# europe_turk042 - Neseli - 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/5557 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_turk042 - Neseli - 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: Neseli # Location: # Country: Turkey # Northernmost_Latitude: 37.2 # Southernmost_Latitude: 37.2 # Easternmost_Longitude: 34.47 # Westernmost_Longitude: 34.47 # Elevation: 1725 m #-------------------- # Data_Collection # Collection_Name: europe_turk042B # Earliest_Year: 1235 # Most_Recent_Year: 2001 # 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":"3.62099253143","T2":"15.8239449369","M1":"0.0224325336868","M2":"0.410698521293"}} #-------------------- # Species # Species_Name: Greek juniper # Species_Code: JUEX #-------------------- # 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 1235 0.846 1236 0.991 1237 0.927 1238 0.998 1239 1.102 1240 1.323 1241 1.41 1242 1.216 1243 0.973 1244 1.101 1245 0.995 1246 0.952 1247 0.922 1248 1.024 1249 1.143 1250 1.024 1251 0.779 1252 0.914 1253 1.021 1254 1.049 1255 1.2 1256 0.981 1257 0.758 1258 0.759 1259 0.837 1260 0.843 1261 1.02 1262 0.83 1263 1.129 1264 1.257 1265 1.32 1266 1.133 1267 1.025 1268 0.903 1269 0.795 1270 0.924 1271 0.993 1272 0.742 1273 0.995 1274 1.008 1275 0.697 1276 0.691 1277 0.877 1278 0.855 1279 0.935 1280 0.962 1281 0.849 1282 0.892 1283 0.831 1284 0.996 1285 1.088 1286 1.538 1287 1.203 1288 0.984 1289 0.909 1290 0.927 1291 0.902 1292 1.068 1293 0.969 1294 0.892 1295 1.168 1296 0.986 1297 1.21 1298 1.324 1299 1.283 1300 1.1 1301 0.946 1302 0.856 1303 0.663 1304 0.893 1305 1.218 1306 1.175 1307 1.004 1308 1.174 1309 1.157 1310 1.707 1311 1.08 1312 1.243 1313 0.971 1314 1.035 1315 0.955 1316 0.912 1317 0.812 1318 1.066 1319 1.384 1320 1.403 1321 1.086 1322 1.024 1323 0.778 1324 0.677 1325 0.713 1326 0.811 1327 1.043 1328 1.237 1329 1.273 1330 1.431 1331 1.33 1332 1.342 1333 1.225 1334 1.01 1335 1.146 1336 0.925 1337 0.659 1338 0.861 1339 1.151 1340 0.993 1341 1.297 1342 1.166 1343 1.021 1344 0.939 1345 1.216 1346 1.199 1347 1.262 1348 1.302 1349 1.098 1350 0.881 1351 0.978 1352 0.844 1353 0.765 1354 0.779 1355 0.6 1356 0.709 1357 0.617 1358 0.568 1359 0.81 1360 0.706 1361 0.823 1362 0.78 1363 1.219 1364 0.838 1365 0.985 1366 0.57 1367 0.838 1368 0.921 1369 0.922 1370 0.951 1371 0.691 1372 1.046 1373 1.333 1374 1.378 1375 0.653 1376 0.923 1377 1.191 1378 0.911 1379 1.204 1380 0.911 1381 1.266 1382 1.241 1383 0.849 1384 0.941 1385 1.158 1386 0.918 1387 1.108 1388 1.119 1389 0.815 1390 1.349 1391 0.689 1392 0.868 1393 1.425 1394 1.053 1395 0.695 1396 0.738 1397 0.758 1398 0.923 1399 0.945 1400 0.733 1401 0.794 1402 1.173 1403 0.917 1404 1.041 1405 1.101 1406 0.92 1407 0.825 1408 1.073 1409 0.926 1410 0.805 1411 