# northamerica_canada_cana061 - Lac Romanel - 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/4498
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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_cana061 - Lac Romanel - 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
#--------------------
# 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: Lac Romanel
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 56.23
#	Southernmost_Latitude: 56.23
#	Easternmost_Longitude: -67.72
#	Westernmost_Longitude: -67.72
#	Elevation: 1000 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana061B
#	Earliest_Year: 1849
#	Most_Recent_Year: 1988
#	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":"5.73299483794","T2":"17.1238003986","M1":"0.0223316864362","M2":"0.394574090719"}}
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# Species
#	Species_Name: black spruce
#	Species_Code: PCMA
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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
#
age	trsgi
1849	0.893
1850	0.943
1851	0.956
1852	0.85
1853	0.866
1854	1.003
1855	0.895
1856	0.969
1857	0.873
1858	1.21
1859	0.994
1860	0.882
1861	1.016
1862	0.796
1863	0.879
1864	0.877
1865	0.826
1866	0.807
1867	0.856
1868	0.849
1869	1.041
1870	1.076
1871	1.169
1872	1.121
1873	1.265
1874	1.284
1875	1.318
1876	0.979
1877	1.233
1878	1.111
1879	1.099
1880	1.146
1881	1.222
1882	0.944
1883	1.042
1884	0.945
1885	1.041
1886	1.196
1887	0.966
1888	0.951
1889	0.938
1890	0.733
1891	1.191
1892	1.029
1893	1.148
1894	0.871
1895	1.196
1896	0.956
1897	1.154
1898	0.899
1899	0.833
1900	0.875
1901	0.887
1902	0.98
1903	0.891
1904	0.837
1905	0.697
1906	0.978
1907	0.999
1908	0.908
1909	1.061
1910	0.997
1911	1.079
1912	0.894
1913	1.106
1914	1.284
1915	1.11
1916	1.277
1917	1.07
1918	0.933
1919	0.979
1920	0.819
1921	0.833
1922	0.844
1923	0.842
1924	0.96
1925	0.726
1926	0.595
1927	0.821
1928	1.072
1929	0.74
1930	0.874
1931	0.994
1932	0.69
1933	0.678
1934	1.051
1935	1.067
1936	1.02
1937	1.466
1938	1.24
1939	1.077
1940	0.904
1941	1.18
1942	1.278
1943	1.203
1944	1.109
1945	0.936
1946	1.044
1947	1.187
1948	1.352
1949	0.964
1950	0.917
1951	1.037
1952	1.086
1953	0.837
1954	1.058
1955	0.874
1956	0.953
1957	0.839
1958	0.814
1959	0.921
1960	0.857
1961	0.943
1962	0.954
1963	1.024
1964	0.754
1965	0.803
1966	0.868
1967	0.938
1968	0.853
1969	1.165
1970	0.933
1971	0.882
1972	1.109
1973	1.021
1974	1.012
1975	0.882
1976	0.921
1977	0.836
1978	1.017
1979	1.084
1980	1.135
1981	0.721
1982	1.079
1983	1.012
1984	1.24
1985	1.247
1986	1.055
1987	1.098
1988	1.31