# Northern Russia Air Temperature Reconstructions during the Holocene #----------------------------------------------------------------------- # World Data Service for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program # National Centers for Environmental Information (NCEI) #----------------------------------------------------------------------- # Template Version 3.0 # Encoding: UTF-8 # NOTE: Please cite Publication, and Online_Resource and date accessed when using these data. # If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed. # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/32612 # Online_Resource_Description: NOAA Landing Page # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/27330 # Online_Resource_Description: NOAA Landing Page for Temperature-12k Database # # Online_Resource: https://www.ncei.noaa.gov/pub/data/paleo/reconstructions/climate12k/temperature/version1.0.0/Temp12k_directory_NOAA_files/Valiranta.Kharinei.2015.txt # Online_Resource_Description: NOAA location of the template # # Online_Resource: https://www.ncei.noaa.gov/pub/data/paleo/reconstructions/climate12k/temperature/version1.0.0/Temp12k_directory_LiPD_files/Valiranta.Kharinei.2015.lpd # Online_Resource_Description: Linked Paleo Data (LiPD) formatted file containing metadata and data related to this file, for version 1.0.0 of this dataset. # # Original_Source_URL: # Description/Documentation lines begin with # # Data lines have no # # # Data_Type: Climate Reconstructions # Parameter_Keywords: air temperature # Dataset_DOI: # #------------------ # Contribution_Date # Date: 2020-04-15 #------------------ # File_Last_Modified_Date # Date: 2020-05-16 #------------------ # Title # Study_Name: Northern Russia Air Temperature Reconstructions during the Holocene #------------------ # Investigators # Investigators: Väliranta, M.; Salonen, J. S.; Heikkilä, M.; Amon, L.; Helmens, K.; Klimaschewski, A.; Kuhry, P.; Kultti, S.; Poska, A.; Shala, S.; Veski, S.; Birks, H. H. #------------------ # Description_Notes_and_Keywords # Description: This dataset was contributed as part of the Temperature-12k project (https://doi.org/10.25921/4RY2-G808). Data were contributed to the project from the original data generators, who are listed in the Investigator field of this template file. Additional notes regarding the use of these data in the Temperature-12k project can be found in the LiPD file listed as an Online_Resource of this template file. #------------------ # Publication # Authors: Väliranta, M.; Salonen, J. S.; Heikkilä, M.; Amon, L.; Helmens, K.; Klimaschewski, A.; Kuhry, P.; Kultti, S.; Poska, A.; Shala, S.; Veski, S.; Birks, H. H. # Published_Date_or_Year: 2015 # Published_Title: Plant macrofossil evidence for an early onset of the Holocene summer thermal maximum in northernmost Europe # Journal_Name: Nature Communications # Volume: 6 # Edition: # Issue: 1 # Pages: 6809 # Report: # DOI: 10.1038/ncomms7809 # Online_Resource: # Full_Citation: # Abstract: Holocene summer temperature reconstructions from northern Europe based on sedimentary pollen records suggest an onset of peak summer warmth around 9,000 years ago. However, pollen-based temperature reconstructions are largely driven by changes in the proportions of tree taxa, and thus the early-Holocene warming signal may be delayed due to the geographical disequilibrium between climate and tree populations. Here we show that quantitative summer-temperature estimates in northern Europe based on macrofossils of aquatic plants are in many cases ca. 2°C warmer in the early Holocene (11,700–7,500 years ago) than reconstructions based on pollen data. When the lag in potential tree establishment becomes