# europe_spai038 - Guadarrama Rascafria - 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/4252 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai038 - Guadarrama Rascafria - 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 Rascafria # Location: # Country: Spain # Northernmost_Latitude: 40.8 # Southernmost_Latitude: 40.8 # Easternmost_Longitude: -3.95 # Westernmost_Longitude: -3.95 # Elevation: 1850 m #-------------------- # Data_Collection # Collection_Name: europe_spai038B # Earliest_Year: 1697 # 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":"5.19973076259","T2":"15.9375161234","M1":"0.0224387027748","M2":"0.313480680568"}} #-------------------- # 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 1697 0.822 1698 0.658 1699 0.839 1700 0.879 1701 1.021 1702 1.044 1703 1.016 1704 1.015 1705 1.063 1706 1.332 1707 0.936 1708 0.915 1709 0.946 1710 1.264 1711 1.164 1712 0.989 1713 0.933 1714 0.993 1715 1.249 1716 0.92 1717 0.937 1718 1.074 1719 0.945 1720 0.864 1721 1.029 1722 0.914 1723 1.146 1724 0.917 1725 0.748 1726 0.925 1727 1.129 1728 0.927 1729 0.955 1730 1.195 1731 0.706 1732 1.12 1733 0.909 1734 1.352 1735 0.85 1736 0.974 1737 1.443 1738 1.144 1739 0.867 1740 0.812 1741 0.873 1742 0.888 1743 0.664 1744 0.818 1745 0.951 1746 0.696 1747 0.864 1748 1.016 1749 0.752 1750 1.119 1751 0.942 1752 0.956 1753 1.049 1754 0.888 1755 0.985 1756 0.952 1757 1.027 1758 0.519 1759 0.758 1760 1.039 1761 1.163 1762 1.411 1763 1.105 1764 0.888 1765 0.871 1766 0.886 1767 0.811 1768 0.806 1769 0.965 1770 0.946 1771 0.647 1772 0.841 1773 1.032 1774 0.867 1775 0.84 1776 0.958 1777 0.954 1778 0.777 1779 0.862 1780 1.007 1781 1.074 1782 0.976 1783 1.138 1784 0.746 1785 0.778 1786 0.974 1787 0.943 1788 1.437 1789 1.221 1790 0.879 1791 1.155 1792 1.048 1793 1.191 1794 1.393 1795 1.271 1796 1.049 1797 0.886 1798 1.136 1799 0.978 1800 0.827 1801 1.004 1802 0.813 1803 0.751 1804 0.603 1805 0.956 1806 0.862 1807 1.321 1808 1.158 1809 0.901 1810 0.929 1811 1.021 1812 0.951 1813 1.061 1814 1.151 1815 1.003 1816 0.883 1817 1.051 1818 0.928 1819 1.053 1820 1.053 1821 1.18 1822 1.174 1823 1.073 1824 1.003 1825 1.161 1826 0.982 1827 1.019 1828 1.446 1829 1.299 1830 1.23 1831 0.884 1832 0.821 1833 1.123 1834 1.28 1835 1.088 1836 0.985 1837 1.446 1838 1.245 1839 0.934 1840 0.958 1841 1.21 1842 0.982 1843 0.91 1844 0.804 1845 0.563 1846 0.867 1847 0.933 1848 0.976 1849 1.027 1850 1.082 1851 0.94 1852 0.786 1853 1.022 1854 1.233 1855 0.888 1856 0.772 1857 0.867 1858 0.984 1859 1.183 1860 1.109 1861 1.039 1862 0.938 1863 0.923 1864 1.482 1865 1.166 1866 1.108 1867 1.231 1868 1.213 1869 1.162 1870 1.205 1871 1.324 1872 1.121 1873 1.157 1874 1.149 1875 1.033 1876 0.915 1877 0.743 1878 0.698 1879 0.607 1880 0.673 1881 0.92 1882 1.129 1883 0.933 1884 0.919 1885 1.05 1886 0.926 1887 0.991 1888 1.09 1889 1.268 1890 1.117 1891 1.021 1892 1.183 1893 1.415 1894 0.889 1895 1.037 1896 0.773 1897 0.82 1898 0.893 1899 0.853 1900 0.807 1901 0.989 1902 1.156 1903 1.08 1904 1.239 1905 1.102 1906 1.166 1907 1.013 1908 0.716 1909 0.905 1910 0.974 1911 0.904 1912 0.959 1913 0.898 1914 1.222 1915 1.088 1916 0.913 1917 1.161 1918 1.074 1919 1.022 1920 0.73 1921 0.503 1922 0.752 1923 1.273 1924 0.899 1925 0.909 1926 0.853 1927 0.873 1928 0.614 1929 0.903 1930 0.899 1931 0.969 1932 1.098 1933 1.213 1934 0.989 1935 0.858 1936 0.988 1937 0.97 1938 0.788 1939 1.034 1940 1.262 1941 0.677 1942 0.66 1943 1.103 1944 1.291 1945 1.139 1946 0.763 1947 1.02 1948 0.715 1949 0.831 1950 0.963 1951 1.123 1952 1.066 1953 1.229 1954 0.867 1955 1.022 1956 1.182 1957 1.413 1958 1.215 1959 1.16 1960 1.166 1961 1.086 1962 0.49 1963 0.35 1964 0.896 1965 0.829 1966 0.663 1967 0.635 1968 0.732 1969 0.935 1970 1.027 1971 1.022 1972 0.877 1973 1.194 1974 1.102 1975 0.844 1976 1.318 1977 1.08 1978 0.906 1979 0.875 1980 1.192 1981 1.438 1982 1.078 1983 1.121 1984 0.869