# europe_spai036 - Guadarrama Iniesto - 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/4250 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai036 - Guadarrama Iniesto - 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: Guadarrama Iniesto # Location: # Country: Spain # Northernmost_Latitude: 40.8 # Southernmost_Latitude: 40.8 # Easternmost_Longitude: -3.98 # Westernmost_Longitude: -3.98 # Elevation: 1800 m #-------------------- # Data_Collection # Collection_Name: europe_spai036B # Earliest_Year: 1762 # Most_Recent_Year: 1983 # 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":"5.53043103717","T2":"15.4025461042","M1":"0.0225415422378","M2":"0.442793556218"}} #-------------------- # 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 1762 1.103 1763 1.122 1764 0.989 1765 1.042 1766 1.021 1767 1.008 1768 1.022 1769 0.85 1770 0.909 1771 0.86 1772 0.806 1773 1.049 1774 0.862 1775 0.942 1776 0.811 1777 0.866 1778 0.843 1779 0.923 1780 0.919 1781 1.023 1782 0.97 1783 1.082 1784 0.878 1785 0.995 1786 0.976 1787 1.056 1788 1.325 1789 1.114 1790 0.998 1791 1.09 1792 1.089 1793 1.185 1794 1.626 1795 1.305 1796 1.013 1797 0.856 1798 1.038 1799 0.907 1800 0.768 1801 0.81 1802 0.822 1803 0.644 1804 0.779 1805 0.934 1806 0.591 1807 1.049 1808 0.931 1809 1.06 1810 0.947 1811 1.329 1812 1.35 1813 1.408 1814 1.107 1815 1.181 1816 1.004 1817 0.939 1818 1.106 1819 1.249 1820 1.07 1821 1.038 1822 1.076 1823 0.95 1824 0.957 1825 1.178 1826 1.026 1827 1.04 1828 1.228 1829 0.922 1830 0.495 1831 0.812 1832 0.922 1833 1.015 1834 1.179 1835 1.109 1836 1.152 1837 1.291 1838 1.115 1839 0.991 1840 0.978 1841 1.256 1842 1.027 1843 1.044 1844 0.913 1845 0.727 1846 0.869 1847 0.939 1848 0.914 1849 1.028 1850 1.117 1851 0.817 1852 0.791 1853 1.005 1854 1.028 1855 0.824 1856 0.824 1857 0.941 1858 1.119 1859 1.268 1860 0.968 1861 0.95 1862 0.967 1863 0.929 1864 1.176 1865 0.943 1866 0.948 1867 1.215 1868 1.294 1869 1.368 1870 0.87 1871 0.889 1872 0.831 1873 0.931 1874 1.089 1875 0.998 1876 0.684 1877 0.898 1878 0.882 1879 0.763 1880 0.862 1881 0.762 1882 1.025 1883 1.109 1884 1.221 1885 1.167 1886 0.917 1887 0.901 1888 0.95 1889 0.795 1890 0.908 1891 0.865 1892 0.943 1893 1.061 1894 0.732 1895 0.897 1896 0.842 1897 0.867 1898 0.836 1899 0.952 1900 0.865 1901 0.898 1902 1.009 1903 1.408 1904 1.26 1905 1.18 1906 1.234 1907 1.011 1908 0.755 1909 0.88 1910 0.945 1911 1.102 1912 1.225 1913 1.068 1914 1.409 1915 1.201 1916 1.117 1917 1.1 1918 1.098 1919 1.092 1920 0.968 1921 0.706 1922 1.038 1923 1.369 1924 1.04 1925 1.19 1926 1.264 1927 0.951 1928 0.815 1929 0.957 1930 1.089 1931 1.011 1932 0.882 1933 0.896 1934 0.781 1935 0.902 1936 0.741 1937 0.91 1938 0.827 1939 0.739 1940 1.048 1941 0.591 1942 0.488 1943 0.815 1944 0.995 1945 1.115 1946 0.888 1947 0.784 1948 0.686 1949 0.478 1950 0.751 1951 0.506 1952 0.504 1953 0.829 1954 0.815 1955 1.103 1956 1.104 1957 1.388 1958 1.332 1959 1.44 1960 1.131 1961 1.189 1962 0.892 1963 0.603 1964 1.019 1965 0.899 1966 0.861 1967 0.754 1968 0.985 1969 0.987 1970 1.156 1971 1.033 1972 0.777 1973 1.199 1974 0.892 1975 0.931 1976 1.011 1977 1.139 1978 0.986 1979 0.784 1980 1.028 1981 1.066 1982 1.22 1983 1.358