NOAA/WDS Paleoclimatology - PAGES2k 2,000 Year Arctic Gridded Temperature Reconstructions
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title: NOAA/WDS Paleoclimatology - PAGES2k 2,000 Year Arctic Gridded Temperature Reconstructions
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abstract: This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Climate Reconstruction. The data include parameters of climate reconstructions with a geographic location of Arctic. The time period coverage is from 1949 to -52 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.
purpose: Records of past temperature, precipitation, and other climate variables derived from paleoclimate proxies. Parameter keywords describe what was measured in this data set. Additional summary information can be found in the abstracts of papers listed in the data set citations.
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keyword: Earth Science > Climate Indicators > Paleoclimate Indicators > Paleoclimate Reconstructions
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keyword: earth science > paleoclimate > climate reconstructions
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keyword: What: temperature; Material: multiple proxies
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keyword: Geographic Region > Arctic > Arctic > LATITUDE > LONGITUDE
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keyword: DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce
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otherConstraints: Cite as: Werner, J.P.; Divine, D.V.; Ljungqvist, F.C.; Nilsen, T.; Francus, P. (2018-04-30): NOAA/WDS Paleoclimatology - PAGES2k 2,000 Year Arctic Gridded Temperature Reconstructions. [indicate subset used]. NOAA National Centers for Environmental Information. https://doi.org/10.25921/9bt9-3d58. Accessed [date].
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otherConstraints: Distribution liability: NOAA and NCEI make no warranty, expressed or implied, regarding these data, nor does the fact of distribution constitute such a warranty. NOAA and NCEI cannot assume liability for any damages caused by any errors or omissions in these data. If appropriate, NCEI can only certify that the data it distributes are an authentic copy of the records that were accepted for inclusion in the NCEI archives.
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otherConstraints: Use liability: NOAA and NCEI cannot provide any warranty as to the accuracy, reliability, or completeness of furnished data. Users assume responsibility to determine the usability of these data. The user is responsible for the results of any application of this data for other than its intended purpose.
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otherConstraints: Please cite original publication, online resource, dataset and publication DOIs (where available), and date accessed when using downloaded data. If there is no publication information, please cite investigator, title, online resource, and date accessed. The appearance of external links associated with a dataset does not constitute endorsement by the Department of Commerce/National Oceanic and Atmospheric Administration of external Web sites or the information, products or services contained therein. For other than authorized activities, the Department of Commerce/NOAA does not exercise any editorial control over the information you may find at these locations. These links are provided consistent with the stated purpose of this Department of Commerce/NOAA Web site.
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title: Spatio-temporal variability of Arctic summer temperatures over the past 2 millennia
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individualName: Johannes P. Werner, Dmitry V. Divine, Fredrik Charpentier Ljungqvist, Tine Nilsen, and Pierre Francus
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description: Johannes P. Werner, Dmitry V. Divine, Fredrik Charpentier Ljungqvist, Tine Nilsen, and Pierre Francus, 2018: Spatio-temporal variability of Arctic summer temperatures over the past 2 millennia. Climate of the Past, 14, 527-557, 10.5194/cp-14-527-2018
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description: Date Range: 1 CE to 2002 CE; Date Range: 1949 cal yr BP to -52 cal yr BP;
