TY - JOUR
T1 - Historical weather data for climate risk assessment
AU - Brönnimann, Stefan
AU - Martius, Olivia
AU - Rohr, Christian
AU - Bresch, David N.
AU - Lin, Kuan Hui Elaine
N1 - Publisher Copyright:
© 2018 New York Academy of Sciences.
PY - 2019/1
Y1 - 2019/1
N2 - Weather- and climate-related hazards are responsible for monetary losses, material damages, and societal consequences. Quantifying related risks is, therefore, an important societal task, particularly in view of future climate change. For this task, climate risk assessment increasingly uses model chains, which mainly build on data from the last few decades. The past record of events could play a role in this context. New numerical techniques can make use of historical weather data to simulate impacts quantitatively. However, using historical data for model applications differs from using recent products. Here, we provide an overview of climate risk assessment methodologies and of the properties of historical instrumental and documentary data. Using three examples, we then outline how historical environmental data can be used today in climate risk assessment by (1) developing and validating numerical model chains, (2) providing a large statistical sample which can be directly exploited to estimate hazards and to model present risks, and (3) establishing “worst-case” events which are relevant references in the present or future. The examples show that, in order to be successful, different sources (reanalyses, digitized instrumental data, and documentary data) and methods (dynamical downscaling and analog methods) need to be combined on a case-by-case basis.
AB - Weather- and climate-related hazards are responsible for monetary losses, material damages, and societal consequences. Quantifying related risks is, therefore, an important societal task, particularly in view of future climate change. For this task, climate risk assessment increasingly uses model chains, which mainly build on data from the last few decades. The past record of events could play a role in this context. New numerical techniques can make use of historical weather data to simulate impacts quantitatively. However, using historical data for model applications differs from using recent products. Here, we provide an overview of climate risk assessment methodologies and of the properties of historical instrumental and documentary data. Using three examples, we then outline how historical environmental data can be used today in climate risk assessment by (1) developing and validating numerical model chains, (2) providing a large statistical sample which can be directly exploited to estimate hazards and to model present risks, and (3) establishing “worst-case” events which are relevant references in the present or future. The examples show that, in order to be successful, different sources (reanalyses, digitized instrumental data, and documentary data) and methods (dynamical downscaling and analog methods) need to be combined on a case-by-case basis.
KW - climate data
KW - climate risk
KW - extreme events
KW - historical data
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U2 - 10.1111/nyas.13966
DO - 10.1111/nyas.13966
M3 - Review article
C2 - 30291628
AN - SCOPUS:85054526246
SN - 0077-8923
VL - 1436
SP - 121
EP - 137
JO - Annals of the New York Academy of Sciences
JF - Annals of the New York Academy of Sciences
IS - 1
ER -