# europe_swed319 - AngerusjÃÂ¤rvi - 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/6129
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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: europe_swed319 - AngerusjÃÂ¤rvi - 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
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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:
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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: AngerusjÃÂ¤rvi
#	Location:
#	Country: Sweden
#	Northernmost_Latitude: 67.63
#	Southernmost_Latitude: 67.63
#	Easternmost_Longitude: 21.77
#	Westernmost_Longitude: 21.77
#	Elevation: 280 m
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# Data_Collection
#	Collection_Name: europe_swed319B
#	Earliest_Year: 1859
#	Most_Recent_Year: 1998
#	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":"4.80730450841","T2":"20.4967067511","M1":"0.0216503878687","M2":"0.166250469035"}}
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# Species
#	Species_Name: Scots pine
#	Species_Code: PISY
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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
1859	0.944
1860	0.985
1861	1.098
1862	1.119
1863	0.806
1864	0.708
1865	0.632
1866	0.683
1867	0.672
1868	0.814
1869	0.759
1870	1.123
1871	0.933
1872	1.372
1873	1.267
1874	1.005
1875	1.126
1876	1.166
1877	0.922
1878	0.553
1879	0.873
1880	0.998
1881	0.852
1882	1.242
1883	1.65
1884	1.378
1885	1.222
1886	0.963
1887	1.132
1888	0.772
1889	0.77
1890	1.145
1891	1.039
1892	0.648
1893	0.75
1894	0.59
1895	1.226
1896	0.742
1897	1.007
1898	0.991
1899	0.655
1900	0.611
1901	0.767
1902	0.478
1903	0.231
1904	0.312
1905	0.597
1906	0.68
1907	0.667
1908	0.718
1909	0.556
1910	0.627
1911	0.588
1912	0.705
1913	0.777
1914	1.286
1915	1.728
1916	1.476
1917	1.333
1918	1.633
1919	1.45
1920	1.57
1921	1.556
1922	1.489
1923	1.409
1924	1.149
1925	1.682
1926	1.428
1927	1.053
1928	1.103
1929	1.119
1930	1.143
1931	1.08
1932	0.852
1933	1.202
1934	1.547
1935	1.139
1936	0.519
1937	1.102
1938	1.223
1939	1.024
1940	1.249
1941	1.711
1942	1.548
1943	1.155
1944	1.304
1945	0.881
1946	0.995
1947	1.276
1948	1.37
1949	1.247
1950	0.911
1951	0.755
1952	0.552
1953	0.903
1954	1.677
1955	1.034
1956	0.958
1957	1.114
1958	1.069
1959	1.386
1960	0.953
1961	0.784
1962	0.937
1963	0.585
1964	0.97
1965	0.219
1966	0.563
1967	0.547
1968	0.698
1969	0.357
1970	1.171
1971	1.408
1972	1.246
1973	1.496
1974	1.124
1975	0.959
1976	1.392
1977	0.773
1978	0.745
1979	1.239
1980	0.87
1981	0.874
1982	0.842
1983	1.022
1984	0.94
1985	0.924
1986	1.149
1987	0.604
1988	0.592
1989	0.861
1990	0.67
1991	0.724
1992	0.736
1993	0.577
1994	0.401
1995	0.668
1996	0.653
1997	0.893
1998	0.804