# southamerica_arge039 - Glaciar Frias - 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/5165
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: southamerica_arge039 - Glaciar Frias - 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: Glaciar Frias
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -41.17
#	Southernmost_Latitude: -41.17
#	Easternmost_Longitude: -71.93
#	Westernmost_Longitude: -71.93
#	Elevation: 1200 m
#--------------------
# Data_Collection
#	Collection_Name: southamerica_arge039B
#	Earliest_Year: 1763
#	Most_Recent_Year: 1985
#	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":"6.09394298572","T2":"13.9455502038","M1":"0.0221191357408","M2":"0.446060395496"}}
#--------------------
# Species
#	Species_Name: lenga nothofagus
#	Species_Code: NOPU
#--------------------
# 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
1763	1.244
1764	1.64
1765	1.096
1766	0.956
1767	0.984
1768	1.112
1769	0.844
1770	0.415
1771	1.011
1772	1.206
1773	1.068
1774	0.912
1775	0.953
1776	1.104
1777	0.85
1778	1.026
1779	0.816
1780	0.806
1781	1.389
1782	1.203
1783	1.149
1784	1.031
1785	0.683
1786	0.965
1787	0.846
1788	0.557
1789	0.808
1790	0.467
1791	0.38
1792	0.497
1793	0.051
1794	0.585
1795	0.751
1796	0.66
1797	0.788
1798	0.689
1799	0.896
1800	0.82
1801	0.733
1802	0.811
1803	0.442
1804	1.229
1805	1.154
1806	1.255
1807	1.519
1808	1.193
1809	0.403
1810	0.693
1811	0.67
1812	0.919
1813	0.846
1814	0.403
1815	0.894
1816	1.052
1817	1.312
1818	0.788
1819	1.203
1820	0.569
1821	0.277
1822	1.199
1823	0.957
1824	1.145
1825	1.306
1826	1.022
1827	1.249
1828	1.571
1829	1.622
1830	1.349
1831	1.208
1832	0.726
1833	0.664
1834	0.617
1835	0.219
1836	0.221
1837	0.255
1838	0.487
1839	0.827
1840	0.645
1841	1.2
1842	0.939
1843	0.772
1844	0.901
1845	1.318
1846	1.478
1847	0.865
1848	1.043
1849	0.685
1850	0.576
1851	0.959
1852	1.336
1853	1.18
1854	0.808
1855	1.066
1856	0.911
1857	0.988
1858	1.086
1859	1.005
1860	1.256
1861	1.057
1862	1.257
1863	1.335
1864	1.545
1865	1.486
1866	1.267
1867	0.986
1868	1.134
1869	1.182
1870	0.858
1871	0.529
1872	0.64
1873	0.96
1874	1.093
1875	0.991
1876	1.65
1877	1.449
1878	1.503
1879	1.208
1880	1.729
1881	0.999
1882	1.147
1883	1.098
1884	1.246
1885	0.629
1886	1.338
1887	1.136
1888	1.139
1889	1.211
1890	0.635
1891	0.813
1892	1.016
1893	1.454
1894	1.416
1895	1.144
1896	1.04
1897	1.133
1898	1.109
1899	0.884
1900	0.89
1901	0.952
1902	0.87
1903	1.339
1904	0.943
1905	1.501
1906	1.38
1907	1.181
1908	1.096
1909	0.808
1910	1.002
1911	0.869
1912	0.527
1913	1.089
1914	0.706
1915	0.845
1916	0.99
1917	0.58
1918	0.632
1919	0.936
1920	0.878
1921	1.232
1922	1.086
1923	0.999
1924	1.294
1925	1.133
1926	0.551
1927	1.007
1928	0.767
1929	0.911
1930	0.82
1931	0.875
1932	1.074
1933	1.056
1934	1.203
1935	0.804
1936	0.839
1937	0.851
1938	0.71
1939	0.928
1940	0.817
1941	0.502
1942	1.414
1943	0.895
1944	0.799
1945	0.796
1946	0.558
1947	0.656
1948	0.403
1949	0.406
1950	0.304
1951	0.688
1952	0.587
1953	1.008
1954	0.961
1955	1.018
1956	0.978
1957	1.145
1958	1.104
1959	1.314
1960	0.913
1961	1.111
1962	0.764
1963	0.944
1964	1.228
1965	1.002
1966	0.78
1967	1.136
1968	0.742
1969	1.043
1970	0.553
1971	0.652
1972	1.168
1973	0.973
1974	1.002
1975	0.858
1976	0.972
1977	1.13
1978	1.076
1979	0.93
1980	1.062
1981	0.993
1982	0.888
1983	1.116
1984	0.741
1985	0.582