# southamerica_arge076 - Rio Minero - 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/5192
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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_arge076 - Rio Minero - 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: Rio Minero
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -40.7
#	Southernmost_Latitude: -40.7
#	Easternmost_Longitude: -71.27
#	Westernmost_Longitude: -71.27
#	Elevation: 1050 m
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# Data_Collection
#	Collection_Name: southamerica_arge076B
#	Earliest_Year: 1752
#	Most_Recent_Year: 1991
#	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":"2.3722005706","T2":"12.1082271835","M1":"0.0230523714596","M2":"0.621333296089"}}
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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
1752	0.689
1753	1.013
1754	1.204
1755	1.106
1756	1.783
1757	1.963
1758	2.075
1759	2.14
1760	2.285
1761	1.501
1762	0.861
1763	1.116
1764	0.948
1765	0.764
1766	0.755
1767	0.822
1768	0.71
1769	0.731
1770	0.683
1771	1.156
1772	1.22
1773	1.412
1774	1.262
1775	1.267
1776	1.236
1777	1.257
1778	0.995
1779	0.753
1780	1.051
1781	1.283
1782	0.936
1783	1.141
1784	1.27
1785	1.059
1786	1.067
1787	0.923
1788	1.192
1789	1.134
1790	1.105
1791	1.221
1792	1.028
1793	0.982
1794	1.103
1795	1.206
1796	1.279
1797	1.638
1798	1.302
1799	1.359
1800	1.536
1801	1.165
1802	1.002
1803	1.083
1804	0.888
1805	0.802
1806	0.857
1807	0.979
1808	1.216
1809	1.228
1810	0.946
1811	1.062
1812	1.129
1813	0.171
1814	0.416
1815	0.753
1816	0.936
1817	1.042
1818	0.938
1819	0.962
1820	0.744
1821	0.708
1822	0.847
1823	0.941
1824	0.887
1825	1.04
1826	0.86
1827	0.554
1828	0.86
1829	1.042
1830	1.331
1831	1.137
1832	1.165
1833	1.006
1834	1.207
1835	1.377
1836	0.947
1837	1.066
1838	0.832
1839	0.673
1840	0.723
1841	0.485
1842	0.826
1843	1.06
1844	0.952
1845	0.577
1846	0.729
1847	0.672
1848	0.881
1849	0.613
1850	0.411
1851	0.346
1852	0.794
1853	0.729
1854	0.617
1855	0.869
1856	0.729
1857	0.77
1858	0.693
1859	0.537
1860	0.709
1861	0.585
1862	0.655
1863	0.98
1864	0.553
1865	0.551
1866	0.871
1867	1.116
1868	1.446
1869	1.417
1870	1.823
1871	1.041
1872	1.209
1873	1.127
1874	0.895
1875	0.889
1876	0.829
1877	0.534
1878	1.219
1879	1.702
1880	1.194
1881	1.183
1882	1.123
1883	0.978
1884	1.185
1885	1.058
1886	0.86
1887	1.04
1888	0.97
1889	0.901
1890	0.924
1891	0.849
1892	1.069
1893	0.774
1894	0.904
1895	0.907
1896	0.957
1897	0.878
1898	1.493
1899	1.317
1900	1.246
1901	0.943
1902	1.289
1903	1.22
1904	0.897
1905	1.1
1906	0.963
1907	1.197
1908	0.713
1909	0.914
1910	1.124
1911	0.597
1912	0.82
1913	0.499
1914	0.687
1915	1.229
1916	1.053
1917	0.693
1918	0.956
1919	0.783
1920	1.116
1921	1.19
1922	0.705
1923	0.402
1924	0.904
1925	1.077
1926	1.224
1927	0.819
1928	0.893
1929	1.126
1930	0.966
1931	0.843
1932	0.784
1933	1.349
1934	0.97
1935	1.053
1936	1.085
1937	0.966
1938	1.035
1939	1.284
1940	1.267
1941	1.428
1942	1.315
1943	0.671
1944	0.753
1945	1.619
1946	1.774
1947	1.437
1948	1.281
1949	1.179
1950	0.837
1951	1.324
1952	1.099
1953	0.922
1954	0.758
1955	1.078
1956	0.681
1957	0.373
1958	0.469
1959	0.641
1960	0.558
1961	0.407
1962	0.336
1963	0.887
1964	0.984
1965	1.049
1966	1.033
1967	0.837
1968	0.793
1969	0.625
1970	0.891
1971	0.913
1972	0.818
1973	1.066
1974	1.223
1975	1.298
1976	1.285
1977	1.507
1978	0.895
1979	0.733
1980	1.22
1981	0.941
1982	1.085
1983	0.995
1984	0.983
1985	1.061
1986	1.182
1987	0.69
1988	1.025
1989	1.069
1990	0.955
1991	1.36