# 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/temperature/ # 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: temperature #-------------------- # 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) alkenone (°C) 137 20.529 235 20.662 333 20.515 431 20.485 498 20.632 533 20.647 568 20.721 603 20.75 638 20.809 675 20.647 712 20.132 748 20.559 785 19.691 822 18.324 863 19.706 910 20.75 957 20.809 1003 20.735 1050 20.75 1097 20.941 1143 20.706 1190 20.529 1515 20.676 1630 20.353 1745 20.456 1860 20.721 1975 20.397 2090 20.25 2270 20.309 2451 20.441 2632 20.574 2813 20.294 2994 20.735 3175 20.5 3355 20.088 3536 20.603 3717 20.618 3898 20.456 4079 20.632 4260 20.926 4321 21.324 4383 20.926 4445 20.368 4507 20.632 4568 20.735 4661 20.353 4723 20.706 4785 20.941 4846 20.544 4908 20.618 4970 20.721 5032 21.544 5093 21.103 5155 21.132 5217 20.956 5279 20.618 5372 20.882 5497 20.588 5621 20.75 5746 20.794 5870 21.147 5995 21.338 6120 21.529 6244 21.544 6369 21.265 6493 21.103 6618 21.235 6742 21.221 6867 21.015 6992 20.897 7054 21.309 7178 21.441 7303 21.515 7400 21.294 7469 21.147 7538 21.309 7570 21.412 7603 21.353 7635 21.221 7667 21.353 7699 21.206 7731 21.279 7763 21.103 7795 21.235 7828 21.221 7860 21.132 7892 20.926 8026 20.971 8159 20.426 8293 20.279 8528 20.985 8763 20.324 8998 20.176 9233 20.118 9468 20.353 9631 19.647 9793 19.441 9956 19.632 10091 19.547 10200 19.588 10308 19.574 10417 19.471 10525 19.382 10634 19.72 10742 19.32 10851 19.65 10960 19.63 11068 19.34 11177 19.6 11286 19.63 11373 19.588 11440 19.441 11506 19.353 11573 19.324 11639 19.294 11706 19.235 11772 19.191 11905 19.147 11939 19.206 11972 19.103 12171 17.971 12238 18.397 12305 18.191 12371 18 12437 17.706 12504 18.118 12570 18.206 12637 18.132 12703 17.926 12770 18.397 12836 18 12903 18.647 12963 18.618 13010 18.912 13050 18.588 13090 18.588 13130 18.353 13170 18.191 13210 18.426 13250 18.706 13312 18.412 13396 18.324 13480 18.162 13564 17.971 13648 17.926 13733 17.985 13817 18.118 13901 17.882 13985 18.176 14057 18.235 14116 17.941 14172 18.221 14223 18.676 14422 18.662 14770 18.765 15118 18.868 16312 19.235 17505 18.882 17675 18.868 17844 18.662 18012 18.868 18179 19.515 18347 19.265 18515 19.382 18681 19.382 18850 18.779 19018 18.735 19186 18.441 19318 19.176 19414 18.912 19510 19.647 19606 19.676 19703 20.176 19799 20.118 19895 20.147 19991 19.809 20088 19.618 20184 19.5 20280 19.235 20376 19.368 20472 19.162 20569 19.294 20665 19.588 20761 19.794 20857 19.838 20954 19.721 21050 20.044 