# northamerica_usa_ca087 - Kaiser Pass - 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/3532 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_ca087 - Kaiser Pass - 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: Kaiser Pass # Location: # Country: United States # Northernmost_Latitude: 37.28 # Southernmost_Latitude: 37.28 # Easternmost_Longitude: -119.08 # Westernmost_Longitude: -119.08 # Elevation: 2731 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_ca087B # Earliest_Year: 1140 # Most_Recent_Year: 1981 # 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":"4.86176765156","T2":"17.3117130014","M1":"0.0230807255878","M2":"0.492884308972"}} #-------------------- # Species # Species_Name: western juniper # Species_Code: JUOC #-------------------- # 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 1140 0.975 1141 1.13 1142 1.152 1143 0.989 1144 1.052 1145 1.043 1146 1.219 1147 1.252 1148 0.612 1149 0.519 1150 1.018 1151 0.936 1152 0.895 1153 0.761 1154 0.73 1155 0.804 1156 0.627 1157 0.323 1158 0.691 1159 0.671 1160 0.65 1161 0.64 1162 0.8 1163 0.865 1164 0.855 1165 0.771 1166 1.028 1167 0.708 1168 0.752 1169 0.785 1170 1.001 1171 0.722 1172 0.831 1173 1.015 1174 0.995 1175 1.083 1176 1.019 1177 0.716 1178 0.434 1179 0.63 1180 0.86 1181 0.708 1182 0.939 1183 0.468 1184 0.391 1185 0.711 1186 0.811 1187 0.757 1188 0.514 1189 0.581 1190 0.682 1191 0.905 1192 1.018 1193 1.232 1194 1.211 1195 1.213 1196 1.237 1197 0.89 1198 1.094 1199 1.05 1200 1.153 1201 1.234 1202 1.156 1203 1.033 1204 1.205 1205 1.173 1206 1.186 1207 1.119 1208 1.74 1209 1.352 1210 1.423 1211 1.54 1212 1.358 1213 1.232 1214 1.072 1215 1.422 1216 1.086 1217 1.076 1218 0.961 1219 1.021 1220 1.163 1221 1.141 1222 1.025 1223 1.026 1224 1.146 1225 1.124 1226 1.375 1227 0.984 1228 1.057 1229 1.309 1230 1.228 1231 1.146 1232 1.135 1233 1.461 1234 1.379 1235 1.068 1236 1.36 1237 0.986 1238 1.267 1239 1.645 1240 1.173 1241 1.065 1242 1.531 1243 1.338 1244 1.205 1245 1.342 1246 1.43 1247 1.297 1248 1.051 1249 1.437 1250 1.216 1251 1.031 1252 1.145 1253 1.159 1254 1.136 1255 0.912 1256 1.089 1257 0.952 1258 0.398 1259 0.613 1260 0.931 1261 0.881 1262 1.048 1263 1.228 1264 1.166 1265 1.142 1266 1.221 1267 0.902 1268 1.006 1269 1.188 1270 0.867 1271 1.218 1272 1.025 1273 1.027 1274 0.937 1275 1.199 1276 0.796 1277 0.81 1278 1.153 1279 1.01 1280 0.682 1281 0.881 1282 0.935 1283 0.897 1284 0.858 1285 0.433 1286 0.78 1287 1.13 1288 0.769 1289 0.69 1290 0.798 1291 0.988 1292 