# asia_nepa020 - GhurchiLehk - 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/3777 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa020 - GhurchiLehk - 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: GhurchiLehk # Location: # Country: Nepal # Northernmost_Latitude: 29.3 # Southernmost_Latitude: 29.3 # Easternmost_Longitude: 82.05 # Westernmost_Longitude: 82.05 # Elevation: 3450 m #-------------------- # Data_Collection # Collection_Name: asia_nepa020B # Earliest_Year: 1755 # Most_Recent_Year: 1979 # 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":"4.83729422414","T2":"17.5697224744","M1":"0.0226170115485","M2":"0.380637151671"}} #-------------------- # Species # Species_Name: silver fir # Species_Code: ABSB #-------------------- # 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 1755 0.837 1756 0.793 1757 0.738 1758 0.837 1759 1.081 1760 0.963 1761 0.925 1762 0.855 1763 1.027 1764 0.914 1765 0.946 1766 1.066 1767 1.049 1768 0.927 1769 0.945 1770 0.87 1771 1.032 1772 0.837 1773 0.865 1774 0.85 1775 0.779 1776 0.801 1777 0.838 1778 0.937 1779 0.901 1780 0.811 1781 0.848 1782 0.972 1783 1.07 1784 1.203 1785 1.156 1786 1.167 1787 1.031 1788 1.041 1789 1.002 1790 0.848 1791 0.885 1792 1.118 1793 0.922 1794 1.028 1795 0.765 1796 0.774 1797 1.044 1798 1.125 1799 0.924 1800 0.747 1801 0.755 1802 0.877 1803 1.094 1804 0.947 1805 0.888 1806 0.932 1807 0.878 1808 0.879 1809 1.117 1810 1.009 1811 0.842 1812 0.886 1813 0.83 1814 0.915 1815 0.764 1816 0.738 1817 0.581 1818 0.646 1819 0.682 1820 0.758 1821 0.749 1822 0.662 1823 0.676 1824 0.825 1825 0.909 1826 1.161 1827 1.146 1828 1.023 1829 1.106 1830 1.002 1831 0.992 1832 1.049 1833 1.024 1834 0.875 1835 0.864 1836 0.844 1837 0.872 1838 0.883 1839 0.898 1840 1.136 1841 1.12 1842 1.073 1843 1.055 1844 1.071 1845 1.277 1846 1.383 1847 1.537 1848 1.564 1849 1.425 1850 1.376 1851 1.35 1852 1.211 1853 1.212 1854 1.239 1855 1.274 1856 1.451 1857 1.474 1858 1.386 1859 1.078 1860 1.157 1861 1.179 1862 1.055 1863 1.234 1864 1.114 1865 1.113 1866 1.037 1867 1.019 1868 0.965 1869 0.921 1870 0.865 1871 0.899 1872 0.911 1873 1.06 1874 0.986 1875 1.037 1876 1.151 1877 0.965 1878 0.997 1879 1.013 1880 1.109 1881 1.353 1882 1.265 1883 1.269 1884 1.097 1885 1.113 1886 1.294 1887 1.049 1888 1.031 1889 1.065 1890 1.018 1891 0.978 1892 0.856 1893 0.895 1894 0.951 1895 0.831 1896 1.277 1897 1.212 1898 1.084 1899 1.012 1900 1.118 1901 0.97 1902 1.009 1903 1.039 1904 0.829 1905 0.805 1906 0.946 1907 1.003 1908 1.065 1909 0.958 1910 0.935 1911 1.105 1912 1.064 1913 1.018 1914 1.039 1915 0.965 1916 1.076 1917 1.145 1918 0.944 1919 1.04 1920 1.118 1921 0.933 1922 0.848 1923 0.837 1924 0.944 1925 0.803 1926 0.788 1927 0.711 1928 0.678 1929 0.683 1930 0.749 1931 0.804 1932 0.709 1933 0.803 1934 0.932 1935 0.755 1936 0.769 1937 0.765 1938 0.882 1939 0.874 1940 0.904 1941 0.857 1942 0.988 1943 0.917 1944 0.843 1945 0.888 1946 0.87 1947 1.118 1948 0.905 1949 0.743 1950 0.726 1951 0.798 1952 0.835 1953 0.818 1954 0.756 1955 0.759 1956 0.926 1957 1.044 1958 1.126 1959 0.944 1960 0.94 1961 0.951 1962 0.792 1963 0.851 1964 1.036 1965 0.851 1966 0.998 1967 0.811 1968 0.725 1969 0.911 1970 0.892 1971 0.972 1972 1.128 1973 1.1 1974 0.933 1975 0.973 1976 1.137 1977 1.319 1978 1.17 1979 1.217