# europe_spai010 - Tierra Muerta - 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/3291 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai010 - Tierra Muerta - 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: Tierra Muerta # Location: # Country: Spain # Northernmost_Latitude: 40.3 # Southernmost_Latitude: 40.3 # Easternmost_Longitude: -2.13 # Westernmost_Longitude: -2.13 # Elevation: 1350 m #-------------------- # Data_Collection # Collection_Name: europe_spai010B # Earliest_Year: 1786 # Most_Recent_Year: 1988 # 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":"4.30266275471","T2":"15.8259029008","M1":"0.0229964844651","M2":"0.428592870524"}} #-------------------- # 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 1786 0.983 1787 1.024 1788 1.47 1789 0.708 1790 0.629 1791 0.955 1792 1.167 1793 1.21 1794 1.319 1795 1.344 1796 1.478 1797 0.952 1798 0.887 1799 1.006 1800 0.992 1801 1.185 1802 0.902 1803 0.528 1804 0.828 1805 0.763 1806 0.66 1807 0.867 1808 0.834 1809 0.932 1810 1.032 1811 1.142 1812 0.561 1813 1.039 1814 1.14 1815 1.113 1816 0.94 1817 1.238 1818 1.284 1819 1.039 1820 0.264 1821 0.545 1822 0.692 1823 0.816 1824 0.621 1825 0.852 1826 0.943 1827 0.847 1828 0.916 1829 1.1 1830 1.022 1831 1.27 1832 1.113 1833 1.12 1834 1.667 1835 1.111 1836 0.814 1837 1.001 1838 1.023 1839 0.995 1840 0.928 1841 0.522 1842 0.382 1843 0.967 1844 1.119 1845 1.375 1846 1.789 1847 1.044 1848 0.397 1849 0.665 1850 0.997 1851 0.991 1852 0.467 1853 0.299 1854 0.808 1855 0.976 1856 1.659 1857 1.669 1858 1.539 1859 1.429 1860 0.669 1861 0.905 1862 1.001 1863 1.224 1864 1.341 1865 1.263 1866 0.934 1867 1.04 1868 1.132 1869 1.262 1870 0.924 1871 0.866 1872 1.01 1873 0.911 1874 1.257 1875 1.231 1876 1.127 1877 1.302 1878 0.716 1879 0.42 1880 1.042 1881 1.33 1882 1.027 1883 1.378 1884 1.392 1885 1.717 1886 1.466 1887 0.948 1888 1.161 1889 1.177 1890 0.881 1891 0.824 1892 1.224 1893 0.97 1894 0.837 1895 0.848 1896 0.975 1897 0.915 1898 0.596 1899 0.399 1900 0.514 1901 0.634 1902 0.952 1903 1.274 1904 0.851 1905 1.042 1906 1.189 1907 1.028 1908 1.073 1909 0.696 1910 0.818 1911 1.107 1912 1.223 1913 1.071 1914 1.037 1915 0.597 1916 0.699 1917 0.85 1918 0.779 1919 1.044 1920 1.326 1921 1.004 1922 1.038 1923 1.471 1924 0.612 1925 0.713 1926 1.135 1927 0.945 1928 1.102 1929 1.124 1930 1.042 1931 0.88 1932 1.164 1933 1.397 1934 0.59 1935 0.568 1936 1.109 1937 1.282 1938 1.026 1939 1.128 1940 1.379 1941 1.133 1942 1.037 1943 1.022 1944 1.069 1945 1.045 1946 0.764 1947 0.556 1948 0.931 1949 0.705 1950 0.972 1951 1.096 1952 1.367 1953 1.183 1954 0.913 1955 0.962 1956 0.962 1957 0.956 1958 1.059 1959 1.113 1960 1.014 1961 1.173 1962 0.653 1963 0.408 1964 0.621 1965 0.519 1966 0.797 1967 0.664 1968 0.424 1969 0.612 1970 0.785 1971 0.883 1972 0.812 1973 1.151 1974 1.023 1975 1.192 1976 1.3 1977 1.366 1978 0.944 1979 0.987 1980 1.261 1981 0.85 1982 1.024 1983 0.869 1984 0.747 1985 0.937 1986 0.897 1987 0.969 1988 1.064