# europe_norw002 - Tua Steinkier - 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/4698 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_norw002 - Tua Steinkier - 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: Tua Steinkier # Location: # Country: Norway # Northernmost_Latitude: 63.95 # Southernmost_Latitude: 63.95 # Easternmost_Longitude: 10.88 # Westernmost_Longitude: 10.88 # Elevation: 300 m #-------------------- # Data_Collection # Collection_Name: europe_norw002B # Earliest_Year: 1807 # Most_Recent_Year: 1978 # 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":"6.06363524547","T2":"19.2001902088","M1":"0.0222171898298","M2":"0.364947292335"}} #-------------------- # 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 1807 0.974 1808 1.188 1809 1.226 1810 0.894 1811 1.093 1812 0.876 1813 1.015 1814 1.068 1815 1.124 1816 1.238 1817 1.179 1818 1.147 1819 1.437 1820 0.981 1821 0.817 1822 1.082 1823 1.148 1824 0.98 1825 1.002 1826 1.227 1827 1.081 1828 1.479 1829 1.137 1830 0.858 1831 1.193 1832 0.942 1833 1.196 1834 1.152 1835 0.855 1836 0.972 1837 0.842 1838 0.942 1839 0.798 1840 0.853 1841 0.93 1842 1.064 1843 0.874 1844 0.7 1845 0.784 1846 0.703 1847 0.878 1848 0.812 1849 0.783 1850 0.777 1851 0.994 1852 0.968 1853 0.716 1854 1.061 1855 0.967 1856 0.882 1857 1.27 1858 1.488 1859 1.017 1860 1.191 1861 1.177 1862 1.127 1863 0.827 1864 0.637 1865 0.508 1866 0.734 1867 0.959 1868 1.279 1869 1.261 1870 1.296 1871 1.208 1872 1.11 1873 1.065 1874 0.95 1875 1.218 1876 1.1 1877 1.236 1878 1.172 1879 1.175 1880 0.86 1881 0.69 1882 1.276 1883 1.11 1884 1.257 1885 1.139 1886 0.991 1887 1.27 1888 1.006 1889 1.012 1890 0.86 1891 0.851 1892 0.714 1893 0.781 1894 0.818 1895 0.931 1896 0.928 1897 0.931 1898 0.911 1899 0.916 1900 0.996 1901 1.068 1902 0.874 1903 0.617 1904 0.78 1905 0.734 1906 0.852 1907 0.829 1908 0.814 1909 0.792 1910 0.97 1911 0.767 1912 0.803 1913 0.812 1914 0.946 1915 0.942 1916 1.11 1917 1.191 1918 0.881 1919 0.999 1920 0.775 1921 0.669 1922 0.795 1923 0.618 1924 0.821 1925 0.971 1926 0.786 1927 0.982 1928 0.634 1929 0.864 1930 1.088 1931 0.926 1932 0.968 1933 1.243 1934 1.47 1935 0.876 1936 1.129 1937 1.398 1938 1.303 1939 1.221 1940 1.115 1941 1.327 1942 1.167 1943 1.093 1944 1.016 1945 1.065 1946 1.081 1947 1.152 1948 0.901 1949 0.995 1950 1.242 1951 1.083 1952 0.851 1953 1.268 1954 1.238 1955 1.099 1956 0.776 1957 0.991 1958 0.874 1959 0.976 1960 1.133 1961 0.849 1962 0.884 1963 0.891 1964 0.801 1965 0.905 1966 0.863 1967 1.013 1968 1.001 1969 1.04 1970 1.043 1971 0.924 1972 1.082 1973 1.007 1974 0.769 1975 1.109 1976 0.953 1977 0.836 1978 1.034