# asia_indi004 - Sarbal - 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/3575 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_indi004 - Sarbal - 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: Sarbal # Location: # Country: India # Northernmost_Latitude: 34.5 # Southernmost_Latitude: 34.5 # Easternmost_Longitude: 75.75 # Westernmost_Longitude: 75.75 # Elevation: 3110 m #-------------------- # Data_Collection # Collection_Name: asia_indi004B # Earliest_Year: 1800 # 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":"3.53771663921","T2":"14.9636435665","M1":"0.0232560820896","M2":"0.502059356513"}} #-------------------- # 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 1800 1.0 1801 0.944 1802 0.722 1803 0.772 1804 0.845 1805 0.735 1806 0.694 1807 0.96 1808 0.968 1809 0.835 1810 0.988 1811 0.954 1812 0.845 1813 0.836 1814 1.215 1815 1.135 1816 1.289 1817 1.014 1818 1.196 1819 1.048 1820 1.203 1821 1.146 1822 1.115 1823 0.929 1824 0.836 1825 0.863 1826 0.877 1827 0.816 1828 0.863 1829 0.96 1830 1.059 1831 0.957 1832 1.036 1833 1.066 1834 1.004 1835 0.904 1836 1.112 1837 1.276 1838 1.206 1839 1.326 1840 1.355 1841 1.012 1842 1.174 1843 1.142 1844 1.089 1845 0.922 1846 0.943 1847 0.861 1848 1.054 1849 1.006 1850 1.003 1851 1.165 1852 0.951 1853 0.957 1854 1.031 1855 1.335 1856 1.514 1857 1.56 1858 1.433 1859 1.069 1860 1.131 1861 1.008 1862 0.932 1863 0.894 1864 0.978 1865 0.978 1866 0.806 1867 0.747 1868 0.741 1869 0.757 1870 1.017 1871 0.834 1872 0.762 1873 0.95 1874 1.013 1875 0.836 1876 0.956 1877 1.053 1878 1.047 1879 0.855 1880 0.904 1881 0.989 1882 0.977 1883 0.878 1884 0.854 1885 0.691 1886 0.839 1887 0.689 1888 0.755 1889 0.899 1890 0.895 1891 1.072 1892 1.21 1893 1.239 1894 1.483 1895 1.123 1896 1.177 1897 0.799 1898 0.982 1899 0.912 1900 1.152 1901 1.236 1902 1.081 1903 1.21 1904 1.324 1905 1.087 1906 0.958 1907 1.126 1908 0.988 1909 0.875 1910 0.783 1911 0.838 1912 0.84 1913 0.765 1914 0.907 1915 0.699 1916 0.654 1917 0.77 1918 0.798 1919 0.864 1920 0.927 1921 0.979 1922 1.083 1923 0.958 1924 0.796 1925 0.788 1926 0.894 1927 1.006 1928 1.062 1929 1.174 1930 1.264 1931 1.215 1932 1.261 1933 1.138 1934 0.984 1935 1.092 1936 0.974 1937 0.863 1938 0.863 1939 0.78 1940 0.795 1941 0.825 1942 0.901 1943 1.09 1944 1.179 1945 1.122 1946 0.949 1947 0.953 1948 1.149 1949 1.31 1950 1.06 1951 1.229 1952 0.96 1953 0.985 1954 1.021 1955 0.971 1956 1.006 1957 0.751 1958 1.121 1959 0.919 1960 0.892 1961 0.746 1962 0.61 1963 0.737 1964 0.702 1965 0.727 1966 0.804 1967 0.815 1968 0.78 1969 0.849 1970 0.972 1971 0.904 1972 0.821 1973 1.088 1974 0.952 1975 0.97 1976 1.013 1977 1.172 1978 1.404 1979 1.343 1980 1.479 1981 1.605