# europe_turk032 - Bayat Bademleri - 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/5125 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_turk032 - Bayat Bademleri - 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: Bayat Bademleri # Location: # Country: Turkey # Northernmost_Latitude: 37.03 # Southernmost_Latitude: 37.03 # Easternmost_Longitude: 30.47 # Westernmost_Longitude: 30.47 # Elevation: 700 m #-------------------- # Data_Collection # Collection_Name: europe_turk032B # Earliest_Year: 1869 # Most_Recent_Year: 2000 # 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":"3.92517883384","T2":"15.3659953195","M1":"0.0227653955501","M2":"0.415416137804"}} #-------------------- # Species # Species_Name: Calabrian pine # Species_Code: PIBR #-------------------- # 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 1869 0.847 1870 0.895 1871 1.056 1872 1.303 1873 1.457 1874 0.761 1875 0.717 1876 0.959 1877 0.913 1878 1.06 1879 0.699 1880 0.776 1881 0.988 1882 1.017 1883 1.331 1884 1.232 1885 1.2 1886 1.032 1887 0.699 1888 0.9 1889 1.189 1890 0.852 1891 0.984 1892 1.07 1893 0.874 1894 0.79 1895 0.949 1896 1.011 1897 1.126 1898 0.782 1899 0.895 1900 1.149 1901 1.216 1902 1.134 1903 1.152 1904 1.284 1905 1.295 1906 0.985 1907 0.802 1908 0.63 1909 0.76 1910 0.978 1911 0.885 1912 0.843 1913 1.244 1914 1.298 1915 1.587 1916 0.764 1917 1.15 1918 1.095 1919 1.177 1920 0.982 1921 1.007 1922 1.034 1923 1.193 1924 1.015 1925 1.18 1926 0.865 1927 0.906 1928 0.706 1929 0.801 1930 1.053 1931 1.037 1932 0.714 1933 1.093 1934 0.799 1935 0.725 1936 1.316 1937 0.972 1938 0.914 1939 1.133 1940 1.389 1941 0.88 1942 1.075 1943 1.289 1944 1.004 1945 0.861 1946 0.992 1947 0.757 1948 1.082 1949 0.748 1950 1.101 1951 1.301 1952 1.155 1953 0.905 1954 1.144 1955 0.898 1956 0.639 1957 0.907 1958 0.898 1959 0.78 1960 1.029 1961 0.746 1962 1.231 1963 1.079 1964 0.864 1965 0.923 1966 1.369 1967 0.889 1968 1.119 1969 0.942 1970 0.837 1971 0.85 1972 1.338 1973 0.706 1974 0.762 1975 0.939 1976 1.068 1977 1.067 1978 1.038 1979 1.127 1980 1.181 1981 1.065 1982 1.491 1983 1.094 1984 1.292 1985 0.919 1986 1.051 1987 0.847 1988 1.08 1989 0.695 1990 0.292 1991 0.638 1992 0.764 1993 0.977 1994 0.989 1995 1.231 1996 0.901 1997 1.282 1998 1.241 1999 0.818 2000 0.435