# europe_fran7 - Mt. Ventoux - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# 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.
#
#
# 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/4754
#
# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: europe_fran7 - Mt. Ventoux - 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.
#--------------------
#	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
#	Location:
#	Country: France
#	Northernmost_Latitude: 44.17
#	Southernmost_Latitude: 44.17
#	Easternmost_Longitude: 5.25
#	Westernmost_Longitude: 5.25
#	Elevation: 1775 m
#--------------------
# Data_Collection
#	Collection_Name: europe_fran7B
#	Earliest_Year: 1720
#	Most_Recent_Year: 1975
#	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":"4.76964574057","T2":"14.7496946677","M1":"0.022741682712","M2":"0.611940676491"}}
#--------------------
# Species
#	Species_Name: silver fir
#	Species_Code: ABAL
#--------------------
# 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)
#
##age	age, , ,years AD, , , , ,N
##trsgi	tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1720	0.721
1721	1.288
1722	0.933
1723	1.036
1724	0.994
1725	0.992
1726	1.306
1727	0.955
1728	1.148
1729	0.729
1730	0.952
1731	0.625
1732	1.701
1733	1.575
1734	1.419
1735	1.313
1736	1.564
1737	1.247
1738	1.376
1739	0.872
1740	1.271
1741	1.196
1742	0.917
1743	1.128
1744	1.104
1745	0.966
1746	0.952
1747	1.21
1748	0.963
1749	1.085
1750	1.11
1751	0.719
1752	0.797
1753	0.866
1754	0.737
1755	0.839
1756	0.98
1757	1.114
1758	1.104
1759	1.273
1760	1.036
1761	1.088
1762	1.059
1763	1.178
1764	0.784
1765	0.866
1766	0.928
1767	0.672
1768	0.696
1769	0.412
1770	0.788
1771	0.666
1772	0.606
1773	0.704
1774	0.709
1775	0.759
1776	0.862
1777	0.876
1778	0.922
1779	0.871
1780	0.373
1781	0.603
1782	0.656
1783	0.656
1784	0.571
1785	0.582
1786	0.686
1787	0.821
1788	0.754
1789	0.929
1790	0.805
1791	0.841
1792	0.672
1793	0.64
1794	0.865
1795	0.827
1796	0.641
1797	0.643
1798	0.811
1799	0.906
1800	1.146
1801	1.063
1802	1.125
1803	0.483
1804	0.485
1805	0.84
1806	0.817
1807	1.012
1808	0.735
1809	1.348
1810	1.391
1811	1.376
1812	1.089
1813	1.048
1814	1.374
1815	1.19
1816	1.112
1817	1.399
1818	1.022
1819	1.077
1820	0.785
1821	0.913
1822	0.639
1823	0.565
1824	0.586
1825	0.823
1826	0.973
1827	1.059
1828	0.973
1829	1.277
1830	1.371
1831	0.929
1832	0.901
1833	0.64
1834	0.903
1835	0.922
1836	0.837
1837	0.605
1838	0.809
1839	0.729
1840	0.61
1841	0.658
1842	0.91
1843	0.937
1844	0.937
1845	0.975
1846	1.352
1847	0.769
1848	1.074
1849	0.883
1850	0.997
1851	1.051
1852	1.191
1853	1.011
1854	1.411
1855	1.017
1856	0.99
1857	1.003
1858	1.093
1859	1.253
1860	0.977
1861	1.325
1862	0.809
1863	0.884
1864	1.029
1865	0.99
1866	0.987
1867	1.296
1868	0.767
1869	0.89
1870	0.728
1871	1.071
1872	1.022
1873	0.974
1874	0.993
1875	1.334
1876	1.255
1877	0.965
1878	1.098
1879	1.012
1880	1.261
1881	0.975
1882	0.915
1883	1.323
1884	1.668
1885	1.3
1886	1.177
1887	1.048
1888	0.939
1889	1.37
1890	1.05
1891	0.972
1892	1.025
1893	1.062
1894	0.836
1895	1.068
1896	1.027
1897	1.076
1898	0.919
1899	0.937
1900	0.821
1901	1.151
1902	1.324
1903	1.353
1904	1.241
1905	1.039
1906	0.934
1907	0.827
1908	1.114
1909	1.147
1910	1.315
1911	1.177
1912	0.943
1913	0.976
1914	1.51
1915	1.482
1916	1.18
1917	1.303
1918	0.832
1919	0.742
1920	0.675
1921	0.896
1922	0.61
1923	0.544
1924	0.44
1925	0.675
1926	0.656
1927	0.806
1928	0.677
1929	0.617
1930	0.577
1931	0.487
1932	1.233
1933	1.114
1934	1.05
1935	0.832
1936	1.105
1937	0.999
1938	0.904
1939	1.209
1940	1.479
1941	1.388
1942	0.838
1943	0.588
1944	1.119
1945	1.031
1946	0.903
1947	0.854
1948	0.877
1949	0.858
1950	0.632
1951	0.522
1952	0.695
1953	1.03
1954	0.845
1955	1.303
1956	0.764
1957	0.972
1958	1.047
1959	1.162
1960	1.203
1961	1.239
1962	0.656
1963	0.915
1964	1.174
1965	0.897
1966	1.119
1967	0.889
1968	0.859
1969	1.046
1970	0.808
1971	0.811
1972	0.74
1973	0.969
1974	0.564
1975	0.7