# europe_gree003 - Panetolikon-Oro - 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/4581 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_gree003 - Panetolikon-Oro - 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: Panetolikon-Oro # Location: # Country: Greece # Northernmost_Latitude: 38.72 # Southernmost_Latitude: 38.72 # Easternmost_Longitude: 21.67 # Westernmost_Longitude: 21.67 # Elevation: 1350 m #-------------------- # Data_Collection # Collection_Name: europe_gree003B # Earliest_Year: 1858 # Most_Recent_Year: 1981 # 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":"4.52184782126","T2":"13.9002760809","M1":"0.0228203211638","M2":"0.426502738249"}} #-------------------- # Species # Species_Name: Bulgarian fir # Species_Code: ABBO #-------------------- # 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 1858 1.041 1859 1.286 1860 1.34 1861 0.998 1862 1.01 1863 0.906 1864 1.013 1865 1.132 1866 1.212 1867 1.072 1868 1.011 1869 0.906 1870 0.92 1871 0.92 1872 0.961 1873 1.051 1874 1.045 1875 0.884 1876 1.31 1877 1.281 1878 0.924 1879 0.773 1880 0.673 1881 0.99 1882 0.858 1883 0.803 1884 1.275 1885 1.544 1886 1.14 1887 0.898 1888 0.962 1889 0.845 1890 0.79 1891 0.748 1892 0.71 1893 0.987 1894 0.925 1895 0.924 1896 0.891 1897 1.01 1898 0.946 1899 1.085 1900 1.06 1901 1.2 1902 1.025 1903 1.104 1904 1.051 1905 1.064 1906 0.973 1907 0.816 1908 0.74 1909 0.913 1910 0.927 1911 1.146 1912 1.363 1913 1.729 1914 1.414 1915 1.079 1916 0.75 1917 1.322 1918 1.022 1919 1.02 1920 1.083 1921 1.091 1922 0.911 1923 0.717 1924 0.787 1925 0.874 1926 0.875 1927 0.759 1928 0.791 1929 0.582 1930 0.79 1931 0.702 1932 0.597 1933 0.776 1934 0.869 1935 0.821 1936 1.072 1937 1.041 1938 1.001 1939 0.887 1940 0.694 1941 0.822 1942 0.972 1943 0.824 1944 0.741 1945 0.927 1946 0.962 1947 1.02 1948 1.239 1949 0.988 1950 1.097 1951 1.094 1952 0.818 1953 1.058 1954 0.784 1955 0.872 1956 0.89 1957 0.922 1958 0.794 1959 1.226 1960 1.176 1961 1.383 1962 1.141 1963 0.826 1964 1.285 1965 1.134 1966 0.979 1967 0.86 1968 0.721 1969 0.628 1970 0.738 1971 0.779 1972 0.784 1973 0.917 1974 0.948 1975 1.371 1976 1.159 1977 1.155 1978 0.975 1979 0.944 1980 0.48 1981 0.884