# southamerica_chil009 - Caramavida - 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/3512
#
# 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_chil009 - Caramavida - 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: Caramavida
#	Location:
#	Country: Chile
#	Northernmost_Latitude: -37.68
#	Southernmost_Latitude: -37.68
#	Easternmost_Longitude: -73.17
#	Westernmost_Longitude: -73.17
#	Elevation: 900 m
#--------------------
# Data_Collection
#	Collection_Name: southamerica_chil009B
#	Earliest_Year: 1707
#	Most_Recent_Year: 1975
#	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":"6.16358344436","T2":"17.6588271468","M1":"0.0225483608288","M2":"0.294611766645"}}
#--------------------
# 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
1707	0.654
1708	0.668
1709	0.629
1710	0.549
1711	0.698
1712	0.992
1713	0.996
1714	0.924
1715	0.928
1716	0.808
1717	1.055
1718	0.911
1719	0.945
1720	0.805
1721	0.977
1722	0.947
1723	0.96
1724	0.941
1725	1.13
1726	1.053
1727	0.968
1728	0.823
1729	0.953
1730	0.858
1731	0.912
1732	1.118
1733	1.233
1734	1.054
1735	1.064
1736	0.958
1737	0.838
1738	0.905
1739	0.762
1740	0.687
1741	0.657
1742	0.625
1743	0.778
1744	0.786
1745	0.753
1746	0.899
1747	0.901
1748	1.019
1749	1.005
1750	0.845
1751	0.745
1752	0.918
1753	1.007
1754	1.037
1755	1.155
1756	1.369
1757	1.332
1758	1.444
1759	1.454
1760	1.217
1761	1.202
1762	1.265
1763	1.327
1764	1.207
1765	1.042
1766	1.089
1767	1.041
1768	1.233
1769	1.292
1770	1.297
1771	1.383
1772	1.242
1773	1.298
1774	1.26
1775	1.293
1776	1.193
1777	1.063
1778	1.125
1779	1.227
1780	1.255
1781	1.055
1782	0.953
1783	0.939
1784	1.149
1785	1.048
1786	1.144
1787	0.94
1788	0.99
1789	1.019
1790	0.955
1791	1.054
1792	1.006
1793	1.16
1794	1.191
1795	1.277
1796	1.045
1797	1.185
1798	0.982
1799	0.985
1800	1.131
1801	0.991
1802	0.933
1803	0.732
1804	1.038
1805	1.004
1806	1.126
1807	1.125
1808	1.105
1809	1.247
1810	0.98
1811	1.044
1812	0.963
1813	0.943
1814	1.166
1815	1.339
1816	1.104
1817	0.851
1818	0.764
1819	0.845
1820	0.984
1821	0.951
1822	1.054
1823	0.985
1824	1.15
1825	1.16
1826	1.062
1827	0.942
1828	0.955
1829	0.966
1830	0.91
1831	0.943
1832	0.957
1833	0.862
1834	1.007
1835	1.09
1836	0.983
1837	0.91
1838	0.737
1839	0.781
1840	1.009
1841	1.054
1842	1.156
1843	0.879
1844	0.845
1845	1.0
1846	1.101
1847	1.034
1848	1.021
1849	1.011
1850	0.835
1851	0.753
1852	0.938
1853	0.939
1854	0.921
1855	0.905
1856	0.813
1857	0.863
1858	0.781
1859	0.744
1860	0.914
1861	0.726
1862	0.902
1863	0.961
1864	1.115
1865	0.922
1866	0.866
1867	0.851
1868	0.987
1869	0.973
1870	0.994
1871	1.064
1872	1.05
1873	1.035
1874	1.001
1875	0.882
1876	0.922
1877	0.941
1878	0.712
1879	0.68
1880	0.898
1881	1.108
1882	1.119
1883	1.025
1884	1.099
1885	0.889
1886	0.908
1887	0.874
1888	0.651
1889	0.84
1890	0.815
1891	0.926
1892	0.928
1893	0.799
1894	0.807
1895	0.764
1896	0.57
1897	0.475
1898	0.841
1899	0.817
1900	0.811
1901	0.877
1902	1.017
1903	1.225
1904	1.03
1905	0.971
1906	0.869
1907	1.05
1908	0.788
1909	0.764
1910	1.111
1911	1.037
1912	0.951
1913	0.894
1914	0.965
1915	0.971
1916	1.097
1917	0.929
1918	0.756
1919	0.664
1920	0.476
1921	0.661
1922	0.817
1923	0.774
1924	0.663
1925	0.7
1926	0.784
1927	0.854
1928	0.834
1929	0.937
1930	0.728
1931	0.977
1932	1.057
1933	1.088
1934	1.111
1935	1.176
1936	1.049
1937	0.964
1938	0.971
1939	0.889
1940	0.845
1941	0.754
1942	0.912
1943	0.923
1944	1.042
1945	1.122
1946	1.253
1947	1.382
1948	1.244
1949	1.203
1950	1.054
1951	1.08
1952	0.9
1953	0.955
1954	0.919
1955	0.735
1956	0.887
1957	1.128
1958	0.986
1959	1.117
1960	0.843
1961	1.0
1962	1.051
1963	1.262
1964	1.992
1965	2.116
1966	2.121
1967	2.184
1968	2.268
1969	2.196
1970	1.909
1971	1.738
1972	1.556
1973	1.563
1974	1.474
1975	1.25
