# europe_lith012 - Kunigiskiai - 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/5205 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_lith012 - Kunigiskiai - 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: Kunigiskiai # Location: # Country: Lithuania # Northernmost_Latitude: 55.97 # Southernmost_Latitude: 55.97 # Easternmost_Longitude: 21.08 # Westernmost_Longitude: 21.08 # Elevation: 12 m #-------------------- # Data_Collection # Collection_Name: europe_lith012B # Earliest_Year: 1828 # Most_Recent_Year: 2002 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"3.88384101168","T2":"15.7531592453","M1":"0.0224293891371","M2":"0.496630856402"}} #-------------------- # Species # Species_Name: Scots pine # Species_Code: PISY #-------------------- # 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 1828 1.162 1829 0.91 1830 0.893 1831 1.02 1832 0.992 1833 1.059 1834 1.073 1835 1.162 1836 1.172 1837 1.194 1838 0.972 1839 0.845 1840 0.908 1841 1.003 1842 0.925 1843 0.985 1844 1.013 1845 0.98 1846 1.264 1847 1.269 1848 1.106 1849 0.818 1850 0.828 1851 0.906 1852 0.743 1853 0.701 1854 0.756 1855 0.894 1856 0.981 1857 0.98 1858 0.936 1859 0.899 1860 1.02 1861 1.207 1862 0.989 1863 0.991 1864 0.903 1865 0.933 1866 0.981 1867 0.933 1868 1.042 1869 0.784 1870 0.739 1871 0.937 1872 0.992 1873 0.956 1874 0.809 1875 0.822 1876 0.82 1877 0.929 1878 0.983 1879 0.949 1880 0.914 1881 0.899 1882 0.85 1883 0.918 1884 1.081 1885 1.186 1886 1.018 1887 0.942 1888 0.834 1889 0.788 1890 1.047 1891 1.162 1892 1.005 1893 0.89 1894 1.022 1895 0.931 1896 1.037 1897 1.303 1898 1.276 1899 0.915 1900 0.867 1901 1.124 1902 1.071 1903 1.103 1904 1.133 1905 1.167 1906 1.275 1907 1.242 1908 1.125 1909 1.311 1910 1.295 1911 1.148 1912 1.125 1913 1.15 1914 1.004 1915 1.053 1916 1.209 1917 1.208 1918 1.221 1919 1.293 1920 0.931 1921 0.906 1922 0.976 1923 0.948 1924 0.953 1925 1.349 1926 1.23 1927 1.331 1928 1.303 1929 1.004 1930 1.037 1931 0.975 1932 1.077 1933 1.101 1934 1.029 1935 0.934 1936 0.894 1937 1.008 1938 1.223 1939 1.13 1940 0.761 1941 0.942 1942 0.93 1943 1.085 1944 1.119 1945 1.198 1946 1.264 1947 1.161 1948 1.21 1949 1.037 1950 0.996 1951 1.001 1952 0.963 1953 1.131 1954 1.129 1955 0.917 1956 0.694 1957 0.897 1958 0.887 1959 0.895 1960 0.855 1961 0.935 1962 0.785 1963 0.803 1964 0.898 1965 0.928 1966 0.847 1967 1.121 1968 0.682 1969 0.561 1970 0.718 1971 0.695 1972 0.793 1973 0.819 1974 0.946 1975 0.881 1976 0.785 1977 0.774 1978 0.877 1979 0.813 1980 0.848 1981 1.05 1982 0.886 1983 0.854 1984 0.807 1985 0.922 1986 0.894 1987 0.832 1988 0.825 1989 1.042 1990 0.945 1991 0.952 1992 0.811 1993 0.724 1994 0.688 1995 0.842 1996 0.808 1997 0.709 1998 0.823 1999 0.922 2000 0.854 2001 0.811 2002 0.68