# europe_ital019 - Corte Brugnatella (Piacenza) - 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/4042 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_ital019 - Corte Brugnatella (Piacenza) - 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: Corte Brugnatella (Piacenza) # Location: # Country: Italy # Northernmost_Latitude: 44.72 # Southernmost_Latitude: 44.72 # Easternmost_Longitude: 9.32 # Westernmost_Longitude: 9.32 # Elevation: 900 m #-------------------- # Data_Collection # Collection_Name: europe_ital019B # Earliest_Year: 1860 # Most_Recent_Year: 1989 # 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":"4.7676072129","T2":"13.2154495272","M1":"0.0226686048176","M2":"0.598237738845"}} #-------------------- # Species # Species_Name: English oak # Species_Code: QURO #-------------------- # 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 1860 0.779 1861 0.597 1862 0.976 1863 1.12 1864 0.92 1865 0.825 1866 0.826 1867 0.919 1868 1.142 1869 1.328 1870 1.085 1871 1.106 1872 1.073 1873 0.889 1874 0.944 1875 1.498 1876 1.123 1877 0.987 1878 1.075 1879 0.664 1880 0.645 1881 0.664 1882 0.653 1883 1.021 1884 1.165 1885 0.899 1886 1.095 1887 0.974 1888 1.107 1889 1.257 1890 0.915 1891 0.891 1892 0.806 1893 1.115 1894 1.015 1895 1.107 1896 1.017 1897 0.984 1898 1.164 1899 1.498 1900 1.183 1901 1.444 1902 1.022 1903 1.13 1904 1.024 1905 0.983 1906 1.183 1907 0.824 1908 1.068 1909 0.977 1910 0.987 1911 1.212 1912 1.13 1913 0.923 1914 1.203 1915 1.261 1916 1.148 1917 1.317 1918 1.155 1919 0.748 1920 0.733 1921 0.81 1922 0.797 1923 0.701 1924 0.982 1925 0.863 1926 1.001 1927 0.887 1928 0.813 1929 1.098 1930 1.19 1931 0.804 1932 1.057 1933 1.037 1934 0.909 1935 0.769 1936 0.896 1937 0.981 1938 0.804 1939 0.915 1940 1.181 1941 0.996 1942 0.876 1943 0.82 1944 0.966 1945 0.752 1946 0.828 1947 0.89 1948 0.973 1949 0.94 1950 0.543 1951 0.963 1952 0.878 1953 0.872 1954 1.026 1955 1.168 1956 1.084 1957 1.04 1958 0.936 1959 0.787 1960 0.995 1961 1.23 1962 1.047 1963 1.095 1964 0.971 1965 1.048 1966 1.077 1967 1.135 1968 1.341 1969 1.451 1970 0.988 1971 1.158 1972 1.065 1973 1.042 1974 0.851 1975 1.059 1976 0.915 1977 0.738 1978 1.043 1979 1.026 1980 0.939 1981 0.856 1982 0.975 1983 0.962 1984 0.717 1985 0.938 1986 1.129 1987 0.902 1988 1.071 1989 1.014