# europe_spai043 - Gudar Villarluengo - 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/4257 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai043 - Gudar Villarluengo - 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 Villarluengo # Location: # Country: Spain # Northernmost_Latitude: 40.63 # Southernmost_Latitude: 40.63 # Easternmost_Longitude: -0.48 # Westernmost_Longitude: -0.48 # Elevation: 1500 m #-------------------- # Data_Collection # Collection_Name: europe_spai043B # Earliest_Year: 1841 # 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":"4.45468025237","T2":"17.8423779269","M1":"0.0223917533645","M2":"0.461335025153"}} #-------------------- # 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 1841 1.329 1842 0.914 1843 1.18 1844 0.778 1845 1.055 1846 1.104 1847 0.62 1848 0.734 1849 0.527 1850 0.587 1851 0.744 1852 0.779 1853 1.05 1854 1.13 1855 0.741 1856 1.155 1857 1.099 1858 1.06 1859 0.976 1860 0.882 1861 1.024 1862 1.089 1863 1.15 1864 1.241 1865 1.366 1866 1.074 1867 0.747 1868 1.157 1869 1.445 1870 0.796 1871 1.159 1872 1.328 1873 0.917 1874 1.026 1875 1.053 1876 0.779 1877 0.789 1878 0.858 1879 0.522 1880 1.059 1881 1.065 1882 0.728 1883 0.693 1884 0.968 1885 1.264 1886 1.188 1887 0.863 1888 1.004 1889 1.333 1890 0.907 1891 0.775 1892 1.075 1893 1.004 1894 0.894 1895 0.899 1896 1.122 1897 0.978 1898 0.806 1899 1.174 1900 1.091 1901 1.063 1902 0.928 1903 1.174 1904 1.111 1905 1.039 1906 0.983 1907 0.815 1908 1.345 1909 0.789 1910 0.888 1911 1.334 1912 0.838 1913 0.8 1914 1.816 1915 1.579 1916 0.779 1917 0.821 1918 0.752 1919 0.774 1920 1.062 1921 0.77 1922 0.873 1923 1.096 1924 0.608 1925 0.656 1926 1.068 1927 1.194 1928 0.908 1929 1.184 1930 1.043 1931 0.508 1932 1.154 1933 1.265 1934 0.883 1935 1.289 1936 1.112 1937 1.483 1938 1.584 1939 1.18 1940 1.187 1941 0.827 1942 0.856 1943 1.211 1944 0.971 1945 0.784 1946 0.778 1947 1.019 1948 0.854 1949 0.719 1950 0.562 1951 1.243 1952 1.446 1953 0.782 1954 0.778 1955 0.912 1956 1.015 1957 1.043 1958 1.525 1959 1.973 1960 1.783 1961 0.648 1962 1.091 1963 0.944 1964 1.516 1965 0.828 1966 0.983 1967 0.637 1968 0.831 1969 0.684 1970 0.581 1971 0.585 1972 0.784 1973 1.047 1974 0.726 1975 0.745 1976 0.867 1977 1.619 1978 1.002 1979 0.816 1980 1.116 1981 0.846 1982 0.911 1983 0.539 1984 0.783 1985 0.536