# Northern Hemisphere Holocene Latitudinal Temperature Reconstructions #----------------------------------------------------------------------- # 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/25890 # Description: NOAA Landing Page # Online_Resource: https://www1.ncdc.noaa.gov/pub/data/paleo/reconstructions/routson2019/ProxyRecords/temperature/ # Description: NOAA location of the template # # Original_Source_URL: # Description: # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Climate Reconstructions # # Dataset DOI: # # Parameter_Keywords: temperature #-------------------- # Contribution_Date # Date: 2019-03-27 #-------------------- # File_Last_Modified_Date # Date: 2019-03-27 #-------------------- # Title # Study_Name: Northern Hemisphere Holocene Latitudinal Temperature Reconstructions #-------------------- # Investigators # Investigators: Routson, C.C.; McKay, N.P.; Kaufman, D.S.; Erb, M.P.; Goosse, H.; Shuman, B.N.; Rodysill, J.R.; Ault, T. #-------------------- # Description_Notes_and_Keywords # Description: Composite latitude band (10S to 90N) temperature reconstructions for the Northern Hemisphere and tropics for the past 9,900 years, plus underlying proxy records. # Latitudinal temperature composites and proxy data and metadata are in Table S1. Mid-latitude hydroclimate proxy data and metadata are in Table S2. # # TableS1.xlsx contains: # 1.) metadata for each proxy record used in this analysis (PLEASE CITE ORIGINAL AUTHORS WHEN USING THEIR DATA). # 2.) Full references for each proxy record listed in the metadata tab # 3.) Data presented in Figure 3 including zonal temperature composites, latitudinal temperature gradient calculations, latitudinal insolation gradient, and mid-latitude hydroclimate composite # 4.) Raw temperature records as used in this study. Tabs/files are labeled by Site.Author.Year. These data include age and temperature reconstruction columns. # Some of these records were obtained from other syntheses efforts (e.g. Marcott et al., 2013) and the associated data (potentially not the original age model) are included here. # # TableS2.xlsx contains: # 1.) metadata for each proxy record used in this analysis (PLEASE CITE ORIGINAL AUTHORS WHEN USING THEIR DATA). # 2.) Full references for each proxy record listed in the metadata tab # 3.) Site level hydroclimate records used in this study. Tabs/files are labeled Site.Author.PubYear. These data include age and hydroclimate reconstruction columns. # Some of these records were obtained from other syntheses efforts and the associated data (potentially not the original age model) are included here. # Site names with “*” indicate records that are calibrated in units of mm/yr. # # Proxy Abreviations: # nitrogen 15 isotopes/argon 40 isotopes (15N/40AR) # glycerol dialkyle glycerol tetraethers (GDGT) # long chain diol index (LDI) # magnesium/calcium (Mg/Ca) # tree-ring width (TRW) # carbon 13 isotopes (d13C) # oxygen 18 isotopes (d18O) # loss on ignition (LOI) # strontium/calcium (Sr/Ca) # deuterium isotopes of leaf wax (dD) # records composed of two or more proxy types (hybrid) # #-------------------- # Publication # Authors: Cody C. Routson, Nicholas P. McKay, Darrell S. Kaufman, Michael P. Erb, Hugues Goosse, Bryan N. Shuman, Jessica R. Rodysill, Toby Ault # Published_Date_or_Year: 2019-03-27 # Published_Title: Mid-latitude net precipitation decreased with Arctic warming during the Holocene # Journal_Name: Nature # Volume: # Edition: # Issue: # Pages: # Report_Number: # DOI: 10.1038/s41586-019-1060-3 # Online_Resource: https://www.nature.com/articles/s41586-019-1060-3 # Full_Citation: # Abstract: The latitudinal temperature gradient between the Equator and the poles influences atmospheric stability, the strength of the jet stream and extratropical cyclones. Recent global warming is weakening the annual surface gradient in the Northern Hemisphere by preferentially warming the high latitudes; however, the implications of these changes for mid-latitude climate remain uncertain. Here we show that a weaker latitudinal temperature gradient - that is, warming of the Arctic with respect to the Equator - during the early to middle part of the Holocene coincided with substantial decreases in mid-latitude net precipitation (precipitation minus evapotranspiration, at 30 N to 50 N). We quantify the evolution of the gradient and of mid-latitude moisture both in a new compilation of Holocene palaeoclimate records spanning from 10 S to 90 N and in an ensemble of mid-Holocene climate model simulations. The observed pattern is consistent with the hypothesis that a weaker temperature gradient led to weaker mid-latitude westerly flow, weaker cyclones and decreased net terrestrial mid-latitude precipitation. Currently, the northern high latitudes are warming at rates nearly double the global average, decreasing the Equator-to-pole temperature gradient to values comparable with those in the early to middle Holocene. If the patterns observed during the Holocene hold for current anthropogenically forced warming, the weaker latitudinal temperature gradient will lead to considerable reductions in mid-latitude water resources. #------------------ # Funding_Agency # Funding_Agency_Name: Science Foundation Arizona Bisgrove Scholar # Grant: BP 0544-13 #------------------ # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: AGS-1602105, EAR-1347221 #------------------ # Funding_Agency # Funding_Agency_Name: State of Arizona Technology and Research Initiative Fund # Grant: #------------------ # Funding_Agency # Funding_Agency_Name: USGS Climate and Land Use Program # Grant: #------------------ # Site_Information # Site_Name: # Location: # Country: # Northernmost_Latitude: # Southernmost_Latitude: # Easternmost_Longitude: # Westernmost_Longitude: # Elevation: #------------------ # Data_Collection # Collection_Name: # Earliest_Year: # Most_Recent_Year: # Time_Unit: # Core_Length: # Notes: #------------------ # Chronology_Information # Chronology: # #---------------- # Variables # # Data variables follow are preceded by "##" in columns one and two. # Data line variables format: one per line, shortname-tab-variable components (what, material, error, units, seasonality, data type,detail, method, C or N for Character or Numeric data, free text) # # #---------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: # age (BP) dinocyst (°C) 1361.5 5.052338169 1522.6 8.731003974 1715.9 6.662773901 1844.9 7.674367198 2040.1 7.756242797 2171 5.942940652 2368.3 7.497659997 2500.8 5.975132777 2700.5 8.940736622 2834.1 6.774001553 3036.1 6.222296597 3171.7 6.453232964 3375.9 6.613006311 3513.2 7.089124988 3720.5 10.00175355 3859.3 7.19934083 4067.4 6.662179205 4207.1 6.426654298 4417.7 6.438802128 4559.3 8.76882062 4772.8 9.200465135 4915.7 6.699745177 5131.2 7.703021302 5275.1 8.713047979 5491.6 8.370451616 