# asia_nepa012 - BudoRouke - 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/3769 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa012 - BudoRouke - 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: BudoRouke # Location: # Country: Nepal # Northernmost_Latitude: 27.45 # Southernmost_Latitude: 27.45 # Easternmost_Longitude: 87.17 # Westernmost_Longitude: 87.17 # Elevation: 2970 m #-------------------- # Data_Collection # Collection_Name: asia_nepa012B # Earliest_Year: 1707 # 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":"4.88726191257","T2":"20.8201902005","M1":"0.0223714540042","M2":"0.288121217686"}} #-------------------- # 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 1707 1.04 1708 1.318 1709 1.352 1710 1.114 1711 1.088 1712 0.9 1713 0.934 1714 1.246 1715 1.195 1716 0.987 1717 1.083 1718 0.985 1719 0.835 1720 0.58 1721 0.666 1722 0.806 1723 0.749 1724 0.88 1725 0.921 1726 0.99 1727 0.941 1728 0.778 1729 0.667 1730 0.569 1731 0.666 1732 0.647 1733 0.907 1734 1.06 1735 0.978 1736 0.804 1737 0.81 1738 0.818 1739 0.809 1740 0.797 1741 0.696 1742 0.831 1743 0.755 1744 0.987 1745 0.925 1746 0.762 1747 0.972 1748 1.036 1749 1.17 1750 0.706 1751 0.662 1752 0.782 1753 0.856 1754 0.833 1755 0.922 1756 1.046 1757 1.155 1758 1.113 1759 1.051 1760 1.007 1761 1.122 1762 1.105 1763 0.829 1764 0.703 1765 0.7 1766 0.859 1767 0.85 1768 1.014 1769 0.859 1770 0.925 1771 1.126 1772 1.147 1773 1.19 1774 1.139 1775 1.02 1776 1.044 1777 1.037 1778 1.156 1779 1.219 1780 0.998 1781 0.911 1782 0.815 1783 0.862 1784 0.937 1785 1.094 1786 0.985 1787 0.878 1788 1.047 1789 1.052 1790 0.939 1791 0.997 1792 1.077 1793 0.873 1794 0.918 1795 0.834 1796 0.925 1797 0.699 1798 0.857 1799 0.835 1800 1.099 1801 1.101 1802 1.567 1803 1.59 1804 1.517 1805 1.437 1806 1.296 1807 1.275 1808 0.909 1809 0.736 1810 0.845 1811 0.93 1812 0.78 1813 0.743 1814 0.869 1815 0.638 1816 0.638 1817 0.695 1818 0.672 1819 0.55 1820 0.49 1821 0.68 1822 0.99 1823 0.914 1824 0.934 1825 0.708 1826 0.762 1827 0.96 1828 0.703 1829 0.982 1830 1.454 1831 1.274 1832 1.185 1833 1.433 1834 1.325 1835 1.473 1836 0.926 1837 0.667 1838 0.754 1839 0.819 1840 0.847 1841 1.044 1842 1.068 1843 1.268 1844 1.231 1845 1.288 1846 1.061 1847 0.896 1848 0.939 1849 0.849 1850 0.969 1851 1.022 1852 1.046 1853 0.775 1854 0.886 1855 0.985 1856 0.994 1857 1.085 1858 1.039 1859 1.349 1860 1.107 1861 0.78 1862 1.025 1863 0.906 1864 0.918 1865 1.179 1866 0.9 1867 0.808 1868 0.925 1869 0.832 1870 0.847 1871 1.354 1872 0.829 1873 0.618 1874 0.614 1875 0.814 1876 0.635 1877 0.87 1878 0.905 1879 1.042 1880 1.574 1881 1.434 1882 1.269 1883 1.307 1884 1.076 1885 0.959 1886 1.311 1887 0.907 1888 0.93 1889 0.944 1890 1.027 1891 1.156 1892 0.922 1893 0.924 1894 0.993 1895 0.723 1896 0.753 1897 0.905 1898 1.164 1899 1.045 1900 1.481 1901 0.941 1902 0.83 1903 0.868 1904 0.736 1905 0.566 1906 0.755 1907 0.92 1908 1.176 1909 1.143 1910 1.075 1911 1.614 1912 1.528 1913 1.394 1914 1.725 1915 1.002 1916 0.717 1917 0.839 1918 0.917 1919 1.448 1920 1.03 1921 1.064 1922 1.515 1923 1.065 1924 1.043 1925 1.031 1926 1.154 1927 1.143 1928 1.004 1929 0.873 1930 1.169 1931 0.903 1932 0.815 1933 0.838 1934 0.835 1935 0.825 1936 0.797 1937 0.642 1938 0.386 1939 0.501 1940 0.986 1941 0.699 1942 0.917 1943 1.029 1944 1.231 1945 1.062 1946 1.106 1947 1.096 1948 1.355 1949 1.406 1950 1.226 1951 1.408 1952 1.882 1953 1.25 1954 0.997 1955 0.998 1956 0.969 1957 1.38 1958 1.437 1959 0.929 1960 0.962 1961 0.986 1962 0.756 1963 0.797 1964 0.828 1965 0.791 1966 0.955 1967 0.684 1968 0.638 1969 0.768 1970 0.906 1971 0.845 1972 0.778 1973 0.681 1974 0.914 1975 0.968 1976 0.761 1977 1.016 1978 0.516 1979 0.511 1980 0.468 1981 0.686 1982 0.664 1983 0.656 1984 0.476 1985 0.483 1986 0.554 1987 0.568 1988 0.706 1989 0.585 1990 0.546 1991 0.534 1992 0.499 1993 0.663 1994 0.715 1995 0.711 1996 0.662