# southamerica_arge072 - FutaleufÃÂº - 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/5164
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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_arge072 - FutaleufÃÂº - Breitenmoser Tree Ring Chronology Data
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# 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: FutaleufÃÂº
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -43.18
#	Southernmost_Latitude: -43.18
#	Easternmost_Longitude: -71.7
#	Westernmost_Longitude: -71.7
#	Elevation: 470 m
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# Data_Collection
#	Collection_Name: southamerica_arge072B
#	Earliest_Year: 1759
#	Most_Recent_Year: 1992
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"2.40338194344","T2":"11.6322081521","M1":"0.023732384524","M2":"0.61170784448"}}
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# 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)
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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
1759	1.227
1760	1.235
1761	1.287
1762	1.101
1763	1.572
1764	1.347
1765	1.335
1766	1.435
1767	1.175
1768	1.253
1769	1.034
1770	1.02
1771	1.282
1772	0.756
1773	0.98
1774	1.229
1775	1.308
1776	1.027
1777	1.236
1778	1.032
1779	1.092
1780	1.075
1781	0.986
1782	1.06
1783	0.674
1784	1.331
1785	1.241
1786	0.921
1787	1.153
1788	1.035
1789	1.041
1790	0.848
1791	0.805
1792	0.781
1793	0.952
1794	0.991
1795	0.678
1796	0.806
1797	0.999
1798	0.926
1799	1.056
1800	1.116
1801	0.658
1802	0.762
1803	0.869
1804	0.794
1805	0.948
1806	1.032
1807	0.831
1808	1.139
1809	0.915
1810	1.111
1811	1.041
1812	0.971
1813	0.723
1814	0.779
1815	0.472
1816	0.765
1817	0.527
1818	0.636
1819	0.51
1820	0.428
1821	0.411
1822	0.532
1823	0.656
1824	0.71
1825	0.803
1826	1.087
1827	0.515
1828	0.709
1829	0.694
1830	0.713
1831	0.625
1832	0.762
1833	0.708
1834	0.781
1835	0.594
1836	0.422
1837	0.708
1838	0.862
1839	0.589
1840	0.931
1841	0.544
1842	0.977
1843	0.929
1844	0.957
1845	0.599
1846	1.091
1847	1.035
1848	0.836
1849	0.844
1850	0.922
1851	0.525
1852	1.62
1853	0.901
1854	0.984
1855	0.587
1856	0.87
1857	0.833
1858	0.725
1859	0.47
1860	0.698
1861	0.426
1862	0.703
1863	0.689
1864	0.612
1865	0.621
1866	0.782
1867	0.63
1868	0.827
1869	0.664
1870	0.481
1871	0.687
1872	1.628
1873	1.873
1874	2.123
1875	2.153
1876	1.979
1877	1.74
1878	1.789
1879	1.176
1880	1.593
1881	1.094
1882	1.35
1883	1.119
1884	0.811
1885	0.668
1886	1.352
1887	1.528
1888	1.581
1889	1.735
1890	1.292
1891	1.254
1892	0.907
1893	1.069
1894	0.956
1895	1.278
1896	1.1
1897	1.012
1898	1.279
1899	1.501
1900	1.572
1901	0.989
1902	1.416
1903	1.401
1904	0.925
1905	1.358
1906	0.918
1907	1.258
1908	0.847
1909	0.836
1910	0.942
1911	0.582
1912	0.941
1913	0.565
1914	0.906
1915	1.102
1916	1.402
1917	0.894
1918	1.231
1919	1.081
1920	1.344
1921	1.242
1922	0.901
1923	1.204
1924	0.819
1925	1.108
1926	1.314
1927	0.94
1928	1.206
1929	1.156
1930	1.167
1931	0.762
1932	1.018
1933	1.053
1934	0.893
1935	1.16
1936	1.275
1937	0.869
1938	1.24
1939	1.079
1940	1.073
1941	1.12
1942	0.866
1943	0.506
1944	0.523
1945	0.583
1946	1.105
1947	0.869
1948	0.786
1949	0.773
1950	0.969
1951	0.946
1952	1.064
1953	0.787
1954	1.006
1955	0.609
1956	0.963
1957	0.476
1958	0.833
1959	0.808
1960	0.827
1961	0.885
1962	0.528
1963	1.001
1964	0.957
1965	1.219
1966	0.944
1967	1.148
1968	1.03
1969	0.925
1970	0.89
1971	1.118
1972	0.957
1973	0.979
1974	1.026
1975	1.07
1976	0.929
1977	1.141
1978	0.861
1979	0.958
1980	1.144
1981	0.636
1982	0.959
1983	0.729
1984	1.099
1985	0.866
1986	0.912
1987	0.554
1988	0.896
1989	0.828
1990	0.748
1991	1.268
1992	0.492