How do small-holder farmers understand insurance,and how much do they want it? Evidence from Africa

Innovative micro-insurance schemes can be one tool to help African small-holder farmers cope with climate variability and change. A critical challenge for implementing such risk transfer programs, however, is helping participants understand how insurance operates, and there is evidence that farmers with a poor understanding of insurance are less likely to use it. One of the proposed tools to help farmers understand insurance is a simulation game, through which farmers can gain first-hand experience with a functioning insurance market. This paper reports on the results of experiments in Ethiopia and Malawi, investigating farmers’ understanding and the effectiveness of a role-playing game at improving that understanding. Our results suggest a generally poor understanding of basic insurance concepts, and are consistent with past results in suggesting that better understanding correlates with greater willingness to purchase it. Our results also suggest that role-playing games may be an important tool for improving understanding, but that they do not necessarily out-perform more conventional training practices.     

The Effects of Model Resolution on the Simulation of Regional Climate Extreme Events

The fifth-generation Pennsylvania State University/NCAR Mesoscale Model Version 3 (MM5V3) was used to simulate extreme heavy rainfall events over the Yangtze River Basin in June 1999. The effects of model's horizontal and vertical resolution on the extreme climate events were investigated in detail. In principle, the model was able to characterize the spatial distribution of monthly heavy precipitation. The results indicated that the increase in horizontal resolution could reduce the bias of the modeled heavy rain and reasonably simulate the change of daily precipitation during the study period. A finer vertical resolution led to obviously improve rainfall simulations with smaller biases, and hence, better resolve heavy rainfall events. The increase in both horizontal and vertical resolution could produce better predictions of heavy rainfall events. Not only the rainfall simulation altered in the cases of different horizontal and vertical grid spacing, but also other meteorological fields demonstrated diverse variations in terms of resolution change in the model. An evident improvement in the simulated sea level pressure resulted from the increase of horizontal resolution, but the simulation was insensitive to vertical grid spacing. The increase in vertical resolution could enhance the simulation of surface temperature as well as atmospheric circulation at low levels, while the simulation of circulation at middle and upper levels were found to be much less dependent on changing resolution. In addition, cumulus parameterization schemes showed high sensitivity to horizontal resolution. Different convective schemes exhibited large discrepancies in rainfall simulations with regards to changing resolution. The percentage of convective precipitation in the Grell scheme increased with increasing horizontal resolution. In contrast, the Kain-Fritsch scheme caused a reduced ratio of convective precipitation to total rainfall accumulations corresponding to increasing horizontal resolution.     

Flood insurance arrangements in the European Union for future flood risk under climate and socioeconomic change

Flood risk will increase in many areas around the world due to climate change and increase in economic exposure. This implies that adequate flood insurance schemes are needed to adapt to increasing flood risk and to minimise welfare losses for households in flood-prone areas. Flood insurance markets may need reform to offer sufficient and affordable financial protection and incentives for risk reduction. Here, we present the results of a study that aims to evaluate the ability of flood insurance arrangements in Europe to cope with trends in flood risk, using criteria that encompass common elements of the policy debate on flood insurance reform. We show that the average risk-based flood insurance premium could double between 2015 and 2055 in the absence of more risk reduction by households exposed to flooding. We show that part of the expected future increase in flood risk could be limited by flood insurance mechanisms that better incentivise risk reduction by policyholders, which lowers vulnerability. The affordability of flood insurance can be improved by introducing the key features of public-private partnerships (PPPs), which include public reinsurance, limited premium cross-subsidisation between low- and high-risk households, and incentives for policyholder-level risk reduction. These findings were evaluated in a comprehensive sensitivity analysis and support ongoing reforms in Europe and abroad that move towards risk-based premiums and link insurance with risk reduction, strengthen purchase requirements, and engage in multi-stakeholder partnerships.     

