# northamerica_usa_nm551 - Garcia Park - 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/5079 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_nm551 - Garcia Park - 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: Garcia Park # Location: # Country: United States # Northernmost_Latitude: 36.33 # Southernmost_Latitude: 36.33 # Easternmost_Longitude: -105.37 # Westernmost_Longitude: -105.37 # Elevation: 2743 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_nm551B # Earliest_Year: 1705 # Most_Recent_Year: 1981 # 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":"3.60947825598","T2":"14.5883193723","M1":"0.0224157070374","M2":"0.546585455309"}} #-------------------- # Species # Species_Name: ponderosa pine # Species_Code: PIPO #-------------------- # 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 1705 0.917 1706 1.005 1707 0.491 1708 0.831 1709 0.761 1710 1.219 1711 0.867 1712 1.03 1713 0.997 1714 0.794 1715 0.45 1716 0.351 1717 0.639 1718 1.086 1719 0.6 1720 1.482 1721 0.912 1722 0.864 1723 0.698 1724 1.06 1725 0.661 1726 1.346 1727 0.757 1728 0.427 1729 0.09 1730 0.428 1731 0.464 1732 0.606 1733 0.484 1734 0.865 1735 0.36 1736 0.763 1737 0.347 1738 0.635 1739 0.544 1740 0.789 1741 0.612 1742 0.9 1743 1.188 1744 0.872 1745 0.992 1746 1.208 1747 1.183 1748 0.174 1749 0.844 1750 0.789 1751 1.005 1752 0.162 1753 0.452 1754 0.88 1755 1.002 1756 0.942 1757 0.749 1758 0.89 1759 0.864 1760 1.099 1761 1.503 1762 1.481 1763 1.248 1764 1.831 1765 0.83 1766 1.594 1767 1.39 1768 1.577 1769 1.596 1770 1.369 1771 1.799 1772 1.586 1773 0.646 1774 1.066 1775 0.822 1776 0.939 1777 0.69 1778 0.434 1779 0.578 1780 0.366 1781 0.471 1782 0.69 1783 0.957 1784 1.145 1785 0.971 1786 0.876 1787 1.421 1788 1.053 1789 0.921 1790 0.836 1791 1.236 1792 1.528 1793 1.813 1794 1.386 1795 1.056 1796 1.235 1797 1.323 1798 0.726 1799 1.215 1800 1.392 1801 0.191 1802 0.882 1803 1.007 1804 1.226 1805 0.989 1806 0.706 1807 1.066 1808 0.64 1809 0.668 1810 0.975 1811 1.048 1812 1.119 1813 1.341 1814 0.607 1815 1.293 1816 1.406 1817 1.125 1818 0.823 1819 0.543 1820 0.932 1821 1.249 1822 0.943 1823 1.038 1824 0.956 1825 1.45 1826 1.308 1827 1.505 1828 1.682 1829 1.354 1830 1.132 1831 1.26 1832 1.503 1833 1.652 1834 1.561 1835 1.697 1836 1.014 1837 1.372 1838 1.352 1839 1.616 1840 1.557 1841 1.049 1842 0.326 1843 0.863 1844 0.967 1845 0.68 1846 0.368 1847 0.411 1848 0.368 1849 0.766 1850 0.678 1851 0.169 1852 0.731 1853 0.946 1854 1.191 1855 1.012 1856 0.96 1857 0.934 1858 1.03 1859 0.738 1860 0.853 1861 0.33 1862 0.732 1863 0.692 1864 0.723 1865 0.777 1866 1.059 1867 1.26 1868 1.371 1869 1.372 1870 1.278 1871 0.872 1872 1.254 1873 0.886 1874 0.909 1875 1.094 1876 1.274 1877 0.958 1878 1.076 1879 0.873 1880 0.318 1881 0.699 1882 1.201 1883 0.988 1884 1.316 1885 1.686 1886 1.614 1887 2.054 1888 1.57 1889 1.757 1890 1.203 1891 1.14 1892 1.111 1893 0.852 1894 0.716 1895 1.458 1896 0.64 1897 1.365 1898 1.053 1899 0.587 1900 0.651 1901 0.705 1902 0.458 1903 1.087 1904 0.696 1905 1.06 1906 1.261 1907 1.643 1908 1.338 1909 1.227 1910 1.299 1911 1.536 1912 1.271 1913 1.052 1914 1.478 1915 1.335 1916 1.228 1917 0.794 1918 0.969 1919 1.04 1920 1.021 1921 1.383 1922 0.531 1923 0.424 1924 0.711 1925 0.6 1926 0.836 1927 0.736 1928 0.744 1929 1.222 1930 0.972 1931 0.514 1932 0.847 1933 0.777 1934 0.33 1935 0.915 1936 0.588 1937 1.005 1938 0.765 1939 0.772 1940 0.72 1941 1.233 1942 1.116 1943 0.986 1944 1.14 1945 1.295 1946 0.35 1947 0.924 1948 0.833 1949 1.033 1950 0.839 1951 0.492 1952 0.807 1953 0.755 1954 0.872 1955 0.806 1956 0.053 1957 0.413 1958 0.66 1959 0.401 1960 0.954 1961 0.758 1962 0.963 1963 0.47 1964 1.047 1965 1.565 1966 1.374 1967 0.957 1968 1.035 1969 1.471 1970 0.809 1971 0.168 1972 0.419 1973 0.831 1974 0.908 1975 1.327 1976 1.116 1977 0.85 1978 0.906 1979 1.055 1980 1.118 1981 0.964