# asia_nepa013 - Chardung - 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/3770 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa013 - Chardung - 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: Chardung # Location: # Country: Nepal # Northernmost_Latitude: 27.17 # Southernmost_Latitude: 27.17 # Easternmost_Longitude: 86.42 # Westernmost_Longitude: 86.42 # Elevation: 3300 m #-------------------- # Data_Collection # Collection_Name: asia_nepa013B # Earliest_Year: 1800 # 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":"5.45616832948","T2":"17.7361398571","M1":"0.0225720308652","M2":"0.201668539344"}} #-------------------- # 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 1800 1.39 1801 1.001 1802 1.132 1803 1.144 1804 1.269 1805 0.882 1806 1.011 1807 0.961 1808 0.857 1809 0.851 1810 0.979 1811 0.947 1812 0.938 1813 0.67 1814 0.688 1815 0.794 1816 0.882 1817 0.745 1818 0.585 1819 0.618 1820 0.705 1821 0.905 1822 0.62 1823 0.737 1824 1.015 1825 1.026 1826 0.899 1827 1.136 1828 0.663 1829 0.577 1830 0.563 1831 0.661 1832 0.773 1833 0.718 1834 0.511 1835 0.38 1836 0.625 1837 0.989 1838 0.951 1839 0.896 1840 1.019 1841 0.923 1842 1.064 1843 0.922 1844 0.966 1845 1.039 1846 1.506 1847 1.167 1848 1.232 1849 0.931 1850 1.033 1851 0.986 1852 0.76 1853 0.805 1854 0.743 1855 0.879 1856 1.178 1857 1.238 1858 1.28 1859 0.993 1860 0.995 1861 1.272 1862 1.128 1863 1.115 1864 1.159 1865 1.25 1866 1.042 1867 1.079 1868 1.073 1869 1.031 1870 0.972 1871 1.253 1872 1.154 1873 1.188 1874 1.054 1875 1.349 1876 1.177 1877 1.015 1878 1.171 1879 0.965 1880 0.79 1881 0.937 1882 0.964 1883 0.985 1884 0.989 1885 1.066 1886 0.738 1887 0.48 1888 0.714 1889 1.199 1890 1.15 1891 1.174 1892 1.534 1893 1.272 1894 1.242 1895 0.789 1896 1.137 1897 1.33 1898 1.247 1899 1.197 1900 1.357 1901 1.244 1902 1.416 1903 1.34 1904 1.498 1905 1.26 1906 0.943 1907 0.723 1908 1.186 1909 0.938 1910 1.076 1911 1.109 1912 1.014 1913 0.929 1914 1.044 1915 0.948 1916 0.652 1917 0.866 1918 0.941 1919 0.992 1920 1.252 1921 1.41 1922 0.887 1923 0.681 1924 1.222 1925 1.0 1926 0.887 1927 0.948 1928 0.712 1929 0.425 1930 0.688 1931 1.24 1932 1.101 1933 1.095 1934 1.243 1935 1.103 1936 0.842 1937 0.882 1938 0.762 1939 0.659 1940 1.0 1941 0.927 1942 0.832 1943 0.956 1944 0.98 1945 1.141 1946 0.987 1947 0.901 1948 0.785 1949 0.672 1950 1.045 1951 1.42 1952 1.393 1953 0.956 1954 1.087 1955 0.906 1956 0.957 1957 1.001 1958 1.042 1959 0.859 1960 0.835 1961 0.77 1962 0.75 1963 1.074 1964 0.897 1965 0.404 1966 0.429 1967 0.484 1968 0.581 1969 0.967 1970 0.776 1971 0.469 1972 0.495 1973 0.7 1974 0.725 1975 0.376 1976 0.39 1977 1.006 1978 0.828 1979 0.965 1980 0.798 1981 0.61 1982 0.871 1983 1.095 1984 0.731 1985 0.794 1986 1.098 1987 1.361 1988 1.148 1989 1.173 1990 1.218 1991 1.472 1992 1.292 1993 1.272 1994 1.089 1995 1.001 1996 1.264 1997 1.089 1998 1.086