Climate change impacts on pricing long-term flood insurance: A comprehensive study for the Netherlands

Recently long-term flood insurance contracts with a duration of 5, 10 or 15 years have been proposed as a solution for covering flood risk and mitigating increasing flood losses. Establishing a long-term relation between the policyholder and the insurer can provide better incentives to reduce risk through undertaking damage mitigation measures. However, the uncertainty about the development of future flood risk in the face of climate and socio-economic change may complicate insurers’ rate-setting of long-term contracts. This issue has been examined in this study by estimating the effects of these changes on flood risk and pricing flood insurance premiums of short- and long-term flood insurance contracts in all (53) dike-ring areas in the Netherlands. A broad range of simulations with hydrological and flood damage models are used to estimate the future development of flood risk and premiums. In addition, the long-term development of insurance funds is estimated with a spatial “Climate Risk Insurance Model (CRIM)” for a private insurance arrangement and for a ‘three-layered’ public-private insurance program. The estimation of flood insurance premiums of long-term insurance contracts reveals fundamental problems. One is that there is an incentive for either the consumer or the insurer to prefer short-term rather than long-term contracts in the face of climate-related uncertainty. Therefore, it seems advisable to examine the introduction of one-year flood insurance contracts in the Netherlands, at least until the large uncertainties with climate and socio-economic change on flood risk have been resolved. The estimations performed with the Climate Risk Insurance Model indicate that a private insurance fund could have difficulties with building up enough financial reserves to pay for flood damage, while the layered public-private insurance scheme is more robust.     

An assessment of the potential impact of climate change on flood risk in Mumbai

Managing risks from extreme events will be a crucial component of climate change adaptation. In this study, we demonstrate an approach to assess future risks and quantify the benefits of adaptation options at a city-scale, with application to flood risk in Mumbai. In 2005, Mumbai experienced unprecedented flooding, causing direct economic damages estimated at almost two billion USD and 500 fatalities. Our findings suggest that by the 2080s, in a SRES A2 scenario, an ??upper bound?? climate scenario could see the likelihood of a 2005-like event more than double. We estimate that total losses (direct plus indirect) associated with a 1-in-100 year event could triple compared with current situation (to $690?C$1,890 million USD), due to climate change alone. Continued rapid urbanisation could further increase the risk level. The analysis also demonstrates that adaptation could significantly reduce future losses; for example, estimates suggest that by improving the drainage system in Mumbai, losses associated with a 1-in-100 year flood event today could be reduced by as much as 70%.,We show that assessing the indirect costs of extreme events is an important component of an adaptation assessment, both in ensuring the analysis captures the full economic benefits of adaptation and also identifying options that can help to manage indirect risks of disasters. For example, we show that by extending insurance to 100% penetration, the indirect effects of flooding could be almost halved. We conclude that, while this study explores only the upper-bound climate scenario, the risk-assessment core demonstrated in this study could form an important quantitative tool in developing city-scale adaptation strategies. We provide a discussion of sources of uncertainty and risk-based tools could be linked with decision-making approaches to inform adaptation plans that are robust to climate change.     

SENSITIVITY OF THE WEATHER RESEARCH AND FORECASTING MODEL TO RADIATION SCHEMES IN CHINA

Results of one-year simulations using the Weather Research and Forecast (WRF) model, with the use of different radiation schemes (RRTM, RRTMG, CAM, New Goddard and Goddard), are evaluated for China. The observations used in the model assessment include station data from the China Meteorological Administration, 14 flux field sites arranged in a coordinated observation network, and Global Land Data Assimilation System (GLDAS) data. Specifically, based on a Taylor diagram, the temperature differences between the radiation schemes are small, and the best annual mean spatial pattern and average value for China as a whole is produced by RRTMG. For the rainfall and net radiation annual mean simulation, the New Goddard and CAM schemes present better results than the RRTMG scheme. With respect to low cloud cover, all the schemes have similar reproduction without high cover on east of Tibet Plateau. Overall, the New Goddard and CAM schemes are suitable for longtime simulation without nesting and nudging options.     

