Copulas for hydroclimatic analysis: A practice‐oriented overview

A warming climate is associated with increasing hydroclimatic extremes, which are often interconnected through complex processes, prompting their concurrence and/or succession, and causing compound extreme events. It is critical to analyze the risks of compound events, given their disproportionately...

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Published inWiley interdisciplinary reviews. Water Vol. 9; no. 2; pp. e1579 - n/a
Main Authors Tootoonchi, Faranak, Sadegh, Mojtaba, Haerter, Jan Olaf, Räty, Olle, Grabs, Thomas, Teutschbein, Claudia
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 01.03.2022
Wiley Subscription Services, Inc
Subjects
Confusion
copula
dependence
Distribution
Hazards
Hydrologi
Hydrology
Literature reviews
Mathematical functions
Methods
multivariate
Multivariate analysis
precipitation
Probability distribution
Probability theory
Risk analysis
Robustness (mathematics)
Statistical analysis
temperature
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Abstract A warming climate is associated with increasing hydroclimatic extremes, which are often interconnected through complex processes, prompting their concurrence and/or succession, and causing compound extreme events. It is critical to analyze the risks of compound events, given their disproportionately high adverse impacts. To account for the variability in two or more hydroclimatic variables (e.g., temperature and precipitation) and their dependence, a rising number of publications focuses on multivariate analysis, among which the notion of copula‐based probability distribution has attracted tremendous interest. Copula is a mathematical function that expresses the joint cumulative probability distribution of multiple variables. Our focus is to re‐emphasize the fundamental requirements and limitations of applying copulas. Confusion about these requirements may lead to misconceptions and pitfalls, which can potentially compromise the robustness of risk analyses for environmental processes and natural hazards. We conducted a systematic literature review of copulas, as a prominent tool in the arsenal of multivariate methods used for compound event analysis, and underpinned them with a hydroclimatic case study in Sweden to illustrate a practical approach to copula‐based modeling. Here, we (1) provide end‐users with a didactic overview of necessary requirements, statistical assumptions and consequential limitations of copulas, (2) synthesize common perceptions and practices, and (3) offer a user‐friendly decision support framework to employ copulas, thereby support researchers and practitioners in addressing hydroclimatic hazards, hence demystify what can be an area of confusion. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Methods Schematic visualization of the empirical two‐dimensional copula. In this article, we conducted a systematic literature review of copulas, and underpinned them with a hydroclimatic case study to illustrate a practical approach to copula‐based modeling. We offer a user‐friendly decision support framework to employ copulas in hydroclimatic research.
AbstractList A warming climate is associated with increasing hydroclimatic extremes, which are often interconnected through complex processes, prompting their concurrence and/or succession, and causing compound extreme events. It is critical to analyze the risks of compound events, given their disproportionately high adverse impacts. To account for the variability in two or more hydroclimatic variables (e.g., temperature and precipitation) and their dependence, a rising number of publications focuses on multivariate analysis, among which the notion of copula‐based probability distribution has attracted tremendous interest. Copula is a mathematical function that expresses the joint cumulative probability distribution of multiple variables. Our focus is to re‐emphasize the fundamental requirements and limitations of applying copulas. Confusion about these requirements may lead to misconceptions and pitfalls, which can potentially compromise the robustness of risk analyses for environmental processes and natural hazards. We conducted a systematic literature review of copulas, as a prominent tool in the arsenal of multivariate methods used for compound event analysis, and underpinned them with a hydroclimatic case study in Sweden to illustrate a practical approach to copula‐based modeling. Here, we (1) provide end‐users with a didactic overview of necessary requirements, statistical assumptions and consequential limitations of copulas, (2) synthesize common perceptions and practices, and (3) offer a user‐friendly decision support framework to employ copulas, thereby support researchers and practitioners in addressing hydroclimatic hazards, hence demystify what can be an area of confusion. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Methods
A warming climate is associated with increasing hydroclimatic extremes, which are often interconnected through complex processes, prompting their concurrence and/or succession, and causing compound extreme events. It is critical to analyze the risks of compound events, given their disproportionately high adverse impacts. To account for the variability in two or more hydroclimatic variables (e.g., temperature and precipitation) and their dependence, a rising number of publications focuses on multivariate analysis, among which the notion of copula‐based probability distribution has attracted tremendous interest. Copula is a mathematical function that expresses the joint cumulative probability distribution of multiple variables. Our focus is to re‐emphasize the fundamental requirements and limitations of applying copulas. Confusion about these requirements may lead to misconceptions and pitfalls, which can potentially compromise the robustness of risk analyses for environmental processes and natural hazards. We conducted a systematic literature review of copulas, as a prominent tool in the arsenal of multivariate methods used for compound event analysis, and underpinned them with a hydroclimatic case study in Sweden to illustrate a practical approach to copula‐based modeling. Here, we (1) provide end‐users with a didactic overview of necessary requirements, statistical assumptions and consequential limitations of copulas, (2) synthesize common perceptions and practices, and (3) offer a user‐friendly decision support framework to employ copulas, thereby support researchers and practitioners in addressing hydroclimatic hazards, hence demystify what can be an area of confusion. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Methods Schematic visualization of the empirical two‐dimensional copula. In this article, we conducted a systematic literature review of copulas, and underpinned them with a hydroclimatic case study to illustrate a practical approach to copula‐based modeling. We offer a user‐friendly decision support framework to employ copulas in hydroclimatic research.
