# asia_russ062w - Kedvaran - 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/4460 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ062w - Kedvaran - 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: Kedvaran # Location: # Country: Russia # Northernmost_Latitude: 64.25 # Southernmost_Latitude: 64.25 # Easternmost_Longitude: 53.57 # Westernmost_Longitude: 53.57 # Elevation: 70 m #-------------------- # Data_Collection # Collection_Name: asia_russ062wB # Earliest_Year: 1774 # 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":"6.54340138597","T2":"19.9077236871","M1":"0.0222453246551","M2":"0.265920877163"}} #-------------------- # 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 1774 0.843 1775 1.065 1776 0.911 1777 0.833 1778 0.606 1779 0.696 1780 0.7 1781 0.588 1782 0.743 1783 0.777 1784 0.559 1785 0.662 1786 0.501 1787 0.521 1788 0.559 1789 0.534 1790 0.595 1791 0.573 1792 0.634 1793 0.776 1794 0.826 1795 1.376 1796 1.307 1797 1.103 1798 1.096 1799 1.0 1800 1.13 1801 1.012 1802 0.885 1803 0.788 1804 0.953 1805 1.156 1806 0.954 1807 1.197 1808 1.34 1809 1.226 1810 0.75 1811 0.745 1812 0.914 1813 0.974 1814 1.041 1815 0.845 1816 0.786 1817 0.735 1818 0.791 1819 0.828 1820 1.048 1821 1.476 1822 1.39 1823 1.384 1824 1.394 1825 1.267 1826 1.144 1827 1.345 1828 1.132 1829 1.609 1830 1.677 1831 1.389 1832 1.545 1833 1.422 1834 1.211 1835 0.961 1836 0.922 1837 0.834 1838 0.751 1839 1.016 1840 0.86 1841 0.93 1842 1.262 1843 1.134 1844 1.381 1845 1.097 1846 1.184 1847 1.149 1848 1.148 1849 1.437 1850 1.305 1851 1.217 1852 1.121 1853 0.924 1854 1.252 1855 1.213 1856 1.363 1857 1.137 1858 0.748 1859 0.938 1860 1.019 1861 0.844 1862 0.641 1863 0.47 1864 0.733 1865 0.467 1866 0.535 1867 0.514 1868 0.657 1869 0.807 1870 0.803 1871 0.807 1872 0.697 1873 0.684 1874 0.734 1875 0.687 1876 0.829 1877 0.945 1878 1.061 1879 1.004 1880 0.947 1881 0.784 1882 0.616 1883 0.716 1884 0.893 1885 0.883 1886 0.739 1887 0.716 1888 0.677 1889 0.751 1890 1.081 1891 1.07 1892 0.706 1893 1.176 1894 0.882 1895 0.696 1896 0.669 1897 0.737 1898 0.968 1899 0.767 1900 0.897 1901 1.06 1902 1.005 1903 0.431 1904 0.701 1905 0.928 1906 0.901 1907 1.175 1908 1.173 1909 1.041 1910 0.908 1911 1.232 1912 1.058 1913 1.306 1914 1.1 1915 1.285 1916 1.022 1917 1.072 1918 1.167 1919 1.038 1920 0.915 1921 0.924 1922 0.973 1923 0.954 1924 1.245 1925 1.263 1926 0.909 1927 1.144 1928 1.17 1929 0.922 1930 1.282 1931 1.178 1932 1.11 1933 0.901 1934 1.084 1935 1.112 1936 1.142 1937 1.213 1938 1.365 1939 1.289 1940 1.283 1941 0.868 1942 0.796 1943 0.909 1944 0.957 1945 0.961 1946 0.974 1947 0.724 1948 0.92 1949 1.131 1950 1.217 1951 1.284 1952 1.341 1953 1.046 1954 1.328 1955 1.101 1956 1.437 1957 1.423 1958 0.923 1959 0.983 1960 1.148 1961 1.208 1962 0.826 1963 0.92 1964 1.092 1965 1.036 1966 1.141 1967 1.155 1968 1.036 1969 0.542 1970 0.757 1971 0.733 1972 0.624 1973 0.576 1974 0.614 1975 0.481 1976 0.59 1977 0.759 1978 0.645 1979 0.589 1980 0.784 1981 0.896 1982 0.687 1983 0.752 1984 1.296 1985 0.973 1986 0.79 1987 0.766 1988 0.978 1989 0.949 1990 0.961