# southamerica_arge054 - Estancia Pulmari - 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/5161
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: southamerica_arge054 - Estancia Pulmari - 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: Estancia Pulmari
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -39.08
#	Southernmost_Latitude: -39.08
#	Easternmost_Longitude: -71.3
#	Westernmost_Longitude: -71.3
#	Elevation: 1890 m
#--------------------
# Data_Collection
#	Collection_Name: southamerica_arge054B
#	Earliest_Year: 1706
#	Most_Recent_Year: 1989
#	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":"2.33335778784","T2":"11.8073407521","M1":"0.0230746725796","M2":"0.602812648723"}}
#--------------------
# 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
1706	0.907
1707	1.041
1708	1.185
1709	1.1
1710	0.967
1711	0.925
1712	0.849
1713	0.84
1714	1.044
1715	1.212
1716	0.833
1717	0.832
1718	0.849
1719	0.808
1720	1.26
1721	0.974
1722	0.814
1723	1.024
1724	0.985
1725	1.075
1726	1.276
1727	0.877
1728	1.218
1729	1.106
1730	1.039
1731	0.982
1732	0.888
1733	0.854
1734	0.852
1735	0.725
1736	1.013
1737	0.747
1738	0.847
1739	1.038
1740	1.099
1741	0.994
1742	1.002
1743	0.651
1744	0.702
1745	0.894
1746	1.008
1747	0.948
1748	0.981
1749	1.384
1750	1.202
1751	0.914
1752	0.756
1753	0.893
1754	0.875
1755	0.849
1756	0.975
1757	1.044
1758	1.053
1759	1.077
1760	1.244
1761	1.283
1762	0.954
1763	1.034
1764	0.926
1765	0.957
1766	1.082
1767	0.698
1768	0.761
1769	0.93
1770	0.967
1771	1.021
1772	0.911
1773	0.897
1774	0.802
1775	1.04
1776	1.115
1777	1.098
1778	0.821
1779	0.848
1780	0.896
1781	1.179
1782	1.054
1783	0.941
1784	1.172
1785	1.072
1786	0.896
1787	0.795
1788	0.976
1789	0.821
1790	1.012
1791	0.989
1792	0.929
1793	1.029
1794	1.198
1795	1.099
1796	1.209
1797	1.116
1798	1.072
1799	1.029
1800	1.259
1801	0.883
1802	0.878
1803	0.974
1804	1.062
1805	0.7
1806	0.669
1807	0.673
1808	0.985
1809	0.993
1810	0.857
1811	0.849
1812	1.057
1813	0.819
1814	1.009
1815	0.995
1816	1.164
1817	1.139
1818	1.106
1819	0.884
1820	0.937
1821	0.856
1822	1.01
1823	1.206
1824	1.114
1825	0.873
1826	1.134
1827	1.026
1828	1.045
1829	1.236
1830	1.075
1831	1.01
1832	1.152
1833	1.24
1834	1.376
1835	1.243
1836	0.978
1837	1.466
1838	1.598
1839	0.866
1840	1.108
1841	0.802
1842	0.881
1843	1.092
1844	1.176
1845	0.885
1846	0.886
1847	1.038
1848	0.992
1849	1.114
1850	0.982
1851	0.869
1852	1.162
1853	0.856
1854	0.854
1855	1.039
1856	1.031
1857	1.105
1858	0.91
1859	0.537
1860	0.664
1861	0.496
1862	0.642
1863	0.696
1864	0.661
1865	0.653
1866	0.744
1867	0.699
1868	1.075
1869	0.938
1870	0.748
1871	0.69
1872	0.94
1873	0.807
1874	0.746
1875	0.46
1876	0.927
1877	0.665
1878	0.702
1879	0.711
1880	0.966
1881	0.887
1882	0.996
1883	0.903
1884	1.044
1885	0.786
1886	0.984
1887	1.008
1888	0.859
1889	0.709
1890	0.871
1891	0.932
1892	1.216
1893	0.808
1894	1.094
1895	1.227
1896	0.877
1897	0.731
1898	1.279
1899	1.053
1900	1.083
1901	1.2
1902	0.91
1903	1.15
1904	1.156
1905	0.907
1906	0.636
1907	1.109
1908	0.923
1909	0.55
1910	0.827
1911	0.77
1912	0.78
1913	0.692
1914	0.931
1915	0.995
1916	0.806
1917	0.848
1918	1.156
1919	1.017
1920	0.86
1921	0.998
1922	1.151
1923	1.274
1924	0.842
1925	1.017
1926	1.618
1927	1.311
1928	1.383
1929	1.766
1930	1.279
1931	1.25
1932	1.275
1933	1.55
1934	1.387
1935	1.295
1936	1.255
1937	0.956
1938	1.44
1939	1.324
1940	1.474
1941	1.497
1942	1.119
1943	1.023
1944	1.168
1945	1.128
1946	1.569
1947	1.156
1948	1.203
1949	0.956
1950	1.438
1951	1.599
1952	0.808
1953	0.943
1954	1.075
1955	1.01
1956	1.207
1957	0.925
1958	0.878
1959	1.015
1960	0.819
1961	1.056
1962	0.694
1963	0.974
1964	1.074
1965	0.748
1966	0.865
1967	0.699
1968	0.718
1969	0.803
1970	0.634
1971	1.129
1972	0.791
1973	0.633
1974	0.811
1975	0.897
1976	0.954
1977	0.851
1978	0.799
1979	0.974
1980	0.685
1981	0.594
1982	0.871
1983	0.945
1984	0.925
1985	0.988
1986	0.751
1987	0.916
1988	0.853
1989	1.004