# southamerica_arge079 - Norquinco - 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.
#
#
# 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/5171
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: southamerica_arge079 - Norquinco - 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.
#--------------------
#	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: Norquinco
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -39.12
#	Southernmost_Latitude: -39.12
#	Easternmost_Longitude: -71.12
#	Westernmost_Longitude: -71.12
#	Elevation: 1150 m
#--------------------
# Data_Collection
#	Collection_Name: southamerica_arge079B
#	Earliest_Year: 1743
#	Most_Recent_Year: 1989
#	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":"2.8711133947","T2":"11.9940062966","M1":"0.0224703123755","M2":"0.492719659115"}}
#--------------------
# 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
1743	0.476
1744	0.683
1745	0.822
1746	0.956
1747	0.745
1748	0.895
1749	1.278
1750	1.091
1751	0.7
1752	0.582
1753	0.907
1754	0.715
1755	0.862
1756	1.206
1757	1.079
1758	1.157
1759	1.29
1760	1.561
1761	1.301
1762	1.017
1763	1.392
1764	0.879
1765	0.844
1766	1.307
1767	0.832
1768	0.979
1769	0.67
1770	1.08
1771	1.07
1772	1.097
1773	1.25
1774	0.876
1775	1.005
1776	0.746
1777	0.966
1778	0.508
1779	0.529
1780	0.758
1781	1.072
1782	0.955
1783	0.508
1784	1.164
1785	1.009
1786	0.657
1787	0.636
1788	1.326
1789	1.363
1790	1.308
1791	1.156
1792	0.977
1793	1.539
1794	1.265
1795	1.223
1796	0.838
1797	1.055
1798	0.879
1799	0.969
1800	1.172
1801	1.161
1802	1.038
1803	1.076
1804	1.013
1805	0.813
1806	0.524
1807	0.738
1808	1.389
1809	1.294
1810	1.482
1811	1.267
1812	1.19
1813	1.002
1814	1.217
1815	1.328
1816	0.907
1817	1.133
1818	1.067
1819	0.556
1820	0.813
1821	1.085
1822	1.367
1823	1.425
1824	0.795
1825	1.042
1826	0.746
1827	0.758
1828	0.715
1829	1.211
1830	0.911
1831	1.173
1832	1.058
1833	0.949
1834	1.098
1835	0.63
1836	0.5
1837	1.017
1838	1.114
1839	0.638
1840	0.662
1841	0.426
1842	0.918
1843	0.89
1844	0.883
1845	0.4
1846	0.611
1847	0.95
1848	1.065
1849	1.101
1850	0.752
1851	0.782
1852	1.033
1853	0.866
1854	0.765
1855	1.063
1856	1.119
1857	1.176
1858	0.846
1859	0.477
1860	0.566
1861	0.675
1862	0.841
1863	0.985
1864	0.916
1865	0.687
1866	1.24
1867	1.011
1868	1.447
1869	1.112
1870	0.903
1871	0.8
1872	0.969
1873	0.864
1874	0.822
1875	0.851
1876	0.788
1877	0.602
1878	0.574
1879	0.89
1880	0.77
1881	0.705
1882	0.801
1883	0.872
1884	1.079
1885	1.088
1886	1.104
1887	0.999
1888	1.019
1889	0.884
1890	1.015
1891	0.686
1892	0.697
1893	0.466
1894	1.009
1895	1.097
1896	0.782
1897	1.072
1898	1.268
1899	0.895
1900	0.951
1901	0.964
1902	0.744
1903	0.901
1904	1.03
1905	0.929
1906	0.863
1907	1.244
1908	1.29
1909	1.132
1910	0.854
1911	1.073
1912	0.996
1913	0.563
1914	0.374
1915	0.783
1916	0.456
1917	0.46
1918	0.782
1919	0.356
1920	0.825
1921	0.703
1922	0.623
1923	0.873
1924	0.717
1925	1.014
1926	1.19
1927	0.843
1928	0.871
1929	1.218
1930	1.339
1931	0.83
1932	0.948
1933	1.049
1934	0.917
1935	1.079
1936	0.939
1937	1.035
1938	1.24
1939	1.0
1940	1.405
1941	1.523
1942	1.036
1943	0.687
1944	1.246
1945	2.086
1946	2.161
1947	1.037
1948	1.03
1949	0.917
1950	1.033
1951	1.468
1952	1.004
1953	0.615
1954	1.007
1955	1.293
1956	1.136
1957	0.868
1958	0.702
1959	0.639
1960	0.618
1961	0.695
1962	0.437
1963	0.96
1964	1.412
1965	1.298
1966	1.516
1967	0.985
1968	1.31
1969	0.689
1970	1.168
1971	1.154
1972	0.917
1973	0.724
1974	0.845
1975	1.127
1976	1.261
1977	1.108
1978	0.763
1979	1.024
1980	1.412
1981	0.678
1982	0.831
1983	0.455
1984	0.82
1985	0.918
1986	0.991
1987	0.876
1988	0.828
1989	0.655