# europe_pola012 - Poznan - 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/5220 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_pola012 - Poznan - 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: Poznan # Location: # Country: Poland # Northernmost_Latitude: 52.27 # Southernmost_Latitude: 52.27 # Easternmost_Longitude: 16.8 # Westernmost_Longitude: 16.8 # Elevation: 70 m #-------------------- # Data_Collection # Collection_Name: europe_pola012B # Earliest_Year: 1848 # Most_Recent_Year: 1986 # 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":"4.7505379581","T2":"16.9564202307","M1":"0.0230801687221","M2":"0.448982314288"}} #-------------------- # 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 1848 0.589 1849 1.285 1850 1.337 1851 1.201 1852 0.88 1853 1.43 1854 1.486 1855 1.194 1856 0.858 1857 0.993 1858 0.894 1859 0.991 1860 1.007 1861 1.317 1862 1.456 1863 1.23 1864 0.832 1865 0.939 1866 0.731 1867 1.191 1868 0.848 1869 1.251 1870 1.155 1871 0.988 1872 1.013 1873 0.739 1874 0.811 1875 0.925 1876 0.581 1877 0.856 1878 1.033 1879 0.924 1880 0.84 1881 0.85 1882 0.828 1883 0.777 1884 0.601 1885 0.756 1886 0.802 1887 0.752 1888 0.74 1889 0.802 1890 0.942 1891 0.962 1892 0.854 1893 0.785 1894 0.946 1895 0.786 1896 0.836 1897 0.861 1898 0.897 1899 0.734 1900 0.664 1901 0.761 1902 1.133 1903 1.227 1904 1.103 1905 0.95 1906 1.108 1907 1.087 1908 1.134 1909 1.112 1910 1.046 1911 0.992 1912 0.899 1913 1.062 1914 0.77 1915 0.926 1916 1.127 1917 0.902 1918 0.98 1919 1.048 1920 1.037 1921 0.904 1922 0.949 1923 1.049 1924 1.22 1925 1.05 1926 1.079 1927 1.286 1928 1.135 1929 1.123 1930 1.035 1931 1.218 1932 1.183 1933 0.858 1934 0.802 1935 1.025 1936 1.017 1937 1.033 1938 1.245 1939 1.128 1940 0.733 1941 0.911 1942 0.927 1943 0.883 1944 0.856 1945 0.983 1946 1.033 1947 1.016 1948 1.186 1949 1.369 1950 1.073 1951 1.142 1952 0.84 1953 0.757 1954 0.927 1955 0.915 1956 0.864 1957 0.929 1958 0.863 1959 0.687 1960 0.655 1961 0.788 1962 0.964 1963 0.929 1964 0.964 1965 1.125 1966 1.108 1967 1.303 1968 1.198 1969 0.887 1970 0.774 1971 0.876 1972 0.938 1973 1.154 1974 1.148 1975 1.034 1976 0.947 1977 0.991 1978 0.786 1979 1.031 1980 0.996 1981 1.376 1982 1.215 1983 0.977 1984 1.358 1985 1.037 1986 1.092