# northamerica_usa_nc012 - Joyce Kilmer Memorial Forest - 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/4871
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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_nc012 - Joyce Kilmer Memorial Forest - 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: Joyce Kilmer Memorial Forest
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.35
#	Southernmost_Latitude: 35.35
#	Easternmost_Longitude: -83.92
#	Westernmost_Longitude: -83.92
#	Elevation: 250 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nc012B
#	Earliest_Year: 1865
#	Most_Recent_Year: 1997
#	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":"3.23260211215","T2":"18.3235271954","M1":"0.0224083072108","M2":"0.451558670029"}}
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# Species
#	Species_Name: tuliptree
#	Species_Code: LITU
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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
1865	0.767
1866	0.763
1867	0.794
1868	0.65
1869	0.755
1870	0.799
1871	0.775
1872	0.917
1873	0.814
1874	0.664
1875	1.137
1876	1.156
1877	0.697
1878	0.793
1879	0.457
1880	0.816
1881	0.681
1882	0.812
1883	0.909
1884	1.012
1885	0.953
1886	0.825
1887	0.967
1888	0.681
1889	0.94
1890	0.76
1891	0.98
1892	1.368
1893	0.998
1894	0.963
1895	0.697
1896	0.976
1897	1.03
1898	0.834
1899	0.691
1900	0.783
1901	0.919
1902	0.97
1903	1.078
1904	0.807
1905	1.024
1906	1.388
1907	1.151
1908	0.902
1909	0.815
1910	0.92
1911	0.698
1912	0.89
1913	0.997
1914	0.574
1915	0.783
1916	1.623
1917	0.822
1918	0.734
1919	0.868
1920	0.965
1921	1.135
1922	1.673
1923	1.572
1924	0.997
1925	0.809
1926	0.524
1927	1.618
1928	1.537
1929	1.308
1930	0.669
1931	0.824
1932	1.396
1933	1.31
1934	1.659
1935	1.94
1936	1.015
1937	1.721
1938	1.827
1939	1.82
1940	1.107
1941	1.2
1942	1.57
1943	1.102
1944	0.846
1945	0.975
1946	0.971
1947	0.999
1948	0.686
1949	0.907
1950	0.855
1951	0.741
1952	0.58
1953	1.094
1954	0.806
1955	0.852
1956	0.986
1957	0.999
1958	0.787
1959	0.746
1960	0.821
1961	0.697
1962	0.773
1963	0.526
1964	0.825
1965	0.577
1966	0.837
1967	0.737
1968	0.862
1969	0.675
1970	0.935
1971	0.916
1972	1.038
1973	1.062
1974	0.711
1975	1.126
1976	0.855
1977	0.722
1978	0.682
1979	0.762
1980	1.028
1981	0.779
1982	1.181
1983	1.071
1984	0.732
1985	1.101
1986	0.712
1987	0.916
1988	0.868
1989	1.209
1990	1.349
1991	1.387
1992	1.25
1993	1.052
1994	0.856
1995	1.007
1996	0.831
1997	0.904