# europe_swed329 - Abisko Valley - 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/6126
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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_swed329 - Abisko Valley - 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:
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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: Abisko Valley
#	Location:
#	Country: Sweden
#	Northernmost_Latitude: 68.33
#	Southernmost_Latitude: 68.33
#	Easternmost_Longitude: 18.8
#	Westernmost_Longitude: 18.8
#	Elevation: 470 m
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# Data_Collection
#	Collection_Name: europe_swed329B
#	Earliest_Year: 1844
#	Most_Recent_Year: 1983
#	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":"3.54229003051","T2":"17.7741035798","M1":"0.0224205142677","M2":"0.351411370905"}}
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# Species
#	Species_Name: downy birch
#	Species_Code: BEPU
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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
1844	1.244
1845	0.883
1846	0.904
1847	1.531
1848	0.787
1849	0.909
1850	0.904
1851	1.191
1852	1.216
1853	1.237
1854	1.064
1855	1.089
1856	0.621
1857	0.573
1858	0.434
1859	0.527
1860	0.929
1861	0.581
1862	0.488
1863	0.786
1864	0.801
1865	0.693
1866	0.827
1867	0.546
1868	0.723
1869	0.878
1870	1.223
1871	0.977
1872	0.96
1873	1.149
1874	0.569
1875	1.186
1876	1.451
1877	0.891
1878	0.66
1879	0.456
1880	0.585
1881	0.892
1882	1.522
1883	1.924
1884	1.151
1885	1.261
1886	1.298
1887	0.677
1888	0.831
1889	1.007
1890	0.921
1891	0.988
1892	0.652
1893	0.691
1894	0.892
1895	1.18
1896	1.162
1897	1.157
1898	0.872
1899	1.162
1900	0.566
1901	1.043
1902	0.457
1903	0.28
1904	0.409
1905	0.667
1906	0.663
1907	1.164
1908	0.968
1909	0.681
1910	0.677
1911	0.674
1912	1.106
1913	1.363
1914	1.493
1915	1.061
1916	0.846
1917	0.324
1918	0.346
1919	0.51
1920	0.532
1921	0.695
1922	1.38
1923	0.671
1924	1.174
1925	1.17
1926	1.182
1927	1.235
1928	0.715
1929	0.817
1930	1.703
1931	1.01
1932	1.162
1933	1.419
1934	1.176
1935	1.094
1936	1.326
1937	1.895
1938	1.641
1939	1.638
1940	1.167
1941	1.238
1942	0.872
1943	0.922
1944	0.713
1945	0.91
1946	0.879
1947	1.344
1948	0.736
1949	0.785
1950	1.335
1951	0.549
1952	0.934
1953	1.163
1954	0.391
1955	0.049
1956	0.2
1957	0.56
1958	0.612
1959	0.823
1960	1.947
1961	1.914
1962	1.12
1963	1.133
1964	1.379
1965	0.942
1966	1.553
1967	1.104
1968	0.993
1969	1.238
1970	1.305
1971	0.894
1972	1.305
1973	1.164
1974	0.781
1975	0.351
1976	0.829
1977	0.49
1978	0.911
1979	0.989
1980	1.142
1981	0.413
1982	0.652
1983	0.439