# asia_russ031w - Ozera Lama - Breitenmoser Tree Ring Chronology Data #----------------------------------------------------------------------- # 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: # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611 # # Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/4579 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ031w - Ozera Lama - Breitenmoser Tree Ring Chronology Data #-------------------- # Investigators # Investigators: Breitenmoser, P.; Bronnimann, S.; Frank, D. #-------------------- # Description_and_Notes # Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details #-------------------- # Publication # Authors: Breitenmoser, P.; Bronnimann, S.; Frank, D. # Published_Date_or_Year: 2014-03-11 # Published_Title: Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies # Journal_Name: Climate of the Past # Volume: 10 # Edition: # Issue: # Pages: 437-449 # DOI: 10.5194/cp-10-437-2014 # Online_Resource: www.clim-past.net/10/437/2014/ # Full_Citation: # Abstract: We investigate relationships between climate and tree-ring data on a global scale using the process-based Vaganov–Shashkin Lite (VSL) forward model of tree-ring width formation. The VSL model requires as inputs only latitude, monthly mean temperature, and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree rings to monthly climate conditions obtained from the CRU TS3.1 data set back to 1901. Our key aims are (a) to assess the VSL model performance by examining the relations between simulated and observed growth at 2287 globally distributed sites, (b) indentify optimal growth parameters found during the model calibration, and (c) to evaluate the potential of the VSL model as an observation operator for data-assimilation-based reconstructions of climate from tree-ring width. The assessment of the growth-onset threshold temperature of approximately 4–6 C for most sites and species using a Bayesian estimation approach complements other studies on the lower temperature limits where plant growth may be sustained. Our results suggest that the VSL model skilfully simulates site level treering series in response to climate forcing for a wide range of environmental conditions and species. Spatial aggregation of the tree-ring chronologies to reduce non-climatic noise at the site level yielded notable improvements in the coherence between modelled and actual growth. The resulting distinct and coherent patterns of significant relationships between the aggregated and simulated series further demonstrate the VSL model’s ability to skilfully capture the climatic signal contained in tree-ring series. Finally, we propose that the VSL model can be used as an observation operator in data assimilation approaches to reconstruct past climate. #-------------------- # 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: Swiss National Science Foundation # Grant: #-------------------- # Funding_Agency_Name: National Science Foundation # Grant:AGS-1304263 # Funding_Agency_Name: National Oceanic and Atmospheric Administration # Grant:NA14OAR4310176 #------------------ # Site_Information # Site_Name: Ozera Lama # Location: # Country: Russia # Northernmost_Latitude: 69.58 # Southernmost_Latitude: 69.58 # Easternmost_Longitude: 90.5 # Westernmost_Longitude: 90.5 # Elevation: 60 m #-------------------- # Data_Collection # Collection_Name: