# asia_indi021 - Jageswar - 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/2792 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_indi021 - Jageswar - 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: Jageswar # Location: # Country: India # Northernmost_Latitude: 29.77 # Southernmost_Latitude: 29.77 # Easternmost_Longitude: 79.17 # Westernmost_Longitude: 79.17 # Elevation: 2000 m #-------------------- # Data_Collection # Collection_Name: asia_indi021B # Earliest_Year: 1767 # Most_Recent_Year: 1989 # 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":"4.56974770897","T2":"17.968052545","M1":"0.0223171464321","M2":"0.467452946436"}} #-------------------- # Species # Species_Name: deodar cedar # Species_Code: CDDE #-------------------- # 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 1767 0.835 1768 0.701 1769 0.983 1770 1.031 1771 1.052 1772 1.094 1773 1.342 1774 0.835 1775 1.322 1776 1.193 1777 0.815 1778 1.12 1779 0.724 1780 0.669 1781 0.739 1782 0.458 1783 0.708 1784 0.514 1785 0.692 1786 0.959 1787 0.82 1788 0.975 1789 0.884 1790 0.765 1791 1.054 1792 0.964 1793 0.914 1794 0.994 1795 0.79 1796 1.056 1797 0.778 1798 1.212 1799 1.164 1800 1.247 1801 1.089 1802 0.967 1803 1.011 1804 0.794 1805 0.737 1806 1.123 1807 0.995 1808 1.186 1809 0.646 1810 0.787 1811 0.943 1812 0.898 1813 0.593 1814 1.041 1815 0.955 1816 0.461 1817 0.923 1818 0.927 1819 0.95 1820 0.786 1821 0.71 1822 1.132 1823 0.807 1824 1.204 1825 1.304 1826 1.215 1827 1.32 1828 0.949 1829 1.159 1830 1.189 1831 0.91 1832 1.138 1833 0.911 1834 1.209 1835 1.16 1836 1.125 1837 0.845 1838 0.94 1839 1.175 1840 0.841 1841 1.057 1842 1.076 1843 0.921 1844 0.798 1845 1.088 1846 0.592 1847 0.694 1848 0.634 1849 0.746 1850 1.09 1851 0.905 1852 1.324 1853 1.105 1854 1.058 1855 0.971 1856 0.96 1857 0.849 1858 1.192 1859 1.604 1860 0.731 1861 1.292 1862 1.2 1863 1.152 1864 1.029 1865 1.206 1866 0.62 1867 0.911 1868 1.338 1869 0.587 1870 0.931 1871 1.012 1872 0.901 1873 0.574 1874 0.731 1875 0.894 1876 0.324 1877 0.709 1878 0.675 1879 0.286 1880 0.619 1881 0.722 1882 0.768 1883 0.704 1884 0.469 1885 0.735 1886 0.97 1887 0.597 1888 0.556 1889 0.808 1890 0.396 1891 0.841 1892 0.209 1893 1.146 1894 0.758 1895 1.072 1896 0.523 1897 0.567 1898 0.616 1899 0.625 1900 0.715 1901 0.512 1902 0.527 1903 0.49 1904 0.531 1905 0.719 1906 0.653 1907 0.733 1908 0.373 1909 0.57 1910 0.456 1911 0.592 1912 0.814 1913 1.004 1914 1.226 1915 1.081 1916 0.86 1917 1.019 1918 0.664 1919 0.823 1920 0.816 1921 0.282 1922 0.529 1923 0.565 1924 0.637 1925 0.892 1926 0.947 1927 1.133 1928 1.156 1929 0.627 1930 0.837 1931 0.345 1932 0.664 1933 1.343 1934 0.586 1935 0.554 1936 1.165 1937 1.207 1938 0.963 1939 0.798 1940 1.16 1941 0.603 1942 0.769 1943 0.789 1944 0.836 1945 0.605 1946 1.097 1947 0.586 1948 0.651 1949 1.303 1950 0.938 1951 0.886 1952 0.978 1953 0.689 1954 1.26 1955 1.133 1956 1.121 1957 1.549 1958 0.999 1959 1.419 1960 1.343 1961 1.36 1962 1.32 1963 1.501 1964 0.8 1965 0.921 1966 0.397 1967 0.476 1968 0.987 1969 0.963 1970 1.051 1971 1.603 1972 0.758 1973 1.337 1974 0.825 1975 1.364 1976 1.656 1977 1.793 1978 1.696 1979 2.213 1980 1.326 1981 1.574 1982 1.553 1983 1.584 1984 1.374 1985 0.857 1986 1.599 1987 1.543 1988 1.49 1989 0.84