# asia_indi016 - Narkhanda - 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/2798 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_indi016 - Narkhanda - 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: Narkhanda # Location: # Country: India # Northernmost_Latitude: 31.2 # Southernmost_Latitude: 31.2 # Easternmost_Longitude: 77.23 # Westernmost_Longitude: 77.23 # Elevation: 3000 m #-------------------- # Data_Collection # Collection_Name: asia_indi016B # Earliest_Year: 1783 # 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":"3.86878395344","T2":"13.9892495714","M1":"0.0226272444656","M2":"0.321025162401"}} #-------------------- # Species # Species_Name: Himalayan spruce # Species_Code: PCSM #-------------------- # 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 1783 1.066 1784 1.074 1785 1.06 1786 1.122 1787 1.242 1788 1.127 1789 1.205 1790 0.867 1791 1.279 1792 1.105 1793 0.947 1794 1.015 1795 0.729 1796 0.71 1797 0.648 1798 1.105 1799 1.034 1800 0.785 1801 0.723 1802 0.892 1803 0.995 1804 0.899 1805 1.021 1806 1.047 1807 1.075 1808 1.116 1809 1.05 1810 1.025 1811 0.779 1812 0.707 1813 0.775 1814 0.871 1815 0.941 1816 0.457 1817 0.756 1818 0.916 1819 1.005 1820 0.973 1821 0.939 1822 1.132 1823 1.061 1824 1.066 1825 1.239 1826 1.219 1827 1.411 1828 1.282 1829 1.285 1830 1.174 1831 1.209 1832 1.107 1833 1.108 1834 1.004 1835 1.114 1836 1.148 1837 1.005 1838 1.04 1839 0.988 1840 1.126 1841 1.15 1842 1.083 1843 1.157 1844 1.337 1845 1.133 1846 1.337 1847 1.151 1848 1.099 1849 0.803 1850 0.748 1851 0.96 1852 1.104 1853 1.042 1854 1.062 1855 1.217 1856 1.007 1857 0.774 1858 0.878 1859 0.933 1860 0.948 1861 0.887 1862 0.947 1863 0.875 1864 0.872 1865 0.926 1866 1.165 1867 0.915 1868 0.924 1869 1.027 1870 0.807 1871 0.729 1872 0.836 1873 0.864 1874 0.591 1875 0.848 1876 0.548 1877 0.61 1878 0.822 1879 0.968 1880 0.641 1881 0.782 1882 1.08 1883 1.049 1884 1.064 1885 0.962 1886 0.632 1887 0.829 1888 0.538 1889 0.674 1890 0.887 1891 0.884 1892 0.483 1893 0.801 1894 0.854 1895 0.983 1896 0.973 1897 1.033 1898 0.825 1899 0.803 1900 0.807 1901 0.909 1902 0.879 1903 0.954 1904 0.888 1905 0.96 1906 0.965 1907 0.877 1908 0.559 1909 0.72 1910 0.662 1911 0.804 1912 0.918 1913 1.096 1914 1.284 1915 1.232 1916 1.05 1917 1.228 1918 1.313 1919 1.241 1920 1.028 1921 0.423 1922 0.661 1923 0.519 1924 0.7 1925 1.007 1926 0.917 1927 0.619 1928 0.836 1929 0.545 1930 0.752 1931 0.915 1932 0.587 1933 0.737 1934 0.732 1935 0.736 1936 0.859 1937 0.94 1938 1.0 1939 1.014 1940 0.857 1941 0.475 1942 0.624 1943 0.73 1944 1.036 1945 1.054 1946 1.111 1947 0.864 1948 0.992 1949 0.768 1950 0.997 1951 0.975 1952 0.943 1953 0.728 1954 0.681 1955 0.763 1956 0.802 1957 0.714 1958 1.157 1959 1.2 1960 1.303 1961 1.468 1962 1.533 1963 1.383 1964 1.619 1965 1.402 1966 1.067 1967 1.168 1968 0.892 1969 1.181 1970 0.946 1971 1.091 1972 1.232 1973 1.152 1974 1.112 1975 1.123 1976 1.07 1977 0.924 1978 1.174 1979 0.971 1980 1.089 1981 1.142 1982 1.081 1983 0.875 1984 0.939 1985 0.446 1986 1.17 1987 1.33 1988 1.405 1989 1.755