# asia_russ043w - Voroney - 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/4726 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ043w - Voroney - 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: Voroney # Location: # Country: Russia # Northernmost_Latitude: 63.43 # Southernmost_Latitude: 63.43 # Easternmost_Longitude: 43.55 # Westernmost_Longitude: 43.55 # Elevation: 120 m #-------------------- # Data_Collection # Collection_Name: asia_russ043wB # Earliest_Year: 1775 # 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":"6.13666965517","T2":"20.0636843979","M1":"0.0215948874355","M2":"0.266004858261"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1.116 1776 1.275 1777 1.206 1778 0.891 1779 0.883 1780 1.168 1781 1.32 1782 0.977 1783 1.141 1784 1.265 1785 1.112 1786 1.175 1787 1.037 1788 1.117 1789 0.841 1790 0.915 1791 1.059 1792 0.987 1793 0.961 1794 1.078 1795 0.943 1796 0.948 1797 1.101 1798 1.27 1799 0.934 1800 0.97 1801 0.951 1802 0.737 1803 0.998 1804 0.967 1805 1.069 1806 0.91 1807 0.799 1808 0.894 1809 1.16 1810 0.866 1811 1.023 1812 0.934 1813 0.72 1814 0.783 1815 0.934 1816 0.672 1817 0.413 1818 0.421 1819 0.638 1820 0.6 1821 0.497 1822 0.575 1823 0.863 1824 1.314 1825 1.482 1826 1.507 1827 1.3 1828 1.596 1829 1.743 1830 1.617 1831 1.256 1832 1.231 1833 1.461 1834 1.191 1835 1.104 1836 0.577 1837 0.627 1838 0.352 1839 0.478 1840 0.444 1841 0.555 1842 0.409 1843 0.402 1844 0.736 1845 0.732 1846 0.877 1847 0.871 1848 0.753 1849 0.91 1850 1.022 1851 1.16 1852 0.831 1853 1.031 1854 0.994 1855 1.083 1856 1.193 1857 1.039 1858 0.965 1859 0.944 1860 1.053 1861 0.903 1862 1.021 1863 0.992 1864 1.254 1865 0.921 1866 1.191 1867 0.88 1868 0.983 1869 0.911 1870 0.656 1871 0.683 1872 0.842 1873 0.966 1874 0.798 1875 0.687 1876 0.711 1877 0.826 1878 1.306 1879 0.783 1880 0.822 1881 0.679 1882 0.764 1883 0.939 1884 1.058 1885 1.14 1886 0.858 1887 0.819 1888 0.759 1889 0.914 1890 1.038 1891 0.924 1892 0.841 1893 0.854 1894 0.743 1895 0.818 1896 0.989 1897 0.877 1898 1.106 1899 1.027 1900 1.079 1901 1.149 1902 1.118 1903 0.998 1904 0.959 1905 0.941 1906 1.156 1907 1.311 1908 1.045 1909 0.936 1910 0.875 1911 1.042 1912 1.047 1913 1.032 1914 1.087 1915 1.008 1916 0.889 1917 1.134 1918 0.966 1919 1.099 1920 0.868 1921 1.135 1922 1.36 1923 1.161 1924 1.28 1925 1.347 1926 1.344 1927 1.359 1928 0.887 1929 1.07 1930 1.136 1931 1.282 1932 1.249 1933 1.408 1934 1.298 1935 1.157 1936 1.16 1937 1.12 1938 1.227 1939 1.049 1940 1.14 1941 0.702 1942 0.899 1943 1.005 1944 0.733 1945 1.001 1946 0.903 1947 0.946 1948 1.067 1949 0.982 1950 0.978 1951 1.146 1952 1.306 1953 1.374 1954 1.363 1955 1.067 1956 1.183 1957 0.986 1958 0.655 1959 1.218 1960 1.165 1961 0.81 1962 0.523 1963 0.612 1964 0.973 1965 1.039 1966 1.145 1967 0.684 1968 0.907 1969 0.755 1970 1.084 1971 0.851 1972 0.872 1973 0.882 1974 0.764 1975 0.433 1976 0.653 1977 0.741 1978 0.801 1979 0.847 1980 0.855 1981 0.957 1982 0.54 1983 0.97 1984 1.159 1985 0.926 1986 0.912 1987 1.142 1988 1.219 1989 0.797 1990 0.756