# 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 1097.010661 50 1075.106183 100 1020.25974 150 1023.014925 200 965.7206822 250 1070.036248 300 1123.857143 350 1150.905714 400 1177.954285 450 1205.002856 500 1190.711933 550 1144.854202 600 1098.996471 650 1059.419586 700 1060.418303 750 1061.41702 800 1062.415736 850 1062.364203 900 1061.864844 950 1061.365486 1000 1060.866128 1050 1060.366769 1100 1059.867411 1150 1059.368053 1200 1072.977858 1250 1089.373454 1300 1105.769049 1350 1114.784929 1400 1112.829109 1450 1110.873289 1500 1108.917469 1550 1106.961649 1600 1105.00583 1650 1103.05001 1700 1102.008985 1750 1101.759305 1800 1101.509626 1850 1101.298597 1900 1101.423437 1950 1101.548277 2000 1101.673116 2050 1101.797956 2100 1101.922795 2150 1102.047635 2200 1099.378558 2250 1087.726866 2300 1076.075174 2350 1064.423482 2400 1067.230008 2450 1073.555212 2500 1079.880417 2550 1086.205621 2600 1092.530825 2650 1098.85603 2700 1105.181234 2750 1092.686211 2800 1078.953859 2850 1065.221508 2900 1061.645936 2950 1068.012754 3000 1074.379571 3050 1080.746389 3100 1087.113206 3150 1093.480024 3200 1099.846841 3250 1098.604186 3300 1093.069633 3350 1087.535079 3400 1086.480859 3450 1102.653347 3500 1118.825835 3550 1134.998324 3600 1151.170812 3650 1167.343301 3700 1183.515789 3750 1199.688278 3800 1215.860766 3850 1196.465322 3900 1167.002235 3950 1137.539148 4000 1108.076061 4050 1098.163632 4100 1103.249321 4150 1108.335009 4200 1113.420697 4250 1118.506385 4300 1123.592073 4350 1128.677762 4400 1133.76345 4450 1140.059233 4500 1153.8584 4550 1167.657567 4600 1181.456735 4650 1195.255902 4700 1176.833625 4750 1155.812781 4800 1134.791937 4850 1113.771092 4900 1096.587799 4950 1080.957784 5000 1065.327769 5050 1049.697754 5100 1065.529497 5150 1113.029824 5200 1160.530152 5250 1208.03048 5300 1235.760955 5350 1213.858592 5400 1191.956228 5450 1170.053864 5500 1147.26332 5550 1112.91315 5600 1078.56298 5650 1044.21281 5700 1009.86264 5750 989.3624115 5800 1021.07167 5850 1052.780929 5900 1084.490188 5950 1116.199447 6000 1147.908706 6050 1143.040845 6100 1122.480385 6150 1101.919926 6200 1081.359466 6250 1060.799006 6300 1042.766235 6350 1035.516815 6400 1028.267395 6450 1021.017975 6500 1013.768555 6550 1006.519135 6600 999.2697151 6650 992.0202951 6700 984.7708752 6750 977.5214552 6800 970.2720353 6850 963.0226153 6900 955.7731954 6950 948.5237754 7000 941.2743554 7050 934.0249355 7100 926.7755155 7150 919.5260956 7200 912.2766756 7250 905.0272557 7300 897.7778357 7350 890.5284158 7400 883.2789958 7450 876.0295759 7500 868.7801559 7550 864.1447705 7600 872.9067051 7650 881.6686396 7700 890.4305741 7750 899.1925087 7800 907.9544432 7850 916.7163778 7900 925.4783123 7950 934.2402468 8000 943.0021814 8050 951.7641159 8100 960.5260504 8150 969.287985 8200 978.0499195 8250 986.8118541 8300 995.5737886 8350 1004.335723 8400 1013.097658 8450 1021.859592 8500 1030.621527 8550 1039.383461 8600 1048.145396 8650 1056.90733 8700 1065.669265 8750 1074.431199 8800 1083.193134 8850 1082.281466 8900 1078.601115 8950 1074.920765 9000 1071.240415 9050 1067.560065 9100 1063.879715 9150 1060.199365 9200 1056.519014 9250 1052.838664 9300 1049.158314 9350 1045.477964 9400 1041.797614 9450 1037.887829 9500 1031.495049 9550 1025.10227 9600 1018.709491 9650 1012.316711 9700 1005.923932 9750 999.5311521 9800 993.1383726 9850 986.7455932 9900 980.3528137 9950 973.9600342 10000 967.5672548 10050 961.1744753 10100 953.9628201 10150 945.4794442 10200 936.9960684 10250 928.5126925 10300 920.0293166 10350 911.5459408 10400 903.0625649 10450 894.579189 10500 886.0958132 10550 877.6124373 10600 870.0407799 10650 865.3981363 10700 860.7554928 10750 856.1128493 10800 851.4702057 10850 846.8275622 10900 842.1849187 10950 837.5422751 11000 832.8996316