# europe_brit010 - Ludlow - 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/4222 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_brit010 - Ludlow - 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: Ludlow # Location: # Country: United Kingdom # Northernmost_Latitude: 52.35 # Southernmost_Latitude: 52.35 # Easternmost_Longitude: -2.73 # Westernmost_Longitude: -2.73 # Elevation: 185 m #-------------------- # Data_Collection # Collection_Name: europe_brit010B # Earliest_Year: 1832 # 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":"4.72358367583","T2":"14.3477637566","M1":"0.0223760400893","M2":"0.564066818257"}} #-------------------- # 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 1832 1.005 1833 1.24 1834 1.258 1835 1.113 1836 0.946 1837 1.154 1838 0.707 1839 0.921 1840 0.627 1841 0.93 1842 1.093 1843 0.98 1844 0.542 1845 0.895 1846 0.91 1847 0.601 1848 0.547 1849 0.963 1850 1.145 1851 1.457 1852 1.334 1853 1.253 1854 0.976 1855 1.172 1856 0.912 1857 1.458 1858 1.213 1859 1.381 1860 1.053 1861 1.607 1862 1.107 1863 0.704 1864 0.497 1865 0.714 1866 0.733 1867 0.913 1868 0.974 1869 0.769 1870 0.831 1871 0.991 1872 1.019 1873 1.094 1874 0.786 1875 1.245 1876 0.757 1877 0.905 1878 1.114 1879 0.952 1880 1.015 1881 0.677 1882 0.666 1883 0.783 1884 0.85 1885 0.848 1886 0.791 1887 0.698 1888 0.791 1889 0.732 1890 0.933 1891 1.3 1892 1.54 1893 1.38 1894 0.877 1895 1.319 1896 0.942 1897 1.182 1898 0.948 1899 0.992 1900 1.252 1901 1.184 1902 1.059 1903 1.294 1904 1.242 1905 0.978 1906 1.008 1907 1.065 1908 1.347 1909 0.924 1910 1.302 1911 1.002 1912 1.215 1913 1.241 1914 1.133 1915 1.018 1916 0.984 1917 1.027 1918 1.238 1919 1.041 1920 1.192 1921 0.908 1922 1.089 1923 1.098 1924 1.258 1925 1.127 1926 1.072 1927 1.019 1928 1.011 1929 1.199 1930 1.33 1931 1.257 1932 1.016 1933 0.784 1934 0.817 1935 0.855 1936 0.886 1937 0.897 1938 0.955 1939 1.294 1940 0.77 1941 0.593 1942 0.613 1943 0.799 1944 0.583 1945 1.007 1946 0.771 1947 1.188 1948 0.742 1949 0.603 1950 0.716 1951 0.746 1952 0.906 1953 0.89 1954 0.827 1955 0.948 1956 0.688 1957 0.625 1958 1.063 1959 0.992 1960 1.093 1961 0.76 1962 1.005 1963 1.188 1964 1.288 1965 0.938 1966 1.202 1967 1.095 1968 0.951 1969 0.955 1970 0.98 1971 1.071 1972 0.839 1973 0.919 1974 0.631 1975 0.734 1976 0.692 1977 0.961 1978 1.069