# Pupuke Lake Surface 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/30829 # 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/PupukePollen.VandenBos.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/PupukePollen.VandenBos.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: 2020-05-16 #------------------ # Title # Study_Name: Pupuke Holocene Lake Surface and Surface Air Temperature Reconstructions #------------------ # Investigators # Investigators: van den Bos, Valerie; Rees, Andrew; Newnham, Rewi; Vandergoes, Marcus; Wilmshurst, Janet; Augustinus, Paul #------------------ # 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. Note added by Temperature-12k authors: WA-PLS reconstruction more reliable than MAT reconstruction. #------------------ # Publication # Authors: van den Bos, Valerie; Rees, Andrew; Newnham, Rewi; Vandergoes, Marcus; Wilmshurst, Janet; Augustinus, Paul # Published_Date_or_Year: 2018 # Published_Title: Holocene temperature, humidity and seasonality in northern New Zealand linked to Southern Hemisphere summer insolation # Journal_Name: Quaternary Science Reviews # Volume: 201 # Edition: # Issue: # Pages: 77-88 # Report: # DOI: 10.1016/j.quascirev.2018.10.008 # Online_Resource: # Full_Citation: # Abstract: The Holocene thermal maximum (HTM) is a spatio-temporally variable period of generally warmer conditions during the early and middle Holocene that is often used as an analogue for future climate change. Global scale climate reconstructions and models tend to smooth out the variations and complexity of the HTM and inconsistencies between reconstructions from different locations and proxies are often attributed to bias arising from different locations or proxies. We use these differences as a source of information about seasonality and precipitation during the Holocene in a multi-proxy investigation of the sediments of Lake Pupuke, northern New Zealand. The sediments, spanning the last 16 kyr, were analysed for pollen, from which mean annual air temperatures (MAAT) and effective precipitation were estimated, and chironomids, from which summer air temperature (SmT) was estimated. We found no evidence for an HTM in the MAAT reconstruction, questioning the validity of treating the early-to-mid Holocene as an analogue for future climate change in northern New Zealand. SmT increases between 10 and 3 cal kyr BP, correlating strongly with integrated local summer insolation. Early-Holocene low seasonality (from 12 to 9.3 cal kyr BP) was likely driven by low local summer insolation intensity. An early-to-mid-Holocene wet period (9.6–7.5 cal kyr BP) corresponds to relatively high southern westerly wind (SWW) strength. Mid-to-late-Holocene summers following the wet period were hot and dry, especially 4.0–2.4 cal kyr BP, allowing the tall conifer, kauri (Agathis australis) to expand throughout northern New Zealand. Low effective precipitation at this time is consistent with increased evapotranspiration due to higher SmT, although reduced precipitation due to southward displaced SWW or increased El Niño frequency