# europe_brit011 - Blickling - 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/4208 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_brit011 - Blickling - 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: Blickling # Location: # Country: United Kingdom # Northernmost_Latitude: 52.82 # Southernmost_Latitude: 52.82 # Easternmost_Longitude: -1.22 # Westernmost_Longitude: -1.22 # Elevation: 40 m #-------------------- # Data_Collection # Collection_Name: europe_brit011B # Earliest_Year: 1762 # Most_Recent_Year: 1979 # 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":"7.30614690496","T2":"14.4510328483","M1":"0.0226480253039","M2":"0.554636347183"}} #-------------------- # 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 1762 1.075 1763 1.226 1764 1.308 1765 1.564 1766 1.087 1767 1.067 1768 1.476 1769 1.223 1770 1.103 1771 1.049 1772 1.125 1773 0.914 1774 0.679 1775 1.075 1776 1.282 1777 1.365 1778 1.051 1779 0.834 1780 0.807 1781 0.69 1782 0.88 1783 0.932 1784 0.966 1785 0.935 1786 0.918 1787 1.273 1788 1.229 1789 1.111 1790 1.007 1791 0.916 1792 0.722 1793 0.661 1794 0.651 1795 0.521 1796 0.545 1797 0.948 1798 1.065 1799 0.848 1800 0.842 1801 0.456 1802 0.442 1803 0.469 1804 0.657 1805 0.742 1806 0.737 1807 0.614 1808 0.815 1809 0.737 1810 1.053 1811 1.112 1812 0.948 1813 1.027 1814 0.944 1815 0.792 1816 0.805 1817 0.798 1818 0.987 1819 0.985 1820 1.079 1821 0.8 1822 0.962 1823 1.009 1824 0.991 1825 1.059 1826 0.972 1827 0.892 1828 0.943 1829 1.233 1830 1.275 1831 1.309 1832 0.826 1833 0.957 1834 1.228 1835 0.914 1836 0.881 1837 1.088 1838 0.765 1839 0.626 1840 0.369 1841 0.739 1842 1.048 1843 0.904 1844 0.685 1845 0.961 1846 1.435 1847 1.405 1848 1.36 1849 1.513 1850 1.061 1851 1.306 1852 0.86 1853 1.043 1854 0.858 1855 0.862 1856 0.878 1857 1.129 1858 1.105 1859 1.036 1860 0.799 1861 1.111 1862 0.959 1863 0.855 1864 0.911 1865 0.904 1866 0.837 1867 1.031 1868 1.152 1869 0.976 1870 1.186 1871 1.195 1872 0.913 1873 0.84 1874 0.453 1875 0.503 1876 0.592 1877 0.784 1878 0.974 1879 1.095 1880 0.787 1881 0.823 1882 0.824 1883 0.71 1884 0.995 1885 0.981 1886 1.005 1887 0.944 1888 0.562 1889 0.473 1890 0.644 1891 0.912 1892 1.371 1893 1.145 1894 1.033 1895 0.956 1896 0.839 1897 0.738 1898 0.735 1899 0.821 1900 1.276 1901 1.117 1902 1.08 1903 1.207 1904 1.257 1905 1.026 1906 1.014 1907 0.992 1908 0.974 1909 0.669 1910 0.802 1911 1.068 1912 1.302 1913 1.72 1914 1.413 1915 1.405 1916 1.379 1917 1.917 1918 1.765 1919 1.489 1920 1.335 1921 1.244 1922 1.265 1923 1.274 1924 1.305 1925 1.108 1926 0.954 1927 1.196 1928 1.161 1929 1.288 1930 0.782 1931 0.577 1932 0.425 1933 0.567 1934 0.657 1935 0.807 1936 0.914 1937 1.243 1938 0.714 1939 0.693 1940 0.618 1941 0.546 1942 0.718 1943 0.64 1944 0.581 1945 0.86 1946 0.631 1947 0.987 1948 0.633 1949 0.305 1950 0.619 1951 0.517 1952 0.704 1953 1.145 1954 0.988 1955 0.997 1956 0.798 1957 0.616 1958 1.202 1959 0.969 1960 1.105 1961 0.958 1962 1.391 1963 0.947 1964 1.307 1965 1.24 1966 1.369 1967 1.073 1968 0.987 1969 0.957 1970 1.165 1971 1.31 1972 0.74 1973 0.884 1974 0.762 1975 0.949 1976 0.862 1977 0.741 1978 1.008 1979 0.546