The influence of gender and product design on farmers’ preferences for weather-indexed crop insurance

Theoretically, weather-index insurance is an effective risk reduction option for small-scale farmers in low income countries. Renewed policy and donor emphasis on bridging gender gaps in development also emphasizes the potential social safety net benefits that weather-index insurance could bring to women farmers who are disproportionately vulnerable to climate change risk and have low adaptive capacity. To date, no quantitative studies have experimentally explored weather-index insurance preferences through a gender lens, and little information exists regarding gender-specific preferences for (and constraints to) smallholder investment in agricultural weather-index insurance. This study responds to this gap, and advances the understanding of preference heterogeneity for weather-index insurance by analysing data collected from 433 male and female farmers living on a climate change vulnerable coastal island in Bangladesh, where an increasing number of farmers are adopting maize as a potentially remunerative, but high-risk cash crop. We implemented a choice experiment designed to investigate farmers’ valuations for, and trade-offs among, the key attributes of a hypothetical maize crop weather-index insurance program that offered different options for bundling insurance with financial saving mechanisms. Our results reveal significant insurance aversion among female farmers, irrespective of the attributes of the insurance scheme. Heterogeneity in insurance choices could however not be explained by differences in men’s and women’s risk and time preferences, or agency in making agriculturally related decisions. Rather, gendered differences in farmers’ level of trust in insurance institutions and financial literacy were the key factors driving the heterogeneous preferences observed between men and women. Efforts to fulfill gender equity mandates in climate-smart agricultural development programs that rely on weather-index insurance as a risk-abatement tool are therefore likely to require a strengthening of institutional credibility, while coupling such interventions with financial literacy programs for female farmers.     

Teleconnections：Summer Monsoon over Korea and India

This study investigates the relationship between the summer monsoon rainfall over Korea and India,by using correlation analysis and Singular Value Decomposition(SVD).Results reveal that summer monsoon rainfall over Korea is negatively(significant at the 99% level) correlated with the rainfall over the northwest and central parts of India.In addition,coupled spatial modes between the rainfall over Korea and India have been identified by the SVD analysis.The squared covariance fraction explained by the first mode is 70% and the correlation coefficient between the time coefficients of the two fields is significant at the 99% level,indicating that the coupled mode reflects a large part of the interaction between the summer monsoon rainfall over Korea and India.The first mode clearly demonstrates the existence of a significant negative correlation between the rainfall over the northwest and central parts of India and the rainfall over Korea.Possible mechanisms of this correlation are investigated by analyzing the variation of upper-level atmospheric circulation associated with the Tibetan high using NCEP/NCAR Reanalysis data.     

Insuring future climate catastrophes

The combined influences of a change in climate patterns and the increased concentration of property and economic activity in hazard-prone areas has the potential of restricting the availability and affordability of insurance. This paper evaluates the premiums that private insurers are likely to charge and their ability to cover residential losses against hurricane risk in Florida as a function of (a) recent projections on future hurricane activity in 2020 and 2040; (b) insurance market conditions (i.e., soft or hard market); (c) the availability of reinsurance; and (d) the adoption of adaptation measures (i.e., implementation of physical risk reduction measures to reduce wind damage to the structure and buildings). We find that uncertainties in climate projections translate into a divergent picture for insurance in Florida. Under dynamic climate models, the total price of insurance for Florida (assuming constant exposure) could increase significantly by 2040, from $12.9 billion (in 1990) to $14.2 billion, under hard market conditions. Under lower bound projections, premiums could decline to $9.4 billion by 2040. Taking a broader range of climate change scenarios, including several statistical ones, prices could be between $4.7 and $32.1 billion by 2040. The upper end of this range suggests that insurance could be unaffordable for many people in Florida. The adoption of most recent building codes for all residences in the state could reduce by nearly half the expected price of insurance so that even under high climate change scenarios, insurance premiums would be lower than under the 1990 baseline climate scenario. Under a full adaptation scenario, if insurers can obtain reinsurance, they will be able to cover 100 % of the loss if they allocated 10 % of their surplus to cover a 100-year return hurricane, and 63 % and 55 % of losses from a 250-year hurricane in 2020 and 2040. Property-level adaptation and the maintenance of strong and competitive reinsurance markets will thus be essential to maintain the affordability and availability of insurance in the new era of catastrophe risk.     