5636.9 8.457211728 5855.6 9.676664642 6001.8 6.442688857 6219.4 8.260608842 6363.1 8.051154308 6576.4 8.475955259 6715.6 8.126965652 6920.1 8.54151444 7054.1 6.922072466 7243.8 6.767870345 7363.4 8.491421546 7534.2 6.573754299 7644 7.558742524 7811.7 8.895661969 7925.4 7.993947111 8032 7.440297616 8177.5 9.341225423 8257.8 9.435753554 8296.4 12.23320172 8365 7.580614884 8462.3 15.4186441 8523.4 6.134831839 8593.8 10.75004572 8661.7 6.166042647 8674.7 9.351236769 8751.9 11.02987874 8789.1 6.519495078 8863 15.77683228 8911.8 5.875843397 8960.5 7.979167189 9033.4 9.265505454 9081.8 14.62664492 9142.7 5.67993256 9154.9 7.098247525 9217.4 9.937149456 9282.1 7.43266636 9369.3 13.21832547 9431.5 7.787853118 9514.4 9.531478254 9585.9 13.56649858 9604.1 7.814722827 9718.1 12.73196991 9798.2 13.53060003 10021.3 8.222617719 10169.2 5.581247426 10280.6 6.754474314 10457.3 9.726555344 10584.4 5.083180899 10798.6 8.636651204 10961.9 7.477507351 11108.9 12.07949043 11255.9 12.23689556 11446.2 5.905178864 11636.1 14.07780684 11777.4 10.93232623 11918.6 8.119875632 NaN 10.70605647 NaN 9.21770447 NaN 10.65740929 NaN 13.15973151 NaN 8.206978792 NaN 12.72650281 NaN 16.76398305 NaN 12.3590476 NaN 7.948772003 NaN 13.20974932 NaN 22.09711668 NaN 16.98832349 NaN 17.00144666 NaN 9.308639914 NaN 0.12852023 NaN 7.686014729 NaN 10.07161823 NaN 2.080007007 NaN 2.61261753 NaN 6.140899185 NaN 13.66948866 NaN 10.31765588 NaN 12.39538714 NaN 12.19287348 NaN 13.77582044 NaN 12.63592631 NaN 20.38206044 NaN 13.96913565 NaN 17.55738245 NaN 14.75293177 NaN 9.99549992 NaN 10.55290116 NaN 14.65550544 NaN 10.09116937 NaN 14.33406838 NaN 12.39288196 NaN 11.33889514 NaN 8.930260305 NaN 11.45367678 NaN 13.4337862 NaN 10.26320842 NaN 8.87546578 NaN 16.41615217 NaN 6.248283864 NaN 15.49685689 NaN 11.02762602 NaN 10.06466652 NaN 10.55264988 NaN 15.76323479 NaN 10.26776658 NaN 12.46061895 NaN 10.21917806 NaN 12.99599426 NaN 7.588854001 NaN 8.91548352 NaN 17.75 NaN 8.15131244 NaN 11.03833763 NaN 11.30295549 NaN 6.961365136 NaN 5.841005182 NaN 8.319738071 NaN 5.832239995 NaN 6.251265953 NaN 8.50147531 NaN 11.12406726 NaN 6.573726108 NaN 14.62079319 NaN 11.18413856 NaN 6.150001366 NaN 9.369682888 NaN 13.33884299 NaN 11.93058924 NaN 13.42058479 NaN 1.725249669 NaN 8.41316044 NaN 5.47913378 NaN 9.613695533 NaN 9.696569023 NaN 7.419938081 NaN 12.07992816 NaN 8.656959396 NaN 10.88196365 NaN 12.88451543 NaN 13.2424928 NaN 12.46006206 NaN 13.70394164 NaN 11.85984179 NaN 11.7950934 NaN 10.54192466 NaN 12.0785854 NaN 12.14804129 NaN 11.65884472 NaN 14.18948019 NaN 15.2222818 NaN 12.53716693 NaN 12.92263272 NaN 9.643215535 NaN 15.15547023 NaN 13.25255495 NaN 12.43225082 NaN 11.91662251 NaN 14.27154039 NaN 13.26245309 NaN 14.20186097 NaN 10.15588314 NaN 13.63739008 NaN 11.56569753 NaN 14.28809653 NaN 12.68732734 NaN 10.10847997 NaN 12.87443784 NaN 14.2825475 NaN 13.69612093 NaN 14.10128646 NaN 15.13472891 NaN 14.35329165 NaN 15.44862285 NaN 13.20064244 NaN 15.75377966 NaN 15.30070646 NaN 9.806698949 NaN 10.98907459 NaN 12.84246912 NaN 14.39876029 NaN 7.288820899 NaN 13.65446268 NaN 11.66740909 NaN 19.21494005 NaN 9.579515538 NaN 9.746535055 NaN 8.111467324 NaN 5.450811891 NaN 9.275981388 NaN 9.577051621 NaN 6.227109437 NaN 6.396685112 NaN 7.467614469 NaN 8.91005895 NaN 10.55049699 NaN 10.50157224 NaN 9.036854348 NaN 5.953134729 NaN 13.44633192 NaN 7.014018791 NaN 6.270722573 NaN 6.610853752 NaN 7.064826112 NaN 9.024758761 NaN 8.770343929