# asia_russ058w - Charijaga - 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/4377 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ058w - Charijaga - 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: Charijaga # Location: # Country: Russia # Northernmost_Latitude: 66.88 # Southernmost_Latitude: 66.88 # Easternmost_Longitude: 51.95 # Westernmost_Longitude: 51.95 # Elevation: 35 m #-------------------- # Data_Collection # Collection_Name: asia_russ058wB # Earliest_Year: 1734 # 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":"5.79959746339","T2":"19.1688587","M1":"0.0219026820354","M2":"0.25561831797"}} #-------------------- # Species # Species_Name: Scots pine # Species_Code: PISY #-------------------- # 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 1734 0.66 1735 1.067 1736 0.959 1737 1.149 1738 1.265 1739 0.797 1740 0.93 1741 1.114 1742 1.122 1743 1.05 1744 1.118 1745 1.438 1746 1.022 1747 1.003 1748 0.811 1749 0.633 1750 0.802 1751 0.711 1752 0.482 1753 1.026 1754 0.913 1755 1.097 1756 1.169 1757 1.072 1758 0.933 1759 0.851 1760 0.717 1761 0.747 1762 0.885 1763 0.598 1764 0.775 1765 1.138 1766 0.991 1767 1.268 1768 1.248 1769 0.751 1770 0.597 1771 0.942 1772 0.75 1773 1.006 1774 1.536 1775 1.209 1776 0.887 1777 1.09 1778 1.403 1779 0.914 1780 1.146 1781 0.889 1782 0.819 1783 0.655 1784 0.647 1785 0.849 1786 0.689 1787 0.703 1788 0.852 1789 0.72 1790 0.779 1791 0.917 1792 1.286 1793 1.947 1794 1.736 1795 1.595 1796 1.777 1797 1.575 1798 1.641 1799 1.169 1800 1.333 1801 1.189 1802 1.308 1803 1.234 1804 1.427 1805 1.359 1806 1.066 1807 1.358 1808 1.408 1809 1.183 1810 0.74 1811 1.002 1812 1.004 1813 1.11 1814 0.776 1815 0.601 1816 0.369 1817 0.329 1818 0.461 1819 0.55 1820 0.668 1821 0.867 1822 0.752 1823 0.882 1824 1.077 1825 0.875 1826 1.206 1827 1.761 1828 1.075 1829 1.431 1830 1.248 1831 1.023 1832 0.979 1833 0.954 1834 0.717 1835 0.663 1836 0.823 1837 0.534 1838 0.403 1839 0.47 1840 0.735 1841 0.733 1842 1.183 1843 0.795 1844 0.974 1845 0.83 1846 0.758 1847 0.905 1848 1.03 1849 1.214 1850 1.469 1851 1.364 1852 1.384 1853 1.119 1854 1.23 1855 1.103 1856 1.287 1857 0.839 1858 0.65 1859 0.976 1860 0.861 1861 0.832 1862 0.553 1863 0.338 1864 0.98 1865 0.464 1866 0.4 1867 0.552 1868 0.481 1869 0.833 1870 0.716 1871 0.724 1872 0.633 1873 0.552 1874 0.654 1875 0.629 1876 0.7 1877 0.68 1878 0.732 1879 1.106 1880 0.903 1881 0.94 1882 0.638 1883 0.423 1884 0.598 1885 0.606 1886 0.543 1887 0.511 1888 0.659 1889 0.63 1890 0.96 1891 0.813 1892 0.863 1893 1.101 1894 0.708 1895 0.64 1896 0.954 1897 0.787 1898 1.037 1899 0.605 1900 0.48 1901 0.645 1902 0.548 1903 0.273 1904 0.546 1905 0.645 1906 0.626 1907 0.591 1908 0.619 1909 0.893 1910 0.88 1911 0.918 1912 0.914 1913 1.593 1914 0.97 1915 1.374 1916 1.313 1917 1.022 1918 0.846 1919 1.105 1920 1.126 1921 1.182 1922 1.451 1923 1.6 1924 1.759 1925 1.782 1926 0.944 1927 1.476 1928 1.542 1929 1.25 1930 1.332 1931 1.614 1932 1.401 1933 1.185 1934 1.194 1935 1.282 1936 1.198 1937 1.409 1938 1.542 1939 1.671 1940 1.696 1941 1.12 1942 1.132 1943 1.51 1944 1.242 1945 1.138 1946 1.146 1947 0.833 1948 1.008 1949 1.252 1950 1.086 1951 1.357 1952 1.156 1953 0.969 1954 1.432 1955 1.121 1956 1.209 1957 1.496 1958 1.118 1959 1.203 1960 1.54 1961 1.34 1962 1.301 1963 1.227 1964 1.408 1965 1.264 1966 1.197 1967 1.514 1968 1.18 1969 0.72 1970 0.893 1971 0.891 1972 0.785 1973 0.807 1974 0.928 1975 0.594 1976 0.837 1977 0.792 1978 0.821 1979 0.858 1980 0.798 1981 0.946 1982 0.853 1983 1.214 1984 1.299 1985 0.896 1986 0.69 1987 0.746 1988 0.87 1989 0.899 1990 0.994