# Arctic Western Siberia Air Temperature Reconstructions during the last 4000 Years #----------------------------------------------------------------------- # 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/30776 # 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/GYXO.Self.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/GYXO.Self.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: Arctic Western Siberia Air Temperature Reconstructions during the last 4000 Years #------------------ # Investigators # Investigators: Self, Angela E.; Jones, Vivienne J.; Brooks, Stephen J. #------------------ # 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: Self, Angela E., Vivienne J. Jones, and Steve J. Brooks # Published_Date_or_Year: 2015 # Published_Title: Late Holocene environmental change in arctic western Siberia # Journal_Name: The Holocene # Volume: 25 # Edition: # Issue: 1 # Pages: 150-165 # Report: # DOI: 10.1177/0959683614556387 # Online_Resource: # Full_Citation: # Abstract: The Putorana Plateau, western Siberia, situated on the boundary of the Atlantic and continental Siberian climate provinces, is sensitive to shifts in atmospheric circulation. Three lakes on an altitudinal transect were studied using chironomid subfossils to provide the first estimates of late Holocene climate in this remote, poorly studied region of Arctic Russia. The analysis of sediment cores from three closely located lakes is rare in palaeoenvironmental studies and enables the role of other environmental variables, which may be a potential source of error in palaeoclimatic reconstructions, to be assessed. The chironomid-based reconstructions suggest a more maritime climate c. 3400 cal. BP with July temperatures c. 1.5°C warmer than present which cooled rapidly by c. 2°C, with a more continental climate between 3200 and 2600 cal. BP. These trends are similar in timing and scale to other northern hemisphere records. The recent chironomid records from all three lakes show pronounced faunal changes over the last 50 years probably directly or indirectly because of climate-driven changes in catchment hydrology. This is particularly evident in the recent record from an open lake within a large wetland habitat, which appears relatively insensitive to changes in July air temperatures. #------------------ # 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: GYXO # Location: Europe>Eastern Europe>Russia # Country: Russia # Northernmost_Latitude: 68.165 # Southernmost_Latitude: 68.165 # Easternmost_Longitude: 92.1731 # Westernmost_Longitude: 92.1731 # Elevation: 569 #------------------ # Data_Collection # Collection_Name: GYXO.Self.2015 # Earliest_Year: 3476.0 # Most_Recent_Year: -56.0 # Time_Unit: cal yr BP # Core_Length: # Notes: #------------------ # Species # Species_Name: # Species_Code: # Common_Name: #------------------ # Chronology_Information # Chronology: # OriginalDateID depth_top depth_bottom age_type age 1SD IncludeYN material # nan 0.0 nan Core top -56.0 nan Y nan # nan 0.38 nan Pb210-Lead -52.0 2.0 Y nan # nan 1.13 nan Pb210-Lead -42.0 2.0 Y nan # nan 1.88 nan Pb210-Lead -29.0 2.0 Y nan # nan 2.13 nan Pb210-Lead -25.0 2.0 Y nan # nan 2.38 nan Pb210-Lead -19.0 2.0 Y nan # nan 2.88 nan Pb210-Lead -5.0 3.0 Y nan # nan 3.13 nan Pb210-Lead 3.0 3.0 Y nan # nan 3.38 nan Pb210-Lead 14.0 4.0 Y nan # nan 3.63 nan Pb210-Lead 26.0 5.0 Y nan # nan 4.13 nan Pb210-Lead 63.0 12.0 Y nan # nan 4.38 nan Pb210-Lead 93.0 26.0 Y nan # SUERC-51090 11.75 12.0 age14C 1527.0 35.0 Y bulk sediment # SUERC-51091 19.0 19.25 age14C 2488.0 35.0 Y bulk sediment # SUERC-51092 26.25 26.5 age14C 2311.0 35.0 N bulk sediment # Beta-312807 31.75 32.5 age14C 3210.0 30.0 Y bulk sediment #------------------ # 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) # ## depth depth,,,centimeter,,insect;paleolimnology;climate reconstructions,,,N, ## age age,,,calendar year before present,,insect;paleolimnology;climate reconstructions,,,N, ## ageMin age,,range lower bound,calendar year before present,,insect;paleolimnology;climate reconstructions,,,N, ## ageMax age,,range upper bound,calendar year before present,,insect;paleolimnology;climate reconstructions,,,N, ## temperature surface air temperature,midge assemblage,,degree Celsius,Jul,insect;paleolimnology;climate reconstructions,,,N,Western Russian calibration dataset (Self et al. 2011); WAPLS ## uncertainty surface air temperature,midge assemblage,unspecified error upper bound,degree Celsius,Jul,insect;paleolimnology;climate reconstructions,,,N, ## uncertainty-1 surface air temperature,midge assemblage,unspecified error lower bound,degree Celsius,Jul,insect;paleolimnology;climate reconstructions,,,N, ## reliable notes,,,,,insect;paleolimnology;climate reconstructions,,,C,Data are reliable (Yes or No) ## Commentregardingreliability1 notes,,,,,insect;paleolimnology;climate reconstructions,,,C,comment regarding reliability # #------------------ # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing_Values: nan # depth age ageMin ageMax temperature uncertainty uncertainty-1 reliable Commentregardingreliability1 0.0 -56.0 -58.0 -54.0 11.78 12.81 10.75 Y No reason to reject but did not pass Birks & Telford test 1.5 -36.0 -38.0 -34.0 12.35 13.41 11.29 Y No reason to reject but did not pass Birks & Telford test 2.25 -22.0 -24.0 -20.0 12.424 13.47 11.38 Y No reason to reject but did not pass Birks & Telford test 3.0 -1.0 -4.0 2.0 12.043 13.05 11.03 Y No reason to reject but did not pass Birks & Telford test 4.25 78.0 59.0 97.0 12.148 13.17 11.13 Y No reason to reject but did not pass Birks & Telford test 6.0 386.0 366.0 406.0 13.472 14.53 12.42 Y No reason to reject but did not pass Birks & Telford test 7.5 658.0 619.0 697.0 11.814 12.9 10.73 Y No reason to reject but did not pass Birks & Telford test 9.5 1020.0 956.0 1084.0 11.739 12.74 10.73 Y No reason to reject but did not pass Birks & Telford test 11.5 1382.0 1295.0 1469.0 10.975 11.99 9.95 Y Yes using Birks and Telford 2011 13.5 1706.0 1624.0 1788.0 10.933 11.94 9.93 Y Yes using Birks and Telford 2012 15.5 2025.0 1924.0 2126.0 10.741 11.77 9.71 Y Yes using Birks and Telford 2013 17.5 2344.0 2196.0 2492.0 12.044 13.09 11.0 Y Yes using Birks and Telford 2014 19.5 2616.0 2433.0 2799.0 11.193 12.26 10.13 Y Yes using Birks and Telford 2015 21.5 2746.0 2594.0 2898.0 12.391 13.38 11.4 Y Yes using Birks and Telford 2016 23.5 2876.0 2754.0 2998.0 12.088 13.08 11.1 Y Yes using Birks and Telford 2017 25.5 3006.0 2911.0 3101.0 12.904 13.88 11.93 Y Yes using Birks and Telford 2018 27.5 3135.0 3063.0 3207.0 12.521 13.51 11.53 Y Yes using Birks and Telford 2019 29.5 3265.0 3211.0 3319.0 12.949 13.93 11.97 Y Yes using Birks and Telford 2020 31.0 3363.0 3313.0 3413.0 13.899 14.94 12.86 Y Yes using Birks and Telford 2021 32.75 3476.0 3416.0 3536.0 11.354 12.35 10.35 Y Yes using Birks and Telford 2022