# europe_ital018 - Monza (Milano) - 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/4044 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_ital018 - Monza (Milano) - 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: Monza (Milano) # Location: # Country: Italy # Northernmost_Latitude: 45.57 # Southernmost_Latitude: 45.57 # Easternmost_Longitude: 9.28 # Westernmost_Longitude: 9.28 # Elevation: 190 m #-------------------- # Data_Collection # Collection_Name: europe_ital018B # Earliest_Year: 1830 # Most_Recent_Year: 1990 # 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":"5.92710122245","T2":"15.7157322786","M1":"0.0227413381525","M2":"0.583728680851"}} #-------------------- # Species # Species_Name: oak # Species_Code: QUSP #-------------------- # 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 0.775 1831 0.916 1832 0.993 1833 1.002 1834 0.814 1835 1.087 1836 0.742 1837 0.608 1838 0.929 1839 0.72 1840 1.092 1841 1.339 1842 0.7 1843 0.898 1844 1.054 1845 1.134 1846 1.068 1847 0.813 1848 1.035 1849 0.824 1850 1.138 1851 1.401 1852 0.975 1853 1.029 1854 1.178 1855 0.489 1856 0.642 1857 0.735 1858 0.857 1859 1.08 1860 0.852 1861 0.91 1862 0.896 1863 1.116 1864 0.804 1865 0.796 1866 0.742 1867 1.157 1868 0.873 1869 1.261 1870 0.788 1871 1.27 1872 1.03 1873 1.0 1874 1.442 1875 1.329 1876 1.079 1877 1.008 1878 1.084 1879 0.9 1880 0.886 1881 0.706 1882 0.714 1883 0.79 1884 0.918 1885 0.732 1886 1.084 1887 1.078 1888 1.097 1889 1.397 1890 1.288 1891 1.162 1892 0.827 1893 1.245 1894 0.896 1895 0.826 1896 0.952 1897 0.916 1898 1.332 1899 0.813 1900 1.053 1901 0.993 1902 1.104 1903 1.025 1904 0.821 1905 0.935 1906 0.978 1907 0.61 1908 0.732 1909 0.652 1910 0.592 1911 0.98 1912 0.886 1913 0.776 1914 1.235 1915 1.087 1916 1.198 1917 1.14 1918 1.156 1919 0.532 1920 0.711 1921 0.892 1922 0.686 1923 0.902 1924 0.994 1925 0.944 1926 1.243 1927 1.128 1928 0.542 1929 0.544 1930 0.356 1931 0.69 1932 1.339 1933 1.352 1934 1.139 1935 0.936 1936 0.665 1937 1.274 1938 1.045 1939 0.98 1940 1.128 1941 0.573 1942 0.266 1943 0.453 1944 0.536 1945 0.553 1946 1.167 1947 0.978 1948 0.884 1949 1.239 1950 0.917 1951 1.343 1952 1.366 1953 1.749 1954 1.531 1955 1.544 1956 1.823 1957 1.224 1958 1.385 1959 1.187 1960 1.451 1961 1.424 1962 1.166 1963 0.953 1964 0.939 1965 0.805 1966 1.021 1967 1.192 1968 1.337 1969 1.097 1970 0.665 1971 0.778 1972 0.643 1973 0.82 1974 0.704 1975 0.908 1976 0.759 1977 0.953 1978 0.955 1979 0.926 1980 0.792 1981 1.097 1982 0.814 1983 0.902 1984 0.844 1985 0.888 1986 0.979 1987 1.045 1988 0.683 1989 1.017 1990 0.642