may also have contributed. #------------------ # 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: Pupuke Lake # Location: Australia/New Zealand>New Zealand # Country: New Zealand # Northernmost_Latitude: -36.78 # Southernmost_Latitude: -36.78 # Easternmost_Longitude: 174.77 # Westernmost_Longitude: 174.77 # Elevation: 5 #------------------ # Data_Collection # Collection_Name: PupukePollen.VandenBos.2018 # Earliest_Year: 16138.0 # Most_Recent_Year: 1001.0 # Time_Unit: cal yr BP # Core_Length: # Notes: #------------------ # Species # Species_Name: # Species_Code: # Common_Name: #------------------ # Chronology_Information # Chronology: # OriginalDateID depth age_type age 1SD AdditionalNotes # Top 0.0 Core top -57.0 3.0 nan # Rangitoto1/2 84.0 tephra 530.0 31.0 samples have no thickness # Taupo 205.0 tephra 1718.0 10.0 samples have no thickness # Tuhua 399.0 tephra 7637.0 100.0 samples have no thickness # Rotoma 465.0 tephra 9423.0 120.0 samples have no thickness # Waiohau 618.0 tephra 14009.0 155.0 samples have no thickness # Rotorua 653.0 tephra 15635.0 412.0 samples have no thickness # Rerewhakaaitu 701.0 tephra 17496.0 462.0 samples have no thickness #------------------ # 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, ## ageMin age,,range lower bound,calendar year before present,,pollen;climate reconstructions,,,N, ## ageMax age,,range upper bound,calendar year before present,,pollen;climate reconstructions,,,N, ## temperature temperature,,,degree Celsius,annual,pollen;climate reconstructions,,modern analogue technique,N,Defer to WA-PLAS reconstruction ## uncertainty temperature,,unspecified margin of error,degree Celsius,annual,pollen;climate reconstructions,,modern analogue technique,N, ## reliable notes,,,,,pollen;climate reconstructions,,,C,Data are reliable (Yes or No);Modern Analogue Technique ## temperature-1 surface air temperature,,,degree Celsius,annual,pollen;climate reconstructions,,,N,WAPLS ## uncertainty-2 surface air temperature,,unspecified margin of error,degree Celsius,annual,pollen;climate reconstructions,,,N,WAPLS ## reliable-1 notes,,,,,pollen;climate reconstructions,,,C,Data are reliable (Yes or No); WAPLS # #------------------ # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing_Values: nan # OriginalSampleID depth age ageMin ageMax temperature uncertainty reliable temperature-1 uncertainty-2 reliable-1 #1-145-2 134.0 1001.0 535.0 1555.0 14.42 1.43 Y 13.94 1.53 Y #1-154 143.0 1108.0 581.0 1641.0 14.34 1.43 Y 13.72 1.53 Y #1-165-2 153.0 1227.0 692.0 1712.0 14.52 1.44 Y 13.66 1.53 Y #1-174-2 162.0 1332.0 764.0 1725.0 14.48 1.43 Y 13.86 1.53 Y #1-180-2 168.0 1402.0 819.0 1731.0 14.57 1.44 Y 13.31 1.54 Y #1-195-2 183.0 1571.0 986.0 1743.0 14.47 1.44 Y 13.58 1.54 Y #1-205-2 193.0 1669.0 1139.0 1754.0 14.58 1.43 Y 13.81 1.54 Y #2-39-2 206.0 1721.0 1617.0 1972.0 14.6 1.43 Y 13.51 1.54 Y #2-54-4 221.0 1970.0 1663.0 3674.0 14.57 1.43 Y 13.34 1.53 Y #2-64-2 231.0 2267.0 1692.0 4261.0 14.42 1.44 Y 13.54 1.54 Y #2-75-4 242.0 2628.0 1701.0 4778.0 14.53 1.44 Y 13.55 1.54 Y #2-85-2 252.0 2963.0 1707.0 5187.0 