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supplementalInformation: STUDY NOTES: PAGES Arctice2k data, Werner et al. 2018 Clim. Past: Data Data used (input data file) InputData Input data (instrumental data, proxies, grid cell description) Results Results as presented in the article Scripts The scripts to construct the input data and evaluate the reconstruction Barcast |-> source source code for Barcast (see also Werner and Tingley, Clim.Past 2015) | | Readme.md installation and use description InputData: Arc2Kout_chrons_conserv_GreenlandTheta.mat time uncertain proxies CRU_SummerData_G5000.RData instrumental (gridded) data FullGridCells.RData relevant grid cells McCarroll.2013.AllData.csv data from McCarroll, as taken from NOAA PAGES2k_ArcticRegionData_corrected.RData Input proxy data PAGES2k_ArcticRegionData.RData Input proxy data as taken from the PAGES2k database Tornetrask.MXD.dat Tornetrask ./Results: ADMs.pdf pdf showing the age model selection, not cleaned up Arc2Ktrend_1_1850_REV1.txt resulting trends over the common era, starting at 1CE Arc2Ktrend_750_1850_REV1.txt trends staring at 750 CE Arctic2k_ensembles.nc File containing the reconstruction ensemble (750CE on) Arctic2k_ensembles_early.nc File containing the reconstruction ensemble (1-749CE) ArcticRecon_2k0_Summer_PAGES2kv2.0_longseries_CRU_G5000.RData input data AreaMeanRecon.RData mean arctic recon AreaMeanRecon.txt - " - AR_Table.mat scaling behaviour of the reconstruction ExtremeCenturies.RData most extreme centuries, as plotted ExtremeDecades.RData most extreme decades, as plotted ggmcmc.pdf traces of the drawn parameters mean_Arc2K_spatial_variances_REV1.txt spatial variability, intra-ensemble Parameters.Final.RData final parameters, thinned, only for unheated chain PriorPars.RScript priors ProxSNR_table.csv SNR of the used proxies ProxySNR_Data.RData -"- Recon_corrected.RData reconstruction, thinned, only unheated chain SortChains.RData which chain is active when transtimes.txt scaling information ./Scripts: 00_Correct_PAGES2k.R 01_convert_table_tex.sh 01_Get_bibtex_fromDOI.sh 01_ReadPAGES.Arctic_CRU_G5000-grid.R 01_ReadPAGES.Arctic_CRU_G5000_InstData-grid.R 02_ConstructGridEdges.R 02_plotDataOverview.R 09_Correct_Reconstruction.R 10_ExportRecon-netcdf.R 10_MakeMeanRecon.R 11_plotMeanRecon.R 11_plotScore.R 12_plotCompareData.R 13_plotExtremePeriods.R 14_plotProxResponse.R 15_plotProxyTrends.R 15_plotScore.R 16_plotTrendAnalysis.R 17_plotVarMaps.R 18_plotProxyScaling.R 19_plotLTM_Analysis.R 99_Common_helper.R 99_ScoringRules.R ABSTRACT SUPPLIED BY ORIGINATOR: In this article, the first spatially resolved and millennium-length summer (June-August) temperature reconstruction over the Arctic and sub-Arctic domain (north of 60N) is presented. It is based on a set of 44 annually dated temperature-sensitive proxy archives of various types from the revised PAGES2k database supplemented with six new recently updated proxy records. As a major advance, an extension of the Bayesian BARCAST climate field (CF) reconstruction technique provides a means to treat climate archives with dating uncertainties. This results not only in a more precise reconstruction but additionally enables joint probabilistic constraints to be imposed on the chronologies of the used archives. The new seasonal CF reconstruction for the Arctic region can be shown to be skilful for the majority of the terrestrial nodes. The decrease in the proxy data density back in time, however, limits the analyses in the spatial domain to the period after 750 CE, while the spatially averaged reconstruction covers the entire time interval of 1-2002 CE. The centennial to millennial evolution of the reconstructed temperature is in good agreement with a general pattern that was inferred in recent studies for the Arctic and its subregions. In particular, the reconstruction shows a pronounced Medieval Climate Anomaly (MCA; here ca. 920-1060 CE), which was characterised by a sequence of extremely warm decades over the whole domain. The medieval warming was followed by a gradual cooling into the Little Ice Age (LIA), with 1766-1865 CE as the longest centennial-scale cold period, culminating around 1811-1820 CE for most of the target region. In total over 600 independent realisations of the temperature CF were generated. As showcased for local and regional trends and temperature anomalies, operating in a probabilistic framework directly results in comprehensive uncertainty estimates, even for complex analyses. For the presented multi-scale trend analysis, for example, the spread in different paths across the reconstruction ensemble prevents a robust analysis of features at timescales shorter than ca. 30 years. For the spatial reconstruction, the benefit of using the spatially resolved reconstruction ensemble is demonstrated by focusing on the regional expression of the recent warming and the MCA. While our analysis shows that the peak MCA summer temperatures were as high as in the late 20th and early 21st centuries, the spatial coherence of extreme years over the last decades of the reconstruction (1980s onwards) seems unprecedented at least back until 750 CE. However, statistical testing could not provide conclusive support of the contemporary warming to exceed the peak of the MCA in terms of the pan-Arctic mean summer temperatures: the reconstruction cannot be extended reliably past 2002 CE due to lack of proxy data and thus the most recent warming is not captured.
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