# europe_brit019 - Franchise Wood - 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/4418 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_brit019 - Franchise Wood - 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: Franchise Wood # Location: # Country: United Kingdom # Northernmost_Latitude: 50.95 # Southernmost_Latitude: 50.95 # Easternmost_Longitude: -1.68 # Westernmost_Longitude: -1.68 # Elevation: 100 m #-------------------- # Data_Collection # Collection_Name: europe_brit019B # Earliest_Year: 1848 # Most_Recent_Year: 1976 # 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":"4.08973836093","T2":"14.7721379365","M1":"0.0232919127762","M2":"0.55725924411"}} #-------------------- # 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 1848 1.127 1849 0.892 1850 0.974 1851 1.086 1852 1.465 1853 1.274 1854 0.885 1855 1.06 1856 1.172 1857 0.993 1858 0.826 1859 0.792 1860 1.001 1861 0.959 1862 0.62 1863 0.625 1864 0.503 1865 0.601 1866 0.877 1867 0.944 1868 0.914 1869 0.98 1870 0.73 1871 0.993 1872 1.206 1873 0.968 1874 0.935 1875 0.857 1876 0.794 1877 0.828 1878 0.883 1879 0.975 1880 0.915 1881 0.979 1882 1.267 1883 0.909 1884 1.102 1885 1.045 1886 0.864 1887 0.792 1888 0.964 1889 1.02 1890 1.14 1891 1.08 1892 1.247 1893 1.23 1894 1.07 1895 1.072 1896 1.17 1897 1.224 1898 0.993 1899 0.822 1900 1.152 1901 1.259 1902 1.209 1903 1.465 1904 1.389 1905 1.37 1906 1.267 1907 1.109 1908 0.948 1909 0.969 1910 1.229 1911 0.874 1912 0.966 1913 1.125 1914 0.957 1915 1.098 1916 1.0 1917 1.055 1918 1.069 1919 0.82 1920 0.919 1921 0.684 1922 0.746 1923 0.91 1924 1.244 1925 1.239 1926 1.059 1927 1.394 1928 0.835 1929 1.04 1930 1.324 1931 1.077 1932 1.213 1933 1.189 1934 1.093 1935 0.978 1936 0.975 1937 1.168 1938 0.758 1939 0.661 1940 0.438 1941 0.843 1942 0.778 1943 1.105 1944 0.834 1945 0.765 1946 0.745 1947 0.686 1948 0.823 1949 0.811 1950 0.755 1951 0.912 1952 0.928 1953 1.027 1954 0.677 1955 0.799 1956 1.098 1957 1.076 1958 0.923 1959 0.749 1960 1.175 1961 0.958 1962 1.065 1963 0.75 1964 0.908 1965 1.184 1966 0.889 1967 1.233 1968 1.26 1969 0.912 1970 1.046 1971 0.945 1972 0.863 1973 1.032 1974 0.833 1975 1.023 1976 0.777