# southamerica_arge061 - Rio Pipo - 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.
#
#
# 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/2786
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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_arge061 - Rio Pipo - 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: Rio Pipo
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -54.78
#	Southernmost_Latitude: -54.78
#	Easternmost_Longitude: -68.47
#	Westernmost_Longitude: -68.47
#	Elevation: 50 m
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# Data_Collection
#	Collection_Name: southamerica_arge061B
#	Earliest_Year: 1724
#	Most_Recent_Year: 1984
#	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":"3.84792158613","T2":"17.6755659835","M1":"0.0229452107778","M2":"0.381998955071"}}
#--------------------
# 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
1724	1.287
1725	1.051
1726	1.145
1727	0.996
1728	1.223
1729	0.705
1730	0.677
1731	0.832
1732	0.652
1733	0.693
1734	0.74
1735	0.964
1736	0.926
1737	1.204
1738	1.095
1739	1.174
1740	1.157
1741	1.062
1742	0.962
1743	0.808
1744	0.745
1745	0.781
1746	1.032
1747	0.967
1748	1.178
1749	0.877
1750	0.971
1751	0.76
1752	0.785
1753	0.772
1754	1.007
1755	0.938
1756	1.083
1757	1.05
1758	0.909
1759	1.043
1760	1.202
1761	0.962
1762	0.918
1763	1.17
1764	1.182
1765	1.107
1766	1.083
1767	0.953
1768	0.588
1769	0.608
1770	0.96
1771	1.071
1772	0.953
1773	0.773
1774	0.762
1775	0.533
1776	0.858
1777	0.916
1778	0.957
1779	0.992
1780	0.869
1781	0.864
1782	0.735
1783	0.758
1784	0.804
1785	0.813
1786	1.003
1787	1.028
1788	1.04
1789	0.859
1790	1.15
1791	1.049
1792	1.153
1793	1.049
1794	0.801
1795	0.917
1796	1.087
1797	0.917
1798	0.874
1799	0.8
1800	1.002
1801	0.966
1802	1.336
1803	1.102
1804	1.06
1805	1.387
1806	1.051
1807	1.162
1808	1.247
1809	1.011
1810	1.07
1811	1.329
1812	0.742
1813	1.064
1814	1.023
1815	0.991
1816	1.024
1817	0.853
1818	0.776
1819	0.63
1820	0.782
1821	0.754
1822	1.078
1823	0.862
1824	1.075
1825	1.027
1826	1.278
1827	1.433
1828	1.278
1829	1.254
1830	1.332
1831	1.164
1832	0.934
1833	0.883
1834	1.021
1835	0.969
1836	0.826
1837	0.963
1838	0.806
1839	1.118
1840	1.025
1841	0.936
1842	0.778
1843	0.607
1844	0.479
1845	0.682
1846	1.072
1847	1.301
1848	1.109
1849	1.231
1850	0.81
1851	0.895
1852	0.94
1853	0.94
1854	0.944
1855	0.524
1856	0.712
1857	0.863
1858	0.796
1859	0.345
1860	0.931
1861	0.758
1862	1.176
1863	1.09
1864	0.945
1865	0.703
1866	0.827
1867	1.072
1868	1.132
1869	1.219
1870	1.011
1871	0.914
1872	1.025
1873	1.014
1874	1.015
1875	1.106
1876	0.825
1877	0.992
1878	0.731
1879	0.764
1880	0.94
1881	1.005
1882	1.04
1883	0.849
1884	0.906
1885	0.875
1886	0.766
1887	0.603
1888	0.661
1889	0.994
1890	0.827
1891	0.877
1892	0.906
1893	1.161
1894	1.261
1895	1.232
1896	1.338
1897	1.302
1898	1.141
1899	0.494
1900	0.661
1901	0.855
1902	1.234
1903	0.95
1904	1.117
1905	0.527
1906	0.763
1907	0.886
1908	0.981
1909	1.313
1910	1.134
1911	1.11
1912	0.99
1913	0.678
1914	0.819
1915	1.15
1916	1.249
1917	1.071
1918	0.969
1919	1.132
1920	1.211
1921	1.19
1922	1.095
1923	1.129
1924	1.08
1925	1.063
1926	0.925
1927	1.211
1928	1.277
1929	1.293
1930	0.895
1931	1.075
1932	0.712
1933	0.747
1934	0.543
1935	0.804
1936	0.711
1937	0.739
1938	0.571
1939	0.734
1940	1.061
1941	1.189
1942	0.879
1943	0.731
1944	0.762
1945	0.822
1946	0.69
1947	0.684
1948	0.73
1949	0.855
1950	0.925
1951	0.76
1952	0.841
1953	0.983
1954	1.008
1955	0.855
1956	1.249
1957	1.273
1958	1.131
1959	1.122
1960	0.987
1961	0.596
1962	0.679
1963	0.713
1964	0.853
1965	0.885
1966	0.844
1967	0.924
1968	1.017
1969	1.021
1970	0.803
1971	0.889
1972	0.781
1973	0.663
1974	0.753
1975	0.574
1976	0.553
1977	0.586
1978	0.864
1979	0.97
1980	0.883
1981	1.016
1982	1.243
1983	1.231
1984	1.096