# southamerica_arge066 - Aserradero Isla Grande Monticulo - 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.
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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/2768
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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_arge066 - Aserradero Isla Grande Monticulo - 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.
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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: Aserradero Isla Grande Monticulo
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -54.52
#	Southernmost_Latitude: -54.52
#	Easternmost_Longitude: -67.42
#	Westernmost_Longitude: -67.42
#	Elevation: 250 m
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# Data_Collection
#	Collection_Name: southamerica_arge066B
#	Earliest_Year: 1755
#	Most_Recent_Year: 1986
#	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":"4.66992350207","T2":"17.1749558318","M1":"0.0226732941359","M2":"0.38056948403"}}
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# Species
#	Species_Name: lenga nothofagus
#	Species_Code: NOPU
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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
1755	1.194
1756	0.805
1757	0.495
1758	1.1
1759	1.15
1760	1.375
1761	1.182
1762	1.129
1763	0.874
1764	1.188
1765	1.461
1766	1.172
1767	1.209
1768	0.811
1769	0.518
1770	0.853
1771	1.019
1772	0.948
1773	0.612
1774	0.982
1775	0.98
1776	0.807
1777	0.239
1778	0.452
1779	1.326
1780	0.94
1781	0.653
1782	0.484
1783	0.472
1784	0.71
1785	1.222
1786	1.274
1787	1.18
1788	1.44
1789	1.026
1790	0.204
1791	0.138
1792	1.453
1793	1.602
1794	1.245
1795	1.079
1796	0.725
1797	0.67
1798	0.687
1799	1.119
1800	1.377
1801	1.144
1802	1.134
1803	1.183
1804	0.251
1805	0.152
1806	1.131
1807	1.274
1808	1.15
1809	1.167
1810	1.293
1811	0.76
1812	0.468
1813	0.25
1814	1.038
1815	1.43
1816	1.043
1817	1.511
1818	0.878
1819	0.291
1820	1.039
1821	1.21
1822	1.354
1823	1.326
1824	1.061
1825	1.247
1826	1.002
1827	0.663
1828	1.492
1829	1.612
1830	1.505
1831	1.319
1832	1.22
1833	0.645
1834	0.359
1835	1.303
1836	1.47
1837	1.133
1838	0.833
1839	0.605
1840	0.517
1841	1.169
1842	1.213
1843	1.234
1844	1.381
1845	1.475
1846	0.917
1847	0.897
1848	1.616
1849	1.289
1850	1.183
1851	0.749
1852	0.514
1853	1.292
1854	0.626
1855	0.735
1856	1.134
1857	1.195
1858	1.207
1859	0.848
1860	0.561
1861	0.598
1862	1.228
1863	1.577
1864	1.27
1865	1.286
1866	1.223
1867	1.418
1868	1.287
1869	1.528
1870	1.818
1871	1.384
1872	0.899
1873	0.701
1874	0.77
1875	0.828
1876	1.511
1877	1.073
1878	0.795
1879	1.12
1880	1.182
1881	0.916
1882	0.713
1883	1.404
1884	1.473
1885	1.198
1886	1.23
1887	0.827
1888	0.311
1889	0.273
1890	1.003
1891	1.282
1892	1.0
1893	0.826
1894	0.877
1895	0.31
1896	0.16
1897	1.073
1898	1.449
1899	1.055
1900	0.637
1901	0.942
1902	0.982
1903	0.958
1904	1.342
1905	1.221
1906	0.804
1907	0.782
1908	0.844
1909	0.867
1910	0.676
1911	1.393
1912	1.217
1913	0.969
1914	0.935
1915	0.68
1916	0.477
1917	0.703
1918	1.397
1919	0.827
1920	0.95
1921	1.181
1922	0.65
1923	0.358
1924	0.894
1925	1.132
1926	1.335
1927	1.212
1928	0.906
1929	0.385
1930	0.251
1931	0.788
1932	0.892
1933	0.562
1934	0.484
1935	0.458
1936	0.677
1937	1.047
1938	1.505
1939	1.247
1940	0.806
1941	0.833
1942	0.648
1943	0.537
1944	1.38
1945	1.03
1946	1.043
1947	0.97
1948	0.896
1949	0.331
1950	0.853
1951	1.121
1952	1.189
1953	1.115
1954	1.243
1955	1.425
1956	1.206
1957	1.103
1958	0.923
1959	1.086
1960	1.044
1961	0.965
1962	0.968
1963	1.282
1964	1.294
1965	0.864
1966	1.133
1967	1.633
1968	1.077
1969	0.767
1970	0.777
1971	0.611
1972	1.106
1973	0.845
1974	0.973
1975	1.117
1976	1.102
1977	1.05
1978	0.752
1979	1.3
1980	1.175
1981	0.755
1982	1.256
1983	0.914
1984	0.976
1985	1.183
1986	1.302