# asia_russ100w - Polui River Head - 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/4600 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ100w - Polui River Head - 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: Polui River Head # Location: # Country: Russia # Northernmost_Latitude: 65.3 # Southernmost_Latitude: 65.3 # Easternmost_Longitude: 69.68 # Westernmost_Longitude: 69.68 # Elevation: 35 m #-------------------- # Data_Collection # Collection_Name: asia_russ100wB # Earliest_Year: 1757 # 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":"6.3467941627","T2":"16.6498292826","M1":"0.0219959109714","M2":"0.28115939478"}} #-------------------- # 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 1757 0.695 1758 0.684 1759 0.644 1760 0.65 1761 0.785 1762 1.018 1763 1.002 1764 0.719 1765 1.0 1766 0.856 1767 1.091 1768 0.895 1769 0.882 1770 0.299 1771 0.681 1772 0.882 1773 0.669 1774 0.929 1775 0.578 1776 0.477 1777 0.934 1778 0.93 1779 0.763 1780 0.874 1781 0.682 1782 0.841 1783 0.49 1784 0.717 1785 0.63 1786 0.613 1787 0.965 1788 0.541 1789 0.613 1790 0.925 1791 0.947 1792 0.909 1793 0.929 1794 1.191 1795 1.048 1796 0.899 1797 1.05 1798 1.085 1799 0.875 1800 1.058 1801 0.994 1802 0.971 1803 0.805 1804 0.774 1805 0.892 1806 0.846 1807 1.314 1808 1.235 1809 1.13 1810 0.892 1811 0.911 1812 0.762 1813 0.877 1814 0.809 1815 0.618 1816 0.336 1817 0.597 1818 0.125 1819 0.449 1820 0.566 1821 0.685 1822 0.732 1823 0.951 1824 1.125 1825 0.819 1826 0.621 1827 1.085 1828 0.491 1829 0.628 1830 0.718 1831 0.577 1832 0.788 1833 0.802 1834 0.834 1835 1.146 1836 0.903 1837 0.739 1838 0.682 1839 1.058 1840 1.152 1841 1.083 1842 1.058 1843 1.15 1844 1.254 1845 1.356 1846 1.376 1847 1.579 1848 1.511 1849 1.873 1850 1.694 1851 1.035 1852 1.249 1853 1.349 1854 0.984 1855 0.996 1856 1.483 1857 1.133 1858 1.188 1859 1.373 1860 1.294 1861 1.202 1862 0.729 1863 0.64 1864 1.16 1865 0.785 1866 0.883 1867 0.743 1868 1.189 1869 1.013 1870 1.054 1871 1.275 1872 1.049 1873 0.604 1874 1.243 1875 1.364 1876 1.198 1877 1.038 1878 1.511 1879 1.328 1880 1.335 1881 1.187 1882 0.588 1883 0.63 1884 0.755 1885 0.762 1886 0.921 1887 0.809 1888 0.738 1889 0.479 1890 0.527 1891 0.525 1892 0.254 1893 0.311 1894 0.169 1895 0.413 1896 0.359 1897 0.69 1898 0.723 1899 0.414 1900 0.882 1901 0.788 1902 0.846 1903 0.576 1904 0.865 1905 0.98 1906 0.959 1907 0.992 1908 1.1 1909 1.291 1910 1.114 1911 1.246 1912 0.893 1913 1.105 1914 0.783 1915 0.798 1916 0.917 1917 0.768 1918 0.99 1919 0.834 1920 0.83 1921 0.919 1922 1.091 1923 0.982 1924 1.207 1925 1.2 1926 1.045 1927 1.424 1928 1.449 1929 1.271 1930 1.319 1931 1.271 1932 1.057 1933 0.88 1934 0.945 1935 1.035 1936 1.239 1937 1.233 1938 1.359 1939 1.477 1940 1.13 1941 0.712 1942 1.216 1943 1.614 1944 1.56 1945 1.419 1946 1.248 1947 0.985 1948 1.345 1949 1.21 1950 1.078 1951 1.167 1952 1.345 1953 0.991 1954 1.501 1955 1.326 1956 1.475 1957 1.249 1958 1.193 1959 1.36 1960 1.006 1961 1.148 1962 0.87 1963 1.239 1964 1.065 1965 1.049 1966 0.835 1967 1.056 1968 1.032 1969 0.846 1970 0.583 1971 0.607 1972 0.76 1973 0.576 1974 0.641 1975 0.592 1976 0.532 1977 0.579 1978 0.776 1979 0.455 1980 0.591 1981 0.7 1982 0.835 1983 0.788 1984 0.7 1985 0.633 1986 0.769 1987 0.804 1988 0.994 1989 0.962 1990 0.945 1991 0.931