Floods in the Sahel: an analysis of anomalies, memory, and anticipatory learning

This study explores the implications of recent extreme rainfall and flood events in the Sahel and the wider West African region for climate change adaptation. Are these events merely a temporal nuisance as suggested by the lingering desertification discourse or will more climatic extremes characterize the region over the next century? After reviewing incidences of severe rainfall and projected future climate variability, the paper examines local flood knowledge and decision-making, drawing upon a case study in Ghana. The data demonstrate that a variety of response strategies to flooding exist; yet, knowledge of and access to climate forecasts and other learning tools are essentially absent. So far, floods have not triggered mass displacement although cumulative environmental deterioration is likely to cause environmental refugees. The paper recommends to lay to rest the desertification narrative, consider the possibility of both floods and droughts, and mobilize local memory for anticipatory learning and practical adaptation.     

Modeling the role of rainfall patterns in seasonal malaria transmission

Seasonal total precipitation is well known to affect malaria transmission because Anopheles mosquitoes depend on standing water for breeding habitat. However, the within-season temporal pattern of the rainfall influences persistence of standing water and thus rainfall patterns can also affect mosquito population dynamics in water-limited environments. Here, using a numerical simulation, I show that intraseasonal rainfall pattern accounts for 39% of the variance in simulated mosquito abundance in a Niger Sahel village where malaria is endemic but highly seasonal. I apply a field validated coupled hydrology and entomology model. Using synthetic rainfall time series generated using a stationary first-order Markov Chain model, I hold all variables except hourly rainfall constant, thus isolating the contribution of rainfall pattern to variance in mosquito abundance. I further show the utility of hydrology modeling using topography to assess precipitation effects by analyzing collected water. Time-integrated surface area of pools explains 70% of the variance in simulated mosquito abundance from a mechanistic model, and time-integrated surface area of pools persisting longer than 7?days explains 82% of the variance. Correlations using the hydrology model output explain more variance in mosquito abundance than the 60% from rainfall totals. I extend this analysis to investigate the impacts of this effect on malaria vector mosquito populations under climate shift scenarios, holding all climate variables except precipitation constant. In these scenarios, rainfall mean and variance change with climatic change, and the modeling approach evaluates the impact of non-stationarity in rainfall and the associated rainfall patterns on expected mosquito activity.     

Identifying hot spots of security vulnerability associated with climate change in Africa

Given its high dependence on rainfed agriculture and its comparatively low adaptive capacity, Africa is frequently invoked as especially vulnerable to climate change. Within Africa, there is likely to be considerable variation in vulnerability to climate change both between and within countries. This paper seeks to advance the agenda of identifying the hot spots of what we term “climate security” vulnerability, areas where the confluence of vulnerabilities could put large numbers of people at risk of death from climate-related hazards. This article blends the expertise of social scientists and climate scientists. It builds on a model of composite vulnerability that incorporates four “baskets” or processes that are thought to contribute to vulnerability including: (1) physical exposure, (2) population density, (3) household and community resilience, and (4) governance and political violence. Whereas previous iterations of the model relied on historical physical exposure data of natural hazards, this paper uses results from regional model simulations of African climate in the late 20th century and mid-21st century to develop measures of extreme weather events—dry days, heat wave events, and heavy rainfall days—coupled with an indicator of low-lying coastal elevation. For the late 20th century, this mapping process reveals the most vulnerable areas are concentrated in Chad, the Democratic Republic of the Congo, Niger, Somalia, Sudan, and South Sudan, with pockets in Burkina Faso, Ethiopia, Guinea, Mauritania, and Sierra Leone. The mid 21st century projection shows more extensive vulnerability throughout the Sahel, including Burkina Faso, Chad, Mali, northern Nigeria, Niger, and across Sudan.     

Evidence of climatic change in Nigeria based on annual series of rainfall of different daily amounts, 1919–1985

Annual series of light rainfall, moderate rainfall and heavy rainfall are computed for 4 zones arranged from south to north in Nigeria: Coastal, Guinea-Savanna, Midland and Sahelian zones. Daily rainfall data for the period 1919–85 are utilized. Each series is examined for evidence of change in structure in terms of pattern of decrease and increase in dry and wet years, the overall trend, and the occurrence of runs of dry and wet years. The northern Nigeria (Midland and Sahel) heavy rainfall series and the Sahel moderate rainfall series are found to depict evidence of climatic change as defined by Landsberg (1975) that climatic conditions must change to a new equilibrium position with the values of climatic elements changed significantly. On the other hand Landsberg's definition of climatic fluctuations as involving temporary deflection which can revert to earlier conditions is found to fit the 4 regional light rainfall series and the Midland area moderate rainfall series. The southern Nigeria moderate and heavy rainfall series are found to depict only evidence of high frequency oscillations about a stable long-term mean. The recent drought in Nigeria north of about 9° N is shown to be associated with a large decline in moderate and heavy rainfalls over this part of the country.     

