# northamerica_usa_ga005 - J.W. Jones Ecological Research Center - 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/4104
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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_ga005 - J.W. Jones Ecological Research Center - 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:
#--------------------
#	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: J.W. Jones Ecological Research Center
#	Location:
#	Country: United States
#	Northernmost_Latitude: 31.22
#	Southernmost_Latitude: 31.22
#	Easternmost_Longitude: -84.48
#	Westernmost_Longitude: -84.48
#	Elevation: 43 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ga005B
#	Earliest_Year: 1857
#	Most_Recent_Year: 1995
#	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":"4.41166589855","T2":"18.8383031376","M1":"0.0222153677834","M2":"0.58317772727"}}
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# Species
#	Species_Name: longleaf pine
#	Species_Code: PIPA
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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	0.745
1858	0.29
1859	0.46
1860	0.213
1861	0.348
1862	0.396
1863	0.619
1864	0.503
1865	0.647
1866	1.055
1867	1.192
1868	1.21
1869	1.071
1870	1.258
1871	1.454
1872	0.902
1873	0.86
1874	0.753
1875	0.659
1876	0.625
1877	0.651
1878	0.806
1879	0.921
1880	0.848
1881	0.735
1882	1.027
1883	0.743
1884	0.418
1885	0.378
1886	0.773
1887	0.616
1888	0.724
1889	0.687
1890	0.871
1891	0.559
1892	0.516
1893	0.755
1894	0.865
1895	0.874
1896	0.522
1897	0.793
1898	0.858
1899	0.403
1900	0.533
1901	0.711
1902	0.75
1903	1.021
1904	0.654
1905	0.858
1906	1.355
1907	1.265
1908	1.235
1909	1.043
1910	0.675
1911	0.778
1912	1.16
1913	1.13
1914	0.874
1915	0.824
1916	1.099
1917	0.971
1918	1.188
1919	1.525
1920	0.999
1921	1.293
1922	1.563
1923	1.385
1924	1.083
1925	1.027
1926	1.593
1927	0.932
1928	1.607
1929	1.492
1930	1.261
1931	1.16
1932	1.059
1933	0.672
1934	1.2
1935	1.109
1936	1.017
1937	1.022
1938	0.651
1939	1.174
1940	0.651
1941	0.922
1942	0.939
1943	0.745
1944	1.062
1945	1.081
1946	1.156
1947	1.154
1948	0.919
1949	1.005
1950	0.709
1951	0.642
1952	0.948
1953	1.144
1954	0.497
1955	0.793
1956	1.105
1957	1.13
1958	1.13
1959	1.066
1960	1.122
1961	1.197
1962	0.776
1963	1.023
1964	1.308
1965	1.064
1966	0.981
1967	0.852
1968	0.807
1969	1.185
1970	1.255
1971	1.39
1972	0.877
1973	0.95
1974	1.046
1975	1.442
1976	0.669
1977	0.896
1978	0.885
1979	0.889
1980	1.07
1981	1.002
1982	1.224
1983	0.909
1984	1.077
1985	0.62
1986	0.431
1987	0.669
1988	0.722
1989	1.063
1990	0.712
1991	1.409
1992	0.9
1993	0.931
1994	1.476
1995	0.614