# 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/hydroclimate/ # 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: hydroclimate #-------------------- # 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) pollen (precip mm/yr) 0 1208.974437 50 1271.772128 100 1170.79287 150 1221.546614 200 1238.312273 250 1217.17565 300 1267.297818 350 1276.643924 400 1247.959103 450 1263.067579 500 1262.937471 550 1253.531485 600 1271.385351 650 1269.299264 700 1252.034195 750 1269.931039 800 1275.574846 850 1256.026697 900 1251.701521 950 1243.065089 1000 1232.686772 1050 1244.878943 1100 1227.018914 1150 1204.695255 1200 1223.075876 1250 1218.488178 1300 1199.55349 1350 1180.618802 1400 1196.892439 1450 1245.3834 1500 1261.798665 1550 1259.306818 1600 1232.706062 1650 1245.786077 1700 1250.39334 1750 1265.86836 1800 1235.705267 1850 1215.636411 1900 1238.291776 1950 1249.51438 2000 1269.837979 2050 1242.824274 2100 1167.121209 2150 1119.212406 2200 1130.112015 2250 1141.011623 2300 1151.911231 2350 1162.810839 2400 1173.710448 2450 1184.610056 2500 1195.233616 2550 1169.029982 2600 1142.826348 2650 1116.622715 2700 1111.003811 2750 1202.548319 2800 1257.382398 2850 1206.913643 2900 1187.718716 2950 1228.6458 3000 1252.142857 3050 1252.142857 3100 1258.38503 3150 1273.647065 3200 1244.321081 3250 1170.317813 3300 1175.873186 3350 1245.570954 3400 1186.137762 3450 1194.539178 3500 1209.408502 3550 1167.648044 3600 1098.878402 3650 1125.596095 3700 1004.904034 3750 1065.639237 3800 961.5758111 3850 1027.670922 3900 934.1388936 3950 1068.473638 4000 1056.832608 4050 1141.943741 4100 1005.43154 4150 1180.018227 4200 1045.122679 4250 1103.345203 4300 1064.880882 4350 1201.111882 4400 1079.205453 4450 1222.808652 4500 1026.514701 4550 1128.201708 4600 1079.05585 4650 1102.665652 4700 1108.690202 4750 1114.714752 4800 1113.786767 4850 1080.817019 4900 1136.014022 4950 983.6107611 5000 1112.395922 5050 1057.541589 5100 1016.395694 5150 1051.439644 5200 1099.604218 5250 1183.131742 5300 1259.872313 5350 1204.720783 5400 1149.643336 5450 1108.684131 5500 1067.724925 5550 1059.185688 5600 1052.827712 5650 1140.324438 5700 1213.450017 5750 1185.497114 5800 1145.86621 5850 1077.958465 5900 1028.928632 5950 1003.221254 6000 979.9394127 6050 958.2584908 6100 990.71294 6150 1040.501629 6200 1090.290317 6250 1130.743609 6300 1042.393853 6350 967.4736796 6400 939.4436488 6450 932.5864968 6500 960.6168315 6550 986.0896012 6600 1009.319161 6650 1027.702275 6700 1043.885534 6750 1048.629807 6800 1051.241434 6850 1061.718335 6900 1084.955321 6950 1108.192307 7000 1130.076445 7050 1151.730375 7100 1158.037938 7150 1132.878472 7200 1107.719007 7250 1122.868871 7300 1148.028138 7350 1158.270423 7400 1129.051658 7450 1099.832894 7500 1070.614129 7550 1041.395365 7600 1012.176601 7650 982.9578363 7700 1106.974425 7750 1135.110022 7800 1117.97897 7850 1100.282306 7900 1079.770828 7950 1059.25935 8000 1040.964678 8050 1022.984032 8100 1014.033835 8150 1013.545924 8200 1013.058013 8250 1024.559707 8300 1037.679338 8350 1050.798969 8400 1054.435926 8450 1051.555906 8500 1048.675885 8550 1043.041484 8600 1001.301702 8650 959.5619197 8700 917.8221374 8750 931.828766 8800 991.6196196 8850 972.4432941 8900 934.017981 8950 966.1444099 9000 975.9503354 9050 924.2722163 9100 941.8920661 9150 1027.318191 9200 985.6614782 9250 900.3966381 9300 893.0949125 9350 902.1244771 9400 963.6183066 9450 968.2786481 9500 906.7029928 9550 888.0582657 9600 887.7337563 9650 914.8624323 9700 943.3948192 9750 970.329098 9800 962.8625816 9850 907.533732 9900 898.1730014 9950 912.7810418 10000 927.3890822 10050 916.5846633 10100 904.3976179 10150 892.2105726 10200 880.0235272 10250 867.8364819 10300 863.869813 10350 863.6798146 10400 863.4898161 10450 863.2998176 10500 863.1098191 10550 863.0458168 10600 863.1543873 10650 863.2629579 10700 863.3715285 10750 863.480099 10800 861.1878597 10850 846.1779797 10900 831.1680998 10950 816.1582199 11000 801.14834