0.814 1293 0.517 1294 0.816 1295 0.859 1296 0.723 1297 0.424 1298 0.712 1299 0.575 1300 0.81 1301 0.728 1302 0.743 1303 0.869 1304 0.773 1305 0.552 1306 0.761 1307 0.958 1308 0.736 1309 0.919 1310 0.794 1311 0.527 1312 0.556 1313 0.401 1314 0.926 1315 0.459 1316 0.473 1317 0.602 1318 0.388 1319 0.389 1320 0.605 1321 0.678 1322 0.433 1323 0.404 1324 0.463 1325 0.565 1326 0.653 1327 0.625 1328 0.845 1329 0.715 1330 0.73 1331 0.879 1332 1.087 1333 0.912 1334 1.344 1335 1.451 1336 1.394 1337 1.352 1338 1.241 1339 1.038 1340 0.982 1341 1.039 1342 0.918 1343 1.003 1344 0.969 1345 1.159 1346 1.447 1347 1.2 1348 0.892 1349 1.134 1350 0.985 1351 1.014 1352 1.303 1353 1.542 1354 1.077 1355 1.066 1356 1.132 1357 1.041 1358 0.945 1359 1.193 1360 1.193 1361 1.071 1362 1.066 1363 0.884 1364 0.928 1365 0.825 1366 1.025 1367 0.883 1368 1.237 1369 1.231 1370 1.119 1371 1.115 1372 1.214 1373 1.237 1374 1.431 1375 1.059 1376 1.253 1377 0.944 1378 1.138 1379 1.125 1380 1.062 1381 1.228 1382 1.094 1383 1.317 1384 1.028 1385 1.268 1386 0.989 1387 1.106 1388 1.1 1389 1.201 1390 1.03 1391 1.023 1392 1.233 1393 1.22 1394 1.4 1395 0.848 1396 0.853 1397 0.87 1398 1.016 1399 0.904 1400 0.886 1401 0.794 1402 0.66 1403 0.797 1404 0.864 1405 0.941 1406 0.909 1407 0.707 1408 0.7 1409 0.868 1410 0.514 1411 0.795 1412 0.866 1413 0.417 1414 0.692 1415 0.738 1416 0.563 1417 0.822 1418 0.815 1419 0.669 1420 1.316 1421 1.056 1422 1.446 1423 1.486 1424 1.091 1425 0.763 1426 0.686 1427 1.019 1428 1.215 1429 1.419 1430 1.184 1431 0.776 1432 0.807 1433 0.9 1434 0.814 1435 0.997 1436 1.001 1437 0.817 1438 0.902 1439 0.88 1440 1.31 1441 1.158 1442 0.847 1443 1.015 1444 0.897 1445 0.947 1446 0.821 1447 0.933 1448 0.833 1449 0.889 1450 0.882 1451 0.771 1452 0.73 1453 0.84 1454 0.627 1455 0.793 1456 0.747 1457 0.868 1458 0.65 1459 0.592 1460 1.079 1461 0.975 1462 1.247 1463 1.143 1464 0.781 1465 0.97 1466 1.144 1467 1.219 1468 0.449 1469 1.058 1470 1.585 1471 1.165 1472 1.365 1473 1.109 1474 0.995 1475 0.975 1476 0.896 1477 1.126 1478 0.983 1479 0.751 1480 1.098 1481 1.141 1482 0.908 1483 0.952 1484 1.521 1485 1.29 1486 1.048 1487 0.952 1488 0.983 1489 1.166 1490 1.1 1491 1.468 1492 1.477 1493 1.495 1494 1.244 1495 1.072 1496 1.137 1497 1.063 1498 1.084 1499 1.169 1500 0.439 1501 0.887 1502 0.888 1503 1.035 1504 1.167 1505 1.207 1506 0.764 1507 0.659 1508 0.55 1509 1.027 1510 1.03 1511 0.844 1512 0.955 1513 1.066 1514 0.966 1515 0.791 1516 1.03 1517 1.31 1518 0.837 1519 0.812 1520 1.041 1521 1.006 1522 