Communicating adaptation with emotions : the role of intense experiences for concern about extreme weather

Adaptation to extreme weather is often considered as having a low urgency and being a low priority governance option, even though the intensity of extreme weather events is expected to increase as a result of climate change. An important issue is how to raise an adequate level of concern among individuals, policy makers, and broader decision makers in companies and organizations so that adaptation to extreme events becomes mainstream practice. We conducted 40 indepth interviews with individuals from different sectors in The Netherlands to identify the different types of experiences with extreme events, as well as the relationship between such experiences and the level of concern about extreme weather. Our results indicate that individuals who have experienced an intense, life-threatening event have a significantly higher level of concern than those without such an experience. Professional experience and secondhand experience through participating in information events do not significantly affect the level of concern about extreme events. This suggests limited intervention possibilities for communication of adaptation, as well as for raising support for adaptation measures. Framing adaptation measures in relation to personal circumstances and emotions during extreme events could help raise concern about extreme weather events, as well as societal support for adaptation measures

Uncovering the veil of night light changes in times of catastrophe

Natural disasters have large social and economic consequences. However, adequate economic and social data to study subnational economic effects of these negative shocks are typically difficult to obtain especially in low-income countries. For this reason, the use of night light data is becoming increasingly popular in studies which aim to estimate the impacts of natural disasters on local economic activity. However, it is often unclear what observed changes in night lights represent exactly. In this paper, we examine how changes in night light emissions following a severe hurricane relate with local population, employment, and income statistics. We do so for the case of Hurricane Katrina, which struck the coastline of Louisiana and Mississippi in August 2005. Hurricane Katrina is an excellent case for this purpose as it is one of the biggest hurricanes in recent history in terms of human and economic impacts, it made landfall in a country with high-quality sub-national socioeconomic data collection, and it is covered extensively in the academic literature. We find that overall night light changes reflect the general pattern of direct impacts of Katrina as well as indirect impacts and subsequent population and economic recovery. Our results suggest that change in light intensity is mostly reflective of changes in resident population and the total number of employed people within the affected area and less so but positively related to aggregate income and real GDP.</p

Social vulnerability in cost-benefit analysis for flood risk management

Traditional cost-benefit analyses (CBAs) of flood risk reduction measures usually ignore distributions of damages over populations, which disadvantages the poor. Instead, a CBA based on social welfare includes individual social vulnerability through relative impacts on consumption. If vulnerabilities are high, floods are catastrophic and cause poverty, migration or indirect deaths, and risk reductions have high social welfare values. For non-catastrophic risks, social welfare values of risks are relatively higher for vulnerable low-income households. We present a framework to integrate social vulnerability into CBAs, and show how financial protection reduces social flood vulnerability and provides welfare benefits. A case study illustrates that traditional CBAs underestimate the social welfare value of flood risk reduction measures, up to a factor of 30. Data on financial protection is however scarce, which hampers estimation of the social welfare value in practice. A solution is to increase financial protection of individuals, in addition to offering physical flood protection

The Assessment of Impacts and Risks of Climate Change on Agriculture (AIRCCA) model:a tool for the rapid global risk assessment for crop yields at a spatially explicit scale

A main channel through which climate change is expected to affect the economy is the agricultural sector. Large spatial variability in these impacts and high levels of uncertainty in climate change projections create methodological challenges for assessing the consequences this sector could face. Crop emulators based on econometric fixed-effects models that can closely reproduce biophysical models are estimated. With these reduced form crop emulators, we develop AIRCCA, a user-friendly software for the assessment of impacts and risks of climate change on agriculture, that allows stakeholders to make a rapid global assessment of the effects of climate change on maize, wheat and rice yields. AIRCCA produces spatially explicit probabilistic impact scenarios and user-defined risk metrics for the main four Intergovernmental Panel on Climate Change’s (IPCC) emissions scenarios

Impacts of climate change and remote natural catastrophes on EU flood insurance markets:An analysis of soft and hard reinsurance markets for flood coverage

