# southamerica_arge052 - Peninsula Brunswick - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
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# 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
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# Title
#	Study_Name: southamerica_arge052 - Peninsula Brunswick - 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: Peninsula Brunswick
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -53.5
#	Southernmost_Latitude: -53.5
#	Easternmost_Longitude: -71.17
#	Westernmost_Longitude: -71.17
#	Elevation: 100 m
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# Data_Collection
#	Collection_Name: southamerica_arge052B
#	Earliest_Year: 1796
#	Most_Recent_Year: 1988
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"4.52712521788"}{"T2":"16.5517461101"}{"M1":"0.0226440027203"}{"M2":"0.44321359897"}
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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
1796	0.981
1797	0.753
1798	0.909
1799	1.303
1800	1.508
1801	1.311
1802	1.318
1803	1.117
1804	0.354
1805	0.257
1806	1.246
1807	1.475
1808	1.461
1809	1.429
1810	1.229
1811	0.37
1812	0.457
1813	1.131
1814	1.54
1815	1.265
1816	1.181
1817	1.48
1818	0.712
1819	0.259
1820	0.837
1821	1.26
1822	1.376
1823	1.136
1824	0.972
1825	1.449
1826	1.376
1827	0.601
1828	1.278
1829	1.838
1830	1.567
1831	1.152
1832	1.287
1833	0.5
1834	0.51
1835	1.131
1836	1.256
1837	1.357
1838	1.324
1839	0.966
1840	0.85
1841	1.139
1842	1.316
1843	1.351
1844	1.316
1845	0.703
1846	0.674
1847	1.004
1848	1.334
1849	0.782
1850	0.443
1851	0.631
1852	0.824
1853	0.894
1854	0.837
1855	0.941
1856	0.77
1857	0.904
1858	0.974
1859	0.761
1860	0.614
1861	0.697
1862	1.082
1863	1.52
1864	1.28
1865	1.19
1866	0.8
1867	0.34
1868	0.803
1869	1.369
1870	1.155
1871	1.111
1872	0.612
1873	0.6
1874	0.595
1875	0.489
1876	1.229
1877	0.954
1878	0.937
1879	0.573
1880	0.813
1881	1.336
1882	0.86
1883	0.699
1884	1.042
1885	1.475
1886	1.291
1887	0.855
1888	0.484
1889	0.434
1890	1.12
1891	1.114
1892	0.986
1893	1.089
1894	1.314
1895	1.299
1896	1.175
1897	1.429
1898	1.785
1899	1.252
1900	1.421
1901	1.548
1902	1.329
1903	1.41
1904	1.709
1905	1.421
1906	1.215
1907	1.339
1908	0.754
1909	0.711
1910	0.895
1911	1.174
1912	0.874
1913	0.944
1914	0.902
1915	0.885
1916	1.05
1917	1.128
1918	0.983
1919	0.494
1920	0.672
1921	1.234
1922	1.237
1923	1.004
1924	0.586
1925	0.32
1926	0.71
1927	1.062
1928	1.012
1929	0.903
1930	0.711
1931	0.687
1932	0.886
1933	0.658
1934	0.742
1935	0.951
1936	0.717
1937	0.823
1938	0.767
1939	1.04
1940	0.739
1941	0.623
1942	1.044
1943	0.749
1944	1.208
1945	0.938
1946	0.939
1947	1.024
1948	0.929
1949	0.739
1950	0.748
1951	1.023
1952	1.007
1953	1.305
1954	1.352
1955	1.054
1956	0.81
1957	1.198
1958	0.793
1959	0.953
1960	1.196
1961	1.17
1962	1.335
1963	0.999
1964	0.461
1965	0.657
1966	1.152
1967	1.112
1968	0.941
1969	0.799
1970	0.453
1971	0.859
1972	1.055
1973	0.773
1974	1.108
1975	1.038
1976	1.642
1977	1.351
1978	0.757
1979	0.941
1980	1.117
1981	0.952
1982	0.818
1983	0.776
1984	0.871
1985	0.802
1986	0.938
1987	0.818
1988	0.748