e67242f2-e9aa-4402-85a3-be42d13354af eng utf8 dataset dataset NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom polardatacentre@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact 2022-04-26 ISO 19115 Geographic Information - Metadata ISO 19115:2003(E) European Petroleum Survey Group (EPSG) Geodetic Parameter Registry 2008-11-12 publication European Petroleum Survey Group EPSGadministrator@iogp.org https://www.epsg-registry.org/ EPSG Geodetic Parameter Dataset The EPSG Geodetic Parameter Dataset is a structured dataset of Coordinate Reference Systems and Coordinate Transformations, accessible through this online registry. information publisher urn:ogc:def:crs:EPSG::3031 6.18.3 Sea Ice Area climatologies and 21st century change in the CMIP5 and CMIP6 multi-model ensembles 2022-04-26 creation 2022-04-26 revision 2022-04-26 publication 2022-04-26 released 1.0 https://doi.org/10.5285/e67242f2-e9aa-4402-85a3-be42d13354af doi GB/NERC/BAS/PDC/01640 https://data.bas.ac.uk/ NE/N01829X/1 award Please cite this item as: Holmes, C. (2022). Sea Ice Area climatologies and 21st century change in the CMIP5 and CMIP6 multi-model ensembles (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/e67242f2-e9aa-4402-85a3-be42d13354af This dataset comprises summary statistics regarding historical and projected Southern Hemisphere total sea ice area (SIA) and 21st century global temperature change (dTAS), evaluated from the multi-model ensembles contributing to CMIP5 and CMIP6 (Coupled Model Intercomparison Project phases 5 and 6). The metrics are evaluated for two climatological periods (1979-2014 and 2081-2100) from a number of CMIP experiments; historical, and ScenarioMIP or RCP runs. These metrics were calculated to calculate projections of future Antarctic sea ice loss, and drivers of ensemble spread in this variable, for Holmes et al. (2022) "Antarctic sea ice projections constrained by historical ice cover and future global temperature change". Funding was provided by the British Antarctic Survey Polar Science for Planet Earth Programme and under NERC large grant NE/N01829X/1 No credit. completed Holmes, Caroline British Antarctic Survey Researcher author NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact asNeeded completed EARTH SCIENCE > Cryosphere > Sea Ice theme Global Change Master Directory (GCMD) Science Keywords 2026-01-27 publication 23 Global Change Data Center, Science and Exploration Directorate, Goddard Space Flight Center (GSFC) National Aeronautics and Space Administration (NASA) Greenbelt MD United States of America https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords Global Change Master Directory (GCMD) Keywords The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords. information publisher CMIP5 CMIP6 Climate Projections Sea Ice theme Global Southern Hemisphere place Oceanographic geographical features theme GEMET - INSPIRE themes, version 1.0 2021-01-06 revision otherRestrictions no limitations to public access otherRestrictions no limitations license Open Government Licence v3.0 otherRestrictions This data is governed by the NERC Data Policy: https://www.ukri.org/who-we-are/nerc/our-policies-and-standards/nerc-data-policy/ otherRestrictions This data is governed by the NERC data policy and supplied under Open Government Licence v.3 otherRestrictions None doi doi crossReference doi doi crossReference doi doi crossReference doi doi crossReference doi doi crossReference doi doi crossReference url url crossReference textTable eng utf8 climatologyMeteorologyAtmosphere -180.0 180.0 -90.0 90.0 1950-01-01 2100-12-31 It is recommended that careful attention be paid to the contents of any data, and that the author be contacted with any questions regarding appropriate use. If you find any errors or omissions, please report them to polardatacentre@bas.ac.uk. NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information distributor text/plain text/csv bytes 36864 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=e67242f2-e9aa-4402-85a3-be42d13354af WWW:LINK-1.0-http--link Get Data Download data download bytes 36864 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=e67242f2-e9aa-4402-85a3-be42d13354af WWW:LINK-1.0-http--link Get Data Download data download dataset Methodology: Model data The tables contain the model names for all models included in the analysis, and the headers reference the CMIP experiment or forcing scenario from which data was taken. The table also lists additional details of the runs used. The details of the experiment protocol for CMIP5 and CMIP6 are given in Taylor et al. (2012) and O'Neill et al (2016) respectively: Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012). An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93(4), 485-498. https://doi.org/10.1175/BAMS-D-11-00094.1 O'Neill, B. C., Tebaldi, C., Vuuren, D. P. V., Eyring, V., Friedlingstein, P., Hurtt, G., et al. (2016). The scenario model intercomparison project (ScenarioMIP) for CMIP6. Geoscientific Model Development, 9(9), 3461-3482. https://doi.org/10.5194/gmd-9-3461-2016 Sea ice Concentration data from satellites 'NASA-Team v1.1': Cavalieri, D. J., Parkinson, C. L., Gloersen, P., & Zwally, H. J. (1996), updated yearly. Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1.1 [Dataset]. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/8GQ8LZQVL0VL. [Accessed Apr 1 2021]. "Bootstrap v3.1": Comiso, J. C. (2017). Bootstrap Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS, Version 3.1 [Dataset]. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/7Q8HCCWS4I0R. [Accessed Apr 1 2021]. Processing CMIP data was accessed from the CEDA archives of CMIP5 and CMIP6 data on the UK computing resource JASMIN. CMIP5 data was accessed in July 2020; CMIP6 data was accessed in November 2020. SIA was calculated from the CMIP5 variable 'sic' or CMIP6 variable 'siconc', or, where available, is the CMIP6 variable 'siareas'. Global mean surface air temperature was calculated from CMIP variable 'tas'. We define an 'exceedance year' as the year in which a model's 5-year trailing average February SIA drops below 0.1Mkm2 . Exceedance year is calculated separately for historical and scenario runs, and the exceedance year taken as the minimum of these values. Due to the use of the trailing average, there are no exceedances in the first four years of the historical (1950-1953) or future (2015-2018) analysis. Historical climatologies (SIAhist) use the period 1979-2014; CMIP5 historical runs end in 2005, so climatologies also use data from rcp45 or, where this is unavailable, rcp85. End-of-the-century climatologies, to calculate the change in SIA or TAS (dSIA and dTAS in data table), use the period 2081-2100. Ensemble linear regressions were performed (using python's statsmodels ordinary least squares method). Constrained projections were then produced using these linear regression models and one of the observation-derived SIA datasets as the predictor. Other data Equilibrium Climate Sensitivity (ECS) and Transient Climate Response (TCR) data from Meehl et al. (2020): Meehl, G. A., Senior, C. A., Eyring, V., Flato, G., Lamarque, J. F., Stouffer, R. J., et al. (2020). Context for interpreting equilibrium climate sensitivity and transient climate response from the CMIP6 Earth system models. Science Advances, 6(26). https://doi.org/10.1126/sciadv.aba1981 Data description: regression statistics For each combination of forcing scenario, dataset (i.e. CMIP5 or CMIP6 or special subsets therein) and season (February or September) and for each pair of variables named ''''''xname' and 'yname', the datafile regression_statistics.csv contains full regression statistics: * ensemble minimum, mean and max (as in Holmes et al. (2022) Table 1) and standard deviation of each variable * r2 and its p-value, regression slope and intercept * Where relevant, the constrained pr...(8) Data collection: The data is aggregated over the Southern Ocean, derived from CMIP models at various spatial resolution. Data quality: Missing values in one of the future scenario run columns indicate that the given model was not run for that scenario, or, that data was not available to the authors. asNeeded completed