# europe_fran008 - Marseille - 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/4753
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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_fran008 - Marseille - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
#--------------------
# 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:
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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: Marseille
#	Location:
#	Country: France
#	Northernmost_Latitude: 43.35
#	Southernmost_Latitude: 43.35
#	Easternmost_Longitude: 5.0
#	Westernmost_Longitude: 5.0
#	Elevation: 200 m
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# Data_Collection
#	Collection_Name: europe_fran008B
#	Earliest_Year: 1835
#	Most_Recent_Year: 1973
#	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":"4.38621347044","T2":"14.6696978162","M1":"0.0229650814721","M2":"0.573797198042"}}
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# Species
#	Species_Name: Aleppo pine
#	Species_Code: PIHA
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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
1835	1.912
1836	1.472
1837	1.073
1838	1.231
1839	0.9
1840	1.322
1841	1.106
1842	1.134
1843	1.315
1844	1.102
1845	1.204
1846	1.038
1847	0.953
1848	1.127
1849	0.883
1850	0.842
1851	0.844
1852	0.711
1853	1.023
1854	0.92
1855	1.064
1856	1.298
1857	0.708
1858	0.718
1859	0.726
1860	0.987
1861	0.926
1862	0.601
1863	1.137
1864	0.557
1865	0.929
1866	1.256
1867	0.64
1868	0.334
1869	0.598
1870	0.711
1871	0.948
1872	1.739
1873	1.442
1874	1.63
1875	0.677
1876	1.021
1877	0.483
1878	0.284
1879	1.531
1880	1.255
1881	0.873
1882	0.562
1883	1.203
1884	0.852
1885	1.039
1886	1.227
1887	1.386
1888	1.397
1889	1.592
1890	1.369
1891	0.873
1892	1.005
1893	1.053
1894	0.706
1895	0.631
1896	0.166
1897	0.867
1898	1.405
1899	1.401
1900	0.815
1901	1.002
1902	1.076
1903	0.424
1904	0.755
1905	0.731
1906	0.846
1907	1.145
1908	1.237
1909	0.713
1910	1.17
1911	1.207
1912	0.848
1913	1.317
1914	1.115
1915	1.34
1916	1.018
1917	0.972
1918	0.815
1919	0.773
1920	1.003
1921	0.76
1922	0.433
1923	0.743
1924	1.045
1925	1.034
1926	0.963
1927	0.768
1928	0.905
1929	-0.016
1930	0.416
1931	0.104
1932	1.05
1933	1.052
1934	1.451
1935	1.577
1936	1.924
1937	1.214
1938	1.612
1939	1.486
1940	1.162
1941	1.502
1942	1.347
1943	1.26
1944	1.477
1945	0.362
1946	0.937
1947	0.766
1948	1.51
1949	0.911
1950	0.71
1951	1.269
1952	1.258
1953	0.532
1954	0.967
1955	0.781
1956	-0.011
1957	0.135
1958	0.284
1959	0.401
1960	0.697
1961	1.101
1962	0.834
1963	1.154
1964	1.192
1965	0.408
1966	0.704
1967	0.558
1968	0.998
1969	1.58
1970	0.623
1971	0.799
1972	1.315
1973	1.473