# africa_morc003 - Ta'Adlount - 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/4992 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: africa_morc003 - Ta'Adlount - 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: Ta'Adlount # Location: # Country: Morocco # Northernmost_Latitude: 32.38 # Southernmost_Latitude: 32.38 # Easternmost_Longitude: -5.6 # Westernmost_Longitude: -5.6 # Elevation: 2200 m #-------------------- # Data_Collection # Collection_Name: africa_morc003B # Earliest_Year: 1755 # Most_Recent_Year: 1984 # 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":"3.96860437938","T2":"16.8837525101","M1":"0.0232703304855","M2":"0.455145247035"}} #-------------------- # Species # Species_Name: Atlantic cedar # Species_Code: CDAT #-------------------- # 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 1755 1.037 1756 0.839 1757 0.99 1758 1.017 1759 0.865 1760 1.04 1761 0.993 1762 1.219 1763 1.156 1764 0.631 1765 0.731 1766 0.936 1767 1.101 1768 1.005 1769 1.231 1770 1.0 1771 0.916 1772 1.036 1773 1.089 1774 1.103 1775 1.198 1776 1.131 1777 1.132 1778 1.166 1779 0.795 1780 0.884 1781 0.96 1782 0.996 1783 1.185 1784 1.293 1785 1.218 1786 1.37 1787 1.22 1788 1.332 1789 1.034 1790 1.276 1791 1.054 1792 1.229 1793 1.142 1794 0.936 1795 0.968 1796 0.871 1797 0.94 1798 0.875 1799 1.009 1800 0.641 1801 0.594 1802 0.602 1803 0.834 1804 0.91 1805 0.939 1806 0.871 1807 0.96 1808 1.075 1809 1.201 1810 1.059 1811 1.19 1812 1.025 1813 1.094 1814 1.328 1815 1.333 1816 1.19 1817 0.84 1818 1.021 1819 1.073 1820 0.915 1821 1.1 1822 0.974 1823 0.998 1824 0.631 1825 0.453 1826 0.911 1827 0.932 1828 0.756 1829 0.931 1830 1.037 1831 0.903 1832 1.08 1833 1.125 1834 0.936 1835 1.202 1836 0.931 1837 1.438 1838 0.971 1839 0.89 1840 1.028 1841 0.999 1842 0.875 1843 0.746 1844 0.898 1845 0.933 1846 1.122 1847 1.054 1848 1.089 1849 1.23 1850 0.947 1851 1.245 1852 1.069 1853 1.208 1854 1.046 1855 1.297 1856 1.139 1857 0.986 1858 0.895 1859 0.871 1860 1.047 1861 1.005 1862 1.076 1863 1.036 1864 1.117 1865 1.102 1866 0.932 1867 0.608 1868 0.679 1869 0.771 1870 1.118 1871 0.985 1872 0.959 1873 1.042 1874 0.318 1875 1.107 1876 0.974 1877 0.739 1878 0.239 1879 0.749 1880 0.864 1881 0.697 1882 0.188 1883 0.649 1884 0.612 1885 0.763 1886 0.782 1887 0.485 1888 1.039 1889 0.888 1890 0.851 1891 0.82 1892 0.534 1893 0.798 1894 0.796 1895 0.833 1896 0.86 1897 0.372 1898 0.727 1899 0.782 1900 0.988 1901 1.251 1902 1.098 1903 1.162 1904 0.938 1905 0.501 1906 1.02 1907 0.894 1908 0.9 1909 0.918 1910 0.883 1911 0.85 1912 1.054 1913 1.006 1914 1.183 1915 1.174 1916 1.054 1917 1.278 1918 1.204 1919 1.115 1920 1.107 1921 1.297 1922 1.558 1923 1.266 1924 1.228 1925 1.331 1926 1.016 1927 1.091 1928 1.14 1929 1.279 1930 1.441 1931 0.932 1932 1.13 1933 0.871 1934 0.889 1935 0.956 1936 1.168 1937 0.659 1938 0.98 1939 1.129 1940 1.07 1941 1.284 1942 1.203 1943 1.185 1944 1.178 1945 0.004 1946 1.209 1947 1.165 1948 1.129 1949 1.092 1950 0.946 1951 1.038 1952 0.775 1953 0.928 1954 1.129 1955 1.365 1956 1.064 1957 0.824 1958 1.237 1959 1.162 1960 1.617 1961 1.527 1962 1.317 1963 1.481 1964 1.146 1965 1.22 1966 0.515 1967 0.888 1968 0.862 1969 1.235 1970 1.088 1971 0.994 1972 1.026 1973 1.11 1974 1.062 1975 1.31 1976 1.379 1977 0.886 1978 1.321 1979 0.864 1980 0.918 1981 0.597 1982 0.643 1983 0.163 1984 0.382