# northamerica_usa_ca552 - San Bernardino Mountains Q - 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/4189 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_ca552 - San Bernardino Mountains Q - 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 Q # Location: # Country: United States # Northernmost_Latitude: 34.1 # Southernmost_Latitude: 34.1 # Easternmost_Longitude: -116.97 # Westernmost_Longitude: -116.97 # Elevation: 1600 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_ca552B # Earliest_Year: 1764 # 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":"3.96010962642","T2":"16.7746690325","M1":"0.0230784876929","M2":"0.451909598593"}} #-------------------- # 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 1764 1.173 1765 0.391 1766 1.194 1767 1.249 1768 1.354 1769 1.45 1770 1.181 1771 1.404 1772 0.873 1773 0.732 1774 0.903 1775 1.129 1776 1.207 1777 0.307 1778 0.687 1779 0.548 1780 0.711 1781 0.744 1782 0.227 1783 0.786 1784 0.667 1785 0.684 1786 0.875 1787 1.368 1788 0.622 1789 0.819 1790 0.917 1791 1.355 1792 1.155 1793 1.521 1794 0.598 1795 0.821 1796 1.208 1797 1.483 1798 1.09 1799 1.187 1800 0.797 1801 0.977 1802 1.276 1803 0.954 1804 1.344 1805 1.177 1806 0.969 1807 0.797 1808 1.17 1809 0.286 1810 1.002 1811 1.067 1812 0.421 1813 0.829 1814 0.732 1815 0.861 1816 1.144 1817 0.723 1818 1.168 1819 1.248 1820 0.418 1821 0.95 1822 0.43 1823 0.544 1824 0.452 1825 0.763 1826 1.01 1827 0.893 1828 1.176 1829 0.479 1830 1.066 1831 1.071 1832 1.296 1833 1.192 1834 0.921 1835 0.929 1836 1.204 1837 1.187 1838 1.364 1839 1.595 1840 1.425 1841 0.433 1842 0.831 1843 0.622 1844 0.778 1845 0.522 1846 1.038 1847 0.703 1848 0.7 1849 0.68 1850 0.985 1851 0.795 1852 1.042 1853 1.561 1854 1.363 1855 1.493 1856 0.857 1857 -0.053 1858 1.208 1859 1.159 1860 1.041 1861 1.018 1862 1.384 1863 0.848 1864 1.021 1865 1.166 1866 1.516 1867 1.263 1868 1.994 1869 1.571 1870 1.063 1871 1.179 1872 0.887 1873 0.884 1874 0.951 1875 0.612 1876 0.903 1877 0.74 1878 0.894 1879 0.145 1880 0.815 1881 0.819 1882 0.6 1883 0.604 1884 1.117 1885 0.825 1886 1.357 1887 1.115 1888 1.339 1889 1.163 1890 1.41 1891 1.694 1892 1.427 1893 1.155 1894 0.709 1895 1.028 1896 0.446 1897 0.72 1898 0.628 1899 0.322 1900 0.755 1901 1.037 1902 0.805 1903 0.875 1904 0.736 1905 1.097 1906 1.516 1907 1.29 1908 1.487 1909 1.649 1910 1.256 1911 0.921 1912 0.821 1913 0.794 1914 1.3 1915 1.294 1916 1.595 1917 1.779 1918 0.856 1919 0.872 1920 1.447 1921 1.471 1922 1.205 1923 1.037 1924 1.149 1925 0.866 1926 1.022 1927 0.886 1928 0.614 1929 0.818 1930 0.789 1931 0.899 1932 0.996 1933 0.596 1934 0.365 1935 0.973 1936 0.779 1937 0.945 1938 1.208 1939 1.084 1940 1.295 1941 1.413 1942 0.933 1943 1.242 1944 1.211 1945 1.37 1946 1.289 1947 0.924 1948 0.675 1949 0.508 1950 0.652 1951 0.278 1952 0.682 1953 0.72 1954 0.797 1955 0.815 1956 1.063 1957 0.819 1958 1.165 1959 0.404 1960 0.63 1961 -0.059 1962 0.581 1963 0.3 1964 0.814 1965 0.781 1966 0.823 1967 1.105 1968 0.861 1969 0.984 1970 0.812 1971 0.566 1972 0.157 1973 0.742 1974 0.724 1975 0.965 1976 0.572 1977 0.948 1978 0.942 1979 1.211 1980 1.523 1981 0.68 1982 1.127 1983 2.267 1984 0.972 1985 1.528 1986 1.588 1987 1.169 1988 0.847