Potential impacts of afforestation on climate change and extreme events in Nigeria

Afforestation is usually thought as a good approach to mitigate impacts of warming over a region. This study presents an argument that afforestation may have bigger impacts than originally thought by previous studies. The study investigates the impacts of afforestation on future climate and extreme events in Nigeria, using a regional climate model (RegCM3), forced with global climate model simulations. The impacts of seven afforestation options on the near future (2031–2050, under A1B scenario) climate and the extreme events are investigated. RegCM3 replicates essential features in the present-day (1981–2000) climate and the associated extreme events, and adequately simulates the seasonal variations over the ecological zones in the country. However, the model simulates the seasonal climate better over the northern ecological zones than over the southern ecological zones. The simulated spatial distribution of the extreme events agrees well with the observation, though the magnitude of the simulated events is smaller than the observed. The study shows that afforestation in Nigeria could have both positive and negative future impacts on the climate change and extreme events in the country. While afforestation reduces the projected global warming and enhances rainfall over the afforested area (and over coastal zones), it enhances the warming and reduces the rainfall over the north-eastern part of the country. In addition, the afforestation induces more frequent occurrence of extreme rainfall events (flooding) over the coastal region and more frequent occurrence of heat waves and droughts over the semi-arid region. The positive and negative impacts of the afforestation are not limited to Nigeria; they extend to the neighboring countries. While afforestation lowers the warming and enhances rainfall over Benin Republic, it increases the warming and lowers the rainfall over Niger, Chad and Cameroon. The result of the study has important implication for the ongoing climate change mitigation and adaptation efforts in Nigeria.     

用短期降水预报做洪水预报与调度的应用试验

利用2003～2007年潘家口水库流域10场较大降水及其对应的河北省气象局MM5的面雨量预报数据,采用降水预报格点数据与水文洪水预报耦合的方法进行水库的洪水预报和调度,增长了水文洪水预报的预见期,在不增加水库工程投资,不增加上下游和工程风险的前提下,在汛期实施风险调度,以此发挥水库在洪水资源化调度中作用,解决防洪与蓄水的矛盾.     

1958-2012年来河北汛期暴雨气候变化特征分析

应用1958-2012年河北21个基准站和基本站逐日降水观测资料,分析了河北汛期暴雨的气候分布特征、年际、年代际变化以及趋势变化特征。结果表明,汛期暴雨分布呈现东部、南部多,向西北部递减的特征。最大暴雨量中心在河北东部、燕山南麓的唐山、秦皇岛地区。从年际和年代际尺度分析,暴雨量、频次、强度都存在2-3 a的年际变化周期信号,暴雨量和频次在20世纪80年代以后存在15-20 a的年代际周期信号。汛期暴雨量、暴雨频次时间序列整体呈现下降趋势,特别是21世纪以来,河北暴雨量和暴雨频次下降趋势更为明显,暴雨强度在近50 a变化幅度不大。在空间分布上,暴雨量、暴雨频次和暴雨强度三个特征量在年代际变化中整体都呈现东退南缩的特征。从趋势分析看来,大部分站点汛期暴雨量、频次、强度都呈现下降趋势。     

