# southamerica_arge055 - Rio Claro - 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_arge055 - Rio Claro - 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: Rio Claro
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -54.5
#	Southernmost_Latitude: -54.5
#	Easternmost_Longitude: -67.8
#	Westernmost_Longitude: -67.8
#	Elevation: 150 m
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# Data_Collection
#	Collection_Name: southamerica_arge055B
#	Earliest_Year: 1800
#	Most_Recent_Year: 1986
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"5.17225076948"}{"T2":"16.9515397857"}{"M1":"0.023093588994"}{"M2":"0.388280843312"}
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# Species
#	Species_Name: lenga nothofagus
#	Species_Code: NOPU
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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)
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##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
1800	0.95
1801	0.8
1802	0.842
1803	1.074
1804	0.711
1805	0.551
1806	0.809
1807	0.994
1808	1.148
1809	1.241
1810	1.104
1811	0.982
1812	1.253
1813	0.503
1814	0.849
1815	1.218
1816	0.976
1817	0.966
1818	1.045
1819	1.009
1820	0.399
1821	0.211
1822	0.776
1823	1.197
1824	0.577
1825	1.031
1826	1.083
1827	1.035
1828	0.437
1829	0.95
1830	1.123
1831	1.199
1832	1.336
1833	1.1
1834	1.172
1835	1.045
1836	1.29
1837	1.244
1838	0.918
1839	0.833
1840	1.087
1841	0.926
1842	0.947
1843	0.997
1844	1.256
1845	1.081
1846	1.144
1847	1.12
1848	1.559
1849	1.281
1850	1.36
1851	1.193
1852	0.966
1853	1.14
1854	1.005
1855	1.312
1856	0.992
1857	0.973
1858	1.241
1859	0.968
1860	0.954
1861	1.217
1862	0.979
1863	1.39
1864	1.226
1865	1.248
1866	0.88
1867	0.842
1868	0.692
1869	1.189
1870	1.59
1871	1.433
1872	1.256
1873	0.75
1874	1.206
1875	0.7
1876	0.977
1877	1.401
1878	1.068
1879	0.771
1880	1.122
1881	0.902
1882	0.364
1883	0.461
1884	1.335
1885	1.569
1886	1.227
1887	0.985
1888	0.78
1889	0.61
1890	0.352
1891	0.951
1892	1.329
1893	1.0
1894	1.278
1895	1.223
1896	0.529
1897	0.487
1898	1.298
1899	1.26
1900	0.97
1901	0.698
1902	0.885
1903	0.51
1904	0.842
1905	1.188
1906	0.962
1907	0.805
1908	0.858
1909	0.883
1910	1.056
1911	1.033
1912	1.162
1913	1.066
1914	0.795
1915	1.093
1916	1.003
1917	1.038
1918	1.081
1919	0.936
1920	0.888
1921	0.782
1922	1.182
1923	0.382
1924	0.422
1925	0.964
1926	0.693
1927	0.726
1928	0.895
1929	1.018
1930	0.826
1931	0.231
1932	0.108
1933	1.068
1934	0.808
1935	0.592
1936	0.68
1937	0.4
1938	0.96
1939	1.112
1940	0.813
1941	0.951
1942	1.38
1943	0.834
1944	0.435
1945	0.986
1946	0.914
1947	0.573
1948	0.809
1949	0.562
1950	0.393
1951	0.719
1952	1.225
1953	1.088
1954	1.039
1955	1.168
1956	1.192
1957	1.061
1958	0.882
1959	1.235
1960	1.021
1961	1.051
1962	1.181
1963	1.34
1964	1.354
1965	1.243
1966	1.344
1967	1.291
1968	0.85
1969	1.045
1970	0.941
1971	1.141
1972	1.481
1973	1.252
1974	1.553
1975	1.265
1976	1.058
1977	0.999
1978	0.927
1979	0.838
1980	1.197
1981	1.087
1982	0.961
1983	1.089
1984	0.857
1985	0.846
1986	1.154