# asia_russ030w - Kulyumbe River - 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/4487 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ030w - Kulyumbe River - 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: Kulyumbe River # Location: # Country: Russia # Northernmost_Latitude: 67.97 # Southernmost_Latitude: 67.97 # Easternmost_Longitude: 88.92 # Westernmost_Longitude: 88.92 # Elevation: 160 m #-------------------- # Data_Collection # Collection_Name: asia_russ030wB # Earliest_Year: 1727 # 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":"5.66230286173","T2":"18.9900773136","M1":"0.0222379313529","M2":"0.328265064593"}} #-------------------- # 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 1727 0.943 1728 1.337 1729 1.491 1730 1.69 1731 1.289 1732 0.716 1733 1.025 1734 0.69 1735 0.69 1736 0.584 1737 0.851 1738 0.781 1739 1.3 1740 0.853 1741 0.705 1742 0.552 1743 1.04 1744 1.092 1745 0.725 1746 1.131 1747 1.351 1748 1.233 1749 1.309 1750 1.312 1751 1.039 1752 1.099 1753 1.11 1754 1.074 1755 0.813 1756 1.048 1757 0.992 1758 1.207 1759 0.756 1760 0.78 1761 1.092 1762 1.075 1763 1.403 1764 1.315 1765 1.588 1766 1.477 1767 1.48 1768 0.94 1769 1.216 1770 0.98 1771 0.993 1772 0.709 1773 0.64 1774 0.756 1775 1.233 1776 0.82 1777 1.143 1778 1.095 1779 0.944 1780 0.92 1781 0.904 1782 0.966 1783 0.754 1784 1.401 1785 1.102 1786 0.871 1787 1.249 1788 0.623 1789 0.952 1790 0.704 1791 0.635 1792 0.533 1793 0.983 1794 0.828 1795 0.935 1796 1.008 1797 0.715 1798 0.679 1799 0.926 1800 0.924 1801 1.243 1802 0.963 1803 0.915 1804 0.867 1805 1.353 1806 1.063 1807 0.453 1808 0.748 1809 1.028 1810 0.969 1811 0.915 1812 0.861 1813 1.229 1814 1.321 1815 1.101 1816 1.02 1817 0.895 1818 0.637 1819 0.357 1820 0.73 1821 0.784 1822 0.572 1823 0.686 1824 0.612 1825 0.477 1826 0.875 1827 0.969 1828 0.361 1829 0.796 1830 0.208 1831 0.791 1832 0.7 1833 0.412 1834 0.939 1835 1.028 1836 0.679 1837 0.725 1838 1.055 1839 0.801 1840 0.986 1841 0.918 1842 1.191 1843 0.876 1844 1.269 1845 1.174 1846 1.072 1847 0.842 1848 1.085 1849 0.856 1850 0.848 1851 0.994 1852 0.891 1853 0.928 1854 0.634 1855 0.539 1856 0.852 1857 1.049 1858 1.352 1859 0.897 1860 1.009 1861 1.4 1862 1.153 1863 1.57 1864 1.444 1865 1.425 1866 1.009 1867 0.237 1868 1.411 1869 0.744 1870 1.34 1871 0.929 1872 1.105 1873 1.041 1874 0.811 1875 1.056 1876 1.118 1877 1.31 1878 1.171 1879 1.221 1880 1.074 1881 0.795 1882 0.78 1883 0.945 1884 0.856 1885 0.704 1886 1.03 1887 0.716 1888 0.812 1889 0.635 1890 0.703 1891 1.023 1892 1.29 1893 1.222 1894 1.289 1895 0.67 1896 1.022 1897 1.337 1898 1.094 1899 1.024 1900 0.823 1901 0.932 1902 0.908 1903 1.127 1904 0.965 1905 0.998 1906 1.074 1907 0.64 1908 1.538 1909 1.355 1910 0.739 1911 0.854 1912 0.712 1913 1.03 1914 0.895 1915 1.398 1916 0.925 1917 1.189 1918 1.397 1919 1.127 1920 1.739 1921 1.214 1922 1.36 1923 1.22 1924 1.447 1925 1.159 1926 1.59 1927 1.145 1928 1.36 1929 0.873 1930 1.269 1931 0.825 1932 0.99 1933 1.165 1934 1.421 1935 1.13 1936 1.478 1937 1.227 1938 1.257 1939 1.267 1940 1.236 1941 0.907 1942 1.177 1943 1.052 1944 0.832 1945 1.147 1946 1.388 1947 1.176 1948 1.463 1949 1.139 1950 1.581 1951 0.976 1952 1.171 1953 1.376 1954 1.052 1955 1.095 1956 1.207 1957 1.098 1958 1.079 1959 1.404 1960 0.616 1961 0.68 1962 0.939 1963 0.747 1964 0.702 1965 0.963 1966 0.651 1967 0.989 1968 0.772 1969 1.177 1970 0.857 1971 0.584 1972 0.855 1973 0.514 1974 0.364 1975 0.877 1976 0.881 1977 0.647 1978 0.689 1979 0.976 1980 0.382 1981 0.561 1982 0.506 1983 0.804 1984 0.816 1985 0.669 1986 0.641 1987 0.407 1988 0.495 1989 0.355 1990 0.618