1.071 1412 1.037 1413 0.647 1414 0.653 1415 0.806 1416 0.694 1417 0.849 1418 0.864 1419 0.587 1420 0.894 1421 1.077 1422 1.036 1423 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1515 0.884 1516 1.021 1517 0.763 1518 1.297 1519 1.781 1520 1.158 1521 1.188 1522 1.21 1523 1.417 1524 1.197 1525 1.201 1526 1.044 1527 1.056 1528 1.02 1529 1.03 1530 1.032 1531 0.892 1532 1.166 1533 1.183 1534 1.455 1535 1.197 1536 1.119 1537 0.933 1538 0.911 1539 1.308 1540 0.696 1541 0.833 1542 0.83 1543 1.047 1544 1.402 1545 1.206 1546 0.833 1547 1.023 1548 0.745 1549 0.755 1550 1.314 1551 0.768 1552 1.022 1553 1.095 1554 1.362 1555 1.299 1556 1.292 1557 1.027 1558 0.672 1559 0.968 1560 1.09 1561 0.582 1562 1.114 1563 0.948 1564 1.058 1565 1.509 1566 1.526 1567 0.809 1568 0.826 1569 1.084 1570 0.744 1571 0.805 1572 0.841 1573 1.171 1574 1.479 1575 1.341 1576 1.18 1577 1.053 1578 1.009 1579 1.002 1580 1.036 1581 0.894 1582 1.231 1583 1.145 1584 1.452 1585 0.72 1586 1.536 1587 1.33 1588 0.713 1589 1.316 1590 1.31 1591 1.026 1592 0.827 1593 1.031 1594 0.841 1595 0.447 1596 0.789 1597 0.686 1598 0.74 1599 0.668 1600 0.644 1601 1.075 1602 0.944 1603 1.152 1604 1.012 1605 1.045 1606 0.957 1607 0.567 1608 0.575 1609 0.985 1610 1.254 1611 1.183 1612 1.014 1613 0.633 1614 0.616 1615 1.105 1616 1.254 1617 1.133 1618 1.088 1619 1.109 1620 1.107 1621 1.236 1622 0.93 1623 1.024 1624 0.745 1625 0.933 1626 1.086 1627 0.727 1628 0.552 1629 1.267 1630 1.572 1631 1.446 1632 0.935 1633 0.938 1634 1.487 1635 1.226 1636 1.371 1637 1.043 1638 1.355 1639 0.863 1640 1.265 1641 1.499 1642 1.2 1643 1.029 1644 0.94 1645 0.836 1646 1.212 1647 1.227 1648 1.157 1649 1.005 1650 0.566 1651 1.167 1652 0.973 1653 0.918 1654 1.001 1655 1.069 1656 0.921 1657 1.063 1658 0.746 1659 0.928 1660 0.334 1661 1.277 1662 1.277 1663 1.561 1664 1.105 1665 1.476 1666 0.981 1667 1.121 1668 1.099 1669 0.962 1670 0.68 1671 0.863 1672 0.365 1673 0.792 1674 0.806 1675 0.4 1676 0.52 1677 0.906 1678 1.373 1679 0.533 1680 0.716 1681 1.61 1682 1.741 1683 1.376 1684 0.981 1685 0.866 1686 0.897 1687 0.811 1688 0.95 1689 1.012 1690 1.163 1691 0.936 1692 1.084 1693 0.827 1694 1.038 1695 0.944 1696 0.84 1697 1.279 1698 0.896 1699 1.004 1700 0.874 1701 0.852 1702 0.889 1703 0.904 1704 0.908 1705 0.804 1706 0.904 1707 1.215 1708 1.003 1709 1.217 1710 0.711 1711 0.902 1712 1.051 1713 0.819 1714 0.757 1715 0.357 1716 0.699 1717 0.561 1718 1.021 1719 0.957 1720 0.707 1721 0.777 1722 0.921 1723 0.791 1724 0.829 1725 0.479 1726 0.6 1727 1.161 1728 1.286 1729 0.843 1730 0.674 1731 0.762 1732 1.069 1733 0.843 1734 0.82 1735 0.952 1736 1.046 1737 0.899 1738 0.878 1739 0.868 1740 0.876 1741 0.716 1742 0.488 1743 0.904 1744 1.202 1745 1.22 1746 0.654 1747 1.16 1748 1.141 1749 0.999 1750 