# asia_nepa023 - KatyaKhola-2 - 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/3781 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa023 - KatyaKhola-2 - 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: KatyaKhola-2 # Location: # Country: Nepal # Northernmost_Latitude: 29.3 # Southernmost_Latitude: 29.3 # Easternmost_Longitude: 82.02 # Westernmost_Longitude: 82.02 # Elevation: 3330 m #-------------------- # Data_Collection # Collection_Name: asia_nepa023B # Earliest_Year: 1656 # Most_Recent_Year: 1997 # 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":"3.99329911899","T2":"12.3095612365","M1":"0.0234088294428","M2":"0.589123723462"}} #-------------------- # Species # Species_Name: silver fir # Species_Code: ABSB #-------------------- # 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 1656 0.945 1657 0.955 1658 0.978 1659 0.936 1660 0.843 1661 0.917 1662 0.892 1663 0.818 1664 0.981 1665 0.921 1666 0.959 1667 0.978 1668 0.823 1669 1.032 1670 1.089 1671 1.055 1672 0.974 1673 1.041 1674 0.77 1675 0.606 1676 0.822 1677 0.824 1678 1.053 1679 1.195 1680 1.151 1681 1.278 1682 1.29 1683 1.033 1684 0.917 1685 1.096 1686 1.005 1687 1.161 1688 1.115 1689 1.101 1690 1.405 1691 1.202 1692 1.022 1693 0.959 1694 0.745 1695 1.038 1696 0.93 1697 0.929 1698 0.936 1699 0.96 1700 0.766 1701 0.769 1702 0.732 1703 0.827 1704 0.95 1705 0.786 1706 0.653 1707 0.692 1708 1.054 1709 1.253 1710 1.134 1711 1.044 1712 0.801 1713 0.721 1714 0.705 1715 0.685 1716 0.98 1717 0.762 1718 0.713 1719 0.848 1720 0.755 1721 0.811 1722 0.769 1723 0.716 1724 0.979 1725 1.168 1726 1.065 1727 1.087 1728 1.016 1729 0.925 1730 1.131 1731 1.156 1732 1.121 1733 1.297 1734 1.272 1735 0.999 1736 0.965 1737 0.971 1738 1.01 1739 1.02 1740 0.95 1741 0.659 1742 0.858 1743 0.853 1744 0.91 1745 0.732 1746 1.015 1747 0.96 1748 1.12 1749 0.917 1750 0.881 1751 1.185 1752 1.186 1753 1.181 1754 1.162 1755 0.835 1756 0.801 1757 0.761 1758 0.892 1759 1.198 1760 0.774 1761 0.888 1762 0.705 1763 0.781 1764 0.863 1765 0.769 1766 0.742 1767 0.651 1768 0.565 1769 0.675 1770 0.731 1771 0.925 1772 0.859 1773 0.875 1774 0.729 1775 0.706 1776 0.872 1777 0.961 1778 0.932 1779 0.992 1780 0.873 1781 0.741 1782 0.766 1783 0.871 1784 1.058 1785 1.196 1786 1.208 1787 1.224 1788 1.219 1789 0.956 1790 0.926 1791 1.05 1792 0.943 1793 0.631 1794 0.644 1795 0.674 1796 0.871 1797 1.121 1798 1.228 1799 0.837 1800 1.032 1801 0.935 1802 0.961 1803 1.289 1804 0.996 1805 0.969 1806 1.072 1807 1.209 1808 1.269 1809 1.093 1810 1.017 1811 0.989 1812 0.935 1813 0.817 1814 0.972 1815 0.733 1816 0.867 1817 0.887 1818 0.943 1819 0.927 1820 1.059 1821 0.803 1822 0.809 1823 0.758 1824 0.861 1825 1.099 1826 1.131 1827 1.372 1828 1.218 1829 1.117 1830 0.957 1831 0.916 1832 1.113 1833 0.981 1834 0.852 1835 0.836 1836 0.714 1837 0.764 1838 0.835 1839 1.02 1840 1.257 1841 1.246 1842 0.957 1843 0.947 1844 0.926 1845 1.122 1846 1.19 1847 1.219 1848 1.331 1849 1.171 1850 1.239 1851 1.179 1852 1.183 1853 1.135 1854 1.412 1855 1.345 1856 1.476 1857 1.542 1858 1.361 1859 1.198 1860 1.1 1861 1.263 1862 1.229 1863 1.224 1864 1.065 1865 0.969 1866 0.855 1867 0.813 1868 0.916 1869 0.909 1870 0.935 1871 1.061 1872 0.877 1873 0.8 1874 0.801 1875 0.802 1876 0.96 1877 0.964 1878 1.079 1879 1.039 1880 0.998 1881 1.206 1882 1.278 1883 1.312 1884 1.065 1885 1.051 1886 1.507 1887 1.036 1888 0.999 1889 1.03 1890 1.109 1891 1.17 1892 0.753 1893 1.064 1894 1.12 1895 0.876 1896 1.13 1897 1.102 1898 0.84 1899 0.983 1900 1.256 1901 1.073 1902 1.065 1903 1.029 1904 0.895 1905 0.878 1906 0.857 1907 0.834 1908 0.841 1909 0.821 1910 0.894 1911 1.112 1912 0.99 1913 0.913 1914 1.027 1915 1.172 1916 1.147 1917 1.337 1918 1.219 1919 1.249 1920 1.303 1921 0.806 1922 0.767 1923 0.811 1924 0.946 1925 0.848 1926 0.897 1927 0.771 1928 0.758 1929 0.872 1930 1.014 1931 0.887 1932 0.657 1933 0.88 1934 0.963 1935 0.611 1936 0.774 1937 0.791 1938 0.945 1939 0.733 1940 0.909 1941 0.794 1942 0.902 1943 1.03 1944 0.725 1945 0.692 1946 0.871 1947 1.116 1948 0.891 1949 0.794 1950 0.838 1951 0.936 1952 0.885 1953 0.729 1954 0.59 1955 0.584 1956 0.79 1957 0.856 1958 0.683 1959 0.709 1960 0.813 1961 0.881 1962 0.566 1963 0.811 1964 0.96 1965 0.873 1966 0.87 1967 0.693 1968 0.55 1969 0.736 1970 0.618 1971 0.735 1972 0.813 1973 0.994 1974 0.906 1975 1.072 1976 1.27 1977 1.39 1978 1.009 1979 0.932 1980 0.799 1981 0.714 1982 0.949 1983 0.95 1984 0.89 1985 0.835 1986 1.04 1987 1.086 1988 1.123 1989 0.967 1990 1.151 1991 1.298 1992 1.023 1993 1.173 1994 1.047 1995 0.783 1996 0.913 1997 0.985