asia_russ031wB # Earliest_Year: 1730 # Most_Recent_Year: 1990 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"2.69115449912","T2":"17.0333820997","M1":"0.0227247931849","M2":"0.458611565136"}} #-------------------- # Species # Species_Name: Siberian spruce # Species_Code: PCOB #-------------------- # 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 age, , ,years AD, , , , ,N ##trsgi tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N # #-------------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: nan # age trsgi 1730 1.59 1731 0.848 1732 0.909 1733 1.38 1734 1.132 1735 0.939 1736 0.789 1737 0.964 1738 0.559 1739 0.882 1740 1.03 1741 0.863 1742 0.536 1743 1.246 1744 1.236 1745 0.94 1746 1.182 1747 1.65 1748 1.601 1749 1.532 1750 1.292 1751 0.897 1752 0.562 1753 1.108 1754 0.859 1755 0.879 1756 0.888 1757 0.75 1758 0.579 1759 0.285 1760 0.746 1761 0.995 1762 1.419 1763 0.753 1764 1.0 1765 1.058 1766 1.203 1767 1.6 1768 0.961 1769 0.871 1770 0.645 1771 0.868 1772 0.741 1773 0.757 1774 0.917 1775 1.462 1776 0.558 1777 0.747 1778 0.615 1779 0.513 1780 0.529 1781 0.479 1782 0.806 1783 0.548 1784 0.917 1785 1.161 1786 1.246 1787 1.295 1788 1.139 1789 1.493 1790 1.165 1791 1.176 1792 0.855 1793 1.637 1794 1.543 1795 1.35 1796 1.499 1797 0.758 1798 0.858 1799 0.964 1800 0.89 1801 1.334 1802 0.914 1803 0.982 1804 0.849 1805 1.329 1806 1.271 1807 0.633 1808 1.121 1809 1.082 1810 1.141 1811 0.747 1812 0.464 1813 0.742 1814 0.75 1815 0.611 1816 0.494 1817 0.366 1818 0.38 1819 0.163 1820 0.391 1821 0.644 1822 0.574 1823 0.383 1824 0.331 1825 0.369 1826 0.751 1827 0.895 1828 0.633 1829 1.127 1830 0.555 1831 1.127 1832 0.882 1833 0.384 1834 1.13 1835 1.371 1836 1.004 1837 0.731 1838 1.115 1839 1.181 1840 1.084 1841 0.869 1842 1.517 1843 0.999 1844 1.478 1845 1.113 1846 1.235 1847 0.833 1848 1.038 1849 0.972 1850 1.062 1851 0.993 1852 1.023 1853 1.199 1854 0.773 1855 0.598 1856 0.919 1857 0.863 1858 1.078 1859 0.739 1860 0.935 1861 1.112 1862 0.877 1863 0.995 1864 0.808 1865 0.832 1866 0.606 1867 0.319 1868 0.995 1869 0.682 1870 1.085 1871 0.692 1872 0.743 1873 0.588 1874 0.564 1875 0.744 1876 0.807 1877 1.112 1878 1.138 1879 1.229 1880 1.24 1881 0.86 1882 0.901 1883 0.818 1884 0.845 1885 0.582 1886 0.993 1887 0.797 1888 0.724 1889 0.672 1890 0.767 1891 0.963 1892 1.237 1893 1.314 1894 1.136 1895 0.688 1896 0.96 1897 1.627 1898 1.325 1899 1.139 1900 0.96 1901 0.764 1902 0.703 1903 1.208 1904 1.272 1905 0.901 1906 0.993 1907 1.043 1908 1.975 1909 1.495 1910 1.335 1911 0.84 1912 1.052 1913 0.851 1914 0.648 1915 1.304 1916 0.871 1917 0.936 1918 1.272 1919 0.85 1920 1.014 1921 0.777 1922 0.897 1923 0.797 1924 0.985 1925 0.626 1926 1.173 1927 0.735 1928 1.387 1929 0.954 1930 1.307 1931 0.935 1932 1.025 1933 0.773 1934 1.239 1935 1.068 1936 1.39 1937 1.134 1938 1.006 1939 0.95 1940 0.996 1941 1.043 1942 1.612 1943 1.188 1944 1.322 1945 1.7 1946 1.548 1947 1.316 1948 1.585 1949 1.305 1950 1.641 1951 1.279 1952 1.487 1953 1.749 1954 1.186 1955 1.374 1956 1.282 1957 1.233 1958 0.883 1959 1.321 1960 0.479 1961 0.698 1962 0.9 1963 0.518 1964 0.753 1965 0.861 1966 0.78 1967 1.007 1968 0.743 1969 1.189 1970 0.716 1971 0.645 1972 0.691 1973 0.468 1974 0.168 1975 0.59 1976 0.826 1977 0.705 1978 0.834 1979 0.94 1980 0.63 1981 0.93 1982 0.601 1983 0.744 1984 1.275 1985 0.806 1986 0.965 1987 0.538 1988 0.97 1989 0.6 1990 1.514