# asia_indi014 - 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/2797 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_indi014 - 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_indi014B # Earliest_Year: 1778 # Most_Recent_Year: 1988 # 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":"3.27038779537","T2":"15.6139770495","M1":"0.0227755732004","M2":"0.475161515496"}} #-------------------- # 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 1778 1.13 1779 0.808 1780 1.023 1781 0.994 1782 0.835 1783 1.122 1784 0.783 1785 1.06 1786 0.706 1787 0.735 1788 0.912 1789 0.725 1790 0.894 1791 1.007 1792 0.937 1793 0.91 1794 1.085 1795 1.033 1796 0.984 1797 0.789 1798 0.781 1799 0.636 1800 0.575 1801 0.692 1802 0.669 1803 0.97 1804 1.18 1805 1.061 1806 1.172 1807 1.243 1808 1.238 1809 1.195 1810 1.209 1811 1.172 1812 1.1 1813 0.852 1814 0.897 1815 1.008 1816 1.066 1817 0.938 1818 1.307 1819 1.128 1820 0.901 1821 0.989 1822 0.747 1823 1.061 1824 0.916 1825 0.91 1826 1.031 1827 0.839 1828 1.097 1829 0.903 1830 0.922 1831 0.996 1832 0.793 1833 1.021 1834 0.77 1835 0.996 1836 1.126 1837 1.216 1838 0.941 1839 0.765 1840 1.119 1841 0.698 1842 1.006 1843 0.781 1844 0.798 1845 1.104 1846 1.033 1847 1.071 1848 0.78 1849 1.079 1850 0.437 1851 0.61 1852 1.118 1853 1.307 1854 1.284 1855 1.089 1856 0.884 1857 0.843 1858 0.9 1859 1.018 1860 1.234 1861 1.039 1862 0.906 1863 1.055 1864 0.784 1865 0.817 1866 0.866 1867 0.858 1868 0.703 1869 0.834 1870 0.359 1871 0.635 1872 0.741 1873 0.717 1874 0.411 1875 0.753 1876 0.714 1877 0.882 1878 1.069 1879 1.375 1880 0.656 1881 0.844 1882 0.956 1883 0.833 1884 0.848 1885 0.805 1886 0.907 1887 0.915 1888 0.636 1889 0.631 1890 0.624 1891 0.693 1892 0.334 1893 0.857 1894 0.751 1895 0.812 1896 0.829 1897 0.671 1898 0.58 1899 0.665 1900 0.688 1901 0.684 1902 0.717 1903 0.646 1904 0.614 1905 0.64 1906 0.744 1907 0.83 1908 1.211 1909 1.231 1910 1.127 1911 1.156 1912 1.223 1913 1.241 1914 1.399 1915 1.297 1916 1.191 1917 1.419 1918 1.351 1919 1.306 1920 1.044 1921 0.406 1922 0.868 1923 1.219 1924 1.386 1925 1.537 1926 1.7 1927 1.423 1928 1.228 1929 0.948 1930 1.301 1931 1.174 1932 1.021 1933 1.359 1934 1.276 1935 1.184 1936 1.527 1937 1.11 1938 1.167 1939 1.098 1940 1.143 1941 0.663 1942 1.183 1943 1.22 1944 1.405 1945 1.335 1946 1.496 1947 1.122 1948 1.106 1949 1.23 1950 1.037 1951 1.084 1952 0.997 1953 0.939 1954 0.731 1955 1.073 1956 0.914 1957 1.211 1958 0.862 1959 0.649 1960 0.843 1961 0.932 1962 0.931 1963 1.002 1964 1.08 1965 1.259 1966 0.935 1967 0.902 1968 1.1 1969 0.986 1970 0.509 1971 0.734 1972 0.69 1973 0.796 1974 0.444 1975 0.696 1976 0.802 1977 0.697 1978 0.537 1979 0.785 1980 0.479 1981 0.825 1982 1.227 1983 1.233 1984 0.574 1985 0.413 1986 0.934 1987 0.979 1988 0.603