# europe_spai011 - Torreton - 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/3292 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai011 - Torreton - 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: Torreton # Location: # Country: Spain # Northernmost_Latitude: 40.18 # Southernmost_Latitude: 40.18 # Easternmost_Longitude: -2.08 # Westernmost_Longitude: -2.08 # Elevation: 1500 m #-------------------- # Data_Collection # Collection_Name: europe_spai011B # Earliest_Year: 1485 # Most_Recent_Year: 1988 # 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":"4.44335543042","T2":"16.3506990063","M1":"0.022282203604","M2":"0.44509708202"}} #-------------------- # Species # Species_Name: Austrian pine # Species_Code: PINI #-------------------- # 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 1485 1.028 1486 0.814 1487 0.817 1488 0.714 1489 0.754 1490 0.898 1491 1.002 1492 1.068 1493 0.848 1494 1.281 1495 1.288 1496 1.368 1497 1.73 1498 1.948 1499 1.914 1500 0.633 1501 1.136 1502 0.393 1503 0.732 1504 0.74 1505 0.919 1506 0.782 1507 0.675 1508 0.646 1509 0.914 1510 0.623 1511 0.863 1512 0.546 1513 0.69 1514 0.841 1515 0.645 1516 0.636 1517 0.638 1518 0.798 1519 0.625 1520 0.581 1521 0.859 1522 0.886 1523 0.802 1524 0.811 1525 0.891 1526 0.977 1527 1.465 1528 1.166 1529 1.026 1530 1.207 1531 1.542 1532 0.602 1533 0.591 1534 0.711 1535 1.015 1536 0.931 1537 0.915 1538 1.256 1539 1.306 1540 1.618 1541 1.458 1542 1.503 1543 2.029 1544 1.351 1545 0.748 1546 0.734 1547 1.328 1548 1.594 1549 1.118 1550 1.159 1551 0.836 1552 1.403 1553 0.903 1554 0.584 1555 0.973 1556 1.18 1557 1.439 1558 1.675 1559 1.222 1560 0.39 1561 0.503 1562 0.252 1563 0.317 1564 0.381 1565 0.865 1566 0.975 1567 0.915 1568 1.085 1569 0.952 1570 1.082 1571 1.204 1572 0.856 1573 0.977 1574 0.888 1575 1.039 1576 0.956 1577 0.929 1578 1.018 1579 0.81 1580 0.806 1581 0.364 1582 0.529 1583 0.663 1584 0.823 1585 0.937 1586 1.179 1587 1.184 1588 1.245 1589 0.903 1590 0.428 1591 0.518 1592 1.231 1593 1.207 1594 0.953 1595 1.193 1596 0.839 1597 0.69 1598 0.871 1599 1.11 1600 1.165 1601 0.575 1602 1.152 1603 1.478 1604 1.157 1605 1.312 1606 1.126 1607 1.132 1608 1.781 1609 1.312 1610 1.091 1611 0.951 1612 0.995 1613 1.466 1614 1.564 1615 0.795 1616 1.008 1617 1.188 1618 1.258 1619 1.178 1620 1.22 1621 1.074 1622 1.245 1623 1.022 1624 0.66 1625 0.865 1626 0.603 1627 0.644 1628 0.697 1629 0.962 1630 1.208 1631 0.737 1632 1.071 1633 0.722 1634 1.122 1635 1.525 1636 1.116 1637 1.155 1638 1.002 1639 0.911 1640 0.918 1641 0.841 1642 0.981 1643 1.349 1644 1.286 1645 1.102 1646 0.986 1647 1.116 1648 1.073 1649 0.766 1650 0.817 1651 1.14 1652 0.823 1653 1.005 1654 0.847 1655 0.882 1656 1.503 1657 1.152 1658 1.064 1659 0.696 1660 1.031 1661 0.936 1662 1.138 1663 1.078 1664 0.994 1665 0.759 1666 1.091 1667 1.228 1668 0.735 1669 0.683 1670 1.06 1671 1.537 1672 1.067 1673 0.988 1674 1.159 1675 0.778 1676 0.801 1677 0.876 1678 1.061 1679 0.766 1680 0.901 1681 1.11 1682 1.206 1683 0.873 1684 0.436 1685 0.622 1686 1.031 1687 1.122 1688 0.916 1689 0.858 1690 1.296 1691 1.136 1692 1.273 1693 1.172 1694 1.246 1695 1.178 1696 0.875 1697 1.301 1698 1.073 1699 