# northamerica_mexico_mexi036 - Rio Verde - 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/4936 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_mexico_mexi036 - Rio Verde - 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: Rio Verde # Location: # Country: Mexico # Northernmost_Latitude: 21.68 # Southernmost_Latitude: 21.68 # Easternmost_Longitude: -99.78 # Westernmost_Longitude: -99.78 # Elevation: 820 m #-------------------- # Data_Collection # Collection_Name: northamerica_mexico_mexi036B # Earliest_Year: 1700 # Most_Recent_Year: 1996 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]"}}{"VSLite_parameters":{"T1":"5.07407018382","T2":"16.5861874872","M1":"0.0219554378147","M2":"0.521149284135"}} #-------------------- # Species # Species_Name: Montezuma cypress # Species_Code: TAMU #-------------------- # 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 1700 0.615 1701 0.694 1702 0.774 1703 1.34 1704 1.206 1705 1.106 1706 0.85 1707 0.86 1708 0.933 1709 1.243 1710 1.102 1711 1.068 1712 1.294 1713 1.119 1714 1.198 1715 1.257 1716 1.26 1717 0.939 1718 1.148 1719 0.79 1720 0.688 1721 0.818 1722 0.751 1723 0.686 1724 0.888 1725 0.94 1726 1.041 1727 1.071 1728 1.228 1729 0.845 1730 0.917 1731 0.813 1732 0.65 1733 0.693 1734 0.733 1735 0.939 1736 0.981 1737 0.971 1738 1.008 1739 0.568 1740 0.758 1741 0.545 1742 0.35 1743 0.73 1744 0.859 1745 1.014 1746 1.084 1747 0.608 1748 0.795 1749 0.744 1750 0.733 1751 0.644 1752 0.833 1753 0.788 1754 1.08 1755 0.987 1756 0.894 1757 0.702 1758 0.77 1759 0.925 1760 0.857 1761 0.846 1762 0.69 1763 0.778 1764 0.679 1765 0.853 1766 0.658 1767 0.69 1768 1.012 1769 0.917 1770 0.89 1771 0.878 1772 0.984 1773 1.16 1774 1.031 1775 0.941 1776 0.927 1777 0.71 1778 0.612 1779 0.817 1780 0.639 1781 0.741 1782 0.814 1783 0.916 1784 0.802 1785 0.55 1786 0.622 1787 0.491 1788 0.827 1789 0.525 1790 0.687 1791 0.961 1792 0.964 1793 0.651 1794 0.67 1795 0.807 1796 0.616 1797 0.54 1798 0.773 1799 0.574 1800 0.921 1801 0.964 1802 1.28 1803 1.206 1804 0.931 1805 0.777 1806 0.806 1807 0.884 1808 0.618 1809 1.321 1810 0.68 1811 0.647 1812 0.684 1813 0.538 1814 0.51 1815 0.608 1816 0.572 1817 0.59 1818 0.494 1819 0.415 1820 0.729 1821 0.988 1822 1.231 1823 0.797 1824 1.319 1825 1.423 1826 1.475 1827 1.556 1828 0.749 1829 1.409 1830 0.628 1831 1.627 1832 0.876 1833 0.975 1834 0.802 1835 0.963 1836 0.94 1837 0.938 1838 0.725 1839 0.93 1840 1.308 1841 1.045 1842 1.133 1843 0.928 1844 1.057 1845 1.092 1846 1.783 1847 1.435 1848 1.258 1849 1.14 1850 1.158 1851 0.954 1852 0.553 1853 0.524 1854 0.455 1855 0.652 1856 0.552 1857 0.646 1858 0.691 1859 0.551 1860 0.657 1861 0.765 1862 0.5 1863 0.768 1864 0.666 1865 1.144 1866 0.641 1867 0.901 1868 0.617 1869 1.146 1870 0.612 1871 0.544 1872 0.772 1873 0.59 1874 0.744 1875 0.5 1876 0.566 1877 0.821 1878 0.841 1879 0.853 1880 0.643 1881 1.142 1882 0.782 1883 1.21 1884 1.055 1885 1.271 1886 1.606 1887 1.654 1888 1.637 1889 1.219 1890 0.729 1891 0.999 1892 0.838 1893 1.021 1894 1.193 1895 1.247 1896 0.887 1897 1.327 1898 0.886 1899 1.44 1900 0.97 1901 1.058 1902 0.975 1903 1.758 1904 1.212 1905 1.566 1906 1.405 1907 1.3 1908 1.393 1909 0.866 1910 1.546 1911 1.141 1912 1.16 1913 1.452 1914 1.294 1915 0.998 1916 1.05 1917 0.793 1918 1.267 1919 0.971 1920 0.819 1921 0.826 1922 0.746 1923 0.983 1924 0.886 1925 1.074 1926 1.018 1927 0.474 1928 0.895 1929 0.643 1930 1.082 1931 1.239 1932 0.801 1933 0.93 1934 0.982 1935 0.626 1936 0.776 1937 0.641 1938 0.524 1939 0.586 1940 0.8 1941 1.299 1942 0.794 1943 1.106 1944 1.034 1945 0.939 1946 1.093 1947 0.984 1948 1.115 1949 0.9 1950 0.767 1951 0.894 1952 0.93 1953 0.638 1954 1.05 1955 0.696 1956 0.606 1957 0.584 1958 1.385 1959 1.054 1960 0.773 1961 1.008 1962 1.04 1963 1.068 1964 0.899 1965 0.87 1966 1.209 1967 1.219 1968 1.504 1969 0.968 1970 1.337 1971 0.838 1972 0.939 1973 0.921 1974 0.684 1975 0.844 1976 0.989 1977 0.782 1978 1.15 1979 1.21 1980 1.042 1981 1.357 1982 0.915 1983 1.126 1984 1.138 1985 1.27 1986 1.127 1987 1.137 1988 0.992 1989 0.766 1990 1.002 1991 0.922 1992 1.378 1993 0.744 1994 1.051 1995 0.747 1996 0.959