# 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 NaN 50 NaN 100 NaN 150 NaN 200 1179.857143 250 1180.214326 300 1180.57151 350 1180.928693 400 1181.285876 450 1181.64306 500 1182.000243 550 1182.357427 600 1182.571429 650 1182.571429 700 1182.571429 750 1182.571429 800 1182.571429 850 1182.571429 900 1182.571429 950 1182.571429 1000 1182.571429 1050 1182.571429 1100 1182.571429 1150 1182.571429 1200 1182.571429 1250 1182.571429 1300 1182.571429 1350 1182.571429 1400 1182.571429 1450 1180.777937 1500 1174.85489 1550 1168.931844 1600 1163.008797 1650 1157.08575 1700 1151.162704 1750 1145.239657 1800 1139.31661 1850 1133.393563 1900 1127.470517 1950 1136.378514 2000 1150.184692 2050 1163.99087 2100 1177.797048 2150 1181.967028 2200 1181.04313 2250 1180.119232 2300 1179.195334 2350 1178.271435 2400 1177.347537 2450 1176.423639 2500 1175.49974 2550 1173.206498 2600 1169.299904 2650 1165.39331 2700 1161.486716 2750 1157.580122 2800 1153.673528 2850 1149.766934 2900 1145.86034 2950 1136.697108 3000 1117.373068 3050 1098.049027 3100 1078.724987 3150 1086.008771 3200 1097.660634 3250 1109.312497 3300 1120.96436 3350 1132.616223 3400 1144.268086 3450 1155.919949 3500 1145.593309 3550 1132.689451 3600 1119.785593 3650 1106.881735 3700 1093.977877 3750 1081.074019 3800 1068.170161 3850 1055.266304 3900 1042.362446 3950 1029.458588 4000 1016.55473 4050 1003.650872 4100 991.0257503 4150 992.3391772 4200 993.652604 4250 994.9660309 4300 996.2794578 4350 997.5928846 4400 998.9063115 4450 1004.279932 4500 1016.143837 4550 1028.007742 4600 1039.871647 4650 1051.735552 4700 1063.599456 4750 1075.463361 4800 1087.327266 4850 1099.191171 4900 1111.055076 4950 1122.918981 5000 1134.782886 5050 1146.646791 5100 1156.336055 5150 1149.338289 5200 1142.340523 5250 1135.342757 5300 1128.344991 5350 1121.347225 5400 1114.349459 5450 1113.246003 5500 1118.514663 5550 1123.783324 5600 1129.051985 5650 1134.320646 5700 1137.142857 5750 1137.142857 5800 1137.142857 5850 1134.776637 5900 1129.227711 5950 1123.678786 6000 1118.129861 6050 1112.580936 6100 1107.03201 6150 1105.43967 6200 1111.175737 6250 1116.911804 6300 1122.647871 6350 1128.383938 6400 1134.120005 6450 1139.856072 6500 1131.278576 6550 1112.183123 6600 1093.08767 6650 1073.992217 6700 1054.896764 6750 1051.704874 6800 1056.127298 6850 1060.549721 6900 1064.972144 6950 1069.394567 7000 1073.81699 7050 1078.239413 7100 1082.661837 7150 1087.08426 7200 1091.581529 7250 1096.310969 7300 1101.04041 7350 1105.769851 7400 1110.499292 7450 1115.228733 7500 1119.958174 7550 1124.687615 7600 1129.417055 7650 1132.428571 7700 1132.428571 7750 1132.428571 7800 1132.428571 7850 1132.428571 7900 1131.029264 7950 1129.513171 8000 1127.997079 8050 1126.480986 8100 1124.964894 8150 1123.448801 8200 1121.932709 8250 1120.416617 8300 1108.929274 8350 1084.880425 8400 1060.831576 8450 1036.782728 8500 1012.733879 8550 988.68503 8600 964.6361812 8650 940.5873325 8700 925.9715491 8750 967.4588257 8800 1008.946102 8850 1050.433379 8900 1091.920655 8950 1075.756684 9000 1059.282276 9050 1042.807868 9100 1026.33346 9150 1009.859051 9200 993.3846431 9250 976.9102349 9300 960.4358267 9350 935.4474729 9400 906.7414134 9450 878.0353538 9500 785.3084972 9550 774.0388703 9600 773.921224 9650 773.8035778 9700 773.6859315 9750 773.5682852 9800 773.4506389 9850 773.3329927 9900 773.380368 9950 773.5386169 10000 773.6968659 10050 773.8551148 10100 774.0133638 10150 774.1716128 10200 774.3298617 10250 774.4285714 10300 774.4285714 10350 774.4285714 10400 774.4285714 10450 774.4285714 10500 774.4285714 10550 774.4285714 10600 774.4285714 10650 774.4285714 10700 774.4285714 10750 774.4285714 10800 774.4285714 10850 774.4285714 10900 774.4285714 10950 774.4285714 11000 774.4285714