imperceptible in the mid-Holocene (7,500 years ago), the reconstructed temperatures converge at all study sites. We demonstrate that aquatic plant macrofossil records can provide additional and informative insights into early-Holocene temperature evolution in northernmost Europe and suggest further validation of early post-glacial climate development based on multi-proxy data syntheses. #------------------ # Publication # Authors: Salonen, J. Sakari; Seppä, Heikki; Vaeliranta, Minna; Jones, Vivienne J.; Self, Angela; Heikkilä, Maija; Kultti, Seija; Yang, Handong # Published_Date_or_Year: 2011 # Published_Title: The Holocene thermal maximum and late-Holocene cooling in the tundra of NE European Russia # Journal_Name: Quaternary Research # Volume: 75 # Edition: # Issue: 3 # Pages: # Report: # DOI: 10.1016/j.yqres.2011.01.007 # Online_Resource: # Full_Citation: # Abstract: #------------------ # Publication # Authors: Jones, V.J.; Solovieva, N.; Self, A.E.; McGowan, S.; Rosén, P.; Salonen, J.S.; Seppä, H.; Väliranta, M.; Parrott, E.; Brooks, S.J. # Published_Date_or_Year: 2011 # Published_Title: The influence of Holocene tree-line advance and retreat on an arctic lake ecosystem: a multi-proxy study from Kharinei Lake, North Eastern European Russia # Journal_Name: Journal of Paleolimnology # Volume: 46 # Edition: # Issue: 1 # Pages: # Report: # DOI: 10.1007/s10933-011-9528-7 # Online_Resource: # Full_Citation: # Abstract: #------------------ # Publication # Authors: Kaufman, D., N. McKay, C. Routson, M. Erb, B. Davis, O. Heiri, S. Jaccard, J. Tierney, C. Dätwyler, Y. Axford, T. Brussel, O. Cartapanis, B. Chase, A. Dawson, A. de Vernal, S. Engels, L. Jonkers, J. Marsicek, P. Moffa-Sánchez, C. Morrill, A. Orsi, K. Rehfeld, K. Saunders, P. S. Sommer, E. Thomas, M. Tonello, M. Tóth, R. Vachula, A. Andreev, S. Bertrand, B. Biskaborn, M. Bringué, S. Brooks, M. Caniupán, M. Chevalier, L. Cwynar, J. Emile-Geay, J. Fegyveresi, A. Feurdean, W. Finsinger, M-C. Fortin, L. Foster, M. Fox, K. Gajewski, M. Grosjean, S. Hausmann, M. Heinrichs, N. Holmes, B. Ilyashuk, E. Ilyashuk, S. Juggins, D. Khider, K. Koinig, P. Langdon, I. Larocque-Tobler, J. Li, A. Lotter, T. Luoto, A. Mackay, E. Magyari, S. Malevich, B. Mark, J. Massaferro, V. Montade, L. Nazarova, E. Novenko, P. Paril, E. Pearson, M. Peros, R. Pienitz, M. Plóciennik, D. Porinchu, A. Potito, A. Rees, S. Reinemann, S. Roberts, N. Rolland, S. Salonen, A. Self, H. Seppä, S. Shala, J-M. St-Jacques, B. Stenni, L. Syrykh, P. Tarrats, K. Taylor, V. van den Bos, G. Velle, E. Wahl, I. Walker, J. Wilmshurst, E. Zhang, S. Zhilich # Published_Date_or_Year: 2020-04-14 # Published_Title: A global database of Holocene paleotemperature records # Journal_Name: Scientific Data # Volume: 7 # Edition: 115 # Issue: # Pages: # Report_Number: # DOI: 10.1038/s41597-020-0445-3 # Online_Resource: https://www.nature.com/articles/s41597-020-0445-3 # Full_Citation: # Abstract: A comprehensive database of paleoclimate records is needed to place recent warming into the longer-term context of natural climate variability. We present a global compilation of quality-controlled, published, temperature-sensitive proxy records extending back 12,000 years through the Holocene. Data were compiled from 679 sites where time series cover at least 4000 years, are resolved at sub-millennial scale (median spacing of 400 years or finer) and have at least one age control point every 3000 years, with cut-off values slackened in data-sparse regions. The data derive from lake sediment (51%), marine sediment (31%), peat (11%), glacier ice (3%), and other natural archives. The database contains 1319 records, including 157 from the Southern Hemisphere. The multi-proxy