21146 19.926 21242 20.044 21338 20.309 21435 20.25 21531 19.971 21627 19.353 21723 19 21820 18.868 21916 18.985 22012 18.5 22108 18.471 22204 17.912 22301 17.162 22397 16.176 22493 16.926 22589 16.868 NaN 15.985 NaN 18.059 NaN 17.059 NaN 17.838 NaN 18.441 NaN 18.765 NaN 18.162 NaN 18.191 NaN 18.618 NaN 18.809 NaN 17.471 NaN 17.853 NaN 17.735 NaN 17.971 NaN 17.588 NaN 18.676 NaN 18.632 NaN 18.824 NaN 18.956 NaN 18.897 NaN 18.912 NaN 18.794 NaN 18.971 NaN 19 NaN 19.015 NaN 18.603 NaN 18.176 NaN 18.335 NaN 18.794 NaN 19.176 NaN 18.765 NaN 18.897 NaN 19.044 NaN 18.559 NaN 18.353 NaN 18.779 NaN 18.162 NaN 17.868 NaN 17.824 NaN 18.015 NaN 18.75 NaN 18.574 NaN 17.971 NaN 17.809 NaN 17.941 NaN 18.147 NaN 18.559 NaN 19 NaN 18.765 NaN 18.588 NaN 19.103 NaN 19.456 NaN 19.029 NaN 18.912 NaN 18.941 NaN 18.706 NaN 18.824 NaN 19.324 NaN 18.941 NaN 19.147 NaN 19.191 NaN 19.147 NaN 19.206 NaN 19.132 NaN 18.985 NaN 18.632 NaN 18.75 NaN 18.882 NaN 19.294 NaN 19.118 NaN 19.191 NaN 18.941 NaN 18.632 NaN 19.059 NaN 17.985 NaN 18.809 NaN 19.015 NaN 19.265 NaN 19.088 NaN 19 NaN 18.603 NaN 17.912 NaN 18.338 NaN 17.941 NaN 17.971 NaN 18.044 NaN 19.132 NaN 17.838 NaN 16.206 NaN 16.691 NaN 17.412 NaN 17.015 NaN 15.971 NaN 16.632 NaN 16.632 NaN 16.618 NaN 16.632 NaN 15.897 NaN 16.853 NaN 17.074 NaN 16.794 NaN 16.956 NaN 16.176 NaN 14.176 NaN 17.529 NaN 15.779 NaN 16.029 NaN 15.926 NaN 16.103 NaN 17.588 NaN 18.912 NaN 18.912 NaN 19 NaN 19.029 NaN 17.353 NaN 18.912 NaN 19.029 NaN 19 NaN 19.088 NaN 19.206 NaN 19.382 NaN 18.412 NaN 19.206 NaN 19 NaN 19.088 NaN 18.559 NaN 18.676 NaN 18.882 NaN 18.765 NaN 19 NaN 19.029 NaN 19.412 NaN 19.647 NaN 19.353 NaN 19.294 NaN 19.265 NaN 19.235 NaN 18.647 NaN 18.088 NaN 16.941 NaN 18.441 NaN 17.912 NaN 17.853 NaN 17.971 NaN 18.147 NaN 18.176 NaN 18.824 NaN 17.941 NaN 18.794 NaN 18.588 NaN 18.353 NaN 18 NaN 18.235 NaN 18.029 NaN 18.382 NaN 18.059 NaN 18.441 NaN 18.353 NaN 18.647 NaN 17.647 NaN 18.029 NaN 18.265 NaN 17.647 NaN 17.706 NaN 17.706 NaN 17.5 NaN 17.794 NaN 17.059 NaN 16.824 NaN 16.235 NaN 17.471 NaN 15.941 NaN 15.471 NaN 16.676 NaN 17.206 NaN 17.235 NaN 17.206 NaN 18.147 NaN 18.147 NaN 18.059 NaN 17.324 NaN 17.441 NaN 17.5 NaN 17.471 NaN 16.471 NaN 18.088 NaN 17.912 NaN 18.294 NaN 19.029 NaN 19.059 NaN 19.088 NaN 18.941 NaN 19.265 NaN 20.088 NaN 19.882 NaN 19.618 NaN 20.147 NaN 19.353 NaN 20.412 NaN 19.647 NaN 19.941 NaN 20.647 NaN 20.529 NaN 20.853 NaN 20.088 NaN 20.294 NaN 19.971 NaN 19.029 NaN 19.235 NaN 19.353 NaN 19.118 NaN 18.324 NaN 18.529 NaN 18.529 NaN 18.676