# asia_russ167w - Sarma - 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/4628 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ167w - Sarma - 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: Sarma # Location: # Country: Russia # Northernmost_Latitude: 53.18 # Southernmost_Latitude: 53.18 # Easternmost_Longitude: 106.88 # Westernmost_Longitude: 106.88 # Elevation: 500 m #-------------------- # Data_Collection # Collection_Name: asia_russ167wB # Earliest_Year: 1766 # Most_Recent_Year: 1996 # 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":"7.26377059647","T2":"14.9285876749","M1":"0.0229766681047","M2":"0.527293705723"}} #-------------------- # 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 1766 0.211 1767 0.865 1768 0.74 1769 0.312 1770 0.071 1771 0.223 1772 0.807 1773 0.927 1774 1.63 1775 1.615 1776 1.002 1777 1.334 1778 1.246 1779 0.963 1780 0.962 1781 1.696 1782 1.863 1783 1.7 1784 1.917 1785 2.058 1786 2.063 1787 1.709 1788 0.658 1789 0.872 1790 1.682 1791 1.384 1792 1.159 1793 1.643 1794 0.59 1795 1.462 1796 1.306 1797 0.944 1798 1.175 1799 0.717 1800 1.553 1801 1.72 1802 1.813 1803 1.213 1804 0.614 1805 0.626 1806 1.508 1807 1.247 1808 1.782 1809 0.868 1810 1.489 1811 0.443 1812 1.57 1813 0.632 1814 0.9 1815 0.554 1816 1.606 1817 1.637 1818 0.52 1819 1.356 1820 1.829 1821 2.173 1822 1.84 1823 0.615 1824 1.12 1825 1.342 1826 2.043 1827 2.339 1828 1.933 1829 1.87 1830 1.708 1831 1.403 1832 1.287 1833 1.013 1834 0.697 1835 0.637 1836 0.579 1837 0.513 1838 0.158 1839 0.469 1840 0.2 1841 0.446 1842 0.768 1843 0.562 1844 0.469 1845 0.35 1846 0.938 1847 0.69 1848 0.988 1849 0.17 1850 0.063 1851 0.513 1852 0.853 1853 1.105 1854 1.719 1855 0.726 1856 1.089 1857 0.741 1858 0.652 1859 0.817 1860 0.78 1861 1.447 1862 0.769 1863 1.109 1864 1.316 1865 1.98 1866 1.284 1867 0.98 1868 0.924 1869 1.6 1870 1.291 1871 1.198 1872 1.113 1873 1.272 1874 1.196 1875 1.022 1876 1.032 1877 0.738 1878 0.743 1879 0.449 1880 0.22 1881 0.579 1882 0.916 1883 1.448 1884 1.058 1885 1.916 1886 1.411 1887 0.729 1888 0.574 1889 0.318 1890 1.172 1891 1.655 1892 0.886 1893 0.396 1894 0.506 1895 0.658 1896 0.214 1897 0.209 1898 0.095 1899 0.68 1900 0.638 1901 0.578 1902 0.902 1903 0.411 1904 0.813 1905 0.425 1906 0.71 1907 1.282 1908 0.741 1909 0.907 1910 0.394 1911 0.997 1912 1.086 1913 0.631 1914 1.178 1915 1.546 1916 0.821 1917 0.36 1918 1.549 1919 1.242 1920 1.486 1921 1.293 1922 1.254 1923 0.861 1924 0.872 1925 1.244 1926 0.467 1927 1.575 1928 1.33 1929 0.469 1930 1.206 1931 1.375 1932 1.482 1933 1.916 1934 1.077 1935 1.922 1936 1.543 1937 1.164 1938 1.843 1939 1.91 1940 1.78 1941 0.67 1942 1.298 1943 0.81 1944 0.484 1945 0.809 1946 1.381 1947 1.067 1948 1.551 1949 2.037 1950 0.558 1951 1.102 1952 0.969 1953 0.724 1954 0.758 1955 0.48 1956 0.253 1957 0.174 1958 0.676 1959 0.832 1960 0.857 1961 0.704 1962 1.094 1963 0.813 1964 1.341 1965 0.655 1966 1.07 1967 0.979 1968 1.251 1969 0.548 1970 0.513 1971 0.554 1972 0.796 1973 0.484 1974 0.732 1975 0.885 1976 1.223 1977 0.473 1978 0.27 1979 0.296 1980 0.546 1981 0.016 1982 0.677 1983 0.834 1984 1.193 1985 1.494 1986 1.456 1987 0.634 1988 1.259 1989 1.292 1990 0.938 1991 2.146 1992 1.354 1993 1.042 1994 0.643 1995 1.522 1996 1.136