# northamerica_usa_ca553 - San Bernardino Mountains R - 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/4190 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_ca553 - San Bernardino Mountains R - 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: San Bernardino Mountains R # Location: # Country: United States # Northernmost_Latitude: 34.17 # Southernmost_Latitude: 34.17 # Easternmost_Longitude: -116.73 # Westernmost_Longitude: -116.73 # Elevation: 1500 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_ca553B # Earliest_Year: 1756 # Most_Recent_Year: 1988 # 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":"3.83472910524","T2":"17.2368760034","M1":"0.0232487714482","M2":"0.433503460736"}} #-------------------- # Species # Species_Name: bigcone Douglas fir # Species_Code: PSMA #-------------------- # 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 1756 0.665 1757 0.893 1758 0.942 1759 0.866 1760 1.178 1761 1.344 1762 1.241 1763 1.252 1764 1.225 1765 0.167 1766 1.238 1767 1.19 1768 1.128 1769 1.184 1770 0.897 1771 1.318 1772 1.013 1773 0.373 1774 0.785 1775 0.903 1776 0.794 1777 0.205 1778 0.581 1779 0.619 1780 0.717 1781 0.874 1782 0.17 1783 0.596 1784 0.846 1785 0.929 1786 0.895 1787 1.219 1788 0.933 1789 0.789 1790 1.081 1791 1.287 1792 1.365 1793 1.598 1794 1.103 1795 0.589 1796 0.747 1797 1.316 1798 1.177 1799 1.385 1800 1.082 1801 1.108 1802 1.303 1803 1.432 1804 1.691 1805 1.342 1806 1.465 1807 1.206 1808 1.294 1809 0.969 1810 1.205 1811 1.028 1812 0.533 1813 0.631 1814 0.771 1815 1.005 1816 1.318 1817 1.05 1818 1.343 1819 1.516 1820 0.81 1821 0.86 1822 0.444 1823 0.599 1824 0.364 1825 0.761 1826 1.127 1827 1.282 1828 1.471 1829 0.722 1830 0.956 1831 1.225 1832 1.531 1833 1.621 1834 1.016 1835 0.925 1836 1.278 1837 1.08 1838 1.106 1839 1.46 1840 1.369 1841 0.396 1842 0.666 1843 0.519 1844 0.692 1845 0.336 1846 0.88 1847 0.666 1848 0.783 1849 0.724 1850 1.01 1851 0.954 1852 1.003 1853 1.639 1854 1.416 1855 1.717 1856 1.193 1857 0.802 1858 1.0 1859 0.969 1860 0.763 1861 0.616 1862 0.988 1863 0.743 1864 0.122 1865 0.601 1866 0.794 1867 0.915 1868 1.392 1869 1.163 1870 1.11 1871 0.843 1872 0.976 1873 0.65 1874 1.079 1875 0.641 1876 0.784 1877 0.519 1878 0.7 1879 0.247 1880 0.545 1881 0.687 1882 0.766 1883 0.954 1884 1.218 1885 0.991 1886 1.178 1887 1.109 1888 1.058 1889 1.143 1890 1.563 1891 1.741 1892 1.501 1893 1.3 1894 1.442 1895 1.228 1896 0.785 1897 0.708 1898 0.833 1899 0.519 1900 0.353 1901 0.648 1902 0.879 1903 1.094 1904 0.81 1905 1.114 1906 1.535 1907 1.544 1908 1.509 1909 1.421 1910 1.125 1911 0.79 1912 0.787 1913 1.173 1914 1.374 1915 1.226 1916 1.646 1917 1.689 1918 1.192 1919 0.717 1920 1.039 1921 1.436 1922 1.323 1923 1.292 1924 1.016 1925 0.864 1926 0.917 1927 0.848 1928 0.396 1929 0.731 1930 0.821 1931 0.792 1932 0.694 1933 0.683 1934 0.276 1935 0.773 1936 0.793 1937 1.106 1938 1.21 1939 1.123 1940 1.286 1941 1.319 1942 1.628 1943 1.103 1944 1.451 1945 1.286 1946 1.421 1947 1.019 1948 0.672 1949 0.728 1950 0.927 1951 0.515 1952 0.551 1953 0.9 1954 0.944 1955 0.849 1956 0.835 1957 0.784 1958 0.883 1959 0.534 1960 0.553 1961 -0.107 1962 0.319 1963 0.074 1964 0.541 1965 0.776 1966 0.697 1967 0.997 1968 1.134 1969 0.857 1970 0.772 1971 0.554 1972 0.131 1973 0.423 1974 0.399 1975 0.947 1976 1.079 1977 1.322 1978 1.314 1979 1.143 1980 1.796 1981 1.23 1982 1.246 1983 1.827 1984 1.612 1985 1.542 1986 1.344 1987 1.14 1988 0.794