# europe_swed317 - StortjÃÂ¤derberget - 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/6140
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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_swed317 - StortjÃÂ¤derberget - 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: StortjÃÂ¤derberget
#	Location:
#	Country: Sweden
#	Northernmost_Latitude: 64.53
#	Southernmost_Latitude: 64.53
#	Easternmost_Longitude: 19.0
#	Westernmost_Longitude: 19.0
#	Elevation: 290 m
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# Data_Collection
#	Collection_Name: europe_swed317B
#	Earliest_Year: 1846
#	Most_Recent_Year: 1998
#	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":"6.41621318568","T2":"13.2475582862","M1":"0.0225002559203","M2":"0.503262334328"}}
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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
#
age	trsgi
1846	1.011
1847	1.045
1848	0.997
1849	0.851
1850	1.058
1851	0.929
1852	1.199
1853	1.82
1854	2.036
1855	2.073
1856	1.945
1857	1.412
1858	1.169
1859	1.329
1860	1.339
1861	1.335
1862	1.202
1863	0.862
1864	0.881
1865	0.763
1866	0.793
1867	0.703
1868	0.987
1869	0.705
1870	1.002
1871	1.037
1872	1.298
1873	1.06
1874	1.131
1875	1.152
1876	0.808
1877	0.747
1878	0.581
1879	0.605
1880	0.635
1881	0.627
1882	0.539
1883	0.525
1884	0.547
1885	0.627
1886	0.569
1887	0.507
1888	0.505
1889	0.312
1890	0.531
1891	0.471
1892	0.692
1893	0.855
1894	0.532
1895	0.908
1896	0.781
1897	0.822
1898	0.903
1899	0.693
1900	0.855
1901	0.898
1902	0.562
1903	0.625
1904	0.58
1905	0.628
1906	0.694
1907	0.587
1908	0.615
1909	0.733
1910	0.769
1911	0.699
1912	0.894
1913	1.134
1914	1.47
1915	1.627
1916	1.252
1917	1.352
1918	1.107
1919	1.158
1920	0.927
1921	1.025
1922	0.982
1923	0.614
1924	0.678
1925	0.768
1926	0.765
1927	0.738
1928	0.363
1929	0.819
1930	0.673
1931	0.451
1932	0.716
1933	0.679
1934	0.572
1935	0.274
1936	0.478
1937	0.685
1938	0.604
1939	0.698
1940	0.761
1941	0.668
1942	0.604
1943	0.689
1944	0.587
1945	0.506
1946	0.822
1947	1.153
1948	1.027
1949	1.387
1950	1.185
1951	1.068
1952	1.106
1953	1.157
1954	1.445
1955	1.176
1956	1.172
1957	1.139
1958	1.357
1959	1.009
1960	1.079
1961	0.871
1962	1.316
1963	1.48
1964	1.356
1965	0.882
1966	0.971
1967	1.025
1968	1.177
1969	0.872
1970	1.246
1971	1.4
1972	1.399
1973	1.363
1974	1.244
1975	1.305
1976	1.84
1977	1.301
1978	1.485
1979	1.706
1980	1.315
1981	1.366
1982	1.254
1983	1.38
1984	1.603
1985	1.56
1986	1.634
1987	1.451
1988	1.1
1989	1.573
1990	1.224
1991	1.14
1992	1.342
1993	0.818
1994	1.02
1995	0.973
1996	1.026
1997	0.822
1998	0.782