# europe_spai041 - Gudar Los Roquetas - 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/4255 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai041 - Gudar Los Roquetas - 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: Gudar Los Roquetas # Location: # Country: Spain # Northernmost_Latitude: 40.28 # Southernmost_Latitude: 40.28 # Easternmost_Longitude: -0.7 # Westernmost_Longitude: -0.7 # Elevation: 1475 m #-------------------- # Data_Collection # Collection_Name: europe_spai041B # Earliest_Year: 1796 # Most_Recent_Year: 1985 # 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":"3.8142412782","T2":"16.3860682797","M1":"0.0229907337355","M2":"0.501801987227"}} #-------------------- # 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 1796 1.656 1797 1.333 1798 1.13 1799 1.176 1800 1.323 1801 1.639 1802 1.108 1803 0.308 1804 0.65 1805 0.413 1806 0.758 1807 0.644 1808 0.493 1809 0.852 1810 0.832 1811 1.037 1812 0.845 1813 0.774 1814 1.212 1815 1.215 1816 0.98 1817 0.732 1818 1.093 1819 1.09 1820 1.242 1821 0.945 1822 0.499 1823 1.327 1824 0.597 1825 1.179 1826 0.998 1827 1.106 1828 0.656 1829 1.035 1830 1.12 1831 0.897 1832 1.12 1833 1.116 1834 1.265 1835 1.257 1836 0.906 1837 0.8 1838 0.9 1839 0.898 1840 0.934 1841 1.381 1842 0.96 1843 0.958 1844 1.013 1845 1.078 1846 1.127 1847 1.006 1848 1.157 1849 0.375 1850 0.957 1851 0.719 1852 0.792 1853 1.045 1854 1.004 1855 0.697 1856 1.24 1857 0.771 1858 1.072 1859 0.741 1860 0.788 1861 1.113 1862 1.168 1863 1.174 1864 0.886 1865 0.985 1866 1.246 1867 0.587 1868 1.055 1869 0.496 1870 0.78 1871 0.928 1872 1.155 1873 0.938 1874 0.878 1875 0.81 1876 0.491 1877 0.544 1878 0.49 1879 0.319 1880 1.038 1881 0.643 1882 0.35 1883 0.541 1884 1.296 1885 1.287 1886 0.848 1887 0.599 1888 1.334 1889 1.4 1890 1.101 1891 1.173 1892 1.389 1893 1.083 1894 0.97 1895 1.177 1896 0.877 1897 0.921 1898 0.933 1899 1.127 1900 1.014 1901 0.956 1902 0.958 1903 1.378 1904 0.921 1905 0.963 1906 1.134 1907 0.996 1908 1.459 1909 0.745 1910 0.779 1911 1.064 1912 0.573 1913 0.747 1914 1.193 1915 1.25 1916 0.781 1917 0.904 1918 0.801 1919 1.087 1920 1.242 1921 0.882 1922 1.266 1923 1.301 1924 0.938 1925 0.578 1926 0.886 1927 1.069 1928 1.003 1929 1.021 1930 1.237 1931 0.796 1932 1.049 1933 1.265 1934 1.073 1935 1.12 1936 1.382 1937 1.24 1938 1.375 1939 0.948 1940 1.729 1941 1.222 1942 0.964 1943 1.028 1944 0.795 1945 0.598 1946 0.996 1947 0.812 1948 1.223 1949 1.196 1950 0.705 1951 1.266 1952 1.346 1953 0.784 1954 1.262 1955 1.305 1956 1.477 1957 1.158 1958 0.813 1959 1.425 1960 1.396 1961 0.85 1962 1.251 1963 0.866 1964 1.203 1965 0.56 1966 0.922 1967 0.371 1968 0.899 1969 0.734 1970 0.874 1971 0.982 1972 1.334 1973 1.577 1974 1.003 1975 0.787 1976 1.1 1977 1.331 1978 1.145 1979 0.512 1980 0.96 1981 0.324 1982 0.621 1983 0.573 1984 0.669 1985 0.778