# asia_leba001 - Barouk - 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/5124
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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: asia_leba001 - Barouk - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Barouk
#	Location:
#	Country: Lebanon
#	Northernmost_Latitude: 33.68
#	Southernmost_Latitude: 33.68
#	Easternmost_Longitude: 35.68
#	Westernmost_Longitude: 35.68
#	Elevation: 1775 m
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# Data_Collection
#	Collection_Name: asia_leba001B
#	Earliest_Year: 1867
#	Most_Recent_Year: 2002
#	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":"5.50365054621","T2":"17.8839501685","M1":"0.0222409020113","M2":"0.201189426908"}}
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# Species
#	Species_Name: cedar of Lebanone
#	Species_Code: CDLI
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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
1867	0.961
1868	0.772
1869	1.03
1870	0.944
1871	1.077
1872	0.86
1873	0.835
1874	0.789
1875	1.078
1876	1.47
1877	1.31
1878	0.975
1879	1.08
1880	0.763
1881	0.677
1882	0.735
1883	0.616
1884	0.548
1885	0.991
1886	1.236
1887	1.162
1888	1.305
1889	1.284
1890	1.303
1891	1.387
1892	1.443
1893	1.176
1894	1.133
1895	1.21
1896	0.853
1897	0.788
1898	0.521
1899	0.734
1900	1.079
1901	1.217
1902	1.278
1903	1.173
1904	1.516
1905	1.282
1906	1.31
1907	0.638
1908	0.209
1909	0.155
1910	0.534
1911	0.577
1912	0.592
1913	0.708
1914	1.046
1915	0.948
1916	0.609
1917	1.053
1918	0.891
1919	1.526
1920	1.188
1921	1.356
1922	0.958
1923	0.515
1924	0.984
1925	1.213
1926	1.585
1927	1.385
1928	1.23
1929	1.293
1930	0.831
1931	0.49
1932	0.468
1933	0.589
1934	0.906
1935	0.653
1936	1.109
1937	1.169
1938	1.237
1939	1.343
1940	1.368
1941	1.097
1942	0.971
1943	0.922
1944	0.647
1945	0.516
1946	0.865
1947	1.274
1948	1.019
1949	0.873
1950	0.849
1951	0.522
1952	0.477
1953	0.709
1954	0.668
1955	0.921
1956	1.003
1957	0.997
1958	1.241
1959	1.467
1960	1.175
1961	0.847
1962	0.702
1963	1.057
1964	1.174
1965	1.035
1966	1.22
1967	1.194
1968	1.074
1969	0.397
1970	0.392
1971	0.561
1972	0.849
1973	1.06
1974	0.947
1975	1.111
1976	1.236
1977	1.398
1978	1.313
1979	1.177
1980	0.826
1981	0.838
1982	0.769
1983	1.143
1984	1.315
1985	0.904
1986	0.85
1987	0.741
1988	1.013
1989	0.848
1990	1.052
1991	1.079
1992	1.476
1993	1.396
1994	0.953
1995	0.986
1996	1.038
1997	0.941
1998	0.8
1999	0.679
2000	0.776
2001	1.115
2002	1.253