# asia_nepa017 - Dobini Danda - 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/3774 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa017 - Dobini Danda - 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: Dobini Danda # Location: # Country: Nepal # Northernmost_Latitude: 27.43 # Southernmost_Latitude: 27.43 # Easternmost_Longitude: 86.2 # Westernmost_Longitude: 86.2 # Elevation: 3500 m #-------------------- # Data_Collection # Collection_Name: asia_nepa017B # Earliest_Year: 1810 # Most_Recent_Year: 1998 # 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":"5.07658439836","T2":"16.1531141433","M1":"0.0224262120745","M2":"0.538943324756"}} #-------------------- # 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 1810 0.92 1811 1.092 1812 0.815 1813 0.97 1814 0.938 1815 0.96 1816 1.123 1817 0.765 1818 0.717 1819 0.792 1820 0.906 1821 0.857 1822 0.81 1823 1.03 1824 1.128 1825 0.908 1826 0.903 1827 1.001 1828 0.785 1829 0.694 1830 0.803 1831 0.945 1832 0.946 1833 1.108 1834 0.785 1835 0.824 1836 0.926 1837 1.121 1838 0.928 1839 1.029 1840 1.027 1841 0.848 1842 0.801 1843 0.869 1844 1.056 1845 1.08 1846 1.239 1847 0.919 1848 1.088 1849 0.926 1850 0.991 1851 1.011 1852 0.852 1853 0.957 1854 0.913 1855 0.965 1856 1.122 1857 1.139 1858 1.064 1859 0.852 1860 1.07 1861 1.0 1862 1.071 1863 1.048 1864 0.896 1865 0.943 1866 0.997 1867 0.866 1868 0.906 1869 1.066 1870 0.866 1871 1.206 1872 0.997 1873 1.24 1874 0.957 1875 1.027 1876 0.997 1877 1.036 1878 1.231 1879 0.927 1880 0.95 1881 1.11 1882 1.237 1883 0.99 1884 0.864 1885 0.98 1886 0.784 1887 0.598 1888 0.752 1889 0.989 1890 1.04 1891 1.044 1892 1.101 1893 1.015 1894 1.122 1895 0.768 1896 0.934 1897 0.886 1898 0.642 1899 0.837 1900 1.075 1901 0.967 1902 0.975 1903 0.906 1904 0.962 1905 0.913 1906 0.791 1907 0.824 1908 1.288 1909 0.921 1910 1.1 1911 1.413 1912 1.433 1913 1.305 1914 1.352 1915 1.097 1916 0.878 1917 1.041 1918 1.011 1919 1.044 1920 1.082 1921 1.158 1922 1.154 1923 1.192 1924 1.489 1925 1.079 1926 0.961 1927 1.118 1928 0.966 1929 1.11 1930 1.307 1931 1.182 1932 0.866 1933 0.903 1934 1.014 1935 1.138 1936 1.15 1937 1.17 1938 0.96 1939 0.782 1940 0.947 1941 0.917 1942 0.94 1943 0.795 1944 1.137 1945 1.122 1946 1.092 1947 1.057 1948 0.832 1949 0.778 1950 0.864 1951 1.386 1952 1.171 1953 0.756 1954 0.688 1955 0.69 1956 0.773 1957 1.054 1958 1.126 1959 0.829 1960 0.867 1961 0.729 1962 0.731 1963 0.751 1964 0.766 1965 0.519 1966 0.678 1967 0.437 1968 0.404 1969 0.532 1970 0.653 1971 0.733 1972 0.887 1973 0.726 1974 0.863 1975 1.141 1976 1.009 1977 1.561 1978 0.782 1979 0.607 1980 0.792 1981 0.699 1982 0.964 1983 1.18 1984 0.89 1985 0.832 1986 1.028 1987 1.042 1988 1.24 1989 1.15 1990 1.009 1991 1.091 1992 1.291 1993 1.144 1994 0.866 1995 0.798 1996 1.047 1997 0.86 1998 0.877