14.62 1.43 Y 14.1 1.54 Y #2-94-4 261.0 3272.0 1718.0 5515.0 14.62 1.44 Y 13.47 1.54 Y #2-119 269.0 3548.0 1738.0 5786.0 14.63 1.43 Y 13.63 1.54 Y #2-129-4 279.0 3889.0 1854.0 6190.0 14.48 1.43 Y 13.68 1.55 Y #2-135 285.0 4095.0 1974.0 6399.0 14.49 1.43 Y 13.83 1.54 Y #2-144-4 294.0 4403.0 2174.0 6718.0 14.57 1.43 Y 13.62 1.54 Y #2-150 300.0 4610.0 2327.0 6920.0 14.64 1.43 Y 14.06 1.54 Y #2-159-4 309.0 4921.0 2600.0 7168.0 14.55 1.44 Y 13.54 1.54 Y #2-165 315.0 5126.0 2785.0 7307.0 14.57 1.44 Y 14.11 1.53 Y #2-172-4 322.0 5366.0 3068.0 7447.0 14.55 1.43 Y 13.63 1.53 Y #2-179 329.0 5608.0 3297.0 7543.0 14.46 1.43 Y 13.74 1.54 Y #2-189-2 339.0 5948.0 3651.0 7646.0 14.56 1.43 Y 13.49 1.55 Y #2-197 347.0 6223.0 3940.0 7702.0 14.45 1.43 Y 13.22 1.54 Y #2-204 354.0 6460.0 4226.0 7742.0 14.51 1.43 Y 13.03 1.54 Y #4-39 365.0 6827.0 4711.0 7792.0 14.65 1.43 Y 13.74 1.54 Y #4-45-4 371.0 7023.0 5012.0 7816.0 14.57 1.44 Y 13.46 1.53 Y #4-50 376.0 7179.0 5275.0 7839.0 14.5 1.43 Y 13.37 1.54 Y #4-56 382.0 7350.0 5658.0 7863.0 14.51 1.43 Y 13.35 1.54 Y #4-61 387.0 7471.0 6028.0 7883.0 14.65 1.43 Y 13.42 1.53 Y #4-67 393.0 7568.0 6601.0 7903.0 14.52 1.44 Y 13.0 1.54 Y #4-72 398.0 7627.0 7352.0 7878.0 14.49 1.43 Y 13.52 1.53 Y #5-47 399.0 7640.0 7435.0 7843.0 14.54 1.43 Y 14.03 1.53 Y #5-51-2 403.0 7687.0 7384.0 8341.0 14.51 1.44 Y 13.95 1.54 Y #5-56-4 408.0 7765.0 7414.0 8749.0 14.41 1.44 Y 13.4 1.54 Y #5-60 412.0 7849.0 7442.0 8950.0 14.55 1.43 Y 13.86 1.53 Y #5-65-4 417.0 7996.0 7480.0 9128.0 14.53 1.43 Y 14.27 1.53 Y #5-71 423.0 8199.0 7537.0 9273.0 14.67 1.43 Y 13.67 1.53 Y #5-76-4 428.0 8381.0 7582.0 9368.0 14.51 1.44 Y 13.75 1.53 Y #5-80 432.0 8528.0 7623.0 9434.0 14.48 1.45 Y 13.36 1.53 Y #5-86-4 438.0 8747.0 7716.0 9500.0 14.48 1.46 Y 13.29 1.53 Y #5-91 443.0 8924.0 7819.0 9558.0 14.54 1.44 Y 13.37 1.53 Y #5-102 454.0 9244.0 8196.0 9666.0 14.45 1.46 Y 13.32 1.53 Y #5-111 463.0 9393.0 8978.0 9720.0 14.57 1.43 Y 13.14 1.53 Y #5-130-2 471.0 9500.0 9115.0 10444.0 14.19 1.49 Y 13.0 1.54 Y #5-137-2 478.0 9623.0 9144.0 11057.0 13.97 1.47 Y 13.05 1.54 Y #5-142-2 483.0 9745.0 9166.0 11421.0 14.53 1.43 Y 13.12 1.54 Y #5-150-2 491.0 9988.0 9209.0 11846.0 14.51 1.44 Y 13.47 1.53 Y #5-158-2 499.0 10252.0 9251.0 12225.0 14.51 1.47 Y 13.39 1.53 Y #5-166-2 507.0 10526.0 9304.0 12541.0 13.97 1.49 Y 12.38 1.54 Y #5-176-2 517.0 10867.0 9387.0 12873.0 14.1 1.49 Y 12.94 1.55 Y #5-190-2 531.0 11356.0 9555.0 13318.0 13.98 1.46 Y 13.38 1.54 Y #5-201-4 542.0 11741.0 9792.0 13673.0 12.77 1.59 Y 12.06 1.55 Y #5-213-2 554.0 12161.0 10179.0 13926.0 14.32 1.44 Y 13.09 1.54 Y #6-153-4 564.0 12506.0 10480.0 14060.0 14.07 1.51 Y 12.33 1.55 Y #6-171-4 575.0 12890.0 10867.0 14170.0 13.68 1.58 Y 12.08 1.56 Y #6-181-4 585.0 13226.0 11256.0 14245.0 12.43 1.65 Y 11.65 1.56 Y #6-192 596.0 13574.0 11787.0 14316.0 12.19 1.63 Y 11.0 1.57 Y #7-139-2 619.0 14050.0 13661.0 14479.0 11.75 1.66 Y 11.01 1.57 Y #7-157-2 637.0 14844.0 13867.0 15973.0 10.83 1.66 Y 9.84 1.59 Y #7-186-2 654.0 15616.0 14774.0 16461.0 9.58 1.65 Y 9.95 1.58 Y #7-202-2 670.0 16138.0 15022.0 17478.0 8.19 1.53 Y 9.27 1.58 Y