# northamerica_canada_cana204 - MacIntyre 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/2727
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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_cana204 - MacIntyre 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:
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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: MacIntyre Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 57.42
#	Southernmost_Latitude: 57.42
#	Easternmost_Longitude: -106.13
#	Westernmost_Longitude: -106.13
#	Elevation: 500 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana204B
#	Earliest_Year: 1874
#	Most_Recent_Year: 2002
#	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":"4.24838948203","T2":"15.5360389032","M1":"0.022969018415","M2":"0.517755393408"}}
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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
1874	0.851
1875	0.72
1876	0.944
1877	0.776
1878	0.88
1879	0.961
1880	1.048
1881	1.101
1882	1.098
1883	1.154
1884	1.091
1885	1.102
1886	0.966
1887	0.888
1888	0.874
1889	1.041
1890	0.83
1891	0.78
1892	0.976
1893	1.131
1894	1.028
1895	1.047
1896	1.037
1897	0.982
1898	1.04
1899	0.812
1900	0.773
1901	0.792
1902	0.758
1903	0.605
1904	0.701
1905	0.832
1906	0.893
1907	0.887
1908	0.808
1909	0.962
1910	1.113
1911	1.246
1912	0.959
1913	0.992
1914	1.165
1915	1.085
1916	0.948
1917	0.964
1918	1.077
1919	1.186
1920	0.978
1921	1.134
1922	1.24
1923	1.085
1924	1.121
1925	1.306
1926	1.357
1927	1.188
1928	1.02
1929	1.248
1930	1.011
1931	1.047
1932	1.159
1933	1.064
1934	0.926
1935	1.091
1936	1.109
1937	1.006
1938	1.009
1939	0.834
1940	0.931
1941	0.941
1942	0.646
1943	0.853
1944	0.946
1945	1.043
1946	0.734
1947	0.701
1948	0.857
1949	0.822
1950	0.884
1951	0.911
1952	0.726
1953	0.99
1954	1.096
1955	0.796
1956	0.913
1957	1.244
1958	1.264
1959	1.102
1960	1.148
1961	1.114
1962	1.068
1963	1.362
1964	1.59
1965	1.636
1966	1.376
1967	1.229
1968	1.07
1969	1.234
1970	1.129
1971	0.983
1972	0.867
1973	0.593
1974	0.736
1975	0.855
1976	0.928
1977	0.96
1978	0.91
1979	0.902
1980	0.844
1981	0.861
1982	0.633
1983	0.683
1984	0.888
1985	0.883
1986	1.065
1987	1.08
1988	0.859
1989	0.776
1990	0.813
1991	0.831
1992	0.962
1993	0.983
1994	1.049
1995	0.712
1996	0.693
1997	0.838
1998	0.951
1999	1.049
2000	1.171
2001	1.158
2002	0.893