# Global Database of Borehole Temperatures and Climate Reconstructions #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # NOTE: Please cite original reference when using these data, # plus the Online Resource and date accessed. # # Online_Resource: http://hurricane.ncdc.noaa.gov/pls/paleox/f?p=519:1:::::P1_STUDY_ID:1000745 # # Original_Source_URL: ftp://ftp.ncdc.noaa.gov/pub/data/paleo/contributions_by_author/huang2000/huang-2013-DE-Gries.txt # # Reconstruction_temperature_graph_URL: http://www.earth.lsa.umich.edu/climate/RECONSTRUCTION/DE-Gries.html # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Borehole #-------------------- # Contribution_Date # Date: 2013-07-26 #-------------------- # Title # Study_Name: Global Database of Borehole Temperatures and Climate Reconstructions #-------------------- # Investigators # Investigators: Huang, S.; Pollack, H.N.; Shen, P.Y. #-------------------- # Description_and_Notes # Description: This project has as its goal the design, assembly, analysis and interpretation of geothermal observations on # continents relevant to understanding the nature and causes of climate change over the past five centuries. The project was # inititated by the Geothermal Laboratory of the University of Michigan, USA. Important collaborations have been developed # with the Geophysical Institute of the Czech Academy of Sciences, and with a working group of the International Heat Flow # Commission of IASPEI. Funding for this project has come from the U.S. National Science Foundation, the U.S. National # Oceanic and Atmospheric Administration, the International Geological Correlation Program, and the Czech - U.S. Science and # Technology Program. The principal components of the database are: # (1) Basic geothermal observations from field surveys and laboratory measurements, principally comprising borehole # temperature logs and thermophysical properties. This section includes data only from boreholes at least 200 m deep. The # data listed are restricted to the range 20-600 meters. Data above 20 m have been omitted because they include annual # variability, and data below 600 m have not been included because they contain no information about the past 500 # years.Quality control measures have occasionally required the deletion of other data within the 20-600 m range. # (2) A five-century ground surface temperature history derived for each site by a standardized inversion procedure # operating on the basic observations. The derived history is presented as century-long temperature trends for each of the # past five centuries. This representation emphasizes longer term variations of the climate history, and thus is # complementary to high resolution proxies such as tree rings, ice cores, corals and lake sediments. # (3) The name of the person who can be contacted to learn more about the data and the site. This is either the name of the # original investigator who made the observations, or the name of a regional or national data compiler. Some data remain # proprietary, and therefore are not accessible directly from this database. Database users desiring access to these data # should request the data directly from the person listed as the data contact. A list of investigators engaged in climate # studies involving geothermal data can be found at the original web site of this database at the University of Michigan. # #-------------------- # Publication # Authors: Huang, S., Pollack, H. N., and Shen, P.Y. # Published_Date_or_Year: 2000-02-17 # Published_Title: Temperature trends over the past five centuries reconstructed from borehole temperatures # Journal_Name: Nature # Volume: 403 # Edition: # Issue: # Pages: 756-758 # DOI: 10.1038/35001556 # Abstract: For an accurate assessment of the relative roles of natural variability and anthropogenic influence in the Earth's climate, reconstructions of past temperatures from the pre-industrial as well as the industrial period are essential. But instrumental records are typically available for