# southamerica_arge011 - Lago Moquehue - 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/3534
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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_arge011 - Lago Moquehue - 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: Lago Moquehue
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -38.87
#	Southernmost_Latitude: -38.87
#	Easternmost_Longitude: -71.25
#	Westernmost_Longitude: -71.25
#	Elevation: 1250 m
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# Data_Collection
#	Collection_Name: southamerica_arge011B
#	Earliest_Year: 1744
#	Most_Recent_Year: 1974
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"3.41629739217","T2":"13.3287425899","M1":"0.0231193796081","M2":"0.533340289499"}}
#--------------------
# 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
1744	0.605
1745	0.818
1746	0.981
1747	1.097
1748	1.268
1749	1.785
1750	1.553
1751	1.394
1752	1.497
1753	1.573
1754	1.612
1755	1.616
1756	1.728
1757	2.113
1758	2.213
1759	1.997
1760	2.011
1761	1.577
1762	1.344
1763	1.54
1764	1.482
1765	1.31
1766	1.415
1767	1.09
1768	1.302
1769	1.511
1770	1.44
1771	1.366
1772	0.816
1773	0.696
1774	0.747
1775	0.85
1776	0.823
1777	0.795
1778	0.651
1779	0.611
1780	0.848
1781	1.272
1782	1.423
1783	0.869
1784	0.755
1785	0.935
1786	0.797
1787	0.568
1788	0.911
1789	0.654
1790	0.8
1791	0.694
1792	0.638
1793	0.861
1794	0.968
1795	0.758
1796	0.621
1797	0.718
1798	0.745
1799	0.644
1800	1.12
1801	0.649
1802	0.528
1803	0.658
1804	0.906
1805	0.681
1806	0.56
1807	0.376
1808	0.841
1809	0.787
1810	0.749
1811	0.564
1812	0.922
1813	0.942
1814	1.066
1815	1.08
1816	1.054
1817	0.759
1818	0.395
1819	0.28
1820	0.789
1821	0.786
1822	1.121
1823	1.187
1824	0.976
1825	0.827
1826	0.792
1827	1.064
1828	1.225
1829	1.493
1830	1.265
1831	1.666
1832	2.013
1833	1.832
1834	1.526
1835	1.675
1836	1.341
1837	1.257
1838	1.626
1839	1.096
1840	1.098
1841	0.621
1842	0.744
1843	0.944
1844	1.323
1845	1.038
1846	1.099
1847	1.134
1848	1.211
1849	1.398
1850	1.041
1851	0.992
1852	1.199
1853	0.925
1854	0.652
1855	0.699
1856	0.794
1857	0.914
1858	0.741
1859	0.666
1860	0.617
1861	0.548
1862	0.597
1863	0.531
1864	0.638
1865	0.399
1866	0.693
1867	0.591
1868	0.872
1869	0.535
1870	0.497
1871	0.42
1872	0.674
1873	0.736
1874	0.517
1875	0.165
1876	0.637
1877	0.529
1878	0.442
1879	0.332
1880	0.711
1881	0.733
1882	0.765
1883	0.764
1884	0.849
1885	0.777
1886	1.0
1887	0.929
1888	0.682
1889	0.704
1890	0.81
1891	0.739
1892	0.894
1893	0.624
1894	0.829
1895	1.258
1896	1.354
1897	0.67
1898	1.388
1899	1.707
1900	1.787
1901	1.668
1902	1.459
1903	1.85
1904	1.557
1905	1.663
1906	1.311
1907	1.477
1908	1.708
1909	1.08
1910	1.425
1911	1.398
1912	1.274
1913	1.215
1914	1.145
1915	1.13
1916	1.261
1917	1.121
1918	1.487
1919	1.431
1920	1.038
1921	1.244
1922	1.2
1923	1.225
1924	1.066
1925	1.436
1926	1.524
1927	1.189
1928	0.885
1929	1.284
1930	0.987
1931	0.755
1932	0.735
1933	0.89
1934	0.885
1935	0.925
1936	0.557
1937	0.583
1938	0.936
1939	0.757
1940	1.025
1941	0.915
1942	0.841
1943	0.645
1944	0.777
1945	0.734
1946	1.299
1947	1.048
1948	0.911
1949	0.527
1950	0.664
1951	1.062
1952	0.631
1953	0.678
1954	0.772
1955	0.554
1956	0.73
1957	0.631
1958	0.644
1959	0.787
1960	0.651
1961	0.742
1962	0.641
1963	0.751
1964	0.864
1965	0.727
1966	0.747
1967	0.671
1968	1.299
1969	1.458
1970	1.171
1971	1.363
1972	1.156
1973	1.267
1974	1.595