# northamerica_usa_wa009 - War 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/2917 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_wa009 - War 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: War Creek # Location: # Country: United States # Northernmost_Latitude: 48.42 # Southernmost_Latitude: 48.42 # Easternmost_Longitude: -120.4 # Westernmost_Longitude: -120.4 # Elevation: 1224 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_wa009B # Earliest_Year: 1763 # Most_Recent_Year: 1975 # 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":"2.8016498772","T2":"14.2694077926","M1":"0.0236089295027","M2":"0.552874644184"}} #-------------------- # 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 1763 1.011 1764 0.869 1765 0.998 1766 1.218 1767 0.861 1768 0.821 1769 0.798 1770 1.082 1771 1.089 1772 1.019 1773 1.069 1774 0.905 1775 0.855 1776 0.836 1777 0.847 1778 1.161 1779 0.963 1780 1.04 1781 0.872 1782 0.857 1783 0.895 1784 0.977 1785 1.069 1786 0.907 1787 0.855 1788 1.007 1789 1.291 1790 0.757 1791 0.685 1792 0.825 1793 1.141 1794 0.877 1795 1.045 1796 0.946 1797 0.804 1798 0.886 1799 1.076 1800 1.29 1801 1.281 1802 1.081 1803 1.148 1804 1.06 1805 1.292 1806 1.042 1807 0.943 1808 1.056 1809 1.204 1810 1.018 1811 0.987 1812 0.941 1813 1.029 1814 1.284 1815 1.071 1816 1.252 1817 0.891 1818 1.058 1819 1.023 1820 0.938 1821 0.795 1822 0.996 1823 0.947 1824 0.963 1825 1.233 1826 1.024 1827 0.852 1828 0.921 1829 1.01 1830 0.777 1831 0.777 1832 1.2 1833 1.088 1834 0.909 1835 0.824 1836 0.997 1837 1.053 1838 0.931 1839 0.85 1840 0.807 1841 0.982 1842 0.76 1843 0.771 1844 0.92 1845 1.275 1846 1.45 1847 0.834 1848 0.806 1849 0.729 1850 0.693 1851 0.977 1852 0.871 1853 1.015 1854 0.922 1855 1.305 1856 1.266 1857 0.967 1858 1.003 1859 0.852 1860 1.017 1861 1.092 1862 0.989 1863 0.984 1864 1.026 1865 0.83 1866 1.006 1867 0.951 1868 1.022 1869 0.765 1870 0.68 1871 0.777 1872 0.896 1873 1.094 1874 1.116 1875 0.929 1876 0.896 1877 1.291 1878 1.206 1879 1.086 1880 0.959 1881 1.233 1882 0.966 1883 0.861 1884 1.038 1885 1.535 1886 0.9 1887 0.784 1888 0.915 1889 0.54 1890 0.871 1891 0.807 1892 0.976 1893 0.899 1894 0.87 1895 0.906 1896 0.863 1897 1.053 1898 0.81 1899 0.718 1900 1.123 1901 1.112 1902 1.01 1903 1.056 1904 1.137 1905 1.298 1906 1.436 1907 1.103 1908 1.309 1909 0.948 1910 0.89 1911 0.964 1912 1.255 1913 1.267 1914 1.153 1915 1.264 1916 0.946 1917 0.653 1918 0.775 1919 0.815 1920 0.848 1921 0.992 1922 0.475 1923 0.742 1924 0.58 1925 0.578 1926 0.502 1927 0.655 1928 0.723 1929 0.439 1930 0.722 1931 0.574 1932 0.522 1933 0.529 1934 0.893 1935 0.424 1936 0.469 1937 0.572 1938 0.819 1939 0.8 1940 0.84 1941 1.145 1942 1.383 1943 1.008 1944 1.066 1945 1.03 1946 1.204 1947 1.24 1948 1.151 1949 1.191 1950 1.131 1951 1.255 1952 1.195 1953 1.453 1954 1.409 1955 1.632 1956 1.245 1957 1.041 1958 0.959 1959 1.051 1960 1.493 1961 1.351 1962 1.392 1963 1.171 1964 1.181 1965 1.129 1966 1.335 1967 1.264 1968 1.268 1969 1.159 1970 0.855 1971 1.093 1972 1.127 1973 0.872 1974 0.958 1975 0.276