# europe_turk026 - Gazipasa Forest - 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/4201 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_turk026 - Gazipasa Forest - 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: Gazipasa Forest # Location: # Country: Turkey # Northernmost_Latitude: 36.45 # Southernmost_Latitude: 36.45 # Easternmost_Longitude: 32.52 # Westernmost_Longitude: 32.52 # Elevation: 1580 m #-------------------- # Data_Collection # Collection_Name: europe_turk026B # Earliest_Year: 1795 # Most_Recent_Year: 1983 # 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":"3.76800629132","T2":"13.3199957187","M1":"0.0222093721782","M2":"0.229517465392"}} #-------------------- # Species # Species_Name: juniper # Species_Code: JUSP #-------------------- # 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 1795 0.934 1796 0.806 1797 0.827 1798 1.269 1799 0.867 1800 1.18 1801 1.228 1802 1.078 1803 1.145 1804 1.219 1805 1.373 1806 1.241 1807 1.405 1808 1.125 1809 1.347 1810 1.543 1811 0.98 1812 1.16 1813 0.858 1814 1.112 1815 0.838 1816 1.118 1817 0.826 1818 1.249 1819 0.875 1820 0.829 1821 1.046 1822 0.722 1823 0.925 1824 1.081 1825 0.876 1826 1.153 1827 1.285 1828 1.121 1829 1.043 1830 1.034 1831 1.014 1832 1.317 1833 1.05 1834 1.099 1835 1.192 1836 1.054 1837 1.006 1838 0.846 1839 0.925 1840 0.873 1841 1.074 1842 1.226 1843 1.032 1844 0.838 1845 0.901 1846 1.196 1847 1.086 1848 1.05 1849 1.024 1850 0.881 1851 0.865 1852 0.921 1853 0.905 1854 0.77 1855 1.089 1856 0.911 1857 0.992 1858 0.748 1859 0.806 1860 0.828 1861 0.982 1862 0.765 1863 0.697 1864 0.924 1865 1.024 1866 1.114 1867 0.726 1868 0.526 1869 0.612 1870 0.724 1871 0.853 1872 0.967 1873 1.008 1874 0.966 1875 0.871 1876 0.997 1877 1.323 1878 0.987 1879 1.074 1880 0.793 1881 1.277 1882 1.157 1883 1.087 1884 0.918 1885 0.843 1886 0.889 1887 0.764 1888 1.135 1889 1.023 1890 0.927 1891 0.936 1892 0.972 1893 0.813 1894 0.833 1895 1.004 1896 0.864 1897 1.146 1898 1.071 1899 1.322 1900 1.097 1901 1.243 1902 0.985 1903 1.118 1904 0.938 1905 0.862 1906 0.955 1907 0.801 1908 0.724 1909 0.657 1910 0.656 1911 0.669 1912 0.903 1913 1.108 1914 1.181 1915 0.923 1916 1.031 1917 1.11 1918 1.004 1919 1.18 1920 1.122 1921 0.872 1922 1.112 1923 0.895 1924 1.09 1925 1.039 1926 0.842 1927 0.621 1928 0.574 1929 0.754 1930 1.179 1931 1.266 1932 1.013 1933 0.993 1934 1.09 1935 0.655 1936 1.169 1937 1.135 1938 0.781 1939 0.879 1940 1.149 1941 1.121 1942 0.827 1943 0.914 1944 0.9 1945 0.487 1946 0.496 1947 0.999 1948 0.49 1949 0.665 1950 1.061 1951 1.146 1952 0.943 1953 0.656 1954 0.639 1955 0.635 1956 0.656 1957 0.874 1958 0.945 1959 1.062 1960 1.4 1961 1.235 1962 1.216 1963 1.355 1964 1.255 1965 1.179 1966 1.295 1967 1.166 1968 0.954 1969 0.822 1970 1.278 1971 0.912 1972 1.303 1973 1.315 1974 1.374 1975 1.539 1976 1.302 1977 1.482 1978 1.006 1979 1.278 1980 0.892 1981 0.96 1982 1.198 1983 1.041