# asia_nepa038 - Banal-Salme - 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/3761 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa038 - Banal-Salme - 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: Banal-Salme # Location: # Country: Nepal # Northernmost_Latitude: 28.03 # Southernmost_Latitude: 28.03 # Easternmost_Longitude: 85.07 # Westernmost_Longitude: 85.07 # Elevation: 3115 m #-------------------- # Data_Collection # Collection_Name: asia_nepa038B # Earliest_Year: 1769 # Most_Recent_Year: 1996 # 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":"6.19332698012","T2":"17.3485561476","M1":"0.0220320245373","M2":"0.391545895493"}} #-------------------- # 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 1769 0.879 1770 0.8 1771 0.929 1772 1.059 1773 0.967 1774 0.899 1775 0.958 1776 0.945 1777 0.958 1778 0.99 1779 0.902 1780 0.83 1781 0.901 1782 1.02 1783 0.907 1784 0.998 1785 1.087 1786 1.186 1787 1.088 1788 1.128 1789 1.064 1790 0.928 1791 0.951 1792 1.008 1793 0.99 1794 1.202 1795 1.322 1796 1.575 1797 1.272 1798 1.159 1799 1.335 1800 1.386 1801 1.244 1802 1.386 1803 1.102 1804 0.93 1805 0.81 1806 0.846 1807 0.783 1808 0.844 1809 0.826 1810 0.911 1811 0.864 1812 0.873 1813 0.771 1814 0.784 1815 0.88 1816 0.957 1817 0.916 1818 0.709 1819 0.627 1820 0.831 1821 0.907 1822 0.811 1823 0.747 1824 1.094 1825 1.023 1826 1.148 1827 1.262 1828 1.002 1829 0.848 1830 0.937 1831 0.945 1832 1.053 1833 0.982 1834 0.686 1835 0.811 1836 1.012 1837 0.976 1838 0.642 1839 0.446 1840 0.698 1841 0.837 1842 0.829 1843 0.681 1844 0.773 1845 0.992 1846 0.665 1847 0.734 1848 1.036 1849 0.776 1850 0.872 1851 1.013 1852 0.751 1853 0.926 1854 0.895 1855 1.117 1856 1.244 1857 1.436 1858 1.138 1859 0.817 1860 0.974 1861 1.225 1862 1.474 1863 1.501 1864 1.051 1865 1.04 1866 0.903 1867 0.92 1868 0.892 1869 0.845 1870 0.712 1871 0.857 1872 0.89 1873 0.944 1874 0.688 1875 0.615 1876 0.811 1877 0.873 1878 1.271 1879 0.782 1880 0.743 1881 1.074 1882 1.002 1883 1.08 1884 1.026 1885 1.115 1886 0.917 1887 0.785 1888 1.15 1889 1.277 1890 0.751 1891 1.028 1892 1.173 1893 0.853 1894 0.875 1895 0.939 1896 1.076 1897 0.634 1898 0.797 1899 0.992 1900 1.403 1901 1.002 1902 1.3 1903 1.27 1904 1.315 1905 1.347 1906 1.086 1907 0.964 1908 1.393 1909 1.011 1910 1.198 1911 1.424 1912 1.139 1913 1.007 1914 1.005 1915 0.983 1916 1.103 1917 1.263 1918 1.248 1919 1.098 1920 0.967 1921 0.914 1922 0.914 1923 1.04 1924 1.186 1925 0.946 1926 0.791 1927 1.022 1928 0.872 1929 0.83 1930 1.145 1931 0.919 1932 0.656 1933 0.851 1934 1.051 1935 0.794 1936 0.688 1937 0.854 1938 0.626 1939 0.565 1940 0.577 1941 0.623 1942 0.746 1943 0.942 1944 0.855 1945 1.165 1946 0.814 1947 0.871 1948 0.886 1949 0.737 1950 0.779 1951 1.0 1952 0.801 1953 0.709 1954 1.13 1955 0.874 1956 0.901 1957 1.162 1958 1.159 1959 0.796 1960 0.695 1961 0.662 1962 0.755 1963 0.97 1964 1.015 1965 0.722 1966 1.011 1967 0.991 1968 1.042 1969 1.368 1970 0.907 1971 0.923 1972 1.335 1973 0.911 1974 0.418 1975 1.131 1976 1.495 1977 1.894 1978 1.153 1979 1.366 1980 1.131 1981 1.179 1982 1.347 1983 1.265 1984 1.093 1985 1.116 1986 1.126 1987 1.138 1988 0.968 1989 0.729 1990 0.79 1991 0.943 1992 0.684 1993 0.876 1994 0.925 1995 0.609 1996 0.74