ÃÂ¯ÃÂ»ÃÂ¿# southamerica_arge007 - Cerro Los Leones - 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/3514
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: southamerica_arge007 - Cerro Los Leones - Breitenmoser Tree Ring Chronology Data
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# 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Cerro Los Leones
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -41.08
#	Southernmost_Latitude: -41.08
#	Easternmost_Longitude: -71.15
#	Westernmost_Longitude: -71.15
#	Elevation: 1020 m
#--------------------
# Data_Collection
#	Collection_Name: southamerica_arge007B
#	Earliest_Year: 1539
#	Most_Recent_Year: 1974
#	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":"2.40501621158","T2":"12.1694399272","M1":"0.022919229718","M2":"0.596100238128"}} A negative exponential detrending approached 0, thus this dataset was alternately standardized using a 75% cutoff smoothing spline methodology in ARSTAN, following the methodology outlined in Breitenmoser 2014.
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# Species
#	Species_Name: Chilean cedar
#	Species_Code: AUCH
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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
1539	0.683
1540	0.565
1541	0.607
1542	0.698
1543	0.718
1544	0.743
1545	0.805
1546	0.821
1547	0.836
1548	0.907
1549	0.929
1550	1.115
1551	1.052
1552	1.119
1553	1.342
1554	0.894
1555	0.971
1556	0.956
1557	0.924
1558	0.99
1559	1.059
1560	0.843
1561	1.022
1562	1.144
1563	1.184
1564	1.173
1565	0.998
1566	1.23
1567	1.386
1568	1.382
1569	1.215
1570	1.119
1571	1.917
1572	1.034
1573	0.932
1574	1.186
1575	0.977
1576	1.18
1577	1.101
1578	0.645
1579	0.726
1580	0.787
1581	0.736
1582	0.601
1583	0.795
1584	1.174
1585	0.974
1586	1.126
1587	1.097
1588	0.904
1589	1.414
1590	1.327
1591	1.371
1592	1.083
1593	1.097
1594	0.92
1595	0.835
1596	1.092
1597	1.245
1598	1.124
1599	0.791
1600	1.084
1601	0.992
1602	0.949
1603	0.841
1604	0.976
1605	1.175
1606	1.222
1607	1.223
1608	0.899
1609	1.102
1610	0.997
1611	0.751
1612	0.823
1613	0.908
1614	0.868
1615	0.793
1616	0.854
1617	1.027
1618	0.985
1619	1.085
1620	0.909
1621	1.045
1622	0.872
1623	0.932
1624	0.927
1625	0.83
1626	0.897
1627	0.927
1628	0.97
1629	0.7
1630	0.986
1631	0.887
1632	0.796
1633	0.981
1634	1.033
1635	1.274
1636	1.099
1637	1.074
1638	0.948
1639	0.808
1640	0.855
1641	0.924
1642	1.041
1643	1.06
1644	0.785
1645	0.673
1646	0.598
1647	0.647
1648	0.894
1649	0.74
1650	0.905
1651	0.818
1652	1.179
1653	1.575
1654	1.318
1655	0.663
1656	1.076
1657	1.226
1658	1.328
1659	1.393
1660	1.237
1661	1.117
1662	1.144
1663	1.047
1664	0.848
1665	0.707
1666	0.849
1667	0.704
1668	0.964
1669	0.959
1670	0.867
1671	0.994
1672	0.9
1673	0.764
1674	1.106
1675	1.299
1676	0.99
1677	1.015
1678	0.973
1679	1.23
1680	1.019
1681	0.662
1682	0.358
1683	0.472
1684	0.745
1685	0.972
1686	0.742
1687	0.777
1688	0.957
1689	1.024
1690	0.937
1691	0.832
1692	1.035
1693	0.672
1694	0.845
1695	0.925
1696	0.89
1697	0.67
1698	0.803
1699	0.852
