# asia_syri002 - Bedayat Al Khandak Al Tawil + Rawisat Almedeki - 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/5550
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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_syri002 - Bedayat Al Khandak Al Tawil + Rawisat Almedeki - 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:
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#	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: Bedayat Al Khandak Al Tawil + Rawisat Almedeki
#	Location:
#	Country: Syrian Arab Republic
#	Northernmost_Latitude: 35.57
#	Southernmost_Latitude: 35.57
#	Easternmost_Longitude: 36.2
#	Westernmost_Longitude: 36.2
#	Elevation: 1450 m
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# Data_Collection
#	Collection_Name: asia_syri002B
#	Earliest_Year: 1869
#	Most_Recent_Year: 2001
#	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":"5.25641763564","T2":"17.3524928837","M1":"0.0231155219215","M2":"0.439450404894"}}
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# Species
#	Species_Name: Cilician fir
#	Species_Code: ABCI
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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
1869	1.2
1870	1.276
1871	1.705
1872	1.39
1873	1.027
1874	1.297
1875	1.335
1876	1.435
1877	0.917
1878	0.917
1879	0.674
1880	1.044
1881	0.996
1882	1.313
1883	1.334
1884	1.328
1885	1.513
1886	1.2
1887	0.783
1888	1.168
1889	1.182
1890	0.747
1891	0.617
1892	0.539
1893	0.521
1894	0.659
1895	0.601
1896	0.817
1897	1.001
1898	0.703
1899	0.888
1900	1.219
1901	1.186
1902	0.891
1903	0.902
1904	1.107
1905	0.883
1906	0.709
1907	0.825
1908	0.931
1909	0.659
1910	0.98
1911	1.028
1912	0.93
1913	0.942
1914	1.302
1915	1.024
1916	0.612
1917	0.733
1918	0.742
1919	1.039
1920	0.757
1921	0.825
1922	0.974
1923	0.906
1924	1.164
1925	1.096
1926	1.36
1927	0.915
1928	0.792
1929	0.983
1930	1.075
1931	1.139
1932	0.847
1933	1.123
1934	1.203
1935	0.651
1936	1.445
1937	0.904
1938	1.066
1939	0.954
1940	1.31
1941	0.811
1942	0.96
1943	0.725
1944	0.594
1945	0.497
1946	0.547
1947	0.794
1948	0.969
1949	0.489
1950	0.797
1951	0.718
1952	0.924
1953	1.102
1954	1.048
1955	0.831
1956	0.843
1957	0.835
1958	0.709
1959	1.436
1960	1.168
1961	1.032
1962	0.82
1963	0.943
1964	0.736
1965	0.958
1966	0.9
1967	1.158
1968	0.878
1969	0.464
1970	0.935
1971	0.966
1972	1.299
1973	1.3
1974	1.187
1975	1.56
1976	1.518
1977	1.1
1978	1.267
1979	1.064
1980	0.702
1981	1.309
1982	0.893
1983	1.757
1984	0.687
1985	0.44
1986	0.509
1987	0.729
1988	0.844
1989	0.702
1990	1.155
1991	1.117
1992	0.936
1993	0.746
1994	0.887
1995	0.79
1996	0.591
1997	0.56
1998	0.824
1999	0.613
2000	0.721
2001	0.829