# southamerica_arge058 - Rio Bolsas Piedra Parada Jujuy - 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
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# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: southamerica_arge058 - Rio Bolsas Piedra Parada Jujuy - 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 Bolsas Piedra Parada Jujuy
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -23.92
#	Southernmost_Latitude: -23.92
#	Easternmost_Longitude: -65.32
#	Westernmost_Longitude: -65.32
#	Elevation: 1850 m
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# Data_Collection
#	Collection_Name: southamerica_arge058B
#	Earliest_Year: 1810
#	Most_Recent_Year: 1978
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"4.60168622121"}{"T2":"12.1287319819"}{"M1":"0.0226901614412"}{"M2":"0.624781366426"}
#--------------------
# Species
#	Species_Name: Argentine walnut
#	Species_Code: JGAU
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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
1810	0.783
1811	1.338
1812	1.434
1813	0.894
1814	0.862
1815	0.365
1816	0.488
1817	0.978
1818	0.577
1819	0.577
1820	1.125
1821	0.928
1822	0.84
1823	1.283
1824	1.171
1825	0.702
1826	0.709
1827	1.1
1828	1.036
1829	1.051
1830	0.958
1831	1.228
1832	0.652
1833	0.607
1834	1.103
1835	1.506
1836	0.988
1837	1.094
1838	0.796
1839	0.692
1840	0.56
1841	0.959
1842	0.95
1843	1.102
1844	0.681
1845	0.315
1846	1.017
1847	1.187
1848	1.297
1849	1.274
1850	0.768
1851	1.336
1852	0.715
1853	1.259
1854	0.916
1855	0.5
1856	1.429
1857	0.855
1858	0.872
1859	1.164
1860	0.327
1861	0.572
1862	1.085
1863	1.479
1864	0.859
1865	1.4
1866	1.574
1867	0.651
1868	0.568
1869	0.64
1870	0.891
1871	0.652
1872	0.531
1873	0.356
1874	0.422
1875	0.351
1876	0.802
1877	0.791
1878	0.589
1879	0.479
1880	0.995
1881	1.301
1882	1.07
1883	1.061
1884	0.806
1885	1.085
1886	1.199
1887	0.74
1888	1.104
1889	1.012
1890	0.951
1891	1.875
1892	2.172
1893	1.173
1894	0.819
1895	1.49
1896	1.039
1897	0.602
1898	1.185
1899	1.646
1900	1.798
1901	0.93
1902	1.114
1903	0.389
1904	1.19
1905	1.136
1906	1.014
1907	0.53
1908	0.809
1909	1.318
1910	0.806
1911	0.772
1912	0.804
1913	0.734
1914	0.748
1915	1.393
1916	1.115
1917	0.685
1918	1.2
1919	0.689
1920	0.278
1921	0.645
1922	0.851
1923	0.95
1924	1.334
1925	1.065
1926	1.495
1927	1.163
1928	1.053
1929	1.183
1930	0.676
1931	0.489
1932	0.927
1933	1.017
1934	0.503
1935	0.542
1936	0.787
1937	0.932
1938	0.946
1939	0.735
1940	1.283
1941	1.55
1942	0.702
1943	1.607
1944	1.6
1945	1.653
1946	0.794
1947	1.485
1948	0.94
1949	1.071
1950	1.37
1951	0.958
1952	1.159
1953	0.808
1954	0.971
1955	0.634
1956	0.843
1957	0.859
1958	0.872
1959	0.799
1960	1.003
1961	0.963
1962	1.218
1963	1.062
1964	0.685
1965	0.701
1966	0.987
1967	1.174
1968	0.728
1969	1.077
1970	1.148
1971	0.982
1972	1.43
1973	1.204
1974	1.107
1975	0.591
1976	1.217
1977	0.647
1978	0.599