# northamerica_canada_cana283 - Shadow 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/8585
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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_cana283 - Shadow Lake - Breitenmoser Tree Ring Chronology Data
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# 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
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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:
#--------------------
#	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: Shadow Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 62.57
#	Southernmost_Latitude: 62.57
#	Easternmost_Longitude: -114.35
#	Westernmost_Longitude: -114.35
#	Elevation: 209 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana283B
#	Earliest_Year: 1880
#	Most_Recent_Year: 2005
#	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":"5.18170361714","T2":"16.7164119439","M1":"0.0232927566031","M2":"0.446304322835"}}
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# Species
#	Species_Name: jack pine
#	Species_Code: PIBN
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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
1880	1.19
1881	0.827
1882	1.153
1883	0.925
1884	0.952
1885	1.175
1886	0.62
1887	0.694
1888	0.717
1889	1.088
1890	0.792
1891	0.955
1892	1.143
1893	0.616
1894	1.368
1895	1.108
1896	0.997
1897	1.013
1898	0.959
1899	0.975
1900	0.919
1901	0.939
1902	0.835
1903	1.198
1904	0.753
1905	1.012
1906	0.949
1907	1.306
1908	0.976
1909	1.084
1910	1.273
1911	1.295
1912	1.054
1913	1.069
1914	0.788
1915	0.655
1916	0.578
1917	0.762
1918	0.772
1919	1.233
1920	1.211
1921	1.018
1922	1.454
1923	1.176
1924	1.255
1925	0.988
1926	1.314
1927	0.523
1928	0.605
1929	1.157
1930	1.134
1931	0.926
1932	1.069
1933	1.123
1934	1.076
1935	1.028
1936	1.002
1937	0.866
1938	0.872
1939	0.862
1940	0.828
1941	1.399
1942	0.414
1943	0.691
1944	0.957
1945	0.777
1946	0.637
1947	0.75
1948	1.372
1949	0.991
1950	0.934
1951	1.669
1952	0.64
1953	0.697
1954	0.757
1955	0.922
1956	0.921
1957	1.449
1958	0.736
1959	0.86
1960	0.88
1961	1.05
1962	0.901
1963	1.326
1964	0.584
1965	0.665
1966	0.382
1967	0.254
1968	0.437
1969	0.548
1970	0.819
1971	0.306
1972	0.536
1973	0.54
1974	0.682
1975	0.004
1976	0.598
1977	0.847
1978	0.819
1979	0.992
1980	1.169
1981	1.496
1982	1.02
1983	0.905
1984	1.29
1985	1.233
1986	1.266
1987	1.484
1988	1.511
1989	1.163
1990	1.093
1991	1.342
1992	1.381
1993	0.642
1994	1.112
1995	0.367
1996	0.739
1997	0.762
1998	0.989
1999	1.024
2000	1.075
2001	1.392
2002	1.46
2003	1.54
2004	1.202
2005	1.428