# southamerica_arge040 - Estancia Harberton - 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/2775
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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
#--------------------
# Title
#	Study_Name: southamerica_arge040 - Estancia Harberton - 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 Harberton
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -54.92
#	Southernmost_Latitude: -54.92
#	Easternmost_Longitude: -67.33
#	Westernmost_Longitude: -67.33
#	Elevation: 30 m
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# Data_Collection
#	Collection_Name: southamerica_arge040B
#	Earliest_Year: 1772
#	Most_Recent_Year: 1985
#	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":"7.85564432849","T2":"17.2164870448","M1":"0.0221983210377","M2":"0.406437458063"}}
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# Species
#	Species_Name: coihue de Magallanes
#	Species_Code: NOBE
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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
1772	1.35
1773	0.987
1774	0.961
1775	0.984
1776	0.77
1777	0.173
1778	0.211
1779	0.917
1780	0.887
1781	0.901
1782	0.915
1783	0.393
1784	0.911
1785	1.181
1786	1.112
1787	0.699
1788	1.321
1789	0.727
1790	0.154
1791	0.253
1792	1.213
1793	1.275
1794	1.314
1795	1.185
1796	1.013
1797	1.076
1798	1.05
1799	1.193
1800	1.258
1801	1.191
1802	1.018
1803	1.089
1804	0.334
1805	0.098
1806	0.754
1807	1.229
1808	1.309
1809	1.011
1810	1.067
1811	0.867
1812	0.504
1813	0.413
1814	1.11
1815	1.059
1816	0.947
1817	0.997
1818	0.723
1819	0.666
1820	1.087
1821	1.031
1822	1.066
1823	1.145
1824	0.927
1825	0.401
1826	0.568
1827	1.143
1828	1.313
1829	1.19
1830	1.514
1831	1.26
1832	0.821
1833	0.454
1834	0.232
1835	1.16
1836	1.615
1837	1.502
1838	1.245
1839	0.356
1840	0.104
1841	0.855
1842	1.224
1843	1.072
1844	1.167
1845	0.596
1846	0.093
1847	0.107
1848	1.149
1849	1.262
1850	1.221
1851	0.875
1852	0.252
1853	0.861
1854	0.94
1855	0.863
1856	1.074
1857	1.333
1858	1.351
1859	1.26
1860	0.679
1861	0.249
1862	1.137
1863	1.888
1864	1.359
1865	1.105
1866	0.89
1867	0.473
1868	0.66
1869	1.648
1870	1.443
1871	1.234
1872	1.007
1873	0.997
1874	0.495
1875	0.644
1876	1.342
1877	1.303
1878	1.224
1879	1.589
1880	0.646
1881	1.013
1882	1.299
1883	1.611
1884	1.771
1885	1.643
1886	1.303
1887	0.96
1888	0.917
1889	1.3
1890	1.744
1891	1.493
1892	1.266
1893	1.076
1894	0.75
1895	0.87
1896	1.12
1897	1.722
1898	1.787
1899	1.366
1900	1.297
1901	0.527
1902	0.281
1903	0.921
1904	1.186
1905	1.334
1906	1.027
1907	0.896
1908	0.964
1909	1.244
1910	1.112
1911	0.759
1912	0.912
1913	0.905
1914	0.542
1915	0.267
1916	0.721
1917	1.094
1918	0.973
1919	0.713
1920	0.875
1921	0.692
1922	0.773
1923	1.191
1924	1.178
1925	1.297
1926	1.061
1927	0.749
1928	0.21
1929	0.423
1930	1.178
1931	1.103
1932	1.273
1933	0.831
1934	0.949
1935	1.529
1936	0.691
1937	1.282
1938	1.869
1939	1.459
1940	0.997
1941	0.925
1942	0.62
1943	0.408
1944	1.359
1945	0.908
1946	0.617
1947	1.215
1948	0.996
1949	0.368
1950	0.248
1951	0.847
1952	0.414
1953	0.67
1954	1.28
1955	1.179
1956	1.062
1957	0.887
1958	0.241
1959	0.227
1960	0.705
1961	0.863
1962	0.958
1963	1.011
1964	0.522
1965	0.523
1966	1.317
1967	1.297
1968	0.879
1969	0.937
1970	0.546
1971	0.189
1972	1.144
1973	1.206
1974	1.096
1975	1.211
1976	1.376
1977	1.165
1978	1.018
1979	1.261
1980	1.13
1981	0.997
1982	1.298
1983	0.706
1984	0.642
1985	0.87