# asia_indi008 - Pahalgam - 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/4084 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_indi008 - Pahalgam - 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: Pahalgam # Location: # Country: India # Northernmost_Latitude: 34.03 # Southernmost_Latitude: 34.03 # Easternmost_Longitude: 75.7 # Westernmost_Longitude: 75.7 # Elevation: 2900 m #-------------------- # Data_Collection # Collection_Name: asia_indi008B # Earliest_Year: 1676 # Most_Recent_Year: 1980 # 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":"7.14858239886","T2":"18.066749234","M1":"0.0223429206655","M2":"0.380039177141"}} #-------------------- # Species # Species_Name: Himalayan silver fir # Species_Code: ABPI #-------------------- # 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 1676 1.11 1677 1.045 1678 0.996 1679 1.177 1680 1.069 1681 1.109 1682 1.083 1683 1.034 1684 1.083 1685 1.111 1686 1.3 1687 1.118 1688 1.05 1689 1.102 1690 1.113 1691 1.126 1692 1.111 1693 0.957 1694 0.755 1695 0.959 1696 1.023 1697 0.909 1698 0.863 1699 0.875 1700 1.007 1701 1.013 1702 0.846 1703 1.005 1704 0.962 1705 0.812 1706 1.027 1707 0.873 1708 1.118 1709 1.061 1710 1.267 1711 1.091 1712 1.208 1713 1.283 1714 1.204 1715 1.02 1716 1.064 1717 0.762 1718 0.816 1719 0.844 1720 0.833 1721 0.738 1722 0.754 1723 0.642 1724 0.58 1725 0.626 1726 0.575 1727 0.505 1728 0.676 1729 0.635 1730 0.727 1731 0.732 1732 0.937 1733 0.982 1734 0.988 1735 1.08 1736 0.92 1737 0.822 1738 0.967 1739 1.083 1740 1.055 1741 0.991 1742 1.182 1743 0.911 1744 1.052 1745 1.064 1746 0.874 1747 1.041 1748 1.173 1749 0.724 1750 0.643 1751 0.814 1752 0.961 1753 0.961 1754 1.086 1755 0.959 1756 1.222 1757 1.117 1758 1.086 1759 1.294 1760 1.094 1761 1.172 1762 1.151 1763 1.208 1764 1.247 1765 1.179 1766 1.309 1767 1.17 1768 1.099 1769 1.202 1770 1.489 1771 1.291 1772 0.967 1773 1.128 1774 0.823 1775 0.99 1776 0.983 1777 0.913 1778 1.005 1779 0.931 1780 0.656 1781 0.79 1782 0.707 1783 0.809 1784 0.748 1785 0.473 1786 0.694 1787 0.768 1788 0.696 1789 0.857 1790 0.657 1791 0.713 1792 0.917 1793 0.719 1794 0.601 1795 0.522 1796 0.826 1797 0.823 1798 0.813 1799 0.898 1800 0.757 1801 0.883 1802 0.637 1803 0.655 1804 0.721 1805 0.878 1806 0.843 1807 0.813 1808 0.883 1809 0.859 1810 0.83 1811 0.721 1812 0.649 1813 0.677 1814 0.828 1815 0.792 1816 0.954 1817 0.873 1818 0.747 1819 0.706 1820 0.573 1821 0.602 1822 0.679 1823 0.648 1824 0.755 1825 0.912 1826 0.773 1827 0.703 1828 0.745 1829 0.629 1830 0.663 1831 0.664 1832 0.807 1833 0.731 1834 0.796 1835 0.992 1836 0.942 1837 0.964 1838 0.87 1839 0.81 1840 0.836 1841 0.932 1842 0.715 1843 0.681 1844 0.635 1845 0.715 1846 0.505 1847 0.628 1848 0.817 1849 0.715 1850 0.757 1851 0.772 1852 0.732 1853 0.718 1854 0.946 1855 0.909 1856 0.959 1857 0.929 1858 0.807 1859 1.023 1860 0.953 1861 0.911 1862 0.842 1863 0.817 1864 0.932 1865 0.837 1866 0.774 1867 0.879 1868 0.794 1869 0.726 1870 0.761 1871 0.769 1872 0.71 1873 0.807 1874 0.803 1875 0.783 1876 0.816 1877 0.926 1878 0.91 1879 0.931 1880 0.84 1881 0.925 1882 0.804 1883 0.717 1884 0.642 1885 0.814 1886 0.669 1887 0.63 1888 0.735 1889 0.796 1890 0.842 1891 0.871 1892 0.911 1893 0.894 1894 0.959 1895 0.738 1896 1.032 1897 1.062 1898 0.873 1899 0.826 1900 0.88 1901 0.906 1902 1.047 1903 1.254 1904 1.597 1905 1.414 1906 1.199 1907 1.085 1908 1.243 1909 1.254 1910 1.017 1911 0.949 1912 0.979 1913 1.008 1914 1.331 1915 1.031 1916 1.099 1917 1.246 1918 1.275 1919 1.318 1920 1.438 1921 1.302 1922 1.803 1923 1.738 1924 1.783 1925 1.373 1926 1.404 1927 1.764 1928 1.762 1929 1.47 1930 1.683 1931 1.487 1932 1.696 1933 1.125 1934 1.014 1935 0.84 1936 1.099 1937 1.025 1938 0.885 1939 0.898 1940 0.97 1941 1.187 1942 1.274 1943 1.6 1944 1.427 1945 1.425 1946 1.165 1947 0.968 1948 1.054 1949 1.068 1950 1.238 1951 1.438 1952 1.376 1953 1.157 1954 1.181 1955 1.145 1956 1.15 1957 1.114 1958 1.371 1959 1.266 1960 1.146 1961 1.085 1962 1.004 1963 1.314 1964 1.105 1965 1.153 1966 1.221 1967 1.275 1968 1.138 1969 1.024 1970 0.832 1971 0.955 1972 0.823 1973 1.087 1974 0.875 1975 0.842 1976 1.019 1977 1.133 1978 1.158 1979 1.096 1980 1.194