# northamerica_usa_ca642 - Climbing Bear Hill - 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/3683 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_usa_ca642 - Climbing Bear Hill - 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: Climbing Bear Hill # Location: # Country: United States # Northernmost_Latitude: 37.88 # Southernmost_Latitude: 37.88 # Easternmost_Longitude: -119.37 # Westernmost_Longitude: -119.37 # Elevation: 2626 m #-------------------- # Data_Collection # Collection_Name: northamerica_usa_ca642B # Earliest_Year: 1795 # Most_Recent_Year: 2005 # 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":"3.84807274267","T2":"13.7462712297","M1":"0.0225686099983","M2":"0.550406948656"}} #-------------------- # Species # Species_Name: lodgepole pine # Species_Code: PICO #-------------------- # 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 1795 0.897 1796 0.872 1797 1.022 1798 0.98 1799 0.963 1800 0.934 1801 1.067 1802 1.145 1803 0.993 1804 0.993 1805 1.173 1806 1.052 1807 1.068 1808 0.973 1809 0.963 1810 0.803 1811 0.647 1812 0.649 1813 0.794 1814 0.905 1815 1.017 1816 0.886 1817 0.973 1818 0.784 1819 0.959 1820 0.989 1821 0.881 1822 0.794 1823 0.915 1824 0.806 1825 0.965 1826 1.267 1827 1.088 1828 1.056 1829 1.083 1830 1.227 1831 0.882 1832 0.988 1833 0.96 1834 0.88 1835 0.888 1836 0.87 1837 0.917 1838 0.977 1839 0.905 1840 1.053 1841 0.921 1842 0.833 1843 0.803 1844 0.719 1845 1.11 1846 0.909 1847 0.761 1848 0.716 1849 0.855 1850 0.752 1851 0.657 1852 1.001 1853 0.757 1854 0.857 1855 0.915 1856 0.793 1857 0.851 1858 0.747 1859 0.869 1860 0.79 1861 0.86 1862 0.641 1863 0.833 1864 0.657 1865 0.889 1866 0.957 1867 1.073 1868 1.072 1869 1.17 1870 1.094 1871 1.074 1872 1.027 1873 1.137 1874 1.045 1875 1.197 1876 1.234 1877 1.238 1878 1.331 1879 1.15 1880 1.191 1881 1.47 1882 1.257 1883 0.948 1884 1.332 1885 1.361 1886 1.413 1887 1.242 1888 1.822 1889 1.435 1890 1.401 1891 1.502 1892 1.277 1893 1.267 1894 1.311 1895 1.2 1896 1.21 1897 1.238 1898 1.049 1899 0.898 1900 1.104 1901 1.459 1902 1.141 1903 0.985 1904 1.206 1905 0.884 1906 1.101 1907 1.272 1908 1.156 1909 0.995 1910 1.039 1911 0.901 1912 0.812 1913 0.782 1914 0.862 1915 0.831 1916 0.727 1917 0.803 1918 0.736 1919 0.976 1920 0.618 1921 0.611 1922 0.634 1923 0.74 1924 0.764 1925 0.852 1926 1.103 1927 0.889 1928 0.895 1929 0.801 1930 0.755 1931 1.09 1932 0.847 1933 0.745 1934 0.805 1935 0.898 1936 1.03 1937 1.069 1938 1.118 1939 1.04 1940 1.074 1941 0.931 1942 1.034 1943 0.888 1944 0.991 1945 1.063 1946 1.016 1947 1.003 1948 0.993 1949 0.983 1950 0.966 1951 0.935 1952 1.018 1953 0.918 1954 1.19 1955 0.854 1956 0.772 1957 0.628 1958 0.674 1959 0.154 1960 0.205 1961 0.303 1962 0.585 1963 0.692 1964 0.84 1965 0.813 1966 0.999 1967 1.049 1968 1.011 1969 1.385 1970 1.134 1971 0.907 1972 1.061 1973 1.23 1974 1.085 1975 1.061 1976 0.98 1977 1.156 1978 1.007 1979 0.867 1980 0.53 1981 0.196 1982 0.381 1983 0.862 1984 1.321 1985 1.059 1986 1.417 1987 1.394 1988 1.311 1989 1.223 1990 1.477 1991 1.153 1992 1.026 1993 1.295 1994 1.084 1995 1.016 1996 1.165 1997 1.069 1998 1.092 1999 1.151 2000 1.477 2001 1.222 2002 1.03 2003 0.846 2004 0.887 2005 1.021