# southamerica_arge008 - Cuyin Manzano - 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/3516
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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_arge008 - Cuyin Manzano - 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: Cuyin Manzano
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -40.72
#	Southernmost_Latitude: -40.72
#	Easternmost_Longitude: -71.13
#	Westernmost_Longitude: -71.13
#	Elevation: 880 m
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# Data_Collection
#	Collection_Name: southamerica_arge008B
#	Earliest_Year: 1686
#	Most_Recent_Year: 1974
#	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":"1.93847766656","T2":"11.3935689959","M1":"0.0228213104077","M2":"0.617669582911"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1686	0.432
1687	0.386
1688	0.669
1689	0.951
1690	1.376
1691	1.323
1692	1.47
1693	1.004
1694	1.268
1695	1.189
1696	1.218
1697	1.439
1698	1.115
1699	1.271
1700	1.29
1701	1.166
1702	1.027
1703	1.205
1704	1.391
1705	0.706
1706	0.804
1707	1.046
1708	1.057
1709	1.2
1710	0.865
1711	0.874
1712	1.009
1713	0.91
1714	0.757
1715	1.139
1716	0.624
1717	0.729
1718	0.586
1719	0.58
1720	0.931
1721	0.869
1722	0.875
1723	1.11
1724	1.481
1725	1.672
1726	1.448
1727	1.149
1728	1.43
1729	1.156
1730	1.039
1731	1.302
1732	1.335
1733	1.013
1734	1.001
1735	1.033
1736	0.982
1737	0.863
1738	1.065
1739	1.144
1740	1.155
1741	1.174
1742	1.261
1743	0.802
1744	1.026
1745	0.972
1746	0.914
1747	0.674
1748	0.718
1749	1.184
1750	1.085
1751	0.8
1752	0.788
1753	1.031
1754	0.923
1755	0.542
1756	1.173
1757	1.16
1758	0.89
1759	0.748
1760	1.105
1761	1.2
1762	0.702
1763	0.914
1764	0.99
1765	0.897
1766	1.028
1767	0.859
1768	0.83
1769	0.922
1770	0.661
1771	0.722
1772	0.799
1773	0.765
1774	0.72
1775	0.944
1776	1.04
1777	1.072
1778	0.952
1779	0.833
1780	0.9
1781	1.289
1782	0.854
1783	0.692
1784	1.194
1785	0.867
1786	0.954
1787	1.127
1788	1.353
1789	1.33
1790	1.504
1791	1.045
1792	1.218
1793	1.008
1794	0.96
1795	0.907
1796	1.063
1797	1.321
1798	1.171
1799	0.788
1800	0.712
1801	0.583
1802	0.459
1803	0.725
1804	0.703
1805	0.554
1806	0.51
1807	0.55
1808	0.872
1809	0.994
1810	0.904
1811	1.036
1812	1.161
1813	0.325
1814	0.614
1815	0.926
1816	1.136
1817	1.043
1818	1.142
1819	0.77
1820	0.625
1821	0.624
1822	0.92
1823	1.054
1824	1.037
1825	1.155
1826	1.151
1827	0.843
1828	1.067
1829	1.312
1830	1.585
1831	1.418
1832	1.128
1833	1.017
1834	1.61
1835	1.329
1836	1.04
1837	1.328
1838	1.278
1839	0.982
1840	1.193
1841	0.568
1842	0.525
1843	0.967
1844	0.815
1845	0.489
1846	0.977
1847	0.57
1848	0.895
1849	0.69
1850	0.732
1851	0.582
1852	0.77
1853	0.842
1854	0.85
1855	1.157
1856	1.213
1857	1.108
1858	1.012
1859	0.655
1860	0.956
1861	0.855
1862	0.72
1863	1.184
1864	0.811
1865	0.478
1866	0.82
1867	0.757
1868	1.226
1869	1.188
1870	1.316
1871	1.028
1872	1.27
1873	1.215
1874	1.103
1875	0.743
1876	1.097
1877	0.693
1878	1.297
1879	1.444
1880	1.105
1881	0.917
1882	1.217
1883	1.282
1884	1.145
1885	0.896
1886	1.142
1887	0.874
1888	1.229
1889	1.388
1890	1.331
1891	1.13
1892	1.285
1893	0.886
1894	1.087
1895	1.109
1896	0.834
1897	0.523
1898	0.242
1899	0.685
1900	0.812
1901	0.666
1902	0.801
1903	0.788
1904	0.561
1905	0.714
1906	0.896
1907	0.859
1908	0.437
1909	0.76
1910	0.957
1911	0.464
1912	0.514
1913	0.409
1914	0.621
1915	0.969
1916	0.796
1917	0.523
1918	0.922
1919	0.851
1920	0.892
1921	0.875
1922	0.714
1923	0.425
1924	0.673
1925	0.822
1926	1.325
1927	0.858
1928	0.867
1929	1.249
1930	1.045
1931	0.688
1932	0.887
1933	1.249
1934	1.2
1935	1.426
1936	1.068
1937	1.329
1938	1.392
1939	1.615
1940	2.201
1941	2.198
1942	2.142
1943	0.665
1944	0.402
1945	1.165
1946	1.466
1947	1.044
1948	1.116
1949	1.351
1950	0.967
1951	1.521
1952	1.259
1953	1.118
1954	1.144
1955	1.129
1956	0.954
1957	0.677
1958	1.148
1959	1.254
1960	0.757
1961	0.468
1962	0.341
1963	0.822
1964	1.123
1965	1.21
1966	1.392
1967	1.075
1968	0.909
1969	0.816
1970	0.894
1971	0.96
1972	0.909
1973	1.296
1974	1.85