# africa_morc012 - Tissouka - 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/2938 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: africa_morc012 - Tissouka - 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: Tissouka # Location: # Country: Morocco # Northernmost_Latitude: 35.12 # Southernmost_Latitude: 35.12 # Easternmost_Longitude: -5.1 # Westernmost_Longitude: -5.1 # Elevation: 1700 m #-------------------- # Data_Collection # Collection_Name: africa_morc012B # Earliest_Year: 1813 # 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":"5.72424181336","T2":"17.5575216091","M1":"0.0224985019451","M2":"0.387719574539"}} #-------------------- # 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 1813 0.839 1814 0.876 1815 1.183 1816 1.004 1817 1.026 1818 1.069 1819 1.141 1820 0.777 1821 0.879 1822 1.023 1823 1.058 1824 0.968 1825 1.039 1826 1.061 1827 0.929 1828 1.026 1829 0.93 1830 0.898 1831 0.774 1832 1.091 1833 0.92 1834 1.16 1835 1.205 1836 1.139 1837 1.233 1838 0.936 1839 0.941 1840 0.939 1841 1.088 1842 0.936 1843 1.446 1844 1.178 1845 0.963 1846 0.91 1847 1.018 1848 0.983 1849 1.015 1850 1.344 1851 1.271 1852 1.021 1853 1.056 1854 1.238 1855 1.019 1856 0.96 1857 0.925 1858 1.125 1859 0.951 1860 0.92 1861 1.011 1862 1.082 1863 1.19 1864 1.266 1865 1.139 1866 1.19 1867 0.971 1868 1.252 1869 1.367 1870 1.017 1871 0.866 1872 0.848 1873 1.105 1874 1.063 1875 1.012 1876 0.953 1877 0.957 1878 0.854 1879 0.677 1880 0.827 1881 1.076 1882 0.76 1883 0.806 1884 1.007 1885 0.934 1886 0.849 1887 0.966 1888 0.831 1889 0.79 1890 0.902 1891 1.057 1892 0.905 1893 0.847 1894 0.823 1895 0.958 1896 0.866 1897 1.131 1898 1.012 1899 1.144 1900 0.802 1901 0.965 1902 0.903 1903 1.104 1904 1.008 1905 0.967 1906 0.853 1907 0.638 1908 0.888 1909 0.804 1910 0.772 1911 0.815 1912 0.871 1913 0.903 1914 1.251 1915 0.785 1916 0.781 1917 0.675 1918 0.538 1919 0.678 1920 0.759 1921 0.639 1922 0.861 1923 0.76 1924 0.735 1925 0.815 1926 0.868 1927 0.86 1928 0.62 1929 0.751 1930 0.899 1931 0.578 1932 0.741 1933 0.665 1934 0.435 1935 0.553 1936 0.436 1937 0.64 1938 0.636 1939 0.68 1940 0.86 1941 0.656 1942 0.565 1943 0.575 1944 0.835 1945 0.78 1946 0.536 1947 0.877 1948 0.533 1949 0.604 1950 0.661 1951 0.814 1952 1.032 1953 1.082 1954 1.417 1955 1.107 1956 1.137 1957 1.091 1958 1.356 1959 1.285 1960 1.478 1961 1.524 1962 1.053 1963 1.201 1964 1.319 1965 1.121 1966 1.23 1967 1.474 1968 1.154 1969 1.138 1970 1.691 1971 1.146 1972 1.397 1973 1.576 1974 1.199 1975 1.133 1976 1.201 1977 1.822 1978 1.866 1979 1.354 1980 1.222 1981 1.044 1982 1.079 1983 1.295 1984 0.905