# northamerica_canada_cana248 - Eva 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/6153
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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_cana248 - Eva 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
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# 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:
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#	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: Eva Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 48.72
#	Southernmost_Latitude: 48.72
#	Easternmost_Longitude: -91.17
#	Westernmost_Longitude: -91.17
#	Elevation: 424 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana248B
#	Earliest_Year: 1865
#	Most_Recent_Year: 2003
#	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":"3.6431239292","T2":"13.9748313968","M1":"0.0227890723808","M2":"0.549080902292"}}
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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
1865	0.988
1866	0.878
1867	1.037
1868	1.146
1869	1.308
1870	1.024
1871	1.15
1872	1.241
1873	1.43
1874	1.161
1875	0.968
1876	1.079
1877	1.101
1878	0.977
1879	0.834
1880	0.828
1881	0.71
1882	0.993
1883	0.701
1884	0.753
1885	1.014
1886	1.121
1887	1.085
1888	0.857
1889	0.907
1890	0.902
1891	1.086
1892	1.21
1893	0.832
1894	0.698
1895	0.61
1896	0.775
1897	0.868
1898	0.875
1899	1.03
1900	1.214
1901	0.929
1902	1.069
1903	0.988
1904	0.973
1905	1.035
1906	0.812
1907	0.843
1908	0.921
1909	0.639
1910	0.488
1911	0.64
1912	0.727
1913	0.831
1914	1.217
1915	1.191
1916	0.949
1917	1.135
1918	0.842
1919	0.681
1920	0.845
1921	0.782
1922	1.074
1923	0.947
1924	1.108
1925	1.366
1926	1.321
1927	1.13
1928	1.224
1929	1.223
1930	1.037
1931	0.906
1932	1.19
1933	0.884
1934	0.951
1935	1.243
1936	0.93
1937	1.044
1938	1.146
1939	1.343
1940	0.961
1941	1.136
1942	1.244
1943	1.056
1944	1.423
1945	1.162
1946	0.962
1947	1.012
1948	0.801
1949	1.143
1950	1.177
1951	1.05
1952	1.236
1953	1.098
1954	0.835
1955	1.098
1956	1.013
1957	1.02
1958	1.094
1959	1.067
1960	1.196
1961	1.248
1962	1.315
1963	1.078
1964	1.122
1965	1.146
1966	0.876
1967	0.92
1968	1.089
1969	1.298
1970	0.924
1971	1.063
1972	1.13
1973	0.893
1974	0.885
1975	1.111
1976	0.958
1977	0.797
1978	0.811
1979	0.835
1980	0.872
1981	0.955
1982	0.996
1983	1.124
1984	1.1
1985	0.895
1986	0.685
1987	0.642
1988	1.181
1989	1.038
1990	1.003
1991	0.99
1992	0.79
1993	0.969
1994	0.881
1995	0.781
1996	0.775
1997	0.717
1998	0.601
1999	0.801
2000	0.886
2001	0.953
2002	0.943
2003	0.959