# asia_russ111w - Shaguchan 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/4636 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ111w - Shaguchan 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: Shaguchan river # Location: # Country: Russia # Northernmost_Latitude: 63.58 # Southernmost_Latitude: 63.58 # Easternmost_Longitude: 148.28 # Westernmost_Longitude: 148.28 # Elevation: 1000 m #-------------------- # Data_Collection # Collection_Name: asia_russ111wB # Earliest_Year: 1736 # 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":"3.11393657756","T2":"17.8973390614","M1":"0.0221475241863","M2":"0.313144360921"}} #-------------------- # 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 1736 0.818 1737 0.494 1738 0.504 1739 1.052 1740 0.17 1741 0.623 1742 0.998 1743 0.282 1744 0.281 1745 0.906 1746 1.062 1747 0.753 1748 0.419 1749 1.133 1750 1.145 1751 1.208 1752 1.192 1753 1.103 1754 0.849 1755 1.224 1756 0.903 1757 1.624 1758 0.923 1759 1.041 1760 1.325 1761 0.711 1762 0.35 1763 0.937 1764 0.57 1765 0.694 1766 0.971 1767 0.535 1768 0.595 1769 0.894 1770 0.663 1771 1.212 1772 0.836 1773 0.97 1774 0.996 1775 1.306 1776 1.404 1777 0.499 1778 1.393 1779 1.18 1780 1.237 1781 1.567 1782 1.195 1783 1.247 1784 0.832 1785 0.945 1786 1.101 1787 0.895 1788 0.914 1789 1.756 1790 1.461 1791 1.243 1792 1.636 1793 1.509 1794 1.108 1795 1.715 1796 0.94 1797 0.474 1798 1.078 1799 1.419 1800 1.191 1801 0.994 1802 1.084 1803 1.456 1804 1.093 1805 1.998 1806 1.579 1807 1.97 1808 1.183 1809 1.501 1810 1.165 1811 1.232 1812 0.971 1813 0.477 1814 1.152 1815 0.811 1816 1.434 1817 0.373 1818 0.14 1819 1.115 1820 0.951 1821 1.035 1822 0.794 1823 0.478 1824 1.037 1825 0.951 1826 1.296 1827 0.989 1828 1.169 1829 1.464 1830 1.476 1831 1.346 1832 0.835 1833 1.159 1834 0.978 1835 1.143 1836 1.199 1837 0.233 1838 0.556 1839 0.445 1840 0.598 1841 0.587 1842 0.208 1843 0.433 1844 0.561 1845 0.702 1846 0.804 1847 0.856 1848 0.51 1849 0.73 1850 0.678 1851 0.722 1852 0.384 1853 0.917 1854 0.797 1855 0.384 1856 0.432 1857 0.11 1858 0.442 1859 0.521 1860 0.517 1861 0.678 1862 0.515 1863 0.145 1864 0.344 1865 0.486 1866 0.409 1867 0.644 1868 0.519 1869 0.764 1870 0.896 1871 0.856 1872 0.783 1873 1.071 1874 0.718 1875 0.829 1876 0.92 1877 0.754 1878 0.983 1879 0.657 1880 1.019 1881 0.756 1882 0.116 1883 0.662 1884 0.956 1885 0.887 1886 0.63 1887 0.37 1888 0.689 1889 0.485 1890 0.716 1891 1.252 1892 0.982 1893 1.08 1894 0.924 1895 0.936 1896 0.878 1897 0.938 1898 1.36 1899 1.301 1900 1.484 1901 1.099 1902 2.142 1903 1.373 1904 1.178 1905 0.95 1906 1.089 1907 1.204 1908 0.682 1909 1.007 1910 1.174 1911 0.929 1912 1.294 1913 1.168 1914 1.346 1915 0.968 1916 1.159 1917 1.322 1918 0.761 1919 1.168 1920 0.902 1921 1.357 1922 0.765 1923 0.892 1924 1.015 1925 1.038 1926 1.143 1927 0.925 1928 1.368 1929 1.626 1930 1.66 1931 1.46 1932 1.514 1933 1.569 1934 1.126 1935 1.116 1936 1.664 1937 1.161 1938 1.556 1939 1.029 1940 1.205 1941 0.515 1942 1.479 1943 1.273 1944 1.731 1945 0.458 1946 0.713 1947 1.054 1948 1.636 1949 1.124 1950 1.043 1951 1.205 1952 1.289 1953 1.145 1954 1.187 1955 1.048 1956 1.339 1957 1.276 1958 0.954 1959 0.731 1960 1.291 1961 1.254 1962 0.894 1963 0.765 1964 1.191 1965 0.832 1966 1.242 1967 0.937 1968 0.776 1969 1.073 1970 0.904 1971 0.649 1972 0.536 1973 0.987 1974 0.866 1975 1.07 1976 1.003 1977 1.09 1978 0.617 1979 0.343 1980 0.792 1981 0.873 1982 0.388 1983 1.184 1984 0.604 1985 0.674 1986 1.038 1987 0.966 1988 0.863 1989 1.306 1990 0.735 1991 0.755