# europe_gree002 - Langada (Sparta) - 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/4500 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_gree002 - Langada (Sparta) - 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: Langada (Sparta) # Location: # Country: Greece # Northernmost_Latitude: 37.08 # Southernmost_Latitude: 37.08 # Easternmost_Longitude: 22.33 # Westernmost_Longitude: 22.33 # Elevation: 1450 m #-------------------- # Data_Collection # Collection_Name: europe_gree002B # Earliest_Year: 1860 # Most_Recent_Year: 1981 # 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":"5.1625761531","T2":"11.1567043728","M1":"0.0221081874785","M2":"0.143970427772"}} #-------------------- # Species # Species_Name: Austrian pine # Species_Code: PINI #-------------------- # 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 1.46 1861 0.271 1862 0.541 1863 0.713 1864 0.879 1865 0.992 1866 1.068 1867 1.4 1868 1.625 1869 1.142 1870 0.379 1871 0.44 1872 0.865 1873 1.093 1874 1.133 1875 0.964 1876 1.187 1877 1.364 1878 1.167 1879 0.808 1880 0.508 1881 0.758 1882 0.968 1883 0.916 1884 1.133 1885 1.812 1886 1.343 1887 0.678 1888 0.852 1889 1.166 1890 1.204 1891 1.282 1892 1.754 1893 0.257 1894 0.336 1895 0.566 1896 0.84 1897 1.465 1898 1.413 1899 1.781 1900 1.527 1901 0.471 1902 0.696 1903 0.793 1904 0.806 1905 0.853 1906 0.999 1907 0.925 1908 0.457 1909 0.633 1910 0.845 1911 1.262 1912 1.339 1913 2.038 1914 1.77 1915 1.767 1916 0.772 1917 0.399 1918 0.403 1919 0.878 1920 0.972 1921 0.762 1922 1.012 1923 0.703 1924 0.908 1925 0.919 1926 1.504 1927 0.993 1928 0.78 1929 0.769 1930 1.12 1931 0.905 1932 0.961 1933 1.117 1934 1.004 1935 0.823 1936 1.382 1937 1.211 1938 0.87 1939 0.959 1940 0.832 1941 0.967 1942 1.031 1943 0.715 1944 0.276 1945 0.276 1946 0.66 1947 0.734 1948 0.42 1949 0.33 1950 0.792 1951 1.222 1952 0.939 1953 1.095 1954 1.126 1955 1.319 1956 1.24 1957 0.843 1958 0.978 1959 0.982 1960 1.379 1961 1.193 1962 1.227 1963 1.224 1964 1.075 1965 0.761 1966 0.791 1967 0.941 1968 0.898 1969 0.756 1970 0.685 1971 0.809 1972 1.236 1973 0.805 1974 0.953 1975 1.355 1976 1.086 1977 0.885 1978 0.864 1979 1.423 1980 0.973 1981 0.94