Trend analysis for rainfall in Delhi and Mumbai, India

Urbanisation has burdened cities with many problems associated with growth and the physical environment. Some of the urban locations in India are becoming increasingly vulnerable to natural hazards related to precipitation and flooding. Thus it becomes increasingly important to study the characteristics of these events and their physical explanation. This work studies rainfall trends in Delhi and Mumbai, the two biggest Metropolitan cities of Republic of India, during the period from 1951 to 2004. Precipitation data was studied on basis of months, seasons and years, and the total period divided in the two different time periods of 1951–1980 and 1981–2004 for detailed analysis. Long-term trends in rainfall were determined by Man-Kendall rank statistics and linear regression. Further this study seeks for an explanation for precipitation trends during monsoon period by different global climate phenomena. Principal component analysis and Singular value decomposition were used to find relation between southwest monsoon precipitation and global climatic phenomena using climatic indices. Most of the rainfall at both the stations was found out to be taking place in Southwest monsoon season. The analysis revealed great degree of variability in precipitation at both stations. There is insignificant decrease in long term southwest monsoon rainfall over Delhi and slight significant decreasing trends for long term southwest monsoon rainfall in Mumbai. Decrease in average maximum rainfall in a day was also indicated by statistical analysis for both stations. Southwest monsoon precipitation in Delhi was found directly related to Scandinavian Pattern and East Atlantic/West Russia and inversely related to Pacific Decadal Oscillation, whereas precipitation in Mumbai was found inversely related to Indian ocean dipole, El Ni?o- Southern Oscillation and East Atlantic Pattern.     

气候模拟研究进展

根据地回顾了大约４０年来气候模拟研究的发展过程，指出根据研究的目标可以分为三个阶段；模拟大气平均状况、敏感性实验及气候变率的模拟，着重总结了近年来气候变率模拟的最新成果，包括对印度夏季风降水，萨赫勒干旱、气候变率、世界三大涛动、ＥＮＳＯ循环及中国旱涝型的模拟研究。     

The local impacts of climate change in the Ferlo, Western Sahel

Recent increases in the accuracy of climate models have enhanced the possibilities for analyzing the impacts of climate change on society. This paper explores how the local, economic impacts of climate change can be modeled for a specific eco-region, the Western Sahel. The people in the Sahel are highly dependent on their natural resource base, and these resources are highly vulnerable to climate change, in particular to changes in rainfall. Climate models project substantial changes in rainfall in the Sahel in the coming 50 years, with most models predicting a reduction in rainfall. To connect climate change to changes in ecosystem productivity and local income, we construct an ecological–economic model that incorporates rangeland dynamics, grazing and livestock prices. The model shows that decreased rainfall in the Sahel will considerably reduce local incomes, in particular if combined with increases in rainfall variability. Adaptation to these climate change projections is possible if reductions in rainfall are followed by destocking to reach efficient grazing levels. However, while such a strategy is optimal from the perspective of society, the stocking rate is determined by individual pastoralists that face few incentives to destock.     

1961—2015年中国暴雨变化诊断及其与多种气候因子的关联性研究

气候变化背景下,频发的暴雨事件造成城市内涝、人员伤亡和财产损失,已经成为全社会广泛关注的焦点问题之一。为了诊断中国暴雨的时空变化及其与不同自然因子的关联性,采用1961—2015年中国659个降水站点数据,采用线性趋势、EOF分析等多种统计方法诊断了中国暴雨时空变化特征,结果表明,中国暴雨雨量、雨日和雨强在1961—2015年以胡焕庸线为界呈现出东南高-西北低的气候态空间分布格局;线性趋势分析表明1961—2015年中国暴雨雨量和雨日从东南沿海向西北内陆呈明显“增-减-增”的空间分布格局,且呈增长趋势的站点占主导,分别高达80.88%和79.81%;从西北内陆到东南沿海的年代剖面分析表明中国暴雨雨量和雨日随着年代推移在迅速增长;对低通滤波后的中国暴雨进行EOF分析表明中国暴雨雨量和雨日的增长东南沿海快,内陆地区慢。根据IPCC等已有研究中筛选出对中国地区有影响的28个气候因子,并将其与659个站点的暴雨进行相关分析,结果表明不同气候因子与不同区域暴雨呈现出错综复杂的相关性特征,其中与暴雨雨量呈现以正相关和负相关为主的气候因子分别为15和13个,全局相关因子包含AAO(Antarctic Oscillation)、Pacific Warmpool,而其它气候因子在七大分区中与暴雨的关联性各有突出,表现出明显的空间异质性。      

Taming São Paulo’s floods: Dominant discourses,exclusionary practices,and the complicity of the media

Climate change leads to more frequent and severe flooding, urging cities to adapt to protect their populations and assets. Despite exacerbated hazards, governments repeatedly draw on ‘tried-and-true’ approaches to protect the status quo, often with serious adverse effects for the poor and vulnerable. Yet, such dominant approaches do not go unchallenged as the media and other actors prompt public debate to assess flood impacts, scrutinise government decisions, and perhaps even promote alternative practices. News outlets are not, however, balanced or value-free; the events portrayed and the voices (and knowledges) recognised and included in media coverage deeply influence whether and how flooding is incorporated in policy. Focusing on São Paulo, Brazil, we examine how the media framed flood events and conveyed solutions during the city’s worst floods in recorded history. We demonstrate how competing media outlets largely depicted flooding as a natural phenomenon to be solved by governments and experts through existing techno-managerial practices, mirroring governmental partisan plans for adaptive action. In doing so, the media failed to offer a democratic space for public discussion, citizen contestation, and the advancement of alternative trajectories for adaptation. We posit that inclusive trajectories that address entrenched vulnerabilities and projected climate change will benefit from rigorous ethical debates around the media’s role in disaster coverage while strategically leveraging alternative media outlets as public pedagogy and agenda-setting tools.     

