# asia_nepa006 - Bagarchap - 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/3760 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa006 - Bagarchap - 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: Bagarchap # Location: # Country: Nepal # Northernmost_Latitude: 28.3 # Southernmost_Latitude: 28.3 # Easternmost_Longitude: 84.18 # Westernmost_Longitude: 84.18 # Elevation: 2270 m #-------------------- # Data_Collection # Collection_Name: asia_nepa006B # Earliest_Year: 1840 # 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":"6.91270968902","T2":"19.9742925843","M1":"0.0220831725582","M2":"0.304660040739"}} #-------------------- # Species # Species_Name: cottonwood # Species_Code: PPSP #-------------------- # 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 1840 0.886 1841 0.659 1842 0.728 1843 0.94 1844 1.242 1845 1.151 1846 0.948 1847 1.009 1848 1.112 1849 1.151 1850 1.108 1851 0.834 1852 1.007 1853 1.499 1854 0.835 1855 1.021 1856 0.84 1857 0.972 1858 0.931 1859 1.042 1860 0.994 1861 0.914 1862 1.146 1863 0.865 1864 0.84 1865 1.025 1866 1.088 1867 0.959 1868 1.017 1869 1.071 1870 1.059 1871 0.768 1872 1.164 1873 1.246 1874 1.198 1875 1.254 1876 0.957 1877 1.083 1878 1.085 1879 1.084 1880 0.769 1881 1.033 1882 0.979 1883 1.059 1884 0.655 1885 0.554 1886 0.711 1887 0.757 1888 1.171 1889 0.969 1890 0.702 1891 0.457 1892 0.63 1893 0.638 1894 0.538 1895 0.599 1896 1.209 1897 1.082 1898 1.114 1899 0.503 1900 0.961 1901 1.065 1902 0.852 1903 1.229 1904 0.425 1905 0.641 1906 0.906 1907 0.488 1908 1.004 1909 0.894 1910 0.893 1911 0.604 1912 0.836 1913 1.137 1914 1.447 1915 0.985 1916 0.644 1917 0.428 1918 0.447 1919 0.615 1920 0.95 1921 1.057 1922 1.267 1923 1.428 1924 1.47 1925 1.01 1926 1.12 1927 1.233 1928 1.34 1929 1.23 1930 1.384 1931 1.759 1932 1.619 1933 0.79 1934 1.18 1935 1.178 1936 1.237 1937 1.235 1938 1.125 1939 1.079 1940 1.056 1941 0.756 1942 1.253 1943 0.751 1944 0.947 1945 0.747 1946 0.656 1947 0.862 1948 0.665 1949 0.693 1950 0.793 1951 0.786 1952 0.79 1953 1.291 1954 0.941 1955 0.878 1956 0.542 1957 1.175 1958 1.012 1959 0.865 1960 0.915 1961 1.254 1962 1.01 1963 0.747 1964 1.021 1965 0.968 1966 0.967 1967 0.78 1968 1.011 1969 1.173 1970 0.819 1971 0.488 1972 0.97 1973 1.122 1974 1.487 1975 1.096 1976 0.594 1977 0.805 1978 0.798 1979 1.317 1980 1.036 1981 0.738 1982 0.805 1983 1.11 1984 1.099 1985 1.138 1986 0.853 1987 1.106 1988 0.92 1989 0.752 1990 0.669 1991 0.782 1992 1.597 1993 1.193 1994 1.585