# Puruogangri Ice Core Oxygen Isotope Data #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # NOTE: Please cite original reference when using these data, # If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed # # # # Online_Resource: # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611 # # Original_Source_URL: # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Ice Cores # -------------------- # Contribution_date # Date: 2015 # -------------------- # Title # Study_Name: Puruogangri Ice Core Oxygen Isotope Data # # -------------------- # Investigators # Investigators: Thompson, L.G.; Tandong, Y.; Davis, M.E.; Mosley-Thompson, E.; Mashiotta, T.A.; Lin, P.-N.; Mikhelenko, V.N.; Zagorodnov, V.S. # -------------------- # Description_and_Notes # Description: # # -------------------- # Publication # Authors: L.G Thompson, Y. Tandong, M. E. Davis, E. Mosley-Thomspon, T. A. Mashiotta, P.-N. Lin, V. N. Mikhelenko, V. S. Zagorodnov # Published_Date_or_Year: 2006 # Published_Title: Holocene climate variability archived in the Puruogangri ice cap on the central Tibetan Plateau # Journal_Name: Annals of Glaciology # Volume: 43 # Edition: # Issue: # Pages: 61-69 # DOI: # Online_Resource: # Full_Citation: # Abstract: Two ice cores (118.4 and 214.7 m in length) were collected in 2000 from the Puruogangri ice cap in the center of the Tibetan Plateau (TP) in a joint US–Chinese collaborative project. These cores yield paleoclimatic and environmental records extending through the Middle Holocene, and complement previous ice-core histories from the Dunde and Guliya ice caps in northeast and northwest Tibet, respectively, and Dasuopu glacier in the Himalaya. The high-resolution Puruogangri climate record since AD 1600 details regional temperature and moisture variability. The post-1920 period is characterized by above-average annual net balance, contemporaneous with the greatest 18O enrichment of the last 400 years, consistent with the isotopically inferred warming observed in other TP ice-core records. On longer timescales the aerosol history reveals large and abrupt events, one of which is dated 4.7 kyr BP and occurs close to the time of a drought that extended throughout the tropics and may have been associated with centuries-long weakening of the Asian/Indian/African monsoon system. The Puruogangri climate history, combined with the other TP ice-core records, has the potential to provide valuable information on variations in the strength of the monsoon across the TP during the Holocene. # -------------------- # Authors: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G.J., Noone, D., Perkins, W.A., and E. Steig # Published_Date_or_Year: 2018 # Published_Title: Additions to the last millennium reanalysis multi-proxy database # Journal_Name: Data Science Journal # Volume: # Edition: # Issue: # Pages: # Report_Number: # DOI: # Online_Resource: # Full_Citation: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G., J., Noone, D., Perkins, W.A., and E. Steig, submitted. Additions to the last millennium reanalysis multi-proxy database. Data Science Journal. # Abstract: Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR). The 2290 additional series include 2152 tree ring chronologies and 138 other series. They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation. A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project. The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables. Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods. #------------------ # Funding_Agency # Funding_Agency_Name: # Grant: # -------------------- # Funding_Agency_Name: National Science Foundation # Grant:AGS-1304263 # Funding_Agency_Name: National Oceanic and Atmospheric Administration # Grant:NA14OAR4310176 #------------------ # Site_Information # Site_Name: Puruogangri # Location: Asia>Eastern Asia>China # Country: Tibet # Northernmost_Latitude: 33.92 # Southernmost_Latitude: 33.92 # Easternmost_Longitude: 89.08 # Westernmost_Longitude: 89.08 # Elevation: 6070 m # -------------------- # Data_Collection # Collection_Name: 06Puru01 # Earliest_Year: 1900 # Most_Recent_Year: 1999 # Time_Unit: y_ad # Notes: {"database":"LMR"} # # -------------------- # 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 age,,,years AD,,,,,N ##d18O delta 18 oxygen,,,permil SMOW,,Ice Cores,,,N # # -------------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing values: NAN # age d18O 1999 -13.37 1998 -16.045 1997 -13.6709 1996 -14.9557 1995 -13.16 1994 -14.92 1993 -16.8933 1992 -16.332 1991 -17.386 1990 -15.154 1989 -13.609 1988 -13.6871 1987 -12.8308 1986 -13.5715 1985 -13.7518 1984 -14.545 1983 -14.0483 1982 -14.2586 1981 -14.7336 1980 -13.0529 1979 -14.8557 1978 -16.5862 1977 -16.3522 1976 -15.0285 1975 -14.9147 1974 -15.5877 1973 -14.8567 1972 -15.8956 1971 -14.3825 1970 -13.7456 1969 -13.3143 1968 -15.43 1967 -14.187 1966 -13.2206 1965 -13.8193 1964 -15.4829 1963 -15.6567 1962 -13.9533 1961 -14.4964 1960 -16.8813 1959 -17.475 1958 -14.9245 1957 -12.5753 1956 -12.5244 1955 -14.596 1954 -12.6055 1953 -13.1271 1952 -13.2953 1951 -14.164 1950 -14.2287 1949 -15.415 1948 -14.4463 1947 -15.4425 1946 -14.115 1945 -14.1983 1944 -14.8236 1943 -15.65 1942 -13.0979 1941 -15.025 1940 -17.3792 1939 -18.5575 1938 -15.0235 1937 -14.1686 1936 -13.7325 1935 -12.7033 1934 -13.3844 1933 -13.8875 1932 -14.0275 1931 -15.3154 1930 -16.9129 1929 -13.5029 1928 -13.949 1927 -13.0825 1926 -14.7529 1925 -14.5692 1924 -14.1063 1923 -12.6094 1922 -13.515 1921 -12.9236 1920 -13.9083 1919 -14.629 1918 -13.644 1917 -14.3725 1916 -14.8544 1915 -14.1671 1914 -16.4775 1913 -20.3967 1912 -19.088 1911 -15.876 1910 -13.452 1909 -15.3986 1908 -16.4118 1907 -16.899 1906 -16.71 1905 -16.575 1904 -16.73 1903 -16.556 1902 -16.6413 1901 -16.1522 1900 -17.7986