# africa_morc002 - Afechtal - 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/4962 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: africa_morc002 - Afechtal - 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: Afechtal # Location: # Country: Morocco # Northernmost_Latitude: 35.03 # Southernmost_Latitude: 35.03 # Easternmost_Longitude: -4.83 # Westernmost_Longitude: -4.83 # Elevation: 1700 m #-------------------- # Data_Collection # Collection_Name: africa_morc002B # Earliest_Year: 1686 # Most_Recent_Year: 1984 # 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":"5.80231657021","T2":"18.3574843929","M1":"0.022150290951","M2":"0.309790233368"}} #-------------------- # 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 1686 1.065 1687 0.974 1688 0.863 1689 1.204 1690 1.141 1691 1.004 1692 1.086 1693 1.021 1694 0.944 1695 0.829 1696 1.051 1697 1.058 1698 1.318 1699 1.193 1700 1.261 1701 1.25 1702 1.117 1703 0.844 1704 1.057 1705 1.106 1706 0.913 1707 0.882 1708 1.028 1709 0.953 1710 0.861 1711 0.848 1712 0.842 1713 0.791 1714 0.947 1715 1.082 1716 0.719 1717 0.876 1718 0.995 1719 0.955 1720 0.91 1721 1.081 1722 0.977 1723 0.973 1724 0.886 1725 0.695 1726 0.907 1727 0.988 1728 1.0 1729 0.717 1730 1.03 1731 0.625 1732 0.759 1733 0.635 1734 0.845 1735 0.665 1736 0.853 1737 1.047 1738 1.019 1739 0.945 1740 0.849 1741 0.765 1742 0.8 1743 0.901 1744 0.8 1745 0.719 1746 0.637 1747 0.735 1748 0.803 1749 0.885 1750 1.184 1751 0.971 1752 1.048 1753 1.037 1754 1.023 1755 1.057 1756 1.107 1757 1.068 1758 0.849 1759 0.815 1760 1.021 1761 0.869 1762 0.944 1763 0.769 1764 0.756 1765 0.939 1766 0.888 1767 1.118 1768 1.148 1769 0.951 1770 0.99 1771 0.889 1772 1.081 1773 1.354 1774 0.978 1775 1.302 1776 0.897 1777 0.989 1778 0.751 1779 1.125 1780 1.036 1781 1.227 1782 1.051 1783 1.184 1784 0.799 1785 0.932 1786 0.978 1787 1.033 1788 1.037 1789 0.975 1790 1.231 1791 1.303 1792 1.103 1793 0.997 1794 1.009 1795 1.102 1796 0.826 1797 0.856 1798 0.881 1799 1.041 1800 0.89 1801 0.994 1802 0.874 1803 0.813 1804 0.81 1805 1.042 1806 0.75 1807 1.043 1808 0.88 1809 1.036 1810 1.021 1811 1.202 1812 1.09 1813 1.239 1814 1.215 1815 1.436 1816 1.155 1817 1.04 1818 0.775 1819 0.736 1820 0.407 1821 0.801 1822 1.023 1823 1.247 1824 1.117 1825 1.348 1826 1.312 1827 1.222 1828 1.196 1829 1.092 1830 1.108 1831 1.018 1832 1.194 1833 1.222 1834 1.441 1835 1.587 1836 1.119 1837 1.245 1838 1.143 1839 0.947 1840 0.998 1841 1.153 1842 0.879 1843 1.29 1844 1.027 1845 1.174 1846 1.059 1847 0.995 1848 1.034 1849 1.174 1850 1.268 1851 1.038 1852 1.065 1853 0.874 1854 1.001 1855 0.97 1856 0.734 1857 0.898 1858 1.096 1859 1.013 1860 0.925 1861 1.145 1862 0.964 1863 0.869 1864 1.168 1865 0.893 1866 0.94 1867 0.855 1868 1.246 1869 1.061 1870 0.899 1871 1.122 1872 0.922 1873 1.011 1874 1.015 1875 0.906 1876 0.802 1877 0.945 1878 0.88 1879 0.689 1880 0.837 1881 1.103 1882 0.791 1883 0.987 1884 1.084 1885 1.107 1886 1.028 1887 1.039 1888 0.877 1889 1.004 1890 0.883 1891 1.081 1892 0.901 1893 0.535 1894 0.574 1895 0.779 1896 0.762 1897 0.714 1898 0.774 1899 0.874 1900 0.665 1901 0.715 1902 0.75 1903 0.923 1904 0.908 1905 1.051 1906 0.702 1907 0.733 1908 0.462 1909 0.753 1910 0.536 1911 0.638 1912 0.734 1913 0.67 1914 0.59 1915 0.621 1916 0.323 1917 0.508 1918 0.569 1919 0.726 1920 0.831 1921 0.893 1922 1.101 1923 0.817 1924 0.677 1925 0.847 1926 0.752 1927 0.689 1928 0.624 1929 0.856 1930 1.1 1931 0.931 1932 1.114 1933 0.798 1934 0.71 1935 0.926 1936 0.753 1937 0.495 1938 0.37 1939 0.778 1940 1.08 1941 0.973 1942 0.928 1943 0.907 1944 1.09 1945 0.89 1946 0.786 1947 0.901 1948 0.889 1949 1.042 1950 0.878 1951 0.832 1952 0.968 1953 0.984 1954 0.913 1955 1.013 1956 0.834 1957 0.972 1958 1.101 1959 1.17 1960 1.315 1961 1.371 1962 1.386 1963 1.434 1964 1.352 1965 1.459 1966 1.585 1967 1.513 1968 1.33 1969 1.356 1970 1.174 1971 1.167 1972 1.19 1973 1.444 1974 1.244 1975 1.171 1976 1.373 1977 1.41 1978 1.507 1979 1.283 1980 1.214 1981 1.179 1982 1.311 1983 1.568 1984 1.534