# asia_nepa016 - Deorali La - 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/3773 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa016 - Deorali La - 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: Deorali La # Location: # Country: Nepal # Northernmost_Latitude: 28.23 # Southernmost_Latitude: 28.23 # Easternmost_Longitude: 83.42 # Westernmost_Longitude: 83.42 # Elevation: 1830 m #-------------------- # Data_Collection # Collection_Name: asia_nepa016B # Earliest_Year: 1778 # Most_Recent_Year: 1997 # 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":"4.25056254236","T2":"16.1164887853","M1":"0.0226770295633","M2":"0.538198931633"}} #-------------------- # 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 1778 1.091 1779 0.857 1780 0.915 1781 1.048 1782 1.002 1783 0.69 1784 0.908 1785 1.222 1786 1.117 1787 0.903 1788 1.034 1789 0.831 1790 0.659 1791 0.669 1792 0.747 1793 0.901 1794 0.962 1795 1.115 1796 1.435 1797 1.464 1798 1.192 1799 1.033 1800 1.198 1801 1.017 1802 0.593 1803 1.037 1804 1.217 1805 0.964 1806 1.014 1807 0.704 1808 0.933 1809 0.929 1810 1.272 1811 0.885 1812 0.786 1813 0.961 1814 0.82 1815 0.443 1816 0.728 1817 0.494 1818 0.555 1819 0.582 1820 0.666 1821 0.911 1822 0.857 1823 0.951 1824 0.858 1825 0.763 1826 1.019 1827 1.237 1828 0.918 1829 0.909 1830 0.924 1831 0.96 1832 0.877 1833 0.791 1834 0.652 1835 0.564 1836 0.564 1837 0.665 1838 0.432 1839 0.677 1840 1.06 1841 0.942 1842 0.985 1843 0.873 1844 0.988 1845 1.223 1846 1.516 1847 0.994 1848 1.138 1849 0.878 1850 0.994 1851 1.051 1852 1.281 1853 1.638 1854 1.312 1855 1.306 1856 1.257 1857 0.846 1858 1.051 1859 1.142 1860 1.143 1861 0.809 1862 0.949 1863 0.979 1864 0.908 1865 1.101 1866 1.008 1867 0.883 1868 0.983 1869 0.967 1870 0.9 1871 1.076 1872 1.046 1873 0.912 1874 0.562 1875 0.856 1876 1.019 1877 0.915 1878 1.308 1879 1.056 1880 0.844 1881 1.146 1882 1.267 1883 1.108 1884 0.781 1885 0.8 1886 1.063 1887 1.137 1888 1.36 1889 1.172 1890 0.896 1891 1.034 1892 0.853 1893 0.514 1894 0.969 1895 0.95 1896 0.961 1897 1.075 1898 0.782 1899 0.929 1900 1.113 1901 0.615 1902 0.74 1903 1.208 1904 1.106 1905 0.67 1906 0.878 1907 1.005 1908 1.257 1909 1.094 1910 1.091 1911 1.23 1912 1.224 1913 1.235 1914 1.366 1915 1.34 1916 1.162 1917 1.135 1918 1.098 1919 1.192 1920 1.183 1921 0.94 1922 0.755 1923 0.877 1924 1.425 1925 1.04 1926 1.098 1927 1.06 1928 0.865 1929 1.14 1930 1.344 1931 1.042 1932 0.651 1933 0.966 1934 1.503 1935 0.998 1936 0.814 1937 0.885 1938 0.811 1939 0.739 1940 0.762 1941 0.919 1942 1.126 1943 1.153 1944 0.566 1945 0.639 1946 0.731 1947 0.88 1948 0.88 1949 0.942 1950 1.035 1951 1.378 1952 1.196 1953 0.89 1954 1.008 1955 1.062 1956 1.016 1957 1.305 1958 1.214 1959 0.827 1960 0.586 1961 0.775 1962 0.732 1963 0.935 1964 0.927 1965 0.568 1966 0.888 1967 0.691 1968 0.374 1969 0.806 1970 0.71 1971 0.766 1972 1.121 1973 1.062 1974 0.784 1975 0.513 1976 0.878 1977 1.179 1978 0.918 1979 1.168 1980 0.989 1981 0.618 1982 0.838 1983 1.037 1984 0.919 1985 0.863 1986 1.126 1987 1.231 1988 1.0 1989 0.646 1990 0.776 1991 0.919 1992 0.889 1993 0.561 1994 0.597 1995 0.718 1996 1.033 1997 0.891