# europe_spai007 - Torrecilla Ronda - 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/4686 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai007 - Torrecilla Ronda - 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: Torrecilla Ronda # Location: # Country: Spain # Northernmost_Latitude: 36.67 # Southernmost_Latitude: 36.67 # Easternmost_Longitude: -5.08 # Westernmost_Longitude: -5.08 # Elevation: 1650 m #-------------------- # Data_Collection # Collection_Name: europe_spai007B # Earliest_Year: 1790 # Most_Recent_Year: 1982 # 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":"5.40862200862","T2":"17.0007622349","M1":"0.0226200019599","M2":"0.416819476787"}} #-------------------- # Species # Species_Name: Spanish fir # Species_Code: ABPN #-------------------- # 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 1790 1.077 1791 1.117 1792 1.058 1793 1.144 1794 1.35 1795 1.396 1796 1.181 1797 1.024 1798 0.894 1799 0.975 1800 0.953 1801 1.384 1802 1.01 1803 0.889 1804 0.763 1805 1.144 1806 1.195 1807 1.199 1808 0.951 1809 1.323 1810 1.201 1811 1.121 1812 0.854 1813 0.972 1814 0.965 1815 1.317 1816 1.264 1817 1.203 1818 1.37 1819 0.991 1820 0.657 1821 0.717 1822 0.819 1823 1.078 1824 0.697 1825 0.885 1826 0.693 1827 0.7 1828 0.769 1829 0.807 1830 1.081 1831 0.731 1832 1.096 1833 0.981 1834 1.046 1835 1.272 1836 0.963 1837 0.954 1838 0.864 1839 0.861 1840 0.693 1841 0.801 1842 0.997 1843 1.23 1844 1.027 1845 1.093 1846 1.0 1847 0.93 1848 0.728 1849 0.92 1850 1.05 1851 1.017 1852 0.911 1853 0.797 1854 0.978 1855 0.824 1856 1.064 1857 0.827 1858 0.818 1859 0.9 1860 0.981 1861 1.212 1862 1.259 1863 0.984 1864 1.104 1865 0.919 1866 1.029 1867 0.755 1868 1.028 1869 1.069 1870 0.766 1871 0.807 1872 0.951 1873 1.161 1874 0.938 1875 1.15 1876 1.092 1877 1.14 1878 0.929 1879 0.76 1880 0.783 1881 0.875 1882 0.954 1883 0.971 1884 1.093 1885 0.993 1886 0.966 1887 1.077 1888 0.786 1889 0.837 1890 0.816 1891 1.191 1892 1.21 1893 1.044 1894 0.896 1895 1.039 1896 1.135 1897 1.174 1898 0.981 1899 1.089 1900 0.907 1901 1.185 1902 1.169 1903 1.441 1904 1.141 1905 1.288 1906 0.917 1907 0.911 1908 0.956 1909 0.844 1910 0.807 1911 0.73 1912 0.818 1913 0.975 1914 1.006 1915 0.724 1916 0.749 1917 0.694 1918 0.712 1919 0.763 1920 0.833 1921 0.998 1922 1.012 1923 0.904 1924 0.678 1925 0.8 1926 1.077 1927 0.965 1928 0.742 1929 1.065 1930 1.17 1931 0.978 1932 1.247 1933 1.13 1934 0.8 1935 0.935 1936 0.816 1937 1.028 1938 0.955 1939 0.959 1940 1.24 1941 1.157 1942 0.962 1943 0.691 1944 1.147 1945 1.044 1946 0.701 1947 0.577 1948 0.651 1949 0.739 1950 0.84 1951 0.766 1952 0.922 1953 0.88 1954 0.803 1955 0.959 1956 1.123 1957 1.501 1958 1.271 1959 1.112 1960 1.108 1961 1.095 1962 1.185 1963 0.811 1964 0.747 1965 0.827 1966 1.172 1967 1.093 1968 0.963 1969 1.106 1970 1.463 1971 0.951 1972 0.965 1973 1.224 1974 1.126 1975 1.067 1976 1.291 1977 1.211 1978 1.425 1979 1.009 1980 1.018 1981 1.045 1982 1.143