# northamerica_usa_vt003 - Bolton Mountain Low - 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/8512
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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_usa_vt003 - Bolton Mountain Low - 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: Bolton Mountain Low
#	Location:
#	Country: United States
#	Northernmost_Latitude: 44.45
#	Southernmost_Latitude: 44.45
#	Easternmost_Longitude: -72.85
#	Westernmost_Longitude: -72.85
#	Elevation: 550 m
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# Data_Collection
#	Collection_Name: northamerica_usa_vt003B
#	Earliest_Year: 1868
#	Most_Recent_Year: 2005
#	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":"4.28930765788","T2":"20.1107976356","M1":"0.0224003959416","M2":"0.40760011534"}}
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# Species
#	Species_Name: sugar maple
#	Species_Code: ACSH
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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
1868	0.685
1869	0.865
1870	0.951
1871	0.872
1872	0.82
1873	0.868
1874	0.804
1875	0.979
1876	1.285
1877	1.402
1878	1.274
1879	1.153
1880	1.152
1881	1.142
1882	0.828
1883	0.98
1884	0.834
1885	1.123
1886	0.985
1887	1.118
1888	0.93
1889	0.926
1890	0.605
1891	0.629
1892	0.726
1893	0.694
1894	0.646
1895	0.849
1896	0.954
1897	0.732
1898	1.111
1899	1.003
1900	0.971
1901	1.018
1902	0.786
1903	0.934
1904	1.12
1905	0.892
1906	0.982
1907	0.8
1908	0.858
1909	0.861
1910	0.805
1911	0.735
1912	0.666
1913	0.587
1914	0.73
1915	0.739
1916	0.845
1917	0.749
1918	0.615
1919	0.784
1920	0.822
1921	0.834
1922	0.624
1923	0.53
1924	0.66
1925	0.457
1926	0.587
1927	0.61
1928	0.68
1929	0.604
1930	0.66
1931	0.978
1932	0.708
1933	0.754
1934	0.88
1935	0.969
1936	0.83
1937	1.298
1938	1.206
1939	1.164
1940	0.988
1941	1.101
1942	1.181
1943	1.337
1944	1.093
1945	0.848
1946	0.957
1947	1.296
1948	1.162
1949	1.314
1950	1.152
1951	1.406
1952	1.304
1953	1.146
1954	0.888
1955	1.326
1956	1.184
1957	1.112
1958	1.157
1959	1.111
1960	0.952
1961	1.116
1962	0.924
1963	1.033
1964	0.678
1965	0.328
1966	0.713
1967	0.977
1968	0.764
1969	1.092
1970	1.116
1971	1.156
1972	1.221
1973	1.209
1974	1.128
1975	1.147
1976	1.143
1977	1.223
1978	1.406
1979	1.051
1980	1.219
1981	1.089
1982	1.241
1983	1.155
1984	1.201
1985	1.156
1986	0.885
1987	0.922
1988	0.54
1989	0.487
1990	0.721
1991	0.924
1992	0.885
1993	0.734
1994	0.972
1995	0.888
1996	0.842
1997	0.808
1998	0.914
1999	0.923
2000	0.632
2001	0.57
2002	0.598
2003	0.716
2004	0.787
2005	0.654