# asia_russ090w - Ust Nera - 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/4708 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ090w - Ust Nera - 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: Ust Nera # Location: # Country: Russia # Northernmost_Latitude: 64.53 # Southernmost_Latitude: 64.53 # Easternmost_Longitude: 143.12 # Westernmost_Longitude: 143.12 # Elevation: 600 m #-------------------- # Data_Collection # Collection_Name: asia_russ090wB # Earliest_Year: 1719 # Most_Recent_Year: 1991 # 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":"3.50317190075","T2":"15.6030608054","M1":"0.0229827671838","M2":"0.479059721539"}} #-------------------- # Species # Species_Name: Dahurian larch # Species_Code: LAGM #-------------------- # 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 1719 1.024 1720 0.852 1721 0.978 1722 1.287 1723 1.417 1724 0.912 1725 0.89 1726 0.759 1727 1.193 1728 0.596 1729 1.147 1730 0.902 1731 1.161 1732 1.31 1733 1.184 1734 1.327 1735 1.105 1736 0.83 1737 1.052 1738 0.69 1739 0.877 1740 0.73 1741 1.214 1742 1.563 1743 1.549 1744 1.145 1745 1.388 1746 1.347 1747 1.293 1748 1.031 1749 1.12 1750 1.147 1751 1.234 1752 0.954 1753 0.725 1754 0.883 1755 1.22 1756 1.035 1757 0.994 1758 1.138 1759 1.09 1760 1.104 1761 0.681 1762 0.553 1763 0.809 1764 0.329 1765 0.55 1766 0.509 1767 0.592 1768 0.52 1769 0.817 1770 0.549 1771 0.466 1772 0.491 1773 0.57 1774 0.49 1775 0.483 1776 0.514 1777 0.215 1778 0.452 1779 0.468 1780 0.357 1781 0.432 1782 0.516 1783 0.485 1784 0.399 1785 0.457 1786 0.524 1787 0.529 1788 0.297 1789 0.504 1790 0.605 1791 0.489 1792 0.545 1793 0.587 1794 0.601 1795 0.592 1796 0.338 1797 0.157 1798 0.507 1799 0.499 1800 0.622 1801 0.809 1802 1.202 1803 1.206 1804 1.196 1805 1.606 1806 1.806 1807 1.512 1808 1.198 1809 1.555 1810 1.762 1811 2.263 1812 1.677 1813 1.877 1814 1.839 1815 1.984 1816 2.375 1817 1.688 1818 0.598 1819 1.586 1820 1.359 1821 1.64 1822 1.684 1823 1.137 1824 1.599 1825 1.817 1826 1.706 1827 1.775 1828 1.589 1829 1.599 1830 1.9 1831 1.268 1832 1.103 1833 1.377 1834 1.378 1835 1.374 1836 1.346 1837 1.253 1838 1.146 1839 0.935 1840 1.06 1841 1.217 1842 0.793 1843 0.746 1844 0.939 1845 0.821 1846 0.783 1847 0.901 1848 0.759 1849 0.825 1850 0.781 1851 0.614 1852 0.746 1853 0.801 1854 0.733 1855 0.704 1856 0.716 1857 0.73 1858 0.975 1859 0.994 1860 0.707 1861 1.046 1862 0.748 1863 0.667 1864 0.7 1865 0.74 1866 0.986 1867 0.981 1868 0.821 1869 0.943 1870 0.899 1871 0.506 1872 0.907 1873 0.887 1874 0.837 1875 0.859 1876 0.953 1877 0.725 1878 0.963 1879 0.851 1880 0.877 1881 0.805 1882 0.386 1883 0.815 1884 0.965 1885 0.623 1886 0.685 1887 1.014 1888 0.941 1889 0.795 1890 1.243 1891 1.343 1892 1.132 1893 1.44 1894 0.808 1895 1.379 1896 1.059 1897 1.051 1898 1.373 1899 1.65 1900 1.407 1901 1.564 1902 1.689 1903 1.55 1904 1.604 1905 1.447 1906 1.935 1907 1.643 1908 1.45 1909 0.898 1910 0.919 1911 1.104 1912 1.251 1913 1.162 1914 0.904 1915 0.984 1916 1.157 1917 0.924 1918 1.096 1919 1.248 1920 1.365 1921 1.161 1922 1.307 1923 1.099 1924 0.887 1925 0.831 1926 0.843 1927 0.918 1928 0.899 1929 1.137 1930 1.098 1931 0.569 1932 0.983 1933 0.938 1934 0.785 1935 0.966 1936 0.924 1937 0.95 1938 1.067 1939 1.004 1940 1.005 1941 0.816 1942 0.993 1943 0.951 1944 1.036 1945 0.713 1946 1.072 1947 0.959 1948 1.126 1949 0.718 1950 0.742 1951 0.969 1952 0.671 1953 0.473 1954 0.828 1955 0.687 1956 0.764 1957 0.692 1958 0.691 1959 0.754 1960 0.875 1961 0.632 1962 0.704 1963 0.707 1964 0.757 1965 0.639 1966 0.703 1967 0.71 1968 0.528 1969 0.749 1970 0.686 1971 0.718 1972 0.439 1973 0.63 1974 0.776 1975 0.754 1976 0.621 1977 0.648 1978 0.971 1979 0.586 1980 0.579 1981 0.653 1982 0.468 1983 0.592 1984 0.725 1985 0.714 1986 0.779 1987 0.737 1988 0.729 1989 0.704 1990 0.621 1991 0.925