# europe_pola005 - Gdansk Recent - 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/5215 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_pola005 - Gdansk Recent - 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: Gdansk Recent # Location: # Country: Poland # Northernmost_Latitude: 54.3 # Southernmost_Latitude: 54.3 # Easternmost_Longitude: 18.55 # Westernmost_Longitude: 18.55 # Elevation: 20 m #-------------------- # Data_Collection # Collection_Name: europe_pola005B # Earliest_Year: 1775 # Most_Recent_Year: 1985 # 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":"4.92350591713","T2":"17.1380783997","M1":"0.0228686879202","M2":"0.478787621202"}} #-------------------- # Species # Species_Name: English oak # Species_Code: QURO #-------------------- # 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 1775 1.086 1776 1.022 1777 1.277 1778 1.266 1779 1.293 1780 0.957 1781 1.002 1782 0.942 1783 1.171 1784 1.083 1785 0.993 1786 0.866 1787 0.882 1788 0.697 1789 0.65 1790 0.398 1791 0.78 1792 0.826 1793 0.954 1794 0.762 1795 0.839 1796 1.062 1797 0.979 1798 1.092 1799 0.996 1800 0.515 1801 1.06 1802 0.935 1803 0.882 1804 0.868 1805 0.772 1806 0.704 1807 0.769 1808 0.746 1809 0.696 1810 0.74 1811 0.776 1812 1.076 1813 0.883 1814 0.948 1815 1.034 1816 1.086 1817 1.263 1818 1.045 1819 0.946 1820 1.442 1821 1.205 1822 1.201 1823 1.324 1824 1.18 1825 1.128 1826 1.095 1827 1.143 1828 1.464 1829 1.379 1830 1.276 1831 1.475 1832 1.23 1833 1.268 1834 1.268 1835 0.967 1836 0.98 1837 1.055 1838 0.58 1839 0.671 1840 0.913 1841 1.027 1842 1.209 1843 1.025 1844 0.969 1845 0.992 1846 1.091 1847 0.813 1848 0.816 1849 1.142 1850 1.212 1851 1.122 1852 1.024 1853 1.093 1854 0.98 1855 1.18 1856 1.023 1857 0.944 1858 0.773 1859 0.964 1860 1.006 1861 1.31 1862 1.2 1863 0.915 1864 0.859 1865 0.978 1866 0.876 1867 1.018 1868 0.865 1869 0.906 1870 0.932 1871 0.977 1872 0.929 1873 1.028 1874 0.836 1875 0.939 1876 0.983 1877 1.052 1878 1.036 1879 1.039 1880 1.042 1881 0.729 1882 0.949 1883 0.886 1884 0.953 1885 0.872 1886 0.855 1887 0.662 1888 0.789 1889 0.845 1890 1.015 1891 0.998 1892 0.998 1893 0.839 1894 0.977 1895 0.99 1896 0.981 1897 0.919 1898 0.743 1899 0.802 1900 0.77 1901 0.802 1902 0.95 1903 0.985 1904 0.871 1905 0.983 1906 1.017 1907 0.959 1908 1.039 1909 0.808 1910 1.0 1911 0.97 1912 0.876 1913 1.058 1914 0.94 1915 0.919 1916 0.86 1917 0.95 1918 0.943 1919 0.923 1920 0.972 1921 0.931 1922 0.995 1923 0.913 1924 1.108 1925 0.974 1926 1.093 1927 1.134 1928 0.898 1929 0.926 1930 0.871 1931 1.104 1932 1.081 1933 0.954 1934 1.018 1935 1.001 1936 1.042 1937 1.004 1938 0.982 1939 0.947 1940 0.882 1941 0.815 1942 0.816 1943 0.72 1944 0.84 1945 1.161 1946 1.155 1947 0.987 1948 1.044 1949 1.117 1950 1.074 1951 1.021 1952 0.829 1953 1.051 1954 0.958 1955 0.982 1956 1.0 1957 1.146 1958 1.19 1959 1.09 1960 1.062 1961 0.885 1962 1.029 1963 0.997 1964 0.952 1965 0.92 1966 0.925 1967 0.949 1968 1.034 1969 0.772 1970 1.016 1971 1.18 1972 1.073 1973 0.945 1974 0.974 1975 0.915 1976 0.865 1977 0.962 1978 1.031 1979 1.065 1980 1.277 1981 1.051 1982 1.035 1983 1.003 1984 1.228 1985 1.152