# Heshang Cave, Central China Holocene Surface Air Temperature Reconstruction #----------------------------------------------------------------------- # 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/30663 # 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/HeshangCave.Wang.2018.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/HeshangCave.Wang.2018.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: 2020-08-05 #------------------ # Title # Study_Name: Heshang Cave, Central China Holocene Surface Air Temperature Reconstruction #------------------ # Investigators # Investigators: Wang, Canfa; Bendle, James A.; Zhang, Hongbin; Yang, Yi; Liu, Deng; Huang, Junhua; Cui, Jingwei; Xie, Shucheng #------------------ # 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: Wang, Canfa; Bendle, James A.; Zhang, Hongbin; Yang, Yi; Liu, Deng; Huang, Junhua; Cui, Jingwei; Xie, Shucheng # Published_Date_or_Year: 2018 # Published_Title: Holocene temperature and hydrological changes reconstructed by bacterial 3-hydroxy fatty acids in a stalagmite from central China # Journal_Name: Quaternary Science Reviews # Volume: 192 # Edition: # Issue: # Pages: 97-105 # Report: # DOI: 10.1016/j.quascirev.2018.05.030 # Online_Resource: # Full_Citation: # Abstract: To achieve a sufficient understanding of the spatial dynamics of terrestrial climate variability, new proxies and networks of data that cover thousands of years and run up to the present day are needed. Here we show the first Gram-negative bacterial 3-hydroxy fatty acid (3-OH-FA) based temperature and hydrological records from any paleoclimate archive globally. The data, covering the last 9 ka before present (BP), are generated from an individual stalagmite, collected from Heshang Cave, located on a tributary of the Yangtze River, central China (30°27'N, 110°25'E; 294m). Our results indicate a clear early-to-middle Holocene Climatic Optimum (8.0-6.0 ka BP) followed by a long-term monotonic cooling and increasing variability over the last 0.9 ka BP. The hydrological record shows two relatively long wet periods (8.8-5.9 ka BP and 3.0-0 ka BP) and one relatively dry period (5.9-3.0 ka BP) in central China. We show that 3-OH-FA biomarkers hold promise as independent tools for paleoclimate reconstruction, with the potential to deconvolve temperature and hydrological signals from an individual stalagmite. #------------------ # 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: Heshang Cave # Location: Asia>Eastern Asia>China # Country: # Northernmost_Latitude: 30.45 # Southernmost_Latitude: 30.45 # Easternmost_Longitude: 110.4167 # Westernmost_Longitude: 110.4167 # Elevation: 294 #------------------ # Data_Collection # Collection_Name: HeshangCave.Wang.2018 # Earliest_Year: 8807.0 # Most_Recent_Year: 73.0 # Time_Unit: cal yr BP # Core_Length: # Notes: #------------------ # Species # Species_Name: # Species_Code: # Common_Name: #------------------ # Chronology_Information # Chronology: # depth 238Uconc 238Uconc_error 232Thconc 232Thconc_error d234Ua d234Ua_error 230Th/232Th b 230Th/232Th b_error 230Th/238Th b 230Th/238Th b_error Age raw c Age raw c_error age Age error age_type # 13.0 0.466 0.002 1.277 0.014 747.9 2.9 10.9 0.3 0.009 0.0 489.0 13.0 378.0 57.0 U/Th # 28.6 0.416 0.001 1.45 0.001 796.3 2.3 11.8 0.1 0.013 0.0 740.0 10.0 603.0 69.0 U/Th # 53.0 0.487 0.001 1.427 0.001 816.1 2.3 25.0 0.2 0.024 0.0 1387.0 13.0 1273.0 59.0 U/Th # 59.0 0.509 0.001 1.5 0.002 836.9 2.3 27.7 0.1 0.027 0.0 1542.0 12.0 1427.0 58.0 U/Th # 67.0 0.607 0.001 2.298 0.005 824.3 2.3 27.0 0.1 0.034 0.0 1966.0 13.0 1818.0 75.0 U/Th # 79.0 0.498 0.001 0.792 0.001 834.3 2.3 73.5 0.4 0.039 0.0 2286.0 15.0 2224.0 34.0 U/Th # 91.0 