# europe_swed313 - RÃÂ¤lla Tall, HÃÂ¶gsrum sn, ÃÂland - 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/5498
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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_swed313 - RÃÂ¤lla Tall, HÃÂ¶gsrum sn, ÃÂland - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
#--------------------
# Description_and_Notes
#	Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details
#--------------------
# 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:
#--------------------
#	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: RÃÂ¤lla Tall, HÃÂ¶gsrum sn, ÃÂland
#	Location:
#	Country: Sweden
#	Northernmost_Latitude: 56.77
#	Southernmost_Latitude: 56.77
#	Easternmost_Longitude: 16.55
#	Westernmost_Longitude: 16.55
#	Elevation: 30 m
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# Data_Collection
#	Collection_Name: europe_swed313B
#	Earliest_Year: 1861
#	Most_Recent_Year: 2005
#	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":"4.11259494947","T2":"16.4905445712","M1":"0.0220995485254","M2":"0.498833844537"}}
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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
1861	1.166
1862	0.992
1863	0.979
1864	1.109
1865	1.152
1866	1.328
1867	1.266
1868	0.792
1869	0.919
1870	1.034
1871	0.934
1872	0.905
1873	0.896
1874	0.783
1875	0.735
1876	0.749
1877	0.748
1878	1.084
1879	0.972
1880	1.201
1881	0.938
1882	1.322
1883	1.101
1884	1.387
1885	0.981
1886	0.806
1887	0.884
1888	0.675
1889	0.836
1890	1.12
1891	1.005
1892	1.064
1893	0.78
1894	1.041
1895	0.701
1896	0.789
1897	0.838
1898	0.848
1899	0.69
1900	0.669
1901	0.673
1902	0.581
1903	0.892
1904	0.806
1905	0.874
1906	0.979
1907	1.216
1908	0.953
1909	0.983
1910	1.271
1911	0.958
1912	0.907
1913	1.095
1914	0.968
1915	0.999
1916	1.112
1917	0.93
1918	0.815
1919	0.95
1920	1.27
1921	1.017
1922	0.963
1923	1.107
1924	1.155
1925	1.54
1926	1.258
1927	1.518
1928	1.533
1929	1.353
1930	1.55
1931	1.06
1932	1.394
1933	1.372
1934	1.573
1935	1.557
1936	1.476
1937	1.184
1938	1.078
1939	1.076
1940	0.435
1941	0.594
1942	0.62
1943	0.519
1944	0.676
1945	0.8
1946	1.033
1947	0.919
1948	1.182
1949	1.365
1950	1.311
1951	1.176
1952	1.179
1953	1.502
1954	1.084
1955	0.914
1956	1.09
1957	1.371
1958	1.291
1959	0.884
1960	0.979
1961	1.338
1962	1.245
1963	1.046
1964	0.925
1965	1.231
1966	0.851
1967	0.951
1968	1.049
1969	0.615
1970	0.759
1971	0.886
1972	0.995
1973	0.849
1974	0.763
1975	0.879
1976	0.683
1977	0.689
1978	0.805
1979	0.847
1980	0.757
1981	0.935
1982	0.803
1983	0.645
1984	0.817
1985	0.89
1986	0.672
1987	0.976
1988	1.178
1989	0.823
1990	0.956
1991	1.063
1992	0.694
1993	0.725
1994	0.718
1995	0.934
1996	0.924
1997	1.003
1998	0.808
1999	0.807
2000	0.867
2001	0.59
2002	0.687
2003	0.684
2004	0.665
2005	0.742