# europe_brit7 - Raemills - 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/2674 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_brit7 - Raemills - 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: Raemills # Location: # Country: United Kingdom # Northernmost_Latitude: 55.33 # Southernmost_Latitude: 55.33 # Easternmost_Longitude: -3.5 # Westernmost_Longitude: -3.5 # Elevation: 607 m #-------------------- # Data_Collection # Collection_Name: europe_brit7B # Earliest_Year: 1827 # Most_Recent_Year: 1975 # 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":"6.88274968764","T2":"17.7000082151","M1":"0.0224962296103","M2":"0.347754413283"}} #-------------------- # 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 1827 0.758 1828 0.533 1829 0.761 1830 0.741 1831 1.056 1832 0.971 1833 1.13 1834 1.356 1835 1.466 1836 1.156 1837 1.015 1838 0.857 1839 0.82 1840 0.872 1841 0.516 1842 0.512 1843 0.473 1844 0.171 1845 0.364 1846 0.872 1847 0.655 1848 0.499 1849 0.588 1850 0.724 1851 0.85 1852 0.959 1853 1.019 1854 0.882 1855 1.117 1856 0.988 1857 1.197 1858 1.508 1859 1.74 1860 1.246 1861 1.261 1862 1.172 1863 0.989 1864 0.952 1865 1.173 1866 0.978 1867 0.91 1868 0.903 1869 0.948 1870 1.287 1871 1.14 1872 1.27 1873 1.201 1874 1.046 1875 1.224 1876 1.07 1877 1.088 1878 0.935 1879 0.943 1880 0.748 1881 0.553 1882 0.573 1883 0.502 1884 0.726 1885 0.645 1886 0.704 1887 1.202 1888 1.124 1889 1.277 1890 1.758 1891 1.483 1892 1.754 1893 1.481 1894 0.854 1895 0.949 1896 1.46 1897 1.562 1898 1.081 1899 1.485 1900 1.45 1901 1.086 1902 0.656 1903 1.117 1904 1.193 1905 1.017 1906 1.013 1907 0.652 1908 0.843 1909 0.748 1910 0.732 1911 1.304 1912 0.9 1913 0.83 1914 1.182 1915 0.978 1916 1.048 1917 1.13 1918 1.151 1919 1.214 1920 1.02 1921 1.281 1922 1.063 1923 1.044 1924 1.003 1925 0.913 1926 0.744 1927 0.706 1928 0.563 1929 0.757 1930 0.72 1931 0.685 1932 0.784 1933 1.214 1934 1.087 1935 0.684 1936 1.063 1937 0.868 1938 0.794 1939 1.185 1940 1.057 1941 0.916 1942 0.937 1943 0.952 1944 0.869 1945 0.805 1946 0.887 1947 1.073 1948 0.69 1949 0.745 1950 0.894 1951 0.78 1952 1.068 1953 0.971 1954 0.807 1955 0.987 1956 0.755 1957 0.79 1958 0.862 1959 1.224 1960 0.962 1961 0.88 1962 1.432 1963 1.099 1964 1.101 1965 0.787 1966 0.845 1967 0.759 1968 0.866 1969 0.869 1970 0.753 1971 0.695 1972 0.591 1973 0.637 1974 0.696 1975 1.025