# europe_finl015 - Koliberg - 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/4472 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_finl015 - Koliberg - 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: Koliberg # Location: # Country: Finland # Northernmost_Latitude: 63.1 # Southernmost_Latitude: 63.1 # Easternmost_Longitude: 25.48 # Westernmost_Longitude: 25.48 # Elevation: 300 m #-------------------- # Data_Collection # Collection_Name: europe_finl015B # Earliest_Year: 1838 # 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":"5.2070331858","T2":"17.546304219","M1":"0.022111667291","M2":"0.420869099674"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1838 0.957 1839 1.096 1840 1.09 1841 1.337 1842 1.171 1843 0.891 1844 1.144 1845 0.99 1846 1.171 1847 0.96 1848 1.225 1849 1.12 1850 1.18 1851 1.003 1852 0.872 1853 0.924 1854 1.105 1855 0.941 1856 1.018 1857 1.001 1858 0.919 1859 0.78 1860 0.844 1861 0.917 1862 0.868 1863 0.925 1864 0.894 1865 0.929 1866 1.01 1867 0.826 1868 1.122 1869 0.834 1870 0.967 1871 0.968 1872 1.036 1873 1.005 1874 0.868 1875 0.877 1876 0.795 1877 0.85 1878 0.955 1879 0.919 1880 0.951 1881 0.906 1882 1.092 1883 0.951 1884 1.16 1885 1.139 1886 0.899 1887 0.946 1888 0.987 1889 1.053 1890 1.128 1891 0.878 1892 0.856 1893 1.017 1894 1.019 1895 0.913 1896 0.911 1897 0.886 1898 1.051 1899 0.962 1900 1.088 1901 1.102 1902 0.797 1903 0.951 1904 0.8 1905 1.099 1906 1.168 1907 0.919 1908 0.913 1909 0.876 1910 0.763 1911 1.0 1912 0.987 1913 0.956 1914 1.048 1915 1.075 1916 1.068 1917 1.061 1918 0.728 1919 1.203 1920 1.073 1921 1.183 1922 1.261 1923 1.209 1924 1.535 1925 1.475 1926 1.232 1927 1.145 1928 0.771 1929 1.115 1930 1.209 1931 0.974 1932 1.081 1933 1.096 1934 1.332 1935 1.116 1936 1.493 1937 1.122 1938 0.937 1939 0.895 1940 0.944 1941 0.821 1942 0.838 1943 0.881 1944 0.912 1945 0.937 1946 1.145 1947 1.198 1948 0.994 1949 0.724 1950 0.747 1951 0.818 1952 0.981 1953 1.112 1954 1.106 1955 0.865 1956 0.866 1957 0.856 1958 0.765 1959 0.842 1960 0.959 1961 0.881 1962 0.818 1963 1.025 1964 0.933 1965 1.03 1966 1.187 1967 0.997 1968 0.903 1969 1.02 1970 1.047 1971 0.887 1972 1.039 1973 0.801 1974 0.945 1975 0.895 1976 0.826 1977 1.013 1978 0.901