# northamerica_usa_mn018 - Wolsfeld Woods - 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/4998
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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: northamerica_usa_mn018 - Wolsfeld Woods - 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: Wolsfeld Woods
#	Location:
#	Country: United States
#	Northernmost_Latitude: 45.0
#	Southernmost_Latitude: 45.0
#	Easternmost_Longitude: -93.57
#	Westernmost_Longitude: -93.57
#	Elevation: 308 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mn018B
#	Earliest_Year: 1851
#	Most_Recent_Year: 1983
#	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":"4.38663641641","T2":"16.2517132442","M1":"0.0227903951613","M2":"0.473091544998"}}
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# Species
#	Species_Name: sugar maple
#	Species_Code: ACSH
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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
1851	0.986
1852	1.246
1853	0.864
1854	1.174
1855	1.396
1856	1.011
1857	0.599
1858	0.556
1859	0.889
1860	1.244
1861	1.161
1862	0.983
1863	0.75
1864	0.314
1865	0.48
1866	0.871
1867	0.796
1868	0.686
1869	0.508
1870	0.58
1871	0.76
1872	0.844
1873	0.624
1874	0.48
1875	0.6
1876	0.842
1877	0.696
1878	0.834
1879	1.088
1880	1.369
1881	1.155
1882	1.462
1883	1.464
1884	1.365
1885	1.596
1886	1.164
1887	0.934
1888	1.24
1889	1.027
1890	1.051
1891	1.37
1892	1.345
1893	0.896
1894	0.61
1895	0.492
1896	0.803
1897	1.078
1898	1.378
1899	0.979
1900	1.035
1901	1.091
1902	1.437
1903	1.625
1904	1.475
1905	1.652
1906	0.931
1907	1.126
1908	1.288
1909	0.966
1910	0.489
1911	0.474
1912	1.18
1913	1.554
1914	1.237
1915	0.985
1916	1.016
1917	0.724
1918	0.912
1919	1.409
1920	1.085
1921	0.824
1922	0.841
1923	0.926
1924	0.994
1925	1.193
1926	0.529
1927	0.989
1928	1.473
1929	1.307
1930	0.987
1931	0.717
1932	0.668
1933	0.867
1934	0.141
1935	0.381
1936	0.583
1937	0.631
1938	0.825
1939	1.455
1940	1.2
1941	1.217
1942	1.467
1943	1.133
1944	0.813
1945	0.93
1946	1.093
1947	0.893
1948	0.579
1949	1.011
1950	0.851
1951	1.135
1952	1.416
1953	1.034
1954	1.056
1955	0.88
1956	0.846
1957	1.147
1958	1.133
1959	0.859
1960	0.642
1961	0.746
1962	0.893
1963	0.956
1964	0.704
1965	0.496
1966	0.727
1967	0.731
1968	0.917
1969	1.219
1970	0.977
1971	0.983
1972	1.144
1973	1.046
1974	0.72
1975	0.938
1976	0.822
1977	0.808
1978	1.084
1979	1.154
1980	1.275
1981	0.921
1982	1.114
1983	0.98