# southamerica_arge083 - Lago Quillén - 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_arge083 - Lago Quillén - 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 Vaganovâ€“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 4â€“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 modelâ€™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 Quillén
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -39.28
#	Southernmost_Latitude: -39.28
#	Easternmost_Longitude: -71.27
#	Westernmost_Longitude: -71.27
#	Elevation: 1100 m
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# Data_Collection
#	Collection_Name: southamerica_arge083B
#	Earliest_Year: 1798
#	Most_Recent_Year: 1989
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"2.72845332898"}{"T2":"12.8254591131"}{"M1":"0.0225909843259"}{"M2":"0.586845326162"}
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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
1798	1.194
1799	0.81
1800	1.065
1801	0.843
1802	0.889
1803	1.146
1804	1.12
1805	1.201
1806	1.104
1807	0.899
1808	1.439
1809	1.476
1810	1.433
1811	1.771
1812	1.993
1813	0.93
1814	1.107
1815	1.101
1816	1.255
1817	1.172
1818	0.897
1819	0.872
1820	1.088
1821	1.269
1822	1.609
1823	1.551
1824	1.822
1825	1.43
1826	0.921
1827	0.728
1828	0.755
1829	0.803
1830	0.527
1831	0.61
1832	0.672
1833	0.676
1834	0.734
1835	0.877
1836	0.65
1837	0.862
1838	0.953
1839	0.573
1840	0.624
1841	0.44
1842	0.667
1843	0.705
1844	0.848
1845	0.589
1846	0.794
1847	0.91
1848	1.023
1849	1.396
1850	1.276
1851	0.843
1852	0.837
1853	0.718
1854	0.789
1855	0.968
1856	1.003
1857	1.164
1858	1.027
1859	0.405
1860	0.423
1861	0.394
1862	0.363
1863	0.572
1864	0.631
1865	0.784
1866	0.977
1867	1.047
1868	1.281
1869	1.254
1870	1.13
1871	1.031
1872	1.07
1873	0.957
1874	0.856
1875	0.599
1876	0.698
1877	0.718
1878	1.137
1879	1.35
1880	1.193
1881	0.994
1882	0.869
1883	0.764
1884	1.055
1885	1.039
1886	1.292
1887	1.086
1888	1.699
1889	1.521
1890	1.176
1891	1.47
1892	1.69
1893	0.523
1894	0.552
1895	0.824
1896	0.743
1897	0.825
1898	1.324
1899	1.383
1900	0.828
1901	0.791
1902	0.755
1903	0.949
1904	0.881
1905	0.876
1906	0.793
1907	1.001
1908	1.087
1909	1.082
1910	0.979
1911	1.008
1912	1.062
1913	0.784
1914	0.699
1915	0.975
1916	0.954
1917	0.683
1918	0.819
1919	0.721
1920	1.073
1921	1.363
1922	0.972
1923	0.83
1924	0.886
1925	1.236
1926	1.446
1927	1.115
1928	1.189
1929	1.52
1930	1.236
1931	0.922
1932	1.214
1933	1.569
1934	1.397
1935	1.298
1936	1.228
1937	1.32
1938	1.3
1939	1.289
1940	1.439
1941	1.322
1942	1.353
1943	0.737
1944	0.689
1945	1.2
1946	1.674
1947	1.032
1948	0.99
1949	1.029
1950	1.06
1951	1.228
1952	0.891
1953	0.688
1954	0.687
1955	0.971
1956	0.899
1957	0.396
1958	0.47
1959	0.532
1960	0.9
1961	1.148
1962	0.754
1963	0.926
1964	1.218
1965	1.143
1966	1.132
1967	1.03
1968	1.111
1969	0.966
1970	1.189
1971	1.265
1972	0.943
1973	0.871
1974	1.087
1975	1.055
1976	1.176
1977	1.223
1978	0.856
1979	0.648
1980	1.13
1981	0.957
1982	0.736
1983	0.465
1984	0.709
1985	0.837
1986	0.696
1987	0.655
1988	0.855
1989	1.011