A warming climate is associated with increasing hydroclimatic extremes, which are often interconnected through complex processes, prompting their concurrence and/or succession, and causing compound extreme events. It is critical to analyze the risks of compound events, given their disproportionately high adverse impacts. To account for the variability in two or more hydroclimatic variables (e.g., temperature and precipitation) and their dependence, a rising number of publications focuses on multivariate analysis, among which the notion of copula‐based probability distribution has attracted tremendous interest. Copula is a mathematical function that expresses the joint cumulative probability distribution of multiple variables. Our focus is to re‐emphasize the fundamental requirements and limitations of applying copulas. Confusion about these requirements may lead to misconceptions and pitfalls, which can potentially compromise the robustness of risk analyses for environmental processes and natural hazards. We conducted a systematic literature review of copulas, as a prominent tool in the arsenal of multivariate methods used for compound event analysis, and underpinned them with a hydroclimatic case study in Sweden to illustrate a practical approach to copula‐based modeling. Here, we (1) provide end‐users with a didactic overview of necessary requirements, statistical assumptions and consequential limitations of copulas, (2) synthesize common perceptions and practices, and (3) offer a user‐friendly decision support framework to employ copulas, thereby support researchers and practitioners in addressing hydroclimatic hazards, hence demystify what can be an area of confusion.This article is categorized under:Science of Water > Hydrological ProcessesScience of Water > Methods
A warming climate is associated with increasing hydroclimatic extremes, which are often interconnected through complex processes, prompting their concurrence and/or succession, and causing compound extreme events. It is critical to analyze the risks of compound events, given their disproportionately high adverse impacts. To account for the variability in two or more hydroclimatic variables (e.g., temperature and precipitation) and their dependence, a rising number of publications focuses on multivariate analysis, among which the notion of copula-based probability distribution has attracted tremendous interest. Copula is a mathematical function that expresses the joint cumulative probability distribution of multiple variables. Our focus is to re-emphasize the fundamental requirements and limitations of applying copulas. Confusion about these requirements may lead to misconceptions and pitfalls, which can potentially compromise the robustness of risk analyses for environmental processes and natural hazards. We conducted a systematic literature review of copulas, as a prominent tool in the arsenal of multivariate methods used for compound event analysis, and underpinned them with a hydroclimatic case study in Sweden to illustrate a practical approach to copula-based modeling. Here, we (1) provide end-users with a didactic overview of necessary requirements, statistical assumptions and consequential limitations of copulas, (2) synthesize common perceptions and practices, and (3) offer a user-friendly decision support framework to employ copulas, thereby support researchers and practitioners in addressing hydroclimatic hazards, hence demystify what can be an area of confusion.
Author Räty, Olle
Tootoonchi, Faranak
Haerter, Jan Olaf
Sadegh, Mojtaba
Grabs, Thomas
Teutschbein, Claudia
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2020; 10
2014; 132
2012; 14
2018; 45
2014; 23
2018; 6
2018; 9
2010; 24
1978; 65
2013; 57
2007; Risk Books
2008; 29
2019; 23
2019; 26
2013; 53
2019; 28
2009; 15
2009; 368
2018; 36
1992; 5
2004; 44
2018; 29
1979; 19
2019; 9
2004; 40
2006; 51
1996
2019; 223
1993
2012; 39
2008; 52
2014; 41
2007; 98
2007; 12
2020; 703
2018; 19
2017; 53
2003; 108
2012; 110
2006; 42
2016; 3
2010; 46
1904; 15
2019; 44
1947; 18
2006; 47
2009; 100
2016; 20
2005; 10
2020; 24
2008; 44
2012; 48
2007; 85
1985; 72
2005; 94
2020; 718
2018; 10
2019; 573
2019; 571
2021; 25
2009; 44
2012; 2012
2017; 3
2019; 52
2019; 55
2021; 249
2020; 58
2011; 15
2006; 138
2017; 112
2017; 114
1978; 8
2007; 137
2020; 6
2017; 31
2004; 73
2013; 17
2017; 37
2020; 139
2005; 32
2011; 26
2005; 37
1979; 65
2005; 33
2019; 472
2014; 514
2014; 119
2014; 512
2014; 238
1960; 55
2013; 49
2010
1993; 88
2011; 40
2013; 41
2008
2008; 15
2006
2006; 3
2003
2009; 372
2007; 51
2007; 56
1959
2014; 88
2020; 229
2015; 28
2012; 456–457
2015; 29
2017; 14
2021
2020
2004; 13
2019
2016
2015
2014
2013
2007; 43
1938; 30
2011; 189
2009; 37
2003; 65
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Snippet A warming climate is associated with increasing hydroclimatic extremes, which are often interconnected through complex processes, prompting their concurrence...
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SubjectTerms Confusion
copula
dependence
Distribution
Hazards
Hydrologi
Hydrology
Literature reviews
Mathematical functions
Methods
multivariate
Multivariate analysis
precipitation
Probability distribution
Probability theory
Risk analysis
Robustness (mathematics)
Statistical analysis
temperature
Title Copulas for hydroclimatic analysis: A practice‐oriented overview
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fwat2.1579
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Volume 9
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