# europe_fran025 - Miraules Refuge - 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/4530
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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_fran025 - Miraules Refuge - 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: Miraules Refuge
#	Location:
#	Country: France
#	Northernmost_Latitude: 42.47
#	Southernmost_Latitude: 42.47
#	Easternmost_Longitude: 2.4
#	Westernmost_Longitude: 2.4
#	Elevation: 1720 m
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# Data_Collection
#	Collection_Name: europe_fran025B
#	Earliest_Year: 1846
#	Most_Recent_Year: 1977
#	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":"3.7752818074","T2":"13.2250406164","M1":"0.0230450744319","M2":"0.578754908447"}}
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# Species
#	Species_Name: silver fir
#	Species_Code: ABAL
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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
1846	1.279
1847	1.027
1848	1.157
1849	1.212
1850	0.883
1851	1.026
1852	0.825
1853	0.823
1854	0.563
1855	0.659
1856	0.746
1857	0.662
1858	0.581
1859	0.773
1860	0.626
1861	0.914
1862	0.695
1863	0.744
1864	1.013
1865	0.828
1866	0.982
1867	1.056
1868	0.876
1869	1.049
1870	0.989
1871	1.025
1872	1.1
1873	1.121
1874	1.155
1875	1.108
1876	1.268
1877	1.145
1878	1.382
1879	1.072
1880	1.271
1881	1.34
1882	1.07
1883	1.079
1884	1.209
1885	1.243
1886	1.227
1887	1.173
1888	1.138
1889	1.182
1890	1.069
1891	1.037
1892	0.929
1893	1.266
1894	1.123
1895	1.038
1896	0.901
1897	1.116
1898	1.051
1899	1.063
1900	0.976
1901	0.896
1902	1.134
1903	1.214
1904	1.093
1905	1.021
1906	0.995
1907	0.86
1908	0.956
1909	1.044
1910	1.128
1911	1.207
1912	1.003
1913	1.131
1914	1.141
1915	0.994
1916	1.072
1917	0.991
1918	1.161
1919	1.215
1920	1.149
1921	1.056
1922	0.835
1923	0.856
1924	0.498
1925	0.698
1926	0.88
1927	0.695
1928	0.662
1929	0.506
1930	0.9
1931	0.633
1932	0.863
1933	0.932
1934	0.697
1935	0.85
1936	1.181
1937	1.093
1938	0.981
1939	1.057
1940	1.153
1941	1.05
1942	0.791
1943	0.969
1944	1.016
1945	0.788
1946	0.764
1947	0.842
1948	0.856
1949	0.851
1950	0.736
1951	0.868
1952	1.21
1953	0.898
1954	0.83
1955	0.972
1956	0.771
1957	0.825
1958	0.722
1959	0.954
1960	0.93
1961	0.994
1962	0.859
1963	0.737
1964	1.025
1965	0.759
1966	1.075
1967	1.11
1968	0.93
1969	1.117
1970	1.192
1971	0.97
1972	1.006
1973	1.315
1974	1.175
1975	1.249
1976	1.362
1977	1.351