# southamerica_arge085 - Lago Terraplen - 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.
#
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# Online_Resource:
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# Original_Source_URL:
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: southamerica_arge085 - Lago Terraplen - 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.
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# Funding_Agency
#	Funding_Agency_Name: Swiss National Science Foundation
#	Grant:
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# Site_Information
#	Site_Name: Lago Terraplen
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -43.02
#	Southernmost_Latitude: -43.02
#	Easternmost_Longitude: -71.57
#	Westernmost_Longitude: -71.57
#	Elevation: 650 m
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# Data_Collection
#	Collection_Name: southamerica_arge085B
#	Earliest_Year: 1818
#	Most_Recent_Year: 1974
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"2.50440792619"}{"T2":"11.4146074022"}{"M1":"0.0235643626227"}{"M2":"0.619086801901"}
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# Species
#	Species_Name: Chilean cedar
#	Species_Code: AUCH
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# Chronology:
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# Variables
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# 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
#
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# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1818	1.009
1819	1.051
1820	0.86
1821	0.592
1822	0.655
1823	0.852
1824	0.855
1825	1.336
1826	1.245
1827	0.763
1828	1.071
1829	0.964
1830	1.227
1831	1.138
1832	1.174
1833	1.169
1834	1.405
1835	1.352
1836	1.095
1837	1.202
1838	1.133
1839	1.037
1840	1.085
1841	0.845
1842	1.154
1843	1.273
1844	1.251
1845	0.603
1846	0.783
1847	0.676
1848	0.641
1849	0.789
1850	0.876
1851	0.779
1852	1.04
1853	1.064
1854	1.03
1855	0.915
1856	1.133
1857	1.2
1858	1.014
1859	0.856
1860	0.738
1861	0.621
1862	0.87
1863	0.596
1864	0.507
1865	0.69
1866	0.862
1867	0.938
1868	1.218
1869	1.213
1870	1.361
1871	1.006
1872	1.312
1873	1.3
1874	1.078
1875	0.845
1876	0.766
1877	0.565
1878	0.934
1879	1.211
1880	1.294
1881	1.017
1882	0.878
1883	0.932
1884	0.699
1885	0.721
1886	0.779
1887	1.072
1888	0.942
1889	1.154
1890	1.172
1891	0.982
1892	1.061
1893	0.979
1894	1.013
1895	1.006
1896	0.787
1897	0.815
1898	1.094
1899	1.123
1900	0.958
1901	0.775
1902	0.835
1903	0.999
1904	0.575
1905	0.955
1906	0.712
1907	0.961
1908	0.798
1909	0.865
1910	0.854
1911	0.598
1912	0.852
1913	0.648
1914	0.876
1915	1.037
1916	0.949
1917	0.744
1918	1.023
1919	0.98
1920	1.392
1921	1.691
1922	0.756
1923	0.874
1924	0.853
1925	1.162
1926	1.596
1927	1.147
1928	1.494
1929	1.374
1930	1.037
1931	0.893
1932	0.985
1933	1.007
1934	0.704
1935	1.098
1936	1.286
1937	0.743
1938	1.217
1939	0.954
1940	0.695
1941	0.956
1942	0.66
1943	0.384
1944	0.654
1945	0.892
1946	1.366
1947	1.043
1948	1.047
1949	1.068
1950	1.043
1951	1.133
1952	1.176
1953	0.807
1954	0.945
1955	0.99
1956	0.77
1957	0.534
1958	0.74
1959	0.789
1960	1.031
1961	1.149
1962	0.612
1963	0.982
1964	1.307
1965	1.46
1966	1.258
1967	1.219
1968	1.141
1969	0.949
1970	1.151
1971	1.308
1972	0.946
1973	0.784
1974	0.835