# europe_fran028 - Le Tournairet - 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/4504
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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
#--------------------
# Title
#	Study_Name: europe_fran028 - Le Tournairet - Breitenmoser Tree Ring Chronology Data
#--------------------
# 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:
#--------------------
#	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: Le Tournairet
#	Location:
#	Country: France
#	Northernmost_Latitude: 43.87
#	Southernmost_Latitude: 43.87
#	Easternmost_Longitude: 7.33
#	Westernmost_Longitude: 7.33
#	Elevation: 2050 m
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# Data_Collection
#	Collection_Name: europe_fran028B
#	Earliest_Year: 1759
#	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":"6.4033585679","T2":"19.7200730063","M1":"0.0221687408738","M2":"0.297288936539"}}
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# Species
#	Species_Name: Norway spruce
#	Species_Code: PCAB
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# Chronology:
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# Variables
#
# 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
1759	1.058
1760	1.045
1761	1.032
1762	0.98
1763	0.916
1764	0.964
1765	0.916
1766	0.947
1767	0.627
1768	0.813
1769	0.936
1770	0.753
1771	0.829
1772	1.002
1773	0.925
1774	0.969
1775	0.902
1776	0.993
1777	0.777
1778	0.943
1779	0.806
1780	0.967
1781	1.198
1782	1.302
1783	1.186
1784	1.385
1785	1.339
1786	1.214
1787	1.218
1788	1.251
1789	1.185
1790	1.196
1791	1.352
1792	1.164
1793	1.072
1794	0.854
1795	0.868
1796	0.743
1797	0.871
1798	0.787
1799	0.758
1800	1.024
1801	0.904
1802	1.055
1803	0.946
1804	0.971
1805	0.908
1806	1.023
1807	1.157
1808	0.806
1809	0.967
1810	0.949
1811	0.935
1812	0.853
1813	0.702
1814	1.149
1815	1.034
1816	0.992
1817	0.901
1818	0.768
1819	0.818
1820	0.917
1821	0.918
1822	1.005
1823	1.002
1824	0.97
1825	0.891
1826	0.967
1827	0.885
1828	0.951
1829	0.944
1830	0.791
1831	1.1
1832	1.12
1833	0.953
1834	1.098
1835	0.841
1836	1.096
1837	1.095
1838	1.023
1839	0.824
1840	0.792
1841	0.922
1842	1.158
1843	1.07
1844	1.161
1845	1.205
1846	1.34
1847	1.105
1848	1.172
1849	1.157
1850	1.075
1851	1.305
1852	1.216
1853	1.376
1854	1.366
1855	1.526
1856	1.546
1857	1.233
1858	1.083
1859	1.123
1860	0.72
1861	0.788
1862	0.509
1863	0.649
1864	0.713
1865	0.825
1866	0.862
1867	1.033
1868	0.683
1869	0.818
1870	0.984
1871	1.042
1872	1.069
1873	1.099
1874	1.016
1875	0.888
1876	0.933
1877	1.035
1878	0.971
1879	0.779
1880	0.659
1881	0.863
1882	0.811
1883	0.772
1884	0.846
1885	1.167
1886	1.118
1887	1.443
1888	1.354
1889	1.601
1890	1.643
1891	1.231
1892	1.336
1893	1.162
1894	1.014
1895	0.988
1896	0.809
1897	0.816
1898	0.795
1899	0.659
1900	0.87
1901	1.099
1902	0.986
1903	1.099
1904	1.242
1905	1.005
1906	1.132
1907	0.924
1908	1.132
1909	0.934
1910	0.902
1911	0.835
1912	0.59
1913	0.763
1914	0.676
1915	0.822
1916	0.956
1917	1.036
1918	1.046
1919	0.849
1920	0.778
1921	0.861
1922	0.666
1923	0.871
1924	0.722
1925	0.68
1926	0.671
1927	0.646
1928	0.852
1929	0.674
1930	0.815
1931	0.865
1932	0.669
1933	0.704
1934	0.916
1935	1.083
1936	1.022
1937	1.135
1938	1.184
1939	1.214
1940	1.333
1941	1.539
1942	1.384
1943	1.148
1944	1.091
1945	1.168
1946	1.092
1947	0.976
1948	0.629
1949	1.093
1950	0.665
1951	0.689
1952	0.691
1953	0.579
1954	0.632
1955	0.644
1956	0.915
1957	0.725
1958	0.877
1959	0.874
1960	1.119
1961	0.915
1962	1.101
1963	1.026
1964	1.436
1965	1.273
1966	1.319
1967	1.197
1968	1.085
1969	1.274
1970	1.043
1971	1.092
1972	0.934
1973	1.109
1974	0.904
1975	0.781
1976	0.831
1977	0.684