# 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/routson2019temp.txt # 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: air 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: Northern Hemisphere and Tropics # Location: Geographic Region>Northern Hemisphere # Country: # Northernmost_Latitude: 90 # Southernmost_Latitude: -10 # Easternmost_Longitude: 180 # Westernmost_Longitude: -180 # Elevation: #------------------ # Data_Collection # Collection_Name: Routson2019 # Earliest_Year: 9900 # Most_Recent_Year: 100 # Time_Unit: Cal. Year BP # 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) # ## age_calBP age, , , calendar years before present, , , , ,N, ## temp1010 temperature, , , degrees C, ,climate reconstructions,,,N, 10S-10N (Fig. 3a) temperature ## temp1010- temperature error, , , degrees C, ,climate reconstructions,,,N, 10S-10N (error) lower quantile (0.025) temperature ## temp1010+ temperature error, , , degrees C, ,climate reconstructions,,,N, 10S-10N (error) upper quantile (0.975) temperature ## temp1030 temperature, , , degrees C, ,climate reconstructions,,,N, 10N-30N (Fig. 3b) temperature ## temp1030- temperature error, , , degrees C, ,climate reconstructions,,,N, 10N-30N (error) lower quantile (0.025) temperature ## temp1030+ temperature error, , , degrees C, ,climate reconstructions,,,N, 10N-30N (error) upper quantile (0.975) temperature ## temp3050 temperature, , , degrees C, ,climate reconstructions,,,N, 30N-50N (Fig. 3c) temperature ## temp3050- temperature error, , , degrees C, ,climate reconstructions,,,N, 30N-50N (error) lower quantile (0.025) temperature ## temp3050+ temperature error, , , degrees C, ,climate reconstructions,,,N, 30N-50N (error) upper quantile (0.975) temperature ## temp5070 temperature, , , degrees C, ,climate reconstructions,,,N, 50N-70N (Fig. 3d) temperature ## temp5070- temperature error, , , degrees C, ,climate reconstructions,,,N, 50N-70N (error) lower quantile (0.025) temperature ## temp5070+ temperature error, , , degrees C, ,climate reconstructions,,,N, 50N-70N (error) upper quantile (0.975) temperature ## temp7090 temperature, , , degrees C, ,climate reconstructions,,,N, 70N-90N (Fig. 3e) temperature ## temp7090- temperature error, , , degrees C, ,climate reconstructions,,,N, 70N-90N (error) lower quantile (0.025) temperature ## temp7090+ temperature error, , , degrees C, ,climate reconstructions,,,N, 70N-90N (error) upper quantile (0.975) temperature # #---------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: # age_calBP temp1010 temp1010- temp1010+ temp1030 temp1030+ temp1030- temp3050 temp3050+ temp3050- temp5070 temp5070+ temp5070- temp7090 temp7090+ temp7090- 100 25.031796 24.324608 25.97798 24.714478 23.617216 25.524721 9.5739164 9.0215101 10.071123 -3.6366413 -4.1223526 -3.2102146 -15.703422 -16.49892 -14.989665 300 24.805195 24.016098 25.789063 24.188189 23.435839 25.321756 9.4812803 8.8107805 9.9710903 -3.6265583 -3.9992316 -3.0508795 -15.316389 -16.362587 -14.430406 500 25.207956 24.208996 25.920359 24.64563 23.560041 25.423256 9.5612431 8.9001865 9.9217482 -3.2330565 -3.9157851 -2.8557715 -15.260077 -16.202112 -14.371605 700 25.179811 24.519392 26.006788 24.653414 23.799009 25.442896 9.5913382 9.1621466 10.065561 -3.5980649 -3.945509 -3.0903757 -15.264837 -16.005692 -14.738653 900 25.087944 24.476629 26.084431 24.768404 23.918537 25.539778 9.4414549 9.1547155 9.8977633 -3.3863797 -3.7642436 -2.9960067 -15.27703 -15.880061 -14.575575 1100 25.184521 24.381536 25.786526 24.721348 24.106335 25.582581 9.6045227 