no more than the past 150 years. Therefore reconstructions of pre-industrial climate rely principally on traditional climate proxy records, each with particular strengths and limitations in representing climatic variability. Subsurface temperatures comprise an independent archive of past surface temperature changes that is complementary to both the instrumental record and the climate proxies. Here we use present-day temperatures in 616 boreholes from all continents except Antarctica to reconstruct century-long trends in temperatures over the past 500 years at global, hemispheric and continental scales. The results confirm the unusual warming of the twentieth century revealed by the instrumental record6, but suggest that the cumulative change over the past five centuries amounts to about 1 K, exceeding recent estimates from conventional climate proxies. The strength of temperature reconstructions from boreholes lies in the detection of long-term trends, complementary to conventional climate proxies, but to obtain a complete picture of past warming, the differences between the approaches need to be investigated in detail. #------------------ # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: 1202673 #------------------ # Site_Information # Site_Name: DE-Gries # Location: Land>Europe>Western Europe # Country: Germany # Northernmost_Latitude: 49.86 # Southernmost_Latitude: 49.86 # Easternmost_Longitude: 12.50 # Westernmost_Longitude: 12.50 # Maximum Depth: 278.600 m #------------------ # Data_Collection # Collection_Name: DE-Gries-borehole # Data contact: Christoph Clauser (DE) # Date of measurement (year): 1986 # Estimated prior steady state GST (°C): 6.5 # Estimated mean conductivity (W/m/K): 3.43 # Estimated mean thermal gradient (K/km): 21 # Notes: #------------------ # Reconstruction_Temperature: # Pre-1500 baseline GST (°C): 6.490 # # Date_Century Estimated_GST_Change(°C) Notes # 16th 0.012 # 17th 0.002 # 18th -0.026 # 19th -0.080 # 20th 0.044 # # #---------------- # Variables # # Data variables follow (have no #) # 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, Temperature for Character or Numeric data) Depth_m Depth Below Surface , , , m, , , , ,N Temperature_Celsius Measurement Temperature , , , Celsius degree, , , , ,N notes notes , , , , , , , ,N #---------------- # Data: # Data lines follow (have no #) # Data line format - 9-blank-spaced text, variable short name as header # Missing Values: Depth_m Temperature_Celsius Notes 23.80 7.080 26.00 7.120 28.20 7.160 30.40 7.200 32.60 7.230 34.80 7.270 37.00 7.310 39.20 7.340 41.40 7.390 43.60 7.430 45.80 7.470 48.00 7.500 50.20 7.540 52.40 7.590 54.60 7.630 56.80 7.680 59.00 7.720 61.20 7.770 63.40 7.810 65.60 7.860 67.80 7.900 70.00 7.950 72.20 7.990 74.40 8.040 76.60 8.090 78.80 8.130 81.00 8.180 83.20 8.220 85.40 8.270 87.60 8.310 89.80 8.380 92.00 8.430 94.20 8.480 96.40 8.490 98.60 8.560 100.80 8.610 103.00 8.650 105.20 8.670 107.40 8.740 109.60 8.780 111.80 8.840 114.00 8.870 116.20 8.920 118.40 8.980 120.59 9.020 122.75 9.060 124.93 9.110 127.11 9.160 129.30 9.210 131.49 9.250 133.69 9.310 135.89 9.350 138.09 9.390 140.30 9.460 142.50 9.490 144.70 9.530 146.91 9.580 149.11 9.640 151.31 9.690 153.52 9.730 155.72 9.760 157.92 9.820 160.12 9.870 162.31 9.920 164.51 9.970 166.71 10.010 168.90 10.060 171.10 10.100 173.29 10.150 175.49 10.190 177.68 10.240 179.87 10.280 182.07 10.330 184.26 10.380 186.45 10.430 188.65 10.470 190.84 10.520 193.03 10.570 195.23 10.600 197.42 10.650 199.62 10.700 201.82 10.740 204.01 10.790 206.21 10.840 208.41 10.880 210.61 10.930 212.80 10.960 215.00 11.010 217.20 11.060 219.40 11.110 221.60 11.160 223.80 11.200 226.00 11.240 228.20 11.270 230.40 11.370 232.59 11.410 234.79 11.460 236.99 11.510 239.18 11.550 241.38 11.600 243.58 11.640 245.77 11.690 247.96 11.730 250.16 11.780 252.35 11.820 254.54 11.870 256.73 11.910 258.92 11.960 261.11 12.000 263.29 12.050 265.48 12.090 267.67 12.140 269.85 12.190 272.04 12.230 274.23 12.280 276.41 12.330 278.60 12.370