# northamerica_canada_cana209 - Eyeglass Lake - 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.
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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/2920
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# 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: northamerica_canada_cana209 - Eyeglass Lake - 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: Eyeglass Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 57.92
#	Southernmost_Latitude: 57.92
#	Easternmost_Longitude: -61.6
#	Westernmost_Longitude: -61.6
#	Elevation: 100 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana209B
#	Earliest_Year: 1782
#	Most_Recent_Year: 2001
#	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":"5.09880520397","T2":"17.1975878822","M1":"0.0221913663257","M2":"0.385441787442"}}
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# Species
#	Species_Name: white spruce
#	Species_Code: PCGL
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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)
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##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
1782	1.317
1783	1.595
1784	1.099
1785	1.04
1786	0.731
1787	0.929
1788	1.129
1789	0.875
1790	1.147
1791	0.936
1792	1.031
1793	0.895
1794	0.773
1795	0.891
1796	1.087
1797	1.412
1798	0.971
1799	1.02
1800	0.666
1801	0.951
1802	1.016
1803	0.732
1804	0.797
1805	1.085
1806	1.055
1807	1.009
1808	1.246
1809	1.159
1810	1.421
1811	1.175
1812	1.224
1813	1.302
1814	1.363
1815	1.347
1816	1.055
1817	0.595
1818	0.531
1819	0.617
1820	0.593
1821	0.705
1822	0.71
1823	0.715
1824	0.893
1825	0.704
1826	1.048
1827	0.834
1828	0.865
1829	0.768
1830	1.291
1831	0.955
1832	1.02
1833	1.039
1834	1.044
1835	0.556
1836	0.477
1837	0.511
1838	0.815
1839	0.707
1840	0.664
1841	0.771
1842	0.864
1843	0.926
1844	0.809
1845	0.765
1846	0.792
1847	0.765
1848	0.933
1849	1.137
1850	1.351
1851	1.293
1852	1.113
1853	1.331
1854	1.219
1855	1.005
1856	1.121
1857	1.014
1858	1.151
1859	1.052
1860	1.15
1861	1.218
1862	0.784
1863	0.964
1864	0.914
1865	0.675
1866	0.683
1867	0.681
1868	0.984
1869	0.823
1870	0.861
1871	0.97
1872	0.507
1873	0.806
1874	0.939
1875	0.825
1876	0.76
1877	0.766
1878	1.115
1879	0.942
1880	1.367
1881	1.399
1882	0.946
1883	1.18
1884	0.8
1885	1.044
1886	0.782
1887	0.65
1888	0.732
1889	0.979
1890	0.64
1891	0.76
1892	0.618
1893	0.659
1894	0.607
1895	0.961
1896	0.829
1897	1.175
1898	0.769
1899	0.648
1900	0.64
1901	0.802
1902	0.75
1903	0.963
1904	1.295
1905	0.66
1906	1.042
1907	0.922
1908	0.954
1909	0.899
1910	0.771
1911	1.495
1912	1.005
1913	0.983
1914	1.014
1915	0.791
1916	1.022
1917	0.869
1918	0.739
1919	0.897
1920	0.936
1921	0.972
1922	0.987
1923	1.092
1924	0.966
1925	1.034
1926	1.157
1927	1.208
1928	1.082
1929	0.671
1930	1.26
1931	0.912
1932	0.568
1933	1.064
1934	1.035
1935	1.39
1936	0.847
1937	0.995
1938	1.076
1939	1.104
1940	0.755
1941	0.84
1942	1.096
1943	1.173
1944	1.179
1945	1.255
1946	1.508
1947	1.309
1948	1.376
1949	1.23
1950	1.272
1951	1.686
1952	1.246
1953	0.775
1954	1.433
1955	1.402
1956	1.274
1957	1.216
1958	1.097
1959	1.146
1960	0.799
1961	1.086
1962	1.163
1963	0.935
1964	1.112
1965	0.954
1966	0.941
1967	1.352
1968	1.149
1969	1.437
1970	1.495
1971	0.877
1972	1.082
1973	1.047
1974	0.825
1975	0.906
1976	0.935
1977	0.863
1978	0.774
1979	0.778
1980	0.811
1981	0.862
1982	0.932
1983	1.167
1984	1.184
1985	1.404
1986	0.665
1987	0.886
1988	0.901
1989	1.283
1990	1.051
1991	0.86
1992	0.914
1993	1.249
1994	1.007
1995	1.054
1996	0.61
1997	0.758
1998	0.797
1999	0.902
2000	0.824
2001	0.783