# northamerica_usa_ny014 - Winch Pond Adirondack Mountains - 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/3039
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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
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# Title
#	Study_Name: northamerica_usa_ny014 - Winch Pond Adirondack Mountains - 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.
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#	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: Winch Pond Adirondack Mountains
#	Location:
#	Country: United States
#	Northernmost_Latitude: 44.33
#	Southernmost_Latitude: 44.33
#	Easternmost_Longitude: -73.88
#	Westernmost_Longitude: -73.88
#	Elevation: 750 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ny014B
#	Earliest_Year: 1732
#	Most_Recent_Year: 1978
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.78836999468","T2":"15.1825246917","M1":"0.0223690260147","M2":"0.364394804127"}}
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# Species
#	Species_Name: eastern white pine
#	Species_Code: PIST
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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
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# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1732	1.25
1733	0.867
1734	0.778
1735	0.829
1736	0.616
1737	0.649
1738	0.661
1739	0.822
1740	0.874
1741	0.943
1742	1.043
1743	1.148
1744	1.023
1745	0.912
1746	0.878
1747	0.93
1748	0.982
1749	1.226
1750	1.282
1751	1.321
1752	1.154
1753	1.309
1754	1.484
1755	1.517
1756	1.504
1757	1.414
1758	1.146
1759	1.103
1760	1.011
1761	0.91
1762	0.707
1763	0.869
1764	0.905
1765	1.004
1766	1.011
1767	1.02
1768	0.95
1769	1.014
1770	1.002
1771	0.82
1772	0.693
1773	0.81
1774	0.99
1775	1.105
1776	1.059
1777	1.111
1778	0.993
1779	1.001
1780	1.139
1781	1.17
1782	1.032
1783	0.988
1784	1.2
1785	1.046
1786	0.936
1787	0.863
1788	0.842
1789	0.806
1790	0.67
1791	0.626
1792	0.674
1793	0.818
1794	1.044
1795	1.034
1796	1.129
1797	1.033
1798	1.185
1799	1.14
1800	1.198
1801	1.118
1802	1.42
1803	1.333
1804	1.166
1805	1.0
1806	1.121
1807	1.165
1808	1.137
1809	1.014
1810	1.012
1811	0.951
1812	0.944
1813	0.923
1814	0.971
1815	1.086
1816	1.086
1817	1.064
1818	0.863
1819	1.08
1820	0.982
1821	1.052
1822	1.125
1823	1.059
1824	0.937
1825	1.11
1826	1.083
1827	0.964
1828	1.082
1829	1.106
1830	1.059
1831	0.984
1832	0.981
1833	0.923
1834	0.923
1835	0.841
1836	0.712
1837	0.698
1838	0.65
1839	0.612
1840	0.443
1841	0.609
1842	0.675
1843	0.892
1844	0.822
1845	0.982
1846	0.996
1847	0.795
1848	0.869
1849	0.729
1850	0.708
1851	0.813
1852	0.764
1853	0.96
1854	0.853
1855	0.98
1856	1.071
1857	1.022
1858	0.951
1859	0.754
1860	0.837
1861	0.737
1862	0.747
1863	0.782
1864	0.783
1865	0.901
1866	0.955
1867	0.923
1868	0.837
1869	0.982
1870	1.076
1871	1.021
1872	0.984
1873	1.009
1874	0.892
1875	0.966
1876	0.693
1877	0.867
1878	0.864
1879	0.794
1880	0.859
1881	0.761
1882	0.756
1883	0.685
1884	0.727
1885	0.963
1886	1.077
1887	0.935
1888	0.894
1889	0.936
1890	0.865
1891	0.865
1892	0.892
1893	1.034
1894	1.062
1895	1.064
1896	1.367
1897	1.046
1898	1.104
1899	1.05
1900	1.116
1901	0.912
1902	0.871
1903	1.079
1904	1.34
1905	1.082
1906	0.965
1907	0.881
1908	0.965
1909	0.995
1910	1.108
1911	1.061
1912	1.134
1913	1.284
1914	1.197
1915	1.248
1916	1.233
1917	1.027
1918	0.959
1919	0.739
1920	0.829
1921	0.907
1922	1.141
1923	0.988
1924	0.999
1925	0.9
1926	0.972
1927	1.085
1928	0.927
1929	0.752
1930	0.91
1931	1.068
1932	1.296
1933	1.398
1934	1.432
1935	1.314
1936	1.224
1937	0.965
1938	0.959
1939	1.06
1940	1.08
1941	1.158
1942	1.217
1943	0.714
1944	0.826
1945	0.969
1946	0.878
1947	0.938
1948	0.757
1949	1.074
1950	1.166
1951	1.162
1952	1.022
1953	1.332
1954	1.131
1955	1.255
1956	0.999
1957	1.08
1958	1.262
1959	1.252
1960	1.065
1961	1.196
1962	1.078
1963	0.774
1964	0.942
1965	1.064
1966	0.964
1967	0.92
1968	1.015
1969	0.885
1970	0.71
1971	0.85
1972	0.788
1973	0.96
1974	1.059
1975	1.137
1976	0.902
1977	1.039
1978	1.031