9.2607307 9.9499702 -3.3441775 -3.6958284 -2.9567151 -14.964676 -15.797799 -14.379589 1300 25.173107 24.333731 25.806576 24.642921 23.845549 25.683683 9.4751434 9.2486305 9.9507704 -3.2551401 -3.7281592 -2.9517171 -15.312644 -15.915246 -14.433139 1500 25.015368 24.367287 25.831467 24.757162 23.903065 25.569159 9.5926733 9.2556982 9.956852 -3.6588395 -3.7990978 -3.0240188 -15.173589 -16.059475 -14.580229 1700 25.066519 24.318539 25.994455 24.656313 23.66313 25.522804 9.6211014 9.190238 10.119407 -3.4954212 -3.8440392 -2.9112084 -15.017776 -16.057102 -14.422546 1900 25.109264 24.473732 26.017323 24.608248 23.677813 25.361477 9.7739887 9.3414278 10.204129 -3.3859696 -3.7462184 -2.8116505 -15.264293 -16.089388 -14.439966 2100 25.508987 24.419588 26.063103 24.613697 23.812582 25.424995 9.8618069 9.323266 10.229772 -3.3445294 -3.6963706 -2.8183334 -15.294749 -16.136957 -14.371299 2300 25.165035 24.425295 26.016672 24.860638 23.863943 25.569565 9.7291918 9.3504066 10.273894 -3.2406366 -3.6490617 -2.7256217 -15.219624 -16.10523 -14.448728 2500 25.286388 24.417744 25.952497 24.727922 23.898321 25.643021 9.7876825 9.3822956 10.234681 -3.301023 -3.634676 -2.7385781 -15.219848 -16.121599 -14.398427 2700 25.274591 24.368473 26.103622 24.735638 23.922028 25.707729 9.6657343 9.4306002 10.259282 -3.3051 -3.6401961 -2.7711236 -15.359921 -16.068714 -14.44597 2900 25.217588 24.337729 26.017092 24.695229 23.873482 25.708033 9.7441578 9.3251925 10.252921 -3.246871 -3.5821512 -2.7001948 -14.986619 -16.102438 -14.419298 3100 25.121893 24.366709 26.055368 24.781254 23.860968 25.694546 9.9579973 9.3996801 10.288937 -3.3140831 -3.5397882 -2.606178 -14.994694 -16.071115 -14.399939 3300 24.999846 24.467352 26.070131 24.865189 23.921555 25.734634 9.7900686 9.4350653 10.273913 -3.0571187 -3.5094025 -2.5754812 -15.14323 -16.038408 -14.256922 3500 25.149544 24.450565 26.040888 24.863979 23.777798 25.692671 9.7958603 9.3798132 10.323407 -2.961935 -3.4361851 -2.4773831 -14.956876 -16.027315 -14.185176 3700 25.267149 24.509556 26.143908 24.854631 23.796562 25.795149 9.8433104 9.4293766 10.335008 -3.1005225 -3.3971715 -2.4627426 -15.023152 -15.992038 -14.15601 3900 25.265741 24.529055 26.05303 24.787577 23.854885 25.780714 9.7862215 9.4398203 10.406954 -3.0969484 -3.3051932 -2.4310944 -15.058288 -16.00972 -14.090567 4100 25.240213 24.518717 26.102036 24.719639 23.802322 25.826197 9.8933592 9.3749208 10.422267 -2.8898849 -3.285109 -2.4188321 -14.594949 -15.781382 -14.061448 4300 25.340839 24.576267 26.124189 24.517885 23.79443 25.895731 9.820302 9.4564362 10.460414 -2.9234715 -3.2034607 -2.2432842 -14.834212 -15.905792 -13.969332 4500 25.264839 24.593464 26.148155 24.944788 23.802816 25.817158 9.9373026 9.3974705 10.467827 -2.960655 -3.2095742 -2.2076387 -14.606627 -15.741638 -13.937827 4700 25.300837 24.563034 26.14789 24.750393 23.899637 25.847189 9.9857044 9.4345484 10.450337 -2.7623804 -3.1752832 -2.17521 -14.617508 -15.689038 -13.754841 4900 25.444273 24.529179 26.162676 24.807577 23.889559 25.744301 9.8218966 9.5220089 10.580551 -2.6043491 -3.1117949 -2.1804698 -14.635052 -15.620432 -13.687138 5100 25.319588 24.613106 26.178001 24.810249 23.856199 25.741598 9.9457674 9.5043221 10.511034 -2.7041159 -3.0598886 -2.1154268 -14.375379 -15.543776 -13.607377 5300 25.228489 24.612629 26.060686 24.772774 23.858332 25.840014 9.7427216 9.4874582 10.570086 -2.4884102 -3.0750754 -2.0966151 -14.227797 -15.573039 -13.523864 5500 25.259121 24.556801 26.152695 24.761801 23.849552 25.831829 9.9484091 9.5156269 10.573497 -2.5671027 -3.0693493 -2.0899646 -14.29177 -15.389512 -13.513596 5700 25.393778 24.541798 26.114182 24.87578 23.734676 25.849783 10.105849 9.5157452 10.60391 -2.5005074 -3.0388968 -2.054086 -14.156713 -15.461163 -13.539597 5900 25.209635 24.564463 26.106804 24.731413 23.671974 25.772444 9.9914818 9.562809 10.642425 -2.6787522 -3.0467236 -2.0623102 -14.113817 -15.341787 -13.508514 6100 25.274973 24.54303 26.109953 24.710878 23.780851 25.833971 10.084984 9.6249275 10.676641 -2.6693997 -3.0495327 -2.0587947 -14.24678 -15.34446 -13.443433 6300 25.148838 24.549677 26.052994 24.862577 23.650961 25.846012 10.126987 9.5569649 10.707652 -2.6003108 -3.0147233 -1.9972805 -14.296741 -15.372042 -13.416112 6500 25.139696 24.478495 26.068348 24.610273 23.500349 25.786655 10.028608 9.592948 10.700427 -2.413373 -2.987505 -1.9865665 -14.464047 -15.445535 -13.464805 6700 25.304632 24.473257 26.123585 24.607006 23.583895 25.771429 10.198767 9.6304321 10.761389 -2.4800098 -3.0153344 -1.9477773 -14.257719 -15.501335 -13.422224 6900 25.223421 24.533201 26.080235 24.685913 23.52483 25.820393 10.197959 9.6915789 10.748574 -2.5845072 -3.103524 -1.9645137 -14.185555 -15.337335 -13.373317 7100 25.172035 24.53891 26.118214 24.547577 23.537918 25.731964 10.231688 9.6417713 10.742172 -2.8157673 -3.0592182 -1.9894165 -14.050145 -15.347931 -13.415374 7300 25.238462 24.494579 26.150631 24.61438 23.616367 25.642017 10.34549 9.6525955 10.886168 -2.303998 -3.1021998 -1.9837916 -14.262787 -15.484086 -13.309157 7500 25.271978 24.543486 26.088436 24.481604 23.609749 25.656569 10.311416 9.6506891 10.840189 -2.6754191 -3.2173069 -2.0427399 -14.114963 -15.385611 -13.249213 7700 25.22389 24.375256 25.973461 24.528696 23.544497 25.575018 10.200494 9.606885 10.82585 -2.7141521 -3.1936107 -2.038871 -14.278952 -15.339764 -13.212572 7900 25.172785 24.423576 26.093506 24.835569 23.566996 25.572727 10.391631 9.6793127 10.81071 -2.4339714 -3.2744455 -2.0628796 -13.783117 -15.26449 -13.142468 8100 25.249933 24.386705 26.051044 24.57688 23.602512 25.630119 10.383011 9.5955238 10.795754 -2.8488204 -3.3677468 -2.1163003 -14.019262 -15.316505 -13.183184 8300 25.114725 24.399033 25.97718 24.483137 23.45406 25.574778 10.152098 9.582242 10.741555 -2.8422503 -3.3537357 -2.1597509 -13.802908 -15.220944 -13.188309 8500 25.20466 24.375511 26.097179 24.897964 23.598698 25.665218 10.167622 9.500453 10.735313 -2.6569695 -3.4026222 -2.0918972 -13.77434 -15.304426 -13.051537 8700 25.153404 24.384729 26.008825 24.542 23.396013 25.430845 10.085233 9.4315052 10.739935 -2.6650259 -3.4108884 -2.1010303 -13.879307 -15.190941 -13.097395 8900 25.1833 24.399096 26.046211 24.549175 23.387825 25.47237 9.9651499 9.5252142 10.66224 -3.0228422 -3.503413 -2.0945272 -13.878827 -15.183528 -13.097687 9100 25.107128 24.335072 26.056986 24.597622 23.40358 25.4454 10.077585 9.4461918 10.606718 -3.0022185 -3.7831495 -2.1296163 -14.027943 -15.365504 -13.143228 9300 25.190872 24.348639 25.993389 24.577549 23.393208 25.470438 10.012575 9.3211403 10.544905 -3.085587 -3.6404545 -2.1110868 -13.887952 -15.480363 -13.116326 9500 25.21826 24.396437 25.984198 24.288244 23.281195 25.434631 9.9249382 9.2491493 10.595546 -2.5726945 -3.6489186 -2.020849 -13.897465 -15.592663 -13.074775 9700 25.100285 24.280851 25.995626 24.441174 23.227663 25.461594 10.056222 9.0657644 10.545989 -2.824353 -3.7413204 -1.9205365 -13.480171 -15.810029 -13.078151 9900 25.164917 24.290243 25.98218 24.239098 23.230476 25.326132 10.1749 8.962079 10.544685 -2.9696608 -3.8639281 -2.0072827 -14.227027 -15.98407 -13.143068