# southamerica_arge013 - Lonco Luan - 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:
#
# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
#
# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/3542
#
# 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_arge013 - Lonco Luan - 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.
#------------------
# 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
#------------------
# Site_Information
#	Site_Name: Lonco Luan
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -38.98
#	Southernmost_Latitude: -38.98
#	Easternmost_Longitude: -71.05
#	Westernmost_Longitude: -71.05
#	Elevation: 1110 m
#--------------------
# Data_Collection
#	Collection_Name: southamerica_arge013B
#	Earliest_Year: 1610
#	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":"3.0252133278","T2":"13.5250363394","M1":"0.022656679548","M2":"0.524470493029"}}
#--------------------
# Species
#	Species_Name: monkey puzzle
#	Species_Code: ARAR
#--------------------
# Chronology:
#
#
#
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1610	1.038
1611	1.15
1612	0.808
1613	0.884
1614	0.788
1615	0.751
1616	0.802
1617	0.846
1618	1.06
1619	1.532
1620	1.46
1621	1.416
1622	1.146
1623	1.127
1624	0.986
1625	0.828
1626	1.302
1627	1.089
1628	1.268
1629	0.91
1630	1.002
1631	1.069
1632	1.082
1633	1.28
1634	1.361
1635	1.307
1636	1.455
1637	1.062
1638	1.157
1639	1.341
1640	1.022
1641	1.062
1642	1.114
1643	1.111
1644	0.984
1645	0.983
1646	1.169
1647	1.383
1648	1.37
1649	1.214
1650	1.351
1651	0.763
1652	1.011
1653	1.206
1654	1.039
1655	0.629
1656	0.684
1657	0.806
1658	0.644
1659	0.689
1660	0.8
1661	0.457
1662	0.423
1663	0.684
1664	0.658
1665	0.497
1666	0.639
1667	0.721
1668	0.766
1669	0.627
1670	0.639
1671	0.747
1672	0.887
1673	0.797
1674	0.717
1675	0.857
1676	0.856
1677	0.678
1678	1.125
1679	1.209
1680	1.159
1681	1.023
1682	0.845
1683	1.273
1684	1.137
1685	1.189
1686	0.806
1687	0.888
1688	0.919
1689	0.74
1690	0.584
1691	0.812
1692	0.822
1693	0.826
1694	1.284
1695	1.192
1696	0.949
1697	0.918
1698	0.94
1699	0.826
1700	0.958
1701	1.052
1702	1.033
1703	1.128
1704	1.049
1705	0.945
1706	0.856
1707	1.019
1708	1.13
1709	1.167
1710	1.105
1711	1.056
1712	0.856
1713	0.974
1714	0.944
1715	1.071
1716	0.933
1717	0.962
1718	1.047
1719	0.758
1720	1.071
1721	0.747
1722	0.878
1723	0.997
1724	0.965
1725	0.952
1726	1.029
1727	0.922
1728	1.198
1729	1.108
1730	0.991
1731	1.093
1732	0.994
1733	1.001
1734	0.922
1735	0.873
1736	1.138
1737	0.814
1738	0.892
1739	1.116
1740	1.21
1741	0.964
1742	1.034
1743	0.503
1744	0.74
1745	0.779
1746	0.939
1747	0.958
1748	0.819
1749	1.25
1750	1.127
1751	0.783
1752	0.862
1753	0.928
1754	1.086
1755	1.028
1756	0.947
1757	0.892
1758	1.107
1759	1.224
1760	1.206
1761	1.387
1762	0.964
1763	1.015
1764	1.051
1765	1.279
1766	1.242
1767	1.03
1768	0.981
1769	1.242
1770	1.109
1771	1.227
1772	0.986
1773	1.022
1774	0.907
1775	0.798
1776	0.859
1777	0.729
1778	0.775
1779	0.736
1780	0.763
1781	0.967
1782	0.812
1783	0.752
1784	0.964
1785	0.804
1786	0.745
1787	0.674
1788	1.075
1789	0.894
1790	1.059
1791	0.952
1792	0.782
1793	0.974
1794	1.159
1795	0.918
1796	1.174
1797	1.017
1798	0.953
1799	1.036
1800	1.102
1801	0.662
1802	0.74
1803	0.673
1804	0.81
1805	0.72
1806	0.898
1807	0.842
1808	0.893
1809	1.008
1810	0.815
1811	0.699
1812	0.843
1813	0.703
1814	0.902
1815	0.833
1816	0.952
1817	0.868
1818	0.731
1819	0.656
1820	0.861
1821	0.847
1822	0.83
1823	0.941
1824	0.968
1825	0.865
1826	0.979
1827	0.945
1828	1.02
1829	1.0
1830	1.001
1831	1.03
1832	1.127
1833	1.174
1834	1.152
1835	0.994
1836	0.943
1837	1.201
1838	1.323
1839	0.856
1840	1.152
1841	0.833
1842	0.774
1843	0.881
1844	0.857
1845	0.877
1846	0.96
1847	1.001
1848	0.98
1849	1.073
1850	1.08
1851	1.114
1852	1.305
1853	1.001
1854	1.004
1855	1.155
1856	1.243
1857	1.237
1858	1.065
1859	0.753
1860	0.935
1861	0.801
1862	0.815
1863	0.902
1864	0.893
1865	0.704
1866	0.947
1867	0.903
1868	1.318
1869	0.872
1870	0.835
1871	0.782
1872	0.989
1873	0.93
1874	0.792
1875	0.49
1876	1.077
1877	0.863
1878	0.865
1879	0.687
1880	0.989
1881	1.025
1882	1.017
1883	1.129
1884	1.268
1885	0.985
1886	0.973
1887	0.977
1888	0.795
1889	0.696
1890	0.722
1891	0.708
1892	0.891
1893	0.587
1894	0.824
1895	0.87
1896	0.851
1897	0.521
1898	0.918
1899	0.928
1900	0.904
1901	0.857
1902	0.653
1903	0.821
1904	0.864
1905	0.75
1906	0.616
1907	0.943
1908	0.863
1909	0.631
1910	0.847
1911	0.72
1912	0.847
1913	0.903
1914	1.029
1915	1.023
1916	0.997
1917	0.85
1918	1.069
1919	1.089
1920	0.97
1921	1.139
1922	1.23
1923	1.361
1924	1.101
1925	1.266
1926	1.365
1927	1.066
1928	1.206
1929	1.299
1930	1.077
1931	1.119
1932	1.094
1933	1.26
1934	1.286
1935	1.251
1936	0.895
1937	0.793
1938	1.422
1939	1.364
1940	1.606
1941	1.336
1942	1.055
1943	0.966
1944	0.993
1945	1.051
1946	1.487
1947	1.095
1948	1.019
1949	0.969
1950	1.22
1951	1.647
1952	0.998
1953	0.946
1954	1.007
1955	1.023
1956	1.219
1957	0.841
1958	0.889
1959	1.125
1960	1.03
1961	1.339
1962	0.863
1963	1.097
1964	1.262
1965	1.042
1966	0.921
1967	0.671
1968	0.962
1969	1.124
1970	0.838
1971	1.297
1972	0.888
1973	0.787
1974	0.99