# europe_pola010 - Koszalin - 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/5219 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_pola010 - Koszalin - 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: Koszalin # Location: # Country: Poland # Northernmost_Latitude: 54.1 # Southernmost_Latitude: 54.1 # Easternmost_Longitude: 16.15 # Westernmost_Longitude: 16.15 # Elevation: 50 m #-------------------- # Data_Collection # Collection_Name: europe_pola010B # Earliest_Year: 1785 # Most_Recent_Year: 1986 # 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":"5.07873839195","T2":"20.2102026937","M1":"0.0222725348586","M2":"0.293293933515"}} #-------------------- # 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 1785 1.427 1786 0.737 1787 0.802 1788 0.757 1789 0.961 1790 0.832 1791 0.84 1792 0.681 1793 0.687 1794 0.649 1795 0.734 1796 0.891 1797 1.232 1798 1.22 1799 1.032 1800 0.484 1801 1.216 1802 1.447 1803 1.244 1804 0.908 1805 1.119 1806 0.936 1807 1.196 1808 0.574 1809 0.481 1810 0.695 1811 0.738 1812 0.618 1813 1.06 1814 0.91 1815 1.071 1816 1.157 1817 1.384 1818 1.455 1819 1.479 1820 0.959 1821 1.031 1822 1.109 1823 1.275 1824 0.925 1825 1.131 1826 0.968 1827 0.928 1828 1.087 1829 1.228 1830 1.281 1831 1.444 1832 0.82 1833 1.122 1834 1.138 1835 0.885 1836 0.896 1837 1.296 1838 0.999 1839 0.821 1840 0.653 1841 0.783 1842 1.195 1843 0.862 1844 0.732 1845 0.989 1846 1.18 1847 0.917 1848 0.689 1849 1.047 1850 1.401 1851 1.218 1852 1.15 1853 0.962 1854 0.862 1855 0.816 1856 0.844 1857 1.068 1858 0.991 1859 0.894 1860 0.961 1861 1.151 1862 1.04 1863 0.926 1864 0.935 1865 0.925 1866 0.938 1867 1.39 1868 1.037 1869 1.3 1870 1.437 1871 1.162 1872 1.006 1873 1.108 1874 0.889 1875 1.075 1876 1.013 1877 1.184 1878 0.969 1879 0.759 1880 0.899 1881 0.756 1882 1.053 1883 0.93 1884 0.775 1885 0.79 1886 1.203 1887 1.049 1888 0.912 1889 1.019 1890 1.185 1891 1.211 1892 1.052 1893 0.99 1894 0.92 1895 0.833 1896 0.795 1897 0.705 1898 0.883 1899 0.862 1900 1.018 1901 0.652 1902 0.836 1903 1.114 1904 1.11 1905 0.945 1906 0.826 1907 0.875 1908 0.806 1909 0.644 1910 0.954 1911 1.136 1912 0.97 1913 0.913 1914 0.787 1915 0.782 1916 0.953 1917 0.971 1918 0.797 1919 0.854 1920 1.049 1921 0.933 1922 0.752 1923 0.624 1924 0.628 1925 0.62 1926 0.559 1927 0.925 1928 0.794 1929 0.866 1930 0.708 1931 0.94 1932 1.199 1933 0.999 1934 0.963 1935 0.935 1936 0.831 1937 1.266 1938 1.224 1939 1.154 1940 0.732 1941 0.753 1942 0.751 1943 0.844 1944 1.051 1945 0.83 1946 1.182 1947 1.128 1948 0.869 1949 1.122 1950 1.214 1951 0.964 1952 0.86 1953 1.208 1954 0.985 1955 1.04 1956 0.693 1957 0.78 1958 0.746 1959 0.844 1960 0.753 1961 0.858 1962 1.125 1963 1.012 1964 0.928 1965 0.851 1966 0.948 1967 0.931 1968 0.894 1969 0.795 1970 0.94 1971 0.779 1972 0.919 1973 1.03 1974 1.024 1975 0.902 1976 0.87 1977 1.082 1978 1.17 1979 1.29 1980 1.299 1981 1.327 1982 1.165 1983 1.183 1984 1.597 1985 1.412 1986 1.379