# asia_russ117w - Krasnovishersk - 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/4480 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ117w - Krasnovishersk - 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: Krasnovishersk # Location: # Country: Russia # Northernmost_Latitude: 60.38 # Southernmost_Latitude: 60.38 # Easternmost_Longitude: 57.12 # Westernmost_Longitude: 57.12 # Elevation: 140 m #-------------------- # Data_Collection # Collection_Name: asia_russ117wB # Earliest_Year: 1790 # 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":"7.11587828747","T2":"15.4156817692","M1":"0.0225613008748","M2":"0.202938522583"}} #-------------------- # Species # Species_Name: Siberian larch # Species_Code: LASI #-------------------- # 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 1790 1.621 1791 1.248 1792 2.136 1793 2.362 1794 2.021 1795 2.066 1796 1.867 1797 1.579 1798 1.094 1799 0.956 1800 0.747 1801 0.85 1802 0.552 1803 0.805 1804 1.139 1805 1.297 1806 1.327 1807 0.667 1808 0.66 1809 0.694 1810 0.712 1811 0.678 1812 0.781 1813 0.962 1814 0.98 1815 0.928 1816 1.096 1817 1.153 1818 1.278 1819 1.328 1820 1.233 1821 1.405 1822 1.303 1823 1.186 1824 1.13 1825 1.064 1826 1.029 1827 1.078 1828 1.227 1829 1.166 1830 1.177 1831 0.965 1832 0.99 1833 0.984 1834 0.998 1835 0.909 1836 0.79 1837 0.97 1838 1.143 1839 1.081 1840 1.214 1841 0.93 1842 0.813 1843 0.68 1844 0.92 1845 0.864 1846 0.874 1847 0.885 1848 0.76 1849 0.459 1850 0.606 1851 0.375 1852 0.545 1853 0.553 1854 0.828 1855 0.854 1856 1.244 1857 0.802 1858 1.111 1859 1.237 1860 1.286 1861 1.163 1862 0.835 1863 1.067 1864 1.463 1865 1.403 1866 1.174 1867 1.141 1868 1.223 1869 1.17 1870 0.977 1871 0.831 1872 0.962 1873 0.934 1874 0.855 1875 0.898 1876 0.877 1877 0.857 1878 1.198 1879 0.967 1880 1.236 1881 0.727 1882 0.847 1883 0.842 1884 0.955 1885 0.859 1886 1.015 1887 0.933 1888 1.279 1889 0.63 1890 0.904 1891 0.623 1892 0.772 1893 1.065 1894 1.262 1895 1.079 1896 0.789 1897 1.104 1898 1.223 1899 0.952 1900 1.184 1901 1.088 1902 1.143 1903 0.896 1904 0.948 1905 0.797 1906 1.147 1907 1.022 1908 0.734 1909 1.064 1910 0.785 1911 0.909 1912 0.742 1913 0.875 1914 0.251 1915 0.693 1916 0.554 1917 0.485 1918 0.731 1919 0.779 1920 0.979 1921 1.159 1922 1.136 1923 0.845 1924 0.563 1925 0.502 1926 0.604 1927 0.734 1928 0.755 1929 0.873 1930 0.893 1931 0.85 1932 0.653 1933 0.68 1934 0.641 1935 0.494 1936 0.927 1937 1.369 1938 1.907 1939 2.238 1940 1.456 1941 1.331 1942 1.93 1943 2.06 1944 1.983 1945 1.932 1946 1.259 1947 1.167 1948 1.75 1949 1.199 1950 1.666 1951 1.344 1952 1.408 1953 1.379 1954 1.168 1955 0.92 1956 1.374 1957 1.255 1958 1.087 1959 0.985 1960 0.898 1961 0.632 1962 0.844 1963 0.733 1964 0.809 1965 0.624 1966 0.63 1967 0.772 1968 1.173 1969 0.621 1970 0.66 1971 0.816 1972 0.769 1973 0.587 1974 0.732 1975 0.491 1976 0.759 1977 0.801 1978 0.643 1979 0.794 1980 0.679 1981 0.582 1982 0.478 1983 0.414 1984 0.757 1985 0.601 1986 0.669 1987 0.867 1988 0.744 1989 0.758 1990 0.822 1991 0.912