# asia_indi007 - Thijwas A - 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/3578 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_indi007 - Thijwas A - 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 A # Location: # Country: India # Northernmost_Latitude: 34.65 # Southernmost_Latitude: 34.65 # Easternmost_Longitude: 75.47 # Westernmost_Longitude: 75.47 # Elevation: 3200 m #-------------------- # Data_Collection # Collection_Name: asia_indi007B # Earliest_Year: 1805 # Most_Recent_Year: 1981 # 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":"2.45640434222","T2":"15.4754676721","M1":"0.0229017107851","M2":"0.496373137052"}} #-------------------- # 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 1805 0.908 1806 0.783 1807 0.966 1808 0.98 1809 0.996 1810 1.198 1811 1.051 1812 0.966 1813 1.107 1814 1.164 1815 1.095 1816 1.246 1817 0.934 1818 1.137 1819 1.118 1820 1.019 1821 0.733 1822 0.76 1823 0.678 1824 0.89 1825 0.806 1826 1.057 1827 0.78 1828 0.821 1829 0.91 1830 0.938 1831 0.844 1832 0.951 1833 0.737 1834 0.923 1835 0.747 1836 0.857 1837 0.813 1838 1.127 1839 1.069 1840 0.91 1841 0.81 1842 0.849 1843 0.826 1844 0.806 1845 0.648 1846 0.728 1847 0.635 1848 0.998 1849 1.015 1850 0.985 1851 1.015 1852 1.011 1853 1.092 1854 0.92 1855 0.957 1856 1.259 1857 1.539 1858 1.337 1859 1.207 1860 1.359 1861 1.015 1862 0.966 1863 1.034 1864 1.053 1865 1.042 1866 0.835 1867 0.933 1868 1.033 1869 1.027 1870 1.253 1871 1.201 1872 1.068 1873 1.146 1874 1.312 1875 1.262 1876 1.152 1877 0.993 1878 1.201 1879 1.017 1880 1.025 1881 0.965 1882 1.034 1883 0.874 1884 0.963 1885 0.672 1886 0.952 1887 0.908 1888 0.91 1889 1.041 1890 0.938 1891 1.085 1892 1.083 1893 1.292 1894 1.578 1895 1.015 1896 1.06 1897 0.755 1898 0.899 1899 0.727 1900 1.014 1901 1.081 1902 0.938 1903 1.108 1904 1.151 1905 0.837 1906 0.75 1907 0.875 1908 1.101 1909 1.0 1910 1.023 1911 0.732 1912 0.739 1913 0.887 1914 0.913 1915 0.647 1916 0.637 1917 0.66 1918 0.571 1919 0.821 1920 0.751 1921 1.319 1922 1.393 1923 1.153 1924 1.131 1925 0.839 1926 0.82 1927 0.828 1928 0.996 1929 1.185 1930 1.293 1931 1.236 1932 1.321 1933 1.286 1934 0.975 1935 1.033 1936 1.113 1937 0.792 1938 0.96 1939 0.969 1940 0.932 1941 0.904 1942 1.061 1943 1.072 1944 1.093 1945 1.325 1946 1.167 1947 1.054 1948 1.375 1949 1.34 1950 0.948 1951 1.204 1952 1.151 1953 1.048 1954 0.806 1955 0.642 1956 0.91 1957 0.697 1958 0.785 1959 0.814 1960 0.938 1961 1.047 1962 0.716 1963 0.757 1964 0.703 1965 0.766 1966 0.804 1967 0.734 1968 0.645 1969 0.937 1970 0.912 1971 0.865 1972 0.948 1973 1.093 1974 0.9 1975 0.797 1976 0.913 1977 0.88 1978 0.975 1979 0.865 1980 1.193 1981 1.239