database comprises paleotemperature time series based on ecological assemblages, as well as biophysical and geochemical indicators that reflect mean annual or seasonal temperatures, as encoded in the database. This database can be used to reconstruct the spatiotemporal evolution of Holocene temperature at global to regional scales, and is publicly available in Linked Paleo Data (LiPD) format. #------------------ # Funding_Agency # Funding_Agency_Name: # Grant: #------------------ # Site_Information # Site_Name: Kharinei # Location: Europe>Eastern Europe>Russia # Country: Russia # Northernmost_Latitude: 67.3628 # Southernmost_Latitude: 67.3628 # Easternmost_Longitude: 62.7507 # Westernmost_Longitude: 62.7507 # Elevation: 108 #------------------ # Data_Collection # Collection_Name: Valiranta.Kharinei.2015 # Earliest_Year: 11502.7 # Most_Recent_Year: -43.7 # Time_Unit: cal yr BP # Core_Length: # Notes: #------------------ # Species # Species_Name: # Species_Code: # Common_Name: #------------------ # Chronology_Information # Chronology: # depth_top depth_bottom age_type age uncertainty_old uncertainty_young AdditionalNotes # 0.0 1.0 Core top -55.0 nan nan Lake cored in April 2007; Modern age of top sediment confirmed by Pb-210 dating and by a well-resolved Cs-137 spike # 99.0 100.0 age14C 3590.0 3630.0 3550.0 Plant macrofossils # 179.0 180.0 age14C 5460.0 5500.0 5420.0 Plant macrofossils # 223.0 224.0 age14C 6250.0 6290.0 6210.0 Plant macrofossils # 239.0 240.0 age14C 6780.0 6830.0 7230.0 Plant macrofossils # 289.0 290.0 age14C 9440.0 9490.0 9390.0 Plant macrofossils # 297.0 298.0 age14C 9200.0 9250.0 9150.0 Plant macrofossils #------------------ # Variables # # Data variables follow that are preceded by "##" in columns one and two. # Variables list, one per line, shortname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # ## OriginalSampleID sample identification,,,,,pollen;climate reconstructions,,,C,OriginalSampleID ## depth depth,,,centimeter,,pollen;climate reconstructions,,,N, ## age age,,,calendar year before present,,pollen;climate reconstructions,,,N, ## temperature surface air temperature,,,degree Celsius,Jul,pollen;climate reconstructions,,,N,58-lake training set from European Russia; WAPLS ## uncertainty surface air temperature,,unspecified error upper bound,degree Celsius,Jul,pollen;climate reconstructions,,,N, ## uncertainty-1 surface air temperature,,unspecified error lower bound,degree Celsius,Jul,pollen;climate reconstructions,,,N, ## nonreliable surface air temperature,,,degree Celsius,Jul,pollen;climate reconstructions,,,N,non-reliable temperature # #------------------ # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing_Values: nan # OriginalSampleID depth age temperature uncertainty uncertainty-1 nonreliable KHAR781 1.0 -43.7 11.999 13.099 10.898 nan KHAR783 3.0 33.3 12.004 13.066 10.943 nan KHAR785 5.0 112.175 13.71 14.648 12.773 nan KHAR787 7.0 191.129 12.562 13.545 11.579 nan KHAR789 9.0 270.083 nan 12.756 9.28 11.999 KHAR791 11.0 349.037 13.107 14.186 12.027 nan KHAR793 13.0 427.991 13.324 14.37 12.278 nan KHAR795 15.0 506.945 13.354 14.304 12.403 nan KHAR797 17.0 585.899 12.277 13.297 11.258 nan KHAR799 19.0 664.853 12.808 13.762 11.854 nan KHAR801 21.0 743.807 12.675 13.702 11.648 nan KHAR803 23.0 822.761 12.803 13.838 11.769 nan KHAR805 25.0 901.715 13.067 14.067 12.066 nan KHAR807 27.0 980.669 14.238 15.356 13.119 nan KHAR809 29.0 1059.62 14.722 15.754 13.69 nan KHAR811 31.0 1138.58 12.879 13.824 11.935 nan KHAR813 33.0 1217.53 12.624 13.595 11.653 nan KHAR815 35.0 1296.48 13.33 14.28 12.38 nan KHAR817 37.0 1375.44 13.933 14.843 13.022 nan KHAR819 39.0 1454.39 13.831 14.825 12.837 nan KHAR821 41.0 1533.35 