# europe_finl041 - Kaivanto Paskolahti - 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/3989
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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_finl041 - Kaivanto Paskolahti - 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: Kaivanto Paskolahti
#	Location:
#	Country: Finland
#	Northernmost_Latitude: 61.92
#	Southernmost_Latitude: 61.92
#	Easternmost_Longitude: 29.0
#	Westernmost_Longitude: 29.0
#	Elevation: nan m
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# Data_Collection
#	Collection_Name: europe_finl041B
#	Earliest_Year: 1858
#	Most_Recent_Year: 2002
#	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":"4.17057778485","T2":"17.4237394217","M1":"0.022325098102","M2":"0.443155290821"}}
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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
1858	1.046
1859	1.103
1860	1.198
1861	1.234
1862	1.06
1863	1.104
1864	1.056
1865	0.949
1866	0.907
1867	0.66
1868	0.991
1869	0.916
1870	1.224
1871	1.155
1872	1.256
1873	1.146
1874	1.078
1875	0.879
1876	0.822
1877	0.999
1878	0.919
1879	0.92
1880	1.14
1881	0.889
1882	1.187
1883	0.883
1884	0.874
1885	0.975
1886	0.975
1887	0.997
1888	0.954
1889	0.932
1890	1.055
1891	0.799
1892	0.509
1893	0.506
1894	0.665
1895	0.548
1896	0.678
1897	0.732
1898	0.829
1899	0.913
1900	0.995
1901	1.031
1902	0.863
1903	1.05
1904	0.826
1905	0.91
1906	0.839
1907	0.84
1908	0.848
1909	0.777
1910	0.713
1911	0.703
1912	0.789
1913	0.821
1914	0.913
1915	1.119
1916	1.046
1917	0.867
1918	0.863
1919	0.871
1920	1.022
1921	1.214
1922	1.319
1923	1.359
1924	1.496
1925	1.102
1926	0.884
1927	1.051
1928	0.905
1929	0.899
1930	0.694
1931	0.65
1932	0.97
1933	1.041
1934	1.24
1935	1.152
1936	1.317
1937	1.37
1938	1.481
1939	1.203
1940	0.919
1941	1.06
1942	0.776
1943	0.943
1944	0.912
1945	1.115
1946	1.254
1947	1.213
1948	1.094
1949	1.072
1950	1.27
1951	1.194
1952	1.334
1953	1.497
1954	1.461
1955	1.241
1956	0.869
1957	1.412
1958	1.288
1959	1.164
1960	0.864
1961	0.964
1962	1.059
1963	1.107
1964	1.13
1965	1.057
1966	1.202
1967	1.413
1968	1.137
1969	0.986
1970	1.247
1971	1.14
1972	1.137
1973	1.16
1974	1.221
1975	1.192
1976	1.088
1977	0.915
1978	0.912
1979	1.037
1980	0.741
1981	0.706
1982	0.593
1983	0.771
1984	0.732
1985	0.632
1986	0.819
1987	0.764
1988	0.965
1989	0.828
1990	0.86
1991	0.738
1992	0.799
1993	0.628
1994	0.709
1995	0.7
1996	0.666
1997	0.567
1998	0.607
1999	0.687
2000	0.896
2001	0.87
2002	0.698