# asia_nepa008 - Bhratang - 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/3764 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa008 - Bhratang - 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: Bhratang # Location: # Country: Nepal # Northernmost_Latitude: 28.48 # Southernmost_Latitude: 28.48 # Easternmost_Longitude: 84.1 # Westernmost_Longitude: 84.1 # Elevation: 3095 m #-------------------- # Data_Collection # Collection_Name: asia_nepa008B # Earliest_Year: 1852 # 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":"6.95151599468","T2":"15.5560128318","M1":"0.0225335805686","M2":"0.495409653097"}} #-------------------- # Species # Species_Name: Himalayan pine # Species_Code: PIWA #-------------------- # 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 1852 0.96 1853 0.842 1854 0.887 1855 0.862 1856 0.939 1857 0.827 1858 0.823 1859 1.292 1860 1.285 1861 1.344 1862 0.936 1863 0.987 1864 0.968 1865 1.098 1866 0.973 1867 0.962 1868 0.806 1869 0.873 1870 0.849 1871 0.869 1872 0.759 1873 0.948 1874 0.861 1875 0.835 1876 0.864 1877 0.839 1878 1.046 1879 1.039 1880 0.892 1881 1.246 1882 1.461 1883 1.133 1884 1.062 1885 1.154 1886 1.174 1887 1.021 1888 1.051 1889 1.144 1890 1.197 1891 0.867 1892 0.621 1893 0.94 1894 0.821 1895 0.923 1896 0.87 1897 1.204 1898 0.959 1899 1.087 1900 0.939 1901 0.892 1902 0.984 1903 0.392 1904 0.618 1905 0.483 1906 0.72 1907 0.896 1908 0.778 1909 0.892 1910 1.001 1911 0.802 1912 0.605 1913 0.858 1914 0.858 1915 1.137 1916 1.176 1917 1.088 1918 1.044 1919 1.159 1920 1.367 1921 0.936 1922 1.148 1923 0.798 1924 1.113 1925 1.033 1926 1.045 1927 0.994 1928 1.099 1929 1.277 1930 1.185 1931 1.388 1932 1.255 1933 1.321 1934 1.186 1935 1.019 1936 1.35 1937 1.325 1938 1.093 1939 0.898 1940 0.811 1941 0.864 1942 0.932 1943 1.113 1944 1.117 1945 1.236 1946 1.127 1947 1.323 1948 0.996 1949 1.045 1950 0.756 1951 1.181 1952 0.94 1953 1.044 1954 1.001 1955 1.07 1956 1.026 1957 1.09 1958 0.974 1959 1.036 1960 1.097 1961 0.862 1962 0.725 1963 0.565 1964 0.667 1965 0.687 1966 0.601 1967 0.707 1968 0.837 1969 0.979 1970 0.875 1971 0.963 1972 0.87 1973 0.966 1974 1.003 1975 0.969 1976 1.024 1977 1.146 1978 0.884 1979 1.205 1980 1.133 1981 1.032 1982 0.999 1983 0.959 1984 0.947 1985 0.894 1986 0.935 1987 1.111 1988 1.251 1989 1.123 1990 0.75 1991 1.071 1992 0.806 1993 0.926 1994 1.069