# southamerica_arge017 - Estancia Mamuil-Malal - 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/3522
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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_arge017 - Estancia Mamuil-Malal - 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: Estancia Mamuil-Malal
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -39.68
#	Southernmost_Latitude: -39.68
#	Easternmost_Longitude: -71.22
#	Westernmost_Longitude: -71.22
#	Elevation: 890 m
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# Data_Collection
#	Collection_Name: southamerica_arge017B
#	Earliest_Year: 1752
#	Most_Recent_Year: 1976
#	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":"4.88047172968","T2":"13.6608420377","M1":"0.0231516240953","M2":"0.539995539397"}}
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# Species
#	Species_Name: monkey puzzle
#	Species_Code: ARAR
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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
1752	1.129
1753	1.055
1754	0.954
1755	0.712
1756	1.128
1757	0.829
1758	1.054
1759	1.0
1760	1.233
1761	1.293
1762	0.982
1763	1.058
1764	1.066
1765	0.997
1766	1.008
1767	0.834
1768	0.914
1769	0.858
1770	0.88
1771	0.876
1772	0.962
1773	1.049
1774	0.973
1775	1.106
1776	1.225
1777	1.127
1778	1.048
1779	0.996
1780	1.016
1781	1.071
1782	0.971
1783	1.007
1784	1.196
1785	1.103
1786	0.876
1787	0.913
1788	1.081
1789	0.788
1790	0.518
1791	0.883
1792	0.955
1793	1.294
1794	1.221
1795	1.404
1796	1.333
1797	1.129
1798	0.856
1799	0.952
1800	1.027
1801	0.812
1802	0.772
1803	0.802
1804	0.916
1805	0.813
1806	0.995
1807	1.273
1808	1.339
1809	1.323
1810	1.037
1811	1.151
1812	1.086
1813	0.721
1814	0.975
1815	1.093
1816	1.052
1817	0.955
1818	0.884
1819	0.781
1820	0.821
1821	0.836
1822	0.806
1823	0.879
1824	0.884
1825	0.977
1826	1.176
1827	1.067
1828	1.057
1829	1.182
1830	0.88
1831	0.907
1832	1.069
1833	1.16
1834	1.151
1835	1.26
1836	1.122
1837	1.298
1838	1.068
1839	0.785
1840	1.198
1841	0.999
1842	0.884
1843	1.123
1844	1.273
1845	1.03
1846	1.056
1847	1.063
1848	0.989
1849	1.017
1850	1.055
1851	0.925
1852	1.118
1853	0.829
1854	1.044
1855	0.915
1856	0.922
1857	1.027
1858	1.087
1859	0.981
1860	0.898
1861	0.809
1862	0.981
1863	0.858
1864	0.688
1865	0.647
1866	0.734
1867	0.64
1868	0.776
1869	0.922
1870	0.64
1871	0.744
1872	0.874
1873	0.703
1874	0.865
1875	0.842
1876	1.216
1877	1.151
1878	1.084
1879	0.972
1880	1.065
1881	0.967
1882	1.143
1883	1.18
1884	1.161
1885	0.868
1886	0.924
1887	0.816
1888	0.677
1889	0.706
1890	0.862
1891	0.991
1892	0.974
1893	0.786
1894	0.917
1895	0.933
1896	0.687
1897	0.531
1898	0.696
1899	0.616
1900	0.727
1901	0.898
1902	0.897
1903	1.108
1904	1.141
1905	1.029
1906	0.868
1907	1.07
1908	0.883
1909	0.786
1910	0.972
1911	0.861
1912	0.702
1913	0.663
1914	0.931
1915	1.03
1916	0.778
1917	0.777
1918	0.821
1919	0.901
1920	0.978
1921	0.964
1922	1.083
1923	1.088
1924	1.065
1925	1.119
1926	1.337
1927	1.159
1928	1.145
1929	1.277
1930	1.062
1931	0.997
1932	1.129
1933	1.39
1934	1.246
1935	1.011
1936	0.819
1937	0.661
1938	0.999
1939	0.935
1940	1.021
1941	1.158
1942	0.832
1943	0.911
1944	1.047
1945	0.912
1946	1.278
1947	1.025
1948	1.191
1949	1.237
1950	1.484
1951	1.529
1952	0.847
1953	1.105
1954	1.253
1955	1.174
1956	1.102
1957	0.974
1958	1.137
1959	1.437
1960	1.178
1961	1.366
1962	0.942
1963	0.973
1964	1.269
1965	0.88
1966	1.045
1967	0.83
1968	0.77
1969	0.792
1970	0.646
1971	0.955
1972	0.583
1973	0.707
1974	0.893
1975	0.722
1976	0.808