# asia_nepa041 - Tragdobuk - 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/3795 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa041 - Tragdobuk - 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: Tragdobuk # Location: # Country: Nepal # Northernmost_Latitude: 27.35 # Southernmost_Latitude: 27.35 # Easternmost_Longitude: 86.35 # Westernmost_Longitude: 86.35 # Elevation: 2950 m #-------------------- # Data_Collection # Collection_Name: asia_nepa041B # Earliest_Year: 1796 # Most_Recent_Year: 1994 # 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":"4.05212696878","T2":"14.5452738304","M1":"0.0224805614282","M2":"0.545540633718"}} #-------------------- # Species # Species_Name: East Himalayan hemlock # Species_Code: TSDU #-------------------- # 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 1796 1.565 1797 1.11 1798 1.328 1799 0.92 1800 0.899 1801 1.088 1802 0.941 1803 0.826 1804 0.869 1805 0.691 1806 0.861 1807 0.64 1808 0.859 1809 0.848 1810 1.209 1811 0.879 1812 0.828 1813 0.774 1814 0.825 1815 0.907 1816 1.282 1817 0.842 1818 0.767 1819 0.377 1820 0.484 1821 0.815 1822 1.148 1823 1.204 1824 1.35 1825 0.988 1826 1.169 1827 0.932 1828 0.616 1829 0.739 1830 1.201 1831 1.083 1832 1.289 1833 1.128 1834 0.656 1835 0.558 1836 0.389 1837 0.391 1838 0.488 1839 1.101 1840 1.45 1841 1.704 1842 1.176 1843 1.034 1844 0.959 1845 0.771 1846 0.934 1847 0.612 1848 1.085 1849 0.567 1850 0.726 1851 0.685 1852 0.957 1853 1.094 1854 0.587 1855 0.519 1856 0.963 1857 0.876 1858 0.638 1859 0.754 1860 0.574 1861 0.56 1862 0.882 1863 0.506 1864 0.589 1865 0.87 1866 0.473 1867 0.495 1868 0.656 1869 0.795 1870 0.938 1871 1.25 1872 1.052 1873 0.981 1874 0.421 1875 0.57 1876 0.636 1877 0.606 1878 0.888 1879 0.875 1880 0.856 1881 1.325 1882 1.472 1883 1.173 1884 0.894 1885 0.945 1886 1.036 1887 0.815 1888 0.858 1889 0.811 1890 1.119 1891 1.654 1892 1.502 1893 1.114 1894 2.127 1895 1.117 1896 1.297 1897 1.27 1898 1.125 1899 0.952 1900 1.762 1901 1.057 1902 1.329 1903 1.189 1904 1.251 1905 0.29 1906 0.315 1907 0.609 1908 1.023 1909 0.812 1910 1.308 1911 1.167 1912 1.312 1913 1.479 1914 1.439 1915 1.085 1916 0.574 1917 0.891 1918 1.155 1919 1.188 1920 0.794 1921 0.704 1922 1.087 1923 1.268 1924 1.551 1925 1.097 1926 1.429 1927 1.36 1928 1.485 1929 1.51 1930 1.616 1931 1.191 1932 1.007 1933 1.046 1934 1.363 1935 1.084 1936 1.449 1937 1.191 1938 0.801 1939 0.608 1940 0.645 1941 0.554 1942 0.806 1943 0.707 1944 0.79 1945 0.561 1946 0.768 1947 0.792 1948 0.825 1949 0.828 1950 1.378 1951 1.099 1952 1.309 1953 0.662 1954 0.473 1955 0.942 1956 0.857 1957 1.119 1958 0.657 1959 0.796 1960 0.961 1961 0.412 1962 0.312 1963 0.505 1964 0.664 1965 0.467 1966 0.603 1967 0.691 1968 0.85 1969 0.789 1970 0.674 1971 1.092 1972 1.667 1973 1.046 1974 0.824 1975 1.129 1976 1.062 1977 1.471 1978 0.786 1979 0.913 1980 1.013 1981 1.406 1982 1.168 1983 0.816 1984 0.402 1985 0.514 1986 0.733 1987 0.783 1988 0.654 1989 0.656 1990 1.22 1991 0.929 1992 1.057 1993 0.924 1994 1.011