# asia_indi006 - Thijwas B - 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/3579 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_indi006 - Thijwas B - 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: Thijwas B # Location: # Country: India # Northernmost_Latitude: 34.58 # Southernmost_Latitude: 34.58 # Easternmost_Longitude: 75.53 # Westernmost_Longitude: 75.53 # Elevation: 3400 m #-------------------- # Data_Collection # Collection_Name: asia_indi006B # Earliest_Year: 1793 # Most_Recent_Year: 1981 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"3.8838799467","T2":"14.6655404026","M1":"0.0229783047365","M2":"0.523001304671"}} #-------------------- # 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 1793 0.988 1794 0.874 1795 0.879 1796 1.133 1797 1.01 1798 1.338 1799 1.334 1800 1.41 1801 1.237 1802 0.897 1803 1.08 1804 0.91 1805 0.945 1806 0.835 1807 0.901 1808 0.875 1809 0.8 1810 0.949 1811 0.852 1812 0.926 1813 1.064 1814 0.934 1815 0.912 1816 1.055 1817 0.962 1818 1.02 1819 0.943 1820 0.985 1821 0.851 1822 0.786 1823 0.904 1824 0.974 1825 0.881 1826 1.165 1827 1.048 1828 0.992 1829 1.2 1830 1.141 1831 0.948 1832 0.944 1833 0.676 1834 0.807 1835 0.891 1836 1.019 1837 1.065 1838 1.151 1839 1.035 1840 0.995 1841 1.021 1842 0.887 1843 0.983 1844 1.079 1845 1.036 1846 1.024 1847 0.841 1848 1.081 1849 1.029 1850 0.979 1851 1.09 1852 0.915 1853 0.97 1854 0.932 1855 1.106 1856 1.306 1857 1.373 1858 1.121 1859 0.98 1860 1.01 1861 0.931 1862 0.937 1863 0.777 1864 0.777 1865 0.799 1866 0.682 1867 0.708 1868 0.688 1869 0.793 1870 0.95 1871 0.832 1872 0.789 1873 0.965 1874 0.872 1875 1.002 1876 1.025 1877 0.879 1878 0.75 1879 0.772 1880 0.685 1881 0.754 1882 0.89 1883 0.878 1884 0.922 1885 0.841 1886 1.046 1887 0.854 1888 0.976 1889 0.963 1890 1.09 1891 1.081 1892 0.972 1893 1.687 1894 1.47 1895 1.242 1896 1.342 1897 1.01 1898 1.17 1899 0.946 1900 1.002 1901 1.113 1902 1.117 1903 1.265 1904 1.328 1905 1.221 1906 0.968 1907 1.037 1908 1.139 1909 1.161 1910 1.228 1911 1.045 1912 1.082 1913 1.143 1914 1.218 1915 0.868 1916 0.762 1917 0.862 1918 0.908 1919 1.118 1920 0.935 1921 1.076 1922 1.175 1923 1.154 1924 1.127 1925 1.117 1926 1.165 1927 0.954 1928 0.968 1929 0.984 1930 1.047 1931 1.144 1932 1.416 1933 1.074 1934 1.111 1935 0.889 1936 1.088 1937 0.885 1938 0.878 1939 0.86 1940 0.722 1941 0.858 1942 0.815 1943 0.945 1944 0.943 1945 0.955 1946 0.914 1947 0.775 1948 1.026 1949 1.115 1950 0.861 1951 1.151 1952 1.139 1953 1.025 1954 1.124 1955 0.897 1956 1.138 1957 1.006 1958 0.962 1959 0.978 1960 0.889 1961 0.82 1962 0.68 1963 0.822 1964 0.857 1965 0.974 1966 1.03 1967 0.974 1968 0.784 1969 0.799 1970 0.79 1971 0.682 1972 0.73 1973 1.082 1974 0.864 1975 0.84 1976 0.923 1977 1.047 1978 0.887 1979 0.996 1980 1.317 1981 1.407