Evaluation of probable maximum snow accumulation: Development of a methodology for climate change studies
•Climate change influences estimations of the probable maximum snow accumulation.•A deterministic moisture maximization technique is used to compute the PMSA.•Results depend rather on the simulation used than on the particular region. Probable maximum snow accumulation (PMSA) is one of the key varia...
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Veröffentlicht in: | Journal of hydrology (Amsterdam) 2016-06, Vol.537, p.74-85 |
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creator | Klein, Iris M. Rousseau, Alain N. Frigon, Anne Freudiger, Daphné Gagnon, Patrick |
description | •Climate change influences estimations of the probable maximum snow accumulation.•A deterministic moisture maximization technique is used to compute the PMSA.•Results depend rather on the simulation used than on the particular region.
Probable maximum snow accumulation (PMSA) is one of the key variables used to estimate the spring probable maximum flood (PMF). A robust methodology for evaluating the PMSA is imperative so the ensuing spring PMF is a reasonable estimation. This is of particular importance in times of climate change (CC) since it is known that solid precipitation in Nordic landscapes will in all likelihood change over the next century. In this paper, a PMSA methodology based on simulated data from regional climate models is developed. Moisture maximization represents the core concept of the proposed methodology; precipitable water being the key variable. Results of stationarity tests indicate that CC will affect the monthly maximum precipitable water and, thus, the ensuing ratio to maximize important snowfall events. Therefore, a non-stationary approach is used to describe the monthly maximum precipitable water.
Outputs from three simulations produced by the Canadian Regional Climate Model were used to give first estimates of potential PMSA changes for southern Quebec, Canada. A sensitivity analysis of the computed PMSA was performed with respect to the number of time-steps used (so-called snowstorm duration) and the threshold for a snowstorm to be maximized or not. The developed methodology is robust and a powerful tool to estimate the relative change of the PMSA. Absolute results are in the same order of magnitude as those obtained with the traditional method and observed data; but are also found to depend strongly on the climate projection used and show spatial variability. |
doi_str_mv | 10.1016/j.jhydrol.2016.03.031 |
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Probable maximum snow accumulation (PMSA) is one of the key variables used to estimate the spring probable maximum flood (PMF). A robust methodology for evaluating the PMSA is imperative so the ensuing spring PMF is a reasonable estimation. This is of particular importance in times of climate change (CC) since it is known that solid precipitation in Nordic landscapes will in all likelihood change over the next century. In this paper, a PMSA methodology based on simulated data from regional climate models is developed. Moisture maximization represents the core concept of the proposed methodology; precipitable water being the key variable. Results of stationarity tests indicate that CC will affect the monthly maximum precipitable water and, thus, the ensuing ratio to maximize important snowfall events. Therefore, a non-stationary approach is used to describe the monthly maximum precipitable water.
Outputs from three simulations produced by the Canadian Regional Climate Model were used to give first estimates of potential PMSA changes for southern Quebec, Canada. A sensitivity analysis of the computed PMSA was performed with respect to the number of time-steps used (so-called snowstorm duration) and the threshold for a snowstorm to be maximized or not. The developed methodology is robust and a powerful tool to estimate the relative change of the PMSA. Absolute results are in the same order of magnitude as those obtained with the traditional method and observed data; but are also found to depend strongly on the climate projection used and show spatial variability.</description><identifier>ISSN: 0022-1694</identifier><identifier>EISSN: 1879-2707</identifier><identifier>DOI: 10.1016/j.jhydrol.2016.03.031</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Canadian Regional Climate Model ; Climate change ; Climate models ; Computer simulation ; Estimates ; Mathematical models ; Methodology ; Moisture maximization ; Non-stationary frequency analysis ; Precipitable water ; Snow ; Snowstorms ; Spring (season)</subject><ispartof>Journal of hydrology (Amsterdam), 2016-06, Vol.537, p.74-85</ispartof><rights>2016 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a398t-feb8fd58a79b1942741fd16f464306cafa8c83260c9722075720334609d6390e3</citedby><cites>FETCH-LOGICAL-a398t-feb8fd58a79b1942741fd16f464306cafa8c83260c9722075720334609d6390e3</cites><orcidid>0000-0002-3439-2124</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jhydrol.2016.03.031$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Klein, Iris M.</creatorcontrib><creatorcontrib>Rousseau, Alain N.</creatorcontrib><creatorcontrib>Frigon, Anne</creatorcontrib><creatorcontrib>Freudiger, Daphné</creatorcontrib><creatorcontrib>Gagnon, Patrick</creatorcontrib><title>Evaluation of probable maximum snow accumulation: Development of a methodology for climate change studies</title><title>Journal of hydrology (Amsterdam)</title><description>•Climate change influences estimations of the probable maximum snow accumulation.•A deterministic moisture maximization technique is used to compute the PMSA.•Results depend rather on the simulation used than on the particular region.
Probable maximum snow accumulation (PMSA) is one of the key variables used to estimate the spring probable maximum flood (PMF). A robust methodology for evaluating the PMSA is imperative so the ensuing spring PMF is a reasonable estimation. This is of particular importance in times of climate change (CC) since it is known that solid precipitation in Nordic landscapes will in all likelihood change over the next century. In this paper, a PMSA methodology based on simulated data from regional climate models is developed. Moisture maximization represents the core concept of the proposed methodology; precipitable water being the key variable. Results of stationarity tests indicate that CC will affect the monthly maximum precipitable water and, thus, the ensuing ratio to maximize important snowfall events. Therefore, a non-stationary approach is used to describe the monthly maximum precipitable water.
