# 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 1115.255952 50 1101.827381 100 1055.178572 150 1067.035714 200 1055.118099 250 1047.33057 300 1039.543041 350 1031.755512 400 1024.893548 450 1039.791429 500 1054.689311 550 1069.587193 600 1084.485075 650 1075.490736 700 1061.308505 750 1047.126275 800 1035.213985 850 1035.672754 900 1036.131524 950 1036.433717 1000 1033.0847 1050 1029.735683 1100 1026.386665 1150 1019.166772 1200 1011.642953 1250 1004.119134 1300 986.8945052 1350 967.4426796 1400 947.990854 1450 963.5111352 1500 994.0651818 1550 1024.619228 1600 1027.858486 1650 1011.755678 1700 995.6528692 1750 981.7565145 1800 970.3331547 1850 958.9097949 1900 958.6750517 1950 978.5397696 2000 998.4044875 2050 1013.60744 2100 1014.341471 2150 1015.075503 2200 1010.148238 2250 967.2532923 2300 924.3583467 2350 882.3238031 2400 893.7471629 2450 905.1705228 2500 916.5938826 2550 935.2996535 2600 954.797356 2650 974.2950585 2700 962.1110361 2750 941.4035039 2800 920.6959718 2850 942.4317099 2900 968.3037106 2950 994.1757113 3000 1020.047712 3050 1045.919713 3100 1066.966888 3150 1062.224515 3200 1057.482143 3250 1052.73977 3300 1047.997398 3350 1043.255025 3400 1038.663117 3450 1034.293183 3500 1029.923248 3550 1025.736572 3600 1021.714246 3650 1017.691919 3700 1009.512932 3750 999.0996761 3800 988.68642 3850 995.3713347 3900 1018.562974 3950 1041.754613 4000 1064.181843 4050 1079.908542 4100 1095.635241 4150 1111.36194 4200 1103.066295 4250 1084.278132 4300 1065.489968 4350 1041.552238 4400 1004.98242 4450 968.4126015 4500 931.8427834 4550 937.6461786 4600 944.9467221 4650 933.5396229 4700 971.5225795 4750 1063.702007 4800 1054.139771 4850 1018.595921 4900 1033.14836 4950 1047.700799 5000 1062.253238 5050 1062.715225 5100 1056.047104 5150 1049.378984 5200 1043.153794 5250 1038.205126 5300 1020.468765 5350 992.454271 5400 976.8783206 5450 963.4767773 5500 950.075234 5550 936.6736907 5600 923.2721473 5650 928.9004655 5700 943.8779807 5750 958.855496 5800 973.8330112 5850 988.2857143 5900 988.2857143 5950 988.2857143 6000 988.2857143 6050 988.2857143 6100 987.9902172 6150 987.2505868 6200 985.9969429 6250 978.9704542 6300 1006.301 6350 1001.89157 6400 986.7907831 6450 985.1671465 6500 1000.267933 6550 1013.717614 6600 1015.967323 6650 1018.217032 6700 1020.466741 6750 1022.71645 6800 1026.667664 6850 1032.368982 6900 1038.070299 6950 1043.771617 7000 1049.472934 7050 1045.000808 7100 1038.837222 7150 1025.954379 7200 1014.099978 7250 1002.212422 7300 956.8543027 7350 988.5351374 7400 1005.05777 7450 1019.973649 7500 1019.890071 7550 1009.227066 7600 998.5640618 7650 987.9010571 7700 977.2380525 7750 975.7039752 7800 974.6414747 7850 973.5789741 7900 972.5164736 7950 963.9051459 8000 932.031106 8050 900.157066 8100 868.2830261 8150 836.4089862 8200 806.5140443 8250 828.129142 8300 849.7442396 8350 863.1402238 8400 865.7735352 8450 868.4068466 8500 881.5686581 8550 896.9022109 8600 912.2357637 8650 927.5693164 8700 942.9028692 8750 931.2201284 8800 903.0491826 8850 874.8782368 8900 846.707291 8950 818.5363452 9000 799.8900639 9050 794.7812597 9100 789.6724556 9150 784.5636514 9200 779.4548473 9250 774.7142857 9300 774.7142857 9350 774.7142857 9400 774.7142857 9450 774.7142857 9500 774.7142857 9550 774.7142857 9600 775.3483677 9650 776.1450332 9700 776.9416986 9750 777.7383641 9800 778.5350296 9850 779.3316951 9900 780.8736953 9950 783.1043586 10000 785.3350219 10050 787.3919303 10100 789.1673562 10150 790.9427821 10200 790.9327851 10250 785.3788887 10300 779.8249922 10350 774.8235172 10400 774.5048511 10450 774.1861849 10500 773.8675187 10550 774.0112881 10600 774.1706212 10650 774.3299543 10700 774.4892874 10750 774.6486205 10800 774.8079536 10850 774.8571429 10900 774.8571429 10950 774.8571429 11000 774.7312242