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    Quantifying the Anthropogenic Greenhouse Gas Contribution to the Observed Spring Snow-Cover Decline Using the CMIP6 Multimodel Ensemble

    Source: Journal of Climate:;2020:;volume( 33 ):;issue: 021::page 9261
    Author:
    Paik, Seungmok;Min, Seung-Ki
    DOI: 10.1175/JCLI-D-20-0002.1
    Publisher: American Meteorological Society
    Abstract: This study conducts a detection and attribution analysis of the observed changes in boreal spring snow-cover extent (SCE) for an extended period of 1925–2019 for early spring (March and April) and 1970–2019 for late spring (May and June) using updated observations and multimodel simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6). The observed and simulated SCE changes over the Northern Hemisphere (NH), Eurasia, and North America are compared using an optimal fingerprinting technique. Detection results indicate that anthropogenic influences are robustly detected in the observed SCE decrease over NH and the continental regions, in separation from natural forcing influences. In contrast to previous studies, anthropogenic response in the early spring SCE shows a consistent magnitude with observations, due to an extension of the time period to 2019. It is demonstrated for the first time that the greenhouse gas (GHG) influence is robustly detected in separation from anthropogenic aerosol and natural forcing influences, and that most of the observed spring SCE decrease is attributable to GHG influences. The observed SCE decline is also found to be closely associated with the surface warming over the corresponding extratropical lands. Our first quantification of GHG contribution to the observed SCE changes has important implications for reliable future projections of the SCE changes and its hydrological and ecological impacts.
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      Quantifying the Anthropogenic Greenhouse Gas Contribution to the Observed Spring Snow-Cover Decline Using the CMIP6 Multimodel Ensemble

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    contributor authorPaik, Seungmok;Min, Seung-Ki
    date accessioned2022-01-30T17:58:32Z
    date available2022-01-30T17:58:32Z
    date copyright9/28/2020 12:00:00 AM
    date issued2020
    identifier issn0894-8755
    identifier otherjclid200002.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4264284
    description abstractThis study conducts a detection and attribution analysis of the observed changes in boreal spring snow-cover extent (SCE) for an extended period of 1925–2019 for early spring (March and April) and 1970–2019 for late spring (May and June) using updated observations and multimodel simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6). The observed and simulated SCE changes over the Northern Hemisphere (NH), Eurasia, and North America are compared using an optimal fingerprinting technique. Detection results indicate that anthropogenic influences are robustly detected in the observed SCE decrease over NH and the continental regions, in separation from natural forcing influences. In contrast to previous studies, anthropogenic response in the early spring SCE shows a consistent magnitude with observations, due to an extension of the time period to 2019. It is demonstrated for the first time that the greenhouse gas (GHG) influence is robustly detected in separation from anthropogenic aerosol and natural forcing influences, and that most of the observed spring SCE decrease is attributable to GHG influences. The observed SCE decline is also found to be closely associated with the surface warming over the corresponding extratropical lands. Our first quantification of GHG contribution to the observed SCE changes has important implications for reliable future projections of the SCE changes and its hydrological and ecological impacts.
    publisherAmerican Meteorological Society
    titleQuantifying the Anthropogenic Greenhouse Gas Contribution to the Observed Spring Snow-Cover Decline Using the CMIP6 Multimodel Ensemble
    typeJournal Paper
    journal volume33
    journal issue21
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-20-0002.1
    journal fristpage9261
    journal lastpage9269
    treeJournal of Climate:;2020:;volume( 33 ):;issue: 021
    contenttypeFulltext
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