# 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) 0 944.1428571 50 974.3142857 100 1004.485714 150 1034.657143 200 1064.828571 250 1095 300 984.3333333 350 969.7504578 400 951.4028159 450 938.5048319 500 930.3580356 550 922.2112394 600 914.0644431 650 905.9176469 700 897.7708506 750 889.6240544 800 881.4772581 850 873.3304619 900 867.511872 950 870.6992143 1000 873.8865565 1050 877.0738987 1100 880.261241 1150 883.4485832 1200 886.6359255 1250 889.8232677 1300 893.0106099 1350 896.1979522 1400 894.4146445 1450 890.9599712 1500 887.505298 1550 884.0506247 1600 880.5959515 1650 877.1412782 1700 873.686605 1750 870.2319317 1800 866.7772585 1850 863.3225852 1900 863.2763607 1950 863.5811848 2000 863.8860089 2050 864.190833 2100 864.4956572 2150 864.8004813 2200 865.1053054 2250 865.4101295 2300 865.7149536 2350 866.1641415 2400 868.6939743 2450 871.223807 2500 873.7536397 2550 876.2834725 2600 878.8133052 2650 881.343138 2700 883.874121 2750 886.4105021 2800 888.9468832 2850 891.4832643 2900 894.0196453 2950 896.5560264 3000 899.0924075 3050 901.6287886 3100 904.1651696 3150 906.7015507 3200 909.2379318 3250 911.7743129 3300 914.3106939 3350 916.847075 3400 919.3834561 3450 921.9198372 3500 924.4562182 3550 926.9925993 3600 929.5289804 3650 922.6634559 3700 905.4626668 3750 888.2618777 3800 871.0610886 3850 863.1350237 3900 863.1205083 3950 863.1059929 4000 863.0914774 4050 863.076962 4100 863.0624466 4150 863.0479311 4200 863.0334157 4250 863.0189003 4300 863.0043849 4350 863.0303917 4400 863.073938 4450 863.1174843 4500 863.1610306 4550 863.2045769 4600 863.2481232 4650 863.2916695 4700 863.3352158 4750 863.3787621 4800 863.4223084 4850 875.7817778 4900 890.210119 4950 904.6384601 5000 919.0668013 5050 933.4951425 5100 947.9234837 5150 962.3518249 5200 976.7801661 5250 991.2085072 5300 1005.153319 5350 986.0853632 5400 967.0174071 5450 947.949451 5500 928.8814949 5550 909.8135388 5600 890.7455827 5650 871.6776266 5700 862.8686209 5750 862.8899787 5800 862.9113364 5850 862.9326942 5900 862.9540519 5950 862.9754096 6000 862.9967674 6050 867.2956493 6100 872.3574344 6150 877.4192194 6200 882.4810044 6250 887.5427895 6300 892.6045745 6350 895.9762235 6400 890.4659259 6450 884.9556282 6500 879.4453306 6550 873.9350329 6600 868.4247353 6650 862.9144376 6700 860.2112909 6750 860.6598035 6800 861.1083161 6850 861.5568287 6900 862.0053413 6950 862.4538539 7000 862.9023665 7050 895.9436498 7100 938.0539993 7150 980.1643487 7200 1022.274698 7250 1023.716999 7300 1012.946594 7350 1002.17619 7400 991.4057853 7450 980.6353808 7500 969.8649762 7550 959.0945716 7600 948.3241671 7650 937.5537625 7700 929.0507915 7750 923.8822178 7800 918.713644 7850 913.5450703 7900 908.3764966 7950 903.2079229 8000 898.0393491 8050 892.9166512 8100 887.8121507 8150 882.7076502 8200 877.6031496 8250 872.4986491 8300 867.3941486 8350 862.4308965 8400 862.5163275 8450 862.6017584 8500 862.6871894 8550 862.7726204 8600 862.8580514 8650 862.9434823 8700 864.6841999 8750 869.6605539 8800 874.636908 8850 879.6132621 8900 884.5896161 8950 889.5659702 9000 894.5423243 9050 894.079685 9100 890.6840447 9150 887.2884045 9200 883.8927642 9250 880.4971239 9300 902.5063257 9350 948.2464762 9400 993.9866267 9450 969.8054346 9500 918.2456663 9550 866.6858981 9600 912.1306266 9650 965.9876121 9700 1006.944424 9750 954.8741632 9800 902.8039027 9850 896.6767198 9900 896.6341788 9950 896.5916377 10000 910.7477387 10050 937.7528059 10100 964.7578732 10150 953.6152622 10200 928.1138951 10250 902.6125281 10300 877.1111611 10350 863.1813106 10400 863.5872444 10450 863.9931782 10500 864.3991119 10550 864.8050457 10600 865.2109794 10650 865.6169132 10700 866.022847 10750 866.4287807 10800 866.8347145 10850 867.0619265 10900 866.7259813 10950 866.3900361 11000 866.0540909