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Dataset for: Wood et al Role of sea surface temperature patterns for the Southern hemisphere jet stream response to CO2 forcing

Wood, Tom; McKenna, Christine; Chrysanthou, Andreas; Maycock, Amanda

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  <identifier identifierType="DOI">10.5281/zenodo.4250119</identifier>
      <creatorName>Wood, Tom</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-6049-5805</nameIdentifier>
      <affiliation>University of Leeds</affiliation>
      <creatorName>McKenna, Christine</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-9677-4582</nameIdentifier>
      <affiliation>University of Leeds</affiliation>
      <creatorName>Chrysanthou, Andreas</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-8670-5436</nameIdentifier>
      <affiliation>University of Leeds</affiliation>
      <creatorName>Maycock, Amanda</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0002-6614-1127</nameIdentifier>
      <affiliation>University of Leeds</affiliation>
    <title>Dataset for: Wood et al Role of sea surface temperature patterns for the Southern hemisphere jet stream response to CO2 forcing</title>
    <date dateType="Issued">2020-11-09</date>
  <resourceType resourceTypeGeneral="Dataset"/>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4250118</relatedIdentifier>
    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;This is a dataset of output from version 4 of the Reading Intermediate Global&amp;nbsp;Circulation Model (IGCM4) that was used in the article Wood et al (2020) &amp;#39;Role of sea surface temperature patterns for the Southern hemisphere jet stream response to CO2 forcing&amp;#39; published in Environmental Research Letters (&lt;a href=""&gt;;/a&gt;).&lt;/p&gt;

&lt;p&gt;To isolate the role of sea surface temperature (SST)&amp;nbsp;patterns for the Southern Hemisphere&amp;nbsp;circulation response in the abrupt-4xCO2 experiments in CMIP5 and CMIP6, we perform experiments using IGCM4.&lt;/p&gt;

&lt;p&gt;Five 120-year long simulations were performed following a 5-year spin-up period. In the control simulation (CTRL) we prescribe an annually repeating cycle of climatological monthly mean SSTs using the multi-model mean (MMM) of the &amp;lsquo;ts&amp;rsquo; field for the first 200 years of the CMIP5 piControl simulations. Following the CMIP6 protocol (Eyring et al., 2016), greenhouse gas (CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, and N&lt;sub&gt;2&lt;/sub&gt;O) concentrations are set at preindustrial (year 1850) values and ozone is prescribed as a zonally averaged monthly mean preindustrial climatology.&lt;/p&gt;

&lt;p&gt;In two perturbation simulations (4xCO2-FULL&lt;sub&gt;CMIP5&lt;/sub&gt; and 4xCO2-FULL&lt;sub&gt;CMIP6&lt;/sub&gt;) the same boundary conditions are used as in CTRL, but with an annually repeating cycle of climatological monthly mean SST anomalies added using the MMM &amp;lsquo;ts&amp;rsquo; field for either the CMIP5 or CMIP6 FAST (years 4-10) responses.&amp;nbsp;In both the 4xCO2-FULL&lt;sub&gt;CMIP5&lt;/sub&gt; and 4xCO2-FULL&lt;sub&gt;CMIP6&lt;/sub&gt; simulations CO&lt;sub&gt;2&lt;/sub&gt; is quadrupled from its preindustrial concentration. This enables a like-for-like comparison with the CMIP5 and CMIP6 abrupt-4xCO2 simulations. Two further perturbation simulations (SHET-only&lt;sub&gt;CMIP5&lt;/sub&gt; and SHET-only&lt;sub&gt;CMIP6&lt;/sub&gt;) are used to isolate the effect of differences in SH extratropical SST patterns alone. In both simulations CO&lt;sub&gt;2&lt;/sub&gt; is kept at preindustrial values, and CTRL SSTs are used with the SST anomalies from either 4xCO2-FULL&lt;sub&gt;CMIP5&lt;/sub&gt; or 4xCO2-FULL&lt;sub&gt;CMIP6&lt;/sub&gt; added poleward of 18&amp;deg;S. Similarly to McCrystall et al. (2020), the SST anomalies are smoothed between 18&amp;deg;S and 29&amp;deg;S using a cosine squared weighting function with weights of 0 at 18&amp;deg;S and 1 at 29&amp;deg;S. This minimizes sharp gradients in SST across the tropical-extratropical boundary.&lt;/p&gt;

&lt;p&gt;To enable a clean determination of the effects of SST patterns alone, in all perturbation simulations we keep sea ice fixed at preindustrial values by only adding SST anomalies where the MMM sea ice concentration in the CMIP5 piControl simulations is less than 15% (i.e., equatorward of the sea ice edge). Furthermore, to remove the effect of differences in the change in global mean SST, the SST anomalies in each CMIP model are normalised by the respective global mean SST anomaly and then scaled to a global mean value of 2.2 K (the pooled MMM of CMIP5 and CMIP6). The CMIP6 FAST SST anomalies are added to the CMIP5 preindustrial control SSTs, so as to isolate the effect of differences in the fast SST responses between CMIP5 and CMIP6, and not the effect of differences in the base state.&lt;/p&gt;</description>
    <description descriptionType="Other">{"references": ["doi:10.5194/gmd-8-1157-2015", ""]}</description>
      <funderName>Research Councils UK</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000690</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/RCUK/NERC/NE%2FM018199%2F1/">NE/M018199/1</awardNumber>
      <awardTitle>Understanding and Attributing Composition-Climate Feedbacks in the Earth System</awardTitle>
      <funderName>Research Councils UK</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000690</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/RCUK/NERC/NE%2FL002574%2F1/">NE/L002574/1</awardNumber>
      <awardTitle>NERC Science @ Leeds and York - Site for PhD Training in Environmental Research (SPHERES)</awardTitle>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/820829/">820829</awardNumber>
      <awardTitle>Constraining uncertainty of multi decadal climate projections</awardTitle>
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