# northamerica_canada_cana009 - Wolverine Plateau - 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/3487
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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_cana009 - Wolverine Plateau - 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: Wolverine Plateau
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 61.5
#	Southernmost_Latitude: 61.5
#	Easternmost_Longitude: -140.72
#	Westernmost_Longitude: -140.72
#	Elevation: 1370 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana009B
#	Earliest_Year: 1830
#	Most_Recent_Year: 1975
#	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":"5.08027113484","T2":"17.1338182175","M1":"0.023009695382","M2":"0.401856736016"}}
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# Species
#	Species_Name: white spruce
#	Species_Code: PCGL
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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
1830	0.637
1831	0.839
1832	0.825
1833	0.98
1834	0.883
1835	0.73
1836	1.028
1837	0.909
1838	1.158
1839	0.999
1840	1.14
1841	1.132
1842	1.024
1843	0.95
1844	1.391
1845	1.013
1846	1.128
1847	1.077
1848	1.43
1849	0.939
1850	0.979
1851	0.981
1852	1.544
1853	1.25
1854	1.316
1855	1.608
1856	1.191
1857	1.391
1858	1.496
1859	1.439
1860	1.418
1861	1.143
1862	1.368
1863	1.286
1864	1.181
1865	1.106
1866	0.995
1867	1.036
1868	0.968
1869	0.83
1870	0.786
1871	0.799
1872	0.631
1873	0.75
1874	0.693
1875	0.822
1876	1.085
1877	0.901
1878	0.909
1879	0.983
1880	0.815
1881	0.987
1882	1.111
1883	0.937
1884	1.041
1885	0.998
1886	1.084
1887	0.743
1888	1.07
1889	0.959
1890	1.176
1891	1.204
1892	1.217
1893	1.136
1894	1.249
1895	0.985
1896	1.175
1897	1.255
1898	1.295
1899	1.255
1900	1.02
1901	1.096
1902	1.184
1903	1.108
1904	0.545
1905	1.161
1906	0.761
1907	0.971
1908	0.895
1909	0.82
1910	0.739
1911	0.822
1912	0.7
1913	0.948
1914	0.905
1915	0.988
1916	0.908
1917	0.993
1918	1.352
1919	0.765
1920	1.062
1921	1.008
1922	1.017
1923	1.16
1924	0.81
1925	0.861
1926	1.018
1927	1.26
1928	1.061
1929	1.065
1930	1.16
1931	0.992
1932	0.959
1933	1.09
1934	1.185
1935	0.881
1936	1.208
1937	0.908
1938	1.075
1939	1.229
1940	1.078
1941	1.107
1942	1.266
1943	1.199
1944	1.217
1945	1.005
1946	1.606
1947	1.047
1948	1.37
1949	0.783
1950	1.237
1951	1.062
1952	0.895
1953	0.899
1954	0.832
1955	0.987
1956	0.749
1957	0.841
1958	1.018
1959	0.913
1960	0.744
1961	0.878
1962	0.8
1963	0.62
1964	0.899
1965	0.901
1966	0.884
1967	0.873
1968	0.831
1969	0.993
1970	0.652
1971	1.18
1972	0.958
1973	0.683
1974	0.815
1975	1.101