# europe_spai016 - Penahorcada - 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/3287 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai016 - Penahorcada - 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: Penahorcada # Location: # Country: Spain # Northernmost_Latitude: 40.48 # Southernmost_Latitude: 40.48 # Easternmost_Longitude: -4.78 # Westernmost_Longitude: -4.78 # Elevation: 1450 m #-------------------- # Data_Collection # Collection_Name: europe_spai016B # Earliest_Year: 1787 # Most_Recent_Year: 1988 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.48976249775","T2":"15.0054819601","M1":"0.0218773122113","M2":"0.304405176331"}} #-------------------- # Species # Species_Name: Austrian pine # Species_Code: PINI #-------------------- # 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 1787 0.826 1788 1.138 1789 0.955 1790 1.045 1791 1.285 1792 1.221 1793 1.168 1794 1.532 1795 1.448 1796 1.179 1797 1.053 1798 1.045 1799 1.287 1800 1.045 1801 0.774 1802 0.635 1803 0.521 1804 0.76 1805 0.95 1806 0.914 1807 1.151 1808 0.999 1809 1.18 1810 1.223 1811 1.239 1812 0.671 1813 0.523 1814 0.875 1815 1.129 1816 0.861 1817 1.033 1818 0.93 1819 1.046 1820 1.036 1821 1.052 1822 1.106 1823 1.157 1824 1.034 1825 1.377 1826 1.188 1827 0.903 1828 1.16 1829 0.953 1830 0.874 1831 0.738 1832 0.7 1833 0.744 1834 1.275 1835 1.131 1836 1.111 1837 1.057 1838 0.786 1839 0.912 1840 0.812 1841 0.773 1842 0.704 1843 0.821 1844 0.917 1845 0.973 1846 1.303 1847 0.69 1848 0.622 1849 0.809 1850 1.124 1851 0.79 1852 0.849 1853 1.041 1854 0.95 1855 0.719 1856 1.024 1857 0.761 1858 1.08 1859 1.268 1860 0.939 1861 1.239 1862 0.966 1863 1.373 1864 1.389 1865 1.325 1866 1.056 1867 0.923 1868 0.899 1869 1.186 1870 0.677 1871 0.541 1872 0.714 1873 0.647 1874 0.702 1875 0.859 1876 0.824 1877 1.087 1878 1.293 1879 0.691 1880 1.06 1881 1.237 1882 1.116 1883 1.273 1884 1.033 1885 1.482 1886 1.379 1887 1.031 1888 1.178 1889 0.921 1890 0.693 1891 0.629 1892 0.948 1893 1.036 1894 0.781 1895 1.067 1896 1.098 1897 0.928 1898 1.013 1899 1.197 1900 0.836 1901 0.644 1902 0.928 1903 1.411 1904 1.13 1905 1.019 1906 0.965 1907 0.911 1908 0.815 1909 0.693 1910 0.83 1911 0.948 1912 1.051 1913 0.946 1914 1.384 1915 0.787 1916 0.885 1917 0.733 1918 0.706 1919 1.048 1920 1.115 1921 0.908 1922 0.862 1923 1.188 1924 0.699 1925 0.824 1926 1.033 1927 0.853 1928 0.843 1929 1.103 1930 1.198 1931 0.86 1932 0.861 1933 1.026 1934 0.6 1935 0.528 1936 0.815 1937 1.194 1938 1.119 1939 1.039 1940 1.622 1941 0.9 1942 0.548 1943 0.863 1944 0.898 1945 1.144 1946 0.701 1947 0.839 1948 0.952 1949 0.815 1950 1.082 1951 0.986 1952 1.181 1953 1.268 1954 1.03 1955 0.988 1956 0.832 1957 1.209 1958 1.154 1959 1.151 1960 1.163 1961 1.211 1962 0.742 1963 0.697 1964 1.277 1965 0.762 1966 0.826 1967 1.008 1968 0.855 1969 0.974 1970 0.995 1971 0.96 1972 0.844 1973 1.491 1974 1.247 1975 1.022 1976 1.32 1977 1.397 1978 1.285 1979 0.795 1980 1.141 1981 0.856 1982 0.909 1983 1.185 1984 1.155 1985 1.02 1986 0.671 1987 1.04 1988 1.293