# northamerica_usa_co552 - Red Mountain Pass Silverton - 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/2847 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_co552 - Red Mountain Pass Silverton - 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: Red Mountain Pass Silverton # Location: # Country: United States # Northernmost_Latitude: 37.9 # Southernmost_Latitude: 37.9 # Easternmost_Longitude: -107.72 # Westernmost_Longitude: -107.72 # Elevation: 3400 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_co552B # Earliest_Year: 1741 # Most_Recent_Year: 1983 # 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":"5.43059591254","T2":"17.7509684869","M1":"0.0221651053292","M2":"0.389835931988"}} #-------------------- # Species # Species_Name: Engelmann spruce # Species_Code: PCEN #-------------------- # 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 1741 0.855 1742 0.818 1743 0.967 1744 1.101 1745 1.067 1746 0.888 1747 1.099 1748 0.782 1749 1.04 1750 0.909 1751 0.986 1752 1.062 1753 0.978 1754 1.077 1755 1.087 1756 0.891 1757 1.104 1758 1.152 1759 1.211 1760 1.109 1761 0.975 1762 1.256 1763 1.128 1764 1.068 1765 1.124 1766 1.006 1767 1.204 1768 1.157 1769 1.127 1770 1.021 1771 1.096 1772 1.052 1773 0.853 1774 1.114 1775 0.93 1776 0.813 1777 0.718 1778 0.714 1779 0.809 1780 1.033 1781 0.837 1782 0.929 1783 1.156 1784 1.001 1785 1.014 1786 1.107 1787 1.158 1788 1.293 1789 1.259 1790 1.177 1791 1.13 1792 1.292 1793 1.134 1794 1.14 1795 1.334 1796 1.283 1797 1.219 1798 1.425 1799 1.135 1800 1.143 1801 1.379 1802 1.465 1803 1.068 1804 0.983 1805 1.163 1806 1.13 1807 1.435 1808 1.194 1809 1.035 1810 0.975 1811 1.083 1812 1.139 1813 1.047 1814 0.975 1815 1.157 1816 1.11 1817 1.2 1818 0.948 1819 0.992 1820 1.021 1821 1.066 1822 1.009 1823 0.981 1824 0.966 1825 0.851 1826 0.877 1827 1.16 1828 1.031 1829 1.049 1830 1.226 1831 1.285 1832 1.02 1833 1.628 1834 1.391 1835 1.242 1836 0.956 1837 1.315 1838 0.923 1839 1.05 1840 0.892 1841 0.916 1842 0.892 1843 1.053 1844 1.181 1845 1.024 1846 0.977 1847 0.899 1848 1.0 1849 0.942 1850 1.281 1851 0.854 1852 1.066 1853 1.046 1854 1.215 1855 1.066 1856 1.186 1857 1.067 1858 1.06 1859 1.292 1860 1.112 1861 1.309 1862 1.324 1863 1.362 1864 1.182 1865 1.196 1866 1.114 1867 0.883 1868 0.997 1869 1.069 1870 0.981 1871 1.01 1872 0.784 1873 0.952 1874 1.043 1875 0.792 1876 0.93 1877 0.925 1878 0.888 1879 0.802 1880 0.7 1881 1.101 1882 0.711 1883 0.709 1884 0.82 1885 1.002 1886 1.083 1887 0.732 1888 0.646 1889 0.575 1890 0.597 1891 0.709 1892 0.723 1893 0.523 1894 0.824 1895 0.747 1896 0.808 1897 0.736 1898 0.721 1899 0.576 1900 0.688 1901 0.588 1902 0.566 1903 0.92 1904 0.677 1905 0.685 1906 0.559 1907 0.707 1908 0.664 1909 0.9 1910 0.893 1911 0.847 1912 0.823 1913 0.835 1914 0.818 1915 0.865 1916 0.893 1917 1.015 1918 0.928 1919 0.874 1920 0.81 1921 0.908 1922 0.984 1923 0.911 1924 0.872 1925 0.867 1926 0.875 1927 0.889 1928 1.044 1929 1.08 1930 0.962 1931 1.013 1932 1.086 1933 0.967 1934 0.826 1935 1.039 1936 0.904 1937 1.046 1938 1.332 1939 1.165 1940 1.06 1941 1.093 1942 0.996 1943 0.995 1944 1.225 1945 1.198 1946 1.149 1947 1.242 1948 1.227 1949 1.205 1950 1.019 1951 1.242 1952 1.022 1953 1.174 1954 1.079 1955 1.085 1956 0.824 1957 0.792 1958 0.965 1959 0.77 1960 0.87 1961 0.952 1962 0.864 1963 1.083 1964 0.97 1965 1.201 1966 1.191 1967 0.81 1968 1.017 1969 1.069 1970 1.044 1971 0.967 1972 0.852 1973 0.963 1974 1.039 1975 1.044 1976 1.252 1977 0.839 1978 0.953 1979 0.9 1980 0.732 1981 0.684 1982 0.742 1983 0.866