# europe_swed018 - Kaaresuvanto Enontekiö - 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/3986 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swed018 - Kaaresuvanto Enontekiö - 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: Kaaresuvanto Enontekiö # Location: # Country: Sweden # Northernmost_Latitude: 68.48 # Southernmost_Latitude: 68.48 # Easternmost_Longitude: 22.15 # Westernmost_Longitude: 22.15 # Elevation: 350 m #-------------------- # Data_Collection # Collection_Name: europe_swed018B # Earliest_Year: 1837 # Most_Recent_Year: 1992 # 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":"7.06180253784","T2":"19.9278038201","M1":"0.0220383477443","M2":"0.221641913976"}} #-------------------- # 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 1837 0.52 1838 0.551 1839 0.351 1840 0.326 1841 0.374 1842 0.618 1843 0.594 1844 0.694 1845 0.639 1846 0.767 1847 0.831 1848 0.872 1849 0.916 1850 0.745 1851 0.951 1852 1.054 1853 0.966 1854 1.126 1855 1.146 1856 0.867 1857 0.721 1858 0.715 1859 0.695 1860 0.833 1861 0.851 1862 0.858 1863 0.814 1864 0.846 1865 0.935 1866 0.969 1867 0.854 1868 0.741 1869 0.561 1870 0.634 1871 0.765 1872 1.083 1873 0.98 1874 0.797 1875 1.011 1876 1.08 1877 0.973 1878 0.71 1879 0.756 1880 0.711 1881 0.564 1882 0.842 1883 0.895 1884 0.75 1885 0.817 1886 1.101 1887 1.135 1888 0.846 1889 0.919 1890 1.176 1891 1.19 1892 0.788 1893 0.726 1894 0.936 1895 1.2 1896 0.957 1897 1.043 1898 1.229 1899 0.977 1900 0.833 1901 1.435 1902 0.83 1903 0.474 1904 0.584 1905 0.586 1906 0.708 1907 0.786 1908 0.943 1909 0.637 1910 0.655 1911 0.623 1912 0.909 1913 0.95 1914 1.105 1915 1.144 1916 1.127 1917 0.884 1918 1.278 1919 1.261 1920 1.289 1921 1.161 1922 1.422 1923 1.438 1924 1.553 1925 1.661 1926 1.339 1927 1.405 1928 0.971 1929 0.94 1930 1.631 1931 1.051 1932 0.922 1933 1.177 1934 1.48 1935 1.043 1936 0.83 1937 1.34 1938 1.072 1939 0.836 1940 0.853 1941 1.222 1942 0.995 1943 0.919 1944 0.952 1945 0.879 1946 0.626 1947 0.94 1948 1.131 1949 1.058 1950 1.158 1951 1.013 1952 1.005 1953 1.248 1954 1.158 1955 1.002 1956 0.937 1957 1.126 1958 0.877 1959 1.137 1960 1.238 1961 0.804 1962 0.981 1963 0.737 1964 1.203 1965 0.857 1966 0.887 1967 0.94 1968 0.914 1969 1.049 1970 0.996 1971 0.812 1972 0.954 1973 1.052 1974 0.849 1975 0.878 1976 1.124 1977 0.941 1978 0.867 1979 1.125 1980 1.056 1981 0.8 1982 0.991 1983 1.023 1984 0.809 1985 1.074 1986 0.908 1987 0.757 1988 0.892 1989 0.842 1990 0.772 1991 0.759 1992 0.739