# asia_russ061w - Kedvaran - 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/4458 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ061w - Kedvaran - 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: Kedvaran # Location: # Country: Russia # Northernmost_Latitude: 64.25 # Southernmost_Latitude: 64.25 # Easternmost_Longitude: 53.57 # Westernmost_Longitude: 53.57 # Elevation: 70 m #-------------------- # Data_Collection # Collection_Name: asia_russ061wB # Earliest_Year: 1688 # 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":"6.44324426804","T2":"17.0406138029","M1":"0.022150663011","M2":"0.318665732377"}} #-------------------- # Species # Species_Name: Siberian larch # Species_Code: LASI #-------------------- # 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 1688 0.542 1689 0.587 1690 0.643 1691 0.679 1692 0.865 1693 0.378 1694 0.362 1695 0.858 1696 1.259 1697 1.333 1698 1.314 1699 1.336 1700 1.086 1701 1.459 1702 1.62 1703 1.768 1704 1.74 1705 1.831 1706 1.288 1707 1.704 1708 1.406 1709 1.377 1710 1.1 1711 0.763 1712 0.532 1713 0.899 1714 1.186 1715 1.661 1716 1.256 1717 1.251 1718 1.215 1719 1.152 1720 1.029 1721 1.12 1722 0.751 1723 0.977 1724 1.009 1725 1.21 1726 1.101 1727 1.373 1728 1.301 1729 1.094 1730 1.108 1731 1.394 1732 0.759 1733 1.022 1734 0.984 1735 1.098 1736 1.14 1737 1.399 1738 1.237 1739 1.194 1740 0.689 1741 0.743 1742 0.619 1743 0.6 1744 1.041 1745 1.254 1746 1.093 1747 1.013 1748 0.499 1749 0.714 1750 0.406 1751 0.728 1752 0.702 1753 0.862 1754 1.11 1755 1.272 1756 0.986 1757 0.908 1758 1.456 1759 1.083 1760 1.113 1761 0.996 1762 1.093 1763 0.782 1764 0.837 1765 1.018 1766 0.884 1767 1.223 1768 0.831 1769 0.804 1770 0.804 1771 0.944 1772 0.419 1773 0.449 1774 0.975 1775 0.802 1776 0.83 1777 0.916 1778 0.722 1779 1.1 1780 0.882 1781 0.555 1782 1.215 1783 0.893 1784 0.342 1785 0.802 1786 0.627 1787 0.775 1788 0.9 1789 0.751 1790 1.054 1791 0.875 1792 0.878 1793 1.103 1794 1.13 1795 1.199 1796 1.287 1797 1.127 1798 1.412 1799 1.112 1800 1.23 1801 0.643 1802 0.914 1803 1.013 1804 0.923 1805 0.788 1806 0.614 1807 0.763 1808 0.906 1809 0.92 1810 0.499 1811 0.719 1812 0.595 1813 0.587 1814 0.671 1815 0.4 1816 0.597 1817 0.442 1818 0.609 1819 0.808 1820 0.777 1821 0.95 1822 1.026 1823 1.538 1824 1.428 1825 1.516 1826 0.947 1827 1.761 1828 1.71 1829 1.941 1830 1.637 1831 1.267 1832 1.149 1833 1.6 1834 1.042 1835 0.867 1836 0.509 1837 1.102 1838 0.417 1839 0.954 1840 0.935 1841 0.647 1842 0.944 1843 0.871 1844 1.405 1845 1.216 1846 1.202 1847 1.244 1848 0.861 1849 0.652 1850 0.551 1851 0.579 1852 0.668 1853 0.363 1854 0.948 1855 0.971 1856 1.32 1857 0.904 1858 0.598 1859 0.953 1860 0.754 1861 0.935 1862 0.626 1863 0.399 1864 1.148 1865 0.713 1866 0.719 1867 0.896 1868 0.508 1869 1.159 1870 1.21 1871 0.43 1872 0.727 1873 1.011 1874 0.544 1875 1.049 1876 1.161 1877 1.257 1878 1.323 1879 0.978 1880 1.252 1881 0.76 1882 0.471 1883 1.001 1884 1.153 1885 0.672 1886 0.508 1887 0.748 1888 0.99 1889 0.926 1890 1.409 1891 1.069 1892 0.632 1893 0.603 1894 0.39 1895 0.523 1896 0.572 1897 0.788 1898 0.998 1899 0.963 1900 0.987 1901 0.84 1902 0.759 1903 0.474 1904 0.654 1905 0.487 1906 0.997 1907 0.993 1908 0.703 1909 1.098 1910 0.894 1911 1.119 1912 0.893 1913 0.882 1914 0.746 1915 1.118 1916 1.243 1917 0.846 1918 1.14 1919 1.104 1920 1.124 1921 1.629 1922 1.757 1923 1.616 1924 1.259 1925 1.282 1926 1.093 1927 1.024 1928 1.11 1929 1.203 1930 0.995 1931 0.887 1932 0.876 1933 0.831 1934 0.75 1935 0.827 1936 1.251 1937 1.398 1938 1.463 1939 1.37 1940 1.412 1941 1.168 1942 1.374 1943 1.123 1944 1.231 1945 1.234 1946 1.046 1947 1.087 1948 1.435 1949 1.54 1950 1.169 1951 1.016 1952 1.514 1953 1.211 1954 1.442 1955 1.045 1956 1.483 1957 1.004 1958 0.79 1959 0.756 1960 0.792 1961 0.925 1962 0.869 1963 0.603 1964 1.022 1965 0.871 1966 1.12 1967 0.619 1968 0.96 1969 0.545 1970 0.552 1971 0.558 1972 0.404 1973 0.649 1974 0.796 1975 0.523 1976 0.992 1977 1.186 1978 1.023 1979 1.091 1980 0.924 1981 1.194 1982 0.803 1983 1.116 1984 1.543 1985 1.236 1986 1.066 1987 1.098 1988 1.11 1989 1.023 1990 1.118 1991 1.417