Implications of climate change due to the enhanced greenhouse effect on floods and droughts in Australia

Potential impacts of climate change on heavy rainfall events and flooding in the Australian region are explored using the results of a general circulation model (GCM) run in an equilibrium enhanced greenhouse experiment. In the doubled CO₂ simulation, the model simulates an increase in the frequency of high-rainfall events and a decrease in the frequency of low-rainfall events. This result applies over most of Australia, is statistically more significant than simulated changes in total rainfall, and is supported by theoretical considerations. We show that this result implies decreased return periods for heavy rainfall events. The further implication is that flooding could increase, although we discuss here the many difficulties associated with assessing in quantitative terms the significance of the modelling results for the real world.The second part of the paper assesses the implications of climate change for drought occurrence in Australia. This is undertaken using an off-line soil water balance model driven by observed time series of rainfall and potential evaporation to determine the sensitivity of the soil water regime to changes in rainfall and temperature, and hence potential evaporation. Potential impacts are assessed at nine sites, representing a range of climate regimes and possible climate futures, by linking this sensitivity analysis with scenarios of regional climate change, derived from analysis of enhanced greenhouse experiment results from five GCMs. Results indicate that significant drying may be limited to the south of Australia. However, because the direction of change in terms of the soil water regime is uncertain at all sites and for all seasons, there is no basis for statements about how drought potential may change.     

Effectiveness of flood damage mitigation measures: Empirical evidence from French flood disasters

Recent destructive flood events and projected increases in flood risks as a result of climate change in many regions around the world demonstrate the importance of improving flood risk management. Flood-proofing of buildings is often advocated as an effective strategy for limiting damage caused by floods. However, few empirical studies have estimated the damage that can be avoided by implementing such flood damage mitigation measures. This study estimates potential damage savings and the cost-effectiveness of specific flood damage mitigation measures that were implemented by households during major flood events in France. For this purpose, data about flood damage experienced and household flood preparedness were collected using a survey of 885 French households in three flood-prone regions that face different flood hazards. Four main conclusions can be drawn from this study. First, using regression analysis results in improved estimates of the effectiveness of mitigation measures than methods used by earlier studies that compare mean damage suffered between households who have, and who have not, taken these measures. Second, this study has provided empirical insights showing that some mitigation measures can substantially reduce damage during floods. Third, the effectiveness of the mitigation measures is very regional dependent, which can be explained by the different characteristics of the flood hazard in our sample areas that experience either slow onset river flooding or more rapid flash and coastal flooding. Fourth, the cost-efficiency of the flood damage mitigation measures depends strongly on the flood probability faced by households.     

Assessing future climatic changes of rainfall extremes at small spatio-temporal scales

Climate change is expected to influence the occurrence and magnitude of rainfall extremes and hence the flood risks in cities. Major impacts of an increased pluvial flood risk are expected to occur at hourly and sub-hourly resolutions. This makes convective storms the dominant rainfall type in relation to urban flooding. The present study focuses on high-resolution regional climate model (RCM) skill in simulating sub-daily rainfall extremes. Temporal and spatial characteristics of output from three different RCM simulations with 25 km resolution are compared to point rainfall extremes estimated from observed data. The applied RCM data sets represent two different models and two different types of forcing. Temporal changes in observed extreme point rainfall are partly reproduced by the RCM RACMO when forced by ERA40 re-analysis data. Two ECHAM forced simulations show similar increases in the occurrence of rainfall extremes of over a 150-year period, but significantly different changes in the magnitudes. The physical processes behind convective rainfall extremes generate a distinctive spatial inter-site correlation structure for extreme events. All analysed RCM rainfall extremes, however, show a clear deviation from this correlation structure for sub-daily rainfalls, partly because RCM output represents areal rainfall intensities and partly due to well-known inadequacies in the convective parameterization of RCMs. The results highlight the problem urban designers are facing when using RCM output. The paper takes the first step towards a methodology by which RCM performance and other downscaling methods can be assessed in relation to the simulation of short-duration rainfall extremes.     

