Réf. Schwierz & al. 2010 - A

Référence bibliographique complète

SCHWIERZ, C., KÖLLNER-HECK, P., ZENKLUSEN MUTTER, E., BRESCH, D.N., VIDALE, P.L., WILD, M., SCHÄR, C. 2010. Modelling European winter wind storm losses in current and future climate. Climatic Change, Vol. 101, 485–514. [Etude en ligne]

Abstract: Severe wind storms are one of the major natural hazards in the extratropics and inflict substantial economic damages and even casualties. Insured storm-related losses depend on (i) the frequency, nature and dynamics of storms, (ii) the vulnerability of the values at risk, (iii) the geographical distribution of these values, and (iv) the particular conditions of the risk transfer. It is thus of great importance to assess the impact of climate change on future storm losses. To this end, the current study employs—to our knowledge for the first time—a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base. The climate models considered agree regarding an increase in the intensity of extreme storms in a band across central Europe (stretching from southern UK and northern France to Denmark, northern Germany into eastern Europe). This effect increases with event strength, and rare storms show the largest climate change sensitivity, but are also beset with the largest uncertainties. Wind gusts decrease over northern Scandinavia and Southern Europe. Highest intra-ensemble variability is simulated for Ireland, the UK, the Mediterranean, and parts of Eastern Europe. The resulting changes on European-wide losses over the 110-year period are positive for all layers and all model runs considered and amount to 44% (annual expected loss), 23% (10 years loss), 50% (30 years loss), and 104% (100 years loss). There is a disproportionate increase in losses for rare high-impact events. The changes result from increases in both severity and frequency of wind gusts. Considerable geographical variability of the expected losses exists, with Denmark and Germany experiencing the largest loss increases (116% and 114%, respectively). All countries considered except for Ireland (−22%) experience some loss increases. Some ramifications of these results for the socio-economic sector are discussed, and future avenues for research are highlighted. The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.

Mots-clés

 

 

Organismes / Contact

• Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland (schwierz@stat.math.ethz.ch)
Swiss Reinsurance Company, Zürich, Switzerland
Federal Office for the Environment, Berne, Switzerland
Seminar for Statistics, ETH Zürich, Zürich, Switzerland
• WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland
• NCAS-Climate, Reading University, Reading, UK

 

(1) - Paramètre(s) atmosphérique(s) modifié(s)

(2) - Elément(s) du milieu impacté(s)

(3) - Type(s) d'aléa impacté(s)

(3) - Sous-type(s) d'aléa

 Vent

 

 Tempêtes et pertes économiques associées

 

 

Pays / Zone

Massif / Secteur

Site(s) d'étude

Exposition

Altitude

Période(s) d'observation

 Europe

 

 

 

 

 

 

(1) - Modifications des paramètres atmosphériques

Reconstitutions

 

Observations

 

Modélisations

 

Hypothèses

 

 

Informations complémentaires (données utilisées, méthode, scénarios, etc.)

 

 

(2) - Effets du changement climatique sur le milieu naturel

Reconstitutions

 

Observations

 

Modélisations

 

Hypothèses

 

 

Sensibilité du milieu à des paramètres climatiques

Informations complémentaires (données utilisées, méthode, scénarios, etc.)

 

 

 

(3) - Effets du changement climatique sur l'aléa

Reconstitutions

 

Observations

 

Modélisations

This study has explored for the first time the coupling of a regional multi-model climate ensemble to a probabilistic operational insurance model. It produced dynamically meaningful and economically viable estimates of expected changes to insured losses and return periods on the European scale, with regional resolution.

The main findings of this study are:

– Mean gusts of the CTL runs correspond very well to the downscaled ERA40-verification, and the magnitudes are 2–3 times higher than in a GCM alone. Downscaling is thought to be important since a small improvement in the quality of wind data can dramatically increase the accuracy of the damage model (Watson and Johnson 2004), and the sensitivity of the insurance model’s vulnerability function to the wind speed is extremely large.

– Changing the driving GCM has more impact on the spread of the ensemble gust speeds than different versions of regional models. This might be partly caused by the fact that both RCMs use the same gust parametrization. Hence the regional model variability might still be underestimated.

– Projected climate change of wind gusts are consistent within the small ensemble, both in terms of pattern and amplitude. Consistent with existing studies, the strength of the extreme storms are expected to increase in a band across central Europe (southern UK, German bight, northern Germany, and into eastern Europe). The increase is stronger for the rarer events. Wind gusts of storms decrease over northern Scandinavia and Southern Europe and the Mediterranean.

– The probabilistic derivation of the climate change impact offers the novel possibility to estimate return periods of insured losses from climate change scenarios. The changes in the patterns of the 10−, 30−, and 100-year storm gusts and the wind climatologies closely correspond. The rare events show the largest climate change impact, but are also beset with the largest uncertainties (see below). Most intra-ensemble variability is observed for Ireland and the UK, the Mediterranean, and parts of Eastern Europe.

