# asia_mong005 - Urgun Nars - 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/3617 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_mong005 - Urgun Nars - 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: Urgun Nars # Location: # Country: Mongolia # Northernmost_Latitude: 48.57 # Southernmost_Latitude: 48.57 # Easternmost_Longitude: 110.55 # Westernmost_Longitude: 110.55 # Elevation: 1070 m #-------------------- # Data_Collection # Collection_Name: asia_mong005B # Earliest_Year: 1668 # 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":"3.27380225987","T2":"15.5929535914","M1":"0.0228345043809","M2":"0.532606380824"}} #-------------------- # 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 1668 0.893 1669 1.196 1670 0.765 1671 1.364 1672 0.893 1673 0.692 1674 1.264 1675 1.344 1676 0.42 1677 1.083 1678 1.237 1679 1.332 1680 0.995 1681 1.647 1682 0.964 1683 0.516 1684 1.157 1685 0.913 1686 0.643 1687 1.422 1688 1.014 1689 1.007 1690 1.549 1691 1.559 1692 0.645 1693 0.321 1694 0.87 1695 0.64 1696 0.419 1697 0.857 1698 0.309 1699 0.861 1700 0.802 1701 0.641 1702 1.253 1703 1.479 1704 1.109 1705 1.919 1706 1.454 1707 0.812 1708 0.591 1709 1.074 1710 0.956 1711 1.357 1712 1.046 1713 1.145 1714 0.784 1715 0.968 1716 1.106 1717 1.005 1718 1.31 1719 1.304 1720 1.885 1721 1.539 1722 0.963 1723 0.626 1724 1.343 1725 0.637 1726 0.249 1727 0.701 1728 0.697 1729 0.677 1730 0.856 1731 0.417 1732 0.314 1733 0.976 1734 0.714 1735 0.816 1736 0.654 1737 0.846 1738 0.666 1739 0.743 1740 1.549 1741 1.878 1742 1.903 1743 1.943 1744 2.032 1745 0.845 1746 1.208 1747 0.505 1748 0.763 1749 1.304 1750 1.271 1751 1.305 1752 1.48 1753 1.458 1754 1.24 1755 2.115 1756 1.851 1757 1.184 1758 0.27 1759 0.654 1760 0.926 1761 0.865 1762 0.947 1763 1.199 1764 0.955 1765 1.464 1766 0.962 1767 0.677 1768 0.864 1769 1.065 1770 1.238 1771 0.328 1772 0.481 1773 0.781 1774 0.967 1775 0.858 1776 1.357 1777 1.159 1778 1.038 1779 1.218 1780 0.633 1781 0.355 1782 1.004 1783 0.92 1784 0.776 1785 1.519 1786 0.654 1787 1.407 1788 1.359 1789 1.3 1790 1.021 1791 0.513 1792 0.738 1793 0.484 1794 0.442 1795 0.654 1796 0.906 1797 0.692 1798 0.878 1799 0.819 1800 1.03 1801 0.63 1802 0.092 1803 0.846 1804 0.916 1805 0.844 1806 1.234 1807 0.788 1808 0.433 1809 1.098 1810 1.186 1811 0.659 1812 1.509 1813 1.226 1814 1.665 1815 0.546 1816 0.947 1817 1.25 1818 0.418 1819 0.967 1820 0.743 1821 0.535 1822 0.955 1823 0.553 1824 1.069 1825 1.081 1826 1.349 1827 1.291 1828 1.026 1829 1.588 1830 1.503 1831 0.985 1832 1.121 1833 1.068 1834 0.827 1835 0.534 1836 0.914 1837 1.453 1838 1.134 1839 0.886 1840 0.982 1841 0.618 1842 0.425 1843 1.058 1844 1.029 1845 0.464 1846 1.408 1847 1.292 1848 1.007 1849 0.697 1850 0.755 1851 0.791 1852 0.857 1853 0.745 1854 0.905 1855 1.261 1856 1.053 1857 1.441 1858 1.325 1859 0.933 1860 0.928 1861 1.032 1862 0.675 1863 0.94 1864 1.146 1865 0.864 1866 0.974 1867 0.936 1868 0.669 1869 1.296 1870 1.105 1871 0.901 1872 1.098 1873 0.832 1874 1.104 1875 0.697 1876 0.735 1877 0.898 1878 0.604 1879 0.729 1880 0.875 1881 1.195 1882 0.778 1883 0.946 1884 0.563 1885 0.533 1886 1.103 1887 1.267 1888 0.95 1889 1.101 1890 1.418 1891 0.975 1892 0.604 1893 1.211 1894 0.98 1895 1.4 1896 1.063 1897 1.483 1898 0.937 1899 0.659 1900 0.92 1901 1.196 1902 1.114 1903 0.742 1904 0.794 1905 0.604 1906 1.07 1907 0.935 1908 1.437 1909 1.285 1910 1.55 1911 1.373 1912 1.377 1913 1.007 1914 1.018 1915 1.204 1916 1.179 1917 1.398 1918 1.026 1919 1.694 1920 1.35 1921 1.306 1922 1.007 1923 1.061 1924 1.17 1925 0.201 1926 0.797 1927 0.957 1928 0.479 1929 0.414 1930 0.614 1931 0.61 1932 0.628 1933 1.138 1934 1.266 1935 1.139 1936 1.405 1937 1.45 1938 1.4 1939 1.225 1940 0.693 1941 0.931 1942 0.883 1943 0.597 1944 0.172 1945 0.871 1946 0.808 1947 0.348 1948 1.205 1949 0.866 1950 0.667 1951 0.912 1952 0.854 1953 1.258 1954 0.794 1955 0.976 1956 1.179 1957 1.158 1958 1.098 1959 1.544 1960 1.748 1961 0.62 1962 1.147 1963 1.485 1964 1.354 1965 1.005 1966 0.497 1967 1.164 1968 0.811 1969 0.854 1970 1.175 1971 1.316 1972 0.503 1973 0.955 1974 0.989 1975 1.224 1976 1.054 1977 1.267 1978 0.455 1979 0.57 1980 0.888 1981 0.293 1982 0.7 1983 0.688 1984 0.861 1985 1.246 1986 0.819 1987 0.694 1988 1.511 1989 1.273 1990 0.8 1991 1.387 1992 0.66 1993 1.103 1994 1.228 1995 1.143 1996 0.707