1.086 1523 0.989 1524 1.319 1525 1.477 1526 1.196 1527 1.127 1528 1.329 1529 1.099 1530 1.241 1531 1.11 1532 0.878 1533 0.685 1534 1.146 1535 1.078 1536 0.929 1537 0.813 1538 0.767 1539 1.102 1540 0.936 1541 0.683 1542 0.847 1543 0.813 1544 0.848 1545 0.893 1546 0.957 1547 1.005 1548 0.77 1549 1.26 1550 0.699 1551 1.021 1552 1.098 1553 1.413 1554 0.762 1555 0.837 1556 1.599 1557 1.198 1558 1.029 1559 1.199 1560 1.187 1561 1.05 1562 1.105 1563 1.188 1564 1.367 1565 1.223 1566 1.032 1567 1.103 1568 1.279 1569 0.66 1570 0.584 1571 0.811 1572 0.878 1573 1.001 1574 0.902 1575 0.835 1576 0.878 1577 1.424 1578 1.019 1579 0.673 1580 0.57 1581 1.264 1582 0.647 1583 1.054 1584 0.739 1585 0.953 1586 0.788 1587 0.815 1588 0.905 1589 1.368 1590 1 1591 0.971 1592 0.881 1593 0.804 1594 1.152 1595 0.604 1596 1.286 1597 0.929 1598 0.887 1599 1.138 1600 0.851 1601 1.124 1602 0.922 1603 0.875 1604 1.413 1605 1.46 1606 1.275 1607 0.778 1608 1.208 1609 0.967 1610 0.999 1611 1.173 1612 0.997 1613 0.777 1614 1.187 1615 1.25 1616 1.166 1617 1.535 1618 1.152 1619 0.896 1620 0.995 1621 0.92 1622 0.527 1623 0.893 1624 0.94 1625 1.363 1626 0.761 1627 0.979 1628 1.009 1629 0.876 1630 0.801 1631 0.57 1632 0.559 1633 0.941 1634 0.761 1635 0.664 1636 1.181 1637 0.686 1638 0.713 1639 0.645 1640 0.774 1641 0.829 1642 1.251 1643 0.861 1644 1.198 1645 1.331 1646 1.157 1647 1.203 1648 1.491 1649 1.367 1650 1.337 1651 1.355 1652 1.251 1653 0.742 1654 0.954 1655 0.499 1656 1.103 1657 0.36 1658 0.47 1659 0.702 1660 1.228 1661 1.155 1662 0.798 1663 0.743 1664 0.832 1665 0.852 1666 1.171 1667 0.813 1668 0.87 1669 0.691 1670 1.081 1671 1.174 1672 1.208 1673 1 1674 1.111 1675 1.011 1676 1.073 1677 1.316 1678 1.267 1679 1.276 1680 1.243 1681 1.28 1682 1.142 1683 1.355 1684 0.846 1685 0.995 1686 0.916 1687 1.012 1688 0.971 1689 1.01 1690 0.693 1691 0.642 1692 1.093 1693 0.92 1694 0.993 1695 0.859 1696 0.942 1697 1.259 1698 1.099 1699 1.23 1700 1.096 1701 0.89 1702 1.122 1703 0.799 1704 1.288 1705 1.588 1706 1.155 1707 0.911 1708 0.972 1709 1.14 1710 0.678 1711 0.987 1712 0.807 1713 0.766 1714 0.57 1715 0.552 1716 0.663 1717 0.922 1718 0.819 1719 0.739 1720 0.915 1721 0.735 1722 0.699 1723 0.762 1724 0.486 1725 0.931 1726 1.006 1727 0.956 1728 0.853 1729 0.544 1730 1.073 1731 0.863 1732 0.791 1733 0.726 1734 1.364 1735 0.923 1736 1.17 1737 0.929 1738 0.804 1739 0.796 1740 1.336 1741 1.379 1742 1.152 1743 1.279 1744 1.053 1745 1.805 1746 1.126 1747 1.279 1748 0.943 1749 1.153 1750 0.96 1751 1.045 