– The resulting changes on losses over the 110-year period considered are positive for all layers and all model runs considered. A mean increase of 44% (annual expected loss); 23% (10 years loss); 50% (30 years loss); 104% (100 years loss) for Europe ensues. Also there is a disproportionate increase inlosses for rare, extreme events. The changes result from both, an increase in severity and frequency of the selected storm events.

– A large country-to-country variability of the expected losses exists, due to the combination of the spatially inhomogeneous portfolio and the horizontal variability of the gust change. Denmark and Germany experience the largest relative loss increases (116% and 114%, respectively, with small inter-model variability), whereas Ireland shows a negative mean climate change impact. The changes for the UK, Switzerland and Norway are positive, but still inconclusive due to high ensemble variability.

Rare events In the introduction [the authors] have discussed that single events dominate the yearly loss amounts caused by European winter storms. This property implies intrinsic difficulties in the detection of damage trends, be it in the past or future. Hence the impact of climate change on winter storms is difficult to detect in statistical terms, as the underlying trend will be distorted by rare, randomly occurring events, or by the fortuitous absence of catastrophic events. Indeed, a systematic analysis of the issue shows that the probability to detect trends of rare events decreases with the size of the event (Frei and Schär 2001). Thus, the chances to detect the projected trend in wind storms are highest for moderate events, while the expected impacts in terms of damages are highest in the category of extremely rare exceptional events. This highlights a difficult dilemma, and suggests that the course of wind damages in Europe for the next decades will likely remain to be dominated by rare events and interannual variability.

Hypothèses

 

 

Paramètre de l'aléa

Sensibilité des paramètres de l'aléa à des paramètres climatiques

Informations complémentaires (données utilisées, méthode, scénarios, etc.)

 

 

This study employs a coupled approach, using output from high-resolution regional climate model scenarios for the European sector to drive an operational insurance loss model. An ensemble of coupled climate-damage scenarios is used to provide an estimate of the inherent uncertainties. Output of two state-of-the-art global climate models (HadAM3, ECHAM5) is used for present (1961–1990) and future climates (2071–2100, SRES A2 scenario). These serve as boundary data for two nested regional climate models with a sophisticated gust parametrizations (CLM, CHRM). For validation and calibration purposes, an additional simulation is undertaken with the CHRM driven by the ERA40 reanalysis. The operational insurance model (Swiss Re) uses a European-wide damage function, an average vulnerability curve for all risk types, and contains the actual value distribution of a complete European market portfolio. The coupling between climate and damage models is based on daily maxima of 10 m gust winds, and the strategy adopted consists of three main steps: (i) development and application of a pragmatic selection criterion to retrieve significant storm events, (ii) generation of a probabilistic event set using a Monte-Carlo approach in the hazard module of the insurance model, and (iii) calibration of the simulated annual expected losses with a historic loss data base.

 

(4) - Remarques générales

Socio-economic implications Although there is evidence for a positive trend in European wind storm losses from our study, it is likely that no clear trend will be detectable with significance in the next few years, and indeed a great challenge will be avoiding a false sense of security. Some statements for policy makers and stakeholders arise.

Today’s economy would not function without effective and efficient mechanisms to transfer risk. Insurers and reinsurers play a key role in this process. In order for the sector to remain a reliable risk taker in future, changes in the risk landscape have to be identified and communicated at an early stage. In order to write business sustainably, impacts of climate change have to be systematically integrated into the risk assessment and management processes of the insurance industry. The risk premium which is the basis for the insurance premium, must reflect the changes in exposure, and the increased risk must be reflected in capital and capacity steering models.

Underwriting adjustments are however only part of the solution. An optimal outcome is achievable only through devoting significant effort to mitigate the impact of natural catastrophes. It is in the interest of all stakeholders, including insurers to create incentives for clients to implement protective changes and structural modifications for their properties. Preventive building maintenance can considerably reduce storm damage.

In conclusion, it should be noted that while the insurance industry is an important contributor, the climate question cannot be answered by one stakeholder group alone. It needs the participation of all relevant societal, political and economic stakeholders. New, sustainable and effective protection measures need to be taken, to reduce the loss burden, including those that involve politics and society. These measures range from global climate protection, with the reduction of greenhouse gas emissions, cutting back on energy consumption, and the development of new, environmentally friendly technologies; to mitigation and to the adaptation to extreme events. Examples are the protection of objects, including constructive measures, appropriate land-use planning and construction standards, risk and catastrophe management (early warning systems). It is only through combined efforts that the challenges of climate change can be met adequately.

The technique introduced in this study and its application to realistic market portfolios offer exciting prospects for future research on the impact of climate change that is relevant for policy makers, scientists and economists.

 

(5) - Syntèses et préconisations

 

Références citées :

Frei C, Schär C (2001) Detection probability of trends in rare events: theory and application to heavy precipitation in the Alpine region. J Climate 14:1568–1584