# asia_russ175w - Nirukda, P.Tung. - 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/4554 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_russ175w - Nirukda, P.Tung. - 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: Nirukda, P.Tung. # Location: # Country: Russia # Northernmost_Latitude: 61.93 # Southernmost_Latitude: 61.93 # Easternmost_Longitude: 95.15 # Westernmost_Longitude: 95.15 # Elevation: 160 m #-------------------- # Data_Collection # Collection_Name: asia_russ175wB # Earliest_Year: 1849 # Most_Recent_Year: 1994 # 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":"3.61927319945","T2":"17.1612996646","M1":"0.0224411976239","M2":"0.403420511831"}} #-------------------- # Species # Species_Name: Siberian spruce # Species_Code: PCOB #-------------------- # 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 1849 1.355 1850 1.296 1851 0.927 1852 0.901 1853 1.195 1854 0.76 1855 1.055 1856 1.145 1857 1.186 1858 1.285 1859 1.238 1860 1.363 1861 1.323 1862 1.145 1863 1.325 1864 1.091 1865 1.226 1866 1.023 1867 0.801 1868 0.946 1869 0.885 1870 0.87 1871 0.911 1872 0.929 1873 0.668 1874 0.905 1875 0.998 1876 1.045 1877 1.087 1878 1.372 1879 0.934 1880 1.052 1881 0.952 1882 1.024 1883 0.809 1884 0.97 1885 0.945 1886 0.774 1887 0.681 1888 0.669 1889 0.787 1890 0.737 1891 0.902 1892 0.919 1893 0.886 1894 0.872 1895 0.707 1896 0.517 1897 0.679 1898 0.798 1899 0.794 1900 0.894 1901 0.773 1902 0.624 1903 0.963 1904 0.837 1905 0.833 1906 0.814 1907 0.519 1908 1.072 1909 1.005 1910 1.112 1911 1.209 1912 1.046 1913 0.982 1914 0.909 1915 0.974 1916 0.829 1917 0.874 1918 0.865 1919 0.861 1920 0.895 1921 0.794 1922 0.886 1923 0.878 1924 0.935 1925 0.979 1926 1.134 1927 1.038 1928 1.067 1929 0.772 1930 1.049 1931 1.013 1932 0.928 1933 0.898 1934 0.829 1935 0.923 1936 0.835 1937 1.049 1938 0.9 1939 1.088 1940 1.061 1941 1.115 1942 1.251 1943 1.16 1944 1.339 1945 1.617 1946 1.421 1947 1.401 1948 1.399 1949 1.05 1950 1.348 1951 1.144 1952 1.276 1953 1.397 1954 1.192 1955 1.15 1956 1.082 1957 1.085 1958 0.766 1959 0.769 1960 0.922 1961 0.899 1962 1.139 1963 0.929 1964 1.005 1965 0.794 1966 0.919 1967 1.132 1968 1.096 1969 1.214 1970 1.009 1971 1.028 1972 1.03 1973 0.944 1974 0.815 1975 1.079 1976 0.929 1977 0.959 1978 0.879 1979 0.941 1980 0.652 1981 0.718 1982 0.766 1983 0.81 1984 0.915 1985 0.828 1986 0.968 1987 0.684 1988 0.662 1989 0.692 1990 0.841 1991 0.879 1992 0.935 1993 0.846 1994 0.963