# asia_russ081w - Valaam - 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/4711 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ081w - Valaam - 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: Valaam # Location: # Country: Russia # Northernmost_Latitude: 61.37 # Southernmost_Latitude: 61.37 # Easternmost_Longitude: 30.9 # Westernmost_Longitude: 30.9 # Elevation: 25 m #-------------------- # Data_Collection # Collection_Name: asia_russ081wB # Earliest_Year: 1775 # Most_Recent_Year: 1992 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"5.31671741453","T2":"15.843773853","M1":"0.0226611627515","M2":"0.524723737981"}} #-------------------- # 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 1775 0.266 1776 0.297 1777 0.485 1778 0.825 1779 0.953 1780 0.919 1781 0.544 1782 1.03 1783 1.218 1784 1.224 1785 1.23 1786 1.292 1787 1.335 1788 1.385 1789 0.808 1790 0.888 1791 1.128 1792 0.942 1793 1.13 1794 0.918 1795 0.985 1796 0.616 1797 0.605 1798 0.781 1799 1.091 1800 1.115 1801 1.107 1802 1.2 1803 1.149 1804 0.836 1805 1.324 1806 1.214 1807 0.932 1808 1.011 1809 1.065 1810 1.03 1811 0.988 1812 1.341 1813 1.021 1814 0.862 1815 1.147 1816 0.715 1817 1.149 1818 0.887 1819 1.136 1820 1.121 1821 1.269 1822 0.64 1823 0.915 1824 0.728 1825 0.787 1826 0.588 1827 0.697 1828 0.798 1829 0.724 1830 1.083 1831 0.766 1832 0.773 1833 1.12 1834 1.186 1835 0.581 1836 0.711 1837 1.08 1838 0.853 1839 1.079 1840 1.333 1841 1.643 1842 1.383 1843 0.902 1844 1.433 1845 0.954 1846 1.029 1847 0.975 1848 1.119 1849 1.42 1850 0.871 1851 1.418 1852 1.313 1853 0.69 1854 1.031 1855 0.688 1856 0.969 1857 0.941 1858 1.012 1859 0.696 1860 1.163 1861 0.524 1862 0.84 1863 1.182 1864 1.138 1865 1.371 1866 1.353 1867 1.188 1868 0.975 1869 0.928 1870 1.006 1871 1.084 1872 0.881 1873 1.122 1874 0.706 1875 0.787 1876 0.491 1877 0.972 1878 1.253 1879 1.332 1880 1.366 1881 0.96 1882 1.531 1883 1.119 1884 1.218 1885 1.264 1886 0.854 1887 0.778 1888 1.118 1889 0.719 1890 0.745 1891 0.842 1892 1.085 1893 0.939 1894 1.146 1895 1.132 1896 0.553 1897 0.54 1898 0.988 1899 0.76 1900 0.722 1901 0.928 1902 1.145 1903 1.39 1904 1.422 1905 1.226 1906 1.114 1907 0.915 1908 0.859 1909 0.856 1910 0.745 1911 1.071 1912 0.804 1913 0.772 1914 0.541 1915 0.761 1916 0.834 1917 0.354 1918 0.806 1919 0.508 1920 0.499 1921 0.825 1922 1.364 1923 1.208 1924 1.333 1925 1.282 1926 1.036 1927 1.181 1928 1.05 1929 0.92 1930 1.009 1931 0.64 1932 0.837 1933 0.652 1934 1.414 1935 0.803 1936 0.752 1937 0.858 1938 1.232 1939 0.532 1940 0.504 1941 0.76 1942 0.505 1943 1.217 1944 1.154 1945 1.5 1946 1.939 1947 1.556 1948 1.247 1949 1.61 1950 1.631 1951 0.794 1952 0.93 1953 1.281 1954 1.235 1955 0.571 1956 0.332 1957 0.74 1958 0.824 1959 0.59 1960 0.873 1961 0.98 1962 0.892 1963 0.756 1964 0.911 1965 1.0 1966 0.933 1967 0.933 1968 0.822 1969 0.812 1970 0.777 1971 0.626 1972 0.711 1973 0.762 1974 0.723 1975 0.462 1976 0.659 1977 0.899 1978 0.577 1979 0.818 1980 1.016 1981 1.386 1982 1.322 1983 1.235 1984 0.755 1985 1.104 1986 1.231 1987 1.276 1988 1.224 1989 1.166 1990 1.17 1991 1.414 1992 0.621