Insurance against weather risk: Use of heating degree-days from non-local stations for weather derivatives

Summary ?Weather derivatives enable policy-holders to safeguard themselves against extreme weather conditions. The effectiveness and the efficiency of the risk transfer is determined by the spatial risk basis, which is the stochastic dependency of the local weather outcome being insured and the outcome of the weather underlying the insurance instrument. The lower this risk basis the higher the effectiveness and the efficiency of the risk transfer. To study the spatial risk basis component in relation to the design and evaluation of a weather derivative contract to insure for heating degree-days (HDD), the historical temperature records were analyzed for five sites across the Netherlands. Sensitivity and specificity of the insurance instrument were used to quantify the potential spatial risk basis. Setting indemnification beyond a half standard deviation above the mean meant that between 60% and 76% of the indemnable HDD were classified correctly, while 82% to 99% of the non-indemnable HDD were classified correctly. These results indicate that the spatial risk basis is a major concern and that successful weather derivatives require the utilization of carefully selected weather data obtained from meteorological stations in close proximity to the area being insured. Received November 5, 2001; revised July 3, 2002; accepted July 7, 2002     

Social capital,individual responses to heat waves and climate change adaptation: An empirical study of two UK cities

It has been claimed that high social capital contributes to both positive public health outcomes and to climate change adaptation. Strong social networks have been said to support individuals and collective initiatives of adaptation and enhance resilience. As a result, there is an expectation that social capital could reduce vulnerability to risks from the impacts of climate change in the health sector. This paper examines evidence on the role social networks play in individuals’ responses to heat wave risk in a case study in the UK. Based on interviews with independently living elderly people and their primary social contacts in London and Norwich, we suggest that strong bonding networks could potentially exacerbate rather than reduce the vulnerability of elderly people to the effects of heat waves. Most respondents interviewed did not feel that heat waves posed a significant risk to them personally, and most said that they would be able to cope with hot weather. Bonding networks could perpetuate rather than challenge these narratives and therefore contribute to vulnerability rather than ameliorating it. These results suggest a complex rather than uniformly positive relationship between social capital, health and adaptation to climate change.     

RegCM3模式对中国东部夏季降水的模拟试验

利用最新发布的区域气候模式RegCM3对1998年5—8月中国东部降水进行了模拟试验，考察了模式对降水和大尺度环流系统的模拟能力。结果表明：不同对流性降水方案对不同月份、不同区域的降水模拟效果差别较大，采用Kuo方案和Grell方案时模拟的降水效果要好于BM方案；RegCM3能较成功地再现异常降水的月际尺度变化和空间分布等基本特征；模式还较好地模拟了西太平洋副高脊线的演变过程和两次向北传播的季节内振荡。该模式可应用于中国东部夏季风降水的研究。     

Assessing the effectiveness of non-structural flood management measures in the Thames Estuary under conditions of socio-economic and environmental change

Risk analysis and appraisal of the benefits of structural flood risk management measures such as embankments is well established. Here, a method to quantify, over extended timescales, the effectiveness of non-structural measures such as land use spatial planning, insurance and flood resilient construction is presented. The integrated approach couples socio-economic and climate change scenarios with long term land use modelling and flood risk analysis to generate maps and time series of expected annual damages. The analysis has been applied on a case study in the Thames Estuary in the UK. Stakeholders helped develop a number of scenarios that might lead to substantial changes in existing planning and insurance policies in the UK. The effectiveness of these changes was analysed and showed the substantial benefits in terms of reduction of future flood risks that are achievable with changes in planning policy, financial incentives and resilient property construction in the floodplain. Moreover, the reward can be increased through earlier action. Subsequently, the benefits of a range of policies are explored under the UK Foresight socio-economic scenarios. Different structural and non structural flood management interventions are tested and the results demonstrate that despite the potential for large increases in flood risk in the Thames Estuary, in all scenarios substantial flood risk reductions are possible. The effectiveness of non-structural measures is however sensitive to socio-economic changes and governance arrangements. The analysis described here will help to identify portfolios of non-structural and structural options that are robust to uncertainties.     