1.216 1700 1.329 1701 1.209 1702 1.378 1703 1.639 1704 1.067 1705 0.784 1706 0.867 1707 0.926 1708 0.611 1709 0.602 1710 0.787 1711 1.086 1712 0.956 1713 0.891 1714 0.597 1715 1.208 1716 1.23 1717 0.547 1718 0.604 1719 0.976 1720 1.111 1721 1.038 1722 1.358 1723 1.285 1724 1.181 1725 0.358 1726 0.442 1727 0.541 1728 0.621 1729 0.62 1730 0.812 1731 0.816 1732 0.595 1733 0.738 1734 0.728 1735 0.759 1736 1.038 1737 0.68 1738 0.671 1739 1.04 1740 1.123 1741 0.766 1742 0.801 1743 0.955 1744 0.709 1745 1.174 1746 0.772 1747 1.128 1748 0.93 1749 0.769 1750 0.925 1751 0.615 1752 0.497 1753 0.443 1754 0.494 1755 0.762 1756 0.931 1757 0.95 1758 0.897 1759 1.123 1760 1.17 1761 1.119 1762 1.336 1763 1.591 1764 1.072 1765 1.023 1766 0.785 1767 0.885 1768 0.633 1769 0.528 1770 0.574 1771 0.764 1772 0.964 1773 1.136 1774 0.966 1775 1.038 1776 1.2 1777 1.016 1778 0.702 1779 0.594 1780 0.528 1781 0.969 1782 0.911 1783 1.137 1784 1.435 1785 1.027 1786 0.635 1787 1.017 1788 1.22 1789 0.853 1790 0.892 1791 1.377 1792 1.286 1793 1.179 1794 1.386 1795 1.571 1796 1.872 1797 1.221 1798 1.036 1799 1.057 1800 1.01 1801 1.209 1802 1.173 1803 0.508 1804 0.867 1805 0.794 1806 0.693 1807 0.818 1808 0.817 1809 1.072 1810 1.224 1811 1.185 1812 0.944 1813 1.463 1814 1.509 1815 1.538 1816 1.007 1817 1.118 1818 1.363 1819 1.453 1820 1.108 1821 1.173 1822 0.909 1823 0.871 1824 0.702 1825 0.961 1826 1.092 1827 1.055 1828 1.001 1829 0.944 1830 0.806 1831 0.655 1832 0.996 1833 0.882 1834 1.153 1835 0.807 1836 0.683 1837 0.998 1838 0.822 1839 0.915 1840 0.752 1841 0.816 1842 0.551 1843 0.546 1844 0.712 1845 0.99 1846 1.048 1847 0.717 1848 0.833 1849 0.978 1850 1.315 1851 0.914 1852 0.754 1853 0.737 1854 1.054 1855 0.872 1856 1.193 1857 1.051 1858 0.912 1859 0.986 1860 0.836 1861 0.873 1862 0.941 1863 0.933 1864 0.964 1865 1.006 1866 1.068 1867 0.819 1868 0.753 1869 0.812 1870 0.68 1871 0.756 1872 0.804 1873 0.778 1874 0.915 1875 1.089 1876 0.978 1877 1.34 1878 1.148 1879 0.544 1880 0.835 1881 0.959 1882 0.951 1883 1.115 1884 1.17 1885 1.566 1886 1.405 1887 0.958 1888 1.249 1889 1.294 1890 1.015 1891 0.975 1892 1.269 1893 0.861 1894 0.814 1895 0.635 1896 0.642 1897 0.788 1898 0.721 1899 0.802 1900 0.494 1901 0.595 1902 0.711 1903 0.935 1904 0.927 1905 0.989 1906 0.884 1907 1.028 1908 1.222 1909 0.938 1910 1.032 1911 1.044 1912 1.194 1913 1.363 1914 1.297 1915 0.917 1916 1.065 1917 0.852 1918 0.988 1919 1.279 1920 1.064 1921 1.092 1922 1.053 1923 0.883 1924 0.814 1925 1.083 1926 1.104 1927 0.876 1928 0.899 1929 0.943 1930 0.921 1931 0.799 1932 1.095 1933 1.143 1934 0.816 1935 0.792 1936 1.063 1937 1.389 1938 1.295 1939 1.292 1940 1.908 1941 1.306 1942 1.019 1943 1.149 1944 1.211 1945 1.087 1946 0.914 1947 0.989 1948 1.159 1949 0.861 1950 1.173 1951 1.185 1952 1.622 1953 1.188 1954 1.029 1955 1.052 1956 0.983 1957 0.943 1958 0.93 1959 1.289 1960 1.453 1961 1.391 1962 1.108 1963 0.822 1964 0.826 1965 0.653 1966 0.901 1967 0.649 1968 0.597 1969 0.509 1970 0.603 1971 0.611 1972 0.757 1973 1.073 1974 0.908 1975 1.204 1976 1.108 1977 1.213 1978 1.062 1979 1.203 1980 1.318 1981 0.663 1982 1.078 1983 0.95 1984 0.759 1985 1.102 1986 0.834 1987 1.152 1988 1.217