ÃÂ¯ÃÂ»ÃÂ¿# southamerica_arge001 - Caviahue - 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/3513
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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_arge001 - Caviahue - 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: Caviahue
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -37.87
#	Southernmost_Latitude: -37.87
#	Easternmost_Longitude: -71.02
#	Westernmost_Longitude: -71.02
#	Elevation: 1545 m
#--------------------
# Data_Collection
#	Collection_Name: southamerica_arge001B
#	Earliest_Year: 1605
#	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":"3.11340519456","T2":"13.0936547116","M1":"0.0233510455775","M2":"0.571379309057"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1605	1.362
1606	1.367
1607	1.004
1608	0.839
1609	0.943
1610	1.129
1611	0.922
1612	0.92
1613	1.199
1614	1.143
1615	1.344
1616	1.354
1617	1.294
1618	1.228
1619	1.166
1620	1.017
1621	1.053
1622	1.033
1623	0.988
1624	0.783
1625	0.835
1626	1.188
1627	0.946
1628	1.118
1629	1.021
1630	1.107
1631	1.171
1632	0.976
1633	1.126
1634	1.026
1635	0.903
1636	1.056
1637	0.82
1638	0.931
1639	0.907
1640	0.811
1641	1.034
1642	1.035
1643	1.154
1644	0.8
1645	0.591
1646	0.889
1647	0.724
1648	0.855
1649	0.775
1650	0.989
1651	0.69
1652	1.057
1653	1.161
1654	1.06
1655	0.724
1656	0.573
1657	0.658
1658	1.019
1659	0.891
1660	0.898
1661	0.743
1662	0.544
1663	0.91
1664	0.749
1665	0.786
1666	0.711
1667	0.619
1668	0.727
1669	0.694
1670	0.752
1671	0.581
1672	0.634
1673	0.861
1674	1.006
1675	0.651
1676	0.771
1677	0.8
1678	0.894
1679	0.637
1680	0.412
1681	0.361
1682	0.336
1683	0.49
1684	0.551
1685	0.463
1686	0.502
1687	0.626
1688	0.568
1689	0.766
1690	0.749
1691	0.795
1692	0.743
1693	0.762
1694	0.988
1695	0.749
1696	0.585
1697	0.546
1698	0.734
1699	0.68
1700	1.19
1701	1.157
1702	1.152
1703	1.144
1704	1.059
1705	0.986
1706	1.113
1707	1.007
1708	1.159
1709	1.062
1710	0.882
1711	0.946
1712	1.0
1713	0.967
1714	0.967
1715	1.002
1716	0.847
1717	0.999
1718	0.875
1719	0.717
1720	1.251
1721	1.214
1722	1.058
1723	1.16
1724	1.155
1725	1.224
1726	1.036
1727	0.856
1728	0.864
1729	0.87
1730	0.962
1731	1.028
1732	0.983
1733	0.986
1734	0.981
1735	0.9
1736	0.994
1737	0.595
1738	1.025
1739	1.225
1740	1.276
1741	1.157
1742	1.215
1743	0.687
1744	0.742
1745	1.004
1746	1.081
1747	0.978
1748	1.207
1749	1.687
1750	1.294
1751	0.856
1752	0.911
1753	1.028
1754	0.988
1755	0.963
1756	1.02
1757	1.058
1758	1.13
1759	1.02
1760	1.154
1761	1.138
1762	0.97
1763	0.904
1764	0.821
1765	0.96
1766	0.983
1767	0.746
1768	0.553
1769	0.936
1770	0.842
1771	0.901
1772	0.662
1773	0.758
1774	0.869
1775	0.837
1776	0.763
1777	0.585
1778	0.89
1779	0.662
1780	0.769
1781	1.051
1782	0.969
1783	0.764
1784	1.043
1785	0.745
1786	0.725
1787	0.707
1788	0.876
1789	0.789
1790	0.957
1791	0.986
1792	0.837
1793	0.766
1794	0.971
1795	0.916
1796	1.219
1797	1.275
1798	1.319
1799	1.061
1800	1.246
1801	0.844
1802	0.981
1803	1.138
1804	1.28
1805	1.071
1806	0.982
1807	0.868
1808	0.927
1809	1.297
1810	1.258
1811	1.02
1812	1.109
1813	0.837
1814	1.137
1815	1.277
1816	1.168
1817	1.022
1818	0.932
1819	0.917
1820	1.075
1821	1.125
1822	1.267
1823	1.15
1824	1.171
1825	1.011
1826	1.005
1827	0.932
1828	1.435
1829	1.428
1830	1.328
1831	1.333
1832	1.323
1833	1.224
1834	1.246
1835	1.077
1836	0.8
1837	1.167
1838	1.248
1839	0.793
1840	0.961
1841	0.835
1842	0.803
1843	0.881
1844	0.882
1845	0.808
1846	0.834
1847	0.544
1848	0.531
1849	0.717
1850	0.749
1851	0.746
1852	0.725
1853	0.487
1854	0.568
1855	0.653
1856	0.609
1857	0.553
1858	0.556
1859	0.51
1860	0.509
1861	0.409
1862	0.632
1863	0.677
1864	0.827
1865	0.855
1866	0.83
1867	0.608
1868	0.858
1869	0.741
1870	0.63
1871	0.419
1872	0.649
1873	0.557
1874	0.582
1875	0.376
1876	0.797
1877	0.559
1878	0.705
1879	0.634
1880	1.0
1881	0.928
1882	0.841
1883	0.727
1884	0.787
1885	0.597
1886	0.905
1887	0.914
1888	0.697
1889	0.559
1890	0.614
1891	0.679
1892	0.732
1893	0.551
1894	0.662
1895	0.772
1896	0.871
1897	0.614
1898	1.061
1899	1.164
1900	1.256
1901	1.252
1902	1.498
1903	2.3
1904	2.362
1905	1.679
1906	1.345
1907	1.382
1908	1.189
1909	1.001
1910	1.566
1911	1.363
1912	1.24
1913	1.137
1914	1.306
1915	1.28
1916	1.124
1917	1.0
1918	1.169
1919	1.046
1920	0.932
1921	0.986
1922	1.085
1923	1.102
1924	0.857
1925	1.23
1926	1.342
1927	1.111
1928	1.371
1929	1.577
1930	1.245
1931	1.654
1932	1.367
1933	1.53
1934	1.232
1935	1.014
1936	0.881
1937	0.736
1938	1.133
1939	1.04
1940	1.043
1941	1.069
1942	0.878
1943	0.905
1944	1.172
1945	0.821
1946	1.065
1947	0.912
1948	1.327
1949	0.936
1950	1.196
1951	1.261
1952	0.869
1953	1.181
1954	1.144
1955	0.76
1956	1.16
1957	0.959
1958	0.726
1959	0.859
1960	0.748
1961	1.148
1962	0.703
1963	1.197
1964	1.527
1965	1.309
1966	1.131
1967	1.045
1968	1.064
1969	1.181
1970	0.651
1971	1.309
1972	0.884
1973	0.958
1974	1.243