# europe_brit021 - Dimmie Schottland - 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/4399 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_brit021 - Dimmie Schottland - 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: Dimmie Schottland # Location: # Country: United Kingdom # Northernmost_Latitude: 56.12 # Southernmost_Latitude: 56.12 # Easternmost_Longitude: -3.33 # Westernmost_Longitude: -3.33 # Elevation: 200 m #-------------------- # Data_Collection # Collection_Name: europe_brit021B # Earliest_Year: 1843 # 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":"2.50859554834","T2":"17.0846918207","M1":"0.022227353974","M2":"0.225953855065"}} #-------------------- # 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 1843 1.061 1844 1.181 1845 1.278 1846 1.174 1847 0.837 1848 0.859 1849 0.898 1850 0.763 1851 0.88 1852 1.058 1853 1.014 1854 0.82 1855 0.876 1856 0.944 1857 0.944 1858 0.955 1859 0.885 1860 0.959 1861 0.869 1862 0.766 1863 0.824 1864 0.743 1865 0.792 1866 0.883 1867 0.92 1868 0.997 1869 0.86 1870 0.757 1871 0.95 1872 1.058 1873 1.04 1874 0.963 1875 1.051 1876 0.964 1877 0.831 1878 0.918 1879 0.671 1880 1.315 1881 0.984 1882 1.186 1883 0.77 1884 0.783 1885 0.754 1886 0.939 1887 1.056 1888 1.109 1889 1.032 1890 1.155 1891 1.177 1892 1.098 1893 1.176 1894 0.855 1895 0.362 1896 0.203 1897 0.43 1898 0.708 1899 0.864 1900 0.964 1901 0.946 1902 0.774 1903 1.057 1904 1.278 1905 1.122 1906 1.061 1907 0.874 1908 0.746 1909 0.699 1910 1.077 1911 1.374 1912 1.38 1913 1.548 1914 1.435 1915 1.32 1916 1.353 1917 1.017 1918 1.309 1919 1.227 1920 1.164 1921 1.213 1922 1.154 1923 1.234 1924 1.233 1925 1.217 1926 1.2 1927 1.27 1928 0.871 1929 0.943 1930 0.916 1931 0.938 1932 0.948 1933 0.825 1934 1.172 1935 1.271 1936 1.232 1937 1.251 1938 1.55 1939 1.535 1940 1.027 1941 1.267 1942 1.197 1943 1.523 1944 1.093 1945 1.224 1946 1.072 1947 0.615 1948 0.916 1949 1.199 1950 1.069 1951 0.942 1952 0.946 1953 1.347 1954 1.053 1955 0.961 1956 1.043 1957 1.05 1958 0.903 1959 0.846 1960 0.726 1961 0.673 1962 0.651 1963 0.507 1964 0.443 1965 0.483 1966 0.477 1967 0.727 1968 0.567 1969 0.366 1970 0.504 1971 0.756 1972 0.844 1973 0.712 1974 0.794 1975 0.916 1976 1.071