# southamerica_arge009 - Estancia Teresa - Breitenmoser Tree Ring Chronology Data
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#		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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# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
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# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/3523
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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_arge009 - Estancia Teresa - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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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#	Authors: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G.J., Noone, D., Perkins, W.A., and E. Steig
#	Published_Date_or_Year: 2018
#	Published_Title: Additions to the last millennium reanalysis multi-proxy database
#	Journal_Name: Data Science Journal
#	Volume:
#	Edition:
#	Issue:
#	Pages:
#	Report_Number:
#	DOI:
#	Online_Resource:
#	Full_Citation: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G., J., Noone, D., Perkins, W.A., and E. Steig, submitted. Additions to the last millennium reanalysis multi-proxy database. Data Science Journal.
#	Abstract: Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR).  The 2290 additional series include 2152 tree ring chronologies and 138 other series.  They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation.  A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project.  The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables.  Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods.
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# Funding_Agency
#	Funding_Agency_Name: Swiss National Science Foundation
#	Grant:
#--------------------
#	Funding_Agency_Name: National Science Foundation
#	Grant:AGS-1304263
#	Funding_Agency_Name: National Oceanic and Atmospheric Administration
#	Grant:NA14OAR4310176
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# Site_Information
#	Site_Name: Estancia Teresa
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -42.95
#	Southernmost_Latitude: -42.95
#	Easternmost_Longitude: -71.43
#	Westernmost_Longitude: -71.43
#	Elevation: 820 m
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# Data_Collection
#	Collection_Name: southamerica_arge009B
#	Earliest_Year: 1735
#	Most_Recent_Year: 1974
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"3.18253220882","T2":"13.0805837892","M1":"0.0236761871665","M2":"0.564325799304"}}
#--------------------
# Species
#	Species_Name: Chilean cedar
#	Species_Code: AUCH
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# Chronology:
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# Variables
#
# 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
1735	1.089
1736	0.988
1737	0.845
1738	0.817
1739	0.861
1740	0.831
1741	1.067
1742	1.208
1743	1.147
1744	1.072
1745	0.757
1746	0.827
1747	0.741
1748	0.528
1749	1.02
1750	1.098
1751	0.891
1752	0.776
1753	0.999
1754	0.973
1755	0.288
1756	0.585
1757	1.006
1758	0.964
1759	0.916
1760	1.136
1761	1.211
1762	0.825
1763	1.077
1764	0.896
1765	0.746
1766	1.182
1767	1.066
1768	1.173
1769	1.197
1770	0.969
1771	1.376
1772	1.21
1773	1.491
1774	1.912
1775	1.743
1776	1.58
1777	1.357
1778	1.191
1779	0.829
1780	0.889
1781	1.094
1782	0.846
1783	0.706
1784	0.638
1785	0.882
1786	0.755
1787	0.882
1788	1.128
1789	1.147
1790	1.157
1791	0.816
1792	0.97
1793	1.029
1794	1.052
1795	1.093
1796	1.253
1797	1.799
1798	1.244
1799	1.336
1800	1.422
1801	0.738
1802	0.829
1803	0.999
1804	0.924
1805	0.964
1806	1.091
1807	0.889
1808	1.362
1809	1.151
1810	0.846
1811	0.994
1812	1.042
1813	0.651
1814	0.948
1815	0.627
1816	0.882
1817	0.774
1818	0.853
1819	0.748
1820	0.446
1821	0.26
1822	0.505
1823	0.856
1824	1.205
1825	0.85
1826	0.858
1827	0.429
1828	0.407
1829	0.664
1830	0.864
1831	0.781
1832	0.741
1833	0.831
1834	1.055
1835	1.104
1836	0.949
1837	1.107
1838	1.385
1839	1.206
1840	1.052
1841	0.957
1842	1.04
1843	1.316
1844	1.385
1845	0.902
1846	0.993
1847	0.886
1848	0.878
1849	0.96
1850	1.183
1851	0.796
1852	0.99
1853	0.991
1854	1.05
1855	0.834
1856	1.008
1857	1.281
1858	1.28
1859	1.412
1860	1.455
1861	1.139
1862	1.528
1863	1.365
1864	1.209
1865	0.961
1866	1.143
1867	1.092
1868	1.591
1869	1.499
1870	1.381
1871	1.104
1872	1.523
1873	1.405
1874	1.503
1875	1.26
1876	1.422
1877	1.038
1878	1.547
1879	1.551
1880	1.599
1881	1.188
1882	1.37
1883	1.196
1884	1.166
1885	0.881
1886	1.026
1887	1.051
1888	1.307
1889	1.657
1890	1.49
1891	1.164
1892	1.752
1893	1.22
1894	1.161
1895	1.209
1896	1.18
1897	0.649
1898	0.958
1899	1.136
1900	1.219
1901	0.913
1902	0.851
1903	0.927
1904	0.948
1905	1.435
1906	0.937
1907	0.767
1908	0.425
1909	0.246
1910	0.556
1911	0.461
1912	0.49
1913	0.546
1914	0.711
1915	1.114
1916	0.841
1917	0.448
1918	0.801
1919	0.521
1920	0.83
1921	0.928
1922	0.749
1923	0.66
1924	0.79
1925	0.998
1926	1.163
1927	1.123
1928	1.383
1929	1.24
1930	1.104
1931	0.453
1932	0.393
1933	0.692
1934	0.547
1935	0.957
1936	0.908
1937	0.812
1938	0.777
1939	0.335
1940	0.732
1941	1.116
1942	0.885
1943	0.357
1944	0.077
1945	0.499
1946	0.645
1947	0.297
1948	0.44
1949	0.41
1950	0.456
1951	0.799
1952	0.854
1953	0.857
1954	0.832
1955	0.873
1956	0.681
1957	0.359
1958	0.457
1959	0.599
1960	0.52
1961	0.732
1962	0.382
1963	0.778
1964	0.904
1965	1.281
1966	1.264
1967	1.473
1968	0.95
1969	0.97
1970	1.115
1971	1.118
1972	1.162
1973	0.882
1974	1.184