# europe_ital001 - Camosciara E M.Te Amaro - 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/2752
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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_ital001 - Camosciara E M.Te Amaro - 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: Camosciara E M.Te Amaro
#	Location:
#	Country: Italy
#	Northernmost_Latitude: 41.77
#	Southernmost_Latitude: 41.77
#	Easternmost_Longitude: 13.82
#	Westernmost_Longitude: 13.82
#	Elevation: 1550 m
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# Data_Collection
#	Collection_Name: europe_ital001B
#	Earliest_Year: 1786
#	Most_Recent_Year: 1987
#	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":"5.34567670143","T2":"15.1039884384","M1":"0.0220532842519","M2":"0.21633470753"}}
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# Species
#	Species_Name: Austrian pine
#	Species_Code: PINI
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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
1786	0.992
1787	0.75
1788	0.791
1789	0.882
1790	0.943
1791	1.05
1792	1.032
1793	1.148
1794	1.233
1795	1.159
1796	1.05
1797	1.168
1798	0.953
1799	0.961
1800	0.994
1801	0.826
1802	0.826
1803	0.882
1804	0.837
1805	0.643
1806	0.602
1807	0.641
1808	0.864
1809	0.918
1810	0.936
1811	0.805
1812	0.981
1813	1.058
1814	1.069
1815	0.979
1816	0.94
1817	0.885
1818	0.949
1819	0.903
1820	0.812
1821	0.798
1822	0.531
1823	0.465
1824	0.726
1825	0.849
1826	0.844
1827	0.943
1828	0.925
1829	0.805
1830	1.013
1831	1.522
1832	1.331
1833	0.993
1834	1.234
1835	1.078
1836	1.202
1837	1.176
1838	1.097
1839	0.958
1840	0.892
1841	1.199
1842	1.147
1843	1.433
1844	1.167
1845	1.24
1846	1.25
1847	1.22
1848	1.298
1849	1.133
1850	1.117
1851	0.992
1852	1.114
1853	1.19
1854	1.249
1855	1.171
1856	0.955
1857	1.32
1858	1.264
1859	1.44
1860	1.197
1861	0.877
1862	0.957
1863	1.187
1864	1.201
1865	1.244
1866	1.128
1867	0.931
1868	0.913
1869	1.149
1870	1.122
1871	1.286
1872	1.426
1873	1.38
1874	1.056
1875	1.088
1876	1.38
1877	1.21
1878	1.123
1879	0.766
1880	0.696
1881	0.947
1882	1.07
1883	0.982
1884	0.939
1885	0.996
1886	0.814
1887	0.882
1888	0.86
1889	0.824
1890	0.901
1891	0.755
1892	0.849
1893	1.097
1894	1.282
1895	1.202
1896	0.964
1897	1.288
1898	1.328
1899	1.031
1900	1.033
1901	1.005
1902	1.143
1903	1.106
1904	0.822
1905	0.896
1906	0.879
1907	0.817
1908	0.997
1909	1.143
1910	1.059
1911	0.925
1912	0.98
1913	0.924
1914	0.861
1915	0.672
1916	0.538
1917	0.785
1918	0.648
1919	0.638
1920	0.728
1921	0.608
1922	0.48
1923	0.771
1924	0.974
1925	0.883
1926	1.008
1927	0.974
1928	0.691
1929	0.72
1930	1.041
1931	0.822
1932	0.89
1933	0.983
1934	0.905
1935	0.966
1936	1.112
1937	0.853
1938	0.741
1939	0.914
1940	0.966
1941	0.968
1942	0.911
1943	0.922
1944	0.798
1945	0.876
1946	0.803
1947	0.788
1948	0.988
1949	1.161
1950	1.06
1951	0.851
1952	0.988
1953	1.104
1954	1.028
1955	0.812
1956	1.192
1957	0.637
1958	0.609
1959	1.002
1960	0.835
1961	0.989
1962	1.144
1963	1.053
1964	1.181
1965	1.142
1966	1.356
1967	1.189
1968	1.397
1969	1.447
1970	1.508
1971	1.314
1972	0.922
1973	0.873
1974	0.799
1975	0.757
1976	0.599
1977	0.774
1978	0.81
1979	0.907
1980	0.874
1981	1.008
1982	0.716
1983	0.845
1984	0.825
1985	1.049
1986	0.858
1987	1.011