# europe_spai047 - Urbion Covaleda - 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/4262 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai047 - Urbion Covaleda - 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: Urbion Covaleda # Location: # Country: Spain # Northernmost_Latitude: 41.98 # Southernmost_Latitude: 41.98 # Easternmost_Longitude: -2.87 # Westernmost_Longitude: -2.87 # Elevation: 1750 m #-------------------- # Data_Collection # Collection_Name: europe_spai047B # Earliest_Year: 1602 # Most_Recent_Year: 1983 # 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":"4.61189023479","T2":"18.749751621","M1":"0.0223236549306","M2":"0.245309218375"}} #-------------------- # 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 1602 0.994 1603 1.065 1604 1.158 1605 1.014 1606 1.004 1607 1.166 1608 1.064 1609 1.056 1610 1.039 1611 0.869 1612 0.903 1613 0.853 1614 0.913 1615 1.123 1616 1.307 1617 1.217 1618 1.191 1619 1.137 1620 0.918 1621 0.804 1622 0.915 1623 0.881 1624 0.925 1625 1.057 1626 0.665 1627 0.515 1628 0.038 1629 0.264 1630 0.272 1631 0.333 1632 0.48 1633 0.559 1634 0.557 1635 0.64 1636 0.748 1637 0.84 1638 0.866 1639 1.005 1640 0.951 1641 1.092 1642 0.954 1643 0.787 1644 1.095 1645 1.232 1646 1.369 1647 1.181 1648 0.956 1649 0.929 1650 1.091 1651 1.085 1652 1.307 1653 1.081 1654 1.266 1655 1.442 1656 1.306 1657 1.251 1658 0.691 1659 0.721 1660 1.012 1661 0.886 1662 0.869 1663 0.781 1664 0.794 1665 0.744 1666 0.942 1667 0.963 1668 0.941 1669 0.762 1670 1.13 1671 1.277 1672 1.115 1673 1.232 1674 1.081 1675 1.08 1676 1.383 1677 1.159 1678 0.908 1679 0.946 1680 1.255 1681 0.868 1682 0.878 1683 1.116 1684 1.23 1685 1.197 1686 1.037 1687 1.043 1688 1.089 1689 1.459 1690 1.386 1691 1.373 1692 1.102 1693 1.046 1694 1.056 1695 0.91 1696 1.003 1697 0.677 1698 0.828 1699 1.09 1700 1.055 1701 1.107 1702 1.108 1703 1.04 1704 1.009 1705 1.001 1706 1.028 1707 0.659 1708 0.62 1709 0.693 1710 0.911 1711 0.928 1712 0.965 1713 0.899 1714 1.033 1715 1.316 1716 1.043 1717 1.047 1718 1.038 1719 1.138 1720 1.112 1721 1.262 1722 1.229 1723 1.122 1724 1.023 1725 0.759 1726 0.888 1727 0.424 1728 0.496 1729 0.556 1730 0.78 1731 0.718 1732 1.016 1733 1.113 1734 1.426 1735 1.097 1736 1.09 1737 1.498 1738 1.472 1739 1.284 1740 1.134 1741 1.1 1742 1.118 1743 1.177 1744 0.898 1745 1.083 1746 1.065 1747 1.309 1748 1.472 1749 1.203 1750 1.296 1751 0.928 1752 0.887 1753 1.058 1754 1.154 1755 1.296 1756 1.55 1757 1.482 1758 1.226 1759 1.38 1760 0.973 1761 1.066 1762 1.258 1763 1.157 1764 1.054 1765 0.796 1766 0.895 1767 1.018 1768 1.088 1769 1.09 1770 1.03 1771 1.056 1772 0.871 1773 1.016 1774 0.879 1775 0.964 1776 1.038 1777 1.261 1778 1.075 1779 1.019 1780 1.146 1781 1.396 1782 1.276 1783 1.305 1784 1.192 1785 1.12 1786 1.137 1787 1.195 1788 1.476 1789 1.181 1790 0.994 1791 1.002 1792 0.89 1793 1.134 1794 1.371 1795 1.299 1796 0.986 1797 0.965 1798 1.193 1799 0.858 1800 0.662 1801 0.673 1802 0.568 1803 0.273 1804 0.379 1805 0.561 1806 0.499 1807 0.705 1808 0.68 1809 0.675 1810 0.785 1811 0.894 1812 0.895 1813 1.047 1814 1.176 1815 1.127 1816 0.856 1817 0.814 1818 0.954 1819 1.066 1820 0.931 1821 0.867 1822 1.006 1823 1.027 1824 0.848 1825 1.161 1826 1.041 1827 0.864 1828 1.079 1829 1.106 1830 0.99 1831 0.827 1832 0.742 1833 0.87 1834 1.193 1835 1.123 1836 0.996 1837 1.317 1838 1.232 1839 0.989 1840 0.914 1841 0.965 1842 0.872 1843 0.946 1844 0.766 1845 0.856 1846 0.942 1847 0.819 1848 0.787 1849 0.933 1850 1.172 1851 0.965 1852 0.871 1853 0.991 1854 0.999 1855 0.812 1856 0.803 1857 0.864 1858 0.773 1859 1.137 1860 0.973 1861 1.053 1862 0.939 1863 0.895 1864 1.321 1865 1.062 1866 0.834 1867 0.76 1868 0.98 1869 1.066 1870 1.042 1871 1.085 1872 0.949 1873 0.834 1874 0.721 1875 0.768 1876 0.875 1877 1.111 1878 1.16 1879 0.785 1880 0.884 1881 0.814 1882 0.824 1883 0.807 1884 0.887 1885 0.967 1886 0.97 1887 1.019 1888 1.03 1889 0.984 1890 0.809 1891 0.877 1892 0.954 1893 1.179 1894 0.879 1895 0.944 1896 0.905 1897 0.842 1898 0.872 1899 1.035 1900 0.935 1901 1.091 1902 1.252 1903 1.341 1904 1.218 1905 1.141 1906 1.036 1907 0.997 1908 0.872 1909 0.901 1910 0.924 1911 1.262 1912 0.974 1913 0.985 1914 1.18 1915 1.063 1916 1.026 1917 0.885 1918 0.765 1919 0.825 1920 0.887 1921 0.826 1922 0.576 1923 0.939 1924 0.787 1925 0.875 1926 0.927 1927 0.938 1928 0.886 1929 1.051 1930 1.1 1931 1.109 1932 1.239 1933 1.294 1934 0.983 1935 0.848 1936 1.051 1937 0.959 1938 0.752 1939 0.769 1940 0.954 1941 0.751 1942 0.772 1943 0.891 1944 1.113 1945 1.095 1946 0.775 1947 0.779 1948 1.203 1949 1.182 1950 1.149 1951 1.248 1952 1.141 1953 1.217 1954 0.919 1955 0.909 1956 0.959 1957 0.981 1958 1.116 1959 1.196 1960 1.013 1961 1.073 1962 0.682 1963 0.495 1964 0.977 1965 0.886 1966 0.726 1967 0.76 1968 0.753 1969 0.787 1970 1.111 1971 1.117 1972 0.911 1973 1.312 1974 1.07 1975 0.971 1976 0.941 1977 0.969 1978 0.941 1979 0.637 1980 0.784 1981 0.868 1982 0.72 1983 0.957