Accessing Insurance Flood Losses Using a Catastrophe Model and Climate Change Scenarios

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F22%3A10454804" target="_blank" >RIV/00216208:11310/22:10454804 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21110/22:00358423

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=p5Bu2xqPhV" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=p5Bu2xqPhV</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/cli10050067" target="_blank" >10.3390/cli10050067</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Accessing Insurance Flood Losses Using a Catastrophe Model and Climate Change Scenarios

Popis výsledku v původním jazyce

Impact Forecasting has developed a catastrophe flood model for Czechia to estimate insurance losses. The model is built on a dataset of 12,066 years of daily rainfall and temperature data for the European area, representing the current climate (LAERTES-EU). This dataset was used as input to the rainfall-runoff model, resulting in a series of daily river channel discharges. Using analyses of global and regional climate models dealing with the impacts of climate change, this dataset was adjusted for the individual RCP climate scenarios in Europe. The river channel discharges were then re-derived using the already calibrated rainfall-runoff models. Based on the changed discharges, alternative versions of the standard catastrophe flood model for the Czechia were created for the various climate scenarios. In outputs, differences in severity, intensity, and number of events might be observed, as well as the size of storms. The effect on the losses might be investigated by probable maximum losses (PML) curves and average annual loss (AAL) values. For return period 1 in 5 years for the worst-case scenario, the differences can be up to +125 percent increase in insurance losses, while for the return period 1 in 100 years it is a -40 percent decrease. There is no significant effect of adaptation measures for the return period 1 in 100 years, but there is a -20 percent decrease in the return period 1 in 5 years.

Název v anglickém jazyce

Accessing Insurance Flood Losses Using a Catastrophe Model and Climate Change Scenarios

Popis výsledku anglicky

Impact Forecasting has developed a catastrophe flood model for Czechia to estimate insurance losses. The model is built on a dataset of 12,066 years of daily rainfall and temperature data for the European area, representing the current climate (LAERTES-EU). This dataset was used as input to the rainfall-runoff model, resulting in a series of daily river channel discharges. Using analyses of global and regional climate models dealing with the impacts of climate change, this dataset was adjusted for the individual RCP climate scenarios in Europe. The river channel discharges were then re-derived using the already calibrated rainfall-runoff models. Based on the changed discharges, alternative versions of the standard catastrophe flood model for the Czechia were created for the various climate scenarios. In outputs, differences in severity, intensity, and number of events might be observed, as well as the size of storms. The effect on the losses might be investigated by probable maximum losses (PML) curves and average annual loss (AAL) values. For return period 1 in 5 years for the worst-case scenario, the differences can be up to +125 percent increase in insurance losses, while for the return period 1 in 100 years it is a -40 percent decrease. There is no significant effect of adaptation measures for the return period 1 in 100 years, but there is a -20 percent decrease in the return period 1 in 5 years.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10508 - Physical geography

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Climate [online]

ISSN

2225-1154

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

21

Strana od-do

67

Kód UT WoS článku

000801692000001

EID výsledku v databázi Scopus

2-s2.0-85130409624