# europe_finl039 - KyrÃÂ¶nniemi Savonlinna - 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/3999
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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_finl039 - KyrÃÂ¶nniemi Savonlinna - 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: KyrÃÂ¶nniemi Savonlinna
#	Location:
#	Country: Finland
#	Northernmost_Latitude: 61.85
#	Southernmost_Latitude: 61.85
#	Easternmost_Longitude: 28.9
#	Westernmost_Longitude: 28.9
#	Elevation: nan m
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# Data_Collection
#	Collection_Name: europe_finl039B
#	Earliest_Year: 1866
#	Most_Recent_Year: 1993
#	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":"3.3437039631","T2":"15.682867464","M1":"0.0230759907155","M2":"0.540239566497"}}
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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
1866	1.065
1867	0.862
1868	0.92
1869	0.94
1870	1.067
1871	0.912
1872	0.845
1873	1.004
1874	1.047
1875	0.826
1876	0.911
1877	0.956
1878	0.914
1879	0.912
1880	0.969
1881	0.957
1882	1.258
1883	1.087
1884	1.046
1885	0.963
1886	1.009
1887	0.919
1888	0.996
1889	0.71
1890	1.198
1891	1.064
1892	0.97
1893	0.982
1894	1.012
1895	0.933
1896	0.963
1897	0.971
1898	1.023
1899	0.896
1900	0.825
1901	0.844
1902	0.784
1903	0.999
1904	0.931
1905	0.936
1906	0.762
1907	0.903
1908	0.955
1909	0.721
1910	0.821
1911	0.778
1912	0.859
1913	0.907
1914	1.078
1915	1.115
1916	0.979
1917	0.868
1918	0.896
1919	1.097
1920	1.434
1921	1.666
1922	1.528
1923	1.409
1924	1.552
1925	1.492
1926	1.004
1927	1.313
1928	1.09
1929	1.192
1930	1.229
1931	1.136
1932	1.474
1933	1.32
1934	1.415
1935	1.141
1936	0.956
1937	1.074
1938	1.119
1939	0.953
1940	0.712
1941	0.822
1942	0.728
1943	1.028
1944	0.997
1945	0.989
1946	0.958
1947	0.965
1948	1.02
1949	1.052
1950	1.217
1951	0.955
1952	0.955
1953	1.166
1954	1.221
1955	0.958
1956	0.652
1957	1.126
1958	0.978
1959	0.965
1960	0.727
1961	0.703
1962	0.581
1963	0.518
1964	0.522
1965	0.513
1966	0.533
1967	0.782
1968	0.642
1969	0.488
1970	0.647
1971	0.655
1972	0.704
1973	0.784
1974	0.873
1975	0.94
1976	0.95
1977	1.075
1978	1.003
1979	1.078
1980	1.052
1981	1.006
1982	1.187
1983	1.23
1984	0.976
1985	0.899
1986	1.061
1987	0.961
1988	1.135
1989	0.99
1990	1.121
1991	1.124
1992	1.092
1993	0.922