# northamerica_usa_ok032 - French Lake - 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/6174 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_ok032 - French Lake - 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: French Lake # Location: # Country: United States # Northernmost_Latitude: 34.72 # Southernmost_Latitude: 34.72 # Easternmost_Longitude: -98.7 # Westernmost_Longitude: -98.7 # Elevation: 494 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_ok032B # Earliest_Year: 1750 # Most_Recent_Year: 2005 # 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":"5.08953685426","T2":"17.680751873","M1":"0.0225594739817","M2":"0.418725107471"}} #-------------------- # Species # Species_Name: post oak # Species_Code: QUST #-------------------- # 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 1750 0.724 1751 0.779 1752 0.504 1753 0.967 1754 1.083 1755 0.532 1756 0.666 1757 0.929 1758 1.435 1759 1.16 1760 1.391 1761 1.317 1762 1.081 1763 0.744 1764 0.93 1765 0.791 1766 0.817 1767 0.602 1768 0.776 1769 1.136 1770 1.054 1771 0.841 1772 0.409 1773 0.463 1774 1.146 1775 1.172 1776 1.562 1777 0.764 1778 0.734 1779 1.141 1780 0.973 1781 1.372 1782 1.187 1783 1.71 1784 1.17 1785 1.093 1786 0.742 1787 1.221 1788 1.434 1789 0.54 1790 0.704 1791 0.935 1792 0.92 1793 0.847 1794 0.651 1795 1.159 1796 0.966 1797 1.1 1798 1.023 1799 1.19 1800 0.788 1801 0.388 1802 1.151 1803 1.296 1804 1.382 1805 0.697 1806 0.937 1807 0.968 1808 0.323 1809 1.396 1810 1.354 1811 0.96 1812 0.646 1813 0.946 1814 0.95 1815 0.868 1816 0.892 1817 1.363 1818 1.121 1819 0.942 1820 0.722 1821 0.737 1822 0.594 1823 0.775 1824 0.596 1825 1.618 1826 1.655 1827 1.728 1828 1.351 1829 1.238 1830 1.252 1831 0.908 1832 0.571 1833 1.868 1834 0.782 1835 1.031 1836 1.776 1837 1.69 1838 1.277 1839 1.214 1840 1.259 1841 0.812 1842 0.565 1843 1.203 1844 1.345 1845 0.897 1846 1.188 1847 0.919 1848 0.775 1849 1.113 1850 1.11 1851 0.772 1852 0.869 1853 1.3 1854 1.208 1855 0.587 1856 0.685 1857 0.764 1858 1.009 1859 0.446 1860 0.541 1861 0.492 1862 0.364 1863 0.549 1864 0.547 1865 0.667 1866 0.994 1867 1.003 1868 0.511 1869 1.035 1870 0.657 1871 1.015 1872 0.761 1873 0.703 1874 0.77 1875 0.914 1876 0.844 1877 1.002 1878 1.092 1879 0.817 1880 0.42 1881 0.701 1882 0.683 1883 0.604 1884 0.775 1885 1.12 1886 0.58 1887 0.53 1888 1.0 1889 0.99 1890 0.628 1891 1.15 1892 0.788 1893 0.611 1894 0.848 1895 0.419 1896 0.692 1897 1.051 1898 0.848 1899 0.992 1900 0.966 1901 0.893 1902 0.959 1903 1.006 1904 0.474 1905 1.133 1906 1.153 1907 1.619 1908 1.473 1909 0.987 1910 0.782 1911 0.445 1912 1.367 1913 0.792 1914 1.117 1915 0.779 1916 1.014 1917 0.503 1918 0.409 1919 1.288 1920 1.552 1921 1.601 1922 1.269 1923 1.083 1924 0.979 1925 0.648 1926 1.213 1927 1.298 1928 1.026 1929 0.901 1930 0.673 1931 0.835 1932 1.322 1933 1.0 1934 0.776 1935 0.873 1936 0.703 1937 0.82 1938 0.869 1939 0.46 1940 0.626 1941 1.265 1942 1.059 1943 1.329 1944 1.278 1945 1.4 1946 1.495 1947 1.143 1948 1.038 1949 0.957 1950 1.072 1951 1.174 1952 0.663 1953 0.577 1954 0.912 1955 0.955 1956 0.642 1957 0.962 1958 1.003 1959 0.876 1960 1.31 1961 1.342 1962 1.271 1963 0.73 1964 0.878 1965 1.343 1966 0.596 1967 0.792 1968 1.571 1969 1.11 1970 0.781 1971 0.423 1972 0.992 1973 1.248 1974 1.195 1975 1.726 1976 1.141 1977 0.87 1978 1.045 1979 1.197 1980 0.767 1981 0.803 1982 1.062 1983 0.885 1984 0.656 1985 1.079 1986 1.112 1987 1.56 1988 0.945 1989 1.257 1990 1.012 1991 1.162 1992 1.492 1993 1.544 1994 1.033 1995 1.141 1996 0.704 1997 0.944 1998 0.815 1999 1.185 2000 0.785 2001 0.814 2002 0.88 2003 1.044 2004 0.737 2005 0.805