# europe_ital011 - Mount Pollino - 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/4541 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_ital011 - Mount Pollino - 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: Mount Pollino # Location: # Country: Italy # Northernmost_Latitude: 39.9 # Southernmost_Latitude: 39.9 # Easternmost_Longitude: 16.2 # Westernmost_Longitude: 16.2 # Elevation: 1720 m #-------------------- # Data_Collection # Collection_Name: europe_ital011B # Earliest_Year: 1830 # Most_Recent_Year: 1980 # 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":"5.22282020082","T2":"16.6716756557","M1":"0.0220933770537","M2":"0.222903862795"}} #-------------------- # Species # Species_Name: silver fir # Species_Code: ABAL #-------------------- # 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 1830 0.764 1831 0.789 1832 1.019 1833 0.93 1834 0.848 1835 0.76 1836 0.719 1837 0.926 1838 0.763 1839 0.784 1840 0.692 1841 0.686 1842 0.729 1843 0.719 1844 0.81 1845 0.732 1846 0.862 1847 0.76 1848 0.732 1849 0.92 1850 0.721 1851 1.0 1852 0.804 1853 0.617 1854 0.638 1855 0.859 1856 0.667 1857 0.401 1858 0.691 1859 0.745 1860 0.575 1861 0.611 1862 0.838 1863 0.775 1864 0.976 1865 1.031 1866 1.25 1867 1.035 1868 0.989 1869 0.888 1870 1.301 1871 1.62 1872 1.42 1873 1.595 1874 1.059 1875 1.016 1876 1.568 1877 1.134 1878 0.853 1879 0.762 1880 0.779 1881 0.905 1882 0.652 1883 1.074 1884 1.23 1885 1.286 1886 1.064 1887 1.343 1888 1.085 1889 1.069 1890 1.089 1891 0.997 1892 1.18 1893 1.194 1894 0.931 1895 0.948 1896 0.953 1897 1.341 1898 1.06 1899 1.663 1900 1.378 1901 1.484 1902 1.487 1903 1.136 1904 1.451 1905 1.293 1906 1.159 1907 1.063 1908 1.123 1909 1.281 1910 1.414 1911 1.042 1912 1.026 1913 0.898 1914 0.753 1915 0.931 1916 0.72 1917 0.84 1918 0.561 1919 0.561 1920 0.57 1921 0.603 1922 0.848 1923 1.003 1924 0.856 1925 1.057 1926 1.264 1927 0.911 1928 0.913 1929 0.769 1930 1.575 1931 1.076 1932 0.854 1933 0.923 1934 1.482 1935 0.986 1936 1.199 1937 1.084 1938 0.9 1939 0.838 1940 0.952 1941 0.98 1942 1.2 1943 1.101 1944 1.075 1945 0.951 1946 1.004 1947 1.098 1948 1.129 1949 1.136 1950 1.331 1951 1.141 1952 1.348 1953 1.007 1954 0.791 1955 0.786 1956 0.857 1957 0.614 1958 0.645 1959 0.945 1960 0.902 1961 0.976 1962 0.765 1963 0.891 1964 1.113 1965 0.675 1966 0.976 1967 0.972 1968 1.044 1969 1.218 1970 1.227 1971 1.246 1972 1.094 1973 1.008 1974 0.761 1975 0.898 1976 0.819 1977 0.76 1978 0.641 1979 0.684 1980 0.562