陆面参数化方案对两例不同类型暴雨可预报性的影响

以2003年7月3～4日淮河流域平流型暴雨和2003年8月2～3日江西蒸发型暴雨个例为例, 采用模式试验方法, 研究了陆面参数化方案对两种不同类型暴雨的模式可预报性的影响。关闭陆气通量的试验表明, 陆气通量对淮河流域暴雨的贡献很小, 模式预报结果之间的差异较小, 平流型暴雨具有较高的模式可预报性; 而陆气通量对热对流暴雨的贡献很大, 其误差对暴雨的分布和强度影响也较大, 蒸发型暴雨的模式可预报性相对较低。不同陆面过程参数化方案的比较试验表明, 陆气通量误差引起的能量误差仅在特定区域发展。当陆气通量误差超过一定的临界值, 能量误差将在降水区和风速大值区 (急流区) 迅速发展, 能量误差和不稳定能量同源且同时增长。从陆气通量影响天气过程的角度来讲, 模式预报启动时间选择在夜间, 能量误差发展相对缓慢, 可以延长预报时效。     

Seasonal forecasts in the Sahel region: the use of rainfall-based predictive variables

In the Sahel region, seasonal predictions are crucial to alleviate the impacts of climate variability on populations' livelihoods. Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May–July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920–2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. A total of nine climatic zones were identified in each of which, based on rainfall records from May to July, we derived linear discriminant functions to correctly predict the nature of a potential onset date of the rainy season (real or false) and that of the rainy season (dry or wet) in at least three cases out of five. These functions should contribute to alleviating the negative impacts of climate variability in the different climatic zones of Burkina Faso.     

A case study of excessive rainfall forecasting

Summary Flash floods have been recognized as one of the most significant natural disaster problems in the world. Within the United States, the annual average flood death toll exceeds one hundred and property damage is on the order of a billion dollars. There has been an increased effort of the meteorological community to improve short term quantitative precipitation forecasting, principally by improving mesoscale numerical weather prediction for heavy rain events. Nevertheless, to date, numerical weather prediction has had rather limited impact on the prediction of the most damaging convective rainstorms.This study examines numerical experiments, including both coarse-mesh and fine-mesh model simulations, of the Enid, Oklahoma flood of 10–11 October 1973. Besides the great concentration of rainfall, the Enid flood was rather unique in comparison with other flash flood cases in that it was part of a much larger area of heavy rainfall which soaked the central Plains over the 24h period ending at 1200 UTC 11 October. The objective is to assess the overall usefulness and limitation of numerical weather prediction models in quantitative precipitation forecasting for this flash flood event.The model experiments reveal that the broad-scale precipitation patterns associated with the front and cyclone are well predicted, but the maximum rainfall amounts around Enid are underpredicted. The fine-mesh model is superior to the coarse-mesh model because of the former's ability to generate many significant mesoscale features in the vicinity of the front. In the fine-mesh model, many convection-related parameters (e.g., moisture flux convergence) are correlated very well temporally and spatially with the observed heavy precipitation scenario.     

Archival explorations of climate variability and social vulnerability in colonial Mexico

In this paper, unpublished archival documentary sources are used to explore the vulnerability to–and implications of–climatic variability and extreme weather events in colonial Mexico. Attention focuses on three regions covering a variety of environmental, social, economic, and political contexts and histories and located at key points along a north-south rainfall gradient: Chihuahua in the arid north, Oaxaca in the wetter south and Guanajuato located in the central Mexican highlands. A number of themes are considered. First, the significance of successive, prolonged, or combined climate events as triggers of agrarian crisis. Second, a case study demonstrating the national and regional impacts of a particularly devastating climate induced famine, culminating with the so-called ‘Year of Hunger’ between 1785 and 1786, is presented. The way in which social networks and community engagement were rallied as a means of fortifying social resilience to this and other crises will be highlighted. Third, the impacts of selected historical flood events are explored in order to highlight how the degree of impact of a flood was a function of public expectation, preparedness and also the particular socio-economic and environmental context in which the event took place. An overview of the spatial and temporal variations in vulnerability and resilience to climatic variability and extreme weather events in colonial Mexico is then provided, considering those recorded events that could potentially relate to broader scale, possibly global, climate changes.