# europe_swit141w - Roggwil BE Tanne absterb - 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/4617 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit141w - Roggwil BE Tanne absterb - 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: Roggwil BE Tanne absterb # Location: # Country: Switzerland # Northernmost_Latitude: 47.25 # Southernmost_Latitude: 47.25 # Easternmost_Longitude: 7.83 # Westernmost_Longitude: 7.83 # Elevation: 535 m #-------------------- # Data_Collection # Collection_Name: europe_swit141wB # Earliest_Year: 1875 # Most_Recent_Year: 1975 # 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":"4.15134202032","T2":"19.1091724636","M1":"0.0226377022112","M2":"0.398733343782"}} #-------------------- # Species # Species_Name: silver fir # Species_Code: ABAL #-------------------- # 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 1875 1.111 1876 1.068 1877 1.181 1878 1.195 1879 1.062 1880 0.896 1881 1.025 1882 0.856 1883 0.933 1884 0.865 1885 0.723 1886 0.626 1887 0.57 1888 0.7 1889 0.83 1890 0.825 1891 0.775 1892 0.678 1893 0.576 1894 0.791 1895 0.657 1896 0.783 1897 0.889 1898 0.949 1899 0.775 1900 0.977 1901 0.907 1902 0.965 1903 1.093 1904 0.974 1905 0.967 1906 1.08 1907 0.919 1908 0.928 1909 0.807 1910 1.173 1911 0.974 1912 1.114 1913 1.36 1914 1.328 1915 1.304 1916 1.376 1917 1.133 1918 1.061 1919 1.173 1920 1.071 1921 0.987 1922 0.785 1923 0.959 1924 0.941 1925 1.255 1926 1.383 1927 1.364 1928 1.286 1929 1.085 1930 1.309 1931 1.359 1932 1.741 1933 1.352 1934 1.152 1935 1.228 1936 1.447 1937 1.361 1938 1.288 1939 1.267 1940 1.22 1941 1.208 1942 1.078 1943 1.28 1944 1.017 1945 1.235 1946 1.23 1947 0.953 1948 0.792 1949 1.025 1950 1.578 1951 1.495 1952 1.306 1953 1.269 1954 1.054 1955 1.213 1956 0.672 1957 0.689 1958 0.383 1959 0.555 1960 0.533 1961 0.865 1962 0.586 1963 0.629 1964 0.615 1965 0.505 1966 0.561 1967 0.4 1968 0.308 1969 0.353 1970 0.295 1971 0.235 1972 0.359 1973 0.312 1974 0.174 1975 0.303