# europe_finl1 - Juoksukallio Eteissaari 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/3985
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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_finl1 - Juoksukallio Eteissaari 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: Juoksukallio Eteissaari Savonlinna
#	Location:
#	Country: Finland
#	Northernmost_Latitude: 61.77
#	Southernmost_Latitude: 61.77
#	Easternmost_Longitude: 28.77
#	Westernmost_Longitude: 28.77
#	Elevation: 90 m
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# Data_Collection
#	Collection_Name: europe_finl1B
#	Earliest_Year: 1864
#	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":"3.10715171148","T2":"13.3440091392","M1":"0.0234541732985","M2":"0.565309867551"}}
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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
1864	1.063
1865	0.87
1866	1.005
1867	0.553
1868	0.77
1869	0.861
1870	0.851
1871	0.81
1872	0.799
1873	1.005
1874	1.056
1875	0.661
1876	0.842
1877	1.044
1878	0.866
1879	1.054
1880	1.213
1881	0.891
1882	1.131
1883	1.161
1884	1.095
1885	0.852
1886	1.088
1887	0.813
1888	1.082
1889	0.706
1890	1.408
1891	0.952
1892	1.167
1893	1.106
1894	1.099
1895	0.957
1896	0.719
1897	0.823
1898	1.032
1899	0.868
1900	0.75
1901	0.498
1902	0.57
1903	0.816
1904	0.713
1905	0.794
1906	0.728
1907	0.935
1908	0.949
1909	0.9
1910	0.696
1911	0.8
1912	1.037
1913	0.931
1914	1.016
1915	1.268
1916	0.995
1917	0.674
1918	0.811
1919	0.833
1920	1.165
1921	1.447
1922	1.696
1923	1.591
1924	2.036
1925	1.75
1926	1.156
1927	1.413
1928	1.284
1929	1.243
1930	0.929
1931	0.761
1932	1.07
1933	0.772
1934	1.245
1935	0.804
1936	0.967
1937	0.907
1938	1.109
1939	0.971
1940	0.624
1941	0.886
1942	0.62
1943	0.779
1944	0.585
1945	0.678
1946	0.834
1947	0.732
1948	0.709
1949	0.781
1950	1.048
1951	0.905
1952	1.051
1953	1.151
1954	1.265
1955	0.945
1956	0.701
1957	1.497
1958	1.178
1959	0.601
1960	0.558
1961	0.552
1962	0.805
1963	0.731
1964	0.773
1965	0.982
1966	1.121
1967	1.671
1968	1.245
1969	1.048
1970	1.165
1971	0.756
1972	0.954
1973	0.764
1974	0.956
1975	0.803
1976	1.02
1977	0.895
1978	0.952
1979	1.146
1980	0.9
1981	1.096
1982	1.257
1983	1.266
1984	1.018
1985	0.971
1986	1.224
1987	1.286
1988	1.205
1989	1.127
1990	1.304
1991	1.045
1992	0.495
1993	1.025