# asia_russ189 - Nanjan - 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/3573 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ189 - Nanjan - 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: Nanjan # Location: # Country: Russia # Northernmost_Latitude: 69.45 # Southernmost_Latitude: 69.45 # Easternmost_Longitude: 150.25 # Westernmost_Longitude: 150.25 # Elevation: 80 m #-------------------- # Data_Collection # Collection_Name: asia_russ189B # Earliest_Year: 1720 # Most_Recent_Year: 1994 # 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":"6.23232778725","T2":"18.958307108","M1":"0.0211092972511","M2":"0.205005672167"}} #-------------------- # 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 1720 1.452 1721 1.379 1722 1.162 1723 1.179 1724 0.308 1725 0.648 1726 1.299 1727 1.239 1728 1.07 1729 0.397 1730 0.136 1731 0.596 1732 1.309 1733 0.798 1734 0.944 1735 0.387 1736 1.061 1737 1.277 1738 0.891 1739 1.387 1740 0.702 1741 1.171 1742 1.046 1743 0.937 1744 0.548 1745 1.244 1746 0.63 1747 0.608 1748 0.757 1749 0.89 1750 1.299 1751 0.954 1752 1.44 1753 0.541 1754 1.343 1755 1.614 1756 0.891 1757 1.897 1758 1.531 1759 1.25 1760 0.777 1761 0.885 1762 0.367 1763 1.482 1764 1.077 1765 0.712 1766 1.008 1767 0.792 1768 0.685 1769 0.467 1770 1.004 1771 0.802 1772 0.639 1773 0.835 1774 0.604 1775 0.97 1776 0.547 1777 0.968 1778 1.211 1779 0.505 1780 0.219 1781 0.958 1782 0.88 1783 0.957 1784 1.132 1785 1.159 1786 0.881 1787 0.634 1788 0.573 1789 0.913 1790 0.893 1791 0.925 1792 0.967 1793 0.563 1794 0.255 1795 0.369 1796 0.23 1797 0.325 1798 0.796 1799 0.785 1800 0.709 1801 0.137 1802 1.005 1803 0.639 1804 0.656 1805 1.164 1806 0.772 1807 0.605 1808 0.968 1809 0.599 1810 0.786 1811 0.91 1812 0.291 1813 0.566 1814 0.569 1815 0.791 1816 0.893 1817 0.478 1818 0.248 1819 1.438 1820 1.084 1821 0.711 1822 0.444 1823 1.119 1824 1.061 1825 1.223 1826 0.707 1827 0.566 1828 1.725 1829 1.314 1830 1.253 1831 1.151 1832 1.412 1833 1.842 1834 0.952 1835 1.629 1836 1.659 1837 0.386 1838 1.214 1839 1.237 1840 1.41 1841 0.577 1842 1.803 1843 1.305 1844 1.056 1845 1.162 1846 1.033 1847 0.987 1848 0.893 1849 0.897 1850 0.848 1851 1.009 1852 0.701 1853 1.106 1854 1.413 1855 1.479 1856 0.945 1857 0.781 1858 2.105 1859 0.952 1860 0.941 1861 1.541 1862 0.585 1863 0.345 1864 0.908 1865 0.812 1866 1.194 1867 1.161 1868 0.848 1869 0.947 1870 1.491 1871 1.05 1872 1.097 1873 1.048 1874 0.921 1875 0.53 1876 1.072 1877 1.212 1878 0.699 1879 0.621 1880 0.721 1881 0.641 1882 0.539 1883 0.611 1884 0.636 1885 0.719 1886 0.621 1887 0.792 1888 1.201 1889 0.574 1890 0.978 1891 1.168 1892 0.193 1893 0.708 1894 0.865 1895 0.838 1896 0.406 1897 1.171 1898 1.283 1899 0.893 1900 0.66 1901 1.384 1902 1.829 1903 1.149 1904 0.817 1905 0.693 1906 0.873 1907 0.869 1908 1.031 1909 0.818 1910 0.565 1911 1.478 1912 1.441 1913 1.327 1914 1.467 1915 0.284 1916 0.962 1917 1.192 1918 0.571 1919 0.561 1920 0.943 1921 0.848 1922 1.136 1923 1.219 1924 0.917 1925 1.715 1926 1.008 1927 1.648 1928 1.564 1929 0.992 1930 1.386 1931 0.985 1932 0.923 1933 1.228 1934 0.837 1935 1.297 1936 1.211 1937 0.679 1938 0.98 1939 1.102 1940 0.978 1941 0.656 1942 1.12 1943 1.282 1944 1.149 1945 0.7 1946 0.535 1947 1.134 1948 0.99 1949 0.748 1950 0.824 1951 1.219 1952 1.195 1953 1.534 1954 0.903 1955 1.098 1956 1.616 1957 0.981 1958 1.235 1959 0.658 1960 1.533 1961 1.016 1962 0.483 1963 0.899 1964 1.053 1965 1.329 1966 1.181 1967 0.778 1968 1.487 1969 1.477 1970 1.442 1971 1.325 1972 0.44 1973 1.348 1974 1.507 1975 1.056 1976 1.518 1977 1.518 1978 0.803 1979 0.448 1980 1.119 1981 0.741 1982 0.812 1983 0.806 1984 0.355 1985 1.215 1986 0.901 1987 0.753 1988 0.795 1989 1.082 1990 0.687 1991 0.89 1992 0.251 1993 0.994 1994 0.96