On the economics of coastal adaptation solutions in an uncertain world

The economics of adaptation to climate change relies heavily on comparisons of the benefits and costs of adaptation options that can range from changes in policy to implementing specific projects. Since these benefits are derived from damages avoided by any such adaptation, they are critically dependent on the specification of a baseline. The current exercise paper reinforces this point in an environment that superimposes stochastic coastal storm events on two alternative sea level rise scenarios from two different baselines: one assumes perfect economic efficiency of the sort that could be supported by the availability of actuarially fair insurance and a second in which fundamental market imperfections significantly impair society’s ability to spread risk. We show that the value of adaptation can be expressed in terms of differences in expected outcomes damages only if the effected community has access to efficient risk-spreading mechanisms or reflects risk neutrality in its decision-making structure. Otherwise, the appropriate metric for measuring the benefits of adaptation must be derived from certainty equivalents. In these cases, increases in decision-makers’ aversion to risk increase the economic value of adaptations that reduce expected damages and diminish the variance of their inter-annual variability. For engineering and other adaptations that involve significant up-front expense followed by ongoing operational cost, increases in decision-makers’ aversion increase the value of adaptation and therefore move the date of economically efficient implementation closer to the present.     

在四维变分同化中运用集合协方差的试验

利用浅水方程模式和模式模拟资料进行数值试验比较3种不同的背景误差协方差矩阵处理方法对四维变分(4DVAR)资料同化的影响.3种背景误差协方差矩阵分别是:(1)对单一变量将背景误差协方差矩阵简化为对角矩阵;(2)将背景误差协方差矩阵的作用简化为高斯过滤;(3)由预报集合生成背景误差协方差矩阵并利用奇异值分解技术解决矩阵的求逆.通过一系列数值试验,比较不同观测密度、不同观测误差下3种背景误差协方差处理方法对4DVAR同化效果的影响.结果表明,背景误差协方差的结构对4DVAR有重大影响.当观测资料的空间密度不够高时,采用对角矩阵得不到满意的结果.高斯过滤方案可以明显改善同化结果,但是对背景误差特征长度比较敏感.第3种方法采用的背景误差协方差矩阵是流型依赖的,而且并不以显式的方式出现在目标函数中.避免了对它求逆的复杂运算.由于做了降维处理,在观测点的密度较低和观测误差较大时可望取得较好的同化结果,同化效果较为稳定.     

Comparison of two land surface schemes in week-long cloud-system-resolving simulations of warm season precipitation

This paper presents a case study of the impact of land surface treatment on warm season precipitation simulations at convection-permitting grid resolution. Two surface schemes are tested: Dudhia’s five-layer soil model (FLSM) and the Noah land-surface model (NLSM). The experimentation case involves a 1-week episode of active summertime convection over the central United States. The overall precipitation features, such as the diurnal regeneration of zonally propagating rainfall episodes and the spatial distribution of accumulative rainfall, are adequately replicated by the two parameterizations. In comparison, NLSM produces roughly 12% more and broader rainfall than FLSM. This differential rainfall amount is consistent with the differential surface moisture fluxes between the two schemes, whereas the precipitation feedback plays a negligible role. It is also found that FLSM generates comparatively stronger sensible heat transports from the land surface and thus a warmer temperature near the surface.     

