Simulation of economic losses from tropical cyclones in the years 2015 and 2050: the effects of anthropogenic climate change and growing wealth
This paper simulates the increase in the average annual loss from tropical cyclones in the North Atlantic for the years 2015 and 2050. The simulation is based on assumptions concerning wealth trends in the regions affected by the storms, considered by the change in material assets (capital stock). F...
Main Authors: | , , |
---|---|
Format: | Report |
Language: | English |
Published: |
Berlin: Deutsches Institut für Wirtschaftsforschung (DIW)
2009
|
Subjects: | |
Online Access: | https://www.econstor.eu/bitstream/10419/29735/1/608201324.pdf |
id |
ftleibnizopen:oai:oai.leibnizopen.de:iJJR04kBdbrxVwz6G-4V |
---|---|
record_format |
openpolar |
spelling |
ftleibnizopen:oai:oai.leibnizopen.de:iJJR04kBdbrxVwz6G-4V 2023-10-01T03:57:59+02:00 Simulation of economic losses from tropical cyclones in the years 2015 and 2050: the effects of anthropogenic climate change and growing wealth Schmidt, Silvio Kemfert, Claudia Faust, Eberhard 2009 https://www.econstor.eu/bitstream/10419/29735/1/608201324.pdf eng eng Berlin: Deutsches Institut für Wirtschaftsforschung (DIW) http://www.econstor.eu/dspace/Nutzungsbedingungen Klimaveränderung Sturm Soziale Kosten Versicherungsschaden Prognose Simulation Wahrscheinlichkeitsrechnung USA Climate change tropical cyclones natural catastrophes insurance Working Paper 2009 ftleibnizopen 2023-09-03T23:28:19Z This paper simulates the increase in the average annual loss from tropical cyclones in the North Atlantic for the years 2015 and 2050. The simulation is based on assumptions concerning wealth trends in the regions affected by the storms, considered by the change in material assets (capital stock). Further assumptions are made about the trend in storm intensity resulting from anthropogenic climate change. The simulations use a stochastic model that models the annual storm loss from the number of storms and the loss per storm event. The paper demonstrates that increasing wealth will continue to be the principle loss driver in the future (average annual loss in 2015 +32%, in 2050 +308%). But climate change will also lead to higher losses (average annual loss in 2015 +4%, in 2050 +11%). In order to reduce the uncertainties surrounding the assumptions on the trend in capital stock and storm intensity, a sensitivity analysis was carried out, based on the assumptions from current studies on the future costs for tropical storms. Report North Atlantic LeibnizOpen (The Leibniz Association) Sturm ENVELOPE(162.967,162.967,-71.050,-71.050) |
institution |
Open Polar |
collection |
LeibnizOpen (The Leibniz Association) |
op_collection_id |
ftleibnizopen |
language |
English |
topic |
Klimaveränderung Sturm Soziale Kosten Versicherungsschaden Prognose Simulation Wahrscheinlichkeitsrechnung USA Climate change tropical cyclones natural catastrophes insurance |
spellingShingle |
Klimaveränderung Sturm Soziale Kosten Versicherungsschaden Prognose Simulation Wahrscheinlichkeitsrechnung USA Climate change tropical cyclones natural catastrophes insurance Schmidt, Silvio Kemfert, Claudia Faust, Eberhard Simulation of economic losses from tropical cyclones in the years 2015 and 2050: the effects of anthropogenic climate change and growing wealth |
topic_facet |
Klimaveränderung Sturm Soziale Kosten Versicherungsschaden Prognose Simulation Wahrscheinlichkeitsrechnung USA Climate change tropical cyclones natural catastrophes insurance |
description |
This paper simulates the increase in the average annual loss from tropical cyclones in the North Atlantic for the years 2015 and 2050. The simulation is based on assumptions concerning wealth trends in the regions affected by the storms, considered by the change in material assets (capital stock). Further assumptions are made about the trend in storm intensity resulting from anthropogenic climate change. The simulations use a stochastic model that models the annual storm loss from the number of storms and the loss per storm event. The paper demonstrates that increasing wealth will continue to be the principle loss driver in the future (average annual loss in 2015 +32%, in 2050 +308%). But climate change will also lead to higher losses (average annual loss in 2015 +4%, in 2050 +11%). In order to reduce the uncertainties surrounding the assumptions on the trend in capital stock and storm intensity, a sensitivity analysis was carried out, based on the assumptions from current studies on the future costs for tropical storms. |
format |
Report |
author |
Schmidt, Silvio Kemfert, Claudia Faust, Eberhard |
author_facet |
Schmidt, Silvio Kemfert, Claudia Faust, Eberhard |
author_sort |
Schmidt, Silvio |
title |
Simulation of economic losses from tropical cyclones in the years 2015 and 2050: the effects of anthropogenic climate change and growing wealth |
title_short |
Simulation of economic losses from tropical cyclones in the years 2015 and 2050: the effects of anthropogenic climate change and growing wealth |
title_full |
Simulation of economic losses from tropical cyclones in the years 2015 and 2050: the effects of anthropogenic climate change and growing wealth |
title_fullStr |
Simulation of economic losses from tropical cyclones in the years 2015 and 2050: the effects of anthropogenic climate change and growing wealth |
title_full_unstemmed |
Simulation of economic losses from tropical cyclones in the years 2015 and 2050: the effects of anthropogenic climate change and growing wealth |
title_sort |
simulation of economic losses from tropical cyclones in the years 2015 and 2050: the effects of anthropogenic climate change and growing wealth |
publisher |
Berlin: Deutsches Institut für Wirtschaftsforschung (DIW) |
publishDate |
2009 |
url |
https://www.econstor.eu/bitstream/10419/29735/1/608201324.pdf |
long_lat |
ENVELOPE(162.967,162.967,-71.050,-71.050) |
geographic |
Sturm |
geographic_facet |
Sturm |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_rights |
http://www.econstor.eu/dspace/Nutzungsbedingungen |
_version_ |
1778530277993218048 |