# europe_roma002 - Novaci - 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/4565 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_roma002 - Novaci - 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: Novaci # Location: # Country: Romania # Northernmost_Latitude: 45.3 # Southernmost_Latitude: 45.3 # Easternmost_Longitude: 23.67 # Westernmost_Longitude: 23.67 # Elevation: 1650 m #-------------------- # Data_Collection # Collection_Name: europe_roma002B # Earliest_Year: 1838 # Most_Recent_Year: 1981 # 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":"5.4449327238","T2":"19.5641899271","M1":"0.0225274288474","M2":"0.344004280742"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1838 0.895 1839 1.121 1840 1.271 1841 1.37 1842 1.071 1843 1.218 1844 1.122 1845 0.904 1846 1.025 1847 1.087 1848 1.182 1849 1.095 1850 1.15 1851 0.859 1852 0.855 1853 1.002 1854 0.965 1855 1.122 1856 0.938 1857 0.95 1858 0.881 1859 0.669 1860 0.651 1861 0.707 1862 1.179 1863 0.963 1864 0.875 1865 0.992 1866 0.886 1867 0.783 1868 0.857 1869 0.672 1870 0.745 1871 0.839 1872 0.731 1873 0.736 1874 0.816 1875 0.816 1876 0.835 1877 0.895 1878 0.729 1879 0.837 1880 0.961 1881 0.915 1882 0.883 1883 0.906 1884 1.333 1885 1.281 1886 1.686 1887 1.451 1888 1.673 1889 1.451 1890 1.453 1891 0.944 1892 0.885 1893 0.577 1894 0.826 1895 0.993 1896 1.146 1897 1.187 1898 1.222 1899 1.408 1900 1.634 1901 1.481 1902 1.519 1903 1.283 1904 1.254 1905 0.886 1906 0.595 1907 0.854 1908 0.887 1909 0.969 1910 0.832 1911 0.938 1912 0.959 1913 0.839 1914 0.743 1915 0.954 1916 1.052 1917 1.078 1918 0.858 1919 0.852 1920 0.754 1921 0.631 1922 0.756 1923 0.762 1924 0.777 1925 0.756 1926 0.964 1927 1.142 1928 0.994 1929 0.999 1930 1.007 1931 1.191 1932 0.992 1933 0.702 1934 0.945 1935 0.906 1936 0.945 1937 1.04 1938 0.958 1939 1.108 1940 0.892 1941 1.031 1942 1.046 1943 0.863 1944 0.934 1945 0.943 1946 1.054 1947 0.847 1948 0.895 1949 0.935 1950 1.207 1951 1.055 1952 1.034 1953 1.142 1954 1.214 1955 1.152 1956 1.053 1957 0.836 1958 0.898 1959 0.896 1960 0.922 1961 0.888 1962 0.916 1963 0.875 1964 0.762 1965 0.741 1966 0.795 1967 0.816 1968 0.892 1969 1.03 1970 1.062 1971 0.967 1972 1.105 1973 0.898 1974 0.955 1975 0.728 1976 0.611 1977 0.885 1978 0.829 1979 1.189 1980 1.1 1981 1.229