0.581 1751 1.256 1752 1.387 1753 1.094 1754 1.176 1755 1.669 1756 1.029 1757 0.873 1758 1.281 1759 0.897 1760 1.176 1761 1.25 1762 1.17 1763 1.113 1764 0.636 1765 0.666 1766 0.99 1767 0.939 1768 0.693 1769 1.191 1770 0.711 1771 1.007 1772 1.04 1773 1.06 1774 1.422 1775 1.006 1776 1.264 1777 1.135 1778 1.147 1779 0.694 1780 0.995 1781 0.796 1782 0.705 1783 1.206 1784 1.338 1785 1.031 1786 1.062 1787 1.056 1788 1.306 1789 1.27 1790 1.201 1791 1.199 1792 1.198 1793 0.91 1794 0.537 1795 1.384 1796 0.944 1797 0.557 1798 0.911 1799 0.556 1800 1.14 1801 1.084 1802 0.875 1803 1.125 1804 1.434 1805 1.299 1806 0.815 1807 0.93 1808 0.749 1809 1.238 1810 1.32 1811 0.976 1812 1.171 1813 0.91 1814 0.795 1815 0.964 1816 1.506 1817 1.202 1818 1.085 1819 0.406 1820 0.638 1821 1.091 1822 0.78 1823 0.83 1824 1.037 1825 0.929 1826 0.563 1827 1.384 1828 0.64 1829 0.778 1830 0.664 1831 0.774 1832 0.776 1833 0.839 1834 0.677 1835 1.378 1836 1.109 1837 0.574 1838 0.931 1839 0.853 1840 0.578 1841 1.004 1842 0.723 1843 0.694 1844 0.729 1845 0.901 1846 0.997 1847 0.988 1848 0.893 1849 0.768 1850 0.744 1851 0.491 1852 0.566 1853 0.821 1854 0.744 1855 1.145 1856 1.248 1857 1.012 1858 0.905 1859 1.009 1860 0.95 1861 0.922 1862 1.066 1863 0.665 1864 0.765 1865 1.091 1866 1.183 1867 0.952 1868 0.546 1869 0.875 1870 0.785 1871 0.868 1872 1.097 1873 0.797 1874 0.537 1875 1.044 1876 1.379 1877 1.246 1878 1.047 1879 0.579 1880 0.718 1881 0.953 1882 0.954 1883 1.154 1884 1.012 1885 1.249 1886 0.85 1887 0.241 1888 0.73 1889 1.217 1890 1.292 1891 1.283 1892 1.422 1893 0.811 1894 0.82 1895 0.82 1896 0.78 1897 1.354 1898 0.672 1899 0.711 1900 1.495 1901 1.491 1902 1.272 1903 1.188 1904 1.275 1905 1.094 1906 1.492 1907 0.921 1908 0.842 1909 0.785 1910 1.203 1911 0.669 1912 0.736 1913 1.143 1914 1.456 1915 1.163 1916 0.683 1917 0.651 1918 0.807 1919 1.322 1920 1.023 1921 1.156 1922 1.242 1923 0.948 1924 1.254 1925 0.977 1926 0.849 1927 0.547 1928 0.539 1929 0.768 1930 1.274 1931 1.021 1932 0.621 1933 0.775 1934 1.222 1935 0.729 1936 1.368 1937 1.422 1938 0.892 1939 1.028 1940 1.129 1941 1.07 1942 0.798 1943 1.05 1944 1.015 1945 0.732 1946 0.755 1947 1.206 1948 0.912 1949 0.433 1950 1.051 1951 1.861 1952 1.804 1953 0.892 1954 0.815 1955 0.783 1956 0.806 1957 0.975 1958 1.203 1959 0.874 1960 1.159 1961 0.996 1962 1.022 1963 1.538 1964 1.361 1965 0.887 1966 0.969 1967 1.077 1968 1.011 1969 1.089 1970 1.143 1971 1.081 1972 1.226 1973 1.018 1974 0.969 1975 1.566 1976 1.28 1977 1.41 1978 1.126 1979 1.353 1980 1.108 1981 1.425 1982 1.079 1983 1.548 1984 0.968 1985 0.997 1986 1.398 1987 1.123 1988 0.867 1989 0.597 1990 0.821 1991 0.617 1992 0.962 1993 0.664 1994 0.481 1995 0.721 1996 0.615 1997 0.943 1998 1.295 1999 0.835 2000 0.773 2001 0.998