# europe_lith014 - Visakio Ruda - 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/8597
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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_lith014 - Visakio Ruda - 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: Visakio Ruda
#	Location:
#	Country: Lithuania
#	Northernmost_Latitude: 54.82
#	Southernmost_Latitude: 54.82
#	Easternmost_Longitude: 23.43
#	Westernmost_Longitude: 23.43
#	Elevation: 60 m
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# Data_Collection
#	Collection_Name: europe_lith014B
#	Earliest_Year: 1868
#	Most_Recent_Year: 2006
#	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":"4.02565657621","T2":"19.5737539145","M1":"0.0222832279715","M2":"0.208901300723"}}
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# Species
#	Species_Name: European larch
#	Species_Code: LADE
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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
1868	0.5
1869	0.943
1870	1.049
1871	1.132
1872	0.973
1873	0.877
1874	0.704
1875	0.836
1876	1.077
1877	1.148
1878	1.291
1879	1.133
1880	1.492
1881	1.395
1882	1.21
1883	0.965
1884	0.8
1885	0.438
1886	0.841
1887	1.117
1888	0.661
1889	0.515
1890	0.585
1891	0.734
1892	0.664
1893	0.766
1894	0.728
1895	1.027
1896	0.871
1897	0.979
1898	0.834
1899	0.75
1900	0.754
1901	1.0
1902	0.956
1903	1.425
1904	1.508
1905	1.671
1906	1.342
1907	1.176
1908	1.262
1909	1.266
1910	1.707
1911	1.506
1912	1.347
1913	1.478
1914	1.188
1915	1.262
1916	1.391
1917	1.081
1918	0.98
1919	0.994
1920	0.379
1921	0.719
1922	0.886
1923	0.843
1924	0.58
1925	0.45
1926	0.528
1927	0.547
1928	0.432
1929	0.629
1930	0.634
1931	0.81
1932	0.886
1933	0.676
1934	0.868
1935	1.015
1936	1.081
1937	0.895
1938	0.857
1939	0.836
1940	0.633
1941	0.563
1942	0.708
1943	0.871
1944	0.995
1945	0.752
1946	1.034
1947	0.945
1948	0.897
1949	0.978
1950	0.908
1951	1.044
1952	0.818
1953	0.853
1954	0.683
1955	0.925
1956	0.662
1957	1.11
1958	0.817
1959	0.848
1960	0.83
1961	1.099
1962	0.903
1963	1.146
1964	0.902
1965	0.931
1966	1.033
1967	0.865
1968	0.879
1969	0.979
1970	1.017
1971	0.917
1972	1.127
1973	1.045
1974	0.866
1975	1.199
1976	0.792
1977	1.055
1978	1.15
1979	1.038
1980	1.082
1981	1.303
1982	1.083
1983	1.283
1984	0.945
1985	1.191
1986	1.498
1987	1.246
1988	1.434
1989	1.062
1990	1.418
1991	1.227
1992	0.798
1993	1.147
1994	0.756
1995	0.742
1996	1.034
1997	1.198
1998	0.956
1999	1.048
2000	0.789
2001	0.915
2002	0.828
2003	0.918
2004	0.775
2005	1.066
2006	0.676