A toolkit for climate change analysis and pattern recognition for extreme weather conditions – Case study: California-Baja California Peninsula. (October 2017)
- Record Type:
- Journal Article
- Title:
- A toolkit for climate change analysis and pattern recognition for extreme weather conditions – Case study: California-Baja California Peninsula. (October 2017)
- Main Title:
- A toolkit for climate change analysis and pattern recognition for extreme weather conditions – Case study: California-Baja California Peninsula
- Authors:
- Ashraf Vaghefi, Saeid
Abbaspour, Nazanin
Kamali, Bahareh
Abbaspour, Karim C. - Abstract:
- Abstract: This paper describes the development of a Climate Change Toolkit (CCT) to perform tasks needed in a climate change study plus projection of extreme weather conditions by analyzing historical weather patterns. CCT consists of Data Extraction, Global Climate Data Management, Bias Correction and Statistical Downscaling, Spatial Interpolation, and Critical Consecutive Day Analyzer (CCDA). CCDA uses a customized data mining approach to recognize spatial and temporal patterns of extreme events. CCT is linked to an archive of 0.5° historical global daily dataset (CRU, 1970–2005), and GCM data (1960–2099) for five models and four carbon scenarios. Application of CCT in California using ensemble results of scenario RCP8.5 showed a probable increase in the frequency of dry periods in the southern part of the region, while decreasing in the north. The frequency of wet periods may suggest higher risks of flooding in the north and coastal strips. We further found that every county in northern California may experience flooding conditions of 1986 at least once between 2020 and 2050. Highlights: Develop a software to consider important tasks of climate change studies in one package. Development of a program to consider more than one variable (precipitation, temperature, and soil moisture) in analyzing extreme events. Development of a program that can use historical flooding conditions to determine the probability of their future occurrences.
- Is Part Of:
- Environmental modelling & software. Volume 96(2017)
- Journal:
- Environmental modelling & software
- Issue:
- Volume 96(2017)
- Issue Display:
- Volume 96, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 96
- Issue:
- 2017
- Issue Sort Value:
- 2017-0096-2017-0000
- Page Start:
- 181
- Page End:
- 198
- Publication Date:
- 2017-10
- Subjects:
- Big data -- Customized data mining -- Bias correction and statistical downscaling -- Spatial interpolation -- Critical consecutive days analyzer -- Extreme events -- ISI-MIP
Environmental monitoring -- Computer programs -- Periodicals
Ecology -- Computer simulation -- Periodicals
Digital computer simulation -- Periodicals
Computer software -- Periodicals
Environmental Monitoring -- Periodicals
Computer Simulation -- Periodicals
Environnement -- Surveillance -- Logiciels -- Périodiques
Écologie -- Simulation, Méthodes de -- Périodiques
Simulation par ordinateur -- Périodiques
Logiciels -- Périodiques
Computer software
Digital computer simulation
Ecology -- Computer simulation
Environmental monitoring -- Computer programs
Periodicals
Electronic journals
363.70015118 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13648152 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.envsoft.2017.06.033 ↗
- Languages:
- English
- ISSNs:
- 1364-8152
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - 3791.522800
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