# southamerica_arge100 - Paso de las Nubes 4 - Breitenmoser Tree Ring Chronology Data
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#		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/5176
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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_arge100 - Paso de las Nubes 4 - 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: Paso de las Nubes 4
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -41.12
#	Southernmost_Latitude: -41.12
#	Easternmost_Longitude: -71.8
#	Westernmost_Longitude: -71.8
#	Elevation: 1230 m
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# Data_Collection
#	Collection_Name: southamerica_arge100B
#	Earliest_Year: 1749
#	Most_Recent_Year: 1991
#	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":"5.99332369646","T2":"15.8933819856","M1":"0.0225270828516","M2":"0.361060256911"}}
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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
1749	0.717
1750	0.853
1751	0.812
1752	0.361
1753	0.431
1754	0.592
1755	0.766
1756	0.743
1757	0.928
1758	0.716
1759	1.052
1760	0.771
1761	0.861
1762	1.078
1763	0.889
1764	0.877
1765	0.958
1766	0.734
1767	0.798
1768	0.777
1769	0.742
1770	0.458
1771	0.729
1772	0.944
1773	0.81
1774	0.487
1775	0.231
1776	0.419
1777	0.634
1778	0.845
1779	0.915
1780	0.901
1781	1.048
1782	1.101
1783	1.027
1784	0.909
1785	0.856
1786	1.207
1787	1.089
1788	0.733
1789	1.082
1790	0.608
1791	0.585
1792	0.975
1793	0.545
1794	0.938
1795	0.915
1796	0.722
1797	0.78
1798	0.612
1799	0.847
1800	0.814
1801	0.81
1802	0.77
1803	0.631
1804	1.216
1805	1.346
1806	1.296
1807	1.677
1808	1.337
1809	1.208
1810	1.041
1811	0.812
1812	1.032
1813	0.882
1814	0.554
1815	0.849
1816	1.019
1817	1.098
1818	0.728
1819	1.248
1820	0.836
1821	0.839
1822	1.512
1823	1.341
1824	1.472
1825	1.441
1826	1.062
1827	1.149
1828	1.621
1829	1.6
1830	1.432
1831	1.26
1832	1.172
1833	1.096
1834	1.098
1835	1.044
1836	1.292
1837	1.222
1838	1.006
1839	1.379
1840	0.913
1841	1.185
1842	1.172
1843	1.043
1844	1.305
1845	1.142
1846	1.532
1847	0.955
1848	1.033
1849	0.695
1850	0.591
1851	0.777
1852	1.129
1853	1.349
1854	1.146
1855	1.241
1856	1.245
1857	1.089
1858	1.13
1859	1.105
1860	1.023
1861	0.803
1862	0.994
1863	1.27
1864	1.129
1865	1.118
1866	0.993
1867	1.096
1868	1.141
1869	0.963
1870	0.565
1871	0.37
1872	0.74
1873	1.034
1874	1.196
1875	1.173
1876	1.076
1877	1.11
1878	1.328
1879	0.943
1880	1.139
1881	0.804
1882	1.015
1883	1.117
1884	1.335
1885	0.722
1886	1.174
1887	1.104
1888	1.102
1889	0.881
1890	1.138
1891	0.991
1892	0.965
1893	1.149
1894	1.486
1895	0.946
1896	0.793
1897	1.094
1898	1.08
1899	0.822
1900	0.981
1901	0.801
1902	0.697
1903	1.171
1904	1.006
1905	1.4
1906	1.262
1907	1.18
1908	1.02
1909	1.036
1910	1.173
1911	1.234
1912	0.878
1913	1.287
1914	0.931
1915	1.038
1916	0.975
1917	0.584
1918	0.801
1919	0.846
1920	0.935
1921	1.273
1922	0.961
1923	0.665
1924	1.194
1925	1.182
1926	0.754
1927	0.98
1928	0.836
1929	0.929
1930	0.89
1931	0.834
1932	1.093
1933	1.075
1934	1.121
1935	0.748
1936	1.061
1937	0.775
1938	0.688
1939	0.787
1940	0.644
1941	0.516
1942	1.164
1943	0.884
1944	1.005
1945	1.162
1946	0.701
1947	1.074
1948	0.88
1949	0.923
1950	0.687
1951	0.769
1952	0.571
1953	0.889
1954	1.038
1955	0.921
1956	0.625
1957	1.145
1958	1.279
1959	1.233
1960	0.967
1961	1.022
1962	0.952
1963	0.901
1964	1.144
1965	0.933
1966	0.824
1967	1.002
1968	0.622
1969	0.963
1970	0.589
1971	0.771
1972	1.055
1973	0.682
1974	0.71
1975	0.595
1976	0.709
1977	0.867
1978	0.82
1979	0.906
1980	0.922
1981	1.116
1982	0.884
1983	1.17
1984	0.931
1985	0.703
1986	0.768
1987	0.801
1988	1.042
1989	1.007
1990	0.901
1991	1.033