The increasing frequency and severity of natural catastrophes due to climate change is expected to cause higher natural disaster losses in the future. Reinsurance companies bear a large share of this risk in the form of excess-of-loss coverage, where they underwrite the most extreme portion of insurers' risk portfolios. Past experience has shown that after a very large natural disaster, or multiple disasters in close succession, the recapitalization need of reinsurers could trigger a "hard" reinsurance capital market, where a high demand for capital increases the price charged by investors, which is opposed to a "soft" market, where there is a high availability of capital for reinsurers. Consequently, the rising costs of underwriting are transferred to insurers, which ultimately could trigger higher premiums for natural catastrophe (NatCat) insurance worldwide. Here, we study the vulnerability of riverine flood insurance systems in the EU to global reinsurance market conditions and climate change. To do so, we apply the "Dynamic Integrated Flood Insurance" (DIFI) model, and compare insurance premiums, unaffordability, and the uptake for soft and hard reinsurance market conditions under an average and extreme scenario of climate change. We find that a rising average and higher variance of flood risk towards the end of the century can increase flood insurance premiums and cause higher premium volatility resulting from global reinsurance market conditions. Under a "mild" scenario of climate change, the projected yearly premiums for EU countries, combined, are ¿1380 higher under a hard compared to a soft reinsurance capital market in 2080. For a high-end climate change scenario, this difference becomes ¿3220. The rise in premiums causes problems with the unaffordability of flood coverage and results in a declining demand for flood insurance, which increases the financial vulnerability of households to flooding. A proposed solution is to introduce government reinsurance for flood risk, as governments can often provide cheaper reinsurance coverage and are less subject to the volatility of the capital markets

Low-carbon transition is improbable without carbon pricing

Unidad de excelencia María de Maeztu CEX2019-000940-MThis Letter has a Reply and related content. Please see: Reply to van den Bergh and Botzen: A clash of paradigms over the role of carbon pricing (https://doi.org/10.1073/pnas.2014350117) - Opinion: Why carbon pricing is not sufficient to mitigate climate change-and how "sustainability transition policy" can help (https://doi.org/10.1073/pnas.2004093117)

Behavioral motivations for self-insurance under different disaster risk insurance schemes

This paper presents a lab-in-the-field experiment with 2111 Dutch homeowners in floodplain areas to examine the impacts of financial incentives and behavioral motivations for self-insurance under different flood insurance schemes. We experimentally varied the insurance type (mandatory public versus voluntary private) and the availability of a premium discount incentive for investing in flood damage mitigation measures. This set-up allowed us to examine the existence of moral hazard, advantageous selection and the behavioral motivations of individual agents who face these different insurance types, without the selection bias that makes a causal inference from survey studies problematic. The main results show that a premium discount can increase investments in self-insurance under both private and public insurance. Moreover, we find no support for moral hazard in our natural disaster insurance market, but we do find a substantial share of cautious people who invest both in private insurance as well as in self-insurance, indicating advantageous selection. The results have implications for the design of insurance schemes to cope with increasing natural disaster risks

Methodological issues in natural disaster loss normalization studies

The mixed results in Pielke (2020) for natural disaster loss normalisation studies are due to methodological differences. Flaws exist in commonly used normalisation approaches that assume unitary elasticities between exposure indicators and losses. We refute Pielke’s arguments that statistical studies estimating these relationships are biased. We conclude with an agenda for future research

Risk allocation in a public-private catastrophe insurance system:an actuarial analysis of deductibles, stop-loss, and premiums

A public-private (PP) partnership could be a viable arrangement for providing insurance coverage for catastrophe events, such as floods and earthquakes. The objective of this paper is to obtain insights into efficient and practical allocations of risk in a PP insurance system. In particular, this study examines how the deductible and stop-loss levels (retentions) for, respectively, the insured and the insurer, relate to the corresponding maximum required coverage and premium amounts under the 99.9% tail value at risk (TVaR) damage constraint. A practical example of flood insurance in the Netherlands is studied in which the (re)insurance could be provided either by a risk-averse (private) or a risk-neutral (public) agency, which could result in large differences in premiums