# europe_fran8 - Mt. Ventoux (facing North) - 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/5111
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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_fran8 - Mt. Ventoux (facing North) - 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 North)
#	Location:
#	Country: France
#	Northernmost_Latitude: 44.17
#	Southernmost_Latitude: 44.17
#	Easternmost_Longitude: 5.25
#	Westernmost_Longitude: 5.25
#	Elevation: 1400 m
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# Data_Collection
#	Collection_Name: europe_fran8B
#	Earliest_Year: 1839
#	Most_Recent_Year: 1979
#	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":"4.78849273969","T2":"15.2745736029","M1":"0.0221244937469","M2":"0.578769360295"}}
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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
1839	0.596
1840	0.902
1841	1.147
1842	1.196
1843	1.284
1844	1.137
1845	1.182
1846	1.497
1847	1.034
1848	0.887
1849	0.649
1850	1.183
1851	1.153
1852	1.29
1853	1.263
1854	1.232
1855	0.756
1856	0.842
1857	1.088
1858	0.89
1859	0.877
1860	0.976
1861	1.247
1862	1.138
1863	1.151
1864	1.058
1865	1.145
1866	1.206
1867	1.36
1868	1.022
1869	0.853
1870	0.608
1871	0.834
1872	1.124
1873	1.06
1874	1.151
1875	1.15
1876	0.938
1877	0.891
1878	1.378
1879	0.708
1880	0.863
1881	0.797
1882	0.929
1883	1.017
1884	1.122
1885	0.859
1886	0.94
1887	1.043
1888	1.074
1889	1.064
1890	0.923
1891	0.856
1892	1.088
1893	1.019
1894	1.15
1895	0.895
1896	0.971
1897	0.9
1898	0.713
1899	0.791
1900	0.749
1901	0.856
1902	0.785
1903	1.213
1904	1.272
1905	1.047
1906	0.632
1907	0.929
1908	1.197
1909	0.869
1910	0.978
1911	0.912
1912	1.023
1913	1.174
1914	1.512
1915	1.238
1916	1.257
1917	1.043
1918	0.666
1919	0.512
1920	0.865
1921	0.467
1922	0.623
1923	0.667
1924	0.671
1925	1.068
1926	0.984
1927	1.221
1928	0.786
1929	0.883
1930	1.451
1931	1.094
1932	1.15
1933	1.009
1934	0.902
1935	0.563
1936	0.763
1937	0.762
1938	0.896
1939	1.259
1940	1.246
1941	1.309
1942	0.814
1943	1.028
1944	1.578
1945	1.064
1946	1.013
1947	1.174
1948	1.056
1949	0.862
1950	0.599
1951	1.123
1952	0.824
1953	0.952
1954	0.977
1955	1.47
1956	0.948
1957	0.846
1958	1.17
1959	1.268
1960	0.893
1961	1.142
1962	0.507
1963	1.038
1964	1.286
1965	1.013
1966	1.06
1967	0.951
1968	0.998
1969	1.184
1970	0.879
1971	1.101
1972	0.97
1973	1.206
1974	0.609
1975	0.756
1976	0.693
1977	0.896
1978	0.843
1979	0.629