# northamerica_canada_cana266 - Turtle Lake - 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/6171
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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_canada_cana266 - Turtle Lake - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
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# 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: Turtle Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 49.18
#	Southernmost_Latitude: 49.18
#	Easternmost_Longitude: -94.15
#	Westernmost_Longitude: -94.15
#	Elevation: 305 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana266B
#	Earliest_Year: 1879
#	Most_Recent_Year: 2004
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"3.33587544601","T2":"14.8783182872","M1":"0.0221529103655","M2":"0.552607070935"}}
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# Species
#	Species_Name: eastern white pine
#	Species_Code: PIST
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# Chronology:
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# Variables
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# 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
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age	trsgi
1879	1.122
1880	0.911
1881	0.994
1882	0.577
1883	0.682
1884	0.874
1885	1.136
1886	0.708
1887	1.192
1888	1.01
1889	0.768
1890	1.076
1891	1.325
1892	1.261
1893	0.975
1894	0.768
1895	1.138
1896	1.384
1897	1.15
1898	0.862
1899	1.354
1900	0.627
1901	0.953
1902	0.967
1903	0.799
1904	1.071
1905	1.109
1906	1.151
1907	0.852
1908	0.981
1909	0.741
1910	0.493
1911	0.85
1912	0.689
1913	1.033
1914	1.052
1915	0.99
1916	1.062
1917	0.966
1918	1.086
1919	0.818
1920	0.57
1921	0.948
1922	1.109
1923	1.003
1924	1.069
1925	1.233
1926	1.088
1927	1.092
1928	1.221
1929	0.522
1930	1.026
1931	0.661
1932	0.989
1933	0.677
1934	0.767
1935	0.937
1936	0.682
1937	1.165
1938	1.008
1939	0.897
1940	0.649
1941	1.029
1942	1.219
1943	1.39
1944	1.109
1945	0.977
1946	0.882
1947	0.827
1948	0.631
1949	0.899
1950	0.8
1951	0.871
1952	1.367
1953	1.073
1954	1.245
1955	1.746
1956	1.213
1957	1.266
1958	1.22
1959	1.296
1960	1.598
1961	0.717
1962	1.796
1963	1.561
1964	1.226
1965	1.402
1966	1.21
1967	1.3
1968	1.1
1969	1.69
1970	0.793
1971	1.317
1972	0.803
1973	0.81
1974	0.525
1975	1.124
1976	0.638
1977	0.855
1978	0.874
1979	0.569
1980	0.449
1981	0.817
1982	0.666
1983	0.584
1984	0.569
1985	0.626
1986	0.595
1987	0.98
1988	1.116
1989	1.247
1990	0.891
1991	0.741
1992	0.674
1993	0.998
1994	0.912
1995	0.797
1996	1.116
1997	0.701
1998	0.724
1999	0.938
2000	0.852
2001	1.129
2002	0.955
2003	1.213
2004	0.844