13.164 14.114 12.214 nan KHAR823 43.0 1612.3 12.756 13.784 11.728 nan KHAR825 45.0 1691.25 14.158 15.121 13.194 nan KHAR827 47.0 1770.21 13.692 14.658 12.727 nan KHAR829 49.0 1849.16 13.64 14.73 12.55 nan KHAR831 51.0 1928.12 13.612 14.573 12.651 nan KHAR833 53.0 2007.07 13.6 14.628 12.573 nan KHAR835 55.0 2086.02 14.887 15.954 13.82 nan KHAR837 57.0 2164.98 13.677 14.629 12.725 nan KHAR839 59.0 2243.93 13.7 14.575 12.825 nan KHAR841 61.0 2322.89 13.619 14.582 12.656 nan KHAR843 63.0 2401.84 13.552 14.505 12.598 nan KHAR845 65.0 2480.79 14.239 15.175 13.302 nan KHAR847 67.0 2559.75 14.065 14.992 13.138 nan KHAR849 69.0 2638.7 14.112 15.073 13.151 nan KHAR851 71.0 2717.66 13.929 14.989 12.868 nan KHAR853 73.0 2796.61 14.534 15.475 13.593 nan KHAR855 75.0 2875.56 13.583 14.57 12.596 nan KHAR857 77.0 2954.52 15.281 16.23 14.332 nan KHAR859 79.0 3033.47 14.337 15.302 13.372 nan KHAR861 81.0 3112.43 13.877 14.827 12.927 nan KHAR865 85.0 3270.33 13.953 14.943 12.962 nan KHAR869 89.0 3428.24 14.761 15.688 13.834 nan KHAR873 93.0 3586.15 15.726 16.63 14.821 nan KHAR877 97.0 3744.06 15.836 16.747 14.926 nan KHAR881 101.0 3891.07 15.275 16.22 14.331 nan KHAR885 105.0 4005.54 15.377 16.29 14.464 nan KHAR889 109.0 4120.01 14.801 15.698 13.904 nan KHAR893 113.0 4234.48 15.261 16.218 14.303 nan KHAR897 117.0 4348.94 15.64 16.703 14.578 nan KHAR901 121.0 4463.41 14.983 15.905 14.061 nan KHAR905 125.0 4577.88 14.752 15.708 13.797 nan KHAR909 129.0 4692.35 15.014 15.91 14.119 nan KHAR913 133.0 4806.82 14.868 15.847 13.889 nan KHAR917 137.0 4921.28 15.299 16.191 14.407 nan KHAR921 141.0 5035.75 16.372 17.299 15.446 nan KHAR925 145.0 5150.22 15.537 16.425 14.65 nan KHAR929 149.0 5264.69 15.177 16.178 14.177 nan KHAR933 153.0 5379.16 15.211 16.131 14.291 nan KHAR937 157.0 5493.62 15.286 16.297 14.274 nan KHAR941 161.0 5608.09 14.95 15.861 14.038 nan KHAR945 165.0 5722.56 14.398 15.295 13.502 nan KHAR949 169.0 5837.03 14.415 15.318 13.512 nan KHAR953 173.0 5951.5 15.21 16.185 14.236 nan KHAR957 177.0 6065.96 15.32 16.333 14.306 nan KHAR961 181.0 6177.21 15.934 17.007 14.862 nan KHAR965 185.0 6278.61 14.777 15.681 13.872 nan KHAR969 189.0 6380.02 15.122 16.024 14.219 nan KHAR973 193.0 6481.43 14.724 15.618 13.829 nan KHAR977 197.0 6582.84 15.119 16.042 14.197 nan KHAR981 201.0 6684.25 15.184 16.064 14.305 nan KHAR985 205.0 6785.65 14.592 15.485 13.7 nan KHAR989 209.0 6887.06 14.847 15.738 13.957 nan KHAR993 213.0 6988.47 14.978 15.882 14.075 nan KHAR997 217.0 7089.88 14.262 15.144 13.38 nan KHAR1001 221.0 7191.29 15.02 15.914 14.125 nan KHAR1005 225.0 7301.79 15.411 16.403 14.42 nan KHAR1009 229.0 7439.64 14.856 15.762 13.951 nan KHAR1013 233.0 7577.49 14.598 15.517 13.678 nan KHAR1017 237.0 7715.34 13.666 14.616 12.717 nan KHAR1021 241.0 7865.42 14.087 15.031 13.143 nan KHAR1025 245.0 8052.19 14.454 15.379 13.529 nan KHAR1029 249.0 8238.95 14.703 15.624 13.782 nan KHAR1033 253.0 8425.71 13.783 14.792 12.774 nan KHAR1037 257.0 8612.48 13.053 13.962 12.144 nan KHAR1041 261.0 8799.24 13.446 14.371 12.521 nan KHAR1045 265.0 8986.01 13.381 14.343 12.419 nan KHAR1049 269.0 9172.77 12.846 13.842 11.85 nan KHAR1053 273.0 9359.53 13.047 13.976 12.119 nan KHAR1057 277.0 9546.3 12.893 13.855 11.931 nan KHAR1061 281.0 9733.06 12.693 13.692 11.693 nan KHAR1065 285.0 9919.83 14.179 15.1 13.258 nan KHAR1069 289.0 10106.6 13.843 14.749 12.937 nan KHAR1073 293.0 10303.2 13.223 14.215 12.232 nan KHAR1077 297.0 10503.1 13.411 14.367 12.456 nan KHAR1081 301.0 10703.0 13.525 14.443 12.608 nan KHAR1085 305.0 10903.0 13.613 14.635 12.591 nan KHAR1089 309.0 11102.9 13.347 14.307 12.388 nan KHAR1093 313.0 11302.8 13.608 14.538 12.678 nan KHAR1097 317.0 11502.7 13.566 14.481 12.65 nan