Literature DB >> 30291628

Historical weather data for climate risk assessment.

Stefan Brönnimann1,2, Olivia Martius1,2,3, Christian Rohr1,4, David N Bresch5,6, Kuan-Hui Elaine Lin7.   

Abstract

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.
© 2018 New York Academy of Sciences.

Keywords:  climate data; climate risk; extreme events; historical data

Mesh:

Year:  2018        PMID: 30291628     DOI: 10.1111/nyas.13966

Source DB:  PubMed          Journal:  Ann N Y Acad Sci        ISSN: 0077-8923            Impact factor:   5.691


  2 in total

1.  Construction of the REACHES climate database based on historical documents of China.

Authors:  Pao K Wang; Kuan-Hui Elaine Lin; Yi-Chun Liao; Hsiung-Ming Liao; Yu-Shiuan Lin; Ching-Tzu Hsu; Shih-Ming Hsu; Chih-Wei Wan; Shih-Yu Lee; I-Chun Fan; Pei-Hua Tan; Te-Tien Ting
Journal:  Sci Data       Date:  2018-12-18       Impact factor: 6.444

2.  A millennium-long reconstruction of damaging hydrological events across Italy.

Authors:  Nazzareno Diodato; Fredrik Charpentier Ljungqvist; Gianni Bellocchi
Journal:  Sci Rep       Date:  2019-07-10       Impact factor: 4.379

  2 in total

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