# Canadian Arctic and Greenland 15,000 Year July Temperature Reconstructions #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # 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: http://ncdc.noaa.gov/paleo/study/18515 # # Original_Source_URL: ftp://ftp.ncdc.noaa.gov/pub/data/paleo/pollen/recons/northamerica/gajewski2015centralcanada.txt # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Climate Reconstructions #-------------------- # Contribution_Date # Date: 2015-03-20 #-------------------- # Title # Study_Name: Canadian Arctic and Greenland 15,000 Year July Temperature Reconstructions #-------------------- # Investigators # Investigators: Gajewski, K. #-------------------- # Description_and_Notes # Description: July temperatures based on pollen from lake sediments across the Canadian Arctic Archipelago and Greenland. # The Modern Analogue Technique was used to estimate Tjul for 1400 pollen spectra from 39 lakes. Values were then interpolated # to 200 year intervals and regional averages computed. Highlights: Spatial patterns of temperature estimated for Canada # and Greenland for past 10ka. Major transitions of Holocene Arctic climate at 8.0ka and 5.2ka. Time-transgressive Holocene # Thermal Maximum quantified. # #-------------------- # Publication # Authors: Gajewski, K. # Published_Date_or_Year: 2015-05-01 # Published_Title: Quantitative reconstruction of Holocene temperatures across the Canadian Arctic and Greenland # Journal_Name: Global and Planetary Change # Volume: 128 # Edition: # Issue: # Pages: 14-23 # DOI: 10.1016/j.gloplacha.2015.02.003 # Online_Resource: http://www.sciencedirect.com/science/article/pii/S0921818115000417 # Full_Citation: # Abstract: Holocene temperature variations were reconstructed for the Canadian Arctic Archipelago and coastal Greenland using pollen data from 39 radiocarbon-dated lake sediment cores. Using the modern analog technique, mean July temperatures were estimated for the past 10.2 ka, and regional averages computed. In the western and central Arctic, maximum temperatures were found before 7 ka. In the eastern Canadian Arctic, north Greenland and east Greenland, maximum temperatures were found between 8 and 5 ka, and in southern Greenland after 4 ka. When combined with previously published reconstructions from boreal Canada and eastern Beringia, the Holocene climate history of this region can be divided into three parts with major transitions at 8.0 and 5.2 ka, however, the different regions had different histories. #------------------ # Funding_Agency # Funding_Agency_Name: Natural Sciences and Engineering Research Council of Canada # Grant: #------------------ # Site_Information # Site_Name: Central Canadian Arctic # Location: Geographic Region>Arctic # Country: # Northernmost_Latitude: 74.0 # Southernmost_Latitude: 68.0 # Easternmost_Longitude: -44.0 # Westernmost_Longitude: -99.0 # Elevation: m #------------------ # Data_Collection # Collection_Name: Gajewski2015CentralCanada # Earliest_Year: 10400 # Most_Recent_Year: 0 # Time_Unit: Cal. Year BP # Core_Length: m # Notes: #------------------ # Chronology: # # #---------------- # Variables # # Data variables follow that are preceded by "##" in columns one and two. # Data line variables format: Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # ##age_calBP age, , , calendar years before present, , , , ,N ##temp-Jul surface temperature July, , , degrees C, July, Climate Reconstruction, regional averages interpolated to 200-year intervals, pollen modern analog technique,N ##tempanom-Jul surface temperature Anomaly July, , , degrees C, July, Climate Reconstruction, regional averages interpolated to 200-year intervals, pollen modern analog technique,N ##temp-Jul+1s surface temperature July+stddev, , , degrees C, July, Climate Reconstruction, regional averages interpolated to 200-year intervals, pollen modern analog technique,N ##temp-Jul-1s surface temperature July-stddev, , , degrees C, July, Climate Reconstruction, regional averages interpolated to 200-year intervals, pollen modern analog technique,N ##numvals number of values, , , , , , Number of sites used for average, ,N # #---------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: # age_calBP temp-Jul tempanom-Jul temp-Jul+1s temp-Jul-1s numvals 0 5.6 0.0 6.8 4.4 3 200 5.5 -0.1 6.4 4.6 3 400 5.0 -0.6 6.1 3.8 5 600 5.2 -0.4 6.2 4.2 5 800 5.3 -0.3 6.4 4.2 5 1000 5.3 -0.3 6.2 4.4 5 1200 5.2 -0.4 6.2 4.2 5 1400 5.2 -0.4 6.6 3.9 5 1600 4.8 -0.8 5.8 3.8 5 1800 4.7 -0.9 5.7 3.6 5 2000 4.6 -1.0 5.7 3.6 5 2200 4.7 -0.9 5.8 3.5 5 2400 4.8 -0.8 6.1 3.5 5 2600 4.7 -0.9 6.0 3.4 5 2800 4.7 -0.9 6.3 3.2 5 3000 4.9 -0.8 6.6 3.1 5 3200 4.8 -0.8 6.2 3.5 5 3400 4.9 -0.7 6.3 3.6 5 3600 5.2 -0.4 6.7 3.7 5 3800 5.6 0.0 7.6 3.6 5 4000 5.6 0.0 7.6 3.7 5 4200 5.4 -0.2 7.0 3.8 5 4400 5.4 -0.2 7.2 3.7 5 4600 5.2 -0.4 6.7 3.6 5 4800 5.4 -0.2 6.9 3.8 5 5000 5.3 -0.3 6.6 4.0 5 5200 5.6 0.0 7.2 3.9 5 5400 5.6 0.0 7.5 3.7 5 5600 5.3 -0.3 7.0 3.6 5 5800 5.1 -0.5 7.0 3.2 5 6000 5.2 -0.4 7.1 3.3 5 6200 5.4 -0.2 7.4 3.4 5 6400 5.6 -0.1 7.5 3.6 5 6600 5.5 -0.1 7.1 3.8 5 6800 5.4 -0.2 7.2 3.6 5 7000 5.4 -0.2 7.4 3.4 5 7200 4.8 -0.8 6.6 2.9 4 7400 4.8 -0.8 6.9 2.8 4 7600 4.9 -0.7 7.1 2.6 4 7800 5.0 -0.6 7.4 2.6 4 8000 5.0 -0.6 6.9 3.0 4 8200 5.5 -0.1 7.8 3.1 4 8400 5.6 0.0 8.1 3.0 4 8600 5.9 0.3 8.5 3.3 4 8800 6.2 0.6 8.9 3.5 4 9000 5.0 -0.6 6.5 3.5 3 9200 5.1 -0.5 6.2 3.9 3 9400 5.7 0.1 7.5 4.0 3 9600 5.8 0.2 7.1 4.5 3 9800 6.1 0.5 7.5 4.7 3 10000 6.3 0.7 7.6 5.0 3 10200 5.2 -0.4 6.0 4.4 2 10400 4.5 -1.1 5.6 3.4 2