Outputs from three simulations produced by the Canadian Regional Climate Model were used to give first estimates of potential PMSA changes for southern Quebec, Canada. A sensitivity analysis of the computed PMSA was performed with respect to the number of time-steps used (so-called snowstorm duration) and the threshold for a snowstorm to be maximized or not. The developed methodology is robust and a powerful tool to estimate the relative change of the PMSA. Absolute results are in the same order of magnitude as those obtained with the traditional method and observed data; but are also found to depend strongly on the climate projection used and show spatial variability.</description><subject>Canadian Regional Climate Model</subject><subject>Climate change</subject><subject>Climate models</subject><subject>Computer simulation</subject><subject>Estimates</subject><subject>Mathematical models</subject><subject>Methodology</subject><subject>Moisture maximization</subject><subject>Non-stationary frequency analysis</subject><subject>Precipitable water</subject><subject>Snow</subject><subject>Snowstorms</subject><subject>Spring (season)</subject><issn>0022-1694</issn><issn>1879-2707</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqFUU1LAzEQDaJg_fgJQo5etuZjm-x6EdH6AYIXPYc0O2lTspua7Fb7783a3h0eDAPvzfDmIXRFyZQSKm7W0_Vq18TgpyyPU8Iz6BGa0ErWBZNEHqMJIYwVVNTlKTpLaU1ycV5OkJtvtR9070KHg8WbGBZ64QG3-se1Q4tTF76xNmZoB__HusWPsAUfNi10_SjRuIV-FZrgw3KHbYjYeNfqHrBZ6W4JOPVD4yBdoBOrfYLLQz9Hn0_zj4eX4u39-fXh_q3QvK76wsKiss2s0rJe0LpksqS2ocKWouREGG11ZSrOBDG1ZIzImWSjE0HqRvCaAD9H1_u92cvXAKlXrUsGvNcdhCEpWlFBZqXk9H-qzB-UshQsU2d7qokhpQhWbWJ2GXeKEjWmoNbqkIIaU1CEZ4wn7vY6yJa3DqJKxkFnoHERTK-a4P7Z8AvOtZO3</recordid><startdate>201606</startdate><enddate>201606</enddate><creator>Klein, Iris M.</creator><creator>Rousseau, Alain N.</creator><creator>Frigon, Anne</creator><creator>Freudiger, Daphné</creator><creator>Gagnon, Patrick</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7U6</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><orcidid>https://orcid.org/0000-0002-3439-2124</orcidid></search><sort><creationdate>201606</creationdate><title>Evaluation of probable maximum snow accumulation: Development of a methodology for climate change studies</title><author>Klein, Iris M. ; Rousseau, Alain N. ; Frigon, Anne ; Freudiger, Daphné ; Gagnon, Patrick</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a398t-feb8fd58a79b1942741fd16f464306cafa8c83260c9722075720334609d6390e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Canadian Regional Climate Model</topic><topic>Climate change</topic><topic>Climate models</topic><topic>Computer simulation</topic><topic>Estimates</topic><topic>Mathematical models</topic><topic>Methodology</topic><topic>Moisture maximization</topic><topic>Non-stationary frequency analysis</topic><topic>Precipitable water</topic><topic>Snow</topic><topic>Snowstorms</topic><topic>Spring (season)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Klein, Iris M.</creatorcontrib><creatorcontrib>Rousseau, Alain N.</creatorcontrib><creatorcontrib>Frigon, Anne</creatorcontrib><creatorcontrib>Freudiger, Daphné</creatorcontrib><creatorcontrib>Gagnon, Patrick</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Journal of hydrology (Amsterdam)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Klein, Iris M.</au><au>Rousseau, Alain N.</au><au>Frigon, Anne</au><au>Freudiger, Daphné</au><au>Gagnon, Patrick</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of probable maximum snow accumulation: Development of a methodology for climate change studies</atitle><jtitle>Journal of hydrology (Amsterdam)</jtitle><date>2016-06</date><risdate>2016</risdate><volume>537</volume><spage>74</spage><epage>85</epage><pages>74-85</pages><issn>0022-1694</issn><eissn>1879-2707</eissn><abstract>•Climate change influences estimations of the probable maximum snow accumulation.•A deterministic moisture maximization technique is used to compute the PMSA.•Results depend rather on the simulation used than on the particular region.
Probable maximum snow accumulation (PMSA) is one of the key variables used to estimate the spring probable maximum flood (PMF). A robust methodology for evaluating the PMSA is imperative so the ensuing spring PMF is a reasonable estimation. This is of particular importance in times of climate change (CC) since it is known that solid precipitation in Nordic landscapes will in all likelihood change over the next century. In this paper, a PMSA methodology based on simulated data from regional climate models is developed. Moisture maximization represents the core concept of the proposed methodology; precipitable water being the key variable. Results of stationarity tests indicate that CC will affect the monthly maximum precipitable water and, thus, the ensuing ratio to maximize important snowfall events. Therefore, a non-stationary approach is used to describe the monthly maximum precipitable water.
Outputs from three simulations produced by the Canadian Regional Climate Model were used to give first estimates of potential PMSA changes for southern Quebec, Canada. A sensitivity analysis of the computed PMSA was performed with respect to the number of time-steps used (so-called snowstorm duration) and the threshold for a snowstorm to be maximized or not. The developed methodology is robust and a powerful tool to estimate the relative change of the PMSA. Absolute results are in the same order of magnitude as those obtained with the traditional method and observed data; but are also found to depend strongly on the climate projection used and show spatial variability.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.jhydrol.2016.03.031</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-3439-2124</orcidid></addata></record> |
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subjects | Canadian Regional Climate Model Climate change Climate models Computer simulation Estimates Mathematical models Methodology Moisture maximization Non-stationary frequency analysis Precipitable water Snow Snowstorms Spring (season) |
title | Evaluation of probable maximum snow accumulation: Development of a methodology for climate change studies |
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