# northamerica_canada_cana290 - River 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/8583
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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_cana290 - River 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: River Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 62.6
#	Southernmost_Latitude: 62.6
#	Easternmost_Longitude: -114.13
#	Westernmost_Longitude: -114.13
#	Elevation: 195 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana290B
#	Earliest_Year: 1864
#	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":"4.46728410879","T2":"16.7570500817","M1":"0.0225758224943","M2":"0.415475570184"}}
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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
#
age	trsgi
1864	0.693
1865	0.738
1866	1.175
1867	1.216
1868	1.035
1869	0.955
1870	1.506
1871	1.506
1872	1.382
1873	1.133
1874	1.17
1875	0.99
1876	1.15
1877	1.145
1878	1.515
1879	0.944
1880	1.324
1881	0.848
1882	1.259
1883	0.779
1884	0.761
1885	1.171
1886	0.699
1887	1.025
1888	0.769
1889	1.155
1890	1.046
1891	0.986
1892	1.039
1893	0.533
1894	1.039
1895	0.861
1896	0.906
1897	0.828
1898	1.076
1899	1.132
1900	0.667
1901	0.692
1902	0.557
1903	0.872
1904	0.492
1905	0.67
1906	0.837
1907	1.129
1908	0.642
1909	1.01
1910	1.076
1911	0.972
1912	0.813
1913	0.877
1914	0.711
1915	0.662
1916	0.835
1917	1.065
1918	1.099
1919	1.267
1920	0.911
1921	1.005
1922	1.262
1923	0.757
1924	0.993
1925	0.812
1926	0.724
1927	0.288
1928	0.592
1929	0.985
1930	0.906
1931	0.803
1932	1.008
1933	0.913
1934	0.809
1935	0.793
1936	0.702
1937	0.829
1938	0.904
1939	1.096
1940	0.685
1941	1.427
1942	0.606
1943	1.077
1944	1.194
1945	0.95
1946	0.773
1947	1.085
1948	1.416
1949	1.521
1950	1.195
1951	1.548
1952	0.75
1953	1.217
1954	1.02
1955	1.329
1956	1.077
1957	1.474
1958	0.745
1959	1.212
1960	1.169
1961	0.871
1962	1.052
1963	1.166
1964	0.643
1965	0.759
1966	0.681
1967	0.662
1968	0.596
1969	0.547
1970	1.152
1971	0.862
1972	0.713
1973	0.534
1974	1.225
1975	0.742
1976	1.187
1977	1.033
1978	1.069
1979	1.174
1980	1.366
1981	1.498
1982	1.111
1983	0.951
1984	1.217
1985	1.099
1986	1.25
1987	1.146
1988	1.462
1989	0.973
1990	1.246
1991	1.49
1992	1.42
1993	0.555
1994	0.983
1995	0.453
1996	0.996
1997	1.012
1998	0.784
1999	0.851
2000	0.831
2001	1.012
2002	0.882
2003	1.052
2004	0.733
2005	1.201