# northamerica_usa_ga001 - Athens - 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/3425
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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_ga001 - Athens - 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: Athens
#	Location:
#	Country: United States
#	Northernmost_Latitude: 33.95
#	Southernmost_Latitude: 33.95
#	Easternmost_Longitude: -83.32
#	Westernmost_Longitude: -83.32
#	Elevation: 243 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ga001B
#	Earliest_Year: 1857
#	Most_Recent_Year: 1986
#	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":"5.20548770834","T2":"18.6202728829","M1":"0.0228840883543","M2":"0.577027143932"}}
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# Species
#	Species_Name: shortleaf pine
#	Species_Code: PIEC
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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
1857	0.869
1858	0.815
1859	1.254
1860	1.131
1861	1.123
1862	0.598
1863	0.712
1864	0.705
1865	0.258
1866	0.445
1867	0.795
1868	1.103
1869	1.024
1870	1.275
1871	0.953
1872	0.989
1873	1.014
1874	1.201
1875	1.015
1876	0.774
1877	0.792
1878	0.786
1879	0.749
1880	1.004
1881	1.099
1882	1.215
1883	0.746
1884	0.801
1885	0.836
1886	1.057
1887	0.809
1888	0.984
1889	1.097
1890	1.075
1891	1.016
1892	1.075
1893	1.102
1894	0.826
1895	0.938
1896	0.831
1897	1.007
1898	1.279
1899	0.853
1900	1.163
1901	1.27
1902	0.996
1903	1.283
1904	0.853
1905	0.991
1906	1.281
1907	1.246
1908	1.092
1909	1.184
1910	0.981
1911	1.126
1912	1.16
1913	0.981
1914	0.738
1915	0.872
1916	1.077
1917	0.882
1918	1.051
1919	1.196
1920	0.904
1921	0.838
1922	0.918
1923	0.869
1924	0.618
1925	0.515
1926	0.988
1927	0.689
1928	1.094
1929	1.157
1930	0.927
1931	0.686
1932	0.89
1933	1.02
1934	0.973
1935	1.019
1936	0.751
1937	0.722
1938	0.949
1939	0.889
1940	0.952
1941	0.614
1942	0.898
1943	0.784
1944	0.456
1945	0.579
1946	0.758
1947	0.643
1948	0.709
1949	0.819
1950	0.853
1951	0.785
1952	0.919
1953	1.138
1954	0.91
1955	0.944
1956	0.939
1957	1.109
1958	1.001
1959	1.291
1960	1.005
1961	1.176
1962	0.929
1963	1.372
1964	1.182
1965	1.14
1966	1.25
1967	1.231
1968	1.11
1969	1.296
1970	1.081
1971	1.092
1972	0.85
1973	1.456
1974	1.501
1975	1.68
1976	0.937
1977	1.111
1978	0.617
1979	0.492
1980	0.643
1981	0.985
1982	1.047
1983	0.916
1984	1.217
1985	1.041
1986	0.414