# europe_fran9 - Mt. Ventoux (facing South) - 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/5112
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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: europe_fran9 - Mt. Ventoux (facing South) - 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
#--------------------
# 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: Mt. Ventoux (facing South)
#	Location:
#	Country: France
#	Northernmost_Latitude: 44.17
#	Southernmost_Latitude: 44.17
#	Easternmost_Longitude: 5.25
#	Westernmost_Longitude: 5.25
#	Elevation: 1600 m
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# Data_Collection
#	Collection_Name: europe_fran9B
#	Earliest_Year: 1844
#	Most_Recent_Year: 1981
#	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":"5.12680098436","T2":"15.1309836556","M1":"0.0230772780846","M2":"0.571146270959"}}
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# Species
#	Species_Name: Scots pine
#	Species_Code: PISY
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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
1844	1.141
1845	0.947
1846	1.119
1847	0.937
1848	0.963
1849	0.856
1850	0.979
1851	1.076
1852	1.219
1853	1.095
1854	1.041
1855	0.847
1856	0.801
1857	1.047
1858	0.821
1859	0.82
1860	0.723
1861	0.935
1862	0.956
1863	1.103
1864	1.138
1865	1.383
1866	1.278
1867	1.487
1868	1.233
1869	1.061
1870	0.786
1871	0.994
1872	1.25
1873	1.123
1874	1.09
1875	1.056
1876	1.267
1877	1.12
1878	1.496
1879	0.868
1880	0.907
1881	0.906
1882	0.977
1883	1.172
1884	1.193
1885	0.886
1886	0.867
1887	1.03
1888	0.975
1889	0.975
1890	0.852
1891	0.868
1892	1.038
1893	0.834
1894	0.814
1895	1.062
1896	1.205
1897	1.369
1898	0.895
1899	0.859
1900	1.127
1901	1.0
1902	0.926
1903	1.032
1904	1.158
1905	1.074
1906	0.681
1907	0.762
1908	1.03
1909	0.782
1910	1.019
1911	0.924
1912	0.931
1913	1.013
1914	1.34
1915	0.959
1916	1.099
1917	1.158
1918	0.692
1919	0.661
1920	0.874
1921	0.803
1922	0.613
1923	0.885
1924	0.819
1925	0.939
1926	0.733
1927	1.085
1928	0.855
1929	0.834
1930	1.133
1931	1.03
1932	1.062
1933	0.975
1934	1.071
1935	0.752
1936	0.674
1937	0.888
1938	1.026
1939	1.157
1940	1.152
1941	1.095
1942	0.755
1943	1.035
1944	1.388
1945	0.807
1946	0.723
1947	0.995
1948	1.214
1949	0.864
1950	0.681
1951	0.989
1952	0.846
1953	0.821
1954	0.85
1955	1.121
1956	1.055
1957	1.051
1958	1.142
1959	1.195
1960	0.904
1961	0.936
1962	0.509
1963	1.075
1964	1.088
1965	1.053
1966	1.109
1967	0.85
1968	1.027
1969	1.332
1970	1.025
1971	1.256
1972	1.115
1973	1.398
1974	0.857
1975	1.056
1976	1.144
1977	1.135
1978	0.844
1979	0.751
1980	1.027
1981	1.058