温相关很好。将该指数与之前汤懋苍定义的指数进行性能综合比较后,发现该指数对川渝地区的夏季降水及气温有更好的指示意义。     

厄尔尼诺衰减年东亚夏季大气环流和降水异常的耦合模式后报试验

利用中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室(LASG)新一代耦合气候模式(FGOALS)进行了气候异常季节后报试验,通过对1982—2005年7个个例的分析,探讨了厄尔尼诺衰减年夏季东亚大气环流和降水异常发生的物理机制。分析结果表明:FGOALS可以模拟出厄尔尼诺衰减年夏季相关气候场的异常态特征,表现为在西北太平洋为负海温异常,在热带印度洋为正海温异常,从而导致西北太平洋地区大气中低层异常反气旋环流的维持,其反气旋的西南部及西部的偏南及西南气流造成中国长江中下游地区降水的异常增多。在提前3—9个月的预测模拟中,模式可以模拟出气候场的异常演变,随着预测时间的延长,产生局地耦合的西北太平洋海表温度异常信号变弱,使得模拟出的西北太平洋反气旋异常偏弱、中心东移,从而导致影响东亚降水的气候场的异常变弱,降水异常区偏东。模拟结果也揭示出,西北太平洋海表温度负异常是厄尔尼诺异常信号的转换模态,并且,由于局地海-气相互作用,热带海温异常信号可以持续到第2年夏季,从而引起东亚大气环流和降水异常。对于东亚降水的季节预测出现误差可能是模式对ENSO的模拟偏差造成的,随着预测时间延长,模式模拟的厄尔尼诺信号偏弱,这将使得海表温度异常偏弱,同时相关物理场的异常响应也减弱。     

The contribution of future agricultural trends in the US Midwest to global climate change mitigation

Land use change is a complex response to changing environmental and socioeconomic systems. Historical drivers of land use change include changes in the natural resource availability of a region, changes in economic conditions for production of certain products and changing policies. Most recently, introduction of policy incentives for biofuel production have influenced land use change in the US Midwest, leading to concerns that bioenergy production systems may compete with food production and land conservation. Here we explore how land use may be impacted by future climate mitigation measures by nesting a high resolution agricultural model (EPIC – Environmental Policy Indicator Climate) for the US Midwest within a global integrated assessment model (GCAM – Global Change Assessment Model). This approach is designed to provide greater spatial resolution and detailed agricultural practice information by focusing on the climate mitigation potential of agriculture and land use in a specific region, while retaining the global economic context necessary to understand the far ranging effects of climate mitigation targets. We find that until the simulated carbon prices are very high, the US Midwest has a comparative advantage in producing traditional food and feed crops over bioenergy crops. Overall, the model responds to multiple pressures by adopting a mix of future responses. We also find that the GCAM model is capable of simulations at multiple spatial scales and agricultural technology resolution, which provides the capability to examine regional response to global policy and economic conditions in the context of climate mitigation.     

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.     

The influence of tropical sea surface temperatures and precipitation on north Pacific atmospheric blocking

Blocking is a major component of the extratropical climate and any changes in it would be a very important aspect of climate change there. Previous studies have shown that mid-latitude variability such as blocking is sensitive to tropical sea surface temperature (SST) anomalies and to variations in tropical precipitation. Climate models exhibit a wide range of skill in representing blocking, with all models having deficiencies in certain respects. In addition, coupled climate models often exhibit significant biases in both tropical precipitation and tropical and extratropical SSTs. This suggests that tropical systematic biases in coupled climate models may influence the representation of blocking and its sensitivity to climate change. We examine the relationship between winter north Pacific blocking and tropical precipitation and tropical SSTs through the use of idealised SST anomaly experiments. We find that interannual variations in convection over the Maritime Continent and eastern equatorial Pacific regions both influence the central and eastern Pacific winter blocking frequency. In addition, systematic underestimation of tropical rainfall over the Maritime Continent region in climate models can lead to underestimation of time-mean winter Pacific blocking. Finally, the sign, magnitude and variability of tropical SST biases in a coupled model, and their associated effects on tropical precipitation, could influence its representation of northern hemisphere blocking, and thus affect its ability to represent this mode of remotely-forced mid-latitude variability. These results have important implications for model development.     

How stable are Australian farmers’ climate change risk perceptions? New evidence of the feedback loop between risk perceptions and behaviour

The exact relationship between people’s climate change attitudes and behaviour is a topic that engages policy-makers and researchers worldwide. Do climate change attitudes influence behaviour or is it possible that behaviour can change attitudes? This study uses a unique repeated survey dataset of 275 farmers (irrigators) in the southern Murray-Darling Basin from 2010–11 to 2015–16, to explore the dynamic relationship between climate change risk perceptions and farm adaptation behaviour. Farmers who had an increased risk exposure (expressed through higher debt, larger irrigated areas, greater share of permanent crops, and located in areas with higher temperatures and less rainfall) were more likely to agree climate change posed a risk. Whilst farmers became more accepting towards climate change over the time-period, a significant percentage of these attitudes were unstable. One reason suggested for this instability is the presence of a feedback loop between risk perceptions and behaviour. Namely, new evidence was found that farmers who agreed climate change was a risk in 2010–11, were more likely to undertake farm production decisions to reduce that risk (e.g. changing crop mix, reducing irrigated area and consequently selling water entitlements) – which had the impact of negatively feeding back and reducing their stated climate change risk perceptions in 2015–16. Conversely, farmers who were originally deniers were more likely to undertake somewhat riskier farm production decisions (e.g. increasing water utilisation rates and irrigation areas) – which consequently had the impact of positively increasing their climate change risk perceptions in 2015–16.     

Intra-seasonal rainfall and piped water revenue variability in rural Africa

Rainfall patterns influence water usage and revenue from user payments in rural Africa. We explore these dynamics by examining monthly rainfall against 4,888 records of rural piped water revenue in Ghana, Rwanda, and Uganda and quantifying revenue changes over 635 transitions between dry and wet seasons.Results show operators experience revenue variability at regional and intra-seasonal scales. Revenues fall by an average of 30 percent during the wettest months of the year in climate regimes with consistent wet season rainfall. However, seasonally stable revenues are observed in areas where consecutive dry days are common during the wet season, potentially reflecting a dependency on reliable services. We also find changes in tariff level, waterpoint connection type, and payment approach do not consistently prevent or increase seasonal revenue variability.Local revenue generation underpins delivery of drinking water services. Where rainfall patterns remain consistent, piped water operators can expect to encounter seasonal revenue reductions regardless of whether services are provided on or off premises and of how services are paid for. Revenue projections that assume consistent volumetric demand year-round may lead to shortfalls that threaten sustainability and undermine the case for future investment. Intra-seasonal rainfall analysis can enhance rural piped water revenue planning by offering localised insight into demand dynamics and revealing where climate variability may increase dependency on reliable services.