1752 1.044 1753 0.869 1754 0.806 1755 0.767 1756 0.79 1757 0.887 1758 1.003 1759 0.79 1760 1.167 1761 1.06 1762 0.842 1763 1.079 1764 0.983 1765 0.89 1766 1.178 1767 1.058 1768 1.112 1769 0.833 1770 0.934 1771 0.913 1772 0.947 1773 0.944 1774 1.019 1775 0.844 1776 1.055 1777 0.807 1778 0.966 1779 0.808 1780 0.779 1781 0.827 1782 0.678 1783 0.72 1784 0.795 1785 0.678 1786 0.776 1787 0.798 1788 0.615 1789 0.751 1790 0.842 1791 0.787 1792 1.109 1793 0.648 1794 0.865 1795 0.648 1796 0.546 1797 0.73 1798 0.755 1799 1.111 1800 0.98 1801 0.857 1802 0.931 1803 0.999 1804 0.85 1805 1.061 1806 0.756 1807 0.782 1808 0.669 1809 1.057 1810 1.056 1811 1.237 1812 1.065 1813 1.281 1814 1.484 1815 1.164 1816 1.284 1817 1.467 1818 1.279 1819 1.277 1820 1.241 1821 1.16 1822 1.08 1823 0.919 1824 0.718 1825 1.251 1826 1.358 1827 0.912 1828 0.917 1829 0.951 1830 1.163 1831 0.989 1832 1.611 1833 0.911 1834 0.824 1835 1.027 1836 0.921 1837 0.914 1838 1.23 1839 0.875 1840 0.844 1841 0.667 1842 0.851 1843 0.87 1844 0.682 1845 1.465 1846 0.912 1847 1.128 1848 1.27 1849 1.031 1850 1.001 1851 0.801 1852 1.395 1853 1.246 1854 0.899 1855 0.977 1856 0.637 1857 1.093 1858 0.743 1859 0.802 1860 0.977 1861 0.902 1862 0.965 1863 1.062 1864 1.228 1865 1.09 1866 1.214 1867 1.108 1868 0.816 1869 0.754 1870 0.916 1871 0.581 1872 0.598 1873 0.721 1874 0.763 1875 0.8 1876 0.866 1877 0.772 1878 1.055 1879 1.032 1880 0.963 1881 1.24 1882 1.127 1883 1.013 1884 1.596 1885 1.816 1886 1.254 1887 1.219 1888 1.575 1889 1.409 1890 1.665 1891 1.48 1892 0.97 1893 1.498 1894 1.426 1895 1.539 1896 1.355 1897 1.468 1898 1.221 1899 0.993 1900 1.262 1901 1.729 1902 1.154 1903 0.978 1904 1.395 1905 1.192 1906 1.442 1907 1.161 1908 1.08 1909 1.012 1910 0.934 1911 1.253 1912 0.795 1913 1.105 1914 1.324 1915 1.069 1916 1.14 1917 0.965 1918 0.829 1919 0.82 1920 0.752 1921 0.894 1922 0.75 1923 0.647 1924 0.564 1925 0.997 1926 0.856 1927 0.529 1928 0.503 1929 0.681 1930 0.457 1931 0.819 1932 0.676 1933 0.455 1934 0.648 1935 0.798 1936 1.016 1937 0.859 1938 1.044 1939 0.838 1940 1.02 1941 0.947 1942 0.894 1943 0.886 1944 0.634 1945 0.816 1946 0.805 1947 0.779 1948 0.838 1949 0.623 1950 0.903 1951 0.89 1952 1.014 1953 0.741 1954 1.07 1955 0.747 1956 0.86 1957 0.958 1958 1.181 1959 0.699 1960 0.517 1961 0.691 1962 0.84 1963 0.799 1964 0.741 1965 0.906 1966 0.886 1967 1.015 1968 0.688 1969 1.319 1970 0.951 1971 0.817 1972 1.124 1973 0.951 1974 0.973 1975 1.167 1976 0.98 1977 1.232 1978 1.686 1979 1.336 1980 1.505 1981 1.165