1700	0.806
1701	0.746
1702	0.845
1703	0.871
1704	1.018
1705	0.849
1706	0.599
1707	0.918
1708	0.981
1709	0.836
1710	0.72
1711	0.797
1712	0.869
1713	1.113
1714	0.732
1715	0.888
1716	0.842
1717	0.813
1718	0.75
1719	0.914
1720	1.104
1721	1.007
1722	0.958
1723	1.069
1724	1.312
1725	1.15
1726	1.25
1727	1.007
1728	1.387
1729	1.214
1730	1.004
1731	1.211
1732	1.236
1733	0.876
1734	0.994
1735	1.186
1736	0.944
1737	1.026
1738	1.07
1739	1.142
1740	1.201
1741	1.337
1742	1.367
1743	1.033
1744	1.189
1745	0.882
1746	0.834
1747	0.965
1748	1.086
1749	1.145
1750	1.272
1751	0.992
1752	0.949
1753	0.82
1754	0.82
1755	0.659
1756	1.063
1757	0.978
1758	0.881
1759	0.99
1760	1.312
1761	1.29
1762	0.713
1763	0.845
1764	1.002
1765	0.819
1766	0.926
1767	0.639
1768	0.922
1769	0.994
1770	0.634
1771	0.771
1772	0.732
1773	0.662
1774	0.901
1775	0.997
1776	1.157
1777	1.066
1778	1.045
1779	0.714
1780	0.815
1781	1.137
1782	0.894
1783	0.633
1784	0.968
1785	0.777
1786	0.845
1787	0.829
1788	1.062
1789	1.106
1790	1.53
1791	1.314
1792	1.304
1793	0.859
1794	1.12
1795	1.094
1796	1.038
1797	1.606
1798	1.528
1799	0.743
1800	0.799
1801	0.826
1802	0.874
1803	1.156
1804	1.013
1805	1.139
1806	0.803
1807	0.795
1808	1.282
1809	1.359
1810	1.151
1811	1.257
1812	1.455
1813	0.433
1814	0.796
1815	0.709
1816	1.133
1817	0.972
1818	0.751
1819	0.792
1820	0.828
1821	0.571
1822	0.634
1823	0.706
1824	0.799
1825	0.822
1826	0.829
1827	0.625
1828	0.819
1829	1.067
1830	1.244
1831	1.149
1832	1.126
1833	1.349
1834	1.37
1835	1.09
1836	1.064
1837	1.101
1838	1.072
1839	1.073
1840	1.28
1841	0.973
1842	1.059
1843	1.415
1844	1.444
1845	0.792
1846	1.042
1847	0.975
1848	1.041
1849	0.973
1850	1.086
1851	0.87
1852	1.281
1853	1.189
1854	0.871
1855	1.117
1856	1.1
1857	1.122
1858	0.925
1859	0.745
1860	0.907
1861	0.841
1862	1.008
1863	1.335
1864	1.092
1865	0.611
1866	0.764
1867	0.819
1868	1.279
1869	1.194
1870	1.06
1871	0.937
1872	1.079
1873	0.916
1874	1.131
1875	0.873
1876	1.087
1877	0.656
1878	1.129
1879	1.294
1880	1.114
1881	0.946
1882	1.019
1883	0.901
1884	1
1885	0.857
1886	0.97
1887	1.029
1888	1.184
1889	1.306
1890	1.258
1891	1.103
1892	1.169
1893	0.805
1894	0.989
1895	0.932
1896	0.758
1897	0.669
1898	1.298
1899	1.033
1900	1.05
1901	0.897
1902	0.919
1903	0.847
1904	0.913
1905	0.906
1906	0.802
1907	0.943
1908	0.504
1909	0.582
1910	0.728
1911	0.607
1912	0.599
1913	0.447
1914	0.68
1915	0.955
1916	0.956
1917	0.813
1918	1.107
1919	0.727
1920	0.955
1921	0.907
1922	0.802
1923	0.702
1924	0.63
1925	0.906
1926	1.405
1927	0.996
1928	1.235
1929	1.193
1930	1.136
1931	1.043
1932	1.024
1933	1.199
1934	1.065
1935	1.193
1936	1.047
1937	1.006
1938	1.385
1939	1.212
1940	1.502
1941	1.574
1942	1.383
1943	0.679
1944	0.754
1945	1.383
1946	1.485
1947	1.077
1948	1.306
1949	1.071
1950	0.896
1951	1.156
1952	1.114
1953	0.892
1954	1.111
1955	1.242
1956	1.039
1957	0.602
1958	0.769
1959	0.886
1960	0.897
1961	0.788
1962	0.712
1963	0.872
1964	0.974
1965	1.04
1966	1.12
1967	0.951
1968	1.008
1969	0.989
1970	0.795
1971	0.953
1972	1.001
1973	0.988
1974	1.057