MM5模式中湿方案的不确定性对“03·7”南京暴雨数值模拟不确定性的影响

利用有限区域非静力MM5模式, 分析了显式降水方案对于2003年7月4—5日南京暴雨数值模拟的不确定性影响。采用混合方案模拟此次暴雨时, 这种不确定性决定于显式和隐式方案的相互协调性及敏感性; 隐式方案基本决定了雨带的整体的空间分布, 而显式方案对于降水型及降水量起到一定的调节作用, 调节的程度与选择的参数化方案有关; 采用隐式方案Grell和KF2模拟此次暴雨时, 应考虑不同的显式方案对于降水模拟的不确定性的影响。     

Performance assessment of three convective parameterization schemes in WRF for downscaling summer rainfall over South Africa

Austral summer rainfall over the period 1991/1992 to 2010/2011 was dynamically downscaled by the weather research and forecasting (WRF) model at 9 km resolution for South Africa. Lateral boundary conditions for WRF were provided from the European Centre for medium-range weather (ECMWF) reanalysis (ERA) interim data. The model biases for the rainfall were evaluated over the South Africa as a whole and its nine provinces separately by employing three different convective parameterization schemes, namely the (1) Kain–Fritsch (KF), (2) Betts–Miller–Janjic (BMJ) and (3) Grell–Devenyi ensemble (GDE) schemes. All three schemes have generated positive rainfall biases over South Africa, with the KF scheme producing the largest biases and mean absolute errors. Only the BMJ scheme could reproduce the intensity of rainfall anomalies, and also exhibited the highest correlation with observed interannual summer rainfall variability. In the KF scheme, a significantly high amount of moisture was transported from the tropics into South Africa. The vertical thermodynamic profiles show that the KF scheme has caused low level moisture convergence, due to the highly unstable atmosphere, and hence contributed to the widespread positive biases of rainfall. The negative bias in moisture, along with a stable atmosphere and negative biases of vertical velocity simulated by the GDE scheme resulted in negative rainfall biases, especially over the Limpopo Province. In terms of rain rate, the KF scheme generated the lowest number of low rain rates and the maximum number of moderate to high rain rates associated with more convective unstable environment. KF and GDE schemes overestimated the convective rain and underestimated the stratiform rain. However, the simulated convective and stratiform rain with BMJ scheme is in more agreement with the observations. This study also documents the performance of regional model in downscaling the large scale climate mode such as El Niño Southern Oscillation (ENSO) and subtropical dipole modes. The correlations between the simulated area averaged rainfalls over South Africa and Nino3.4 index were ?0.66, ?0.69 and ?0.49 with KF, BMJ and GDE scheme respectively as compared to the observed correlation of ?0.57. The model could reproduce the observed ENSO-South Africa rainfall relationship and could successfully simulate three wet (dry) years that are associated with La Niña (El Niño) and the BMJ scheme is closest to the observed variability. Also, the model showed good skill in simulating the excess rainfall over South Africa that is associated with positive subtropical Indian Ocean Dipole for the DJF season 2005/2006.     

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.     

中国夏季不同强度降水模拟对不同积云对流参数化方案的敏感性研究

利用PσRCM9区域气候模式, 分析了中国夏季不同强度降水模拟对不同积云对流参数化方案的敏感性。结果表明, 采用四种积云对流参数化方案, 模式能够模拟出小雨、 大雨和暴雨的雨量百分比和雨日百分比空间分布的一致性特征, 但不能模拟出中雨雨量百分比和雨日百分比空间分布的相似性, 这是由于模式不能模拟中雨雨量百分比的空间分布形式所致。还发现模拟的我国夏季降水以小雨和中雨为主, 四种积云对流参数化方案均低估了中国夏季大雨和暴雨对总降水的贡献, 尤其是在我国西部、 东北和华北地区更明显。不同积云对流参数化方案下模拟的极端强降水阈值的空间分布形式基本与观测一致, 但强度与观测存在较大差异。相比较而言, Grell方案较Kuo、 Anthes-Kuo和Betts-Mille积云对流参数化方案更适合中国东南部地区夏季极端强降水的模拟。