# northamerica_usa_ok025 - Mud Creek - 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/4906 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_ok025 - Mud Creek - 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: Mud Creek # Location: # Country: United States # Northernmost_Latitude: 34.1 # Southernmost_Latitude: 34.1 # Easternmost_Longitude: -97.67 # Westernmost_Longitude: -97.67 # Elevation: 260 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_ok025B # Earliest_Year: 1710 # Most_Recent_Year: 1995 # 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":"4.25089618007","T2":"16.7642093339","M1":"0.0223552080691","M2":"0.512938942142"}} #-------------------- # 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 1710 0.697 1711 1.253 1712 1.496 1713 1.564 1714 0.957 1715 0.71 1716 0.599 1717 0.675 1718 1.54 1719 1.85 1720 1.077 1721 1.275 1722 0.521 1723 1.289 1724 0.504 1725 0.512 1726 0.8 1727 0.608 1728 0.548 1729 1.143 1730 0.339 1731 0.664 1732 1.121 1733 0.792 1734 0.878 1735 1.554 1736 0.565 1737 0.717 1738 1.448 1739 1.017 1740 1.627 1741 1.136 1742 1.016 1743 0.785 1744 1.553 1745 1.074 1746 2.099 1747 1.873 1748 1.806 1749 1.1 1750 1.255 1751 1.054 1752 0.425 1753 0.74 1754 0.647 1755 0.418 1756 0.607 1757 0.651 1758 1.291 1759 0.77 1760 1.687 1761 1.186 1762 1.24 1763 0.918 1764 1.008 1765 0.993 1766 0.888 1767 0.63 1768 0.503 1769 0.489 1770 0.972 1771 1.052 1772 0.416 1773 0.528 1774 0.957 1775 0.828 1776 1.179 1777 0.907 1778 0.696 1779 0.81 1780 0.797 1781 1.204 1782 1.332 1783 1.472 1784 1.198 1785 0.854 1786 0.432 1787 0.736 1788 1.274 1789 0.549 1790 0.575 1791 0.967 1792 1.012 1793 0.864 1794 0.757 1795 1.057 1796 1.372 1797 0.91 1798 0.683 1799 0.93 1800 0.769 1801 0.519 1802 1.035 1803 1.268 1804 1.008 1805 0.637 1806 0.913 1807 1.192 1808 0.611 1809 1.133 1810 0.926 1811 1.159 1812 0.898 1813 0.737 1814 0.825 1815 0.971 1816 0.892 1817 1.589 1818 0.978 1819 1.094 1820 0.903 1821 1.061 1822 0.839 1823 0.966 1824 0.835 1825 1.534 1826 1.462 1827 1.621 1828 1.434 1829 0.968 1830 0.942 1831 0.748 1832 0.855 1833 1.918 1834 1.117 1835 1.078 1836 1.912 1837 1.564 1838 1.269 1839 0.993 1840 1.161 1841 1.002 1842 0.692 1843 1.403 1844 0.892 1845 0.638 1846 0.823 1847 0.665 1848 0.888 1849 1.227 1850 0.912 1851 1.011 1852 0.961 1853 0.909 1854 0.659 1855 0.361 1856 0.7 1857 0.899 1858 0.942 1859 0.613 1860 0.679 1861 0.517 1862 0.609 1863 0.503 1864 0.495 1865 0.59 1866 0.599 1867 0.932 1868 0.799 1869 1.06 1870 0.837 1871 0.959 1872 0.751 1873 0.933 1874 0.725 1875 0.797 1876 0.852 1877 0.743 1878 0.654 1879 0.58 1880 0.547 1881 0.806 1882 0.742 1883 1.02 1884 0.663 1885 1.346 1886 0.616 1887 0.645 1888 1.235 1889 1.004 1890 1.427 1891 1.128 1892 0.825 1893 0.738 1894 1.242 1895 0.454 1896 0.729 1897 0.942 1898 1.333 1899 1.221 1900 1.043 1901 0.844 1902 0.786 1903 1.373 1904 0.617 1905 1.282 1906 1.021 1907 1.263 1908 1.602 1909 0.788 1910 0.549 1911 0.484 1912 1.119 1913 0.974 1914 1.53 1915 1.61 1916 1.425 1917 0.778 1918 0.652 1919 1.288 1920 1.521 1921 1.433 1922 1.016 1923 1.099 1924 1.3 1925 0.576 1926 1.219 1927 1.25 1928 1.547 1929 1.179 1930 1.15 1931 1.436 1932 1.565 1933 1.084 1934 0.932 1935 1.58 1936 1.039 1937 1.35 1938 1.03 1939 0.672 1940 0.794 1941 1.542 1942 1.551 1943 1.458 1944 1.271 1945 1.319 1946 1.18 1947 1.34 1948 1.161 1949 1.212 1950 1.182 1951 1.242 1952 0.742 1953 0.699 1954 0.969 1955 0.895 1956 0.407 1957 1.136 1958 1.036 1959 0.504 1960 1.006 1961 0.918 1962 0.852 1963 0.728 1964 0.611 1965 1.229 1966 0.729 1967 0.856 1968 1.157 1969 0.974 1970 0.837 1971 0.533 1972 0.724 1973 0.896 1974 0.708 1975 1.218 1976 0.802 1977 0.882 1978 0.808 1979 0.715 1980 0.6 1981 0.902 1982 1.014 1983 0.798 1984 0.545 1985 0.885 1986 0.896 1987 1.13 1988 0.864 1989 0.965 1990 0.878 1991 0.871 1992 1.49 1993 1.376 1994 0.962 1995 1.416