0.546 0.001 0.973 0.001 819.0 2.3 76.9 0.3 0.046 0.0 2722.0 15.0 2651.0 38.0 U/Th # 109.0 0.69 0.001 2.003 0.003 793.6 2.3 57.4 0.3 0.055 0.0 3328.0 17.0 3211.0 61.0 U/Th # 121.0 0.556 0.001 1.734 0.002 848.5 2.3 66.1 0.2 0.068 0.0 4038.0 15.0 3915.0 63.0 U/Th # 131.0 0.489 0.001 0.496 0.001 872.5 2.3 207.1 0.8 0.072 0.0 4221.0 20.0 4181.0 28.0 U/Th # 142.0 0.485 0.001 1.423 0.002 821.1 2.3 78.0 0.2 0.076 0.0 4591.0 19.0 4474.0 62.0 U/Th # 154.0 0.48 0.001 2.134 0.004 814.7 2.3 58.9 0.3 0.086 0.001 5251.0 33.0 5071.0 95.0 U/Th # 165.8 0.559 0.002 0.591 0.003 838.5 2.9 273.8 1.5 0.091 0.001 5485.0 46.0 5443.0 50.0 U/Th # 177.0 0.465 0.001 0.973 0.001 826.8 2.3 145.8 0.3 0.102 0.0 6182.0 19.0 6098.0 46.0 U/Th # 183.6 0.518 0.002 0.714 0.004 811.2 2.9 249.4 2.6 0.11 0.002 6756.0 102.0 6699.0 106.0 U/Th # 193.0 0.41 0.001 0.435 0.0 767.1 2.3 299.3 0.9 0.11 0.0 6929.0 29.0 6884.0 36.0 U/Th # 208.0 0.424 0.001 3.892 0.006 741.0 2.3 40.0 0.1 0.12 0.0 7733.0 25.0 7339.0 198.0 U/Th # 217.0 0.405 0.001 1.778 0.003 737.1 2.3 84.6 0.3 0.123 0.001 7899.0 34.0 7710.0 100.0 U/Th # 228.0 0.447 0.001 0.908 0.001 733.4 2.3 182.9 0.4 0.125 0.0 8071.0 25.0 7983.0 51.0 U/Th # 240.0 0.443 0.001 0.964 0.007 795.3 2.9 204.2 1.2 0.139 0.001 8719.0 63.0 8627.0 78.0 U/Th # 253.0 3.797 0.012 3.127 0.052 710.9 2.9 555.6 1.1 0.144 0.001 9483.0 43.0 9446.0 46.0 U/Th #------------------ # 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) # ## sampleID sample identification,,,,,speleothems;climate reconstructions,,,C,sampleID ## age age,,,calendar year before present,,speleothems;climate reconstructions,,,N, ## RAN15 organic compound index,,,,,speleothems;climate reconstructions,,,N,RAN15 ## temperature surface air temperature,organic compound index,,degree Celsius,annual,speleothems;climate reconstructions,,,N,based on RAN15 # #------------------ # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing_Values: nan # sampleID age RAN15 temperature HS4-204 73.0 1.27 19.2 HS4-198 319.0 1.54 18.4 HS4-196 366.0 1.45 18.6 HS4-191 486.0 2.14 16.5 HS4-187 560.0 0.85 20.5 HS4-184 639.0 1.47 18.6 HS4-182 695.0 1.65 18.0 HS4-179 765.0 1.84 17.5 HS4-175 853.0 1.46 18.6 HS4-174 877.0 1.59 18.2 HS4-170 964.0 1.52 18.4 HS4-168 1014.0 1.42 18.7 HS4-166 1073.0 1.45 18.6 HS4-165 1107.0 1.37 18.9 HS4-164 1157.0 1.74 17.8 HS4-161 1296.0 1.56 18.3 HS4-159 1397.0 1.49 18.5 HS4-156 1531.0 1.41 18.7 HS4-154 1635.0 1.58 18.2 HS4-150 1813.0 1.53 18.4 HS4-146 1995.0 1.46 18.6 HS4-144 2080.0 1.26 19.2 HS4-139 2306.0 1.39 18.8 HS4-135 2447.0 1.31 19.1 HS4-132 2551.0 1.34 19.0 HS4-130 2664.0 1.61 18.2 HS4-129 2691.0 1.44 18.7 HS4-128 2717.0 1.23 19.3 HS4-123 2879.0 1.58 18.3 HS4-120 3003.0 1.39 18.8 HS4-119 3039.0 1.29 19.1 HS4-117 3148.0 1.12 19.6 HS4-115 3231.0 1.28 19.2 HS4-112 3353.0 1.62 18.1 HS4-103 3960.0 1.3 19.1 HS4-101 4018.0 1.52 18.4 HS4-100 4045.0 1.5 18.5 HS4-97 4145.0 1.55 18.3 HS4-95 4223.0 1.33 19.0 HS4-92 4317.0 1.11 19.7 HS4-91 4364.0 1.52 18.4 HS4-86 4592.0 1.49 18.5 HS4-83 4782.0 1.3 19.1 HS4-82 4860.0 1.1 19.7 HS4-77 5087.0 1.43 18.7 HS4-76 5136.0 1.36 18.9 HS4-71 5314.0 1.27 19.2 HS4-67 5546.0 1.2 19.4 HS4-66 5619.0 1.11 19.7 HS4-64 5802.0 1.09 19.7 HS4-61 6058.0 1.31 19.1 HS4-60 6129.0 1.32 19.0 HS4-54 6558.0 1.0 20.0 HS4-52 6686.0 1.06 19.8 HS4-50 6741.0 0.98 20.1 HS4-49 6775.0 1.25 19.2 HS4-41 6997.0 1.0 20.0 HS4-40 7026.0 0.81 20.6 HS4-33 7305.0 1.13 19.6 HS4-30 7419.0 0.79 20.6 HS4-28 7503.0 0.89 20.3 HS4-23 7663.0 1.15 19.5 HS4-22 7718.0 1.03 19.9 HS4-21 7759.0 1.07 19.8 HS4-18 7871.0 1.02 19.9 HS4-16 7925.0 0.97 20.1 HS4-15 7956.0 0.9 20.3 HS4-13 8029.0 1.3 19.1 HS4-11 8100.0 1.15 19.5 HS4-9 8178.0 1.19 19.4 HS4-6 8479.0 1.1 19.7 HS4-3 8648.0 1.15 19.6 HS4-1 8807.0 1.14 19.6